Item 1 - 8 - of civil war and brutal child abduction for military and sexual purposes led by the Lord ... collective identification of the formerly abducted children and ...
PTSD and Collective Identity in Former Ugandan Child Soldiers
Wissenschaftliche Arbeit zur Erlangung des Grades einer Diplom-Psychologin im Fachbereich Psychologie der Universität Konstanz
vorgelegt von
Franka Glöckner Fasanenweg 9 78464 Konstanz
Erstgutachter: Professor Dr. Frank Neuner Zweitgutachter: Professor Dr. Thomas Elbert
Konstanz, im April 2007 Konstanzer Online-Publikations-System (KOPS) URL: http://www.ub.uni-konstanz.de/kops/volltexte/2007/3308/ URN: http://nbn-resolving.de/urn:nbn:de:bsz:352-opus-33085
ii
An dieser Stelle möchte ich allen Personen danken, die mir diese Arbeit ermöglicht und mich dabei unterstützt haben!
Einen besonderen Dank an: Prof. Dr. Frank Neuner und Prof. Dr. Thomas Elbert für ihr Vertrauen und diese ganz besondere Möglichkeit mit Kindern und Jugendlichen in Afrika arbeiten zu dürfen.
Verena Ertl, die Leiterin des Norduganda-Projekts, ohne deren Hilfe mir die Umsetzung meiner Diplomarbeit nie möglich gewesen wäre; die sich stets für mich Zeit nahm und meinen Blick in zahlreichen Diskussionen auf neue Perspektiven lenkte.
Elisabeth Schauer, Dr. Julia Müller, Dr. Lamaro Patience Onyut und Jürgen Biedermann, den Teammitgliedern des Norduganda-Projekts, die mir stets mit fachlichem und emotionalem Rat zur Seite standen.
Marcel Thurm, meinem Freund und Ruhepol, für die Aufmunterung und Unterstützung in schwierigen und hektischen Phasen.
Meine Familie, besonders an meine Mutter und meine Großmutter, die stets an mich geglaubt und mich während meines gesamten Studiums unterstützt haben.
Konstanz, im April 2007
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Contents Dedication ................................................................................................................................. ii Contents .................................................................................................................................... iii Tables ....................................................................................................................................... vi Figures ..................................................................................................................................... vii Abstract .................................................................................................................................. viii
1. Introduction ....................................................................................................................... 1 1.1
Child Soldiers in Northern Uganda ............................................................................ 1 1.1.1 The conflict in Northern Uganda – The atrocious war .................................. 3
1.2
Post-Traumatic Stress Disorder (PTSD) .................................................................... 6 1.2.1 PTSD Diagnosis (DSM-IV-TR) ..................................................................... 8 1.2.2 Epidemiology of PTSD and comorbid disorders in the general population .......................................................................................... 9 1.2.3 Epidemiology of PSTD in African populations affected by civil war and forced migration .................................................. 12 1.2.4
Epidemiology of PSTD in soldiers ............................................................... 13
1.2.5 Epidemiology of PSTD and comorbid disorders in children exposed to warfare and child soldiers .......................................................... 15 1.3. Classic Identity Concepts ......................................................................................... 22 1.3.1. Identity Theory (McCall & Simmons; Stryker) ............................................ 22 1.3.2. Social Identity Theory (Tajfel and Turner) .................................................. 23 1.3.3. Self-Categorization Theory (Turner) ........................................................... 26 1.3.4. Activation or salience of personal and social identity (Stets & Burke) ........ 28 1.3.5. Motivations of identification (Deaux) .......................................................... 31 1.3.6. Strength of identification (Deaux) ................................................................ 34 1.3.7. Critical Considerations ................................................................................. 35 1.4. A Multidimensional Framework of Collective Identity (Ashmore, Deaux, and McLaughlin-Volpe) ............................................................. 37 1.4.1. The collective identity concept .................................................................... 37 1.4.2. Multidimensionality of collective identity ................................................... 38 1.4.3. Variability (stability) and context-dependency of collective identity .......... 40
iv 1.4.4. Outcomes of collective identification ........................................................... 43 1.5. Stage Models of Collective Identity Development (Cross)....................................... 44 1.6. Collective identification and PTSD in child soldiers ............................................... 45 1.7. Hypotheses ............................................................................................................... 48 1.7.1. PTSD and the building block effect in former Ugandan child soldiers ....... 49 1.7.2. Factorial design and reliability of the Collective Identity Questionnaire .... 49 1.7.3. Abduction duration and strength of collective identification in former Ugandan child soldiers ................................................................. 50 1.7.4. Number of traumatic events and collective identification in former Ugandan child soldiers ................................................................. 50 1.7.5. Collective identity as protective factor for PTSD and comorbid disorders in former Ugandan child soldiers ................................................. 51 1.7.6. Collective identity and aggression in former Ugandan child soldiers .......... 51 2. Method .............................................................................................................................. 52 2.1
Setting ....................................................................................................................... 52
2.2
Procedure .................................................................................................................. 53
2.3
Participants ................................................................................................................ 55
2.4
Instruments ............................................................................................................... 61 2.4.1 Demographic interview ................................................................................ 61 2.4.2
Events list .................................................................................................... 62
2.4.3 Clinician-Administered PTSD Scale (CAPS) .............................................. 62 2.4.4
Mini-International Neuropsychiatric Interview (M.I.N.I.) ........................... 64
2.4.5 Aggression Scale .......................................................................................... 66 2.4.6 Collective Identity Questionnaire and PRISM ............................................. 66 2.5
Data analysis ............................................................................................................ 68
3. Results .............................................................................................................................. 69 3.1
Results concerning the six main hypotheses ............................................................ 69 3.1.1 PTSD (CAPS) and the building block effect ............................................... 70 3.1.2
Factorial design and reliability of the Collective Identity Questionnaire (items 1-13) ........................................................................... 78
3.1.3 Abduction duration and strength of collective identification ....................... 82 3.1.4 Number of traumatic events and collective identification............................. 83 3.1.5. Collective identity as protective factor for PTSD and comorbid disorders ................................................................................ 84
v 3.1.6. Collective identification and aggression ...................................................... 86 3.2
Further analyses ........................................................................................................ 87 3.2.1 The adapted PRISM version ......................................................................... 87 3.2.2 Collective Identity Questionnaire item 14..................................................... 89 3.2.3 Number of events, current depression and suicidality ................................. 90 3.2.4 Aggression, psychological outcomes and event load ................................... 91
4. Discussion ......................................................................................................................... 93 4.1
Hypotheses ............................................................................................................... 93 4.1.1 PTSD (CAPS) and the building block effect ............................................... 93 4.1.2
Factorial design and reliability of the Collective Identity Questionnaire (items 1-13) ........................................................................... 98
4.1.3 Abduction duration and strength of collective identification ....................... 99 4.1.4 Number of traumatic events and collective identification .......................... 101 4.1.5 Collective identity as protective factor for PTSD and comorbid disorders .............................................................................. 102 4.1.6 Collective identification and aggression .................................................... 104 4.2 Further analyses ...................................................................................................... 105 4.2.1 The adapted PRISM version ...................................................................... 105 4.2.2 Collective Identity Questionnaire item 14................................................... 107 4.2.3 Number of events, current depression and suicidality ............................... 107 4.2.4 Aggression, psychological outcomes and event load ................................. 108 4.3
Critical discussion of the method ........................................................................... 109
4.4 Discussion of the LRA-related collective identity concept and its associations with event load, PTSD symptomatology and aggression .................. 110 4.5 Excurse perpetrator research after World War II ................................................... 116 4.6 General strengths and weaknesses of the study ..................................................... 119 4.7
Summary and implications of the study ................................................................. 121
5. Literature ....................................................................................................................... 124 6. Appendix ........................................................................................................................ 137
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Tables
Table 1:
Demographic characteristics of participants in the GUSCO reception centre (RC) and Internally Displaced People (IDP) camps.............. 58
Table 2:
Aspects of displacement and abduction due to the LRA rebellion in participants in the GUSCO reception centre (RC) and Internally Displaced People (IDP) camps ........................................................ 59
Table 3:
Frequency of each events (experienced and witnessed) of the event list......... 60
Table 4:
CAPS diagnosis and CAPS sum scores for criteria B (intrusions), C (avoidance), D (hyperarousal) and/or associated (PTSD-related) features in dependence on interview location (GUSCO reception centre (RC) vs. Internally Displaced People (IDP) camps) ............................. 72
Table 5:
CAPS diagnosis and CAPS sum scores for criteria B (intrusions), C (avoidance), D (hyperarousal) and/or associated (PTSD-related) features in dependence gender ......................................................................... 73
Table 6:
Pearson correlations of the CAPS score and the total number of events and the event types ........................................................................................... 75
Table 7:
Items 1-13 of the Collective Identity Questionnaire ........................................ 78
Table 8:
Item statistic 1-13 of the Collective Identity Questionnaire using a 5-point-Likert-Scale (0-4) for N=61 ................................................................ 79
Table 9:
Inter-item correlations of items 1-13 of the Collective Identity Questionnaire for N=61.................................................................................... 81
Table 10:
Descriptive distributions of abduction durations for N=61.............................. 82
Table 11:
Pearson correlations of abduction duration and mean score of the Collective Identity Questionnaire items 1-8 and 11-13.................................... 82
Table 12:
Pearson correlations of the mean score of the Collective Identity Questionnaire items 1-8 and 11-13 with psychological outcomes.................. 85
Table 13:
Distribution of the adapted PRISM components of the Collective Identity Questionnaire item (distance measures in 0-27 cm) ........................... 87
Table 14:
Pearson inter-correlations of the adapted PRISM components of the Collective Identity Questionnaire item 15........................................................ 88
Table 15:
Pearson correlations of the adapted PRISM components of the Collective Identity Questionnaire item 15 and clinical outcomes, collective
vii identification (items 1-8 and 11-13), aggression and event load ..................... 89 Table 16:
Distribution of the free item 14 of the Collective Identity Questionnaire by gender, interview location (reception centre RC vs. IDP camps) and PTSD diagnosis for N=61.......................................... 90
Table 17:
Pearson correlations of the total aggression score and psychological outcomes........................................................................................................... 91
Table 18:
Pearson correlations of the total aggression score and the total number of events, event types and total abduction duration ............................ 92
Figures
Figure 1:
CAPS scores of criteria B (intrusions), C (avoidance) and D (hyperarousal) in dependence on interview location (RC – GUSCO Reception Centre; IDP – Internally Displaced People Camps) ....................... 71
Figure 2:
Linear regression of the total number of events on the CAPS score (of PTSD criteria B, C, D) ............................................................................... 75
Figure 3:
Linear regression of the total number of events on the CAPS score (of PTSD criteria B, C, D) depending on interview location (RC vs. IDP camps) ......................................................................................... 77
Figure 4:
Answer patterns for items 1-13 of the Collective Identity Questionnaire (N=61) .................................................................................... 79
Figure 5:
The role of LRA-perpetrator events for collective identification, PTSD symptom score and aggression level .................................................. 115
viii
Abstract Worldwide hundred thousands of children and adolescents are recruited and misused as fighters. However, only little research exists that has investigated psychological well-being and trauma-related symptomatology of this particular population. This study aimed to explore this issue in the war-torn North of Uganda – an area that is characterized by almost 20 years of civil war and brutal child abduction for military and sexual purposes led by the Lord Resistance Army (LRA). This work further represents a pilot study for a subsequent therapy study with former Ugandan child soldiers. The team consisted of members of the NGO vivo international (www.vivo.org) and the University of Konstanz, Department of Clinical Psychology, off-site Psychotrauma Research- and Outpatient Clinic for Refugees and the Outpatient Clinic for Victims of Torture and War of the University of Zurich. It was possible to examine 61 former child soldiers in and around Gulu town. The sample comprises two subsamples: 40 of the children and adolescents had just escaped from abduction or had just been freed and were living in the reception centre of the local organization GUSCO (Gulu Support the Children Organization), which is responsible for reintegration of former Ugandan child soldiers. Another 21 children and adolescents, who could be interviewed, had already left GUSCO and had gone back to their communities. With the help of GUSCO social workers it was possible to visit them there. All participants could be interviewed by experts regarding potentially traumatic experiences (as victims and as perpetrators), post-traumatic stress disorder (PTSD), comorbid disorders (depression and suicidality) and aggressive behaviours. Furthermore, a new questionnaire has been developed in order to assess possible collective identification of the formerly abducted children and adolescents with the LRA’s ideology. Relationships between strength of identification, psychological outcomes (PTSD, depression, suicidality) and aggression level have been analysed. The received knowledge will be passed back to local organizations and social workers in order to teach them about possible psychological problems of former child soldiers and to support their important work (in terms of helping the helpers). However, this work not only follows psychological research interests, it also documents the enormous violations of human and child rights in Northern Uganda. The first section (or introduction) of this work describes the situation of child soldiers and aspects of child recruitment followed by a brief history of the civil war of Northern Uganda. Post-traumatic stress disorder (PTSD) was expected to be one of the main psychological problems associated with abduction and child soldiering. Accordingly, PTSD phenomenology
ix and relevant epidemiological knowledge about PTSD in general Western, African, soldier and child soldier populations are considered. Furthermore, it has been attempted to generate a sufficient theoretical framework for role-related, personal, social and collective identification with main focus on the latter. This part ought to be the basis for the development of the collective identification concept of former Ugandan child soldiers. Finally, the hypotheses are deduced according to the information gained in the preceding paragraphs. The second chapter describes the methodology of the study. This paragraph also includes the development of the Collective Identity Questionnaire. Subsequently, chapter three displays all results concerning event load, PTSD, depression, suicidality, aggression and collective identification with the rebellious group LRA an the inter-relations of these variables. Finally, the results and the entire study, its strengths and weaknesses, are discussed within the last chapter according to theoretical and empirical knowledge that has been described in the introduction. Additionally, it is referred to perspectives of perpetrator research following World War II. Reported literature is specified in the reference list. New materials and instruments that have been developed for this study can be found in the Appendix at the end of this work.
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“A child soldier has been defined as any person under 18 years of age who forms part of an armed force in any captivity, and those accompanying such groups, other than purely as family members, as well as girls recruited for sexual purposes and forced marriage.” (United Nations, Security Council, Report of the Secretary-General, S/2000/101, 11 February 2000, p. 2).
Introduction
1.
Introduction
1.1
Child Soldiers in Northern Uganda
1
“Child soldier refers to any person under eighteen years of age who is part of any, regular or irregular, armed force or group. This includes all child or adolescent participants regardless of function [cook or combatant] … and those forcibly recruited as well as those who join voluntarily.” (Beth, 2001, p. 27). Today many child soldiers have been forced to join an armed group. Reasons for voluntarily participation may be false promises or relatives taking part in the group. Risk factors for becoming a child soldier are poverty, less or no access to education, living in a war-torn region, and displacement, separation from one’s family, with orphans and refugees being particularly vulnerable (Beth, 2001, p. 27). Child soldiers are an issue that concerns the whole world, but is far too often forgotten! According to terre des hommes (Daten und Fakten zum Thema Kindersoldaten [Data and facts concerning child soldiers]; www.terre-des-hommes.org), approximately 300.000 children below the age of 18 (among those, many below the age of 15) are used as child soldiers worldwide. Many states still miss recruitment laws with specified and compulsory age limits. Children are recruited as fighters in Africa (e.g., Uganda, Sudan, Congo, Somalia, Rwanda, Sierra Leone, Burundi, Tanzania, Liberia, Angola), in South America (e.g., Columbia, Paraguay, Peru, Bolivia), and in Asia (e.g., India, Indonesia, Myanmar, Philippines, Nepal, Sri Lanka, Laos, Afghanistan). Furthermore, there are reports about child recruitment for military service in Europe and Eurasia starting at the age of 16, for orphans even at the age of 10 (e.g., Ireland, Russia, Georgia, Moldavia, Kazakhstan, Ukraine, Serbia, Montenegro). The USA and Canada recruit adolescents under the age of 18. There are case reports about sexual exploitation of child soldiers (mainly girls) in Afghanistan, Angola, Burundi, Congo, Honduras, Cambodia, Canada, Columbia, Liberia, Mozambique, Myanmar/Burma, Peru, Rwanda, Sierra Leone, Uganda, as well as in the UK and the USA (Alfredson, 2001, no pagination). Child recruitment for war and sexual purposes is the most considerable violation of child rights (United Nations Convention on the Rights of the Child) and has enormous implication on the child’s development since identity formation is socially influenced, particularly during adolescents (Beth, 2001, p. 27, no age ranges specified). What is worse, often former child soldiers are not granted asylum since their cases are not officially
Introduction
2
recognized as “child-specific persecution” (e.g., Germany, Norway; Child Soldiers: Global Report 2004, Coalition to Stop the Use of Child Soldiers). Blattman (2007) summarized several reasons why fighter recruitment may focus on children and young adolescents. These arguments should be interpreted as complementary facets of motivations for child recruitment. Firstly, the current demographic shift in poor countries (in part due to HIV/AIDS) led to the largest population of children and adolescents ever. So, this age group is just most available for recruitment and abduction. Secondly, especially African commanders emphasize stamina, survival and stealth of child soldiers as well as their fearlessness and will to fight (International Labor Organization (ILO), 2003). This may be due to limited ability to assess risks, feelings of invulnerability, and short-sightedness (e.g., Brett & Specht, 2004). Thirdly, child soldiers are cheaper for the respective group or organization than adult ones since they need (or can handle) only fewer and smaller weapons and equipment. On the other side, becoming a fighter may be an attractive possibility for children and adolescents facing poverty, starvation, unemployment, and ethnic or political persecution (ILO, 2003). Facing these problems children may be more willing to fight for honour or duty, for revenge or protection from violence (e.g., Brett & Specht, 2004). Fourthly, children are also easier to retain in the group. Commanders reported that children are more malleable and adaptable. They are easier to deceive or to indoctrinate and they stick more to authorities without questioning them (e.g., Gutiérrez, 2006 as cited in Blattman, 2007, p. 8; ILO, 2003). Gutiérrez (2006), among others, also state that moral and personality development is not yet completed in children causing differences in decision-making when compared to adults. Interviews with rebel leaders (of the Ugandan Lord Resistance Army) and conscripts revealed that adults have been the most skilled fighters, but also those who were most likely to desert. Despite being weak fighters, young children have been most likely to stay since they were easiest to indoctrinate. Adolescents seemed to offer the best fit between malleability (or likelihood to stay) and effectiveness as fighters (Blattman, 2007).
Introduction
3
1.1.1 The conflict in Northern Uganda – The atrocious war
The hitherto longest civil war on the African continent refers to the almost 20-year-long Ugandan rebellion led by the LRA (Lord Resistance Army) under Joseph Kony and is deeply anchored in the Ugandan history (Ugandan map see Appendix A). From 1893 to 1962 Uganda was British protectorate. During that time the United Kingdom divided the Ugandan people (or tribes) into three classes according to their home region: the Baganda (Eastern Uganda) became administrative officials of the protectorate, the Bantu tribes (Western Uganda) became workers for coffee and sugar-cane plantation, and the “warlike” Luo-Ethnien (e.g., the Acholi) from Northern Uganda have been recruited for military, police and as prison warders. In 1962, Obote, who belonged to a Northern Uganda tribe, became Ugandan premier (due to election manipulation by the UK). Soon a conflict between Obote and the head of general staff, Amin, arose. Amin also came from Northern Uganda, however, he wanted to undermine police, army and secret services. In 1971, Obote was removed by Amin, which was the beginning of a brutal military regime as well of the decline of the Ugandan economy. Under Amin more than 300.000 members of the opposition have been killed. After Amin’s army had invaded Tanzania, Uganda was conquered in 1979 by Tanzanian troupes with the help of the UNLA (Uganda National Liberation Army) led by Museveni. Amin was removed and replaced by Lule who became head of the provisional civil government. In 1980, the military introduced the deposition of this government and Obote returned from exile. During his dictatorship the decline of the Ugandan economy went further on and human rights had been violated dramatically. In 1985, Acholi troups under Basilo Okello exhibited the putsch of Obote, with Tito Okello Lutwa being appointed Head of State. On the 26th of January in 1986 the Ugandan capital Kampala was taken over by the NRA (National Resistance Army) under Yoweri Kaguta Museveni (a Bantu) who eventually became President of the Ugandan Republic three days later. His period of office lasts until today. Since Museveni’s appointment the Luo-Ethnien (above all the Acholi) tried to regain power by force. Museveni’s counterattacks, however, are supported by the United States as well as by the rebellious movement in Sudan who want to undermine the regime of Khartum (Uganda, Geschichte [Uganda, history], Auswärtiges Amt Deutschland; www.auswaerigesamt.de). In 1987, the voodoo priest Alice Lakwena (lakwena, Acholi language: the messenger) led thousands of Acholi fighters in fatal battles against President Museveni only armed with wooden sticks, stones, voodoo things, and few guns (the Holy Spirit Movement). Trying to
Introduction
4
take over Kampala, they had to face machine guns and heavy artillery. Between 1987 and 1988 thousands of Acholi fighters lost their lives. Those who survived fled into the hills, reunited and formed the LRA (Lord Resistance Army). In 1989, Joseph Kony – nephew and successor of Alice Lakwena – became the LRA’s leader in the war against Museveni. He continued the brutal abduction of children from the villages in Northern Uganda that his aunt had already started some years ago to increase the number of fighters of her Holy Spirit Movement. Within the following decades more than 8.000 children had been abducted and forced to serve the LRA as fighters or sexual slaves. It is assumed that most of them have already been killed. Kony claims to be possessed of several holy ghosts and pursues a faith that is a mixture of Christianity and African witchcraft. He forces all LRA members to believe in his “10 commandments of the Acholi nation” otherwise they are in danger to be severely beaten or even killed. Like Lakwena, Kony believes that there will be a time when the only humans to survive will be those using only simple weapons (i.e., stones, spears, machetes) to put an enemy down. On the battlefield LRA fighters believe (or are compelled to believe) that they are protected by supernatural powers (i.e., by Kony’s holy ghosts). Shortly before a battle Kony is telling what he has just foreseen. During the battle some of the children are wearing crosses, bracelets or water bottles that are believed to create a river that swallows every bullet of the enemy. They are also told to sing prayers during fighting or to sew stones into their clothes, which will raise a mountain in front of them and protect them from the enemy. However, these rituals seem not be implemented consequently by all rebel leaders. But in order to make them conform to the fighting and sexual slavery, the children are beaten, tortured or mutilated by LRA soldiers or other children that are forced to do so. Everybody who tries to escape will be executed. Of course, during battles Kony always stayed far behind them in security. During the last years the LRA mostly operated from Southern Sudan where they established their main camp. Sudan supported them with heavy weapons and ammunition – a departure from Alice Lakwena. Children and adolescents arriving in the LRA’s main camp underwent military and spiritual schooling. UNICEF estimated 500 children to be abducted per month. Living there (with his growing number of wives) Kony included part of the Islamic dogma into his belief system (although foreseeing is a deadly sin in Islam, as well as witchcraft is forbidden in Christianity). Additionally, he developed an eleventh commandment, which forbids riding a bicycle and demands punishment of those who break it. By that time, Museveni – who calls himself the “Redeemer” – feared possible conflict with Sudan when
Introduction
5
invading in order to attack the LRA’s main camp and finish the rebellion. In 2003, the civil war reached a new peak of brutality as the Sudanese government allowed the UPDF (Ugandan People’s Defence Force) under Museveni to enter Southern Sudan to fight the LRA rebels. But the rebels escaped nourishing speculations that Khartum may have warned them. The Sudanese rebellion trying to undermine Khartum supported the UPDF and killed several LRA members. The LRA fled and looted many Sudanese villages in revenge. Thousands of people had been bestially killed. Within the following months, the LRA attacked IDP (Internally Displaced People) camps of several districts, among those, Pader, Gulu, Apac, Kitgum, Lira, and Soroti. They also started attacking catholic priests and nuns. In 2004, the number of people living in IDP camps increased up to 1.6 million and protest marches had been carried out against the massacres. Children who were able to escape from the LRA talked in radio transmissions and called the others to leave the bush. Museveni promised to finish the war and demonstrated readiness for negotiation. In September 2004, the International Court declared support for prosecution and sentencing of all LRA members. Three months later, in December 2004, Kony and Museveni considered collaboration and peace negotiations but in January 2005 the armistice was already broken as LRA troupes attacked UPDF patrols. Since 2006 the actions of Kony and his rebel leaders became more and more bizarre. Kony appeared to loose reality. The LRA started breaking apart with smaller group being spread in Sudan and Congo and the number of abducted children per month is declining. In July 2006 peace talks started in Juba since mediated by the autonomous government of Southern Sudan. The LRA agreed to leave Northern Uganda and to assemble in two locations in Southern Sudan. Initially the security situation improved in Northern Uganda and the number of (originally ten thousands of) night commuters i.e., children coming into Gulu town every night in order to escape from rebel attacks declined drastically. However, both sides violated the agreements for several times. In October 2006 LRA rebels massacred 41 civilians in Southern Sudan. In January 2007 the LRA completely quitted the talks with the demand for a new mediating party but the Ugandan government refused (Mynott, 2007, BBC News). LRA leaders stated that they would not leave the bush until the indictments by the International Criminal Court in Den Haag are dropped. Until 2007, up to 1.2 million of the refugees have stayed in the IDP camps or have moved to satellite camps closer to their home villages (in order to have the ability of farming). Only approximately 230.000 people have already returned to their villages despite huge resettlement programs. They still fear possible attacks by the LRA rebels as well as the
Introduction
6
devastating sight of their land. After 20 years of civil war all the land is overgrown with bush and the infrastructure is destroyed; the cattle that has always been a symbol of wealth for the Acholi people has nearly been exterminated in Northern Uganda. Caritas International (Johnson, n.d.; www.caritas-international.de) estimated the number of children being abducted since 1986/1987 to be 20.000 or more (including children below the age of ten). Others report more than 60.000 abductions with focus on young adolescents (Blattman, 2007). Among those, still 13.000 have been abducted since 2003. During the last two decades the LRA has killed more than 100.000 people and more than one million have been expelled. These internally displaced people (IDPs), who represent approximately 90% of the Northern Ugandan (Acholi) population, are forced to live in 52 different IDP camps mostly depending on food rations. The hygienic conditions within the IDP camps are catastrophically; 63% of the Acholi population live below the poverty line; for 47% the life expectancy is below 40 years and 25% of their children are undernourished (Delius, 2005; www.gfbv.de). Spokespersons of the civil rights movement of Northern Uganda demand for the International Criminal Court to lie down the warrants of arrest for the leading LRA commanders and to charge them according to the Acholi law. Peace negotiations progressed, if at all, very slowly. They stopped on the first of March in 2007 since the International Criminal Court did not respond to the LRA’s demand. Museveni is blamed to do nothing for the Northern Ugandan people; he often promised peace but the situation did not really improve for them.
1.2 Post-Traumatic Stress Disorder (PTSD)
Due to the huge amount of potentially traumatic events Ugandan child soldiers have to face it is expected that a corresponding percentage of them develops related psychological disorders during their life courses, above all a post-traumatic stress disorder (PTSD). Already during the antiquity there have been reports about abnormal psychological reactions after mental load (e.g., psychogenetic blindness). During the late 19th and early 20th century, clinicians became aware of physical and psychological implications of war. In 1871, Da Costa describes a syndrome after traumatizing experiences during the American civil war. This syndrome was characterized by strong vegetative symptoms and, hence, was given the names “Da Costa syndrome”, “irritable heart”, “effort-syndrome” or “neurocirculatory asthenia”. By the end of the 19th century, Charcor examined cases of hysteria and often found sexual
Introduction
7
traumata in his patients’ childhood. In 1889, Oppenheim introduced the term “traumatic neurosis” since he believed that a trauma can involve organic and neurotic symptoms. Similarly, Freud defined the traumatic neurosis as caused by a psychological trauma leading to, among others, bodily symptoms. During the First World War traumatic reactions after “shell shocks” have been described using the term “shiver tremor”, “war trembling” or “war neurosis”. Though this syndrome seemed to be quiet common (estimates of 10% of the American soldiers unable to fight, 40% of the British soldiers being injured) some stated that it would be due to missing will-power (Matsakis, 1994, as cited in Berger, 2004, p. 716). Kardiner also observed strong psycho-vegetative symptoms in soldiers experiencing traumata and introduced the term “physioneurosis”. During the Second World War, victims in the Nazi concentration camps had to suffer unbelievable agonies. Their general assumptions about the world had been scattered. Everyday they had to face terror, torture, death threats, and feelings of hopelessness, which had not been without physical and psychological consequences. The latter became known as “KZ-syndrome” (i.e., Nazi concentration camp syndrome) or “survivor-syndrome”, which included symptoms similar to those of the current concept of post-traumatic stress disorder (PTSD) like rapid psychophysical exhaustion, depression, anxiety and asthenia as well as personality disorders and psychosocial problems. The severity of symptoms correlated with severity and duration of the traumata. In a post-test 45 years later, more than 45% of the holocaust survivors still fulfilled PTSD criteria according to DSM-III-R (American Psychiatric Association (APA), 1987). More recent examinations even reported lasting implications for the next generation (Berger, 2004, p. 716). Later, rape-related syndromes have been described that would also fit today’s PTSD concept (e.g., “rape trauma syndrome”; Foa & Meadows, 1997). Within the third edition of the Diagnostic and Statistic Manual of Mental Disorders (DSM-III, APA, 1980) PTSD was fully recognized and described using clear diagnostic criteria. The International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10: F43.1, World Health Organization (WHO), 1992) followed the DSM-III operationalization.
This work mainly focuses on the DSM criteria (current text revision: DSM-IV-TR, APA, 2000) for PTSD diagnosis since these are more concrete and stricter than those of ICD (current revision: ICD-10, WHO, 1992).
Introduction
8
1.2.1 PTSD Diagnosis (DSM-IV-TR)
According to DSM-IV-TR (APA, 2000), which classifies post-traumatic stress disorder (PTSD) as an anxiety disorder, a PTSD diagnosis is restricted to individuals who have ever experienced or witnessed at least one traumatic event (A criterion). But not every event that is perceived as extremely stressful by the respective person can be considered traumatic. A traumatic event, as defined in DSM-IV-TR (APA, 2000) must involve objective threat to life or physical integrity of oneself or of another person and subjective perception of intense fear, helplessness and/or horror. Victims as well as eye-witnesses “enter a psychological alarm state during the [traumatic] event … [and] a cascade of responses in the body and mind is triggered which can damage both the mind and the body” (Schauer, Neuner, & Elbert, 2005, p. 5). Traumatic events can be man-made or caused by natural disasters. The former involves state-sanctioned or organized violence (e.g., war and combat, torture and brutal imprisonment, persecution, riots, terrorism and mass killing) and interpersonal violence (e.g., experienced or witnessed killing, severe physical or sexual assault, sexual abuse and rape) as well as catastrophes (e.g., car accidents, air-plane crashs and accidents involving poisonous substances). Traumatic natural disasters may be severe floods, hurricanes, earthquakes, or volcanic eruptions. Symptom description of PTSD according to DSM-IV-TR (APA, 2000) involves three main criteria: intrusions (B criterion), avoidance (C criterion), and hyperarousal (D criterion). Intrusion (involuntary re-experiencing) symptoms include repetitive and distressing images or memories, nightmares and flashbacks related to the traumatic event, as well as intense emotional and/or bodily reactions after confrontation. In children, re-experiencing can also mean repetitive re-enactment and frightening dreams without trauma-relation. Criterion C includes active and passive avoidance. The former involves avoidance of thoughts, feelings, and conversations that relate to the traumatic event and avoidance of people, places, and activities that trigger memories of the event. Passive avoidance involves partial amnesia, loss of interest in important activities, emotional numbing, feelings of estrangement and shortened future. Hyperarousal refers to sleep and concentration problems, increased irritability and anger, hypervigilance, and exaggerated startle responses/jumpiness. Associated symptoms reported by sufferers further include derealization, depersonalisation, guilt and shame. The disorder must last at least one month (E criterion) and cause clinically relevant distress and suffering as well as social, educational or occupational function impairment (F criterion).
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Herman (1992) introduced the concept of “complex PTSD”, which is based on the distinction between Type I and Type II traumata. The former refers to traumatic events that can already cause pathological symptoms after a single exposure (e.g., car crash, rape). Type II traumata, however, are traumatic events that occur repeatedly within a certain time span (e.g., childhood sexual abuse, torture, warfare). The latter can lead to (post-traumatic) problems that go beyond the classic PTSD symptoms (intrusions, avoidance, hyperarousal). These problems are categorized as follows: (I) alterations in regulation of affect and impulses, (II) alterations in attention or consciousness (including dissociation and depersonalisation), (III) somatization, (IV) alterations in self-perception (including guilt, shame and self-blame), (V) alteration in perception of the perpetrator (including distorted beliefs), (VI) alterations in relation with others, and (VII) alterations in systems of meaning (including despair, hopelessness, and loss of the previous belief system). A traumatic event can also lead to other disorders than post-traumatic stress disorder (PTSD). Depression, specific phobias, adjustment disorders, enduring personality change (see ICD-10, WHO, 1992), dissociative disorders, neurological damage (because of injuries) and psychosis should therefore be considered in differential diagnosis.
1.2.2
Epidemiology of PTSD and comorbid disorders in the general population
According to Kessler, Sonnega, Bromet, Hughes, & Nelson (1995), the majority of people (51.2% of the males, 60.7% of the females) experiences at least one traumatic event throughout their whole lifetime. On average, men do experience more traumatic events than women, but women do experience more severe events and are more likely to show symptoms of PTSD afterwards (Kessler et al., 1995). Combat events and interpersonal violence (in particular sexual assault) are more likely to be followed by the development of PTSD than witnessed injury or death, accidents, fires or natural disasters (e.g., Kessler et al., 1995; Creamer, Burgess, & McFarlane, 2001). Estimates of PTSD lifetime prevalence for victims of crime range from 19% to 71%, with the last value referring to rapes (Berger, 2004, p.717). Rape elicits highest PTSD rates with a comparatively long duration within the general population (Berger, 2004, p. 718). One third of the people who experience at least one traumatic event throughout their life develop PTSD symptoms (Berger, 2004, p. 718). Breslau (2001a, 2001b; both as cited in Berger, 2004, pp. 717-718) reported that 82% of the people who received a PTSD diagnosis
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showed symptoms for more than three months (chronic PTSD) and that the average duration of PTSD lay between 12 months (for men) and 48 months (for women). PTSD duration was longer for victims than for eye-witnesses. PTSD rates decline with increasing distance of time to the traumatic event (Berger, 2004, p. 718). One third of the people who develop a PTSD in the first month after the traumatic event remain symptomatic for at least three years with enormous risk of comorbid disorders (men 88.3%, women 79%) and secondary problems (Kessler et al., 1995) whereas another substantial part of the sufferers show a steep decline in symptomatology after the first year of illness (Breslau et al., 1991; Kessler et al., 1995). Secondary problems of PTSD are, above all, social withdrawal, relationship problems, hostility, decreasing performance in school or at work and resulting financial problems. Comorbid disorders include alcohol abuse/dependence (male 51.9%, female 27.9%), drug abuse/dependence (male 34.5%, female 26.9%), major depression (48%), dysthymia (22%), generalized anxiety disorder (16%), simple phobia (30%), social phobia (28%), panic disorder (male 7.3%, female 12.6%), agoraphobia (male 16.1%, female 22.4%), conduct disorder (male 43.3%, female 15.4%) and increased suicidality, as well as somatization, chronic pain and general (physical) health problems (Kessler et al., 1995, using DSM-IV (APA, 1994); National Clinical Practice Guideline, 2005, No. 26 on post-traumatic stress disorder). Despite the early assumption that children and adolescents cannot develop PTSD, the disorder can occur at any age and is quiet common. Kessler et al. (1995) reported 7.8% lifetime prevalence for PTSD (10.4% for women, 5.0% for men). They further reported incidence estimates (i.e., the risk of developing the disorder after occurrence of the traumatic event) of 8.1% for men and 20.4% for women. Breslau et al. (1991), however, found an incidence rate of 23.6% (13% for men, 30.2% for women, ratio 1:2). Rape is that traumatic event leading to highest PTSD rates (46% of the women, 65% of the men; Kessler et al., 1995) compared to other event types. Epidemiological studies of children reported estimates of lifetime prevalence of 6% (Giaconia, Reinherz, Silverman, & Pakiz, 1995, as cited in the National Clinical Practice Guideline, 2005, No. 26 on post-traumatic stress disorder, p. 105) to 10% (Kessler et al., 1995). Meltzer, Gatward, & Goodman (2000, as cited in the National Clinical Practice Guideline, 2005, No. 26 on post-traumatic stress disorder, p. 105) reported a point prevalence of 0.4% among children between the age of 11 to 15 years, with the rate for girls being twice as high as that for boys. Registration of PTSD in children below the age of 10 is very rare within the general population (what may be, at least in part, due to missing elaboration of PTSD diagnosis criteria for children). The morbidity risk of PTSD in children and adolescents is approximately 1%, in adults it ranges from 1.5% to 3% (National Clinical
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Practice Guideline, 2005, No. 26 on post-traumatic stress disorder, p. 105). In a meta-analysis of 34 studies and 2697 children Fletcher (1996; as cited in Salmon & Bryant, 2002, pp. 166167) stated that 36% of all children (compared to 24% of the adults) met PTSD criteria after diverse traumata. He found no significant differences in PTSD rates across different developmental stages. PTSD diagnosis received by 39% of the children below the age of 7, 33% of the children aged 6 to 12, and by 27% of all children above the age of 12. Variations of PTSD rates in children may be due to interview style and validity of the assessment instrument since children may have restricted verbal and cognitive abilities (McNally, 1993; as cited in Salmon & Bryant, 2002, pp. 167-168). Brewin et al. (2000) examined potential risk factors of PTSD. Trauma severity, lack of social support and subsequent life stress showed strongest associations with PTSD. Ozer (Ozer, Best, & Lipsey, 2003; Ozer & Weiss, 2004) identified additional factors associated with higher PTSD rates including dissociation during the traumatic event and perceived life threat. Mayou, Ehlers, & Bryant (2002) confirmed female gender to be one risk factor of PTSD. For further risk factors see the National Clinical Practice Guideline, 2005, No. 26 on posttraumatic stress disorder. People especially at risk of PTSD (according to National Clinical Practice Guideline, 2005, No. 26 on post-traumatic stress disorder) are victims or witnesses (including journalists) of violent crime (interpersonal or state-sanctioned), terrorism and forced migration, severe accidents, catastrophes or natural disasters. Furthermore, women following traumatic childbirth, neglected children and people who have received diagnose of a life-threatening illness are also at heightened risk. Additionally, perpetrators and helpers (including members of armed forces, police officers, emergency personnel, and firemen) are also reported to be at risk. Cultural factors seem to have no relevant influence on prevalence rates and validity of PTSD but they should be considered when trying to approach mental health problems in nonwestern societies in general (Schauer, Neuner, & Elbert, 2005): There are considerable similarities and consistencies in the clinical manifestations of psychopathology across different refugee groups; these similarities and consistencies outweigh cultural and ethnic differences. Knowledge of this should lead us away from treating the mental health difficulties of refugees as something new and unusual while allowing us to focus attention on developing culturally sensitive assessment and
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treatment approaches to meet the special needs. (Garcia-Peltoniemi, 1991, as cited in Schauer, Neuner, & Elbert, 2005, p. 13) The most relevant differences between cultures or ethnicities (e.g., Western populations versus African populations) may be type, intensity, and duration of traumatic events (especially of those related to civil war, rebellious movements, ethnic/political persecution, and forced migration).
1.2.3
Epidemiology of PTSD in African populations affected by civil war and forced migration
Populations that experience plural events connected to war, persecution and poverty-related violence are expected to show significant higher rates of physical and psychological morbidity. Most related studies have examined refugees who have migrated into surrounding countries. Karunakara et al. (2004), for example, compared traumatic events and PTSD rates in three different populations: Sudanese refugees (affected by the Sudanese and Ugandan civil wars), Sudanese nationals (stayees in the conflict area), and Ugandan nationals (of stable areas of Northern Uganda). The number of traumatic event types differed significantly among the three populations with the Sudanese refugees reporting the highest amount of experienced and witnessed events. Estimates for PTSD prevalence have been 18% for Ugandan nationals, 48% for Sudanese nationals and 48% for Sudanese refugees. Risk factors for the development of PTSD symptoms had been female gender, low education and older age. However, the Sudanese nationals (living still in Southern Sudan) showed a reversal in the gender difference with males reporting significant higher PTSD rates (maybe because of a higher risk in Sudan of being abducted by rebels at that time). In contrast to findings within the general population, witnessing of (not experiencing) a traumatic event was the best predictor for the development of PTSD symptoms (maybe because of eliciting fears about what else can possible happen to oneself). Summarizing, this study clearly demonstrated the association between violent events related to war and forced migration and the development of PTSD symptoms. Peltzer (1999; as cited in Karunakara et al., 2004, p. 84, 91) found a comparable PTSD prevalence rate of 32% in Sudanese refugees in Uganda. Onyut et al. (2004) interviewed 561 refugee adolescents and adults of Rwandan and Somali nationality in the Nakivale Refugee Camp in South-western Uganda. In 2003, 14.000 refugees had settled in Nakivale with the Rwandans being the largest group due to the Rwandan
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genocide during the 1990s followed by the Somalis due to the Somalia civil war. Other refugees living in Nakivale came from Burundi, Sudan, Ethiopia, Kenya, and Eritrea. On average, traumatic events had happened 9 to 11 years ago, but Onyut et al. (2004) still revealed PTSD prevalences of 31.1% among the Rwandan and 47% among the Somali refugees as well as significant dysfunctioning in the work sector. Similar results have been received in different studies focussing on different populations, areas and continents (see e.g., Mollica, McInnes, Poole, & Tor, 1998; Shrestha et al., 1998, as cited in Karunakara et al., 2004, p. 84; Silove, Steel, McGorry, Miles, & Drobny, 2002). What is more, it has been repeatedly demonstrated that the risk of PTSD increases with an increasing number of previous traumata until the rate of nearly 100% when experiencing more than 28 traumatic events (the so-called building block effect or dose effect; e.g., Neuner et al., 2004; Mollica et al., 1998). Neuner et al. (2004) interviewed the same three population types like Karunakara et al. (2004) in order to examine concrete correlations between number of traumatic events and number of PTSD symptoms. All respondents who reported the highest number of events fulfilled the DSM-IV criteria for PTSD (r = .45 for the last year, r = .49 for the whole life). Overall, DSM-IV criteria for PTSD have been fulfilled by 31.6% of the men and 40.1% of the women. Regarding the three different populations, PTSD prevalence rates amounted to 23.2% in Ugandan nationals, 44.6% in Sudanese nationals and 50.5% in Sudanese refugees living in Northern Uganda. PTSD rate and total number of events correlated linearly with 23% PTSD prevalence in all respondents reporting three or less traumatic experiences up to 100% PTSD in respondents with 28 and more traumatic events.
1.2.4
Epidemiology of PTSD in soldiers
The U.S. government has accomplished two large and independent studies in order to estimate PTSD prevalence in U.S. ex-soldiers ten years after the Vietnam War – the National Vietnam Veterans Readjustment Study (NVVRS) and the Vietnam Experience Study (VES). Both studies received differing PTSD rates: 15.2% in the NVVRS versus 2.2% in the VES. Thompson, Gottesman, and Zalewski (2006) estimated combat-related PTSD prevalences in Vietnam veterans by applying uniform procedures of diagnosing (according to DSM-III-R) to the NVVRS and the VES data. By using narrow and more specific criteria of diagnosis they received similar prevalence estimates for both data sets: 2.9% for the NVVRS and 2.5% for
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the VES. Using broader and more sensitive criteria they received estimates of 15.8% for the NVVRS and 12.2% for the VES, respectively. Laufer, Gallops, and Frey-Wouters (1984) interviewed 350 Vietnam veterans in order to assess associations between psychological well-being and war trauma type (combat exposure, witnessing abusive violence and participation in abusive violence). They developed a 10-item Combat Scale in order to assess combat exposure. The item about having killed an enemy in a combat situation or not was not included but analysed separately: 169 of the veterans answering this item with yes reported 8.0 combat experiences on average compared to only 3.8 experiences among those answering with no. In order to assess exposure to abusive violence as a direct eye-witness and as participant Laufer et al. (1984) used open-ended questions: 32% of all participants reported at least one related event (above all, torture of prisoners, physical mistreatment of civilians, use of non-humanitarian weapons against villages and mutilation of bodies) with 8.4 combat events on average compared to only 4.7 events among those having not at all been exposed to abusive violence. Psychiatric symptomatology has been assessed using the 21-item Stress Scale (Boulanger, Ghislaine, Kadushin, & Martin, 1981; as cited in Laufer et al., 1984, p. 71) in 275 of the participants, which includes symptoms similar to those of PTSD, and five (out of 19) scales of the Psychiatric Epidemiology Research Instrument battery (PERI, Dohrenwend, Shrout, Egri, & Mendelsohn, 1980): demoralization, guilt, anger, active hostility and perceived hostility of others. Both instruments do not allow clinical diagnoses. The results showed that, on average, participants exposed to combat reported one symptom of the Stress Scale more (during the war and currently during the last 12 months), that had already started during the war, than those who had not been exposed. Participants who participated in abusive violence reported even two symptoms more. Overall, Blacks reported more symptoms during the war than Whites (but this may be due to the fact that Blacks were more likely to fight in the first line during Vietnam War). They also showed higher rates of active and perceived hostility than Whites. Concerning current symptomatology, however, effects of race reached nonsignificance. Witnessing abusive violence had no impact on post-traumatic stress symptoms (neither during the war nor currently). However, the impact of participation in abusive violence increased over time. Furthermore, Laufer et al. (1984) reported a cumulative development of stress symptoms with time especially among Blacks since they already reported twice as high initial stress levels during the war than Whites. Vietnam veterans who had actually participated in abusive violence reported that 37-73% of their symptoms already started during war (up to 72-99% when adding the first 12 months after return to a civil life)
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compared to 17-39% (up to 50-69%) of the symptoms of those who had only been witnesses, with the higher rates mostly corresponding to black veterans. Finally, Whites witnessing abusive violence scored higher on feelings of demoralization, perceived hostility and anger and showed worse psychological well-being than Whites who actually participated in abusive violence. Among Blacks the effects were stronger but the other way round (although nearly equally exposed to and participated in abusive violence). Combat exposure had no significant effects indicating that the development of post-traumatic stress symptoms is not always related to a pure cumulative effect of the number potentially traumatic events. The symptom onset was delayed (or developed cumulative over time) for most cases. The authors proposed that war stress has plural elements and that race and participation in abusive violence are factors determining individual responses to war stressors. Further analyses revealed that Whites participating in abusive violence differed (negatively) from all others (independent of race) concerning attitudes toward war practices and the Vietnamese population, they reported more neutral emotions connected to the act and perceived the event as less traumatic. Laufer et al. (1984) also stressed that acts of abusive violence have mainly been conducted by a complete unit (that mostly polarized either black or white) supplying their members with mutual support and justification rather than by individual soldiers. Further studies also showed that witnessing abusive violence and enormous cruelty during the wars in Vietnam and Kuwait was of especially high traumatic valence (Nader, Pynoos, Fairbank, Al Ajeel, & Al Asfour, 1993 and Hiley-Young, Blake, Abueg, Rozynko, & Gusman, 1995).
1.2.5
Epidemiology of PSTD and comorbid disorders in children exposed to warfare and in child soldiers
Dyregrov, Gjestad, and Raundalen (2002) conducted a longitudinal study in Iraq focussing on possible implications of the 1991 Gulf War on children and their families. They interviewed 94 children, aged 6 to 17 years (mean age of 11.5 years; 53% boys, 47% girls), six months, one year, and two years after the war in an area close to the Al Ameriyah shelter. All of them had experienced a bombing of a shelter with more than 750 deaths. In a semi-structured interview (including the Impact of Event Scale (IES), the Child Behaviour Inventory (CBI), the Posttraumatic Stress Reaction Checklist (PTSRC) and the War Trauma Questionnaire the children reported demographic information and experiences of loss, separation and war. The
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results revealed that, among those, 37% of the children had experienced extreme poverty and deprivation due to war conditions, 93% had lost at least one person to whom they felt close to (mostly a friend), 29% had been separated from the father or male caregiver, 83% had been close to bombings, 58% had seen dead bodies and 41% body parts and 76% smelled burned bodies. At all three times of assessment, the majority of the children reported being unhappy. This feeling declined significantly from time 1 and time 2 to time 3 but still stayed at a high amount. 81% reported fear of losing a relative without significant decline. Intrusive and avoidance symptoms reduced two years after the war but also still stayed high. The highest score of avoidance was displayed by children at the age of 10 to 13 years. There were no age differences for intrusions. About 80% of all the children scored above the IES-cutoff point indicating a high rate of possible PTSD diagnoses. Both, boys and girls reported high grief reactions that correlated significantly with the IES-intrusion scores but not with the avoidance scores. Summarizing, children exposed to warfare showed high post-traumatic and grief symptoms that diminished a bit over time but still remained clinical relevant. Thabet and Vostanis (1999) examined 239 Palestinian children aged 6 to 11 years who had experience war-related traumatic events. Using the Gaza Traumatic Event Checklist (Hein Qouta, Thabet, & El Sarraj, 1993) they came to the result that the children had experienced four traumatic events on average (range 0-15 out of 21). Using the Child Post-Traumatic Stress Index (CPTSD-RI, Pynoos, Frederick, & Nader, 1987, DSM-III-R criteria for PTSD, APA, 1987) they found that 174 (72.8%) of the children showed at least mild post-traumatic stress reactions (mean score of 19.9, range 0-49 out of 59 possible points). Among those, 85 (35.6%) showed moderate, 13 (5.4%) severe PTSD reaction. A further examination using the Rutter Scale A2 (parent version, Rutter, Tizard, & Whitmore, 1970; as cited in Thabet & Vostanis, 1999, p. 386) and B2 (teacher version, Rutter, 1967) for behavioural and emotional problems of children revealed that 64 (26.8%) of the children exceeded the A2 cut-off score (of 13) of symptoms including restlessness, irritability, worrying, bed-wetting, headaches, and asthma. This score correlated with the results of the CPTSD-RI. There was no correlation between the teacher version and PTSD detection. The best predictor of PTSD (presence and severity) was the total number of experienced traumatic events. There are only few studies that have been conducted with child soldiers. The most prevalent reason may be seen in its methodological challenges concerning accessibility of these populations (which affects representativeness and size of the sample) and adaptation of instruments.
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Derluyn, Broekaert, Schuyten, and De Temmerman (2004) interviewed 301 former Ugandan child soldiers (82% boys, 18% girls) who had been abducted by the LRA (Lord Resistance Army). The study needed to be restricted to children living in and around Gulu and Lira town due to unstable conditions in Northern Uganda. The average age of abduction had been 12.9 years (age range 12-28 years; age at abduction range 1-22 years) and the average abduction duration 744 days (range 3-2988 days). Of course, almost every respondent experienced traumatic events with an average number of six events (range 0-13 events). 233 of the children (77%) witnessed the killing of another person; 118 (39%) had to kill another person themselves. 18 children (6%) witnessed how a first grade family member (mother, father, sister, brother) had been killed; 7 (2%) had to kill their own father or brother or another family member. 139 children (64%) had been forced to fight as soldiers. Further events that the children reported included, for example, being forced into military training (65%), being forced to loot property and burn houses of civilians (63%), carrying heavy loads (55%), being seriously beaten (52%), getting injured (48%), being forced to abduct other children (39%), being sexually abused/“given as wife” (35%) and giving birth to one or more children in captivity (18%). For a group of 71 randomly selected children (86% boys, 14% girls) posttraumatic stress reaction could be assessed using the impact of event scale-revised (IES-R, Weiss & Marmar, 1997; not validated Luo-version). The IES-R is a self-report measure that consists of three subscales: intrusions, avoidance and hyperarousal. These subscales parallel the DSM-IV criteria (B, C, D) for PTSD. 69 (97%) of these children showed clinically relevant post-traumatic stress reactions. Additionally, demographic characteristics have been assessed in order to examine possible associations with experiences during abductions and post-traumatic stress. 30 (10%) out of all the children were orphans. Derluyn et al. (2004) found no association between age, abduction duration, passed time since escape and PTSD symptoms (no values specified). Likewise, unlike Neuner et al. (2004) they could only demonstrate very weak correlations between total number of events, event type and PTSD symptoms (no values specified). The results should be considered with caution since there are clear methodological drawbacks (e.g., large age range; no concrete PTSD diagnoses basing on a validated screening instrument; missing data). Somasundaram (2002) proposed several “push factors” and “pull factors” making children and adolescents more vulnerable to become child soldiers (i.e., to become adopted by or willingly become member of rebellious movements) by referring to the political situation in Sri Lanka. As push factors he named traumatization (e.g., experiences related to shootings, shelling, landmines, destructions, mass arrests, injuries and killings), brutalisation (mass
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executions and mass detainments of adolescents by the military), deprivation (joining the military because of displacement, poverty and starvation/malnutrition), institutionalised violence (joining rebellious groups because of frustration, hopelessness, fear and dissatisfaction caused by legitimated torture and oppression of (Tamil) minorities) and sociocultural factors (joining rebellious groups in order to escape and liberate from oppressive society (caste) systems). He referred to an epidemiological study conducted in the civil war affected Northern Sri Lanka in 1993 (Somasundaram, 1993, as cited in Somasundaram, 2002, p. 1268). Interviewing 613 adolescents in Vaddukoddai he uncovered several direct stressors of war affecting adolescents: war-related death of a relative (32%), life threats (26%), witnessing violence (25%), injury (7%), detention (6%) and torture (4%). Displacement (39%), economic problems (34%) and lack of food (15%) had been identified as indirect stressors of war. On average every adolescent of the sample experienced four types of war stress. Concerning relevant pull factors Somasundaram (2002) stated, “because of their age, immaturity, curiosity, and love for adventure children [and younger youths] are susceptible to “Pied Piper” enticement through a variety of psychological methods” (p. 1269). These methods that create one (minority) group identity characterised by patriotism and pressure of conformity may involve “public displays of war paraphernalia, funerals and posters of fallen heroes; speeches and videos, particularly in schools; and heroic melodious songs and stories” (Somasundaram, 2002, p. 1269). Older youths are assumed to loose this illusionary view (of the civil war). But what is more, military training (for children above the age of 14 in the Tiger group) is associated with several advantages for the children and adolescents. Society even promotes the development of child soldiers by legitimating oppression of minorities and ignoring (or allowing) the abduction of children for war purposes. The psychosocial and psychological implications for the abducted children have been numerous. 305 school children in Vaddukoddai (Somasundaram, 1993; as cited in Somasundaram, 2002, p. 1268) showed the following symptoms of traumatization (that are similar to those of post-traumatic stress disorder): sleep problems (88%), irritability (73%), decline in school performance (60%), hyperalertness (50%), clinging (45%), sadness (43%), separation anxiety (40%) and withdrawal (25%). Additionally, these children showed increased brutalisation in terms of war vocabulary (64%), war games (54%), aggressiveness (46%), antisocial behaviour (44%) and cruelty (30%). Out of 625 adolescents 31% demonstrated post-traumatic stress disorder (PTSD), 34% anxiety, 29% depression, 32% somatization, 7% alcohol and drug misuse, 45% hostility, 35% functional disability and 34% relationship problems. They also reported cognitive impairments like loss of concentration (48%), loss of memory (44%) and loss of
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motivation (32%). In defending child soldiers as being victims and not perpetrators that should be killed (like it is done in Sri Lanka) Somasundaram (2002) stated that “children are particularly vulnerable during their impressionable formative period” (p. 1270, no age range specified) and assumed that military leaders prefer younger children because of their suggestibility and fearlessness (or weaker ability to estimate dimensions of danger). Using “a cross-sectional self-report design” Amone-P’Olak (2005) examined experiences of war, of physical and of sexual abuse and related psychological pathology (above all, PTSD symptom load) in 123 formerly abducted adolescent girls in Northern Uganda (p. 33). The girls were aged from 12 to 18 years (mean 16.22 years). At the time of the study 59 of them were living in the World Vision Trauma Centre (48%), 45 in the Gulu Support the Children Organisation (GUSCO) centre (36.6%) and 19 in the Kitgum Concerned Women’s Association centre (15.4%). All the three centres are concerned with rehabilitation of former Ugandan child soldiers. 39 out of the 123 girls were child mothers, 15 had already lost their children during captivity and 6 were pregnant. The duration of their abduction ranged from 6 months up to 9 years. Medical records and files of each girl have been checked in order to gain information about physical and sexual abuse and other traumatic experiences during captivity, about sexually transmitted diseases, as well as related physical and psychological (emotional, cognitive and behavioural) symptoms. A War Experiences Checklist (WEC) has been developed to assess war-related events; possible traumatic events before and after the abduction have been assessed by another self-made scale (not specified). In order to assess PTSD symptomatology the Impact of Event Scale – Revised (IES-R, Weiss & Marmar, 1997, using DSM-IV criteria for intrusions, avoidance and hyperarousal, APA, 1994) has been applied. The results demonstrated that more than 90% of the girls saw seriously wounded people and dead bodies, witnessed other people being severely beaten and being abducted. 98.4% of the girls reported that they have been threatened to be killed when disobeying, 97.6% thought to be killed, and 99.2% could only narrowly escape from death. 88.6% have been beaten during captivity themselves; 72.4% have been sexually abused by rebels (forceful marriage usually with the age of 13 and above after the initiation ritual, which involves 15 to 100 strokes with a cane, oil and/or blood smearing) and 3.3% by fellow abductees. 87.8% have been told that their parents were dead, but still 87.0% escaped voluntarily from the rebels. More than 65% witnessed people dying or being killed; 43.9% witnessed others being mutilated. 13.8% smeared themselves with blood of people in order to be brave; 17.9% participated in killings (apart from relatives); 6.5% participated in killing their own relatives; 4.1% witnessed a sibling being killed; 1.6% witnessed one parent or both being killed. On
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average, the girls experienced 23.5 events during captivity (range 8 to 38 events). All but one of the girls (99.2%) showed clinically significant PTSD-related symptoms (especially intrusion and avoidance symptoms at a moderate level). Similarly, concerning their psychological state in general all the girls reported at least one physical (e.g., malnutrition, poor hygiene, extreme sweating, muscular pain), emotional (e.g., anxiety/captivity-related phobias, depression, irritability, hopelessness), cognitive (e.g., intrusive thoughts, problems concentrating, incoherent speech pattern) or behavioural symptom (nightmares, social withdrawal, repetitive play, biting, difficulties in rule compliance). In a very recent study by Blattman (2006), who represents a more economical point of view, examined 741 children and young adults (all male) between the age of 14 and 30 in Northern Uganda (Acholi districts Kitgum and Pader). 462 of those have been ex-combatants (ex-LRA members of any kind). All the respondents completed questionnaires concerning war and abduction experiences, educational and psychosocial outcomes (aggression/violence, hostility, social exclusion and psychological distress) as well as economical (productivity at work), social (membership in a church, school or community group) and political outcomes (voting behaviour). Unfortunately, items and interview procedures are not sufficiently described. For assessment of violent experiences and psychological disorders the Harvard Trauma Questionnaire and the Hopkins Symptom Checklist have been adapted to Northern Uganda (19 items for depression and traumatic stress without description). Abductees seemed not to be stigmatised or socially and politically excluded. The average age at (the longest) abduction had been 14.7 years (SD = 4.8 years). The average duration of (the longest) abduction had been 8.1 months (SD = 15.2 months). 25 % of the abductees haven been forced to kill others, 74% witnessed killings, and 60% have been severely beaten. Intensity of the abduction (i.e., degree of violence) has been operationalized by a 12-item traumatic events scale (not specified). Among those, 89% of the formerly abducted and still 58% of the non-abductees witnessed beating and torturing of others; 78% of the abductees and 37% of the nonabductees witnessed killings; 52% of the abductees and 41% of the non-abductees have been in a crossfire. But events like being forced to abuse dead bodies (23%) and being forced to kill a civilian (stranger 18%; relative or friend 8%) had been restricted to the formerly abductees (Annan, Blattman, & Horton, 2006, Survey for War Affected Youth [SWAY] Final Report). Longer abduction (more than six months) was associated with more educational deficits. Greater violence (experienced vs. committed not clearly separated) was associated with poorer productivity, higher aggression and psychological distress, but not with educational outcomes. Abduction duration and abduction intensity (violence) displayed no
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correlation. The same is true for psychological distress and productivity. Aggression and psychological distress, however, have been strongly related to violence during abduction, but not to abduction duration (i.e., the impact of abduction duration is indirect). More violent traumata have been associated with 0.38 more psychological symptoms – an effect, which has been interpreted as occuring due to selective exposure to violent events rather than to the abduction in general. Pre-abduction household size (smaller households may have been easier to raid by smaller rebel groups), location (in insecure areas) and year of birth (course of the civil war) have been the only predictors for abduction. Aggression in terms of physical fights during the previous six month was found in only 7% and aggression in terms of hostility (being quarrelsome, using abusive language, threatening others and disrespecting other’s property) in only 6% of all cases. There was no difference in frequency of physical fights during the previous six months between abductees and non-abductees, but formerly abductees had been 1.7 times more hostile than non-abducees indicating a more violent socialization in the bush. When comparing abductees and non-abductees Blattman (2006) came to the result that experiences during abduction have most impact on education (0.70 years less schooling and greater reading problems) and productivity (lower work quality). Education and productivity was more impaired when abducted at an adult age (with only the latter being significant). Furthermore, according to Blattman (2006) there have been only small or moderate effects of abduction on the children’s psychological health in general (10% depression and 20-25% PTSD-like symptoms/ intrusions) with the exception of a minority. However, these when keeping in mind that the abduction duration was quite scattering (including also several one-monthly abductions with a lower expected event load than longer abduction durations), rates do not appear to be as low as he assumed. Those abductees who experienced extreme violence displayed greater symptom severity, but on average formerly abductees show similar symptom load like non-combatants. Blattman (2006) concluded that, in general, child soldiers are at least as (or even more) resilient as older soldiers. Furthermore, he emphasized that these results speak against the current Ugandan policy, which focuses mainly on psychosocial rehabilitation of child soldiers and points more on possible education and economic programs (but it could also mean that former child soldiers are not only ones how might need assistance in Northern Uganda).
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1.3 Classic Identity Concepts
1.3.1 Identity Theory (McCall & Simmons; Stryker)
According to identity theory (e.g., Stets & Burke, 2000) identity is based on roles (e.g., as woman, parent or employee) and involves processes concerning self-verification and selfefficacy. Since the self is defined as being reflexive, the process of identification (or identity formation) involves categorization processes. These processes involve naming and categorizing (or classifying) oneself as role occupant in relation to other roles and categories (or classifications). Roles, which are specified by the society, represent certain positions within the social structure. They are defined as relatively stable components. Naming and categorization processes elicit meanings or expectations regarding ones own behaviours and the behaviours of others. These meanings and expectations need to be adopted and fulfilled by the role occupant and serve as behaviour-guiding standards (Burke & Reitzes, 1981, see also para. 1.3.6). In addition, the naming process also refers to the meaningfulness of an individual’s plans and activities (McCall & Simmons, 1978, as cited in Stets & Burke, 2000, p. 225) and resources (Freese & Burke, 1994, as cited in Stets & Burke, 2000, p. 225). So the set of activated (salient) roles and related meanings and expectations can vary across individuals and situations (Stets & Burke, 2000, p. 227). What is more, yet within early developments of the theory (e.g., McCall & Simmons, 1978) roles within an interaction context (or group) have been defined as being interconnected. Personal interests connected to different roles can be competing, so that sufficient role performance (and, hence, satisfying role identity verification) is influenced by counter-role occupants. Thus, sufficient role performance can often only be achieved by interaction and negotiation (i.e., by committing oneself to interaction) and manipulation of one’s environment in order to reach control over resources related to one’s role. According to Stets & Burke (2000) “having a particular role identity means acting to fulfil the expectations of the role, coordinating and negotiating interaction with role partners and manipulating the environment to control the resources for which the role has responsibility.” (p. 226). In contrast to group-based (social or collective) identities of members of one group, role-based identities ground on a difference in perception and action among his or her role and related but distinct counter-roles i.e., individuals do not perceive themselves as being similar to but different from others.
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Summary The main aspects of an identity are categorization of the self into a certain role (defined by society or context) and incorporation of role-related meanings and expectations into the self (Burke & Tully, 1977) or in other words, an individual’s identity consists of self-views that develop through reflexive categorization of the self (identification) in terms of holding particular roles. Role-based identities express “interconnected uniqueness”, not uniformity, and maintain “the complex interrelatedness of social structures” (Stets & Burke, 2000, p. 227). Role occupants differ in their role-related perceptions and actions (Stets & Burke, 2000, p. 226). Role-salience is achieved by interactional commitment to a role-identity and leads to role choice (Stryker, 1980). Thus, identity theorists mainly examined the association between an individual's meanings he or she assigned to his or her role and the individual's role-related behaviour during interpersonal interactions (e.g., Burke & Reitzes, 1981). The concept of role identity can also be applied to groups by defining group members as interrelated individuals with unique, but integrated roles (Stets & Burke, 2000, p. 228). In this case, intragroup relations are the core of consideration: All group members follow their own perspectives but interact to perform their roles. However, not all roles are closely bound to groups. Besides roles (role identities), person factors (personal identities) and group memberships (social identities) are also important and intertwined aspects of an individual’s identity as well as of the society structure. These aspects and its interrelations are considered in the following paragraphs.
1.3.2
Social Identity Theory (Tajfel, Turner)
The origins of social identity theory grew out of H. Tajfel’s and J. Turner’s work during the 1970s addressing psychological and social aspects of “intergroup relations and group processes” (Abrams & Hogg, 1990, p. 2) since these topics have become more and more the focus of social psychological considerations in times of political crises and revolutionary change. Social identity theory (e.g., Tajfel, 1978a; Turner, Hogg, Oakes, Reicher, & Wetherell, 1987) and its descendent self-categorization theory (Turner et al., 1987), which will be discussed later (see para. 1.3.3), are the most central and influential approaches to the understanding of group membership, an individual’s relationship to the group and intergroup relations, above all discrimination and conflict (Capozza & Brown, 2000). It further focuses
Introduction
24
on the relationship between processes of categorization (group membership) and intergroup discrimination (ingroup bias). Social identity theory defines groups as social structures that try to set their members certain “norms, boundaries, goals, purposes and a social context” in order to “establish and maintain a distinctive identity” (Abrams & Hogg, 1990, p. 1). Multiple social categories (or groups) are thought to build social structures by competing for resources, rights and power. Individuals are psychologically bound to those structures through their “self-definition as members of various categories” (Abrams & Hogg, 1990, p. 4). Social identity theory integrates both cognitive and motivational processes (self-related motives and emotions) and assumes that all existing identities basically underlie the same principles (Deaux, 1993, 2000). Self-categorization (i.e., allocating oneself to a particular social category) represents the cognitive component of the theory and was introduced by Turner et al. (1987). This concept involves processes of emphasizing relevant differences between and devaluing differences within categories (or groups). Considerations concerning abandonment, maintenance and enhancement of the respective social identity as well as search for social coherence reflect the motivational aspects. Thus, this component is mainly related to the need for positive self-esteem (self-esteem hypothesis, see also Brown, 2000), which can be achieved by social comparison (Festinger, 1954). The introduction of the self-categorization concept allowed a new distinction between personal and social identity based on contextual or situational salience. According to that, contemporary social identity theory (as well as self-categorization theory) divides an individual's identity into personal and social identification (Worchel et al., 2000, pp. 17-18) but assumes that both identity concepts are arranged along one continuum (see also para. 1.3.4). Personal identity refers to an individual's unique characteristics (e.g., physical appearance, personality traits, past experiences) and is associated with interpersonal comparisons and behaviours. There are no assumptions about how personal identity may be influenced by its social context. Social identity is the result of a categorization process dividing the world into ingroup and outgroup and defining the self as a member of the ingroup (self-categorization). Social identity theory (and self-categorization theory) mainly focuses on social identity aspects and related intergroup behaviours. Tajfel (1972) defined social identity as “the individual’s knowledge that he/she belongs to certain social groups together with some emotional and value significance to him/her of the group membership (p. 31). In other words, “social identity is self-conception as a group member” (Abrams & Hogg, 1990, p. 2). Accordingly, social identity theory simultaneously analyses intergroup behaviour from an individualistic as well as from an social perspective: Psychological processes within the
Introduction
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respective individual, above all self-categorization (Turner et al., 1987), lead to perception of group membership and internalization of overall group norms what in turn produces collective (or social) behaviour of ingroup members (e.g., prejudice and social protest movements: Turner, 1982). The concept of (upward) social comparison (social comparison theory, Festinger, 1954) is originally directed towards people who are similar or even slightly better than oneself in order to enable self-evaluation (Worchel, Iuzzini, Coutant, & Ivaldi, 2000). Social comparison in terms of social identity theory, however, refers to comparison between ingroup and outgroups with focus on distinguishing features that are important (stereotypic) or of social value for the ingroup. As a result, social identity can be enhanced (or positively evaluated) and ingroup variations can be reduced by perceiving the outgroup as worse and different (Abrams & Hogg, 1990). This also means that groups gaining more power, status and resources are more likely to spread their values and ideology (even to other groups). Subordinate groups, however, may communicate negative social identity to their members, who in turn may look for other ways to maintain a positive identity (see Abrams & Hogg, 1990, pp. 4-5). Summary Social identity theory can be delineated by means of a two-process model involving selfcategorization as the cognitive component responsible for social stability and self-esteem (derived from self-evaluation or social comparison) as the motivational component responsible for social change (Billig, 1985, as cited in Hogg & Abrams, 1990, p. 46). In social identity theory an individual’s self-conception is, to a large extent, determined by his or her plural social group memberships (derived from self-categorization), which are assumed to build his or her social identity. That means, social identity is derived from group membership and creates uniformity. The individual is like the others and sees things from the same (group) perspective like the other group members (Stets & Burke, 2000, p. 226). By means of evaluative comparison between ingroups and relevant outgroups, social identity is assumed to be maintained. When this comparison is positive, a positive social identity (and, hence, a positive general self-concept) is achieved. Since there is a clear tendency to favour positive self-concept, social comparison processes also include a motivational aspect: One is more prone to recognize intergroup differences, which bring one’s ingroup in favour over relevant outgroups (Hinkle & Brown, 1990, p. 48).
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1.3.3 Self-Categorization Theory (Turner)
Originally, research connected to social identity theory was interested in intergroup relations and social change. During the late 1970s and early 1980s “intragroup processes and the social group as a psychological entity” became focus of research interest. In line with this, Turner (1981; as cited in Hogg & McGarty, 1990, pp. 11, 14-15) redefined the term “social group” as involving the “structure of self” (personal versus social self, see para. 1.3.3) and emphasized interrelations of categorization and social comparison processes (Hogg & McGarty, 1990, p. 11). Accordingly, self-categorization theory “grew out of the body of research on social categorization … and the related theoretical concept of social identity” in 1985 (Turner, 1985, p. 94, as cited in Hogg & McGarty, 1990, p. 11). Turner stated that “the social identity theory of the group … is a perfectly acceptable alternative name” for his self-categorization theory. But he added that they are “substantively different theories, in terms of the problems they address and the hypotheses they propose (Turner et al., 1987, p. ix). The fundamental element of self-categorization theory (Turner, 1985, as cited in Hogg & McGarty, 1990, p. 10-27; Turner et al., 1987) is the cognitive process of categorization, which involves pointing out similarities among stimuli of every kind within and differences between categories in order to maximize separateness of one’s category. This so-called principle of metacontrast states that “the salient category is that which simultaneously minimizes intracategory differences and maximizes intercategory differences within the social frame of references” and that “the salient social comparative dimension [within the social categorization process] ... represents the in-group prototype or norm” (Hogg & McGarty, 1990, p. 14). This principle is similar to social comparison theory (Festinger, 1954), but it is more concretely directed towards the explanation of group behaviour. Self-categorization in social categories can be considered as the cognitive mechanism underlying social identity formation (or psychological group formation), group processes including discrimination, and self-perception according to group norms, stereotypes, and prototypes (Turner et al., 1987). Furthermore, this process directs focus at context-relevant (group-related) actions in order to keep or maximize subjective meaningfulness of the world within that context. But social selfcategorization does not include motives related to self-esteem or self-enhancement (Turner, 1985, as cited in Hogg & McGarty, 1990, p. 10-27). Instead, the theory involves the dual principle of fit and accessibility in terms (Oakes & Turner, 1986) as motivational aspects of categorization and identification, which leads to category salience.
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In contrast to social identity theory, which conceptualised a continuum ranging from “acting in terms of self” to “acting in terms of group” (see para. 1.3.2), self-categorization theory considers the latter to be just an “expression of the former” and summarizes behaviour of both group and individual as actions of the self (Turner et al., 1987, pp. viii-ix). The self, however, is considered to operate at different abstraction levels. There are three levels of abstraction most important for categorizing oneself and others (Hogg & McGarty, 1990, p. 13): (1) “the superordinate level of humanity (defining one’s human identity)”, (2) “the intermediate level of in-group–out-group (defining one’s social identity) and (3) “the subordinate level of self as unique from other in-group members (defining one’s personal identity). Since the cognitive system (i.e., the categorization process) depends on context as well as on current intentions and past experiences, the abstraction level is not constant and fixed (on the subjectively most important or predominant category) but variable with varying degrees of salience. On level (2) the group is described as prototypical involving stereotypes and norms. The individual member, however, becomes depersonalised, which should not be interpreted in terms of loss of identity but in terms of a contextual change in identity level (or context dependence of the social self-concept). “The depersonalization of self-perception is the basic process underlying group phenomena (social stereotyping, group cohesion and ethnocentrism, co-operation and altruism, emotional contagion and empathy, collective behaviour, shared norms and mutual influence process, etc.)” (Turner, 1985, pp. 99-100, as cited in Hogg & McGarty, 1990, p. 13). Social identity theory originally emphasized one process of social identification (categorizing oneself as a member of the group) leading to conformity to group norms. Turner (1981, as cited in Hogg & McGarty, 1990, pp. 11, 14-15; 1982, as cited in Hogg & McGarty, 1990, pp. 14-15; Hogg & Turner, 1987, as cited in as cited in Hogg & McGarty, p. 15), however, introduced a three-step process of development of conformity to group norms, which he called referent informational influence. These three stages or processed are described as follows: (1) self-categorization as member of a social category or self-assignment to a social identity, (2) formation or acquirement of norms that are stereotypic of that category and (3) self-assignment of these norms with individual behaviour becoming more normative as the membership the respective social category becomes salient. The referent informational influence theory is further supplemented by conceptualizing social identification as selfcategorization process with greater value pointed on salient in-group norms, which minimize ingroup inequalities but at the same time also maximize intergroup differences. In other words, “the most prototypical [or most normative] group member [who represents the relevant group norm] … is simultaneously most different to the out-group and least different to the in-
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group” (Hogg & McGarty, 1990, p. 16). Thus, extreme ingroups (i.e., ingroups with a more extreme norm diverging from “the mean but in the same direction”) have more extreme prototypes or polarized norms (Hogg & McGarty, 1990, pp. 16-17). Further, the salient ingroup norm is that to which individuals (group members) conform. If the social influence (which derives from the social comparative context and, hence, is mediated by the process of self-categorization) is sufficient, conformity to the group norm (or convergence to the prototype) is achieved (Hogg & McGarty, 1990, p. 16). This process can predict polarization or extremism (see Hogg, Turner, & Davidson, 1990). However, support for this assumption mainly stems from research using rather simple and not real-life comparative contexts. Within a more complex and highly textured social comparative context that comprises multiple “conflicting social frames of reference” (Hogg & McGarty, 1990, p. 19) and, hence, plural social comparison dimensions as well as plural possible self-categorizations selfcategorization theory is not longer able to explain or predict the degree of salience of social categories. Summary Self-categorization theory, which is a development of social identity theory, emphasizes “the cognitive process of categorical assimilation and differentiation and especially … the principle of metacontrast – maximizing the ratio of inter- to intracategory differences”, which is essential to social comparison (Hinkle & Brown, 1990, p. 49). The most salient category (an individual chooses to identify with) is that offering greatest accessibility and fit for the respective person.
1.3.4 Activation or salience of personal and social identity (Stets & Burke)
Which identity level (personal, role or social) becomes activated depends on situational factors (e.g., social comparison, fit, roles; Stets & Burke, 2000, p. 228). Furthermore, personal, role- and social identity do influence and infiltrate each other, hence, meanings associated with these identities can be conflicting. But once a type of identity is activated the others may loose influence. Identity theory assumes that commitment plays an important role in identity activation (e.g., Stryker & Serpe, 1994). This commitment involves a quantitative (the number of persons one is connected to by holding an identity) and qualitative component (the relative strength of these ties). The higher the number people one is tied to, the stronger the social embeddedness
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29
of the identity and the more likely is the activation of that identity. The stronger ties to others become by holding that identity, the more salient the identity. Hence, the degree of salience increases with strength of commitment. Salience in terms of identity theory does not refer to characteristics of the situation but only of the respective identity. Identity theory further distinguishes salience of an identity (the probability of identity activation), which is influenced by commitment, and activation of the respective identity (meaning acting it out), which is influenced by contextual factors (e.g., presence of an appropriate role cooperator). Furthermore, by introducing the concept of salience-hierarchy (Stryker, 1968) salience is assumed to be rather relative: It is not excluded that more than one role-identities may be appropriate despite different positions in society and different impact on performance. In such cases Stryker (1968) proposed that individuals strive to act out (activate) the most highly salient identity (at the top of the hierarchy) independent of situational factors. Social identity theory and self-categorization theory merge the concepts of identity salience and activation i.e., a salient identity is simultaneously an activated identity (Stets & Burke, 2000, p. 229). In social identity theory categorization processes play an important role in social identity formation, especially when the group in question is important for the individual, i.e. “social identity becomes relevant when one of the categories includes oneself”, for example, his or her own ethnicity, nationality or sports club (Abrams & Hogg, 1990, p. 2). Furthermore, social identity theory assumes that the self-concept is “a collection of selfimages”, which are aligned along a continuum from personal to social extremes. Thus, a person acts as a group member when social identifications are salient (e.g. “I am a psychologist” or “I am a woman”). The personal self-conception becomes activated (or salient) with the person acting as an individual when personal identity features are predominant (e.g. “My favourite colour is green” or “I am a friend of XY”). Group behaviour (e.g., discrimination) is created by activating (making salient) the social self-concept, not by establishing relationships to other group members, providing group-related rewards, or putting social pressure (Abrams & Hogg, 1990, pp. 3-5). Commitment plays no important role in social identity theory. That means, feelings of involvement (concern or pride) with the group can arise without having close personal relationships to other members or material interests connected to group membership. Instead, a sense of belonging can be established only by the pure knowledge of ones membership. The most important aspects of this salience are separateness and clarity (or distinctiveness) of the social categories. These aspects are not related to situational stimuli, individual motives, goals or behaviours, instead they represent a perceptional bias.
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As an extension of social identity theory, self-categorization theory is also concerned with conditions under which individuals perceive themselves as being part of a category or group (e.g., as being black). Early work stated that “the salience of social categories is determined by their relative novelty, statistical frequency, or perceptual prominence” (Hogg & McGarty, 1990, p. 22) i.e., the category needs to be distinctive. Oakes & Turner (1986) extended the concept of perceptual prominence within self-categorization theory and, hence, elaborated the search for coherence concept (see para. 1.3.5) by stressing the importance of social meaningfulness and relevance of social category membership in a given situation in terms of accessibility and fit. Accessibility refers to the “readiness of a given category to become activated in the person”, which is influenced by physical closeness, current tasks and goals of the person that need to be fulfilled or satisfied (Stets & Burke, 2000, p. 230). Fit is the congruence between category (or group) characteristics and the surrounding situation. It is assumed to have two facets: The concept of comparative fit refers to the metacontrast principle (see para. 1.3.3) with fit being perceived when intragroup differences are evaluated to be smaller than intergroup differences. Normative fit refers to the extent to which characteristics of a category (or group) reflect stereotypes and norms of the respective culture. Thus, this salience concept, which is also accepted by the current social identity theory, emphasizes interactions between individual and contextual/situational characteristics. It allows simultaneous achievement of personal and social goals. Salience in terms of social identity theory and self-categorization theory can also be considered as relative by assuming a hierarchy of inclusiveness of categorization levels (superordinate humanity, intermediate and subordinate). At different points of time different identities may be salient depending on changes in situation and present categorizational dimensions. All theories agree that without activation, an identity has no effect on individual behaviour (Stets & Burke, 2000, p. 231).
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1.3.5 Motivations for identification (Deaux)
According to possible multidimensionality of social (or collective) identity (see para. 1.4.2) it is assumed that identities can vary in content (norms and stereotypes) and meaning (which is influences by personal characteristics, traits, goals, priorities and experiences as well as by context and situation, possible group pressure and society, culture or subculture, see Deaux, 2000, pp. 6-8; see also para. 1.3.6). Underlying social identification processes may relate to different self-evaluations and motivational goals, may have different frames of reference and, hence, have different relevance for different social identities (Deaux, 2000, p. 4). According to social identity theory (e.g., Tajfel, 1978a; Turner et. al, 1987), one reason (motive) for social identification might be the fact that the group or category is there or visible. For gender or ethnic categories the label (or box) is often imposed by surrounding others, and the respective person has to decide whether he or she wants to accept the box (identity) and whether he or she wants to accept content and meaning of that identity (Deaux, 2000, p. 9). If it is almost impossible to deny the labelled identity (like in the case of gender or ethnicity), the person can choose to minimize importance of that category by lowering its position within his or her identity hierarchy and emphasizing others (Deaux, 2000, p. 9). In other cases, social identity theory refers to the so-called self-esteem hypothesis when considering the motivation of social identification. Tajfel (1969) stated that under conditions when a particular social identity is salient (activated), stereotypic features of the respective category or group become assimilated creating a positive social identity in order to preserve or enhance positive self-image (self-esteem). Individuals strive to (positively) enhance the evaluation of their ingroup compared to the outgroup and thereby to enhance also their own self-evaluation (as part of the ingroup). This process represents the fundamental human motivation to strive for (cognitive) coherence also referred to as self-enhancement motive in social comparison processes (see Festinger, 1954). This motive is defined as motivating intergroup behaviour (e.g., group-evaluation in terms of outgroup discrimination and ingroup favouritism; ethnocentrism). This implies (according to social comparison theory, Festinger, 1954) that groups not only compete for material resources but also for anything that can increase positive group self-conception (i.e., positive social identity). The result is that subordinate groups (and their members) have a lower self-esteem than dominating groups. Self-esteem hypothesis has been empirically tested, mainly in minimal group studies (see e.g., Sachdev & Bourhis, 1991), but could not be constantly supported (see e.g., Hogg & Morkans, 1989; Hogg & Sunderland, 1991; both studies cited in Hogg & Abrams, 1990, p. 37).
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Alternative motives for social identification that have been proposed as substitute for the selfesteem motive are e.g., the collective self-esteem motive (Crocker & Luhtanen, 1990), the self-knowledge or self-coherence motive, the self-consistency motive, and self-efficacy motive (Abrams & Hogg, 1990, pp. 42-46). Brewer's (e.g., 1991) optimal distinctiveness theory alternatively assumes that people have two important but countervailing needs regarding social identification: the need for differentiation from others and the need for inclusion into collectives. The individual continuously seeks for optimal (homeostatic) balance between the two endeavours so that a highly differentiated person will rather look for group membership (i.e., social identity) and a person who is part of a larger group will rather look for more distinctive identities. Still another explanation why people choose particular social identifications derives from the assumption that people experience uncertainty when trying to understand and interpret the world. By choosing a particular category (or social identity) and internalizing its prototype (i.e., defining themselves as part of this category), people are able to reduce this uncertainty since it gives them access to a social consensus (Hogg, 1996). Self-esteem hypothesis (see Stets & Burke, 2000; Hogg & McGarty, 1990) is an important part of social identity theory but in self-categorization theory it is neither a module nor is it rejected. Instead, motivations for social identification are discussed in terms of salience in terms of accessibility and fit, (Oakes & Turner, 1986; see para. 1.3.4). Self-categorization theory can better explain social identification according to changes in contextual salience and social change (by applying the concepts of accessibility and fit) when multiple social identities are possible than social identity theory (using self-esteem hypothesis). The motivation behind is the need to maximize meaningfulness of structures of self and others, which can again be achieved by categorization. The categorization process can behaviourally manifest at levels of “intergroup discrimination, acquiescence, intragroup normative competition, elevated self-esteem, depressed self-esteem, in fact virtually anything, but predictable from socio-cultural and contextual factors” (Hogg & Abrams, 1990, p. 47). However, distinctiveness of a certain social category alone is not sufficient to elevate selfesteem. According to Hogg and Abrams (1990, p. 47) “search after meaning” (Bartlett, 1932, as cited in Hogg & Abrams, 1990, p. 43) as human desire concerning one’s self and one’s experiences (i.e., interpreting them in a meaningful way or make them meaningful) may be the primary motive initiating behaviour. This concept involves multiple cognitive processes (e.g., categorization including internalization of ideologies and norms connected to social group
Introduction
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memberships, social representation of experiences, causal attributions, belief systems and judgmental heuristics). One way among many to achieve meaningfulness in a group context is engaging in intergroup discrimination with the possible outcome, among many, of elevated self-esteem. The cognitive process probably underlying the process of meaning maximization may be the categorization process (which defines the parameters of meaning maximization). Finally, actions or behaviours resulting from social categorization are thought to be dependent on the respective social context (which defines the form of meaning maximization). Identity theory considers the motivation for identification in terms of commitment and salience (see also para. 1.3.4): The stronger the commitment the greater the salience and the more likely are actions in terms of this identity (as an indicator of identification). Identity theory also considers the concept of self-esteem and self-efficacy as possible motives: Positive or negative evaluations of an individual’s role-performance enhance or decrease his or her self-esteem provided that the respective role-identity is salient (Stryker, 1980). In terms of self-efficacy, good role-performance enables gaining control over one’s environment. Both concepts have been supported by the findings that self-verification (which is achieved by sufficient role-performance) increased self-esteem and self-efficacy (Burke & Stets, 1999). Further alternative motives (e.g., self-similar to those of the self-esteem hypothesis of social identity theory as well as context dependency of identification have been proposed (see e.g., Burke & Stets, 1999). In contrast to the preceding assumptions about one main motive of social identification Deaux (2000, p. 11) suggests that social identification can serve plural function and that individuals (according to personality or individual differences) may ascribe different levels of relevance to those motivations. Deaux and her colleagues (Deaux, Reid, Mizrahi, & Cotting, 1999), for example, identified seven possible functions of social identification including three individual needs that are related to the self and the development of self-concept (self-insight and understanding, downward social comparison, collective self-esteem) and four group-related needs (ingroup cooperation, intergroup comparison and competition, social interaction and romantic involvement). Stark and Deaux (1996; as cited in Ashmore et al., 2004, pp. 13-14) also found the religious need to be one of the relevant functions. The full range of functions (or motivational aspects) of social identification still needs to be discovered taking into account the great variety of social identity types (e.g., racial, ethnic, gender-related, religious or political). Similarly, recent motivational research concerning identity theory considers multiple motives leading an individual to act in terms of a role (Stets & Burke, 2000, p. 233).
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1.3.6 Strength of identification (Deaux)
One factor differentiating within and between identity categories and related behaviours is strength of identification (Doosje, Ellemers, & Spears, 1995; Ellemers, Spears, & Doosje, 1997; Spears, Doosje, & Ellemers, 1997). Higher group identification is correlated with greater perceived similarity among group members and a lessened tendency to leave the group when confronted with threat. Identity theory again considers commitment and salience (see also para. 1.3.4) as factors influencing strength of identification: The stronger the commitment the greater the salience and the stronger the identification. More recent research concerning social identity theory reports plural factors influencing strength of social identification. First of all, social identities may differ in the extent to which they satisfy an individual’s personal and social motivations (Deaux, 2000, p. 12; Deaux et al., 1999, see para. 1.3.5). This may influence the degree of importance ascribed to these identities and, hence, strength of identification. Additionally, strength of group identification has been shown to be related to self-understanding, collective self-esteem, downward social comparison, ingroup cooperation and social interaction (Deaux, 2000, p. 12; Deaux et al., 1999). The individual’s position within the group in relation to other ingroup members as well as the position of the group the individual belongs to compared to the outgroup are both social factors that elicit social comparison and, hence, also influence strength of an individual’s identity (Worchel, Iuzzini, Coutant, & Ivaldi, 2000, p.24). Furthermore, social comparison influences and is influenced by self-categorization processes (Turner, 1987). Other factors influencing strength of social identification include culture, salience of the group identity (with greater salience as reached by creating interdependence and uniformity leading to stronger identification, see Worchel, Rothgerber, Day, Hart, & Butemeyer, 1998), presence of an outgroup (with an reduction of social identification when there is no relevant or comparable outgroup) and threat to an individual’s social identity (with internal threat by the ingroup causing greater reduction in identification than external threat exerted by the outgroup, see Worchel et al., 2000, pp. 28-29). Differences between cultures are often examined in terms of the collectivism-individualism dimension (Hofstede, 1980; Triandis, 1994, 1995; Hinkle & Brown, 1990). Collective (or collectivistic) cultures emphasize the group as a whole and interdependence of its members. Individualistic cultures, however, focus more on the individual, thereby attaching value to independence, uniqueness and individual responsibility. Capozza, Voci, and Licciardello
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(2000, p. 63) subsumed the several factors defining individualism versus collectivism as follows: Collectivistic cultures emphasize self-interdependence, coherence between collective and individual goals, norm-/obligation-/duty-guided behaviour and independence of personal relationships and personal benefits. Individualistic cultures, however, emphasize selfindependence, preference of personal goals over collective aims, rights-guided behaviour and maintenance of relationships according to rational cost-benefit-calculations. Related research indicates that African, Asian and Latin American cultures tend to be collectivistic; cultures of Western Europe, Canada and the United States, however, tend to be more individualistic (Bond, 1988; Hofstede, 1980; Triandis, 1989). On the personality level, individualistic or idiocentric persons are defined as being less concerned with their group's needs and as feeling proud of personal achievements. Collectivistic or allocentric people, however, are thought to be involved in their ingroup's problems and are able to experience elevated self-esteem after success of other ingroup members. Social identity is thought to be more evident in collectivistic than in individualistic cultures since the former show greater and more permanent pronunciation of group-categorization (Triandis, 1994). In individualistic societies social comparison takes place on a more personal level (interpersonal comparison within the ingroup). Thus, a form of personal identity should be most salient. As a result, Hinkle and Brown (1990) hypothesize that enhancement of one's ingroup in order to heighten one's social identity or collective self-esteem (and hence one's personal self-esteem) prevails in collective cultures (or groups) and persons. Individualists strive for greater distance between them and other ingroup members and, hence, may show less strong identification.
1.3.7 Critical considerations
Self-categorization theory and social identity theory are similarly supported by empirical work and studies addressing minimal group paradigm (see e.g., Tajfel, 1982) and group formation (see Hogg & Turner, 1985a; 1985b), group solidarity, cohesiveness and attraction, social influence, conformity (see e.g., Hogg & Turner, 1987) and group polarization (see Wetherell, 1987), crowd psychology (see Reicher, 1987) and group membership salience (see Oakes & Turner, 1986). However, both theories are not without problems (see Stets & Burke, 2000). For example, roles are mostly neglected in social identity theory and selfcategorization theory. Most important is the criticism connected to the relationship of social identity to the concept of personal identity. In social identity and self-categorization theory
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these two levels of identification have always been considered to be oppositional with the more salient one prevailing in dependency on the given context. But there are assumption that under certain circumstances both levels of identity (groups and roles) might be significant simultaneously (e.g., Worchel et al., 2000, see para. 1.4). Challenging the social identity theory’s identity conception, Worchel et al. (2000) further propose a more textured four-stage rather than two-stage model of an individual’s identity with all four stages of identity acting simultaneously when guiding behaviour but varying in prominence or salience. Within their framework, personal identity is further divided into person characteristics (uniquely personal features including “personality traits, physical characteristics, skills and abilities, personal experiences, and personal aspirations” (Worchel et al., 2000, p. 18) that are not connected to social group membership) and intragroup identity (“the role the individual has within the group and the relationship with the group” but not the group membership itself (Worchel et al., 2000, p. 18). The third component named group membership refers to “the categorization of the world into groups and the determination of personal membership” (Worchel et al., 2000, p. 20). Finally, Worchel et al. (2000, p. 20) describe a fourth dimension called group identity which goes beyond an individual's identity and, hence, is neither sufficiently considered within social identity theory nor within self-categorization theory. Just like individuals try to establish a self-identity and enhance their self-esteem by acting in terms of a group membership (see para. 1.3.5), so, too, do groups aspire to establish a group identity with a certain character label (Worchel, 1998). Individual members may deny this label but still remain part of the group. Group identity needs to be considered within its social context. Another concern comprises the diversity of possible group identities and raises the question whether there is a single identification (as assumed by social identity theory: Tajfel, 1978b) or whether there can be multiple identifications. There may be different group identities at a salient level at the same time with different amounts of individual significance and social consequences (Deaux, 2000). This would indicate that ingroup members are not only concerned with social comparison between their own group and the outgroup, which results in ingroup favouritism (as assumed by social identity theory). Support for this idea stems, in part, from the finding that strength of group identification is only associated with strength of ingroup bias in certain but not all group situations depending on the groups’ collectivisticindividualistic and relational-autonomous orientation (Hinkle & Brown, 1990). Other problems refer, for example, to the explanation of outgroup favouritism and multidimensional intergroup comparison (Hinkle & Brown, 1990, p. 49). Finally, one should keep in mind that most of the research on social identity has taken place in the laboratory using small and
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artificial groups (minimal group paradigm) so that generalization may not be sufficiently possible.
1.4
A Multidimensional Framework of Collective Identity (Ashmore, Deaux, & McLaughlin-Volpe)
1.4.1 The collective identity concept
Since there are multiple theories and approaches trying to describe social (or collective) identities using narrowly selected elements (see para. 1.3) Ashmore, Deaux, and McLaughlinVolpe (2004) offered a multidimensional framework and tried to include plural concepts of possible social identity elements. They referred to identity theory (see para. 1.3.1), social identity theory (see para. 1.3.2), self-categorization theory (see para. 1.3.3) and stage theories (see para. 1.5) but also pointed on a shift in terminology from social identity to collective identity (e.g. Sedikides & Brewer, 2001; Simon & Klandermaus, 2001) because (contraire to assumptions of social identity theory) all aspects of the self are thought to be socially influenced (Simon, 1997). But using the term collective identity is not without problems since it often implies a sense of political consciousness (and identification) and collective action (e.g., social movements). According to Ashmore et al. (2004) these features are only “possible rather than essential elements of collective identity” (p. 81). According to Simon and Klandermaus (2001) when analysing collective rather than social identity one puts greater emphasis on “relatively enduring memberships in real-life social groups, which are in turn typically embedded in structured and rather stable systems of intergroup relations” (p. 320). They further defined collective identity as psychological rather than sociological (group-focussed) concept that refers to the “identity of a person as group member and not [to] the identity of a group as a sui generis entity” (p. 320). In other words, collective identity is defined as psychological construct that refers more to the individual rather than to the group or to ingroup versus outgroup comparison (Ashmore et al., 2004). The term “collective”, however, indicates that the person’s identity is based on group membership i.e., the identity is shared with other group members and, hence, is embedded in a social world. There are multiple collective identities with different dimensions that exist within the social context and are not all necessarily shared with the same people e.g., ethnicity, gender, age, traits and attitudes. Different collective identities can be overlapping, crosscutting or
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conflicting but not all collective identities a person has are automatically salient at the same time. Which collective identities become salient depends on which shared dimensions or group memberships are predominant what in turn depends on accessibility of person variables (perceptual prominence of the group or of group members) and fit of social context variables (meaningfulness and relevance for favourable social comparison within the respective context; Oakes & Turner, 1986; Turner et al., 1987). Additionally, development and evaluation of an individual’s collective identities depends, in part, on his or her life experiences (Simon & Klandermaus, 2001, pp. 320-321). Collective identity (like the social identity concept) also needs to be distinguished from personal identity as well as from relational self and social roles. The former refers to unique characteristics of the self that sets the individual apart from other people or groups. Collective identity, however, “is explicitly connected to a group of people outside the self” (Ashmore et al., 2004). Relational selves and social roles, in contrast, also refer to relationships with other individuals but focus more on the type of relationship between oneself and another individual than on category membership. Like other forms of identity collective identity also serves certain psychological functions. If holding a particular collective identity is satisfying depends on the extent to which this collective identity actually fulfils these functions or satisfies an individual’s psychological needs (e.g., belongingness, social support and solidarity, distinctiveness (from the outgroup), meaningfulness (of the social world) and respect (or positive self-esteem; see also para. 1.3.5). Processes on the cognitive level (stereotyping and self-stereotyping), affective level (ingroup favouritism, outgroup discrimination and prejudicing), and behavioural level (conformity and collective action) support or mediate satisfaction of these psychological needs by the held collective identity (Simon & Klandermaus, 2001, p. 321).
1.4.2 Multidimensionality of collective identity
Social identity theory does not directly exclude the possibility of individual differences in the extent to which people identify with a social category or group (Crocker and Luhtanen, 1990). Hence, it is also important to consider different social (or collective) identity components that are differently expressed within one social (or collective) identity and lead to different related outcomes or consequences. Deaux, Reid, Mizrahi, and Ethier (1995), for example, pointed out that social identities can differ from one another in various ways, among others centrality, the
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collective or individual orientation, social desirability and status of the identity and the extent to which a collective identity is ascribed or achieved (Deaux, 2000, p. 3). The origin of a multidimensional concept of social (or collective) identity is based on Tajfel´s definition of social identity (1972, p. 31, see para. 1.2.3), which allowed a first deduction of three facets of social identification measurement: awareness of group membership, group evaluation and emotional aspects of belonging (e.g., Brown, Condor, Mathews, Wade, & Williams, 1986). Similarly, in a factor analysis of a nine-item measure of social identification (derived from the ten-item Social Identification Scale of Brown et al., 1986) Hinkle et al. (Hinkle, Taylor, Fox-Cardamone, & Crook, 1989) found the following three components: affective (positive emotional) group membership (identification, belonging), a second affective factor referring to the conflict between individual needs and the dynamics of the group (negative affect due to interdependence) and a cognitive component (importance of the group and feeling of strong ties). Ellemers, Kortekaas, and Ouwerkerk (1999) received three factors according to the former distinction of cognitive, evaluative and affective aspects of social identity (using the minimal-group paradigm in the laboratory): group self-esteem (derived from evaluation of one’s group membership), self-categorization (derived from the cognitive process of defining oneself as group member) and affective commitment to the group. Jackson and Smith (1999) also found three components (one cognitive and two emotional ones) that are comparable to those derived from Ellemers et al.’s (1999) analysis: cognitive self-categorization, evaluation of the group and perception of solidarity, togetherness and common fate. Luhtanen and Crocker (1992; Crocker & Luhtanen, 1990) further introduced the collective self-esteem concept (and scale) referring to a social (or group-related) type of self-esteem, which is derived from (positive) evaluation of one’s ingroup. The concept involves four components: (a) private collective self-esteem (i.e., the extent of positive evaluation of one's social groups), (b) membership esteem (i.e., the extent of positive evaluation of oneself as a good member of the social groups one belongs to), (c) public collective self-esteem (i.e., the evaluation of one's social groups by others) and (d) importance to identity (i.e., the extent to which one perceives one's memberships in the social groups as important for one's self-concept). Factor analyses support the distinctiveness of each of these four-item subscales. More recently, Cameron (2004) tried to combine these results and proposed a theory-based three-factor model of social identity which involves ingroup affect (“specific emotions that arise from group membership”, “emotional quality” or “evaluation of group membership”), centrality (“the frequency with which membership in a given group comes to mind” and “subjective importance to the self”) and ingroup ties
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(“emotional closeness” or “sense of belonging with the group”, pp.241-242). Additionally, Prentice, Miller, and Lightdale (1994) distinguished between social identities based on “common bonds” and social identities based on “a common identity”. Ruttenberg, Zea, and Seligman (1996) proposed collective self-esteem (according to Crocker & Luhtanen, 1992; Luhtanen & Crocker, 1990), religious involvement and involvement in ethnic organizations (clubs, associations) to be important indicators (or dimensions) of collective identity. Religious involvement was further divided into religiosity, regular attendance at religious services, affiliation with church, mosque or synagogue and frequent prayer (p. 212). Hence, there is enormous evidence for multidimensionality of social (or collective) identity demanding more complex and elaborated models but still there is no consensus about what dimensions are the most important ones. Plural possible components of social (or collective) identities may actually vary in quantity and quality differentiating identification within and between social (or collective) identities (e.g., differentiating between social identity types according to religion, ethnicity and political orientation). When reviewing current and past research on social and collective identity, Ashmore et al. (2004) came to the result that the broad relevance of the concepts leads to much confusion e.g., different research groups emphasize different dimensions of identification, with some of those meaning literally the same but having been labelled with different names and measured using different methods by the respective researchers, or different researchers using the same name although referring to divergent concepts. According to that they tried to organize the individual-level elements of collective identity creating a multidimensional framework with focus on the following components: self-categorization, evaluation, importance (salience), attachment (commitment) and sense of interdependence, social embeddedness (interactions), behavioural involvement (identity or role choice) and content and meaning (Ashmore et al., 2004; for element descriptions see Appendix B). Ashmore et al. (2004) give the following reasons for their assumption of multidimensionality of collective identity: Firstly, collective identity is not only based on pure categorical (or group) membership, instead it also comprises related cognitive beliefs (e.g., stereotypic traits, ideology and goals of the group). Secondly, collective identity also has affective components (i.e., “some emotional and value significance” (Tajfel, 1972, p.31); one’s evaluation of the group, judgments about one’s group made by others, affective commitment and closeness to the group and other group members). Thirdly, collective identity eventually involves behavioural implications (e.g., individual actions that reflect group membership, collective action like language usage in ethnic identities or church attendance in religious identities).
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Ashmore et al. (2004) also emphasize the interrelatedness of elements of collective identity. These (although mainly moderate) correlations indicate, for example, that affective commitment can exist in the absence of positive ingroup evaluations and vice versa (see also Ellemers et al., 1999). Additionally, interrelations can vary with type of collective identity (e.g., gender, ethnicity or religion), expression of identity elements, type of population (e.g., first-generation or second-generation immigrants) and contextual variables. However, elements of collective identity (that can be assigned to higher order cognitive, affective, and behavioural components of collective identity) do combine to unique profiles (cluster) of collective identification with differences in related attitudes and behaviours (Ashmore et al., 2004, p. 100).
1.4.3 Variability (stability) and context-dependency of collective identity
Ashmore et al. (2004) proposed interindividual and intergroup variability of collective identity elements. Firstly, personal factors (personality traits; predispositions for selfmonitoring and locus of control; preferences for particular people and places in terms of fit) and environmental factors (extent of homogeneity of the environment regarding the respective group; extent of fit between social norms and group norms) may influence variability. Second, stability of an individual’s self-esteem might also influence the stability of his or her collective identity. It has been assumed, for example, that genocide and mass violence are more likely in societies with a “self-concept of superiority” (Staub, 2001, p.168, as cited in Ashmore et al., 2004, pp. 98-99) i.e., with a highly positive view of their group combined with a highly variable, uncertainty-causing evaluation of their group. Like individual thoughts, feelings and behaviours, elements of collective identity also depend on situation and context. According to Ashmore et al. (2004) situations are “concrete physical or social settings in which a person is embedded at any one point in time” (p. 103). Contexts build the surrounding of situations and offer sources of content of social categories (e.g., stereotypes held by the society). Contexts can also be overlapping but they always consist of the following components: (1) material components (number and status of included people and things), (2) social structural components (formal positions and power distributions, rules and procedures), and (3) socio-psychological components (patterns of interpersonal behaviour, shared beliefs (e.g., minority versus majority status) and informal norms, rules and procedures). A situation can prime a collective identity (i.e. make it salient); a context
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moderates and directly influences the situation and, hence, the collective identity (e.g., by presence or absence of identity-relevant cues). Verkuyten (2005, pp. 53-60) also assumed several context elements (according to Ashmore et al., 2004) and pointed on the importance of context when considering collective (ethnic) identity: Social context (situations and relations) influences whether and how a social identity becomes relevant. This is not an automatic process but relates to individual and collective interpretations of this context. As a result, identity formation should be a flexible, context-dependent process that is neither totally stable nor totally malleable but inevitable. Collective identities can be re-/defined and negotiated by actively taking part in the social life i.e., by actively interacting with group members. Ashmore et al. (2004) went even beyond the general research about how a situation makes a collective (or social) identity salient and stated that “how an individual experiences and enacts his or her collective identity [and all its elements] in any given situation depends on the contexts surrounding the person in the situation” (p. 104). This context influence (especially regarding identity salience, see para. 1.3.4) can again be analysed at different levels (e.g., family, school, region, country, state and social, political and economic systems). Since context elements have strongest associations to the narrative element (content and meaning) of collective identity, its analysis should consider the following questions: Firstly, are identity-relevant stories present (e.g., particular texts)? If so, are the continuously present or only at certain points of time? Secondly, how are present stories communicated (approvingly in public or in secret) and by whom? Thirdly, what content do present group stories have (including evaluations of group members and the public; minority or majority status)? Finally, what quality do present stories have (in terms of coherence and organization)? However, there are also context variables that may be relevant for most of the collective identity elements: representation (of other group members), evaluation (of the group by others), power (authority positions) and status (of other group members), personal relations between groups (friendships and romantic relations across groups). Additional context variables affecting collective identities are political variables (e.g., democracy versus dictatorship as form of government), economic factors (e.g., poverty rates of the country versus poverty rates of the respective group) and cultural values and norms (e.g., individualism versus collectivism; see also para. 1.3.6) as well as material, social structural and socio-psychological context components (Ashmore et al., 2004, p. 104). Regarding the development of collective identity Ashmore et al. (2004) state that how an individual defines himself or herself socially and eventually experiences and enacts his or her collective (or social) identities “varies as a function of historical time [or context]” (p. 99).
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Stewart and Healy (1989) reported that events, which occurred during the transition period from childhood to adulthood (no age range specified), affected female identity formation more than events occurring earlier or later in life. Collective identity formation further is thought to be influenced by an “individual’s progression through the life course” (Ashmore et al., 2004, p. 99) e.g., by types of learning experiences during childhood, extent of inclusion of social (group) memberships into the self-concept during adolescence and type and extent of integration of role-based selves (see also para. 1.3.1) in social (collective) self-definitions. Thus, collective identity development can be seen as multidimensionally influenced (for further details see para. 1.5).
1.4.4 Outcomes of collective identification
Collective identification can predict several outcomes at personal, interpersonal, group, and intergroup levels. These outcomes can vary in its evaluative implications since they can be positive (e.g., academic achievement) or negative (e.g., gang violence). It is important to note that, according to Ashmore et al. (2004), behavioural involvement is not an outcome but an element of collective identity. However, possible outcomes are physical and psychological well-being, academic achievement, interpersonal relations (e.g., ingroup bias, prejudice, outgroup discrimination and formation of interpersonal relations), organizational commitment (e.g., extra-role behaviour at the workplace and turnover intentions) and civic and social engagement (e.g., voting behaviour and civic or social volunteering). It has been assumed that collective identification (particularly ethnic identification) may have buffer effects when confronted with potential stressors like (racial) discrimination. According to that, importance of identity (or strength of identification) should predict better physical and psychological health (Sellers, Caldwell, Schmeelk-Cone, & Zimmerman, 2003). Ashmore et al. (2004) propose that analysis of this buffering function of collective identity should involve the comparison of collective identity elements. They suggest that “public regard might be related to a tendency to perceive more discrimination in one’s daily life; [and that] social embeddedness might be related to the availability of coping strategies for dealing with discriminatory treatment” (p. 101). Collective identification can also affect personal selfesteem (in terms of psychological well-being) since individuals often incorporate other people’s attitudes about and evaluations of the group they belong to. However, there is no
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consistent evidence for an association between group stigmatising and lowered self-esteem (see e.g., Crocker & Major, 1989).
1.5
Stage Models of Collective Identity Development (Cross)
Cross’s (e.g., 1991, as cited in Ashmore et al., 2004, pp.106-107; 1994) model of nigrescence for African American identification was one of the first and is still one of the most influential stage models of collective identity. This model assumes that an individual must go through five stages in order to develop a racial or cultural self: (1) pre-encounter stage, (2) encounter stage, (3) immersion-emersion stage, (4) internalisation stage and (5) internalisationcommitment stage. Since Cross’s model of nigrescence offers the best fit to Ashmore et al.’s (2004) model of multiple elements of collective identity (Ashmore et al., 2004, p. 106, table 8), the following descriptions of these five stages will also include references to the respective elements of collective identity (see also Appendix B). During the first stage, race is not yet a relevant part of an individual’s self-concept (i.e., low explicit importance). The second stage involves events (situations) that make his or her race salient (heightened explicit importance) leading to conscious considerations about being Black and possible implications for his or her personal identity. Feelings of interdependence (concerning the achievement of personal outcomes) and mutual fate arise. As the label indicates, stage three includes cognitions, affect and behaviour connected to the knowledge of being a Black person and related self-identification. It refers to a process of transition from just thinking about one’s race to acting in terms of one’s Black race or racial group membership. This process leads to ingroup favouritism and discrimination of the outgroup (the Whites). Collective identity elements that characterize stage three are “high private regard (and low public regard), high social embeddedness (seeking out other African Americans), high behavioural involvement (adopting African dress and going to African cultural events), high explicit importance (“I am Black and proud of it”), espousing a “proBlack, anti-White” belief system (or ideology) and – concerning self-attributed characteristics – an exaggerated emphasis on defining self in terms of the positive stereotypic attributes of African Americans (e.g., “soul”)” (Ashmore et al., 2004, p 107). Stage four refers to the development of a more comfortable view of one’s group membership (or race), which may be interpreted as enhanced attachment, extreme private and little or some public regard. Finally,
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in the fifth stage the racial identity is shown and consistently guides the individual’s actions and outcomes related to the collective identity (see also para. 1.4.4). Further stage models of collective identification have been developed, for example, by Phinney (e.g., 1989; 1990) for ethnic identity and by Downing and Roush (1985; as cited in Ashmore et al., 2004, p. 106) for feminist identity.
1.6 Collective identification and PTSD in child soldiers
Punamäki (1996) introduced the term ideological commitment as a “consistent belief in the justification of the national war and the readiness to participate in it and to interpret its consequences in favourable terms, as well as a defiant stance toward the enemy” (Punamäki, 1996, p. 56). De Silva, Hobbs, and Hanks (2001; as cited in Kanagaratnam et al., 2005, p. 512) assumed that the influential and idealistic minds of children ease their recruitment into armed/rebellious forces (see also Blattman, 2007, para. 1.1). Additionally, ideological commitment was assumed to have strong mediating effects on children’s mental health (Boyden, 1994, as cited in Kanagaratnam et al., 2005, p. 512) but there are also critical considerations about the cognitive abilities of children to think about ideology and nation (Garbarino, Kostelny, & Dubrow, 1991, as cited in Kanagaratnam et al., 2005, p. 512; Goodwin-Gill & Cohn, 1994, as cited in Kanagaratnam et al., 2005, p. 512). Hence, measurement of these concepts in children is not without problems. This may be one reason for the lack of empirical data about collective identity of children in general (and especially of child soldiers due to difficult access). However, war experiences do affect children’s emotional state and attitudes. Jensen and Shaw (1993, as cited in Kanagaratnam et al., 2005, p. 512), for example, reported stronger identification with the community when the child was exposed to warfare. Additionally, Punamäki and Suleiman (1990) described the development of political and nationalistic oriented worldviews in children after war exposure that are often associated with pro-war attitudes (Feshbach, 1994) and showed that Palestinian children were not always pure passive victims of increasing political hardship but instead were also able to engage in active (collective) coping. Parkes (1975) introduced the term “assumptive world”, which was referred to as a “strongly held set of assumptions of the world and the self which is confidently maintained and used as a means of recognizing, planning and acting” (p. 132). Tying up this concept, Janoff-Bulman (1992) claimed that people strive for sustaining old schemas (one’s “assumptive world”) and
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assumed that PTSD symptoms are the result of coping attempts (conscious or unconscious) after losing meaning connected to this “assumptive world”. Potentially traumatic events can conflict with or scatter an individual’s basic assumptions about the (save and just) world. Resulting scattered assumptions, in turn, lead to a disorganized memory structure, which may be shown in PTSD symptomatology. Thus, recovery from PTSD symptoms can only be achieved by re-establishing an “assumptive world” that also integrates the preceding traumatic experiences. People who are just developing their schemas (i.e., who have not yet fix schemas) or who have weak schemas are more likely to be able to integrate inconsistent information (no age range specified). Kanagaratnam, Raundalen, and Asbjørnsen (2005) assessed the relationship between present ideological commitment and PTSD symptoms in former Tamil child soldiers (18 men and 2 women aged 25 to 37) who had been part of different Tamil armed groups in Sri Lanka during their adolescence (13 to 17 years of age) but are now living in exile in Norway. All of them had been recruited below the age of 18 (range 13 to 17 years) and had subsequently actively participated in warfare (range 6 to 120 months). All but one woman had joined combat training (range 0 to 24 months). Living in Norway (range 2 to 108 months) no participant had received a current or lifetime diagnosis of any psychiatric disorder. Exposure to possibly traumatic events has been assessed using the 11-item Exposure Scale for Child Soldiers (ESCS, Raundalen, n.d.; as cited in Kanagaratnam et al., 2005, p. 514), which was supplemented with one further Tamil-specific item. PTSD symptomatology has been assessed using the Impact of Event Scale – Revised (IES-R, Weiss & Marmar, 1997); in order to assess ideological commitment qualitative methods (semi-structured interview about recruitment, combat life, and current situation; Sentence Completion task, Netland, 1992, as cited in Kanagaratnam et al., 2005, p. 514; Kimble et al., 2002, as cited in Kanagaratnam et al., 2005, p. 512, adapted to the armed conflict in Sri Lanka; written assessment in terms or written answering of the questions “Who am I?”, “my past”, “my present”, “my future”) have been applied. In this study strong (or low) ideological commitment has been defined according to Punamäki (1996) and operationalized in terms of strong (or no) glorification and justification of the Tamil war against the government of Sri Lanka in order to reach independence, patriotic (or no) involvement/non-ambivalent (or ambivalent) identification and participation as soldier and defiant (or non-defiant) attitudes toward the enemy” (Kanagaratnam et al., 2005, p. 511, 514). Referring to Somasundaram (2002) and the participants young (and vulnerable) age during relatively chronic stress they expected high psychological distress. They further assumed a more chronic and disabling course of PTSD in non-Western cultures
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than in Western populations (see also Kessler, 2000, as cited in Kanagaratnam et al., 2005, p. 512). Accepting an “assumptive world” (or ideology) is thought to provide an explanatory context affirming the suffering of the individual or the group. This cognitive process further enables the individual to engage in coping strategies and to exert control of his or her emotional state what, in turn, protects the individual from severe implications of traumatic stress (Kanagaratnam et al., 2005, p. 513). The development of strong ideology (and political thinking) is hypothesized to be associated with less severe or fewer PTSD symptoms and is assumed to follow successful integration of past (war) experiences creating consistency with already existing assumptions about the world. Hence, participants expected to show highest PTSD symptom load (or highest vulnerability) are those having experienced the change from the war of the Tamil against the Sinhalese government (suppressing the Tamil minority) to an internal Tamil conflict due to the loss of protective ideology-related explanations of potentially traumatic war experiences and political hardship. Accordingly, low ideological commitment is thought to be associated with integration difficulties concerning traumatic events. Additionally, unwilling participation in atrocities is assumed to be related to higher PTSD symptomatology. According to Kanagaratnam et al. (2005) 17 participants (85%) had been in combat, all men and women reported having seen wounded people and dead bodies and 13 (65%) had been wounded themselves; 9 (45%) had killed and 5 (25%) had tortured or killed other Tamils. All had lost a person they felt close to and all had repeatedly thought that they would die themselves. On average, participants showed 43 posttraumatic symptoms as measured by the IES-R (range 10 to 69 symptoms, which is remarkabe since none of the participant was ever under psychiatric care) but there was no significant correlation between this score and age at recruitment, training duration, duration of exposure (or recruitment), time elapsed since last exposure and time living in Norway (exile). Furthermore, five participants (four men and one woman) demonstrated strong ideology; the other 15 (75%) showed only weak ideological commitment. PTSD symptomatology (of avoidance, arousal and the total IES-score but not of intrusions alone) was significantly different between persons showing strong and persons showing weak ideological commitment. Additionally, participants with strong ideology subjectively reported being less affected by the respective war-related experiences, verifying the results. However, Kanagaratnam et al. (2005) proposed that these differences in strength of identification (or ideological commitment) may have already existed at the time of recruitment (according to Janoff-Bulman, 1992). There was also a significant group difference in time since exposure with the tendency of ideological commitment getting weaker with time. What is most important, none of the participants
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reporting intense exposure (as indicated by relatively long duration of exposure/recruitment, being wounded, having killed (i.e., involvement), having tortured/killed other Tamils and having been in a direct combat) demonstrated strong ideology. Accordingly, ideological commitment can have significant impact on the development of severe PTSD symptomatology of former child soldiers. However, strong present ideological commitment seems to be a better predictor of mental health in cases of least intense and overwhelming traumatic exposure (see also Punamäki, 1996). Event type, duration of exposure and time elapsed since life in the rebellious group moderate the effect of ideological commitment on mental pathology. In reference to other studies (Punamäki, 1996; Muldoon & Wilson, 2001; as cited in Kanagaratnam et al., 2005, p. 518) Kanagaratnam et al. (2005) further proposed that (strong) ideological commitment to the cause of (war-related) events (e.g., suppression of the Tamil minority and striving for independence) may serve as protective factor of the mental health of former combatants.
1.7
Hypotheses
This study was the first phase of a treatment project for former Ugandan child soldiers of Verena Ertl (member of the non-governmental organization vivo and the University of Konstanz, Department of Psychology, Clinical Psychology & Behavioral Neuroscience Unit, Research and Psychological Outpatient Clinic for Refugees; Ertl et al., 2007, in prep.). The aim was to gain first quantitative data about former Ugandan child soldiers (abductees) with focus on traumatic experiences during abduction, related psychological pathologies (PTSD, depression and suicidality), collective identification with the LRA or the group in the bush (as predictor for PTSD) and aggression level. The main part of this work was the development of an instrument that enables measurement of collective identification of former Ugandan child soldiers. Item formulation and categorization referred to Ashmore et al.’s (2004; see para. 1.4) multidimensional model of collective identity (see para. 2.4.6). It is assumed that the abduction of the child first leads to a forced group membership without true identification with LRA norms. Within the following days, months or years of pressure and fear to be killed abducted children and adolescents may accept the rebel identity in order to survive. On the other hand, a LRA-related collective identity may develop (and norms and values become assimilated) as a function of abduction duration or time with the group in the bush and may be associated with intergroup
Introduction
49
differentiation, outgroup discrimination and collective (rebellious or aggressive) behaviours like aggressive acts against the UPDF.
1.7.1 PTSD and the building block effect in former Ugandan child soldiers
It is expected that most of the children and adolescents who have been abducted by the rebels have experienced and/or witnessed at least one traumatic event. As a result it is expected that PTSD rates among formerly abductees are higher than in the general population. It is further assumed that former child soldiers reporting higher event load are more likely to receive a PTSD diagnosis (or are more likely to report more PTSD-related symptoms) than those who report only few or no traumatic events i.e., the probability of a PTSD diagnosis should raise as a function of the number of experienced and/or witnessed traumatic events (building block effect/dose effect; Neuner et al., 2004; see also para. 1.2.3). Further, duration of abduction should also positively correlate with the number of traumatic events and PTSD symptomatology (although the latter correlation could not be found in Kanagaratnam et al., 2005). PTSD diagnosis (or PTSD-related symptom score) is assessed by applying the ClinicianAdministered PTSD Scale (CAPS; see para. 2.4.3). Depression and suicidality are measured using the Mini-International Neuropsychiatric Interview (M.I.N.I.) section A and C (see para. 2.4.4).
1.7.2 Factorial design and reliability of the Collective Identity Questionnaire
The Collective Identity Questionnaire has been developed according to Ashmore et al.’s (2004) model of multidimensionality of collective identity (see para. 1.4) with focus on the following elements: attachment, behavioural involvement and ideology and meaning (deduced from the content and meaning element). Within this study this three-factorial design of LRA-specific collective identity should be replicated for item 1-13 with sufficient (moderate) item reliability.
Introduction
50
1.7.3 Abduction duration and strength of collective identification in former Ugandan child soldiers
Several models assume that an individual develops his or her collective identity (e.g., of his or her race or ethnicity) by going through several stages (e.g., Cross, 1991, as cited in Ashmore et al., 2004, pp.106-107; 1994; see also para. 1.5). Accordingly, it can be assumed that former Ugandan child soldiers may develop a LRA-related collective identity over time (for the concrete stages see Biedermann, 2007, in prep.) i.e., strength of identification of formerly abductees in Northern Uganda is expected to be positively correlated with the duration of their abduction. However, Kanagaratnam et al. (2005) demonstrated that strong identification could not be found in former Tamil child soldiers having been part of the rebellious group for a relatively long time (see also para. 1.6). Thus, it can also be assumed that abduction duration is negatively correlated with strength of LRA-specific identification.
1.7.4
Number of traumatic events and collective identification in former Ugandan child soldiers
Existing studies report that child soldiers these children are not only perpetrators acting according to a rebel ideology but, above all, are also victims (e.g., of beatings, torture, rape) during abduction (e.g., Derluyn et al., 2004; Somasundaram, 1993, as cited in Somasundaram, 2002, p. 1268; 2000; Annan, Blattman, & Horton, 2006, SWAY Final Report; see also para. 1.2.5). Kanagaratnam et al. (2005) reported that strong identification could not be found in former Tamil child soldiers having experienced highly intense exposure (e.g., having been wounded, having killed/having been a perpetrator; see also para. 1.6). Thus, it is proposed that strength of collective identification with the LRA (or the group in the bush) is negatively correlated with the total number of events (or with certain event types) experienced and/or witnessed during the time in the LRA.
Introduction 1.7.5
51 Collective identity as protective factor for PTSD and comorbid disorders in former Ugandan child soldiers
According to the main hypothesis of this work, children and adolescents reporting relatively strong identification with the LRA (or the group in the bush) after their abduction should be less likely to receive a diagnosis of PTSD and comorbid disorders (or should show less PTSD-related symptoms), hence, collective identification is assumed to be a protective factor or buffer of PTSD and comorbid disorders (depression and suicidality). Children and adolescents demonstrating lower or no LRA-related collective identity should show higher pathology (see also Kanagaratnam et al., 2005, para. 1.6).
1.7.6
Collective identity and aggression in former Ugandan child soldiers
Since the LRA is a rebellious movement using aggressive acts and leading a civil war since almost 20 years in order to reach its goals (see para. 1.1.1) it is additionally expected that children and adolescents reporting stronger identification with the LRA should also show higher levels of aggression. Thus, (higher) collective identity is assumed to correlate positively with (greater) aggression.
Method 2.
Method
2.1
Setting
52
This work has been conducted between the 12th of April and the 15th of May 2006 as the first epidemiologically quantitative step (using cross-sectional design) within the “Rehabilitation of former abducted children Project” of Verena Ertl (member of the non-governmental organization vivo (“victims voice”; www.vivo.org) and the University of Konstanz, Department of Clinical Psychology, off-site Psychotrauma Research- and Outpatient Clinic for Refugees), which examines demography, traumatic events, PTSD, depression, suicidality, aggression, and identification of former Ugandan child soldiers before and after a type of trauma focussed treatment. The study took place in Gulu town and surrounding IDP camps in Northern Uganda and was supported by the local organization GUSCO (Gulu Support the Children Organisation). GUSCO runs a reception centre that houses former Ugandan child soldiers who have been brought there by UPDF soldiers (Uganda People Defence Forces) after a battle or escape. GUSCO receives all former abductees until the age of 18 (children above the age of 18 are brought to World Vision reception centres) as well as child mothers who could escape or be freed from the LRA and unaccompanied infants whose mothers had been killed in a fight against the UPDF. GUSCO aims at reintegrating these children and adolescents into their communities (which are mainly situated in IDP camps in and around Gulu district), following them up, and supplying their basic material needs (e.g., a mattress, plate and cup, and a hoe for digging). In the centre, girls and boys sleep separately in two large tents. The young infants sleep with the girls who have the task to watch after them. In front of the tents a small playground has been built for the children and infants. All receive primary medical care (above all, malaria treatment) and have to take part in most of the activities of the daily curriculum, which involves, among other things, class talks (lessons), daily hygiene, cooking fetching water, cleaning the compound, praying, and leisure activities like netball, soccer and traditional dancing. All the activities in the reception centre are supervised by several social workers. Children and adolescents have the opportunity to go to the local hospital if necessary. If parents do not live too far away from the reception centre they are allowed to visit their children there.
Method
53
The staff of GUSCO was fluent in English and could be contacted at any time on the compound of the reception centre or in the office building of the organization directly next to the centre. Children and adolescents living in the centre mainly spoke Acholi or other Luo languages. With the support of GUSCO it was additionally possible to interview former abductees who have already returned to their families living in the IDP camps Unyama, Coope, and Koro. There, people have to live under devastating living conditions and poor health care. Many of them depend on food rations.
2.2 Procedure
In a first meeting of the expert team with the GUSCO director expectations of the local organization as well as research interests and ideas of practical implications within following project phases been discussed. Subsequently, the reception centre has been visited in order to introduce the team to the social workers and to get a first impression of the children. In a second and larger meeting with the GUSCO social workers we tried to get (qualitative) information about former abducted children and adolescents that would help to refine and adapt the items of the Collective Identity Questionnaire (see para. 2.4.6). They reported that former abductees who are at greater risk for lasting effects of the abduction are young mothers, children and adolescents who show signs of mental illness or possession by an ‘evil spirit’ that mainly arise in the community (e.g., speaking in tongues, shouting, running around, chasing others, getting mad, no recognition of social workers, and isolation). Children and adolescents at low risk stay only for a short time in the reception centre, have caring parents, can well reintegrate, and continue or start school soon after arrival in the community. The social workers also reported a lot of stigmatisation, abuse, and social exclusion of the former abductees when back in the community (but this statement could not be verified by freely asking the adolescents in the IDP camps). Within the following days a one-week training of interpreters, who had partly been recommended by GUSCO, was conducted by clinical experts from the university of Konstanz and the university of Zurich. The first step has been expert-explanations of all items of all instruments and the concepts behind (PTSD, depression, suicidality, aggression and collective identification). Further, sufficient expert-guided translation of all items into Acholi language was conducted. One item after the other had to be interpreted by one person followed by a
Method
54
group discussion about the proposal (translation-back-translation principle) with subsequent refinement of the translation. Similarly, each of the interpreters had to translate items by himself or herself and then discuss the translation in the group until an adequate formulation was found. The whole translation/back-translation process was supervised by experts who provided help and sufficient explanations at any time if needed. Subsequently, the formulations have been written down. The second step included expert-guided small-group practical exercises of interpreting with another interpreter checking the translation and roleplays with one of the interpreter playing himself or herself (in real self-experience) and the others playing interviewer and interpreter. The last step was to do first interviews as interpreter of expert diagnostic interviews in the reception centre. Interpreters who still had some problems had been supported by a second interpreter. After theoretical and practical training phase and training on the job finally five interpreters have been selected (one man and four women) and taken under contract. All of them demonstrated high and sufficient qualification. We continued the survey in the GUSCO reception centre directly after interpreter selection. After introducing the project to IDP camp leaders with the help of GUSCO social workers we were also able to interview adolescents who had already left GUSCO and returned to their families into the IDP camps. There we used the same set of structured questionnaires but also asked about possible confrontation with social norms and stigmatisation to get an impression of necessary further assessments in a qualitative manner. Overall, only clinician interviews have been done. On average the interviews lasted 2 to 2.5 hours depending on the extent of psychological distress of the child and his or her ability to concentrate. The children at the reception centre knew our team and were informed and invited by their social workers before the interview started. We tried not to clash with the daily curriculum of the centre as good as possible. In order to establish contact and trust we tried to be present in the centre as often as possible and participated in some of the activities, above all in games and dances. The interviewer dispersion (all clinical experts) has been as follows: Dipl.-psych. Verena Ertl (project leader) did 9.8% of the interviews, Elisabeth Schauer, MA/MPH did 23.0%, Dr. Julia Müller did 11.4%, Dr. Patience L. Onyut did 6.6%, and I, cand.-psych. did 49.1% of the interviews in the reception centre and IDP camps. Due to limitations in time 29.5% of all interviews (most of the interviews in the IDP camps) have been shared by two interviewers with cand.-psych. Jürgen Biedermann always doing the non-diagnostic part (i.e., the demographic interview, the Collective Identity Questionnaire, and the Aggression Scale).
Method 2.3
55
Participants
We interviewed 40 (65.6%) children and adolescents (50% boys, 50% girls) aged 10 to 24 years (M = 15.2) in the GUSCO reception centre and 21 (34.4%) former GUSCO adolescents (71.4% boys, 28.6% girls) aged 13 to 22 years (M = 16.8) in three different IDP camps. The overall average age amounted to 15.7 years of age (SD = 2.6). Originally, we initially defined an age range of 12 to 21 years but this could not always be guaranteed since the children and adolescents (as well as the GUSCO social workers) did not always know the exact age (or year of birth). Information about age should be considered with caution. Random selection of participants in the reception centre could only be applied during the first weeks of the study. By the end the team was forced to interview nearly every child and adolescent within the proposed age range since many of them left early and only few arrived newly (a tendency that reflects reports about declining abduction rates, see para. 1.1). The result was an up-coming sample that included all children and adolescents in the reception centre who were available and agreed with the interview. Adolescents in the IDP camps have been previously selected by GUSCO social workers and the IDP camp’s leaders. Again, the result was an up-coming sample that included children and adolescents who could be found within a very short time, who were able to interrupt work or school and agreed with the interview. An informed consent was signed by GUSCO and the social workers as temporary guardian. Similarly, all of the children and adolescents signed an informed consent (see Appendix C) after receiving sufficient psychoeducation, information about the contents and the process of the interview as well as an explanation that they will not be paid for answering the questions before the interview. The whole set of structured instruments (see para. 2.4) could be applied to all participants. Possible group differences due to interview location (reception centre vs. IDP camps) have been analysed using variance analysis (Oneway ANOVA given homogeneity of variances according to the Levene-Test; F-statistic) for normally distributed continuous variables (according to the Kolmogorov-Smirnov-Z-Test). Fisher’s Exact Test of SAS V8 has been applied for categorical variables. In order to assess possible group differences in continuous variables of non-normal distribution the non-parametric Mann-Whitney-U-Test has been applied. In cases of normal distribution but heterogeneous variances the Welch-Test has been applied (asymptotic F-statistic). The results are summarized in Table 1 and Table 2.
Method
56
Overall, 86.9% of the children and adolescents belonged to the Acholi ethnicity (only 11.5% Langi and 1.6% mixed ethnicity). 75.4% of them have never been married, however, 23.0% (all girls) have been given as wife to a LRA soldier or commander by force. Only 4.9% of all the children and adolescents have never been to school, 75.4% have been to primary school but only 6.6% completed it (i.e., reached P7 level without starting secondary school). 9.8% reached some secondary school (without completing it i.e., without reaching S4 level) but this mainly referred to participants that already lived in the IDP camps (5 out of 6 children). Only 3.3% attended vocational school what again only referred to children living in IDP camps. However, it is noteworthy that only primary school is without school fees in Uganda. Accordingly, many families just cannot afford to send their children to secondary school and further levels. 60.7% of the children (mainly those living in the reception centre) reported to have three proper meals per day (M = 2.8; range 0-4). Almost all the children and adolescents (96.7%) were Christians (only 1.6% Moslems and 1.6% without religion). 96.7% regularly prayed, 82.0% regularly attended religious meetings (the GUSCO reception centre was visited by a priest every week), but only four (6.6%) attended traditional rituals. Furthermore, the children reported to have suffered from 4.0 medical symptoms on average during the past four weeks (above all, flue, headaches, cough, stomach pain and pain in general followed by malaria, fever and shivering, and diarrhoea). Chronic medical conditions have been reported in 31.1% of the cases (above all, chest pain maybe due to carrying heavy loads in the LRA, pain due to bullet wounds, and back pain). Only one adolescent (already living in an IDP camp) reported to have been positively tested for HIV/AIDS (which contrasts to the folk-tale that most of the children in the bush/ the LRA have HIV/AIDS). None of the children and adolescents had drunk alcohol (beer, waragi), used drugs (khat, marihuana) or sniffed glue neither during the past four weeks nor during the time in the LRA. However, 9.8% reported to have been given pills, injections, and/or powder by LRA members that made their body feel different (6.6% once or twice; 1.6% several times; 1.6% often). More than half of the children and adolescents (52.5%) reported that they had been displaced due to civil war. Among those, 31.1% have been displaced with their family only once but still 16.7% have been displaced twice, 3.3% three times and 1.6% four times. 49.2% reported that at least one first grade family member had died during the conflict (among those, 29.5% lost one, 11.5% lost two, 8.2% lost three or more first grade family members). 26.2% of the children and adolescents reported that at least one first grade family member has disappeared during the conflict (among those, 18.0% missed one, 8.2% missed two or more family members).
Method
57
All of the children and adolescents interviewed in the reception centre and the IDP camps had been abducted by the LRA at least once (and hence were former child soldiers). 90.2% had been abducted once, 6.6% had been abducted twice, 1.6% three times, and 1.6% four times. The majority of them (67.2%) has been abducted from their homes. Average abduction duration has been 28.5 months (SD = 35.1) for the first (or only) abduction (45.0 months for the second abduction) with no significant gender differences (U = 453.00; p = .977 for the duration of the first abduction). Total abduction duration (sum score of first, second and third abduction duration) has been 33.6 months on average (SD = 37.1) with no significant gender difference between boys and girls (U = 406.00; p = .474). Most of them (68.9%) could escape from the LRA themselves; 19.7% have been rescued, 8.3% have been released. 26.2% reported that at least one first grade family member had also been abducted by the LRA (among 16.4% one had been abducted, among 9.8% two or more family members had been abducted, too). During abduction they had been exposed to 19.3 potentially traumatic events on average (mode = 16 for both boys and girls) with no significant difference (F = .61; p = .438) between boys (M = 18.9; SD = 5.4) and girls (M = 19.9; SD = 5.1). 53.8% of the girls have been raped (or given as wife). Distributions of all events are displayed in Table 3. 90.2% have been threatened to be killed by LRA members. 87.0% of all the children and adolescents have at least once been forced to be a perpetrator (M = 2.0; SD = 1.6) i.e., to beat or mutilate other people (45.9%); to kill other people (44.3%); to abduct other children (44.3%); to loot or burn houses (60.7%); to sexually assault or violate others (1.6%); to skin, chop humans or to cook human flesh (8.2%). However, nobody had been forced to eat human flesh. Six girls (9.8%; all from the reception centre) gave birth to a child in the bush. At least one event of domestic violence (experienced or witnessed) occurred in 19.7% of the cases. On average they had been 13.4 years of age (SD = 1.9; range 10-19) when experiencing their subjectively worst event. The most common worst events included having been forced to kill other people (23,0%), above all, having beaten others to death, having witnessed others being severely beaten and killed (16,4%), having been severely beaten and threatened to death (16,4%), and having been raped (9,8%), above all, having been given as wife by force; these are followed by having been forced to kill a friend or family member (6,6%), having been in a combat situation (6,6%), having seen dead bodies (6,6%), having witnessed friends or family members being killed (4,9%), and having to cut dead bodies (3,3%). Almost none of them reported to have had a real LRA rank (more than just soldier or private). Only one (1.6%) reported to have been a corporal. At the time of the interview the children and adolescents living in the GUSCO reception centre had already stayed there for 1.8 months (SD = 1.9) on
Method
58
average with no significant difference between boys and girls (U = 135.50; p = .081). Three of them have been in a reception centre for the second time and have already stayed at GUSCO for .8 months (SD = .4) on average. Those interviewed in the IDP camps had returned to their families on average 29.2 months (SD = 22.5) ago (which may at least partly explain the age difference between children and adolescents of the reception centre and those of the IDP camp). None of them had been in a reception centre more often than once.
Table 1 Demographic characteristics of participants in the GUSCO reception centre (RC) and Internally Displaced People (IDP) camps Variable Age in years: M (SD) Sex: n (%) Male Female Ethnicity: n (%) Acholi Atesot Langi Mixed Other Marital status: n (%) Single (never married) Married Cohabiting Divorced Widowed “Given as wife” Religion: n (%) Christianity Islam African tradition Other None Education: n (%) No school Primary school P1-P6 Complete primary school P7 Vocational school Secondary school S1-S3 Complete secondary school S4 Advanced level No. meals per day: M (SD) No. medical disease (last 4 weeks): M (SD) Chronic medical condition (yes): n (%) a b
GUSCO RC (n = 40) 15.2 (2.5) 20 (50.0) 20 (50.0)
IDP camps (n = 21) 16.8 (2.3)
a
b
p
F=5.92 Fisher’s Exact
.018 .173
Fisher’s Exact
.085
Fisher’s Exact
.010
Fisher’s Exact
1.00
Fisher’s Exact
.008
U=103.00 U=297.50 Fisher’s Exact
.000 .057 .244
15 (71.4) 6 (28.6)
32 0 7 1 0
(80.0) (0.0) (17.5) (2.5) (0.0)
21 0 0 0 0
(100.0) (0.0) (0.0) (0.0) (0.0)
27 0 0 0 0 13
(67.5) (0.0) (0.0) (0.0) (0.0) (32.5)
19 0 0 1 0 1
(90.5) (0.0) (0.0) (4.8) (0.0) (4.8)
38 1 0 0 1
(95.0) (2.5) (0.0) (0.0) (2.5)
21 0 0 0 0
(100.0) (0.0) (0.0) (0.0) (0.0)
3 33 3 0 1 0 0 3.2 3.7 10
(7.5) (82.5) (7.5) (0.0) (2.5) (0.0) (0.0) (0.4) (1.8) (25.0)
0 13 1 2 5 0 0 2.0 4.7 9
(0.0) (61.9) (4.8) (9.5) (23.8) (0.0) (0.0) (0.8) (1.8) (42.9)
Mann-Whitney-U-Test due to non-normal distribution significance level ≤ .05 (two-tailed)
Statistic
Method
59
Table 2 Aspects of displacement and abduction due to the LRA rebellion in participants in the GUSCO reception centre (RC) and Internally Displaced People (IDP) camps Variable Displacement: n (%) Once Two times and more Abduction: n (%) Once Two times and more st 1 abduction duration (months): M (SD) Mdn Total abduction duration (months): M (SD) Mdn How left captivity/the LRA: n (%) Escaped Rescued/freed Released other No. family members died in the war: n (%) 0 1 2 3 and more No. family members disappeared: n (%) 0 1 2 3 and more No. family members also abducted: n (%) 0 1 2 3 and more Total no. events: M (SD) Mdn 1 No. LRA specific events : M (SD) 2 No. LRA perpetrator events : M (SD) Mdn No. events of the CAPS event list: M (SD) 3 No. domestic violence events : M (SD) Total no. experienced events: M (SD) Total no. witnessed events: M (SD) Age worst events: M (SD) a b
GUSCO RC (n = 40)
IDP camps (n = 21)
28 (70.0) 12 (30.0)
1 (4.8) 20 (95.2)
Statistic
a
b
p
U=111.50
.000
U=386.50
.325
20 1 23.5 12.0 24.4 12.0
(95.2) (4.8) (28.5)
U=415.50
.945
(28.0)
U=377.00
.513
Fisher’s Exact
.067
(65.0) (22.5) (12.5) (0.0)
16 3 0 2
(76.2) (14.3) (0.0) (9.5) U=242.00
.003
25 11 3 1
(62.5) (27.5) (7.5) (2.5)
6 7 4 4
(28.6) (33.3) (19.0) (19.0) U=326.00
.064
33 3 3 1
(82.5) (7.5) (7.5) (2.5)
12 8 0 1
(57.1) (38.1) (0.0) (4.8) U=342.50
.127
27 8 1 4 17.6 16.0 4.1 1.5 1.5 12.4 .2 9.0 8.3 16.6
(67.5) (20.0) (2.5) (10.0) (5.2)
18 2 0 1 22.6 23.0 4.7 3.1 3.0 15.2 .1 11.7 10.8 13.2
(85.7) (9.5) (0.0) (4.8) (3.6)
F=15.82
.000
(1.1) (1.4)
U=327.00 F=18.83
.138 .000
(2.2) (.4) (2.5) (1.6) (2.2)
F=13.75 U=391.50 F=14.66 c F=15.98 F=.68
.000 .155 .000 .000 .413
35 5 31.2 12.0 38.4 24.0
(87.5) (12.5) (38.2)
26 9 5 0
(40.6)
(1.7) (1.3) (3.1) (.5) (3.0) (2.6) (1.8)
Mann-Whitney-U-Test due to non-normal distribution significance level ≤ .05 (two-tailed) c Welch-Test due to heterogeneity of variances 1 threatened to be killed (experienced/witnessed); given birth to a child during captivity (experienced/ witnessed); forced to abandon a child (experienced/witnessed); forced to eat human flesh (experienced/witnessed) 2 forced to beat, injure or mutilate others; forced to kill others; forced to abduct other children; forced to loot and burn houses of civilians; forced to sexually assault or violate others; forced to skin, chop or cook dead bodies 3 ever been hit by a parent or caretaker in a way that marks were left on the body (experienced/ witnessed); burned by a parent or caretaker (experienced/witnessed)
Method
60
Table 3 Frequency of each events (experienced and witnessed) of the event list Item
Experienced Witnessed n (%) n (%)
General events (CAPS event list) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Natural disaster (for example, flood, hurricane, tornado, earthquake) Fire or explosion Accident (e.g. car accident, boat accident, train wreck, plane crash, serious accident at work, home, or during, recreational activity) Exposure to toxic substance (for example, dangerous chemicals, radiation) Physical assault (for example, being attacked, hit, slapped, kicked, beaten up) Assault with a weapon (for example, being shot, mutilated, stabbed, threatened with a knife, gun, bomb) Unwanted or uncomfortable sexual experience (someone tried to touch your private parts against your will, attempted rape)? Sexual assault (rape, made to perform any type of sexual act through force or threat of harm, e.g. „given as wife“) Combat or exposure to a war-zone (in the military or as a civilian) Captivity (for example, being kidnapped, abducted, held hostage, prisoner of war) Life-threatening illness or injury (self or family member, close friend) Severe human suffering (e.g. forced to carry heavy loads, starvation, torture etc.) Sudden, violent death (for example, homicide, suicide) Sudden, unexpected death of someone close to you Serious injury, harm, or death you caused to someone else
16 Have you seen people with mutilations or dead bodies? Domestic violence 17 Have you ever been hit (with or without belt, board, stick, etc.) by one of your parents/your caretaker in a way that marks were left on your body? 18 Has one of your parents/your caretaker ever tried to burn you (e.g. hot water, cigarette, fire)
4 (6.6) 17 (27.9) 8 (13.1) 3 (4.9)
----32 (52.5) ---
57 (93.4)
57 (93.4)
49 (80.3)
55 (90.2)
17 (27.9)
21 (34.4)
14 (23.0)
24 (39.3)
53 (86.9) 61 (100.0)
--59 (96.7)
26 (42.6) 60 (98.4)
35 (57.4) 60 (98.4) 47 (77.0)
----33 (54.1)
25 (41.0) ---
---
52 (85.2)
9 (14.8)
6 (9.8)
2 (3.3)
4 (6.6)
55 (90.2)
55 (90.2)
6 (9.8) 0 (0.0)
18 (29.5) 15 (24.6)
0 (0.0)
5 (8.2)
LRA-specific events 19 Have you in any way been threatened to be killed by the LRA (e.g. for no reason, for disobeying rules, for failed escape-attempt)? 20 Have you given birth to a child during captivity? 21 Have you ever been forced to abandon your child (either in the bush during captivity or because of the abduction)? 22 Have you ever been forced to eat human flesh by the LRA? LRA-perpetrator events 23 Have you been forced to beat, injure or mutilate someone by the LRA? 24 Have you been forced to kill someone by the LRA? (who?: family ( ), village/community ( ), other ( )) 25 Did you have to abduct other children? 26 Did you have to loot properties and burn houses of civilians? 27 Have you ever been forced to sexually assault/violate someone by the LRA? 28 Have you ever been forced to skin, chop or cook dead bodies by the LRA? 29 anything else?
28 (45.9) 27 (44.3)
-----
27 (44.3) 37 (60.7) 1 (1.6)
-------
5 (8.2)
---
8 (13.1)
1 (1.6)
Method 2.4
61
Instruments
Within this study the following instruments have been applied: a demographic interview, a traumatic event list, the CAPS (Clinician-Administered PTSD Scale; Blake et al., 2000) for the assessment of PTSD since this tool allows extremely detailed evaluation of following therapeutic interventions, the M.I.N.I. 5.0.0 (Mini-International Neuropsychiatric Interview; Sheehan et al., 1998) section A for major depression and section C for suicidality, an aggression scale, and collective identity questionnaire for LRA-related identity of former Ugandan child soldiers that also include an adapted version of the PRISM (Pictorial Representation of Illness and Self Measure; Büchi et al., 2002). Adult versions of CAPS and M.I.N.I. have been chosen since these are more widely used, better validated and have already been applied to multiple populations. Furthermore, since all interviews have been conducted by experts, it could be comprehensible reacted to each child. What is more, the age range of the participants has been quite large with most of them being 15-17 years of age, which justifies the application of adult versions. This work mainly focuses on results of the CAPS and the collective identity questionnaire (including its reliability). Further results will be considered more briefly. All newly developed instruments can be found in the Appendix at the end of this work.
2.4.1 Demographic interview
The demographic part of the interview (see Appendix D) assessed personal characteristics of the former abducted child or adolescent. It has been developed by members of the nongovernmental organization vivo and the Research and Psychological Outpatient Clinic for Refugees of the University of Konstanz. The whole questionnaire consisted of 34 items, however, not all of them could be applied to all participants. For the children and adolescents still living in the GUSCO reception centre item 6 (persons living in the household), 8 (main sources of food for the household), and 9 (household possessions) had to be omitted. These items could be applied only to children and adolescents who had already gone back to their families in IDP camps. The remaining items addressed gender, estimated age, marital status, births, education, ethnicity, religion and religious practices, physical health problems that are common for the region (chronic diseases and diseases during the past month), alcohol and drug use and sniffing glue (during the past month and during the time in the bush/the LRA),
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former displacement, drug application by the LRA (e.g., to enhance physical strength), number of family members displaced and/or killed in the civil war, and frequency, time, place, and duration of abduction in detail.
2.4.2
Event list
The event list entailed 28 items referring to possibly traumatic events the participants might have experienced or witnessed in their lives (see Appendix E). It included the current CAPS Event List (see para. 2.4.3) that has been supplemented with four LRA-specific events, six perpetrator events that were thought to be common in the particular population of former Ugandan child soldiers (see epidemiological research para. 1.2.4), and two items concerning domestic violence. Some events referred only to the girls (e.g., “being given as wife”, given births during captivity, abandonment of one’s own child in the bush). The interviewer had to code the respective event as experienced and/or witnessed and as related to the time in the LRA or to times before and/or after the abduction. The worst event had to be described with few more details at the end of the event list.
2.4.3 Clinician-Administered PTSD Scale (CAPS)
The Clinician-Administered PTSD Scale (CAPS, Blake et al. 1995, 2000) was developed at the National Center of Posttraumatic Stress Disorder in 1990 according to DSM-III-R (APA, 1987) and revised in 1994 in order to guarantee adaptation to the DSM-IV criteria (APA, 1994). It is known as the “gold standard” of PTSD assessment. The CAPS demands evaluation of frequency and intensity of each single symptom according to the strict DSM-IV criteria (APA, 1994, see also para. 1.2.1), and, hence, allows both assessment of presence or absence of PTSD and the quantitative symptom load (PTSD severity) using the symptom score (which is especially important for the evaluation of treatment outcomes). It allows diagnosing for acute stress disorder (ASD with symptom duration less than four weeks after the traumatic event), current or chronic PTSD (symptom duration lasting more than four weeks after the traumatic event), and lifetime PTSD (symptom duration at least four weeks after the respective traumatic event ever in life). Frequency and intensity is evaluated on a five-point Likert-rating scale (0-4) using clear behavioural (for intensity) and frequency
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referents, which can be subsumed to a nine-point severity rating (0-8) for PTSD criterions B (intrusions), C (avoidance), and D (hyperarousal) and for the whole syndrome (Weathers, Keane, & Davidson, 2001, p. 133). One intrusive item, three avoidance items, two hyperarousal items and criterion A need to be fulfilled. The CAPS can furthermore be used to assess both change in symptom status using the 1-week time frame (with a difference of 15 points being a significant change) and current or lifetime diagnoses using the 1-month time frame (past month or worst month after the traumatic event). In this work a 1-month time frame was used. The CAPS (English version) contains a Life Event Checklist (for criterion A: exposure to a traumatic event; A1: objective life threat, severe injury, threat to physical integrity; A2: subjective intense fear, helplessness, horror), which has been supplement with specific items of LRA-related experiences (as victim and as perpetrator) as well as of domestic violence (see para. 2.4.2). The event list is followed by 17 items concerning PTSD symptomatology (items 1-5 for criterion B, items 6-12 for criterion C, items 13-17 for criterion D), onset and duration of symptoms (items 18-19), a lifetime diagnosis instruction, global ratings (items 20-25 concerning subjective distress, impact on social and occupational functioning, global validity of responses, overall degree of impairment, and degree of improvement since last measurement), and optional associated features of guilt over acts of commission or omission, survivor guilt, reduction in awareness of his or her surrounding, derealization, and depersonalisation (items 26-30). We supplemented this version with the ‘shame item’ (associated feature) and three open questions (How do you think (EVENT) has affected your life?; Has anything helped you to feel better since the event?; What do you do to help yourself to feel better when you are sad?) from the CAPS-CA (English child version) since the age range was chosen 12 to 21 years. Furthermore, the functioning items have been supplemented with two more questions concerning help seeking behaviour and self medication: First, in the past (month/week) did you talk to a doctor, traditional healer, priest, any other professional about the problems you have because of the (PTSD SYMPTOMS/problems)? Second, in the past (month/week) did you take medication, use drugs or alcohol for the problems which occurred as a result of the (PTSD SYMPTOMS/problems)? The CAPS has originally been validated on combat Veterans but meanwhile has also been proven to be a very successful tool with excellent psychometric properties in other traumatized populations (e.g., victims of crime and rape, victims of accidents, victims of torture, people having received diagnose of cancer, and Holocaust victims). Weathers, Keane, and Davidson (2001) and Weathers and Litz (1994) reviewed plural psychometric studies and
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came to the conclusion that the CAPS is the most valid instrument for PTSD assessment when compared to other valid instruments or self-report measures. Its reliability has also been proved in analyses of interrater reliability (.90 to 1.00), test-retest reliability (.70 to .90), and internal consistency (.80 to .90). Convergent and discriminant construct validity proved to be equally good: Convergent validity reached .70 and above (e.g., with the SCID PTSD part) and .80-.90 with self-report measures (e.g., the IES, Mississippi Scale for Combat-Related PTSD, Keane PTSD Scale, Davidson Trauma Scale, and PTSD Checklist). Measures of discriminant validity, however, can be problematic since there are substantial overlaps, particularly with depression and anxiety disorders (comorbid disorders, see para. 1.2.2). Diagnostic utility (criterion validity) often reached .70 to .90 or above for sensitivity, specificity, and efficiency with a kappa (degree of concurrence with/prediction of the criterion by the score/diagnosis) of .60 to .70 and above (e.g., with the SCID diagnosis as criterion). Its development according to expert judgments and reliance on DSM-IV criteria (APA, 1994) for PTSD is evidence for its content validity. However, application of the CAPS is not easy to learn and, hence, is mainly restricted to experts.
2.4.4 Mini-International Neuropsychiatric Interview (M.I.N.I.)
The Mini-International Neuropsychiatric interview (M.I.N.I.) is a structured and economic interview (approximately 15 minutes per disorder for the M.I.N.I. standard version, M.I.N.I.Plus version, and M.I.N.I.-Kid version and 5 to 10 minutes for the shorter M.I.N.I.-Screen version) that was developed in the USA and Europe for the assessment of several mental disorders according to DSM-IV (APA, 1994) with compatibility to ICD-10 disorders (WHO, 1992) for the purpose of psychiatric screenings and epidemiological research studies. It allows current and lifetime diagnoses. The aim was also to make detection of subsyndromal variants possible. The application of the M.I.N.I. requires only little interviewer training and, hence, is available as clinician-rated version (M.I.N.I.-CR) and patient-rated version (M.I.N.I.-PR). It enables to diagnose major depression for the last two weeks and recurring (section A), dysthymia for the last two years (section B), current suicidality (section C), current and lifetime (hypo)mania (section D), current and lifetime panic disorder (section E), current (panic disorder with or without) agoraphobia (section F), current social phobia (section G), current obsessive-compulsive disorder (section H), current PTSD (section I), current (12month time frame) alcohol dependence and abuse (section J), current (12-month time frame)
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non-alcohol drug dependence and abuse (section K), current and lifetime psychotic disorder (section L), anorexia nervosa (section M) and bulimia (section N) for the last three month, current (6-month time frame) generalized anxiety disorder (section O), and lifetime antisocial personality disorder (section P). If not otherwise specified, ‘current’ refers to the past month. Sections A to B and D to O refer to the DSM-IV Axis I disorders; section P refers to Axis II disorders (APA, 1994) with a 12-month prevalence of 0.5% and more. Within this study we used the current clinician-rated M.I.N.I. English Version 5.0.0 (Sheehan et al., 1998, using DSM-IV criteria, APA, 1994) section A for current major depression and section C for suicidality. Reliability and validity of this instrument have proved to be sufficient with a more than 50%reduction of application time (when compared to e.g., the SCID or CIDI), which is its greatest advantage (Sheehan et al., 1998). Interrater reliability proved to be excellent with kappa values (for dichotomous diagnoses) of .75 and higher (70% above .90). Likewise, test-retest reliability (with a third blind interviewer one to two days after the initial interview) proved to be good with 61% of the kappa values above .75 (except current mania with a kappa below .45). Validation of the M.I.N.I.-CR with the SCID-P showed sensitivity of .07 or more (except for dysthymia, obsessive-compulsive disorder, and current drug dependence) and specificity of .85 or higher for all diagnoses with a good or very good kappa (.50-.90) for most of the diagnoses (except current drug dependence due to different time frames). Negative predictive values reached .85 or more for all diagnoses; positive predictive values were above .75 for major depression, lifetime mania, current and lifetime panic disorder, lifetime agoraphobia, lifetime psychotic disorder, anorexia, and PTSD and .60 to .74 for current mania, generalized anxiety disorder, current agoraphobia, obsessive-compulsive disorder, current alcohol dependence, lifetime drug dependence, and bulimia (the remaining disorders still reached acceptable values of .45-.59). Concordance of the M.I.N.I-PR has been lower but still good, except (below .45) for disorders with high comorbidity (e.g., dysthymia, social phobia, and drug dependence) and severe psychopathology (e.g., psychotic disorder or mania). Concordance rates of the M.I.N.I.-CR with the CIDI proved to be of similar values. Values for current suicidality diagnoses are not available.
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2.4.5 Aggression Scale
This scale is a shortened version of Buss’ and Perry’s (1992) 4-factorial Aggression Questionnaire (that has already been applied to combat veterans, psychiatric patients in general, forensic patients, perpetrators, students, and adolescents) in order to assess verbal and physical aggression, anger and hostility in former Ugandan child soldiers (see Appendix F). Development of this scale was not focus of this work (personal communication; for further information see Ertl et al., 2007, in prep.), however, correlative associations to PTSD and the collective identity concept will be considered.
2.4.6 Collective Identity Questionnaire and PRISM
The Collective Identity Questionnaire for former Ugandan child soldiers (see Appendix G) was developed according to Ashmore et al.’s (2004) multidimensional model of collective identification (see para. 1.4). However, in order to construct an instrument that, on the one hand, is adapted to the situation of former abducted children and adolescents of Northern Uganda and, on the other hand, is also economic i.e., that is applicable within 15 to maximal 30 minutes (since this was not the only tool and the capability to concentrate is limited), we focused on only three elements of collective identity of Asmore et al.’s (2004) model (see Appendix B): (1) attachment (to friends within the group in the bush and to the group as a whole), (2) behavioural involvement (concerning learned skills, rituals and norms), and (3) meaning and ideology (concerning Kony’s supernatural powers and the sense of fighting; from Ashmore et al.’s, 2004 content and meaning), which was proposed to be the strongest factor. The factors attachment and meaning/ideology both included items (three altogether), that were assumed to inter-correlate and to belong to a construct one could refer to as “inner resistance” (During my time within my group in the bush I always felt like an outsider.2; I never felt emotionally connected to the group in the bush.2; Throughout my time in the bush I resisted to believe in Kony’s rituals and norms.3). The questionnaire consisted of 13 items using a 5-point-Likert-Scale (0- I strongly disagree; 1- I disagree; 2- neither, nor; 3- I agree; 4- I strongly agree) and one additional item for free report, which assessed if there was something good in the bush (or LRA). Within the first 12 items the three factors have not been distributed equally. Instead, factor 3 (meaning and ideology) took the greatest part with six items; factor 1 (attachment) comprised five items (and was also referred to the open item
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14) and factor 3 (behavioural involvement) only consisted of two items. Three out of the first 13 items – namely the inner resistance items – had been reversed coded, in order to control for systematic answer-tendencies (especially to one extreme point of the scale). All items had been pre-designed in Germany but adapted and re-formulated in Gulu, Uganda by all team members (see para. 2.2) after discussions with GUSCO social workers. A factorial analysis could not be applied due to the dichotomous character of replies and small sample size (see para. 3.1.2). The last part of the questionnaire (item 15) comprised a more projective but still quantitative tool that was thought to assess a further important but quite abstract element of collective identification – namely self-categorization (which is part of all main identity theories, see para. 1.3) in an easy manner. Initially, it was intended to use the Inclusion of Ingroup in the Self Scale (IIS, Tropp & Wright, 2001) that uses the Venndiagram metaphor of self and group (a series of circles overlapping at different degrees) in order to assess psychological merging of self and ingroup. But after having adapted the first 14 items of the questionnaire we decided to use an adapted version of the Pictorial Representation of Illness and Self Measure (PRISM, Büchi et al., 2002) instead since this instrument appeared to be easier to apply to the study sample. Büchi et al. (2002) used this instrument to assess the perceived distress and suffering caused by an illness. Their participants were instructed to imagine that a white DIN A4 metal board represented their lives at the moment of the examination and that the yellow disk that was fixed on the board represented their “selves”. Then the participants had been given a red (magnetic) disk that ought to represent their illness. Finally, they had been asked to put the red disk on a board in a way that it reflected the importance of the respective illness in his or her lives at the moment of the study. In order to quantify this importance the distance (in cm) was measured between the midpoint of the yellow (self) and the midpoint of the red (illness) disk (the so-called “Self-Illness Separation”, SIS) with a maximum range of 0-27 cm due to the DIN A4 format of the board and the size of the disks (yellow: 7 cm in diameter; red: 5 cm in diameter). As a result, smaller values of distance between the two disks represented greater subjective suffering due to the illness. This instrument proved to be of good reliability (test-retest reliability of .95; interrater reliability of .79) and validity. In our Collective Identity Questionnaire we tried to apply this concept of distance to the self to assess the child’s or adolescent’s perceived emotional closeness (retrospectively and currently) to Kony, the group in the bush (LRA), and his or her family i.e., we tried to explore to whom the child or adolescent felt he or she would belong to during the time of the abduction (in the bush, in the LRA) and at the moment of the interview (in the reception
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centre or in the IDP camps). We used a white DIN A4 sheet of paper and painted a circle (7 cm in diameter) in the right bottom corner. We painted one yellow paper circle (7 cm in diameter) three additional circles in red, blue, and green (5 cm in diameter). Like Büchi et al. (2002) we asked the children and adolescents to imagine the white sheet of paper to represent their whole life and the yellow circle, that was placed in the right bottom circle, to represent themselves at the moment of the interview. Then the interviewer explained the meaning of the smaller circles as well as what is meant by a shorter or longer distance between the yellow circle and each of the others. The blue circle represented Kony, the green one represented the group in the bush (LRA), and the red circle represented his or her family. The instruction was: “Please place these discs on the sheet in a way that it becomes clear how much space this person/this group takes/took in your life. If the person/the group takes/took a lot of space in your life then place the corresponding disc close to the circle that represents yourself. If you place the disc in a greater distance to yourself then you show that this person/this group takes/took less space.” We first asked the interviewee to imagine the time when he or she still had to stay in the bush in the LRA. When this was understood the interviewer asked how close he or she felt to Kony, to the group in the bush, and to his or her family during that time. Each of the three respective circles had to be placed on the sheet of paper separately according the child’s perceived closeness (close to the yellow circle) or distance (far away from the yellow circle representing the self). The distance to the yellow circle was measured for each of the three smaller circles separately (with a possible range of 0-27 cm between two midpoints). Finally, the whole procedure was repeated for the present (current closeness or distance). All of the interviewed children and adolescents replied to both parts of the Collective Identity Questionnaire.
2.5
Data analysis
Data analysis was done using the statistical computer programs SPSS for Windows 12.0, standard version and the SAS System for Windows V8 (for further details of the data analysis see para. 3.).
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3. Results The data have been analysed using descriptive statistics (e.g., M; SD). Possible group differences (reception centre vs. IDP camps or boys vs. girls) have again been analyses using Oneway ANOVA (F-statistic, given homogeneity of variances according to the Levene-Test) for normally distributed continuous variables (normality according to the KolmogorovSmirnov-Z-Test). For categorical variables the Fisher’s Exact Test of SAS V8 has been applied (for all other analyses SPSS 12.0 was used). In order to assess possible group differences in (dependent) continuous variables of non-normal distribution the non-parametric Mann-Whitney-U-Test has been applied. In cases of normal distribution but heterogeneous variances the Welch-Test (asymptotic F-statistic) was used. For the assessment of differences in variable distribution within related samples the Wilcoxon Signed-Rank Z-Test has applied. Pearson correlations have been assessed in order to explore possible associations between continuous variables. Additionally, partial correlations have been assessed to uncover possible apparent correlations. Kendall’s Tau-b has been assessed to explore possible associations between categorical variables. Results that refer to correlative effects can be evaluated as good when the correlations are significant according to an at least 95%-confidence probability (alpha of .05 or below). When evaluating results that have been received from linear regression analyses in order to determine possible predictors of the dependent variable (H0: all real regression coefficients βi = 0 or there is no significant association with the population) several indicators should be considered (according to Backhaus, Erichson, Plinke, & Weiber, 2006, pp. 45-117). Most important for the goodness of the regression model (i.e., its closeness to reality) are the coefficient of determination R², Beta (standardized regression coefficient, which equals the Pearson correlation coefficient in a simple linear regression using only one predictor) and significance of the regression coefficients (according to the t-Test with 95%-confidence probability or according to the F-statistic of the oneway ANOVA when considering the whole regression model). The higher R², the better the fit of the regression model (when considering only one possible predictor in the regression model). In cases of multiple predictors the value of R² raises and never falls with increasing number of possible predictors (independent variables) no matter if some of them are inadequate or wrong chosen. Hence, further considerations concerning its goodness of fit should be done. Above all, one regressor must not be (highly) linear dependent on the other regressors of the model, which may be indicated by high inter-correlations of the independent variables. This multi-co-linearity can further be
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checked by calculating the so-called ‘tolerance’ of each of the independent variables, which subtracts R² resulting from each regression on each independent variable with all the other independent variables as regressors from 1 (1–R²). This value should be relatively close to one otherwise the independent variables are highly inter-correlated and a linear regression is invalid. General premises of linear regression are normal distribution of the dependent variable, normal distribution of the residua (which can be assumed when N > 40 according to the central limit theorem and tested with the help of the P-P-diagram), linearity between the dependent and all independent variables (can be checked by plotting a point-diagram), nonheteroscedasticity (or homoscedasticity in terms of constant scattering of the residua, which can be seen in the scatter plot of the estimates (predictions) of the dependent variable and the standardized residua and tested in using the Levene-Test) and non-autocorrelation (uncorrelatedness of the residua, which can be seen within the same diagram).
3.1
Hypotheses
3.1.1
PTSD (CAPS) and the building block effect
PTSD sum score and diagnosis have been assessed using the Clinician-Administered PTSD Scale (CAPS; see para. 2.4.3). Overall, 24.6% of all the children and adolescents received a PTSD diagnosis with an average CAPS score (of the criteria B, C and D; normally distributed) of 60.5 points (SD = 17.2) out of 96 compared to 21.4 points (SD = 14.9) in children and adolescents without PTSD diagnosis (F = 72.28; p = .000; difference valid for all three criteria B, C, D). Average CAPS score for all participants reached 31.0 points (SD = 22.9). There has also been a significant difference in the CAPS average score between boys (M = 36.4; SD = 26.7) and girls (M = 23.8; SD = 13.9) according to the Welch-Test (asymptotic F = 5.67; p = .021; due to heterogeneity of variances). When comparing CAPS score and CAPS diagnosis of children and adolescents still living in the GUSCO reception centre with CAPS score and diagnosis of those already living in their communities (IDP camps), a significant CAPS score × interview location (reception centre vs. IDP camps) interaction was found (F = 9.63; p = .003) with 24.9 points on average (SD = 17.7) in the reception centre versus 42.8 points (SD = 27.2) in the IDP camps (see also Fig. 1). Due to heterogeneity of variances, group differences (reception centre vs. IDP camps) concerning CAPS score (of the criteria B, C and D) have further been proved using the
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Welch-Test (asymptotic F = 7.44; p = .011). Children and adolescents in the IDP camps received more PTSD diagnoses (n = 10; 12.5%) compared to only five PTSD diagnoses (47.6%) in the reception centre (Fisher’s Exact Test: p = .004). However, there was no significant difference in the PTSD criterion D (hyperarousal) between children and adolescents interviewed in the reception centre and those interviewed in the IDP camps (see Fig. 1). Again, there was no significant difference in frequency of the PTSD diagnosis between boys (n = 11) and girls (n = 4) in general (Fisher’s Exact Test: p = .230).
The additional feature of shame about what happened was fulfilled (i.e., coded yes) by only 13 children (21.3%) of the whole sample with no significant difference according to location of the interview or gender. Guilt over acts of commission or omission was reported by 10 (16.4%), survivor guilt by 5 (8.2%), and reduction of awareness of the surrounding, derealization and depersonalisation each only by 3 children and adolescents (4.9%). There have been no significant differences between boys and girls or between those interviewed in the reception centre and those interviewed in the IDP camps (see also Table 4 and Table 5). PTSD onset among those who received a diagnosis (24.6% out of 61 children and adolescents) was delayed (i.e., referring to the symptom onset the worst event was more than three month ago) in 5 cases (8.2%) and not delayed in 10 cases (16.4%). In the reception centre 35 cases (87.5%) received no PTSD diagnosis, 4 (10.0%) displayed PTSD without delayed onset, 1 (2.5%) displayed PTSD with delayed onset (PTSD point prevalence 12.5%).
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In the IDP camps, in contrast, 11 (52.4%) did not fulfil the PTSD criteria in a way to receive a diagnosis, 6 (28.6%) displayed PTSD without delayed onset, 4 (19.0%) displayed PTSD with delayed onset (PTSD point prevalence 47.6%). Furthermore, 24 boys (68.6%) had no PTSD, 7 (20.0%) had a PTSD without delayed onset, 4 (11.4%) with delayed onset. Similarly, 22 girls (84.6%) had no PTSD, 3 (11.5%) displayed PTSD without delayed onset and 1 (3.8%) with delayed onset. There was no significant difference when considering only the diagnosed cases regarding PTSD onset (delayed vs. non-delayed) between reception centre and IDP camps (Fisher’s Exact Test: p = .600) as well as between boys and girls (Fisher’s Exact Test: p = 1.00; see also Table 4 and Table 5).
Table 4 CAPS diagnosis and CAPS sum scores for criteria B (intrusions), C (avoidance), D (hyperarousal) and/or associated (PTSD-related) features in dependence on interview location (GUSCO reception centre (RC) vs. Internally Displaced People (IDP) camps) Variable CAPS PTSD diagnosis: n (%) Yes No CAPS sum score (B, C, D): M (SD) CAPS associated features (yes): n (%) Guilt over acts of commission/omission Survivor guilt Reduction of awareness of the surrounding Derealization Depersonalization Shame PTSD onset if diagnosed (n=15): n (%) Without delay Delayed
GUSCO RC (n = 40)
5 (12.5) 35 (87.5) 28.9 (17.7) 5 3 1 1 2 7
(12.5) (7.5) (2.5) (2.5) (5.0) (17.5)
4 (80.0) 1 (20.0)
IDP camps (n = 21)
10 (47.6) 11 (52.4) 42.8 (27.2) 5 2 2 2 1 6
(23.8) (9.5) (9.5) (9.5) (4.8) (28.6)
6 (60.0) 4 (40.0)
* significance level ≤ .05 (two-tailed) ** asymptotic F-statistic (Welch-Test due to heterogeneity of variances)
Statistic
p*
Fisher’s Exact
.004
F=7.44**
.011
Fisher’s Exact Fisher’s Exact Fisher’s Exact Fisher’s Exact Fisher’s Exact Fisher’s Exact Fisher’s Exact
.291 1.00 .270 .270 1.00 .341 .600
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Table 5 CAPS diagnosis and CAPS sum scores for criteria B (intrusions), C (avoidance), D (hyperarousal) and/or associated (PTSD-related) features in dependence gender Variable CAPS PTSD diagnosis: n (%) Yes No CAPS sum score (B, C, D): M (SD) CAPS associated features (yes): n (%) Guilt over acts of commission/omission Survivor guilt Reduction of awareness of the surrounding Derealization Depersonalization Shame PTSD onset if diagnosed (n=15): n (%) Without delay Delayed
male (n = 35)
female (n = 26)
Statistic
p*
Fisher’s Exact .230 11 (31.4) 24 (68.6) 36.4 (26.7) 7 4 3 3 2 8
(20.0) (11.4) (8.6) (8.6) (5.7) (22.9)
7 (63.6) 4 (36.4)
4 (15.4) 22 (84.6) 23.8 (13.9) 3 1 0 0 1 5
(11.5) (3.8) (0.0) (0.0) (3.8) (19.2)
F=5.67**
.021
Fisher’s Exact Fisher’s Exact Fisher’s Exact Fisher’s Exact Fisher’s Exact Fisher’s Exact Fisher’s Exact
.494 .382 .254 .254 1.00 1.00 1.00
3 (75.0) 1 (25.0)
* significance level ≤ .05 (two-tailed) ** asymptotic F-statistic (Welch-Test due to heterogeneity of variances)
For the CAPS score (of the criteria B, C and D) Pearson correlations with several demographic variables have been considered. Significant correlations could be found with age (r = .257; p = .046), total number of meals per day (r = -.333; p = .009; due to regular meals in the reception centre: M = 3.2, but not in the IDP camps: M = 2.0) and total number of family members who died in the civil war (r = .322; p = .011). Age differed significantly between reception centre (M = 15.2; SD = 2.5) and IDP camps (M = 16.8; SD = 2.3; F = 5.92; p = .018). When analysing associations between the CAPS score and age for reception centre and IDP camps separately, significance of the Pearson correlation could not be replicated (reception centre r = .266; p = .098; IDP camps r = .034; p = .885). Similarly, when analysing associations between the CAPS score and the number of meals per day separately for cases in the reception centre and cases in the IDP camps, significance of the Pearson correlation disappeared (reception centre r = .078; p = .633; IDP camps r = -.233; p = .309). Correlation with frequency of displacement (r = .249; p = .052) and abduction (r = -.160; p = .219), total number of family members who disappeared (r = .142; p = .274) or have also been abducted during the conflict of Northern Uganda (r = .000; p = .997), total number of medical conditions during the past four weeks (r = .151; p = .245) and age at the point of the worst event (M = 13.4; SD = 1.9; r = .033; p = .807) did not reach significance. Similarly, the CAPS score did not correlate significantly with the time already spent in the reception centre (first time; r = .136; p = .402) or the time already living in the IDP camp after GUSCO (r = .283; p
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= .214) at the time of the interview. This time span has been analysed separately for both interview locations since it refers to different periods of life for the children and adolescents in the reception centre (time in the centre) and those already living in an IDP camp (time past since leaving the centre). CAPS diagnosis (yes/no) does not correlate with the level of education (Kendall’s Tau-b = .215; p = .082). As expected, Pearson correlations of the CAPS score and the total number of event (normally distributed) reached high significance (r = .482; p = .000). When considering the different event types in sense of experienced versus witnessed (most events could be coded as experienced or witnessed or both if there were more than one such event), the CAPS score correlated significantly positive with both total number of experienced events (normally distributed; .501; p = .000) and total number of witnessed events (normally distributed; r = .390; p = .002). When considering the different event types according to the event list separation (see Attachment E) the CAPS score correlated significantly with the total number of events of the CAPS event list (events 1-15; normally distributed; r = .362; p = .004) and the total number of LRA-perpetrator events (events 23-28; only codable as experienced; normally distributed; r = .488; p = .000) but not with the total number of events related to domestic violence (events 17-18; not normally distributed; r = .215; p = .096). Pearson correlation of the CAPS score with the total number LRA-specific events (events 19-22; not normally distributed) was marginally significant (r = .284; p = .054). When considering Pearson correlations between the CAPS score and the total number of events as well as the total number of perpetrator events for both interview locations separately (due to 5.0 events in total and 1.6 LRA-perpetrator events more in the IDP camps than in the reception centre; see Table 2), higher correlations could be revealed in the IDP camps than in the reception centre. The CAPS score and the total number of events correlated with r = .363 (p = .021) in the receptions centre compared to r = .481 (p = .027) in the IDP camps. Likewise, The CAPS score and the total number of LRA-perpetrator events correlated with r = .316 (p = .047) in the receptions centre compared to r = .464 (p = .034) in the IDP camps. Accordingly, the total number of witnessed events played no significant role in the IDP camps (notice that perpetrator events, which seem to be most important, could only be coded as experienced) The events of the CAPS event list seemed to play no important role at all for the CAPS score when analysed separately for each interview location. The results are summarized in Table 6.
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Table 6 Pearson correlations of the CAPS score and the total number of events and the event types Correlations of the CAPS score with: Total no. of events Total no. of experienced events Total no. of witnessed events Total no. of events of the CAPS event list Total no. of events related to domestic violence Total no. of LRA-specific events Total no. of LRA-perpetrator events (only experienced)
N = 61 .482 (.000) .501 (.000) .390 (.002) .362 (.004) .215 (.096) .248 (.054) .488 (.000)
Pearson r (p*) Reception centre (n = 40)
IDP camps (n = 21)
.363 (.021) .362 (.022) .316 (.047) .259 (.107) .265 (.099) .275 (.085) .314 (.047)
.481 (.027) .514 (.017) .279 (.220) .249 (.276) .265 (.246) .095 (.681) .464 (.034)
* significance level ≤ .05 (two-tailed)
The total number of events highly inter-correlated with the total abduction duration (not normally distributed; r = .391; p = .002; N = 61). Furthermore, some but not all event types highly inter-correlated with total abduction duration, too: total number experienced events (r = .381; p = .002), total number of witnessed events (r = .349; p = .006) and total number of events of the CAPS event list (r = .342; p = .007). However, this inter-correlation was not significant for the total number of events related to domestic violence (r = .212; p = .102), the total number LRA-specific events (r = .183; p = .159) and the total number of LRAperpetrator events (r = .223; p = .085) with one exception: When considering only cases of the reception centre, total abduction duration correlated significantly with the total number of LRA-perpetrator events (r = .382; p = .015 vs. r = .337; p = .135 in the IDP subsample). Finally, the total abduction duration did not correlate with the CAPS score (r = -.083; p = .774) independent of interview location. In a linear regression on the CAPS score with the total number of events as potential predictor (building block effect) R² reached .23 (Beta = .482; p = .000; N = 61; see also Fig. 2).
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Furthermore, the building block effect has been investigated for the different event types. Firstly, the total numbers of experienced versus witnessed events have been considered. Both event types were highly inter-correlated (r = .759; p = .000) indicating high co-linearity, so that they could not be considered within one regression analysis. In separate analyses the total number of experienced events (R² = .25; Beta = .501; p = .000; N = 61) proved to be a stronger predictor than the total number of witnessed events (R² = .15; Beta = .390; p = .002; N = 61). Secondly, predictive power of all event types according to the event list separation that proved to correlate significantly with the CAPS score have been considered (see also Table 6). Both, CAPS and LRA-perpetrator events inter-correlated highly significant (r = .605; p = .000; high co-linearity) and, hence, had to be analysed separately. The total number of perpetrator events proved to be the best predictor for the CAPS score when compared to all other event types (R² = .24; Beta = .488; p = .000; N = 61). Notice that perpetrator events could only be coded as committed/experienced. The total number of events of the CAPS event list did not prove to be a sufficient predictor of the CAPS score (R² = .13; Beta = .362; p = .004; N = 61). Since the CAPS score is significantly different when comparing children and adolescents interviewed in the reception centre with those living in IDP camps, linear regression analyses have also been considered separately for each location. The expected building block effect could not be sufficiently verified for the total number of events in the reception centre subsample (R² = .13; Beta = .363; p = .021; n = 40). However, in the IDP camp subsample it could be confirmed (though with still small predictive power: R² = .23; Beta = .481; p = .027; n = 21; see also Fig. 3). Accordingly, the total number of experienced events played a much less important role for the CAPS score in the reception centre (R² = .13; Beta = .362; p = .022) than in the IDP camps (R² = .26; Beta = .514; p = .017). The total number of witnessed events again seemed to have no or only few impact on the CAPS score (reception centre: R² = .10; Beta = .316; p = .047; IDP camps: R² = .08; Beta = .279; p = .220). It is important to mention that the majority of events referred to the time in the LRA and not to other life spans.
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Like in the whole sample, best predictor for the CAPS score proved to be the total number of perpetrator events in both the reception centre (R² = .10; Beta = .316; p = .047; n = 40) and the IDP camps (R² = .22; Beta = .464; p = .034; n = 21) when compared to the total number of events of the CAPS events list, the total number of LRA-specific events and the total number of events related to domestic violence. None of the other three event types correlated significantly with the CAPS score when analysed separately for reception centre and IDP camps (see also Table 6). No regression reached significance when considering only cases with a positive PTSD diagnosis according to the CAPS (n = 15). For all regression analyses heteroscedasticity has been tested in a scatter plot of the standardized residua and the estimated (predicted) values of the dependent variable as well as in the Levene Test for homogeneity of variance. Overall, heteroscedasticity proved not to be significant. Auto-correlations have been no problem (analyses of the same diagrams). Normality of the residua could be proven in P-P-diagrams for all of the linear regressions (though with some more deviations in the smaller IDP subsample). The event list further included the separation between “happened in the LRA” and “happened before or after the abduction”. However, this was not sufficiently rated by all interviewers leading to missings or ambivalences. Hence, these data have not been considered within this work.
Results 3.1.2
78 Factorial design and reliability of the Collective Identity Questionnaire
At the beginning of this study a factorial analysis of the items 1-13 of the Collective Identity Questionnaire (see Table 7) was planned in order to verify the expected three-factorial structure (attachment, behavioral involvement and ideology and meaning). However, responses to these items have mainly polarized to either one extreme (0 or 4, with 0 being the majority; see also Fig. 4) reducing the 5-point-Likert-Scale (0 – “I strongly disagree”; 1 – “I disagree”; 2 – neither/nor; 3 – “I agree”; 4 – “I strongly agree”) to a rather dichotomous one. Still another problem was the small sample size (N=61). According to that, a sufficient factorial analysis was not possible. Explorative factorial analysis using SPSS 12.0 (standard version) produced with factors (according to the Kaiser-criterion extraction of factors with an eigenvalue above 1), which not at all reflected the expected structure of collective identification. Thus, a factorial analysis of items 1-13 will not be considered within this work. Table 7 Items 1-13 of the Collective Identity Questionnaire Item
Description 2
1
I used to have friends in my group in the bush that I miss now.
2
Kony is protected by holy ghosts, which give him supernatural power.
3
I appreciate the skills I learned in my group in the bush.
4
During my time within my group in the bush I always felt like an outsider.
5
When life turns out difficult here, I would prefer to go back in the bush.
6
Some of the LRA’s aims are right for the Acholi.
7
Without wearing Kony’s symbols (bracelet, bottle) I feel unprotected.
8
By leaving the bush I lost a family.
9
I still keep up rituals and norms I learned in the bush.
4
3 2
2
4 4
2 3
10
The children in the bush still fight for the good of all Acholi.
4
11
I never felt emotionally connected to the group in the bush.
2
12
Throughout my time in the bush I resisted to believe in Kony’s rituals and norms.
13
Even now Kony reads my mind from the distance.
2
Attachment Behavioral involvement Meaning/ideology
3 4
4
4
The item statistic (items 1-13) of the Collective Identity Questionnaire is shown in Table 8.
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Table 8 Item statistic 1-13 of the Collective Identity Questionnaire using a 5-point-Likert-Scale (0-4) for N=61 Adjusted total Cronbach’s α if Item M Mode SD Range item correlation item deleted 01 02 03 04 05 06 07 08 09 10 11 12 13
2.5 2.9 .7 1.9 .5 .5 1.0 1.1 .1 .3 1.2 1.3 1.2
4 4 0 0 0 0 0 0 0 0 0 0 0
1.8 1.4 1.3 1.7 1.2 1.1 1.5 1.6 .5 .9 1.6 1.7 1.7
4 4 4 4 4 4 4 4 3 4 4 4 4
.328 .439 .334 .220 .257 .283 .282 .425 .293 .231 .467 .651 .408
.719 .703 .716 .733 .724 .721 .722 .704 .726 .726 .698 .669 .706
Overall reliability of the scale (items 1-13): Cronbach’s α = .730
As one can see in Table 8, items 9 and 10 were very little scattering (even less than all the other items). Furthermore, both items have almost only been answered with 0 (“I strongly disagree”; see also Fig 4), which is an indicator that these two items should be excluded (without affecting the reliability of the whole scale).
Figure 4. Answer patterns for items 1-13 of the Collective Identity Questionnaire (N=61)
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Pearson inter-item correlations are displayed in Table 9 in order to estimate tendencies of factor building. However, this did also not reveal tendencies of the expected factorial design. As one can see, item 1 (“I used to have friends in my group in the bush that I miss now.”) does only inter-correlate with item 3 (“I appreciate the skills that I learned in my group in the bush.”); item 6 (“Some of the LRA’s aims are right for the Acholi.”) even correlated with non of the other items significantly but marginally with item 10 (“The children in the bush still fight for the good of all Acholi.”). Item 4 (“During my time within my group in the bush I always felt like an outsider.”) only correlated with items 11 (“I never felt emotionally connected to the group in the bush.”) and 12 (“Throughout my time in the bush I resisted to believe in Kony’s rituals and norms.”). However, items 11 and 12 correlated significantly with other items, too. There are some more (but weak) correlative tendencies of item relationships according to their wordings: Items 2, 7 and 13 refer to Kony and are in part inter-correlated but they also correlate significantly with other items. Items 3 and 9 refer to skills learned in the bush (daily structure). Both items inter-correlate but not exclusively with each other. Possible explanations for these correlative tendencies are provided in para. 4.1.2. Overall, the collective identity mean score without items 9 and 10 (normally distributed according to the Kolmogorov-Smirnov-Z-Test) reached 1.3 points (SD = .8) with no significant difference when comparing children and adolescents of the reception centre reception centre (M = 1.3; SD = .8) with those interviewed in the IDP camps (M = 1.4; SD = .7; F = .35; p = .557) as well as no significant difference between boys (M = 1.3; SD = .7) and girls (M = 1.3; SD = .9; F = .00; p = .974). Notice that a collective identity mean score of 2 or below indicates that the repliants have not been identified with the LRA. The following results concerning collective identification do only refer to the items 1-8 and 11-13. Nevertheless, the item selectivity (adjusted total item correlation) is not sufficient for most of the items.
Pearson correlation p * (two-tailed)
Pearson correlation p * (two-tailed)
Pearson correlation p * (two-tailed)
Pearson correlation p * (two-tailed)
Pearson correlation p * (two-tailed)
Pearson correlation p * (two-tailed)
Pearson correlation p * (two-tailed)
Pearson correlation p * (two-tailed)
Pearson correlation p * (two-tailed)
Pearson correlation p* (two-tailed)
Pearson correlation p* (two-tailed)
Pearson correlation p* (two-tailed)
Item 2
Item 3
Item 4
Item 5
Item 6
Item 7
Item 8
Item 9
Item 10
Item 11
Item 12
Item 13
* significance level ≤ .05 (two-tailed)
Pearson correlation p* (two-tailed)
Item 1
1.00
Item 1
1.00
.199 .124
Item 2
1.00
.090 .490
.286 .025
Item 3
1.00
.191 .140
.192 .137
.127 .328
Item 4
1.00
-.046 .724
.013 .920
.307 .016
.189 .144
Item 5
1.00
.156 .231
.093 .476
.174 .179
.206 .112
.231 .073
Item 6
Inter-item correlations of items 1-13 of the Collective Identity Questionnaire for N=61
Table 9
1.00
-.138 .291
.050 .703
-.188 .147
.268 .037
.261 .043
.100 .441
Item 7
1.00
.232 .072
.147 .259
.098 .452
.047 .720
.338 .008
.232 .072
.238 .064
Item 8
1.00
.067 .610
.223 .085
.018 .892
.275 .032
.198 .127
.365 .004
-.029 .822
.042 .746
1.00
.302 .018
-.151 .246
.256 .047
.239 .063
.051 .699
.149 .251
-.020 .879
.124 .341
-.034 .793
1.00
.257 .046
.125 .337
.404 .001
.122 .350
.223 .084
.012 .927
.272 .034
.196 .130
.128 .325
.195 .133
1.00
.412 .001
.293 .022
.274 .033
.367 .004
.416 .001
.216 .095
.115 .376
.316 .013
.246 .056
.284 .026
.244 .058
1.00
.451 .000
.289 .024
.108 .407
.008 .951
.256 .046
.181 .162
.121 .352
.437 .000
.057 .660
-.104 .424
.426 .001
.069 .598
Item 9 Item 10 Item 11 Item 12 Item 13
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Abduction duration and strength of collective identification
Total abduction duration (sum score of the first, and possibly second and third abduction) and strength of identification with the LRA or group in the bush (operationalized by the mean score of the Collective Identity Questionnaire items 1-8 and 11-13; see para. 3.1.2) have been correlated using the bivariate Pearson correlation. Notice, that only seven children and adolescents have been abducted more often than once (see also Table 10). Identification with the LRA or group in the bush is assumed to be stronger with increased collective identity mean score. Neither a positive nor a negative correlation could be found when considering only the first abduction duration. However, total abduction duration correlated positive with strength of identification (see Table 11). This correlation was even stronger when considering only cases from the reception centre, but it disappeared in the IDP subsample. Table 10 Descriptive distributions of abduction durations for N=61 st nd 1 abduction 2 abduction Statistic duration duration N M Mode SD Range
61 28.5 12.0 35.1 .00-120.00
6 45.0 36.0 41.8 .27-120.00
rd
3 abduction duration
Total abduction duration
1 36.0
61 33.6 12.0 37.1 .03-120.00
Table 11 Pearson correlations of abduction duration and mean score of the Collective Identity Questionnaire items 1-8 and 11-13 Pearson r (p *) Correlation of the CAPS score with:
Collective identity mean score
N=61
Reception centre (n=40)
IDP camps (n=21)
.371 (.003)
.513 (.001)
.015 (.948)
* significance level ≤ .05 (two-tailed)
A linear regression on the collective identity mean score (without items 9 and 10) as second outcome measure with the total abduction duration as predictor proved to be significant (F = 9.42; p = .003; N = 61) though with low explanatory power (R² = .138; Beta = .371). Separate analyses for the reception centre and IDP camp subsamples proved that the total abduction duration is a good predictor for collective identification in the former (R² = .26) but not at all in the latter subsample (R² = .00). Heteroscedasticity and autocorrelations could not be shown. The residua proved to be normally distributed.
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3.1.4 Number of traumatic events and collective identification
The distribution of the traumatic events is described in para. 2.3 (Table 3) and 3.1.1. An initial Pearson correlation between the total number of events and strength of identification reached significance with r = .346; p = .006 (all data considered without item 9 and 10 of the Collective Identity Questionnaire). However, this was not true for all event types when considering them separately. The collective identity mean score (items 1-13) correlated significantly with the total number experienced events (r = .351; p = .006), the total number of witnessed events (r = .293; p = .022) and the total number of LRA-perpetrator events (r = .405; p = .001) but not with the total number of events of the CAPS event list (r = .220; p = .089), the total number of events related to domestic violence (r = .230; p = .074) and the total number of LRA-specific events (r = .148; p = .255). Due to the high inter-correlation between collective identity score and total abduction duration (r = .371; p = .003) as well as between the total number of events and some but not all of the events types and total abduction duration (with the total number of experienced events, the total number of witnessed events and total number events of the CAPS event list but not with the total number of events related to domestic violence, the total number of LRA-specific events and the total number of LRAperpetrator events; see para. 3.1.1) relevant partial correlations have been considered. Controlling for total abduction duration revealed apparent correlations between the collective identity mean score and the total number of events (r = .236; p = .070), the total number experienced events (r = .244; p = .061) and the total number of witnessed events (r = .188; p = .150). Since the total number of LRA-perpetrator events did not correlated with total abduction duration in the whole sample (N = 61) and the IDP subsample, no apparent correlation could be uncovered. However, in the reception centre the correlation between the total number of LRA-perpetrator events and the collective identity mean score proved to be an apparent one (when controlling for the total abduction duration). Hence, the expected negative correlation between the total number of events or event types and strength of collective identification could not be verified. For all other cases, a positive correlation between the collective identity mean score and the total number of LRA-perpetrator events could be shown. Linear regression has been applied in order to assess the predictive power of the total number of perpetrator events on the collective identity mean as secondary outcome measure. The predictive power has been proved but only with a very small amount of explained variance (R² = .16; Beta = .405; p = .001; N = 61). This effect proved to be stronger when analysed only for the IDP subsample (R² = .34; Beta = .582; p = .006; n = 21), what reflects
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the correlative tendencies. For the reception centre subsample (n = 40) the total number of LRA-perpetrator events did not prove to be a sufficient predictor of the collective identity mean score (R² = .12; Beta = .349; p = .027) although the difference in the total number of LRA-perpetrator events between the two interview locations was only small (1.6; see Table 2). Since only an identity mean score above 2 indicates a clear identification with the LRA or the group in the bush, Pearson correlations for those cases exclusively (n = 12) have also been assessed. However, no significant correlation could be found neither for all cases with collective identity score above 2 (r = .053; p = .871; n = 12) nor for those living in the reception centre (r = .377; p = .358; n = 8) or the IDP camps (r = -.422; p = .578; n = 4) separately. The difference in frequency of collective identity mean scores above 2 versus 2 and below in the reception centre versus in the IDP camps did not prove to be significant (Fisher’s Exact Test: p = 1.00). Heteroscedasticity and autocorrelations could not be shown. The residua proved to be normally distributed.
3.1.5 Collective identity as protective factor for PTSD and comorbid disorders
The average CAPS score for all participants amounted to 31.0 points (SD = 22.9) with no significant difference between boys and girls (U = 339.50; p = .092) but a significant difference between reception centre and IDP camps (F = 9.63; p = .003; higher scores in the IDP camps than in the reception centre; N = 61; see para. 3.1.1). A current depression diagnosis has been given to only three children (2 boys and 1 girls; Fisher’s Exact Test: p = 1.00; 1 from the reception centre and 2 from the IDP camps; Fisher’s Exact Test: p = .270). Hence, average current depression sum score (not normally distributed) reached only .46 points (SD = 1.3) with no significant difference between boys (M = .5; SD = 1.5) and girls (M = .4; SD = 1.1; U = 439.50; p = .700) and between children living in the reception centre (M = .3; SD = 1.0) and those living in an IDP camp (M = .9; SD = 1.8; U = 351.00; p = .074; N = 61). The suicidality sum score (not normally distributed) reached 2.6 points on average (SD = 6.4) with no significant difference between boys (M = 2.7; SD = 5.7) and girls (M = 2.4; SD = 7.3; U = 428.00; p = .611) but with a significant difference between those still living in the reception centre (M = 1.5; SD = 6.0) and those already living in an IDP camp (M = 4.6; SD = 6.8; U = 302.50; p = .021; N = 61).
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When analysing the protective effect of collective identification on PTSD and comorbid disorders within this study, a significant negative correlation between the CAPS score and the collective identity mean score (without items 9 and 10) and, hence, a significant linear regression function with a negative increase (B) have been expected. The same principle was expected for the current depression score and the suicidality sum score. In order to analyse possible associations between the mean score of collective identification (items 1-8 and 11-13 of the Collective Identity Questionnaire) of the children and adolescents with the LRA (or group in the bush) and possible clinical outcomes (PTSD, current depression and suicidality), Pearson correlations have been assessed for the whole sample (N = 61). The results are summarized in Table 12.
Table 12 Pearson correlations of the mean score of the Collective Identity Questionnaire items 1-8 and 11-13 with psychological outcomes Correlations of the collective identity mean score with: CAPS score Current depression score Suicidality sum score
Pearson r (p*) N = 61
RC (n = 40)
IDP (n = 21)
.187 (.148) .198 (.126) .423 (.001)
-.005 (.974) .226 (.098) .423 (.007)
.441 (.045) .120 (.603) .416 (.061)
* significance level ≤ .05 (two-tailed)
When considering the whole sample (N = 61) collective identity did not correlate significantly with the CAPS score (of criteria B, C and D; r = .187; p = .148) and the current depression sum score (r = .198; p = .126). However, it correlated significantly positive with the suicidality sum score (r = .423; p = .001). As a result, the expected negative correlation between the collective identity mean score and psychological outcomes could not be confirmed at all. As a result, a linear regression on the CAPS score with the collective identity mean score as predictor made no sense. A linear regression analysis (contraire to the hypothesis) in order to investigate a possibly predictive effect of collective identification (collective identity mean score without items 9 and 10) on suicidality was not possible since the suicidality sum score was not normally distributed. When considering only cases with an identity mean score (items 1-8 and 11-13) above 2 (which indicates identification with the LRA or group in the bush) there is no significant correlation between collective identity mean score and suicidality sum score anymore (r = .400; p = .197; very small n = 12).
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Since the CAPS and suicidality scores are significantly different in the two interview locations with higher prevalences in the IDP camps, associations between collective identity mean score and measured outcomes have also been considered separately for each location. In the reception centre (n = 40) there was also no significant Pearson correlation between the identity mean score an d the CAPS score (r = -.005; p = .974) or the current depression score (r = .266; p = .098); the correlation between the identity mean score and the suicidality mean score (r = .423; p = .007) stayed significant. In contrast, in the IDP camps (n = 21) the CAPS score correlated significant with the collective identity mean score (r = .441; p = .045) but significance of the correlation between collective identity mean score and the suicidality sum score disappeared (r = .416; p = .061). The correlation between the identity mean score and the current depression score was still non-significant (r = .120; p = .603). When controlling for the total number of perpetrator events (due to high inter-correlation with the CAPS score, see para. 3.1.1 and the collective identity mean score, see para. 3.1.4) in a partial correlation between collective identity mean score and the CAPS score, an apparent correlation was revealed (r = .238; r = .313; n = 21/ IDP camps).
3.1.6 Collective identification and aggression
Collective identity mean score (items 1-8 and 11-13) correlated significantly with the total aggression score (Pearson r = .411; p = .001). When considering the four aggression components, a significant correlation with physical (r = .334; p = .009) and verbal aggression (r = .304; p = .017) and anger (r = .344; p = .007) but not with hostility (r = .193; p = .137) was revealed. Furthermore, the total aggression score correlated significantly with the CAPS score (r = .424; p = .001), the total number of events (r = .438; p = .000), the total number of perpetrator events (r = .411; p = .001) but not with the total abduction duration (r = .130; p = .318). Partial correlation between the total aggression score and the collective identity mean score did not prove to be an apparent correlation when controlling for the total number of perpetrator events (r = .294; p = .023) though they highly inter-correlated with the CAPS score and the collective identity mean score (see para. 3.1.1 and 3.1.4). When considering both interview locations separately, the Pearson correlation between the total aggression score and the collective identity mean score stayed significant with a little stronger association in the IDP camps (r = .484; p = .026) than in the reception centre (r = .370; p = .019). Hence, the expected positive correlation between collective identification with the group in the bush (the
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LRA) and the total aggression score could be verified according to the assumed higher aggression potential in armed rebellious groups.
3.2 Further analyses
3.2.1
The adapted PRISM version
The descriptive characteristics of the six components of the adapted PRISM version (not normally distributed) are displayed in Table 13.
Table13 Distribution of the adapted PRISM components of the Collective Identity Questionnaire item (distance measures in 0-27 cm) Component Kony then Group in the bush then Family then Kony now Group in the bush now Family now
N 60 60 60 61 61 61
M 20.9 13.4 5.4 23.9 18.0 3.9
SE 8.1 8.0 6.1 5.3 8.7 4.5
Min 0.0 0.0 0.0 3.5 0.0 0.0
Max 27.0 27.0 27.0 27.0 27.0 20.5
The distanced laid by the children are significantly different when comparing “Kony then” versus “Kony now” (Wilcoxon Z = -3.757; p = .000), the “group in the bush (LRA) then” versus the “group in the bush (LRA) now” (Wilcoxon Z = -4.702; p = .000) and “family then” versus “family now” (Wilcoxon Z = -2.778; p = .005). Even the components “Kony then” and the “group in the bush (LRA) then” (Wilcoxon Z = -5.356; p = .000) as well as “Kony now” and the “group in the bush (LRA) now” (Wilcoxon Z = -5.021; p = .000) are significantly different, which indicates that both Kony and the group in the bush are strong but distinct aspects of the life in the LRA. This is also true for the “group in the bush (LRA) then” versus the “family then” (Wilcoxon Z = -4.834; p = .000) and the “group in the bush (LRA) now” versus the “family now” (Wilcoxon Z = -6.451; p = .000). These results stay the same when considering both interview locations separately with one exception: “family then” versus “family now” does not reach significance in both the reception centre (Wilcoxon Z = -1.900; p = .057) and the IDP camps (Wilcoxon Z = -1.887; p = .059) at the 95%-confidence level. According to the Mann-Whitney-U-Test there are no significant differences in the categories between reception centre and IDP camps with again one exception: The distance for “family
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then” (U = 271.50; p = .030) and “now” (U = 250.50; p = .008) is significantly longer in the reception centre than in the IDP camps, indication less emotional closeness to the families of cases in the reception centre. Inter-item correlations are displayed in Table 14. As expected the “Kony”-items do highly positive inter-correlate with the “group in the bush” (LRA)-items but both do not correlate with the “family”-items since this category is clearly different from the two former.
Table 14 Pearson inter-correlations of the adapted PRISM components of the Collective Identity Questionnaire item 15 (notice: the longer the distance the less emotional close did the child or adolescent feel) Kony Group Family Kony Group Family (then) (then) (then) (now) (now) (now) 1
Pearson r p*
Group in the 1 bush (then)
Pearson r p*
Kony (then)
Family (then) Kony (now)
1
1.00
Pearson r p*
2
Pearson r p* Group in the Pearson r 2 bush (now) p* Family (now)
* 1 2
2
Pearson r p*
.432 .001
.065 .622
.565 .000
.390 .002
.172 .188
1.00
-.062 .638
.415 .001
.678 .000
.002 .988
1.00
.011 .936
.120 .363
.690 .000
1.00
.518 .000 1.00
-.002 .987 .072 .584 1.00
significance level ≤ .05 (two-tailed) N=60 N=61
Pearson correlations of each of the six items with the collective identity mean score, the total aggression score, the CAPS score (for criteria B, C, and D), the current depression sum score, the suicidality sum score and total number of events are displayed in Table 15. The “Kony”items as well as the “group in the bush” (LRA)-items correlated significantly positive with the collective identity mean score, what indicates that items 1-8 and 11-13 and the adapted PRISM version do measure similar aspects. As expected, the “family”-items did not correlate with the collective identity mean score since these items did not include issues concerning one’s biological family. The category “Kony now” correlated barely significant with the total aggression score (r = -.248; p = .054). However, there are no further correlations of these components with any of the considered outcomes (PTSD, depression, suicidality or aggression) for the whole sample (N = 61). This non-correlatedness was the same in the
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reception centre (n = 40) and IDP camp (n = 21) subsamles, what indicates that this measures cannot replace more detailed collective identity-related items but supplement them. Interestingly, only “family then” and “now” correlated significantly with most of the event types (total number of events, total number of experienced events, total number of witnessed events, total number of events of the CAPS event list, total number of LRA-specific events and total number of perpetrator events but not with the total number of events related to domestic violence).
Table 15 Pearson correlations of the adapted PRISM components of the Collective Identity Questionnaire item 15 and clinical outcomes, collective identification (items 1-8 and 11-13), aggression and event load (notice: the longer the distance the less emotional close did the child or adolescent feel) Identity mean score 1
Total aggression score
CAPS score (B, C, D)
Current Suicidality Total depression sum number of sum score score events
Pearson r p* Pearson r p*
-.538 .000 -.413 .001
-.175 .182 .035 .793
.015 .908 .113 .392
.192 .141 .016 .905
.090 .494 -.115 .383
-.068 .608 -.069 .602
Pearson r p*
.003 .984
-.114 .385
-.163 .215
.038 .776
-.096 .464
-.335 .009
2
Pearson r p*
-.515 .000
-.248 .054
.187 .148
.037 .778
-.136 .297
.022 .866
Group in the 2 bush (now)
Pearson r p*
-.347 .006
-.044 .737
.067 .609
-.025 .849
-.079 .543
-.074 .569
Pearson r p*
-.086 .511
-.105 .423
-.105 .422
-.106 .418
-.085 .514
-.377 .003
Kony (then)
Group in the 1 bush (then) Family (then) Kony (now)
Family (now)
* 1 2
1
2
significance level ≤ .05 (two-tailed) N=60 N=61
3.2.2
Collective Identity Questionnaire item 14
This item ought to explore the evaluation of the time in the bush (in the LRA) by asking the free question: “If you think back now, what was good during your time in the bush? (give examples)”. It resembled a pure qualitative measure and involved the factor “attachment”. The results are summarized in Table 16. The distribution of item 14 (there is nothing good in the bush vs. there is something good in the bush) is not significantly different when comparing cases in the reception centre with those in the IDP camps (Fisher’s Exact Test: p = .405). This is conform to the finding that item 5 of the Collective Identity Questionnaire
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(“When life turns out difficult here, I would prefer to go back in the bush.”) is equally distributed in both interview locations (Fisher’s Exact Test: p = .169; with most of the participants (85.2%) answering “I strongly disagree”).
Table 16 Distribution of the free item 14 of the Collective Identity Questionnaire by gender, interview location (reception centre RC vs. IDP camps) and PTSD diagnosis for N=61 n (%)
Male (n=35)
Female (n=26)
RC (n=40)
IDP (n=21)
PTSD (n=15)
54 (88.5)
32
22
34
20
11
Made good friends there
1 (1.6)
1
0
1
0
0
Some of Kony’s aims, beliefs and rules are good
1 (1.6)
0
1
1
0
0
Sometimes we were free
1 (1.6)
0
1
1
0
1
Taught other children how to become a soldier
1 (1.6)
1
0
0
1
1
Teachings about dressing decently and sticking to one man
1 (1.6)
0
1
1
0
1
There is no HIV/AIDS in the bush
1 (1.6)
1
1
0
1
Thrill of winning and victory after the battle
1 (1.6)
0
1
0
0
Answer There was nothing good in the bush
1
Interestingly, those seven children and adolescents who reported that at least one things was good in the bush showed a higher collective identity mean score (M = 2.2 indicating some identification; SD = .6) and a higher total aggression score (M = 2.7; SD = .8) than the average (collective identity mean score = 1.3; SD = .8; total aggression mean score = 2.2; SD = .8).
3.2.3
Number of events, current depression and suicidality
The current depression score and the suicidality sum score both correlated positively with the total number of events (current depression score: Pearson r = .436; p = .000; suicidality sum score: r = .440; p = .000). Linear regressions analyses, however, have not been possible due to non-normal distribution of both variables according to the Kolmogorov-Smirnov-Z-Test.
Results 3.2.4
91 Aggression, psychological outcomes and event load
Another factor worthy to consider is the total aggression score since it inter-correlated significantly with the CAPS score (r = .424; p = .001), the current depression sum score (r = .302; p = .018), the suicidality sum score (r = .494; p = .000) and the collective identity mean score (see para. 3.1.6). In the reception centre (n = 40) the correlation between the total aggression score and the CAPS score disappeared (r = .180; p = .267); Pearson correlations between the total aggression score and the current depression score as well as the suicidality sum score stayed significant (see Table 17). In contrast, in the IDP camps (n = 21) the total aggression score correlated highly significant with the CAPS score (r = .627; p = .002) and the suicidality sum score (r = .644; p = .002). The correlation with the current depression score disappeared.
Table 17 Pearson correlations of the total aggression score and psychological outcomes Pearson r (p*)
Correlations of the total aggression score with: CAPS score Current depression score Suicidality sum score
N = 61
RC (n = 40)
IDP (n = 21)
.424 (.001) .302 (.018) .494 (.000)
.180 (.267) .359 (.023) .358 (.023)
.627 (.002) .190 (.410) .644 (.002)
* significance level ≤ .05 (two-tailed)
The total aggression score further correlated significantly with each of the event types except with the total number of LRA-specific events (threatened to be killed; giving birth to a child in the bush; forced to abandon a child in the bush; forced to eat human flesh; all items could be coded as experienced and/or witnessed). However, when considering these correlations separately for each interview location this pattern totally changed. The events of the CAPS event list were no longer associated with the aggression score. Furthermore, in the reception centre the total number of experienced and of witnessed events seemed to be similarly associated. In the IDP camps only the total number of experienced events (but not the total number of LRA-perpetrator events) correlated significantly with the total aggression score (see Table 18). However, the average total aggression score was not significantly different when comparing cases of the reception centre (M = 2.1; SD = .7) and cases of the IDP camps (M = 2.5; SD = .8; F = 3.44; p = .069).
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Table 18 Pearson correlations of the total aggression score and the total number of events, event types and total abduction duration Pearson r (p*)
Correlations of the total aggression score with: Total no. of events Total no. of experienced events Total no. of witnessed events Total no. of events of the CAPS event list Total no. of events related to domestic violence Total no. of LRA-specific events Total no. of perpetrator events (only experienced) Total abduction duration * significance level ≤ .05 (two-tailed)
N = 61
RC (n = 40)
IDP (n = 21)
.438 (.000) .475 (.000) .330 (.000) .320 (.012) .281 (.028) .227 (.079) .411 (.001) .130 (.318)
.383 (.015) .377 (.017) .339 (.032) .243 (.131) .305 (.056) .257 (.110) .251 (.026) .215 (.183)
.405 (.069) .547 (.010) .060 (.797) .277 (.225) .301 (.185) .026 (.912) .344 (.127) .096 (.678)
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4.
Discussion
4.1
Hypotheses
4.1.1
PTSD (CAPS) and the building block effect
The main differences concerning the PTSD symptom score (CAPS score of criteria B, C, D) or in the number of PTSD diagnoses referred to the two different interview locations (GUSCO reception centre vs. IDP camps) with more PTSD symptoms and a higher PTSD point prevalence in the IDP camps (47.6%) than in the reception centre (12.5%). One exception was criterion D (hyperarousal), but one must consider that all of the interviewed children and adolescents lived in a war-torn area. Accordingly, all participants might already have had an increased baseline arousal. In cases of PTSD some hyperarousel more was just put on top (notice that there was a significant difference in the hyperarousal score of the CAPS between cases with and those without a PTSD diagnosis; see para. 3.1.1). Regarding the associated features (in the CAPS), there was no significant difference between reception centre and IDP camps and no gender difference. Significant gender differences could be found in the CAPS score with boys showing higher scores than girls but not in the frequency of PTSD diagnoses. This effect is amazing since 14 girls (53.8% of the girls) have been raped/”given as wife” (see highest PTSD prevalences following rape in epidemiological studies in general Western populations e.g., Kessler et al., 1995; para. 1.2.2). Furthermore, children and adolescents interviewed in the IDP camps had experienced significantly more potentially traumatic events in total (5.9 events more) as well as significantly more LRAperpetrator events (1.6 events more) than those interviewed in the reception centre – a fact, that might have confounded the difference in PTSD sum score and the number of PTSD diagnoses. However, Pearson correlations between the CAPS score and event load stayed significant when considered separately for each location (reception centre and IDP camps). Yet, the amazing difference in PTSD point prevalence of 12.5% in the reception centre and 47.6% in the IDP camps cannot only be explained by the difference in the number of traumatic events (see the low amounts of explained variance in the regression analyses of the total number of events and the total number of perpetrator events on the CAPS score in para. 3.1.1). Other important factors might have become activated within the communities (IDP camps) that have influenced post-traumatic symptomatology (e.g., moral reflection with the
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community functioning as mirror, evaluations of their acts by others than LRA-members, moral development of the child with increasing age and post hoc reflection of the own behaviour – but these are all only assumptions, the real factors are not yet known). Another problem of the data is the missing significant difference in the PTSD onset when comparing children and adolescents still living in the reception centre with those who had already went back into their communities (IDP camps). But notice, like with information about age, PTSD onset time frames should be considered with caution since most of the children and adolescents had problems estimating time spans. The expected building block effect could be replicated for the total number of events when considering the whole sample (N = 61) though with weak predictive power (R² = .23). This indicates that with an increasing number of traumatic events the PTSD symptom score also increases. However, other factors must also play a role. In line with Laufer et al.’s (1984, see para. 1.2.4) conclusion that different trauma event types lead to post-traumatic stress reactions of different magnitude, assessed event types that correlated significantly with the CAPS score have also been analysed separately in terms of the building block effect. When comparing experienced versus witnessed events in linear regression analyses (each reported event had to be categorized as experienced or witnessed in the event list, see Appendix E), the total number of experienced events proved to be a more sufficient and more important factor explaining CAPS score variance (R² = .25) than the total number of witnessed events (R² = .15) indicating that the latter barely predicts the development of PTSD symptoms. This effect reflects some of the earlier studies in the general Western population (e.g., Kessler et al., 1995; Creamer, Burgess, & McFarlane, 2001, see para. 1.2.2) but contrasts other studies on the African continent (Karunakara et al., 2004). However, one should keep in mind that ‘experienced’ traumatic events also included ‘committed violence against others’ (perpetrator events) within this particular population. Since the role of perpetrator experiences is not yet sufficiently understood, results of this study cannot be interpreted in relation to other populations with 100% accuracy. When analysing the predictive power of each event type according to the event list separation (see Appendix E) that correlated significantly with the CAPS score (the total number of LRAperpetrator events and the total number of events of the CAPS event list), the total number of LRA-perpetrator events proved to be the only significant and sufficient predictor (R² = .24 vs. .13 for the events of the CAPS event list). This indicates, the more violence one has committed against others the more PTSD-related symptoms can be expected. It also means that PTSD symptomatology is not a cumulative function of all potentially traumatic events (or
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event types) within this particular sample of former Ugandan child soldiers (see also Laufer et al., 1984 for similar results; para. 1.2.4). Instead, perpetrator event types are most salient or dominate over others. Several studies showed that witnessing abusive violence and enormous cruelty was of especially high traumatic valence (proven in wars in Vietnam and Kuwait, para. 1.2.4; Nader, Pynoos, Fairbank, Al Ajeel, & Al Asfour, 1993 and Hiley-Young, Blake, Abueg, Rozynko, & Gusman, 1995). Furthermore, this effect was reported to be stronger among Blacks when compared to white people (e.g. Laufer et al., 1984). However, the impact of participation in abusive violence against others is not yet completely clear. Laufer et al (1984), for example, demonstrated that in black Vietnam veterans participation in abusive violence caused more psychological distress and aggression that witnessing abusive violence against others (which would support the findings of this study). However, in white Vietnam veterans it was the other way round. But independent of race, those who had participated in abusive violence against others reported more neutral emotions connected to the act and perceived the event as less traumatic. This was sometimes but not consistently the impression during the interviews and might be considered in future assessments. Separate analyses for both interview locations revealed further important insights. Total event load was a better predictor for the CAPS score in the IDP camps (R² = .23) than in the reception centre (R² = .13). The total number of witnessed events had almost no important influence on the CAPS score in both interview locations. The total number of experienced events, however, was a predictor in the IDP subsample but had only little impact on PTSD symptomatology in the reception centre. When analysing the event types according to the event list separation, the events of the CAPS event list did not correlate significantly with the CAPS score anymore. A linear regression could only be considered for the total number of perpetrator events, which again revealed higher predictive power for the cases in the IDP camps (R² = .22) than for cases in the reception centre (R² = .10) and reflected initial correlative tendencies (see para. 3.1.1; Table 6). In the reception centre subsample the explained variance was small overall. Hence, other factors might have also played a role. What could be shown so far is that in the reception centre (i.e., shortly after the abduction) neither the perpetrator event load nor the total event load predicted PTSD symptomatology sufficiently. However, in the IDP camps (i.e., 1.6 years later) predictive power was much stronger. In the receptions centre this effect might still have been suppressed since the interviewed former abductees mainly interacted with other former abductees. Furthermore, GUSCO social workers did not talk about and did not evaluate what happened in the bush (i.e., in the reception centre there was no or only little moral reflection). Since this study only
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cross-sectionally assessed potentially traumatic events and PTSD symptoms within both subsamples, this difference cannot be explained by a delay of symptom onset, yet, but it is a possibility. Support for this assumption stems from Laufer et al.’s (1984) study with Vietnam veterans that revealed a cumulative development of post-traumatic stress symptoms with time (see para. 1.2.4). A longitudinal assessment that also tests this assumption is currently running using the same sample (see Ertl et al., 2007, in prep.). There might be an association between participation in violence (i.e., being a perpetrator) and delayed onset of post-traumatic symptoms: According to the reports of the children and adolescents, they have been threatened to be killed if they did not conform. Hence, most of them committed violence against others in order to survive and blamed LRA leaders for what they had to do (only 16.4% reported to feel guilty for what they did; see para. 3.1.1). In the reception centre, children and adolescents have been encouraged to forget anything that happened during the abduction and to look ahead. When returning into the communities, however, they might learn that all or most actions of the LRA and its members (including those of the abducted children) are evaluated as extremely negative and brutal. They might start reasoning and clash with earlier beliefs with the result of perceived psychological distress (see cognitive dissonance theory in para. 4.4). The missing correlation between the CAPS score and the total abduction duration as well as between the CAPS score and the age at the worst event replicated the results of Kanagaratnam et al. (2005). The following variables have not been considered as possible predictors for the CAPS score (PTSD symptom score) although Pearson correlations proved to be significant. Firstly, children and adolescents living in the reception centre and those living in the IDP camps differed significantly in age (with those from the IDP camps being 1.6 years older on average). However, age was not included as one possible predictor for the CAPS score since the correlations were not significant anymore when calculated separately for the reception centre and the IDP camps. The age difference is logical to explain: Those participants already living in an IDP camp have been interviewed approximately two years later in their lives (two years after GUSCO) than those still living in the GUSCO reception centre. Secondly, the total number of meals per day also differed significantly between children in the reception centre and those in the IDP camps (with 1.2 meals more in the reception centre). But notice that the reception centre was led by the local organization GUSCO, which tries to support the wellbeing and reintegration of former abducted children and adolescents into their communities. Accordingly, in the reception centre the children are supplied with three regular meals. In contrast, those who had already gone back to their families in the IDP camps relied on food
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97
rations or had no support at all. Thus the differences are due to differences in the socioeconomic living conditions of the respective interview location. The initially significant correlation between the CAPS score and the total number of meals per day disappeared when calculated separately for both interview locations (see para. 3.1.1). As a result, total number of meals per day has not been considered as one possible predictor of the CAPS score. Thirdly, the total number of family members who died in the civil war has not been analysed separately since their deaths should have been assessed as potentially traumatic events by the events list (see Appendix E) provided that the affected child has witnessed or directly taken part in the act of murder. The applied instruments did not include items concerning possible traumatic grief. Accordingly, conclusions about associations between loss and PTSD symptoms could not be drawn from the present data.
Summary The building block effect could not be verified sufficiently for both interview locations (reception centre and IDP camps) when analysed separately. The total number of events predicted the CAPS score (PTSD symptom score) better in the IDP camps (R² = .23) then in the reception centre (R² = .13). Among the assessed event types (see Appendix E), the LRAperpetrator events seemed to have the greatest influence on the development of PTSD symptoms, especially in the IDP camps. In the reception centre, traumatic events seemed to be little associated with trauma-related symptomatology. All related regression analyses proved to be significant. However, in the reception centre subsample these linear regressions did not provide enough explanation of the CAPS score variance (only 10-13%). A delayed onset or increased development of PTSD symptoms after reintegration into the communities (IDP camps) could be expected provided that emotions and cognitions that are related to their traumatic life experiences, especially to their perpetrator events during the time in the LRA, were still suppressed in the reception centre. Overall, the amounts of explained variance of the dependent variable (PTSD score according to the CAPS) were rather small indicating an unsatisfactory fit between the regression model and the assessed data. Other factors that have not yet been considered and are not yet known might have played a role.
Discussion 4.1.2
98 Factorial design and reliability of the Collective Identity Questionnaire
A sufficient factorial analysis of items 1-13 could not be conducted due to the polarized answer patterns (either 0 or 4) and the resulting dichotomous character of the data. The small sample size did not allow a latent class analyses, too. The expected three-factorial structure (attachment, behavioural involvement, ideology and meaning) or respective tendencies could not be replicated neither in an explorative factorial approach nor when analysing the interitem correlations of items 1-13 of the Collective Identity Questionnaire. Items that were supposed to relate to a particular latent factor were mixed up. There were some hints for associations according to wording and identity aspect between items 1 and 8 (friends and family substitute), between items 3 and 9 (skills and daily structure), items 2, 7 and 13 (Kony), items 6 and 10 (LRA policy/ideology) and between items 4, 11 and 12 (inner resistance). However, since these items also correlated with other items than those mentionioned, the interpretation of the correlation pattern was not unequivocally possible (see also Table 9). Analysis of answer distributions of each of the 13 items showed that items 9 and 10 were least scattering. As a result, these two items have been excluded from all following data analyses. Furthermore, items 1 and 6 showed outstanding patterns of inter-correlation with the rest of the items: Item 1 (“I used to have friends in my group in the bush that I miss now.”) only correlated with item 3 (“I appreciate the skills that I learned in my group in the bush.”). This may indicate that the children and adolescents evaluated the group and the life in the bush separately from being a member of the LRA. For the assessment of LRA-related collective identity a clearer distinctions between the group in the bush and the LRA itself may by needed. Item 6 (“Some of the LRA’s aims are right for the Acholi.”) correlated with none of the other items significantly, which may be due to its political character as the marginal significant correlation with item 10 (“The children in the bush still fight for the good of all Acholi.”) indicates. None of the other items referred to ideological statements that were closely related to the LRA’s policy. The item statistic revealed an acceptable reliability of the questionnaire. However, the item selectivity proved not to be sufficient indicating revision of factorial design and item formulation. The identification with the LRA (or group in the bush) was assumed to be stronger with increasing collective identity mean score (of items 1-8, 11-13). But on average, there was no identification of the whole sample at all (M = 1.3; SD = .8). There was no significant difference between children and adolescents interviewed in the reception centre and those
Discussion
99
interviewed in the IDP camps as well as no significant difference between boys and girls (see para. 3.1.2). Several reasons might have played a role: Firstly, it may be true that the children and adolescents did not really identify with the LRA. Instead they just did what they were supposed to do in order to survive (most of them had reported that they had been threatened to be killed if they did not conform; see para. 4.5 for role-conflicts; see also Biedermann, 2007, in prep.). Secondly, LRA-specific collective identity might not have been assessed sufficiently. As already mentioned, the items of the Collective Identity Questionnaire (1-13) include both, items that related more to the group (of other abductees) in the bush and items that clearly related to the LRA as rebel movement with its mystic background. The expected factors (attachment, behavioural involvement, ideology and meaning) could not be found indicating that these items did not refer to one single but to several collective identities (e.g., the group of abductees; the political component of the LRA, Kony and the mystic component of the LRA; the group of LRA members that dominated the daily structure of the child or adolescent). It is possible that the participants identified with plural collective (or social) identities but not necessarily with all of them (Deaux, 2000; see para. 1.3.7). Instead, they might have built an identity or salience hierarchy (Stryker, 1968) depending on the context and social frame of reference (see also para. 1.3.3 and 1.3.4). Coming to the point, the Collective Identity Questionnaire may not be adequate to clearly measure collective identification with the LRA. Instead, it possibly mixes several identity types leading to imprecise and invalid conclusions about either one collective identification (see also para. 4.4).
4.1.3
Abduction duration and strength of collective identification
Neither a positive nor a negative correlation could be confirmed when considering only the first abduction duration. However, the total abduction duration (additive score of the first and possibly second and third abduction duration) correlated positively with strength of identification (operationalized by the collective identity mean score of items 1-8 and 11-13) when considering the whole sample or the reception centre subsample. This may just be due to the fact that the second or third abductions had been longer than the first. However, those interviewed in the IDP camps showed no association at all between abduction duration and strength of collective identification.
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100
The positive correlation in the reception centre goes conform to several models of collective identity development (e.g., Cross, 1971, 1991; see also para. 1.5). It might indicate that former Ugandan child soldiers develop a stronger LRA-related collective identity with time of abduction (or enduring salience of the respective identity). This association may be still activated and, hence, measurable during the time in the GUSCO centre. In contrast, the lack (or possible decrease) of such an association within the IDP camp subsample resembles in part the findings of Kanagaratnam et al. (2005). They reported less strong identification (ideological commitment) of former Tamil child soldiers with the rebellious group after experiences of especially intense exposure (which they operationalized with relatively long abduction duration and being involved as perpetrator; see also para. 1.6). However, within the present data set the total number of perpetrator events correlated significantly with both, the collective identity mean score (r = .405; p = .001; see para. 3.1.4) and the PTSD symptom score (r = .488; p = .000; see para. 3.1.1), but only in the reception centre subsample it correlated with the total abduction duration (r = .382; p = .015; see para. 3.1.1). Accordingly, the results of both studies are somewhat contradicting. One reason might be the difference in the samples itself and its contexts, for example the exile status (see also para. 4.4 for Tamil vs. Ugandan child soldiers). Within this sample, perpetrator events might function as kind of initiation rites or demonstrations of the LRA’s rules of behaviour (most forced beatings and killings have happen right at the beginning; see Biedermann, 2007, in prep.). As a result, they might, at least in part, promote collective identification with the LRA (see para. 4.1.4). However, this association or its measurability might decrease over time after returning into another (a community- or family-based) social context (notice that both, Kanagaratnam et al.’s (2005) sample as well as the IDP subsample of this study had already returned to ‘normal’ life for quite some time and both showed no association between abduction duration and strength of collective identification). Finally, the missing correlation of total abduction duration and number of perpetrator events (for the whole sample and the IDP subsample) might further indicate that an increase in duration of exposure does not necessarily mean ongoing increase in intense of exposure within this population i.e., exposure or event severity might even decline over time after the child or adolescent has been integrated in the LRA group. Accordingly, the total abduction duration is assumed to play only a minor role after returning into the community and another (moral) context. The whole complexity this issue will be considered in detail within para. 4.4.
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4.1.4 Number of traumatic events and collective identification
The initially significant Pearson correlation between the total number of events and strength of collective identification proved not to be true for all event types when considering them separately. The correlations with the collective identity mean score (without items 9 and 10) were still significant and positive for the total number experienced events, the total number of witnessed events, the total number of perpetrator events but not for the total number of events of the CAPS event list, the total number of events related to domestic violence and the total number of LRA-specific events (with the two latter having almost no effect on all relevant calculations). However, when further controlling for the total abduction duration in a partial correlation of the collective identity mean score and the total number experienced events, the total number of witnessed events and the total number of events of the CAPS event list (due to the significant inter-correlation; see para. 3.1.1), apparent correlations have been revealed for all of these three event types. This indicates that these event types have no relevant implications on collective identification. A more important role seems to play the total number of perpetrator events. In the IDP subsample this event type did not correlate with the total abduction duration and, hence, could not be unmasked as being only apparently correlated with the strength of collective identification with the LRA. However, the opposite was the case in the reception centre. But still this means, that an increase of traumatic events is not (cumulative) associated with stronger collective identification. Instead, in the IDP camps only an increase of perpetrator events related to development of collective identification with the LRA (or the group in the bush). The more violence a child or adolescent committed to others during his or her time in the LRA, the stronger his or her identification with the LRA. A possible reason might be that these events functions like an initiation rite (see Biedermann, 2007, in prep.). A linear regression of the total number of perpetrator events (which could only be coded as experienced; related witnessed events have been acknowledged elsewhere) on the collective identity mean score showed that the former is one (though weak) predictor of the latter (R² = .16; N = 61). This effect proved to be much stronger when analysed only for cases of the IDP camps (R² = .34; n =21) but it shrank in the reception centre subsample (R² = .12; n =40). The impact of the LRA-perpetrator events seems to be delayed. In the reception centre the total abduction duration and its association with collective identification (due to contextual salience of the LRA) seems to be still activated. Over time (after returning into the community), the experiences as perpetrator might gain dominance over the pure time of togetherness in the bush. After returning into the
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community collective identification might also (re-)occur post-hoc. Questions or discussions of family and community members about the cruelty of the LRA’s actions may activate a process of reasoning about what has happened. Former beliefs about right and wrong might clash with current one causing ‘cognitive dissonance’. In order to regain cognitive homeostasis identification with the LRA is aspired (cognitive dissonance theory; for further details see para. 4.4). If this was true, collective identification with the LRA is assumed to develop firstly with time of abduction, but after changing social context it is assumed to be established or re-gained only due to experiences as LRA-perpetrator. Results of later followups should be considered (see Ertl et al., 2007, in prep.). On average, identification in the IDP camps was no higher than in the reception centre. This fact could also be interpreted in terms of two different ways of identification instead of identification versus no identification. When considering only cases with a collective identity mean score above 2 (which indicates identification) the collective identity mean score is not significantly correlated with the total number of perpetrator events anymore (what might be, at least in part, due to the very small subsample sizes n = 8 in the reception centre and n = 4 in the IDP camps).
4.1.5 Collective identity as protective factor for PTSD and comorbid disorders
According to the main hypothesis of this work, collective identification is assumed to be a protective factor or buffer of PTSD symptomatology and comorbid disorders (current depression and suicidality). That means, former abducted children and adolescents of Northern Uganda who reported relatively strong identification with the LRA or the group in the bush (i.e., ideally with a collective identity mean score above 2 in the Collective Identity Questionnaire, items 1-8 and 11-13) should show less symptoms related to PTSD and the comorbid disorders. To sum up, PTSD prevalence of the whole sample (N = 61) reached 24.6% with significantly higher rates in the IDP camps (47.6%) than in the GUSCO reception centre (12.5%). Taking into account the average number of traumatic events the children and adolescents went through (22.6 in the IDP camps vs. 17.6 in the reception centre), the latter PTSD rate can be evaluated as being below of what one could expect from other studies (e.g., Karunakara et al., 2004; Neuner et al., 2004; see also para. 1.2.3; Dyregrov et al., 2002; Thabet & Vostanis, 1999; Derluyn et al., 2004; Amone-P’Olak; 2005; see para. 1.2.5). On the other hand, Blattman (2006) received similar results. Accordingly, it is not yet sure what one should
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expect. One possible influencing factor may be the year of abduction and release since during the last years the number of abductions and related brutality declined somewhat (see para. 1.1.1). Those abducted longer ago might have experienced (and committed) even more cruel events. Unfortunately, an exact assessment of time frames proved to be very difficult in general. Current depression diagnoses have been even less likely (4.9%) with no difference between reception centre and IDP camps or boys and girls. Similarly, suicidality was not common (M = 2.6) and involved no gender difference. However, the suicidality score differed significantly according to the respective interview location (reception centre M = 1.5; IDP camps M = 4.6) but only correlated significantly with the PTSD symptom score of those living in the reception centre and not with those in the IDP camps. The collective identity mean score did not correlated significantly with CAPS score and the current depression score. However, it correlated significantly but positively with the suicidality sum score (r = .423; p = .001; N = 61). This correlation might indicate that the probability to become suicidal is higher among those reporting stronger collective identification with the LRA or the group in the bush. In other words, the stronger the collective identification with the LRA, the more suicidality symptoms had been reported. This would indicate that collective identification with the LRA has negative consequences instead of a protective function. However, causal relations cannot be clarified with only crosssectional and correlative data. It may also be that those who feel bad now, think that it was better then (among those children and adolescents reporting that something was good in the bush (item 14 of the Collective Identity Questionnaire) 5 showed no or very few suicidality but 2 reached very high scores; M = 7.6, n = 7). Furthermore, the effect is not consitent. When considering the correlation between collective identity mean score and suicidality sum score separately for cases in the reception centre and cases in the IDP camps it could be revealed that those with higher suicidality (i.e., those in the IDP camps) did not show such an association. This could mean that the children and adolescents in the reception centre had been in a tattered state. In the bush they had a daily structure though the life there was hard and cruel, but in the centre they might not have known what to expect after GUSCO. May-be they feared reactions of the community; they were not sure what their future would be. Reasoning about that might have caused hopelessness in some of them. When considering only relevant cases with a collective identity mean score above 2 (i.e., with at least some collective identification) there was no significant correlation at al, but this might, at least in part, be due to the very small subsample size (n = 12).
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Summary The expected protective impact of (stronger) collective identification on PTSD, depression and suicidality symptoms could not be verified. In contrast, when considering the whole sample (N = 61) or the reception centre subsample separately, collective identification correlated significantly positive with suicidality. However, cases in the IDP camps, who showed significantly higher suicidality scores, displayed no such association. Accordingly, these data should only be interpreted with caution. No assumptions about the direction of the effect are possible.
4.1.6 Collective identification and aggression
One additional assumption of this study was that collective identification with the LRA of a former abducted child or adolescent should positively correlate with his or her aggression level since the rebellious movement in Northern Uganda involves enormous brutality that lasts since almost two decades (see also para. 1.1.1). In line with this assumption, the collective identity mean score (of the items 1-8 and 11-13) correlated significantly positive with the total aggression score (above all, with physical and verbal aggression and anger). This correlation was stable (non-apparent). Hence, the expected positive correlation between collective identification with the LRA or the group in the bush and the total aggression score could be verified and goes conform to the evidently higher aggression potential in armed rebellious groups. However, causal effects cannot be defined. Collective identification with the rebellious group (LRA) might lead to higher aggression potential. On the other hand, it could also be possible that those with higher initial aggression potential are more likely to seek a more aggressive collective identity. Post-hoc assessment is not possible.
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4.2 Further analyses
4.2.1
The adapted PRISM version
The significant differences in distances between the self and the three categories (“Kony”, “group in the bush” and “family”) for the times of reference (“then” vs. “now”) indicate that the children and adolescents have understood the concept of different points in time and have expressed that something has chanced in their perceived emotional closeness to each of the categories. The fact that the category “family” was also significantly different when comparing “then” and “now” (for cases in the reception centre and in the IDP camps separately the difference were very marginal significant with p = .057 for the former and p = .059 for the latter location), however, could either mean that they really felt less close to their family members since the perceived similarity was lessened due to their acts and roles in the LRA, which in turn activated the rebel identity more than the identity as a part of their biological family (see also para. 1.3.4 about identity salience and para. 1.4.3 about contextdependency of collective identities) or that the children and adolescents misinterpreted the concept of emotional closeness as physical closeness (or real distance in space). But the latter is not very probable since the distances for the “group in the bush” was “then” (i.e., when they had stayed with them) significantly more than twice as high as for their families (though they were far away). However, those living in the IDP camps felt closer to their families than those still living in the reception centre. But this might be explainable when taking into account that those in the reception centre still had only few interactions with their families. The categories “Kony” and the “group in the bush” inter-correlated significantly with each other but both were uncorrelated with the “family”. Further, the significant differences between the distances “Kony then/now” and “group in the bush then/now” show that for the children and adolescents Kony and the group in the bush are strong but distinct aspects of life in the LRA, which are clearly separated from their home families. The items 1-13 of the Collective Identity Questionnaire correlated significantly negative with the categories “Kony” and the “group in the bush” but not at all with “family” (notice that the smaller the distance the more emotional close did the child feel and the higher the collective identification with Kony or the group in the bush). This is a further hint that the collective identification items (1-13) related to separate possible identities in the bush. Hence, the adapted version of the PRISM gave further indications for the rather weak validity of the Collective Identity Questionnaire. For future investigations “Kony” and “the group in the
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bush” should not be mixed up within one scale. Possible adaptations might be splitting the questionnaire into two scales or deciding either for the more mystic (Kony-related) aspects or for aspects that are more related to daily structure and policies within the rebel group. It could also be useful to add “the LRA” as additional category in the adapted version of the PRISM in order to detect further possible distinctions between the group in the bush, the LRA and Kony in order to get the rebel identity concept of the LRA clearer. Furthermore, the category “Kony now” correlated barely significant with the total aggression score (r = -.248; p = .054). This might mean, the closer the child feels to Kony now, the more aggression can be revealed (may-be due to rebel identification). The effect could be supported by the high inter-correlation of the collective identity mean score and the total aggression score. However, no more significant correlations of the six categories with psychological outcomes could be shown, neither with the total aggression score, nor with PTSD, current depression and suicidality. As a result, the adapted PRISM version is not a better measure than the Collective Identity Questionnaire (items 1-8 and 11-13 though these items also need to be revised). But it could be considered if a less abstract scaling than that of the Likert-Scale may by easier to apply within the special population of former Ugandan child soldiers since it can be assumed that the hard time in the LRA delays the cognitive development of a child (as it was the impression of the interviewer). Finally, the categories “family then” and “now” (but none of the others) correlated significantly negative with the total number of events and each event type except with domestic violence. This means, the more potentially traumatic events he or she had experienced or witnessed, the closer the child or adolescent felt to his or her family during the abduction and now provided that the family climate was not violent. This effect might indicate that the seeking or wishing for shelter and support from their families grew with increasing numbers of traumata. This could be a hint for decreasing identification with the LRA with increasing number of events, but not necessarily. According to Deaux (2000; see para. 1.3.7) plural collective (or social) identifications are possible. The results indicate that the latter possibility is more likely within this sample since the total number of perpetrator events also significantly predicted the collective identity mean score (items 1-8, 11-13), especially for children and adolescents who had already returned to their families and/or communities (IDP camps; see para. 3.1.4).
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4.2.2 Collective Identity Questionnaire item 14
As Table 16 shows, the majority (88.5%) of the children and adolescents interviewed in the reception centre and in the IDP camps retrospectively reported that there was nothing good in the bush. And among the six who reported at least one good thing (boys and girls equally distributed and no significant difference between reception centre and IDP camps) there have been four with a PTSD diagnoses. This finding also contradicts the hypothesis of collective identification as a protective factor of PTSD and related disorders. Of course, the answers to this item might have been influenced by opinions of the social workers in the reception centre and/or their communities but most of the children and adolescents (85.2%; no significant difference between reception centre and IDP camps) credibly made clear that they never want to go back in the bush (item 5 of the Collective Identity Questionnaire) and that the most important thing for them is continuing school. However, those reporting that there was something good in the bush showed higher collective identification and aggression than the average. This might indicate that positive aspects of a social group enhance the probability of identification with the respective group (one further way to collective identification with the LRA next to long abduction duration and acts as LRA-perpetrator). As a result of identification with a brutal movement, aggression can be assumed to increase, too. Unfortunately, clear causal relations cannot be reconstructed from cross-sectional data.
4.2.3 Number of events, current depression and suicidality
Both the current depression sum score as well as the suicidality sum score correlated significantly with the total number of events (see para. 3.2.3). Accordingly, one could assume that suicidality and depression increases with increasing number of potentially traumatic events (similar to the building block effect for PTSD). However, directions of the effects or causality cannot be calculated.
Discussion 4.2.4
108 Aggression, psychological outcomes and event load
Laufer et al. (1984) came to the conclusion that aggression was associated with better psychological well-being provided that the participants had only witnessed abusive violence. On the other hand, when they had actively participated in abusive violence, lower aggression levels and worse psychological well-being was found (see also para. 1.2.4). Within this data set the total aggression score correlated positively with each of the event types (except with LRA-specific events). The total number of experienced events was even stronger related with the total aggression score (r = .475; p = .000) than witnessing events (r = .330; p = .009). However, Laufer et al. (1984) mainly distinguished between “taking part in abusive violence against others” and “witnessing abusive violence against others”. Within this study “experiencing” not only meant being a perpetrator but, above all, also meant being a victim – an important difference that might explain the diverging results. Interestingly, when analysing associations between the total aggression score and event types separately for both interview locations, the correlation patterns differed enormously. In the reception centre experienced, witnessed and committed (perpetrator) events played a role for aggression indication more unspecific causes. In the IDP camps, however, only the total number of experienced events correlated significantly with aggression. The total number of witnessed and the total number of LRA-perpetrator events had no impact at aggression anymore. Furthermore, in the IDP subsample but not in the reception centre the total aggression score was highly positive correlated with the CAPS score (PTSD symptom load; r = .627; p = .002). This might indicate that aggression can derive from two different directions – as symptom and consequence of PTSD and as part or consequence of collective identification with the LRA (see also para. 4.4; Fig. 5). But again, causal relation cannot be determined from cross-sectional data.
Discussion 4.3
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Critical discussion of the method
Since this was only a cross-sectional (epidemiological) study several shortcomings have to be considered. Firstly, a cross-sectional design allows no conclusions about the causality of effects. Instead it gives only information about possible associations between measured variables. A longitudinal design would allow drawing conclusion about causality, however, testing Ugandan children and adolescents before and after the abduction (i.e., allowing a brutal exploitation of them to happen) is ethical not defensible. Another problem are the data themselves. Although only assessed by expert clinicians, most data subjective and rely on retrospective questioning (the last month; during the time in the bush, etc.). In order to gain more objective data further reports by external sources would have been necessary. However, an exploration of the social worker’s and the nurse’s knowledge about the symptomatology of the children proved to be too restricted on common parlance. In the IDP camps the capacities of the team concerning interviewers and time was very restricted so that there was no time to talk to parents or grandparents additionally. So, problems associated with self-reports (especially concerning a biased information selection and forgetfulness of the interviewee) might have confounded the data: Participants may exaggerate their reports. This could be an issue especially in the IDP camps since there living conditions were much worse than those of the children and adolescents still living in the reception centre. Although the informed consent (verbally explained) included the information that there will be no reward for taking part in the interview, some may have hoped for financial or other support when exaggerating their state. On the other hand, since in the reception centre the children have been told not to talk about what happened in the bush in their daily interactions and not to think back, it could be assumed that they rather tended to understatement and omission (especially of perpetrator events) than to exaggeration. This was also the impression during the interviews from time to time. A further factor influencing the reliability of interviews with directly affected persons is possible embarrassment (shame of what happened or lack of confidence in the interviewer) of the interviewee. Shame about was happened was one of the associated features in the CAPS and it was reported by 13 children and adolescents (21.3%) with no significant difference between those living in the reception centre and those living in the IDP camps. So it might have had some effect. Furthermore, in the reception centre there has been some suspicion especially at the beginning of the study due to the original policy of the centre that pointed on forgetting and negative consequences associated with talking freely about what had happened in the LRA (some even believed that they would die if they revealed). Cognitive limitations
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and inattention of the participants are best controlled when using short instruments and/or external resources for confirmation. The former could not be realized since we wanted gain exhausting information as good as possible and the obstructions of the latter have already been considered within this paragraph. In order to control for possible acquiescence three items (items 4, 11 and 12) have been reversed coded. However, it is not quiet sure if all participants really understood what was meant (since even the interpreters had initial problems translating them). As one can see in Table 9 these three items highly inter-correlated (though items 11 and 12 also correlated with other items) but this may also be due to the fact that exactly these three items also referred to one special construct namely “inner resistance” (see also para. 2.4.6). This is one of the main problems of the Collective Identity Questionnaire and should be revised in further studies.
4.4
Discussion of the LRA-related collective identity concept and its associations with event load, PTSD symptomatology and aggression
Overall, the validity of the Collective Identity Questionnaire is doubtful. Remember, for example, that all the results rely on a collective identity mean score (items 1-8 and 11-13) of 1.3 on average with no significant difference between children and adolescents interviewed in the GUSCO reception centre and those already living in the IDP camps (see para. 3.1.2). This indicates that collective identification with the LRA (or the group in the bush) is low or not at all there in general or inadequately measured (a collective identity mean score of 2 is absolutely neutral (neither/nor); cases with an mean score below 2 have not been identified with the collective identity in question). Many factors might have influenced the assessment of LRA-related collective identification. Some of them will be considered within this paragraph: As already mentioned in para. 4.1.2, the goodness of the Collective Identity Questionnaire (items 1-13) is not sufficient. The assumed three-factorial design could not be verified. The item selectivity is unsatisfactory and a possibly negative effect of the reversed coding (items 4, 11, 12) on the comprehensiveness of the respective items is not to except. Furthermore, although the expected factors of the Collective Identity Questionnaire relied on Ashmore et al.’s (2004) multidimensional framework of collective identification (see para. 1.4), item formulations had been completely new developed (since there have been no appropriate scales for the measurement of and no sufficient reports about the identity of former Ugandan child
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soldiers by the time of the study). Accordingly, the formulations might have been too general or too much focussing on aspects that also belonged to other types social identification (e.g., political orientation, religion, African tradition belief systems, community structure) causing the questionnaire to be invalid and unspecific for the proposed LRA-specific collective identity concept. On the one hand, this might have been influenced by varying degrees of salience of multiple possible social or collective identities. An individual’s identity can refer to his or her personality, roles or group memberships (see para. 1.3.1 for role identification; see para. 1.3.2, 1.3.3 and 1.4.1 for personal and social/collective identification). Each of these levels of identification can further comprise several facets and subtypes (e.g., identity as trustful and competitive, as mother and scientist, as woman, Black and Christian; Deaux, 2000; see also para. 1.3.7), which may competing (Stets & Burke, 2000; see also para. 1.3.4) or under certain conditions co-existing (Worchel et al., 2000; see also para. 1.3.7). Which of these identities becomes most salient depends on personal characteristics, experiences and goals (salience hierarchy; Stryker, 1968) as well as on the surrounding situation and context (frame of reference). This also means that which type of personal, role and/or collective identity is most salient and important for the respective individual, changes with time and surrounding conditions. This assumption is supported by most contemporary adaptations of identity theories and models (see para. 1.3 and 1.4) and may refer to one of the key factors influencing the results of this study. Although the diagnostic interview included several questions about events (demographic interview; event list) and life (Collective Identity Questionnaire) in the LRA (in the bush) these memories might not have been enough to activate the related collective identity. In the reception centre most children and adolescents had found new friends or at least companions who had made similar experiences in the bush. It seemed that they had built a group of former abductees of the GUSCO reception centre – an identity, which might have overwritten an identity that was activated during the abduction. Furthermore, children whose communities were not too far away from the reception centre used to be visited by relatives, what may have activated still another and contrasting (familyand community-based) identity. Similarly, in the IDP camps former abducted children and adolescents resume a daily life in their family and community, they continue school and are confronted with the community’s evaluation of the LRA’s brutality; some even formed theatre groups with other former abductees. Accordingly, it might be very difficult to assess (or re-activate) a particular type of identity when the surrounding contexts have drastically changed.
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Verkuyten (2005) further considered “identity” and “identification” to be two inter-related but distinct concepts (pp. 63-67). The latter is proposed to “… establish the link between the individual and the group. As soon as people identify with their group, that group becomes the basis of thinking, feeling and acting.” (p. 64). It is further defined as psychological process (cognitive and affective in nature), which may be intentional or unintentional but depends upon “personal characteristics, preferences, needs, experiences, and circumstances” (p. 64). The term identity refers more to the category or group itself (e.g., to a particular ethny), which can be accepted or rejected. Every identity is further associated with certain interpretation and expectations that need to be fulfilled satisfactorily by the identity-occupant. Identification (e.g., with a film star due to admiration) cannot cause the respective individual to hold a particular social identity or categorization (e.g., American celebrity). Instead, an identity needs to be verified and evaluated by significant others. However, identification can be the basis of the development of shared activities and understanding. Similarly, though an individual obviously refers to a particular identity (e.g., Black skin; LRA due to abduction and life in the bush) he or she does not necessarily choose to identify with the respective group and ideology. The latter might also be true for former Ugandan child soldiers. In contrast to Tamil child soldiers of Sri Lanka (see e.g., Somasundaram, 2002; para. 1.2.5), Ugandan child soldiers have mostly been abducted against their will. Additionally, the Tamil rebellion is directed against a more obvious suppression of the Tamil minority by the Sri Lankese government. Kanagaratnam et al. (2005, p. 518) described child soldiers as “a highly heterogeneous group, differing vastly in their experiences depending on the context of war and on the unique characteristics of the culture to which they belong”. These factors are assumed to have influence on how they “remember, relate to and interpret their past as child rebels”. So, results concerning child soldiers should always be interpreted in light of the respective socio-cultural context the child soldiers live in. In the Tamil culture suffering is thought to strengthen the sufferer’s moral power. Self-enhancement and self-seeking is less accepted than serving, sacrificing, and tolerating (Wadley, 1980, as cited in Kanagaratnam et al., 2005, p. 518). The Hindu religion further lessens moral responsibility of the individual by emphasizing the role of context. However, the Northern Ugandan civil war (though bound to certain ethnic groups) grew out of more mystic-religious consideration of few individuals and, hence, is not comparably associated with patriotism, heroism and other advances. Furthermore, Somasundaram (1998; as cited in Kanagaratnam, 2005, p. 518) reported that young Tamil fighters soon lost their initial dedication and altruism being disillusioned by recognizing that they had also been involved in ideology-divergent acts (e.g., killings of other
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Tamils/other ingroup members like it was often reported by the former Ugandan child soldiers; see also Biedermann, 2007, in prep.). Accordingly, one could assume that Ugandan child soldiers do not deeply identify with the LRA’s ideology but enact their roles in order to survive. What is more, most participants of this study reported forced perpetrator actions that had been directed toward civilians or even towards their own family members, what is related with lessened identification with the respective group (Kanagaratnam et al., 2005; see para. 1.6). Thus, the fact of being defined as LRA-member without identification with the LRA (i.e., no LRA-specific identification assessable) should not lead to (psychological) protection against trauma-related disorders since the individual is missing the conviction of LRA ideology-conform explanations of what happened to him or her and of what he or she did to other people. This assumption is supported by the results of the IDP subsample. The development of those interviewed in the reception centre needs to be followed up after their return in the communities (which is done in the subsequent longitudinal study of Ertl et al., 2007, in prep.). The idea of delayed PTSD onset in former Ugandan child soldiers after return into their communities can be supplemented by aspects of the cognitive dissonance theory (Festinger, 1978). Cognitive dissonance refers to incompatible cognitions (opinions, attitudes, desires or intentions, which depend on individual life experiences) that create an inner conflict, which is preferred to reduce. This happens most often when individual decisions have been uncovered as being wrong by relevant others (e.g., negative evaluations of LRA-related actions by the family or community). However, the individual will only change his or her opinions and attitudes when the individual level of tolerance is exceeded (e.g., when the pressure of the community to conform to the other’s evaluations of their actions has become too strong). If this is not the case, the individual will actively engage in avoidance, selective perception of congruent information and re-interpretation of diverging information in order to make it fit the present belief system (e.g., about not being guilty but having been forced). The policy of the GUSCO reception centre emphasizing forgetting and not talking about reinforces the avoidance of information that might contradict the former abductees’ LRA-related beliefs. In contrast, in the IDP camps trauma-related symptomatology may increase due to confrontation (e.g., by seeing others cry about their losses during the civil war) although cognitive harmony is achieved by adapting the related belief system. But this theory can also be interpreted the other way round: Those suffering the most during their time in the LRA (as victim and as perpetrator) will develop fewer symptoms due to post-hoc identification (in order to regain harmonious cognitions) with the LRA’s ideology after reintegration and moral confrontation.
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However, no such negative correlations between total event load and the CAPS score could be found in the IDP sample. But a highly positive correlation between the total number of perpetrator events and collective identification (identity mean score of item 1-8 and 11-13 of the Collective Identity Questionnaire; see para. 3.1.5 and 4.1.5) could be verified. These results are contradicting. The number of perpetrator events influences PTSD symptoms as well as collective identification with the LRA or group in the bush. However, the two latter are not related. This might indicate that there are two ways of influence of LRA-perpetrator events. Firstly, it led to stronger collective identification and aggression; secondly it promoted PTSD symptomatology (including aggression). As one can see in Figure 5 further distinctions according to the two interview locations can be drawn. In the reception centre collective identification with the LRA (or the group in the bush) was mainly (positively) associated with the total abduction duration. May-be, the fact of being still together with former abducted children and adolescents kept the social identity of the abduction time (may it be the LRA or the group of abductees) active. Aggression was mainly correlated with this identification. In the IDP camps, when confronted with another social context, however, collective identification with the LRA (or the group in the bush) was mainly (positively) associated with the total number of LRA-perpetrator events. Here another distinguishing factor might be the event load that additionally came on top of the number of perpetrator events. That means, the more traumatic events (as victim) are experienced additionally, the higher the probability of PTSD symptomatology (or the higher the probability that collective identification is not enhanced instead). This idea might be supported by the fact that collective identity did not correlate significantly with the total number of events (when controlled for the total abduction duration). Furthermore, in the IDP camps PTSD symptomatology was significantly higher than in the reception centre (see para. 3.1.1) and was influenced by both, the perpetrator and the total event load. In the reception centre PTSD was rarely associated. Additionally, CAPS scores of the IDP subsample were highly correlated with aggression indicating two ways of aggression development – one following collective identification with an aggressive group; another following PTSD or as PTSD symptom. Accordingly, there are multiple factors influencing collective identity and psychological states of former Ugandan child soldiers. Surely, there may be many that have not been considered within this study. As a result, the present data cannot offer an exhausting model of the consequences of child soldiering, but Figure 5 is supposed to give some insights. Notice, that this figure purely relies on correlative associations (see para. 3.1.1; 3.1.3-3.1.6; 3.2.4). Conclusions about causal relations cannot sufficiently be drawn from a cross-sectional study.
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reception centre IDP camps no correlation apparent correlation significant correlation
Aggression (total score)
LRA-abduction duration (total)
Total number of events (LRA and elsewhere)
Total number of LRA-perpetrator events
Collective identification with the LRA (group in the bush)
PTSD symptomatology (CAPS score of criteria B, C, D)
Aggression (total score)
Aggression (total score) 2 ways of aggression development
Figure 5. The role of LRA-perpetrator events for collective identification, PTSD symptom score and aggression level
Discussion
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4.5 Excurse perpetrator research after World War II
In Harald Welzer’s (2005) book “Täter – Wie aus ganz normalen Menschen Massenmörder werden [Perpetrators – How normal people become mass killers]“ he discusses perpetrator definitions and research after World War II. In the course of the trials of Nuremberg Douglas Kelley (responsible forensic psychologist) conducted several psychological investigations regarding personality deviances (psychopathy) of leaders of the National Socialistic Regime (among those, Joseph Goebbels, Rudolf Hess, and Hermann Göring) using the RorschachTest, psychiatric observations, graphology, intelligence and personality tests. The aim was to look for common and highly disgusting personality structures among NS-leaders. According to the findings one has to conclude that such people are neither psychological ill nor unique. Instead, such people might be found in every other country outside of Germany everywhere in the world (Welzer, p. 9). Sadistic or psychiatric deviant personalities could be found in only 5-10% of all examined cases (e.g., Ilse Koch, Erich Koch, and Amon Göth), which is not particularly high but comparable with the amount of perpetrators in the general population under contemporary conditions (USA/Western societies: 0.5-2.5% prevalence of paranoid personality disorder, 1-3% antisocial personality disorder, 7.5% schizoid personality disorder; see Kaplan, Sadock, Grebb, & Grebb, 1994; as cited in Welzer, 2005, p. 11, 270). But in contrast to the victims of the National Socialism (NS), the perpetrators seemed not to suffer significantly from sleeping problems, depression and anxiety (Welzer, 2005, p. 13). Accordingly, Welzer (2005, p. 13) concluded that perpetrators could be distinguished from victims by their unfractured and continuous perception of their own person and the total and lasting lack of understanding of what they have done. That means, they perceive their own person as victim of the historical context, acting in sense of duty, even when these acts contradicted their own sense of humanity (as it is described by Heinrich Himmler and Rudolf Höß; as cited in Welzer, 2005, p. 23). They are not able to relate their personality (identity) to their own actions. They show no break within their life history as well as no feelings of insecurity about their future. Hannah Arendt (1996; as cited in Welzer, 2005, pp. 13-14) similarly concluded that perpetrators are able to return to normality by interpreting their behaviour within particular frames of reference and separating it from the own identity. Individual decisions are not only influenced by personal characteristic, experiences, attitudes and competencies but also by the social situation or context (Welzer, 2005, pp. 15-16). As a result, readiness for sadistic behaviour can also be found in normal, non-hostile people (as one could see in the Milgram experiments, Milgram, 1965, 1974; and the Stanford prison
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experiment of the Stanford University, see Haney, Banks, & Zimbardo, 1973). Furthermore, actions of the ingroup against an inferior or hostile outgroup raises the probability of loyalty, conformity and obedience of individual ingroup members since the negative evaluation of the respective outgroup is perceived as ‘normal’ (Elias & Scotson, 1990; as cited in Welzer, 2005, p. 115). Welzer (2005) added that the existence of ethic belief does not exclude its violation (p. 117). Within this context, Welzer (2005) introduced several concepts that should explain why NS-perpetrators were able to go on with almost no psychological consequences. Firstly, he referred to a group-related morality of the National Socialism (which he also called objective anti-Semitism). This type of morality obligates the individual to act in terms of public welfare beyond his or her interests and existence (pp. 36-37). Public welfare is hypothesized to be dependent on epoch- and society-specific i.e., content and ambit (exclusion of certain outgroups) are variable. For NS-perpetrators killing (against own convictions) was normative integrated into morality (and reputability) leading to a defiant definitions of right and wrong (the normative frame of reference) according to the superordinate welfare. Individual inhibitions, needs and emotions have to stay behind the execution of the historic mission. Another concept Welzer (2005) refers to as possible explanation for the NS-perpetrators’ symptomlessness is the so-called role conflict (a distance between acting and being; Goffman, 1973, pp- 260-279; as cited in Welzer, 2005, pp. 38-39). A role-conflict exists when the possible self (or personal identity) that is implied by the respective role (not the role itself) is denied and, accordingly, the self-perception of the individual does not fit his or her role. This depersonalization is assumed to enable personal stringency and professional behaviour (e.g., as surgeon, teacher or police officer). If the role expectancies (see also para. 1.3.1) contradict an individual’s convictions it is proposed that he or she dissociates from his or her role-identity. As a result, the individual (or the perpetrator) perceives himself or herself as ‘normal’ since he or she only did what was expected (from his or her role). This was also reported by Rudolf Höß (as cited in Welzer, 2005, p. 40) in terms of self conquest and hardness following social demands for inhumanity. Hence, role-distance is thought to balance social norms (shoulds) and individual needs (wantings). Overall, morality is defined as variable and dependent on social frames of reference. Thus, without morality (defining murder as normal) there are no mass killings (Welzer, 2005, p. 40/212). As an example, Welzer (2005, pp. 229-230) refers to the genocide in Rwanda during the 1990s. There an artificial ethnic differentiation between the Tutsi and the Hutu tribe was transformed into a perceived deathly enmity (or „accusation in a mirror“ with the terrorist party accusing the terror-affected one, Des Forges, 2002, as cited in Welzer, 2005, p. 229). Temporary, a new
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reality has been created, which defined the killing of the Tutsi by the Hutu as existentially necessary. Welzer (2005, pp.42-48) comes to the conclusion that the concept of a perpetrator personality (psychopathy) is insufficient since no uniform (social or psychological) profile could be drawn after the Second World War. Instead, the social interpretation of and attributions to the killing situation by the perpetrator are central aspects. Situation-specific behaviour cannot be generalized to the entire personality. Ambivalent thoughts, feelings and behaviours can exist parallel. The role of the social context for these processes is defined by history and culture and can manifest in terms of power, violence, ideology, technology and affect (with all these possibilities creating different social frame of reference). Perpetrators suffer from almost no psychological symptom related to their extremely brutal acts (p. 218) because they have acted within the contemporary frame of reference. They perceived themselves as a victim of that time without questioning if this perception was right (or if there have also been consideration concerning their own career, for example). There were no feelings of guilt but the conviction that they had acted against their own will. When the context changes (after some time) perpetrators often re-interpret their actions in terms of the “new” morality – an effect Welzer (2005, p. 41) referred to as cynicism. Hence (although I do not want to compare the children and adolescents of this study with NS-perpetrators), Welzer’s perspective fits at least in part the assumption of context-dependency with varying activations of (social) identities as it is assumed by current adaptations of social identity and self-categorization theories and collective identity models (see para. 1.3 and 1.4). For example, guilt over acts of commission or omission was reported by only 16.4% of the children with a higher percentage in the IDP camps in tendency (but not significantly; see para. 3.1.1) – may-be due to changed morality concept and moral reflection and/or development in the community (internalization of and identification with social norms is reached until late adolescence or early adulthood; see Kohlberg, 1996). Similarly, Summerfield (1998; as cited in Kanagaratnam et al., 2005, p. 518) emphasized that social contexts of war and meanings ascribed to war events by involved people has impact on the perception of war event-related experiences as traumatic or not traumatic. Furthermore, Welzer’s (2005) work can be seen as additional indicator of the difficulty of collective identity assessment when time went on and life returned to ‘normality’ or when role-distance has occurred. Meaningfulness of experiences within one particular context may even change when confronted with an ideology-conflicting reality, for example, after reintegration into the community or after going into exile (“social memory”; Summerfield, 1998; as cited in Kanagaratnam et al., 2005, p. 518). This may be the result of
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reflection of one’s past and new value formation. But this process can be long and, in part, cause moral conflicts (see West, 2000). However, the lasting symptomlessness of NS-perpetrators as it was reported during the trials of Nuremberg contradicts the high PTSD prevalence rates found in the IDP camps. The fact that the perpetrator events of the examined former Ugandan child soldiers have mainly been directed against no clear outgroup but against other abducted children (who rather represented ingroup members of the LRA or group in the bush then an hostile outgroup) and/or their family members (see Biedermann, 2007, in prep.) as well as their stage of moral development may distinguish them from the classic NS-concentration camp leader or warden (who had a concrete picture of the enemy of the general public – the Jews). This may also be indicated by the fact that the perpetrator events within their time in the LRA proved to be the strongest predictor for PTSD symptomatology within both subsamples (reception centre and IDP camps; see para. 3.1.1). A more detailed overview over the history of perpetrator research after the Second World War and descriptions of related perpetrator studies can be found in Paul’s (2003) book “Die Täter der Shoah. Fanatische Nationalsozialisten oder ganz normale Deutsche? [The Shoah’s perpetrator. Fanatic national-socialists or normal Germans?]“.
4.6
General strengths and weaknesses of the study
This study involved further general problems: Firstly, the sample is quiet small (which was the central problem of the data analysis, especially when considering both interview locations separately with 40 participants in the GUSCO reception centre but only 21 in the IDP camps). Furthermore, both groups (according to the interview location) differ significantly (i.e., the group is heterogeneous) regarding some but in part important characteristics, above all age, the total number of events and the total number of perpetrator events. Accordingly, it is possible that the received group differences in some of the outcome measures, above all the CAPS score for PTSD and the PTSD point prevalence (diagnoses according to the CAPS, see also para. 2.4.3), are at least in part based on different baselines. Another reason for the significant differences in the some of the outcome measure may be due to the fact that those interviewed in the IDP camps have been preselected by the GUSCO social workers and the IDP camp leaders (i.e., have not been randomly selected for the study). Especially the camp leaders may have chosen to demonstrate more extreme cases with the desire of raising
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awareness and more financial support for their respective camp. As a result, it might be that the IDP sample is not representative for all former abducted children and adolescents who have already left GUSCO and went back to their communities. Instead it might represent only the upper range of symptomatology. Similarly, since those living in the IDP camps were worse off (regarding their living conditions) than those still living in the reception centre, there might be a greater bias in the IDP sample for exaggeration of symptoms. Finally, all interviews had to be done with the help of a local interpreter (from Acholi language into English), which may have cause an information loss due to translation problems (e.g., there have been problems differentiating anger from shame in the Acholi language). Additionally, one should keep in mind that the age range of the study included children as well as young adolescents. Only adult versions of the clinical instruments have been applied although obviously the cognitive development of the children was not comparable to Western standards (what seems intelligible when considering the life histories). What is more, the adequacy of the whole PTSD concept as well as the PTSD criteria for children according to DSM-IV (APA, 1994) and ICD-10 (WHO, 1992), especially concerning the three minimum avoidance criteria, is not sufficiently examined. However, despite the many shortcomings this study also has its strengths: First of all, the CAPS is known as the “gold standard” of clinician-guided PTSD assessment. It follows the stricter criteria of the DSM-IV (APA, 1994) and hence has a high level of selectivity. All interviews have been conducted by experts. And there was no indication for culture-based deviances from the PTSD concept. Secondly, this study aimed to represent a pilot study for a subsequent longitudinal study with former Ugandan child soldiers concerning PTSD therapy and reintegration of former abductees. Thus, many possibly influencing variables could be explored for exhaustive description and more precise selection. Furthermore, the additional interviews with children and adolescents who had already been one step further in their lives (i.e., who had already went back to their communities) than those in the reception centre revealed important insights into the life after GUSCO and related symptomatology development though these interviews have been highly capacity-consuming (initially, it had been desired to take also a look on other groups for comparison like the night-commuters and those living outside in the refugee/IDP camps but it could not be planed and fixed from Germany). As a result, parts of the longitudinal study could already be adapted and started within this study.
Discussion 4.7
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Summary and implications of the study
This study gave important insights into the relatively unknown population of former Ugandan child soldiers. Not all hypotheses could be verified but interesting effects could be found additionally. The expected building block effect (meaning the more traumatic events, the higher the probability to develop PTSD symptomatology) could be replicated but the statistical power was only sufficient in the IDP camp subsample. Similar tendencies could be found when analysing the predictive value of for the total event load on the current depression and suicidality scores – effects, which need to be further explored. The enormous differences in PTSD prevalence between the two interview locations (12.5% in the reception centre and 47.6% in the IDP camps), however, cannot be sufficiently explained, yet. Several assumption have been discussed within this work. A current longitudinal study using the same sample is expected to give some more insights (see Ertl et al., 2007, in prep.). A positive correlation between abduction duration and collective identification could be verified for the reception centre subsample. The role of the perpetrator events, in which the children and adolescents had participated, was not without ambiguity. They seemed to play a key role that is not yet completely understood since, on the one hand, perpetrator events proved to be strongest predictor for PTSD symptomatology (especially in the IDP camps) and, on the other hand, they also seem to predict collective identification although this was not correlated with PTSD. Furthermore, collective identification correlated significantly with aggression. Hence, as expected one could assume that identification with a potentially aggressive group increases the probability to become also aggressive – a further tendency that needs to be followed up though it will not be possible (and ethnical to justify) to explore causal directions. The total aggression score also highly correlated with the CAPS score (especially in the IDP camps). Since aggression is also a symptom of PTSD (hyperarousal), this effect should also be followed up in a longitudinal study. Collective identification proved not to be a protective factor for PTSD, depression and suicidality. Due to the ambiguousness of the concept its role for the well-being of former Ugandan child soldiers cannot be sufficiently explained. Overall, development and application of the Collective Identity Questionnaire were not satisfactory. The concept needs to be re-considered keeping in mind the plural influencing factors (above all, context dependency, salience and activation, identity vs. identification). Factorial design as well as item formulations should be re-worked and a sharper distinction between ‘Kony’, the ‘LRA’ and ‘the group in the bush’ or decision for either one focus can be recommended. The adapted PRISM version proved to be a good
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supplement. It also indicated that ‘Kony’ and ‘the group in the bus’ are related but distinct aspects of an LRA membership. The LRA itself could be added as fourth category in order to analyse possible relatedness or distinctiveness of the ‘LRA’, ‘Kony’ and/or ‘the group in the bush’. Again, all these aspects may be associated with related but distinct forms of collective identification following abduction by the LRA and, hence, should be considered more clearly or even separately in order to assess their effects on psychological well-being. What has been shown by now with the present set of instruments is that there was no or only little identification of the examined former Ugandan child soldiers with the LRA or the group in the bush. This may be due to a change in time and/or social frame of reference or context. Even if they had shared the LRA’s ideology during their time in the bush, it might not measurable anymore after returning into ‘normal’ life in the reception centre or the community. However, their former experiences and beliefs might have mad them more vulnerable to become fighters again if the situation in Northern Uganda re-deteriorates (see Somasundaram, 2002 for push and pull factors for becoming a child soldier, para. 1.2.5; or Blattmann, 2007 for reasons for child recruitment, para. 1.1). On the other hand, it could also be true that most of them did really not identify with the LRA and just did what authority persons wanted them to do in order to survive (remember, 88.5% of all participants reported that there was nothing good in the bush, at all). To get this clearer, identity instruments should be adapted, as it has already been recommended. Overall, this study proved to give important clues for future projects concerning the assessment of collective identification, factors influencing collective identification and psychological well-being that is related to abduction and misuse as child soldier, and possible tendencies of psychological development after returning into the preceding state of life. A provisional model has been supplied (see Figur 5). The additional subsample of children and adolescents who had already left the GUSCO reception centre and returned to their communities (IDP camps) was an important aspect of the study. This subsample gave hints about what direction of trauma-related symptom development might be expected from the children and adolescents in the reception centre. Further factors like the degree of reintegration into the community and the development of moral reasoning (guilt and shame) that could influence social and personal identifications of the respective children and adolescents should also be considered within the follow-up (see Ertl et al., 2007, in prep. for related results). Of course, an enlargement of the sample would be desirable, especially for data analyses. However, when the aim is to follow up identity-related and psychological developments from the time of return from abduction (i.e., from the reception centre phase) to
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re-integration into community/family life and beyond, then this would be almost impossible since meanwhile only very few children reach the GUSCO reception centre due to (temporary) sedation of the conflict. It is to hope for no more aggravation (although the peace talks between the LRA and Museveni as well as the armistice have already been broken off).
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Appendix
6.
Appendix
Appendix A:
Uganda map
Appendix B:
Elements of collective identity according to Ashmore et al. (2004, Table 1)
Appendix C:
Informed Consent (interview)
Appendix D:
Demographic Interview
Appendix E:
Event List
Appendix F:
Aggression Questionnaire
Appendix G:
Collective Identity Questionnaire
Retrieved January, 30, 2007, from http://www.un.org/Depts/Cartographic/profile/uganda.pdf
AN ORGANIZING FRAMEWORK FOR COLLECTIVE IDENTITY
Table 1 Elements of Collective Identity as Individual-Level Constructs Element Self-categorization Placing self in social category Goodness of fit/perceived similarity/ prototypicality Perceived certainty of self-identification Evaluation Private regard Public regard Importance Explicit importance Implicit importance
Attachment and sense of interdependence Interdependence/mutual fate Attachment/affective commitment Interconnection of self and others Social embeddedness Behavioral involvement Content and meaning Self-attributed characteristics Ideology Narrative Collective identity story Group story
Definition Identifying self as a member of, or categorizing self in terms of, a particular social grouping Categorizing self in terms of a particular social grouping A person’s subjective assessment of the degree to which he or she is a prototypical member of the group The degree of certainty with which a person categorizes self in terms of a particular social grouping The positive or negative attitude that a person has toward the social category in question Favorability judgments made by people about their own identities Favorability judgments that one perceives others, such as the general public, to hold about one’s social category The degree of importance of a particular group membership to the individual’s overall self-concept The individual’s subjective appraisal of the degree to which a collective identity is important to her or his overall sense of self The placement of a particular group membership in the person’s hierarchically organized self-system; the individual is not necessarily consciously aware of the hierarchical position of his or her collective identities The emotional involvement felt with a group (the degree to which the individual feels at one with the group) Perception of the commonalities in the way group members are treated in society A sense of emotional involvement with or affiliative orientation toward the group The degree to which people merge their sense of self and the group The degree to which a particular collective identity is embedded in the person’s everyday ongoing social relationships The degree to which the person engages in actions that directly implicate the collective identity category in question The extent to which traits and dispositions that are associated with a social category are endorsed as self-descriptive by a member of that category Beliefs about a group’s experience, history, and position in society The internally represented story that the person has developed regarding self and the social category in question The individual’s mentally represented narrative of self as a member of a particular social category The individual’s mentally represented narrative of a particular social category of which he or she is a member
Retrieved from Ashmore et al. (2004), Table 1, p. 83
83
Consent Form Interview My name is …. This is … s/he will interpret everything because I don't speak Acholi. I would like to learn more about what has happened to you and your people, what you have experienced and how you feel about it today. The information collected will help to understand how people respond to violent, stressful, or sad experiences they have undergone in the past. By participating in this study you will contribute a lot to my work and I am very grateful for that. Thank you. I would like to ask you to participate in an interview (me plus the interpreter). The discussion will take about two hours. There are no correct answers to the questions I will ask, I am interested in your personal history, your emotions and your points of view, so I ask you to answer each question as honestly as you can. Me and the interpreter will keep all of your responses strictly confidential. It will not be possible to identify you in any way later. The organizations I am working with are GUSCO and vivo, these are organizations that are by no means affiliated with any government or military. Unfortunately there will be no direct benefit for you by participating, yet I hope that the research I do together with these organizations will benefit Uganda by helping to understand what people feel, think and how they cope with what has happened them. If anything is unclear or if you need me to repeat any of the questions as we go, please stop me. Also if you feel uncomfortable at anytime, please stop me and we will go on to the next question. While I see no foreseeable risk to you from participating in this interview, I am aware that Uganda has suffered a great deal and that many have strong opinions and feelings about what has happened. It can be possible that in the course of the interview recollections of experiences you have gone through will be encouraged and may cause personal stress. You will not receive money if you join this study. Your participation is voluntary. You may refuse to answer any question and you may choose to leave the discussion anytime. Refusing to participate will not affect you or your family in any way. Do you have any questions? You may ask questions about this study at any time.
I have read the consent form to the participant and the participant agreed to take part in the study: __________________________ (interpreter's signature)
I agree to take part in this study: __________________________ (participant’s signature)
__________ 1 2 3 4 5 6 7 8
4. How many biological children have you had?
6. Who lives with you in the household?
meals: ____ 4 food aid 5 RC
1 possessing a own house 2 possessing a vegetable garden 3 possessing agricultural land 4 possessing of economic plants 5 animals - sum: __________ a cattle ____ b chicken ____ c goats ____ d ducks ____ e sheep ___ 6 hoes for agriculture: ____ 7 bush knives and axes: ____ 8 pots for cooking and sauce pans: ____ 9 other cooking utensils: ____ 10 water containers and jerry cans: ____ 11 beds: ____ 12 mats: ____ 13 matresses: ____
8. What is the main source of food for you (-r household)? 1 agriculture 2 barter 3 market
9. What are your (household's) possessions?
5. Alive today: ____
father mother spouse brothers, how many: __________ sisters, how many: __________ children, how many: __________ others, how many: __________ lives in reception centre (RC)
7. How many meals did the household (you) have yesterday?
sum:____
1 2 3 4 5
3. Have you ever been married?
single, never married married, to whom? ___________ partner divorced widowed
________________
2. What year were you born?
2 female
1 male
Date Location of interview Interpreter
1. Sex of the respondent
Personal/Family:
Interviewer
Code Name participant
Demographic Interview
1 2 3 4 5
1 Yes 1 home 3 school
18. Have you ever been abducted? 19. From where have you been abducted? (several answers possible)
2 garden/field work 4 on the way to _________
2 No
__________ 1st year: __________ last year: __________
17. How many times did that happen and when?
2 No
Acholi Atesot Langi mixed, specify: __________ other, specify: __________
1 Yes
1 2 3 4 5
16. Have you ever been displaced from home?
Displacement/Abduction:
15. What is your birth ethnicity?
2 No
2 No
2 No
1 no school 2 some primary school (P1-P6, but not P7) 3 completed primary school (completed P7) 4 vocational school (craft certificate, …) 5 some secondary school (S1-S3, but not S4) 6 completed secondary school or "O" level 7 completed advance level or "A" level 8 some university (started, not completed) 9 completed university or higher
1 Yes
13. Do you attend traditional rituals? 14. What is your education?
1 Yes
12. Do you pray regularly?
1 Yes
Christian Islam African Tradition None other, specify: __________
11. Do you go to the mosque/church/religious meetings regularly?
10. What is your religion?
14 sheets and blankets: ___ 15 chairs: ____ 16 tables: ____ 17 stools: ____ 18 books: ____ 19 radio: ____ 20 television: ____ 21 bicycles: ____ 22 motorbikes: ____ 23 vehicles: ____
1 Yes, how many? ____ 2 No
25. Did any family member disappear during the conflict? (code only first grade! also how many siblings abducted)
1 2 3 4 5
never once or twice several times often is not allowed
3 diarrhoea 6 fever/shivering 9 skin rush/scabies
1 2 3 4 5
never once or twice several times often was not allowed
29. When you stayed in the bush/with the LRA, how many times…?
2 malaria 5 flue 8 pain 11 HIV (tested)
28. How many times did you consume alcohol during the last month?
1 cough 4 stomach pain 7 tuberculosis 10 headache
27. I would like you to think back over the last month and tell me, if you have been suffering from any of the following problems:
26. Do you have any chronic disease, medical condition or injury? 1 Yes 2 No If yes, specify: _________________________________________________
Health:
1 Yes, how many? ____ 2 No
24. Did any family member die in the conflict with the LRA?
5 6 7 8
was forced by the government was afraid of the LRA property was destroyed neighbours and clan moved there/ family is already there was released from captivity could escape from captivity was rescued/freed from captivity other, specify: __________
_____________________
22. How long do you live now in this camp? (…in this reception centre?
23. Why did you decide to move to the IDP-camp? 1 and: How did you reach the reception centre? 2 3 4
1 Yes 2 No If Yes, which position/rank? __________
21. Have you been with the LRA?
duration __________ __________ __________
__________ 1st - year: __________ 2nd - year: __________ 3rd - year: __________
20. How many times did that happen and when?
Waragi, how many glasses per week? ___ Beer, how many bottles per week? ___
never once or twice several times often is not allowed
never once or twice several times often was not allowed
1 2 3 4 5
never once or twice several times often was not allowed
33. When you stayed in the bush/with the LRA, how many times…?
Mairungi (khat) bundles per week? ___
1 2 3 4 5
1 2 3 4
never once or twice several times often
Specify: ________________________________________________________________ _______________________________________________________________________
34. When you stayed in the bush/stayed with the LRA were you given pills, injections or anything to drink or eat which made your body/mind react in an unusual way?
1 2 3 4 5
32. How many times did you sniff glue during the last month?
Mairungi (khat) bundles per week? ___
the last month? 1 never 2 once or twice 3 several times 4 often 5 is not allowed
30. How many times did you smoke opium, 31. When you stayed in the bush/with the cannabis or chew mairungi (khat) during LRA, how many times…?
Waragi, how many glasses per week? ___ Beer, how many bottles per week? ___
18
17
16
13 14 15
12
11
10
09
08
07
06
05
04
03
02
01
Domestic Violence Have you ever been hit (with or without belt, board, stick, etc.) by one of your parents/your caretaker in a way that marks were left on your body? Has one of your parents/your caretaker ever tried to burn you (e.g. hot water, cigarette, fire)
Have you seen people with mutilations or dead bodies?
General Events (CAPS) Natural disaster (for example, flood, hurricane, tornado, earthquake) Fire or explosion Accident (e.g. car accident, boat accident, train wreck, plane crash, serious accident at work, home, or during, recreational activity) Exposure to toxic substance (for example, dangerous chemicals, radiation) Physical assault (for example, being attacked, hit, slapped, kicked, beaten up) Assault with a weapon (for example, being shot, mutilated, stabbed, threatened with a knife, gun, bomb) Unwanted or uncomfortable sexual experience (someone tried to touch your private parts against your will, attempted rape)? Sexual assault (rape, made to perform any type of sexual act through force or threat of harm, e.g. „given as wife“) Combat or exposure to a war-zone (in the military or as a civilian) Captivity (for example, being kidnapped, abducted, held hostage, prisoner of war) Life-threatening illness or injury (self or family member, close friend) Severe human suffering (e.g. forced to carry heavy loads, starvation, torture etc.) Sudden, violent death (for example, homicide, suicide) Sudden, unexpected death of someone close to you Serious injury, harm, or death you caused to someone else --
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LRA
Many people have at one time in their life experienced a very stressful or traumatic event or were witnessing one. I will ask you a few questions about stressful events that you may have experienced in your life. This will be more general events, that people have experienced all over the world and there are some more specific events, that the people especially in Northern Uganda may have experienced during the conflict.
Event List
Perpetrator Have you been forced to beat, injure or mutilate someone by the LRA? Have you been forced to kill someone by the LRA? (who?: family ( ), village/community ( ), other ( )) Did you have to abduct other children? Did you have to loot properties and burn houses of civilians? Have you ever been forced to sexually assault/violate someone by the LRA? Have you ever been forced to skin, chop or cook dead bodies by the LRA?
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(age: _______)
1 Yes
CAPS & MINI (Depression/Suicidality) follows here!
Criterion A met?
2 No
When (EVENT) happened did you feel very anxious or frightened? Horrified? Helpless? 1 Yes 2 No
When did the traumatic event happen? Year: ________
Which traumatic experience would you consider to be the worst? - No. ____ Description: _______________________________________________________________ __________________________________________________________________________ __________________________________________________________________________
If event 29 is marked, please specify below! ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________
Have you had any other traumatic experience that I haven't mentioned so far? 1 Yes 2 No 3 witnessed
29 anything else?
28
27
25 26
24
23
22
21
20
19
LRA-specific Have you in any way been threatened to be killed by the LRA (e.g. for no reason, for disobeying rules, for failed escapeattempt)? Have you given birth to a child during captivity? Have you ever been forced to abandon your child (either in the bush during captivity or because of the abduction)? Have you ever been forced to eat human flesh by the LRA?
Rater Date of Rating
There is nobody I can trust
If somebody hits me, I hit back
09
protect my rights, I will
If I have to resort to violence to
irritation show
When frustrated, I let my
Usually everybody is against me
with people
I often find myself disagreeing
may hit another person
Given enough provocation, I
hothead
Some of my friends think I’m a
argumentative
My friends say that I’m
08
07
06
05
04
03
02
01
and the interpreter.
5
3
3
of me
5
of me
4
extremely characteristic
2
extremely uncharacteristic
1
of me
3
5
of me
4 extremely characteristic
2
extremely uncharacteristic
1
of me
3
5
of me
4 extremely characteristic
2
extremely uncharacteristic
1
of me
3
5
of me
4 extremely characteristic
2
extremely uncharacteristic
1
extremely characteristic
5
of me
4
of me
2
extremely uncharacteristic
1
of me
3
5
of me
4 extremely characteristic
2
extremely uncharacteristic
1
of me
5
of me
4 extremely characteristic
2
extremely uncharacteristic
1
of me
3
5
of me
4 extremely characteristic
2
extremely uncharacteristic
1
extremely characteristic
4 of me
3
3
of me
2
extremely uncharacteristic
1
want to remind you that everything you tell me will be kept strictly confidential. It is only between me and you
wrong or right way of being and therefore there is also no wrong or right way of answering my questions. I also
interested in how you usually feel or react and therefore I would like you to be as honest as possible. There is no
You certainly know and experienced that everybody behaves and reacts different in certain situations. I’m now
Code Name
(Buss and Perry (1992), adapted)
AGGRESSION QUESTIONNAIRE
16
15
14
13
12
11
10
temper
I have trouble controlling my
tell them what I think of them
When people annoy me, I may
explode
bomb/powder keg ready to
I sometimes feel like a
have broken things
I have become so mad that I
rawest deal out of life
4
5
2
3
4
5
of me
5 of me
4
extremely characteristic
2 extremely uncharacteristic
1
of me
of me
of me
3
3
5
extremely characteristic
2
4
extremely characteristic
extremely uncharacteristic
1
of me
extremely uncharacteristic
1
of me
5
of me
4
extremely characteristic
2
extremely uncharacteristic
1
of me
of me
of me
3
3
5
extremely characteristic
2
4
extremely characteristic
extremely uncharacteristic
1
of me
2
with me
1 extremely uncharacteristic
At times I feel I have gotten the
5
of me
4
of me
3
3 extremely characteristic
2
extremely uncharacteristic
1
arguments when people disagree
I can’t help getting into
talk about me behind my back
I know that so called „friends“
2
3
4
4
2 3
2
4
4
2
2
12. Throughout my time in the bush I resisted to believe in Kony’s rituals and norms.
11. I never felt emotionally connected to the group in the bush.
10. The children in the bush still fight for the good of all Acholi.
9. I still keep up rituals and norms I learned in the bush.
8. By leaving the bush I lost a family.
7. Without wearing Kony’s symbols (bracelet, bottle) I feel unprotected.
6. Some of the LRA’s aims are right for the Acholi.
5. When life turns out difficult here, I would prefer to go back in the bush.
4. During my time within my group in the bush I always felt like an outsider.
3. I appreciate the skills I learned in my group in the bush.
2. Kony is protected by holy ghosts, which give him supernatural power.
1. I used to have friends in my group in the bush that I miss now.
4
0 1 I strongly I disagree disagree
2 neither nor
4 3 I agree I strongly agree
If there is something you don’t understand, please feel free to ask and I will try to explain things differently. While going through the questions you can always tell me about how you feel at the moment (e.g. when it is especially stressful for you) and whether you need a break.
In the following I would like to know how you lived in the bush (the LRA) and how you are feeling about it now. Please note again that everything you tell us during this interview (and later) will be kept strictly confidential. There are no right or wrong answers and there is no norm. I’m interested in your feelings and opinions. So it is important for me and my work that you try to be as honest as possible.
COLLECTIVE IDENTITY QUESTIONNAIRE FOR FORMER UGANDAN CHILD SOLDIERS:
2
2
comments:
distance midpoint self - family
your (biological) family:
_____cm
distance midpoint self - group in the bush _____cm
your group in the bush:
_____cm
distance midpoint self - Kony
Kony:
… and how close do you feel now to:
distance midpoint self - family
your (biological) family:
_____cm
distance midpoint self - group in the bush _____cm
your group in the bush:
_____cm
distance midpoint self - Kony
Kony:
Thinking back to your time in the bush can you please show me with these circles how 1 close you felt to
This sheet represents your life. This circle on the right represents you at a certain point in your life. The other three discs represent Kony, your group in the bush, and your (biological) family. Please place these discs on the sheet in a way that it becomes clear how much space this person/this group takes/took in your life. If the person/the group takes/took a lot of space in your life then place the corresponding disc close to the circle that represents yourself. If you place the disc in a greater distance to yourself then you show that this person/this group takes/took less space. *
15. Now we would like to understand better how close several persons/groups are/were to you in your life.
__________________________________________________________________________________________
__________________________________________________________________________________________
__________________________________________________________________________________________
Self-categorization Attachment (incl. Inner Resistance) 3 Behavioral involvement 4 Meaning and ideology (incl. Inner Resistance) * adapted version of the PRISM by Stefan Büchi et al. (2002); maximum distance 0-27 cm
1
4
14. If you think back now, what was good during your time in the bush? (give examples)
13. Even now Kony reads my mind from the distance.
