Psychological Trauma: Theory, Research, Practice, and Policy

Psychological Trauma: Theory, Research, Practice, and Policy Predictors of Posttraumatic Growth 10–11 Months After a Fatal Earthquake Robin Achterhof, Martin J. Dorahy, Amy Rowlands, Charlotte Renouf, Eileen Britt, and Janet D. Carter Online First Publication, June 5, 2017. http://dx.doi.org/10.1037/tra0000286

CITATION Achterhof, R., Dorahy, M. J., Rowlands, A., Renouf, C., Britt, E., & Carter, J. D. (2017, June 5). Predictors of Posttraumatic Growth 10–11 Months After a Fatal Earthquake. Psychological Trauma: Theory, Research, Practice, and Policy. Advance online publication. http://dx.doi.org/10.1037/tra0000286

Psychological Trauma: Theory, Research, Practice, and Policy 2017, Vol. 0, No. 999, 000

© 2017 American Psychological Association 1942-9681/17/$12.00 http://dx.doi.org/10.1037/tra0000286

Predictors of Posttraumatic Growth 10 –11 Months After a Fatal Earthquake Robin Achterhof, Martin J. Dorahy, Amy Rowlands, Charlotte Renouf, Eileen Britt, and Janet D. Carter

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University of Canterbury Posttraumatic growth (PTG) is a commonly observed phenomenon in the wake of a distressing event, capturing potentially beneficial effects for posttraumatic adaptation. However, it is not entirely clear what factors are essential for the development of PTG, especially after natural disasters. Most importantly, it is uncertain what type of relationship exists between posttraumatic stress symptoms (PTSS) and PTG. As yet, there is also no consensus on whether PTG can best be seen as a process outcome or as a coping mechanism. The current study aimed to elucidate these uncertainties. The study explored PTG in a community sample (N ⫽ 412) 10 –11 months after a major earthquake in Christchurch, New Zealand. Nonsymptomatic predictors of PTG were assessed 4 –7 months after the earthquake, and symptomatic predictors were assessed both 4 –7 and 10 –11 months after the earthquake, with PTG measured in the second assessment. Results showed that the unique relationship between PTSS and PTG was modeled best both linearly and curvilinearly, suggesting that PTSS over a certain level shift from a positive association with PTG to a negative one. PTG was predicted by being female, having less household income, PTSS symptoms modeled linearly and curvilinearly at Time 1, and PTSS modeled linearly at Time 2. Support was found for the coping model of PTG, suggesting the importance of fostering growth to manage posttraumatic distress. Keywords: earthquakes, posttraumatic growth, predictors

that in a significant number of individuals traumatic distress might even lead to adaptive changes (e.g., greater appreciation of life). One way in which such adaptive changes have been defined is through the construct of posttraumatic growth (PTG). This refers to positive change that develops from adapting to distressing symptoms and events (e.g., improved relationship functioning, seeing new opportunities in life). PTG has been observed following a wide variety of overwhelming experiences, including illness, combat, and natural disasters (Linley & Joseph, 2004). Two main models have been proposed to explain the concept of PTG: an outcome model and a coping model. Tedeschi and Calhoun (1996, 2004) proposed that PTG may result from the experiencing of a trauma that challenges one’s world beliefs. Through both unconscious and deliberate cognitive processing of the trauma, these belief systems (or schemas) are altered, resulting in long-term PTG (outcome model). Whereas the negative associations with traumatic distress are acknowledged, in this model PTG is viewed as a constructive process, which results in qualitative changes across different life domains (e.g., in personal strength and relationships). An opposing view has been put forward by Taylor and colleagues (e.g., Taylor & Armor, 1996), who claim that PTG is a way of coping with distress and constitutes a positive illusion (coping model). In this way, PTG is a process that is active in the short term, working to deal with the immediate distress of trauma. In this model, experiencing PTG is seen as a form of self-enhancement, for example, someone telling themselves they have grown into a richer person after a traumatic event, whereas they actually feel miserable (Taylor & Armor, 1996). Zoellner and Maercker (2006) combined these models in their two-component model and argued that PTG involves both a constructive and an illusory component. Shortly after a traumatic event, certain illu-

On February 22, 2011, a 6.3 magnitude earthquake hit the city of Christchurch in the Canterbury region of New Zealand. It took the lives of 185 people, destroyed large parts of the city, and caused much additional damage to infrastructure (e.g., sewage, electricity, water supply). Less than 6 months earlier in September 2010, the area was hit by a 7.1 magnitude earthquake, resulting in major infrastructure damage but no fatalities. Both these earthquakes and the thousands of aftershocks that accompanied them had a major impact on Christchurch and its community. The current study examined the degree to which positive posttraumatic changes (i.e., posttraumatic growth) were evident within the first year after the February 22 earthquake and what types of symptoms and psychosocial factors predicted growth. Whereas most research on the psychological consequences of potentially traumatic events focuses on the development of psychopathology, most survivors of disasters show resilience and generally do not develop clinically relevant symptoms (Bonanno, 2004; Bonanno, Brewin, Kaniasty, & Greca, 2010; Bonanno, Galea, Bucciarelli, & Vlahov, 2006). Furthermore, it has been argued

Robin Achterhof, Martin J. Dorahy, Amy Rowlands, Charlotte Renouf, Eileen Britt, and Janet D. Carter, Department of Psychology, University of Canterbury. Robin Achterhof is now at the Center for Contextual Psychiatry, Research Group Psychiatry, University of Leuven. Correspondence concerning this article should be addressed to Martin J. Dorahy, Department of Psychology, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. E-mail: martin.dorahy@canter bury.ac.nz 1

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ACHTERHOF ET AL.

sory self-enhancing appraisals may be developed to deal with initial distress, whereas after some time, actual growth may occur. The outcome model and the coping model imply different types of relationships between distress and PTG. In the outcome model, PTG is seen as a long-term outcome of dealing with distress and thus is considered to occur subsequent to the distress. However, when regarded as a coping mechanism, PTG is hypothesized to work concurrently with or shortly following traumatic distress. Studies of PTG and distress have yielded conflicting results, with positive, negative, and null associations (Linley & Joseph, 2004). A meta-analysis by Helgeson, Reynolds, and Tomich (2006) across 87 studies revealed PTG to be related to less depression and more positive well-being. When trauma was more recent (i.e., within 2 years), these relationships were stronger. Still there was huge variability in the sample compositions, types of trauma, and results. Also, natural disaster research was underrepresented (n ⫽ 5), with no study assessing the potentially unique impact of earthquakes. One later study on earthquake survivors found that both posttraumatic stress symptoms (PTSS) and earthquake exposure were in fact positively associated with PTG (Xu & Liao, 2011). Longitudinal studies may shed more light on the mixed results found in cross-sectional studies. One study following Israeli exprisoners of war found that more PTSS significantly predicted a higher level of PTG 5 years later but not vice versa (Dekel, Ein-Dor, & Solomon, 2012). In contrast, another study measuring PTG and PTSS in soldiers 5 and 15 months after deployment to Iraq found that earlier-measured PTG predicted more later-measured PTSS but not vice versa (Engelhard, Lommen, & Sijbrandij, 2015). More relevant to the current study are two longitudinal studies that assessed the relationship between distress and PTG after an earthquake. A study investigating a relatively severely affected sample after the 2008 Wenchuan earthquake found that a higher level of PTG at 12 months after the earthquake was predictive of less PTSS across almost all symptom clusters 18 months after the earthquake (Chen, Zhou, Zeng, & Wu, 2015). However, Time 1 (T1) PTSS did not predict Time 2 (T2) PTG. Assessing a different sample after the same earthquake, Zhou, Wu, and Chen (2015) found more PTSS at 3.5 and 4.5 years after the earthquake to predict more PTG at 5.5 years after the earthquake, whereas PTG was not at all predictive of later PTSS. Thus, these studies, even when they investigate samples from the same earthquake, do not reach consensus on either the causal direction of the PTG-PTSD relationship or on whether this association is positive or negative. One way in which the relationship between PTG and posttraumatic distress may be obscured in previous research is through moderating variables. The psychological response to disasters can be influenced significantly by risk and resilience factors. These factors include, among others, age, gender, social support, socioeconomic status, severity of traumatic exposure, and material damage (e.g., Bonanno et al., 2010). All of these factors (or proxies of them) are considered in the current study. Two additional trauma-related variables are considered as well. In two earlier studies on Christchurch samples, it was found that the predictability and controllability of the personal response to each aftershock was strongly associated with symptom development (Dorahy & Kannis-Dymand, 2012; Dorahy et al., 2016). Also, increased substance use following a traumatic event might be a hindrance to developing PTG because it could represent an alternative coping strategy for dealing with traumatic distress. There is some evidence for a negative relationship between in-

creased substance use and PTG (Arpawong et al., 2015; Milam, Ritt-Olson, Tan, Unger, & Nezami, 2005). Another cause of the inconsistent findings concerning the relationship between PTSS and PTG may be due to its nonlinear shape. As suggested by Butler et al. (2005), PTSS and PTG may well be related in a curvilinear fashion rather than a linear one. Such a relationship would be of an inverted U shape, whereby a moderate amount of symptoms relates to the highest level of PTG. This might be explained by the idea that a certain level of distress is needed for PTG to occur, whereas too much distress counteracts PTG. A meta-analysis by Shakespeare-Finch and Lurie-Beck (2014) of 42 studies found that, cross-sectionally, a curvilinear relationship between PTG and PTSS explained slightly more variance than a linear relationship. In the current study, both linear and curvilinear relations between PTG and PTSS were assessed over time. PTG was measured only at the second time point (10 –11 months after the earthquake), thereby testing the hypothesis offered by Dekel et al. (2012) and Zhou et al. (2015) that PTSS predict PTG. It is worth noting that one other recent study also investigated PTG in the postearthquake community of Christchurch (Marshall, Frazier, Frankfurt, & Kuijer, 2015). The temporal development of PTG was measured in 144 Christchurch residents, by measuring PTG 1 month after the September 2010 earthquake and 3 and 12 months after the February 2011 earthquake. The main finding was that most participants showed a stable level of PTG over time. Significant predictors of the higher level of PTG were (better) preearthquake mental health, (lower) age, and being female. The present study surveyed PTG 10 –11 months after the February, 2011 earthquake and investigated its relation to both earlier symptomatic distress (4 –7 months after the earthquake) and concurrent symptomatic distress. Symptomatic distress consisted of posttraumatic stress, depression, and anxiety. A curvilinear association between PTSS and PTG was considered. Also, a number of stable (i.e., age, gender, income) as well as trauma-related (i.e., relative earthquake affectedness, losses [of house or job/business], increased substance use, social support, and predictability/controllability of the personal response to aftershocks) factors were assessed as potential PTG predictors. Because earlier research has no consensus on the type, direction, and strength of most predictors of PTG that were investigated, no specific hypotheses concerning predictors are given. There does, however, seem to be a fairly strong age and gender effect, so it was expected that young age and being female would relate to higher levels of PTG.

Method Participants Six hundred participants from six different Christchurch suburbs were recruited 4 –7 months (T1) after the February 2011 Christchurch earthquake (see Dorahy et al., 2015). These six suburbs were selected based on differences in average household income and whether they were affected or relatively unaffected by the earthquake. Each of the three affected suburbs reflected low, medium, and high average household income and were matched to three relatively unaffected suburbs. Matching was based on average household income, average age, gender, and number of people per suburb. Of the 600 participants at T1, 412 were subsequently reassessed between 10 and 11 months after the 22 February earthquake (T2).

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Table 1 shows the demographic data from T1 and T2. As can be seen in Table 2, the level of follow-up is quite consistent across suburbs, and a ␹2 test revealed that group sizes at T2 did not significantly differ, ␹2(5) ⫽ 3.86, p ⫽ .57. For the current study, only those 412 participants at T2 follow-up were taken into account. Mean age of this sample was 50.41 years (SD ⫽ 16.00), and the sample consisted of 35% men (n ⫽ 142) and 65% women (n ⫽ 270). Age was positively related to income level such that at T1 and T2 the low income suburbs were younger than the higher-income suburbs, F(2, 595) ⫽ 10.41, p ⬍ .001; F(2, 409) ⫽ 13.71, p ⬍ .001, respectively. No other demographic differences were found across suburbs.

Measures The survey included the Acute Stress Disorder Scale (ASDS; Bryant, Moulds, & Guthrie, 2000), the nine-item depression module of the Patient Health Questionnaire (PHQ-9; Spitzer, Kroenke, & Williams, 1999), and the Generalized Anxiety Disorder-7 scale (GAD-7; Spitzer, Kroenke, Williams, & Löwe, 2006). At T1 and T2, the ASDS was administered first, then the PHQ-9, and finally the GAD-7 scale. Cutoff scores for a suspected diagnosis of these disorders have been set as follows and were used here: ASDS, dissociation subscale scores greater than 8 and the cumulative scores of the remaining three subscales greater than 27 (Bryant, Moulds, & Guthrie, 2000); PHQ-9, endorsing at least one of the first two items assessing mood and loss of interest and endorsing at least five of the nine symptoms in total on more than half the days (except the suicidal ideation, which can be several days; Kroenke, Spitzer, Williams, & Löwe, 2010); and GAD-7, a mean score greater than 9 (Ebell, 2008). At T1, items for these questionnaires were anchored to the experience of symptoms since the February earthquake; at T2, these items were anchored to the experience of symptoms in the past week. Although the ASDS aims to measure Acute Stress Disorder symptoms, three of the four symptom clusters measured (reexperiencing, avoidance, arousal) constitute the same symptoms as posttraumatic stress disorder, and thus, the combination of these symptoms, as well as the dissociative symptoms assessed by the ASDS, is referred to here as PTSS. In both assessments, participants were asked questions concerning age, gender, increased alcohol and cigarette use since the earthquakes, having lost anything as a result of the earthquakes, having social support, and their ability to predict and control their personal response to aftershocks. Increased alcohol and cigarette use was assessed using a five-point scale ranging from not at all (scored 0) to a significant amount (scored 4). A not applicable option was also available (scored 0). The mean of both these scores at T1 was used in the subsequent analysis. Losses as a result of the earthquake were assessed via an open-ended question. Loss of either a home (n ⫽ 47) or a job/business (n ⫽ 40) was most prevalent. If participants had lost either of these,

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they were given a score of 1 on the losses variable. Social support was assessed by asking participants whether they had people readily available to talk to about their earthquake experiences, with potential answers ranging from not at all/occasionally (scored 0) to constantly (scored 3). Lastly, participants were asked how well they could predict and how well they believed they could control their response to each aftershock. Answers had a possible range from 0 (completely) to 10 (not at all). Given the high theoretical similarity of both controllability and predictability and their high correlation (r ⫽ .73, p ⬍ .001), their mean was used for subsequent analyses (see also Dorahy et al., 2016). The dependent variable in the current study, PTG, was exclusively assessed at T2. Three items from the Posttraumatic Growth Inventory–Short Form were used to define PTG to keep the survey at a manageable length (Cann et al., 2010). These three items were as follows: As a result of the earthquake, have you: (a) developed a greater appreciation for the value of your own life; (b) developed a greater sense of closeness with others; and (c) discovered that you’re stronger than you thought you were? Although these items are a limited representation of the PTG construct, they represent PTG domains that have frequently been observed (i.e., appreciation of life, relating to others, and personal strength; see, e.g., Marshall et al., 2015; Xu & Liao, 2011). Therefore, although the PTG domains of religiosity and new possibilities are omitted, the total PTG score was still considered a valid representation of the PTG construct. The total PTG score was calculated by taking the mean of the items, which are rated from 0 (no) to 5 (very great degree).

Procedure At T1, participants were assessed at their own home. Subsequent to written informed consent, a 20- to 30-min survey was read to them by the interviewer. After completion, participants were asked whether they would be interested in participating in a follow-up study. At T2, participants who had agreed to follow-up were interviewed once more at their own home. PTG questions were added to the T2 survey, which otherwise was the same as at T1. T1 data collection occurred 4 –7 months after the February 2011 earthquake, and T2 data collection occurred 10 –11 months after this earthquake. It is worth noting that throughout data collection, aftershocks continued to occur, some very large (e.g., magnitude 6.3). All parts of the study were approved by the appropriate New Zealand Human Ethics Committee.

Data Analyses After exploratory data analysis, associations between all variables were assessed using correlations. Then it was ascertained whether PTG was best predicted by PTSS linearly or curvilinearly. Two hierarchical multiple regressions were performed, with T1 and T2

Table 1 Demographics in Phase 1 and Phase 2 of Study Study

N

nMale/nFemale %male/%female

Mean age, y (SD)

low decile, n

medium decile, n

high decile, n

Affected, n

relatively unaffected, n

T1 T2

600 412

218/382 36.3%/63.7% 142/270 34.5%/65.5%

49.7 (1.64) 50.4 (1.66)

200 (33.3%) 134 (32.5%)

200 (33.3%) 150 (36.4%)

200 (33.3%) 128 (31.1%)

300 (50.0%) 196 (47.6%)

300 (50.0%) 216 (52.4%)

ACHTERHOF ET AL.

4 Table 2 Number of Participants From Each Suburb per Phase Study

Avonside, Na

North Hornby, Nb

South Brighton, Nc

Papanui, Nd

Mt Pleasant, Ne

Cashmere, Nf

T1 T2

100 (16.7%) 67 (16.3%)

100 (16.7%) 67 (16.3%)

100 (16.7%) 67 (16.3%)

100 (16.7%) 83 (20.1%)

100 (16.7%) 62 (15.0%)

100 (16.7%) 66 (16.0%)

a

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f

Affected, low decile. b Relatively unaffected, low decile. c Affected, medium decile. d Relatively unaffected, medium decile. e Affected, high decile. Relatively unaffected, high decile.

n ⫽ 178; T2, 10%, n ⫽ 42; depression: T1, 5%, n ⫽ 20; T2, 3% n ⫽ 13; anxiety: T1, 23%, n ⫽ 94; T2, 9%, n ⫽ 38). ␹2 tests revealed significant reductions over time in ASD diagnosis, ␹2(1, N ⫽ 412) ⫽ 182.91, p ⬍ .001, and anxiety diagnosis, ␹2(1, N ⫽ 412) ⫽ 43.14, p ⬍ .001, but not for the diagnosis of depression, ␹2(1, n ⫽ 409) ⫽ 2.60, p ⫽ .11, which had a relatively low rate at T1. Correlations for symptom measures generally showed a strong effect within a time period (i.e., T1 and T2, ranging from r ⫽ .71 to r ⫽ .75 at T1, and from r ⫽ .56 to r ⫽ .82 at T2), but this reduced to moderate between time periods. This suggests a stronger relationship across symptom measures within a time period than within a symptom measure across time periods. PTG showed significant positive correlations with sex, T1 predictability/controllability of earthquake response, T1 losses, T1 and T2 PTSS, T1 and T2 depression symptoms, and T1 and T2 anxiety symptoms. Significant negative correlations were found between PTG and both age and average suburb income, whereas PTG was not significantly associated with relative suburb affectedness, social support, and increased alcohol and cigarette use. Mean PTG was 2.48, indicating a small to moderate amount of growth. Only 4% of participants indicated no PTG on all three items.

PTSS as predictors, respectively, in each. In these regressions, linear PTSS estimates were entered first and their square products second. If the square products added a significant amount of explained variance to the linear models, then they were retained for the full exploratory model of predictors of PTG. For this total model, another hierarchical multiple regression was used. All independent variables were entered in subsequent blocks to predict PTG. In the first step, all stable variables were entered (i.e., age, gender, average income). Next, all T1 variables that were nonsymptomatic but trauma relevant were entered (i.e., suburb-affected/ unaffected, increased alcohol and cigarette use, social support, predictability/controllability of response to aftershocks, losing a house/ job/business). In the third block, either linear and/or curvilinear T1 PTSS and T1 depression symptoms and T1 anxiety symptoms were entered. To examine the effect of symptomatic distress on PTG development over time, T2 PTSS (linear or curvilinear, dependent on previous analysis), T2 depression symptoms, and T2 anxiety symptoms were entered in the fourth and final step. All analyses were computed using IBM SPSS version 21.0 (IBM Corp, 2012).

Results Means, standard deviations, and correlations between all variables are given in Table 3. A general drop in symptom distress was evident between T1 and T2, such that fewer participants met criteria for clinical diagnoses at T2 (acute stress disorder: T1, 43%,

Shape of Posttraumatic stress–PTG Relationship To determine whether the relations between PTSS and PTG at both T1 and T2 were best modeled linearly or curvilinearly, two

Table 3 Descriptive statistics and correlations between all variables Variables 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.

Age (T1) Sexa Affectednessb Average incomec Social support (T1) Predictability and controllabilityd(T1) Increased alcohol/cigarettese (T1) Losses (T1) PTSSf (T1) Depression (T1) Anxiety (T1) PTSSf (T2) Depression (T2) Anxiety (T2) PTGg (T2)

Mean

SD

1

2

3

50.41 16.00 1.66 .48 ⫺.08 1.48 .50 ⫺.02 ⫺.01 1.99 .80 .22ⴱⴱ .08 ⫺.01 3.25 .92 .04 .22ⴱⴱ .07 3.26

2.87 ⫺.20ⴱⴱ

.13ⴱ

.39 .55 ⫺.21ⴱⴱ ⫺.01 .21 .41 ⫺.14ⴱⴱ .05 40.67 13.46 ⫺.21ⴱⴱ .28ⴱⴱ ⴱ 5.40 4.91 ⫺.11 .25ⴱⴱ 5.55 4.52 ⫺.18ⴱⴱ .24ⴱⴱ 30.08 9.50 ⫺.01 .07ⴱ 3.63 4.62 ⫺.02 .03 3.25 3.72 ⫺.04 .05 2.48 1.18 ⫺.19ⴱⴱ .23ⴱⴱ

4

5

6

7

8

9

10

.10ⴱ .10ⴱ .34ⴱⴱ .31ⴱⴱ .46ⴱⴱ .17ⴱⴱ .20ⴱⴱ .25ⴱⴱ .21ⴱⴱ

.01 .24ⴱⴱ .27ⴱⴱ .26ⴱⴱ .17ⴱⴱ .17ⴱⴱ .14ⴱⴱ .08

.11ⴱ .19ⴱⴱ .16ⴱⴱ .05 .25ⴱⴱ .17ⴱⴱ .10ⴱ

.70ⴱⴱ .71ⴱⴱ .42ⴱⴱ .28ⴱⴱ .34ⴱⴱ .32ⴱⴱ

.75ⴱⴱ .37ⴱⴱ .44ⴱⴱ .41ⴱⴱ .21ⴱⴱ

11

12

13

14

.45ⴱⴱ

.03

⫺.44ⴱⴱ ⫺.26ⴱⴱ

.10ⴱ .22ⴱⴱ .22ⴱⴱ .33ⴱⴱ .24ⴱⴱ .19ⴱⴱ .35ⴱ .31ⴱ .08

⫺.08 ⫺.18ⴱⴱ ⫺.05 ⫺.13ⴱⴱ ⫺.24ⴱⴱ ⫺.12ⴱ ⫺.32ⴱⴱ ⫺.33ⴱⴱ ⫺.19ⴱⴱ

⫺.08 .01 .01 ⫺.06 ⫺.14ⴱⴱ ⫺.11ⴱ ⫺.15ⴱⴱ ⫺.17ⴱⴱ ⫺.07

.35ⴱⴱ .35ⴱⴱ .56ⴱⴱ .40ⴱⴱ .59ⴱⴱ .82ⴱⴱ .29ⴱⴱ .28ⴱⴱ .15ⴱⴱ .17ⴱⴱ

a 1, male; 2, female. b 1, Relatively unaffected; 2, relatively affected. c 1, low decile; 2, medium decile; 3, high decile. d Mean score of predictability and controllability of earthquake response. e Increased alcohol and cigarette use. f posttraumatic stress symptoms. g Posttraumatic growth. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.

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hierarchical regression analyses were used (see Table 4). The first analysis revealed that when assessed linearly, T1 PTSS explained a significant amount of T2 PTG variance, R2 ⫽ .10, p ⬍ .001. When the quadratic PTSS component was added in the second step, it significantly added a small amount of variance to the purely linear model, ␤ ⫽ ⫺.20, R2⌬ ⫽ .03, p ⬍ .001, leading to a total explained variance of 13%. T2 PTSS also significantly predicted PTG linearly, R2 ⫽ .08, p ⬍ .001, and when the quadratic component was added, it again contributed a small, significant additional amount of variance, ␤ ⫽ ⫺.16, R2 ⌬ ⫽ .01, p ⫽ .02, resulting in 9% explained variance. In line with previous literature, the relation between PTSS and PTG was slightly better modeled curvilinearly than linearly (Shakespeare-Finch & Lurie-Beck, 2014). The negative betas for the quadratic components at both time points reveal these curvilinear relationships to have a reversed U-shape, with a moderate amount of PTSS relating to the highest level of PTG. These analyses demonstrate that for the total model, it is best to model the relationship between PTSS and PTG with both a linear and a quadratic component. To ascertain why the curvilinear relation was not as clear at T2 as it was at T1, it was investigated whether this might be explained by a relative shift in people moving from the high end of the PTSS scale at T1 to the middle/lower end of this scale at T2. For the relation between PTSS and PTG at T1, derivation of the quadratic equation revealed that the maximum of the quadratic curve was at PTSS ⫽ 58.20. So for participants with a score lower than 58.20 on the ASDS, a positive association between symptoms and PTG was evident, whereas for participants with a score above 58.20, a negative association between symptoms and PTG was evident. At T1, 43 participants showed a PTSS score greater than 58.20, whereas at T2, only eight participants showed a PTSS score greater than 58.20. A ␹2 test revealed this difference to be significant, ␹2(1, 412) ⫽ 31.81, p ⬍ .001. These results indicate that at T2, there were significantly fewer participants at the high end of the PTSS scale (in which a negative relation between PTSS and PTG exists) than at T1.

Predictors of PTG Hierarchical multiple regression examined the effects of stable factors (Step 1), trauma characteristics (Step 2), and symptom type and level on PTG (Steps 3 & 4; see Tables 5 and 6). In the first step

Table 4 Hierarchical Regression of Linear and Quadratic PTSS Predictors of PTG at T1 and at T2 Steps Time 1 1a 2b Time 2 1c 2d

Variables

B

SE B

␤

p

T1 PTSS, linear T1 PTSS, linear T1 PTSS, quadratic

.03 .59 ⫺.27

.00 .12 .07

.32 .24 ⫺.18

.000 .000 .000

T2 PTSS, linear T2 PTSS, linear T2 PTSS, quadratic

.03 .05 ⫺.00

.01 .01 .00

.28 .39 ⫺.16

.000 .000 .018

Note. PTSS ⫽ posttraumatic stress symptoms. R2 ⫽ .08, p ⬍ .001. b R2 change ⫽ .09, p ⫽ .02. c R2 ⫽ .10, p ⬍ .001. d R2 change ⫽ .13, p ⬍ .001. a

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of the model, a higher level of PTG was predicted by age (␤ ⫽ ⫺.13, p ⫽ .01), sex (␤ ⫽ .24, p ⬍ .001), and average income of the suburb of the participant (␤ ⫽ ⫺.18, p ⬍ .001). The age and sex effects were consistent with the literature (i.e., lower age and female associated with higher PTG); however, the average income effect was not. Throughout all steps, the sex and income effects remained significant (with p ⬍ .05), whereas the age effect was no longer significant in the last step of the analysis (␤ ⫽ ⫺.09, p ⫽ .08). In the second step, the variables of earthquake affectedness (by suburb), social support, increased alcohol and cigarette use, losing a home/job/business, and the predictability/controllability of the personal response to aftershocks did not add a significant amount of explained PTG variance to the first step, F-change(5, 394) ⫽ 1.43, p ⫽ .21. The only predictor showing a nonsignificant trend was less predictability/controllability of emotional response to aftershock (␤ ⫽ .09, p ⫽ .09). Of note, is that there was a discrepancy between the zero-order correlation of this variable with PTG (r ⫽ .21), and its semipartial correlations with PTG throughout the analysis (sr ⫽ .08 at Step 2; sr ⫽ .01 at Step 4). This indicates large overlap between the explained variance of predictability/controllability and the other variables in the analysis. Taken together, the chosen trauma-related variables added little to predicting PTG. Symptom variables of depression, anxiety, and both linear and quadratic PTSS at 4 –7 months after the earthquake were entered in the third step and yielded a significant addition of explained variance, F-change(4, 390) ⫽ 7.49, p ⬍ .001, leading to a total explained variance of PTG of 19%. Of these symptom variables, only PTSS modeled both linearly and quadratically proved to be significant, ␤ ⫽ .33, p ⬍ .001; ␤ ⫽ ⫺.15, p ⬍ .01. The negative quadratic ␤-coefficient indicates that after controlling for all other variables, PTSS showed a slightly curvilinear (reverse U-shaped) relationship with PTG. Finally, to assess whether symptom level at T2 had an effect on PTG level over and above T1 symptom level, depression, anxiety, and PTSS (linear and quadratic) symptoms at 10 –11 months postearthquake were entered. Again, this step added a significant amount of explained variance, F-change(4, 386) ⫽ 3.98, p ⬍ .01. The only significant predictor in this step was T2 PTSS, ␤ ⫽ .24, p ⬍ .01. This suggests that T2 PTSS explains a significant amount of variance of PTG, beyond T1 PTSS. At T2, no curvilinear relationship between PTSS and PTG was evident. In sum, the final model, accounting for 23% of variance, showed that PTG was significantly predicted by sex (being female), average income of suburb (having less), T1 PTSS (linear and quadratic), and T2 PTSS (linear). All of these predictors made small significant contributions to the explained variance of PTG, which is in line with previous research showing PTG to be influenced by different psychosocial factors (e.g., Helgeson et al., 2006; Zoellner & Maercker, 2006).

Discussion The aim of the current study was to investigate both symptom and nonsymptom predictors of PTG within the first year after a fatal earthquake. Nonsymptom predictors (age, sex, income, community affectedness, social support, predictability/controllability of aftershock response, increased alcohol/cigarette use, and loss of house or job/business) were assessed 4 –7 months after the earth-

ACHTERHOF ET AL.

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Table 5 Explained Variance for PTG by Step Steps

R

R2

Adjusted R2

R2 change

F change

p F change

1 2 3 4

.34 .36 .44 .47

.11 .13 .19 .23

.11 .11 .17 .19

.11 .02 .06 .03

17.22 1.43 7.49 3.98

.000 .21 .000 .004

quake, whereas symptom predictors (PTSS, depression and anxiety symptoms) were examined both 4 –7 months and 10 –11 months after the earthquake. The outcome measure PTG was assessed 10 –11 months after the earthquake. Most participants reported a small to moderate amount of PTG. When controlling for all other variables, being female, being from a suburb with lower average income, and experiencing more PTSS (at both time points) were significantly associated with reporting a higher level of PTG. In line with earlier research, when measured at T1, PTSS related significantly to the level of reported PTG, and this relationship was best described nonlinearly. This nonlinearity followed a reverse-U shape, whereby a moderate level of symptoms were associated with the highest reported PTG. When accounting for T1 PTSS and nonsymptom variables, the relationship between T2 PTSS and PTG was best modeled linearly. Lastly, depression and anxiety symptoms at both time points, although they significantly correlate with PTG, did not significantly predict PTG when controlling for PTSS and nonsymptom variables.

2015). Such a profile would suggest that PTG might actually be an effective coping mechanism because it arises quickly and is followed by a subsiding of symptoms. For now, however, it is not possible to model a causal role of PTG. The relationship between PTSS and PTG was further qualified by the curvilinear results. In accordance with findings from the metaanalysis by Shakespeare-Finch and Lurie-Beck (2014), the curvilinear relation between PTSS at T1 and PTG added a small but significant amount of variance to the linear relation between these variables, whereby a moderate amount of PTSS related to the highest level of PTG. This curvilinearity remained significant for T1 PTSS after accounting for all other variables. T2 PTSS, however, did not show a strong independent curvilinear relation with PTG, and it did not show a curvilinear relationship at all when other variables were taken into account. This might be explained by far fewer participants reporting high levels of PTSS at T2 than T1 (e.g., ASD diagnoses dropped from 43% at T1% to 10% at T2). The curvilinear model assumes that PTSS positively relates to PTG up until a certain point. After that point, there is a negative relation between PTSS and PTG, with more PTSS

Table 6 Predictors of PTG at Each Step Steps

Variables

B

SE B

␤

p

sra

1

Age Sex Average income Age Sex Average income Affectedness Social support Increased alcohol/cigarette use Losses Predictability and controllability Age Sex Average income Affectedness Social support Increased alcohol/cigarette use Losses Predictability and controllability T1 depression T1 anxiety T1 PTSS, linearb T1 PTSS, quadraticb Age Sex Average income Affectedness Social support Increased alcohol/cigarette use Losses Predictability and controllability T1 depression T1 anxiety T1 PTSS, linearb T1 PTSS, quadraticb T2 depression T2 anxiety T2 PTSS, linearb T2 PTSS, quadraticb

⫺.01 .59 ⫺.27 ⫺.01 .58 ⫺.17 .16 ⫺.05 .05 .09 .04 ⫺.01 .43 ⫺.19 .08 ⫺.05 ⫺.02 .06 .00 ⫺.03 .02 .03 ⫺.00 ⫺.01 .43 ⫺.20 .08 ⫺.03 ⫺.05 .10 .00 ⫺.03 .02 .02 ⫺.00 ⫺.01 ⫺.02 .03 .00

.00 .12 .07 .00 .12 .09 .11 .07 .10 .14 .02 .00 .12 .09 .12 .07 .10 .14 .02 .02 .02 .01 .00 .00 .12 .09 .12 .07 .10 .14 .02 .03 .02 .01 .00 .02 .03 .01 .00

⫺.13 .24 ⫺.18 ⫺.11 .23 ⫺.12 .07 ⫺.04 .03 .03 .09 ⫺.07 .17 ⫺.13 .03 ⫺.04 ⫺.01 .02 .01 ⫺.12 .09 .33 ⫺.15 ⫺.09 .18 ⫺.14 .03 ⫺.03 ⫺.02 .04 .01 ⫺.11 .09 .26 ⫺.16 ⫺.05 ⫺.06 .24 .00

.008 .000 .000 .03 .000 .05 .17 .46 .57 .53 .09 .16 .001 .03 .51 .45 .84 .64 .91 .13 .26 .000 .006 .08 .000 .02 .50 .62 .64 .46 .88 .17 .24 .001 .005 .54 .46 .003 .98

⫺.12 .24 ⫺.18 ⫺.10 .22 ⫺.09 .06 ⫺.03 .03 .03 .08 ⫺.06 .16 ⫺.10 .03 ⫺.03 ⫺.02 .02 .01 ⫺.07 .05 .20 ⫺.13 ⫺.08 .16 ⫺.10 .03 ⫺.02 ⫺.02 .03 .02 ⫺.06 .05 .15 ⫺.13 ⫺.03 ⫺.03 .13 .00

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Posttraumatic Stress Symptoms Generally and over time, more PTSS were found to relate to a higher level of reported PTG. Also, it appeared that there is an independent effect of recently experienced PTSS on PTG level, over and above earlier reported PTSS. These results seem to be consistent with the idea of growth as coping (as proposed by Taylor & Armor, 1996) and do not concur with the theory of growth as an outcome (as proposed by Tedeschi & Calhoun, 2004). The coping model argues that PTG represents one way of immediately dealing with posttraumatic distress, which implies that the experience of PTSS relates to a simultaneous experience of PTG. The current findings confirm a concurrent relationship between these variables, thereby supporting the idea of PTG as a potential coping strategy. The outcome model assumes a more long-term process to be at work between PTSS and PTG. Although they do not specify a time frame, Tedeschi and Calhoun (2004) argue that “[g]rowth, however, does not occur as a direct result of trauma” (p. 5). Instead, PTG is described as the product of an elaborate cognitive process that follows a highly challenging life crisis. Because PTG levels were not measured at the beginning of the current study, it cannot be reliably ascertained whether such a constructive PTSS-to-PTG process has occurred for this sample. However, in an earlier study on a similar sample, Marshall et al. (2015) found levels of PTG to be stable during the first 12 months after the Christchurch earthquake. If the same were true for the current sample, it can be hypothesized that in the first year after the earthquake, there are high initial levels of both PTSS and PTG, followed by a sharp drop in PTSS (as evidenced by the current results), and a stable level of PTG (as evidenced by Marshall et al.,

3

4

a

Semipartial correlation.

b

Posttraumatic stress symptoms.

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predicting less PTG. Participants at T2 did not reach this point as much as they did at T1, such that fewer were at that end of the PTSS scale in which a negative relationship between PTSS and PTG had been observed at T1. This indicates that the location of the bend in the curvilinear relationship between PTSS and PTG is quite stable over time and that when there are not enough participants in the sample with PTSS scores above the medium level, no curvilinear relationship is found. It also implies that different individual trajectories can be expected regarding PTSS and PTG over time. Some people who recover from PTSS may experience less PTG (if they initially had very high PTSS), whereas others who recover might report more PTG over time (if PTSS were initially moderate).

Anxiety and Depression The nonsignificant results of depression and anxiety are probably best explained by the large overlap of depression and anxiety symptoms with PTSS. These three symptom clusters correlated highly, whereas PTSS was the only variable that had a strong independent effect on PTG. This is at odds with earlier research that revealed depression and anxiety symptoms to be negatively related to PTG (more so for recent trauma; see Helgeson et al., 2006). It is likely that the discrepancy with the current study is explained by the fact that these earlier findings are mostly based on samples with higher symptom levels. Anxiety and depression scores were generally higher in these earlier studies, whereas in the current study mean anxiety and depression scores were below clinical cutoff scores. It might also be that this nonrelation between PTG and depression/anxiety in the current sample is due to the type of trauma experienced (i.e., exposure to an earthquake). Future work should examine whether the same null relationship is evident in samples exposed to other trauma types to assess the generalization of the current findings.

Nonsymptom Variables Of all nonsymptom variables, gender and average income significantly predicted PTG 10 –11 months after the earthquake in the final model. Being female and having more PTG is consistent with earlier PTG studies (e.g., Helgeson et al., 2006). Women reporting higher levels of PTG may be attributed to women reporting higher levels of subjective threat when confronted with the same objective event. For example, as described by Bonanno et al. (2010), one study conducted within 24 hours after an earthquake found that women overestimated the actual duration of the earthquake more strongly compared with men (78 seconds vs. 46 seconds; Anderson & Manuel, 1994). The quake itself lasted between 8 and 15 seconds (Clough, Martin, & Chameau, 1994). Another possible explanation for women reporting more PTG is given by Marshall et al. (2015), who refer to research indicating that women are more likely to engage in affiliative behavior when confronted with stressful events (Taylor et al., 2000). More research is needed to explain these sex effects. In contrast to earlier findings (Helgeson et al., 2006), average income was found to negatively predict PTG. That is, those participants from more affluent suburbs reported less PTG. It could be that this effect is due to higher experienced symptomatic distress in the lower-income suburbs, which might then lead to a higher level

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of reported PTG. However, an earlier study on the current sample revealed that average suburb income did not have an effect on reported PTSS at 4 –7 months after the earthquake (Dorahy et al., 2015). When regarding PTG as a coping mechanism, another explanation is that those from lower-income suburbs have fewer resources and, with fewer resources, may engage in PTG to deal with their posttraumatic distress.

Limitations The most important limitations of this study concern the measurement of PTG. Only three items were used (taken from the 10-item Posttraumatic Growth Inventory–Short Form; Cann et al., 2010), thereby discounting the full spectrum of PTG. Concerns about the validity of the PTGI have also been voiced, for example that self-reported growth that the PTGI measures does not accurately reflect actual change (Frazier et al., 2009). Furthermore, PTG was measured only at T2 in the current study. Had it been measured at T1, stronger causality claims could have been made. However, Marshall et al. (2015) found PTG to be stable both before, and in the first year after, the February 2011 earthquake, which implies that level of PTG did not change much over time for postearthquake Christchurch residents. Lastly, the current study investigated PTG only up until 11 months after an earthquake, making any long-term conclusions impossible.

Conclusion The current results suggest that PTG is a phenomenon that is widely reported in communities that have experienced an earthquake. It appears that having a moderate amount of PTSS, being female, and being from a low income suburb make PTG more likely. The current findings suggest PTG is a coping mechanism rather than representing actual change. The specific mechanisms underlying the development and causal effects of PTG can be discovered best by studies with longitudinal designs.

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Received September 14, 2016 Revision received March 5, 2017 Accepted April 27, 2017 䡲