Psychology of Addictive Behaviors 2012, Vol. 26, No. 1, 42–50
In the public domain DOI: 10.1037/a0024663
Predictors of Postdeployment Alcohol Use Disorders in National Guard Soldiers Deployed to Operation Iraqi Freedom Shannon M. Kehle, Amanda G. Ferrier-Auerbach, Laura A. Meis, Paul A. Arbisi, Christopher R. Erbes, and Melissa A. Polusny Minneapolis Veterans Affairs Health Care System, University of Minnesota Alcohol use in the military is a significant problem. The goal of this study was to examine the associations between personality, posttraumatic stress disorder (PTSD) symptoms, and postdeployment alcohol use disorders (AUDs) among a group of Operation Iraqi Freedom (OIF) deployed National Guard soldiers, with a focus on differentiating predeployment and postdeployment onset AUDs. Participants were 348 National Guard soldiers deployed to Iraq from March 2006 to July 2007 drawn from the Readiness and Resilience in National Guard Soldiers (RINGS) study. Participants completed self-report measures one month before deployment and 3 to 6 months postdeployment; current and lifetime history of AUDs were assessed 6 to 12 months postdeployment, using the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders (4th ed. text rev.; DSM–IV; American Psychiatric Association, 2000). Overall, 13% of the panel was diagnosed with a current AUD. Of those who met criteria for a current AUD, 38% had an AUD that developed following return from deployment (new onset AUD). The development of new onset AUDs was uniquely predicted by higher levels of PTSD symptom severity, higher levels of avoidance-specific PTSD symptoms, and lower levels of positive emotionality. AUDs with onset prior to deployment were predicted by higher levels of negative emotionality and disconstraint. Results of this study suggest that combat deployed soldiers with current AUDs are a heterogeneous group and point to the influence of combat-related PTSD symptoms in the development of AUDs following deployment. Keywords: posttraumatic stress disorder, alcohol use disorders, veterans
related problems postdeployment (Jacobson et al., 2008) These problems are associated with impaired functioning and quality of life (Kehle et al., 2011). Although it is clear that alcohol use is prevalent and problematic among military personnel, we are limited to mostly cross-sectional research, obtained after combat exposure, from previous generations of veterans to generate hypotheses about why some returning soldiers develop alcohol use disorders (AUDs) following deployment, whereas others do not. Prospective research that assesses how predeployment and deployment-related risk factors predict development of AUDs is sorely needed. Additionally, meaningful heterogeneity may exist among veterans diagnosed with an AUD. Specifically, military personnel whose AUD developed prior to deployment may be more likely to have developed such problems in response to preexisting risk characteristics (i.e., personality traits) than deployment-related risk factors. Alternatively, those who do not develop an AUD until after deployment may be more likely to drink in response to deployment-related factors, like posttraumatic stress disorder (PTSD) symptom severity. These groups may have different reasons for drinking and unique AUD-maintaining factors and therefore may respond differently to treatment. For example, individuals with predeployment onset of an AUD may drink for a broad range of reasons (e.g., to enjoy alcohol use, to influence sociability, to regulate mood) and thus, may be more responsive to traditional evidence-based AUD treatments, whereas those with postdeployment onset may often drink in an effort to self-medicate
Alcohol use in the military is a significant problem. Heavy drinking is endorsed by one in six service members (Bray & Hourani, 2007), and approximately 15% of soldiers returning from combat deployments to Iraq (Operation Iraqi Freedom; OIF) and Afghanistan (Operation Enduring Freedom [OEF]) report alcohol-
This article was published Online First August 8, 2011. Shannon M. Kehle and Laura A. Meis, Center for Chronic Disease Outcomes Research, Minneapolis Veteran Affairs Health Care System, Minneapolis, MN; Department of Medicine, University of Minnesota; Melissa A. Polusny, Department of Psychiatry, Center for Chronic Disease Outcomes Research, Minneapolis Veteran Affairs Health Care System, University of Minnesota, Minneapolis, MN; Amanda G. Ferrier-Auerbach and Christopher R. Erbes, Department of Psychiatry, Minneapolis Veteran Affairs Health Care System, Minneapolis, MN; University of Minnesota; Paul A. Arbisi, Departments of Psychology and Psychiatry, Minneapolis Veteran Affairs Health Care System, University of Minnesota. This research was supported by grants from the Minnesota Medical Foundation (Grant #3662-9227-06) and Department of Defense Congressionally Directed Medical Research Program (W81XWH-07-2-0033). This material is the results of work supported with resources and the use of facilities at the Minneapolis Veterans Affairs Medical Center, Minneapolis, MN. The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs or Department of Defense. Correspondence concerning this article should be addressed to Melissa A. Polusny, Minneapolis Veterans Affairs Medical Center (116A9), One Veterans Drive, Minneapolis, MN 55417. E-mail:
[email protected] 42
POSTDEPLOYMENT ALCOHOL USE
mental health problems and, thus, may require treatments that also address deployment-related problems, such as PTSD. The goals of this study were to examine factors uniquely associated with pre- and postdeployment onset AUDs in a sample of OIF soldiers recently returned from a combat deployment, as well as to use prospective data to extend previous findings in regard to AUD risk factors to an OIF sample. We examined the unique role of predeployment personality risk factors (negative emotionality, disconstraint, and low positive emotionality) and postdeployment PTSD symptoms (severity and symptom clusters) in predicting membership in three groups: soldiers who never developed an AUD, those who developed an AUD prior to deployment that persisted postdeployment, and those who developed an AUD after returning from Iraq.
Personality Traits and Alcohol Use Research has consistently found that individuals with substance use disorders, including AUDs, often report high levels of disconstraint and negative emotionality (Graham, Ben-Porath, & McNulty, 1999; Miller, Vogt, Mozley, Kaloupek, & Keane, 2006; Ruiz, Pincus, & Dickinson, 2003). Disconstraint is the tendency toward behavioral disinhibition, as manifested by impulsivity, risk-taking behaviors, and being less bounded by societal constraints (Harkness, McNulty, & Ben-Porath, 1995; Krueger & Markon, 2006) and is consistently associated with the higher order externalizing dimension of personality (tendency to express distress outward; Krueger, McGue, & Iacono, 2001). Individuals with AUDs who report high levels of disconstraint are descriptively similar to Cloninger’s (1987) Type II alcoholics, in that both engage in sensation seeking, risky, and antisocial behavior. Type II alcoholics are likely to use substances because they find alcoholinduced disinhibition pleasurable and alcohol use enjoyable (i.e., drinking because it feels good; Cooper, Russell, Skinner, & Windle, 1992; to regulate positive affect; Cooper et al., 1992; Sher & Slutske, 2003). Alternatively, negative emotionality is the personality disposition to experience negative affect, as manifested by the tendency to worry, catastrophize, feel guilty, and be self-critical (Harkness, McNulty, Ben-Porath & Graham, 2002). Negative emotionality has been demonstrated to increase risk for the development of clinical syndromes, specifically depressive and anxiety disorders, and is associated with the internalizing dimension of personality (tendency to express distress inward; Harkness et al., 1995; Krueger et al., 2001). As such, individuals characterized by high negative emotionality are likely to drink to reduce their negative emotions such as depression and anxiety or to regulate negative affect (Sher & Slutske, 2003). In so doing, these individuals negatively reinforce the drinking behavior. This description is in step with Cloninger’s (1987) Type I alcoholics, who are characterized as anxious individuals who take pains to avoid harm and struggle to stop drinking once they have started. Cloninger’s description of Type I alcoholism is consistent with the selfmedication hypothesis, which posits that individuals drink to cope with distressing emotions or psychiatric symptoms. Of note, neither of Cloninger’s (1987) types of alcoholism nor externalizing– internalizing personality styles are considered discrete, separate entities, as individuals may have characteristics of both types of
43
alcoholism and both externalizing and internalizing traits (Kessler et al., 2005). Internalizing personality styles are also characterized by low levels of positive emotionality, albeit less consistently than negative emotionality (Krueger et al., 2001). Positive emotionality is a broad disposition to experience positive affect, seek out rewarding experiences including social experiences, and to be actively engage in the environment (Harkness et al., 1995). Positive emotionality is linked to the narrower social dimension of introversion– extraversion, but it serves primarily as a broad overarching dimension associated with the capacity to experience pleasure and reward from a variety of sources, including interpersonal interactions (Watson & Clark, 1997). Consequently, an individuals’ standing along the positive emotionality dimension, as evidenced by hedonic capacity and the ability to experience a broad range of social and interpersonal experiences as rewarding, may also play a role in determining the onset of an AUD. It is unfortunate that the literature related to the impact of the social dimension of positive emotionality, extraversion–introversion, on substance use has been mixed, with studies demonstrating a positive association between extroversion and increased substance use and others failing to find such an association (Ferrier-Auerbach et al., 2009; Kilbey, Downey, & Breslau, 1998; Wennberg, 2002). Sher, Grekin, and Williams (2005) postulated that these mixed findings may indicate that individuals high in extroversion are likely to engage in heavy drinking, but as drinking problems emerge, sociability and extroversion decrease. Consequently, longitudinal studies are required to determine whether standing along the personality disposition of positive emotionality serves as a risk factor for problem drinking or represents the consequence of such a pattern of alcohol consumption.
PTSD and Alcohol Use Consistent with the self-medication hypothesis, PTSD may lead to drinking as a way to cope with distressing psychiatric symptoms (Stewart, 1996). Behaviorally, alcohol use may function to reduce negative trauma-related emotions such as anxiety or fear, which in turn reinforces alcohol use. This hypothesis has been supported by numerous studies that have shown that symptoms of PTSD cooccur with or predate changes in alcohol use (e.g., Coffey, Stasiewicz, Hughes, & Brimo, 2006; Ouimette, Read, Wade, & Tirone, 2010; Ruzek, 2003). For example, Coffey et al. (2006) demonstrated that alcohol cravings and emotional distress are greater when individuals are faced with reminders of their traumatic events and that reduction of trauma-related negative emotion also leads to reductions in alcohol craving. Similarly, Ouimette et al. (2010) found that among patients enrolled in a substance use treatment program, weekly fluctuations in PTSD symptomology were associated with the presence of symptoms of alcohol dependence. Of note, some research has suggested that symptoms of PTSD no longer significantly predicted drug and alcohol outcomes after accounting for negative emotionality and disconstraint, assessed following trauma exposure (Miller et al., 2006). Additional research is needed to examine the importance of PTSD in predicting AUD onset above and beyond preexisting personality traits assessed prior to combat exposure, especially among returning veterans.
KEHLE ET AL.
44
In order to better understand the specific aspects of PTSD that may drive the development of AUDs and to elucidate the functional relationship between alcohol use and PTSD (i.e., what type of symptoms maintain AUDs), researchers have focused on the association between drinking behaviors and PTSD symptom clusters. The prominence of specific symptom clusters may also inform prevention and intervention efforts. For example, exposure therapies directly target the reduction of PTSD-specific symptoms (intrusive thoughts, avoidance, and hyperarousal). If PTSDspecific symptoms uniquely predict AUD onset postdeployment, exposure therapies may be important as an early intervention for those with PTSD to prevent AUD onset and as conjoint treatments for those who have already developed a postdeployment onset AUD. Alternatively, if symptoms of dysphoria are uniquely predictive of postdeployment onset, more general interventions may be indicated to prevent or treat AUDs. Although dysphoria symptoms are necessary to a PTSD diagnosis, they are common across multiple mental health conditions, including sleep difficulties, anger–irritability, loss of interest in activities, limited range of affect (Simms, Watson, & Doebbeling, 2002), and they may be more stable, even prior to deployment, than PTSD-specific symptoms (Meis, Erbes, Kaler, Arbisi, & Polusny, in press). Such symptoms may be responsive to a broad number of interventions. Findings in regard to which specific symptoms clusters are uniquely associated with substance use have been inconclusive and have failed to identify symptom clusters that are consistently associated with AUDs. Research has linked substance use uniquely to each of the traditional three clusters of PTSD symptoms in separate investigations: reexperiencing (Bradizza, Stasiewicz, & Paas, 2006; Read, Brown, & Kahler, 2004; Saladin, Brady, Dansky, & Kalpatrick, 1995), avoidance (Saladin et al., 1995), and hyperarousal (Stewart, Conrad, Phil, & Dongier, 1999). Further research is needed to sort out these mixed findings. Additionally, symptoms of dysphoria have yet to be isolated and compared to PTSD-specific symptoms or personality in their ability to predict AUD onset. Finally, research on PTSD symptom clusters and substance use disorders has yet to be extended to OEF–OIF samples.
This Study Important differences in risk profiles may exist between those who develop problematic drinking after deployment, those who have a predeployment history of an AUD and struggle with drinking following deployment, and those who, despite exposure to a combat deployment, remain free of an AUD diagnosis. Each group may differ on each of the assessed personality traits, PTSD symptoms, and PTSD symptom clusters. Examining how the profiles of significant predictors for each of these three groups differ may help in effectively targeting intervention efforts and understanding differences among these groups of individuals. As a result, we divided our sample of National Guard soldiers deployed to Iraq into individuals who (a) had no current or historical AUD (never group); (b) met criteria for an AUD postdeployment, the onset of which was prior to deployment (persistent AUD group); and (c) met criteria for an AUD postdeployment, the onset of which was after deployment (new onset AUD group). We expected that predeployment personality traits of greater negative emotionality and greater disconstraint would place veter-
ans at risk for developing an AUD, regardless of the timing of onset. Therefore, we expected greater rates of these traits among those with either a current or past AUD (persistent AUD and new onset AUD groups) than the never group. Associations between group membership and positive emotionality were largely exploratory, due to mixed findings suggesting no association, negative associations (due to its link with greater internalizing) or positive associations (due to greater extroversion and sociability). Second, we expected that postdeployment PTSD symptomology would differentiate the new onset AUD group from the other two groups, such that higher PTSD symptomology would be a unique predictor of new onset AUDs, above and beyond the influence of personality. Finally, we examined the unique predictive value of PTSD symptom clusters in differentiating AUD onset group membership. Given the mixed literature in regard to symptom clusters cited above, we had no a priori hypotheses in regard to which symptom clusters would significantly differentiate across these groups. Finally, given the dearth of prospective research on the onset of AUDs among combat deployed OEF/OIF soldiers, we also included all possible comparisons among these three groups on each of the predictors of interest (negative emotionality, positive emotionality, disconstraint, and postdeployment PTSD) to probe for any unanticipated differences.
Method Participants and Procedures Participants were drawn for this study from a larger, prospective longitudinal study of 522 National Guard Brigade Combat Team soldiers deployed to Iraq from March 2006 to July 2007 (Readiness and Resilience in National Guard Soldiers; RINGS Study). As part of the larger study, soldiers provided written informed consent and were administered a battery of self-report measures approximately one month prior to deployment to OIF (predeployment survey). Soldiers were assessed again 3– 6 months after their return through a mailed survey (postdeployment survey). Among other constructs, the predeployment survey assessed predeployment personality traits and baseline PTSD symptomotology; postdeployment surveys assessed deployment-related experiences, postdeployment risk and resilience factors, and psychosocial functioning (including PTSD symptomology). Consistent with standard mail survey methodology, procedures involved repeated mailings and a $50 incentive (Dillman, Smyth, & Christian, 2009). Eighty-one percent (n ⫽ 424) of the predeployment sample completed postdeployment surveys. There were no differences between soldiers who did and did not respond to the postdeployment survey in terms of gender, rank, predeployment vulnerability factors, predeployment protective factors, or baseline symptoms of PTSD at predeployment. Nonresponders had less education and were younger, more likely to be unmarried, and more likely to be from ethnic– racial minority groups than responders (Polusny et al., 2011). All participants from the predeployment sample were invited to participate in a structured diagnostic interview. Interviews were administered 6 to 12 months following return from deployment and conducted either in person at the Minneapolis Veterans Affairs (VA) Medical Center (71%) or over the telephone (29%). Participants were compensated $130 for their time following completion of the structured interviews. Eighty-two percent of postdeployment
POSTDEPLOYMENT ALCOHOL USE
survey responders (66.7% of the predeployment sample) participated in diagnostic interviews and were included in the present analyses (n ⫽ 348). Among postdeployment survey responders, no significant differences were found between interview participants and nonparticipants on age, ethnicity, rank, marital status, selfreported distress (depression and PTSD symptomology), quality of life, or social adjustment. However, interview participants were more likely to report some college education, 2(1, N ⫽ 424) ⫽ 12.96, p ⬍ .001. Study protocols were approved by Institutional Review Boards for the Minneapolis VA Medical Center, University of Minnesota, and Department of Defense as well as the Minnesota National Guard command. Participants were mostly male (87%), White–Caucasian (93%), and enlisted rank (87%); half (50%) were married, and the average participant was 31.30 years old (SD ⫽ 9.5). Soldiers reported high levels of exposure to potentially traumatic events, including combat and other war-related events: 91% participated in combat missions–patrols; 94% participated in units that received small arms incoming fire; 55% reported attack by either civilians, terrorists, or both; and 22% reported participating in combat during which they believe they killed someone.
Measures Alcohol use disorders. Alcohol use disorders were assessed postdeployment through the Substance Use Disorders Module of the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM–IV–TR; American Psychiatric Association [APA], 2000) Non PatientEdition Research Version (SCID-I-RV/NP; First, Spitzer, Gibbon, & Williams, 2002). Diagnostic data obtained by the SCID-I were used to determine whether participants had current (e.g., postdeployment) AUDs and whether they met criteria for alcohol abuse or dependence at any time in their lives prior to deployment. The SCID-I is frequently used as a gold standard for assessing clinical diagnoses (e.g., Kessler et al., 2006; Shear et al., 2000). Reliability and validity of the instrument has been demonstrated across multiple studies (Kidorf, Brooner, King, Stoller, & Wertz, 1998; Kranzler, Kadden, Babor, Tennen, & Rounsaville, 1996). For example, specific to the Substance Use Disorders Module, multisite reliability of 1.0 has been found for diagnosis and a test–retest (7–10 day interval) of .76 –.77 (Zanarini et al., 2000). The SCID has been shown to yield reliable diagnoses when administered over the telephone (Ruskin et al., 1998). Good concurrent, discriminant, and predictive validity for both current and life-time substance use diagnoses have been established (Kranzler et al., 1996). PTSD symptom severity. The PTSD Checklist (PCL; Weathers, Litz, Herman, Huska, & Keane, 1993) was used to assess the severity of PTSD symptoms both pre- and postdeployment. Respondents were asked to rate 17 items (5-point Likert scale), each corresponding to one of the 17 DSM–IV–TR symptoms used for diagnosing PTSD ( APA, 2000; current sample, ␣ ⫽ .93). The PCL has demonstrated good reliability and validity (Weathers et al., 1993). It correlates significantly with alternative instruments that assess self-reported PTSD symptoms and provides predictive utility for diagnoses of PTSD established through structured clinical interview (Blanchard, Jones-Alexander, Buckley, & Forneris, 1996). A PTSD symptom severity score was calculated by summing the 17 items. We also examined PTSD symptoms clusters by
45
using the four-factor dysphoria model proposed by Simms, Watson, and Doebbeling (2002). We chose to use the dysphoria model because a previously conducted factor analysis of National Guard soldiers’ data (including this sample) found that the dysphoria model of PTSD was a better fit for the data both pre- and postdeployment than either the DSM–IV symptom clusters (APA, 2000) or the four-factor numbing model proposed by King, Leskin, King, and Weathers (1998; Meis et al., in press). Predeployment personality. Negative emotionality (NEM), positive emotionality (PEM), and disconstraint (CON) were assessed prior to deployment through abbreviated versions of scales from the Multiphasic Personality Inventory Personality–2 (MMPI-2) Psychopathology Five scales (Harkness et al., 1995). It was necessary to use abbreviated scales due to time constraints in the context of predeployment data collection; items were rationally selected to reflect the scope of the dimensions being assessed. Higher scores on NEM indicate greater negative emotionality, higher scores on PEM designate a lack of positive emotionality, and higher disconstraint scores show greater tendencies toward disconstraint. Measures used in this study were abbreviated versions of the original scales: NEM (23 out of 33 items, ␣ ⫽ .82), PEM (20 of 34 items, ␣ ⫽ .61), and CON (16 of 29 original items, ␣ ⫽ .56)). Internal consistencies of these brief scales are adequate and similar to those found by scale authors by using a nonclinical sample (NEM, ␣ ⫽ .84; PEM, ␣ ⫽ .71; CON, ␣ ⫽ .71; Harkness et al., 1995).
Interviewer Training and Reliability Interviewers were eight graduate, doctoral-level students who were extensively trained and supervised weekly by study investigators. Interviewers received a day-long training in administering the SCID-I and viewed videotaped training examples of others administering the instrument. A second training to prevent drift was conducted approximately 3 months later. A subset of interviews (10%), including a representative proportion of phone interviews, was scored independently by an additional rater who listened to interview recordings and calculated reliability. SCID-I interrater agreement for alcohol dependence was 100% ( ⫽ 1.0) and for alcohol abuse was 84% ( ⫽ .56); discrepancies were resolved through consultation with the investigator team.
Analyses We first assigned participants to alcohol use categories based on their diagnoses and time of onset. Those who met criteria for an AUD prior to deployment but not postdeployment were not included in the analyses. One-way analysis of variance (ANOVA) tests were used to examine associations between alcohol use categories and hypothesized predictor variables. Predictor variables that were significantly associated with alcohol use category were included in the main analyses. For the main analyses, we conducted two sets of multinomial logistic regressions to examine how personality variables and PTSD symptoms were related to alcohol use category. For the first set of regression analyses, we examined total postdeployment PTSD symptomology (total PCL score). For the second set, we examined the unique influence of PTSD symptom clusters as defined by Simms et al.’s (2002) dysphoria model (intrusions, avoidance, hyperarousal, and dys-
KEHLE ET AL.
46
phoria). As multinomial regression compares each group to a single reference group, two multinomial regressions were performed to allow for comparisons across all drinking categories. Predeployment PTSD symptomology was included as a control variable for all multinomial regressions. In addition, Pearson chisquare tests and one-way ANOVAs were used to examine associations between demographic variables previously associated with AUDs (Brennan, Moos, & Mertens, 1994; Ferrier-Auerbach et al., 2009; Jacobson et al., 2008; Parker, Weaver, & Calhoun, 1995) and alcohol use category. Demographic variables that were significantly associated with alcohol use categories were included in the main analyses as control variables. All continuously distributed variables were converted to z scores prior to entry into the regression models and all predictor variables were entered into the model in the same block. Two participants had missing AUD data and were not included in the analyses. All analyses were conducted using SPSS Version 17.
Results Rates of Alcohol Use Disorders Thirteen percent (n ⫽ 45) of the panel met criteria for a current AUD following return from deployment to Iraq. Of those who met criteria for a current AUD, 73% (n ⫽ 33) were diagnosed with dependence, whereas 27% (n ⫽ 12) met criteria for abuse. Of the 45 soldiers with a current diagnosis, 28 (62%) had an onset prior to deployment to OIF (persistent AUD group) and 17 (38%) had a postdeployment onset (new onset AUD group). Thus, 8% (n ⫽ 17) of the panel had a new onset AUD. An additional 89 soldiers (26%) had an alcohol use disorder in the past but did not meet criteria postdeployment. Sixty-one percent (n ⫽ 212) had never met criteria for an alcohol use disorder (never group).
Correlates and Predictors of Alcohol Use Category Pearson chi-square tests and one-way ANOVAs were used to examine the bivariate associations between demographic, personality, overall PTSD symptoms, PTSD symptom clusters, and al-
cohol use categories. As shown in Table 1, all personality and PTSD symptom variables were associated with alcohol use category. Of the demographic variables, only marital status had a significant association. Thus, gender, age, race, and education were not included as control variables in the regression analyses. We first determined the relative contribution of personality variables and overall PTSD symptom severity in the prediction of alcohol use category (never, persistent AUD, and new onset AUD; see Table 2). The deviance goodness-of-fit test indicated that the model was a good fit for the data, 2(472, N ⫽ 243) ⫽ 212.56, p ⫽ 1.00. The only significant difference between the new onset AUD and persistent AUD group was that soldiers with new onset AUD reported more severe symptoms of postdeployment PTSD. Compared to the never AUD group, those soldiers who developed new onset AUD following deployment reported lower levels of positive emotionality, higher levels of disconstraint, and higher levels of overall postdeployment PTSD symptoms. Negative emotionality and disconstraint were higher among those in the persistent AUD group compared to those with no lifetime AUD. We then conducted a second multinomial regression by using the symptom clusters suggested by Simms et al. (2002; see Table 3). The model was a good fit for the data, 2(452, N ⫽ 236) ⫽ 198.16, p ⫽ 1.00. The only symptom cluster that was significantly associated with AUD category was avoidance; avoidance significantly differentiated the new onset AUD group from the never and persistent AUD groups.
Discussion The goal of this study was to use longitudinal data to examine the use of personality traits and PTSD symptomology in differentiating pre- and postdeployment onset AUDs among National Guard soldiers deployed to Iraq. Consistent with our hypothesis, postdeployment PTSD symptoms, particularly avoidance symptoms, independently predicted the onset of postdeployment AUDs, after controlling for predeployment levels of PTSD. These results are consistent with prior research that has shown that PTSD symptoms are associated with heightened risk of increased drink-
Table 1 Associations Between Demographic Characteristics, Personality, Posttraumatic Stress Disorder (PTSD) Symptoms, and Alcohol Use Category (N ⫽ 346) Variable
Never AUD (n ⫽ 212)
Persistent AUD (n ⫽ 28)
New onset AUD (n ⫽ 17)
Test statistic
P
Gender (male) Race (Caucasian) Marital Status (married) Education (some college) Age NEM PEM CON PTSD severity Intrusions Avoidance Hyperarousal Dysphoria
n ⫽ 187 (88.2%) n ⫽ 195 (92.0%) n ⫽ 111 (54.7%) n ⫽ 182 (87.1%) M ⫽ 31.13 (SD ⫽ 10.08) M ⫽ 4.67 (SD ⫽ 3.57) M ⫽ 6.05 (SD ⫽ 2.81) M ⫽ 7.78 (SD ⫽ 2.48) M ⫽ 33.47 (SD ⫽ 13.20) M ⫽ 9.20 (SD ⫽ 1.02) M ⫽ 3.62 (SD ⫽ 1.94) M ⫽ 4.54 (SD ⫽ 2.18) M ⫽ 15.99 (SD ⫽ 7.02)
n ⫽ 26 (92.9%) n ⫽ 26 (92.9%) n ⫽ 8 (29.6%) n ⫽ 26 (92.9%) M ⫽ 29.96 (SD ⫽ 6.87) M ⫽ 8.79 (SD ⫽ 4.58) M ⫽ 6.75 (SD ⫽ 3.23) M ⫽ 9.93 (SD ⫽ 2.61) M ⫽ 35.93 (SD ⫽ 11.22) M ⫽ 9.04 (SD ⫽ 3.22) M ⫽ 3.93 (SD ⫽ 1.78) M ⫽ 4.96 (SD ⫽ 2.30) M ⫽ 17.89 (SD ⫽ 7.02)
n ⫽ 13 (76.5%) n ⫽ 17 (100.0%) n ⫽ 4 (25.0%) n ⫽ 13 (76.5%) M ⫽ 30.53 (SD ⫽ 11.65) M ⫽ 7.76 (SD ⫽ 5.11) M ⫽ 7.82 (SD ⫽ 3.91) M ⫽ 9.53 (SD ⫽ 3.28) M ⫽ 49.12 (SD ⫽ 12.87) M ⫽ 12.82 (SD ⫽ 3.19) M ⫽ 6.53 (SD ⫽ 2.12) M ⫽ 6.00 (SD ⫽ 2.45) M ⫽ 23.76 (SD ⫽ 8.14)
(2) ⫽ 2.76 2(2) ⫽ 1.48 2(2) ⫽ 10.26 2(2) ⫽ 2.52 F(2, 254) ⫽ 0.19 F(2, 254) ⫽ 18.24 F(2, 254) ⫽ 3.34 F(2, 254) ⫽ 11.50 F(2, 253) ⫽ 11.53 F(2, 251) ⫽ 6.96 F(2, 252) ⫽ 17.72 F(2, 251) ⫽ 3.68 F(2, 251) ⫽ 9.89
.251 .477 .006 .284 .829 ⬍.001 .037 ⬍.001 ⬍.001 .001 ⬍.001 .027 ⬍.001
Note.
NEM ⫽ negative emotionality; PEM ⫽ positive emotionality; CON ⫽ disconstraint.
2
POSTDEPLOYMENT ALCOHOL USE
47
Table 2 Multinomial Logistic Regression of Marital Status, Personality, and Total Posttraumatic Stress Disorder (PTSD) Symptom Severity as Predictors of Postdeployment Alcohol Use Category Persistent AUD Comparator Never AUD
Persistent AUD
New onset AUD
IVs
b
SE b
Wald
OR (95% CI)
b
SE b
Wald
OR (95% CI)
NEM PEM CON PTSD NEM PEM CON PTSD
0.90 0.28 1.03 ⫺0.28 — — — —
0.29 0.24 0.28 0.27 — — — —
10.01 1.38 13.73 1.09 — — — —
2.46ⴱⴱ (1.41–4.30) 1.32 (0.83–2.11) 2.80ⴱⴱⴱ (1.62–4.81) 0.30 (0.44–1.28) — — — —
0.38 0.80 0.96 0.74 ⫺0.52 0.52 ⫺0.07 1.03
0.39 0.31 0.34 0.30 0.40 0.34 0.39 0.36
0.97 6.77 7.98 6.33 1.69 2.38 0.03 7.99
1.46 (0.69–3.10) 2.23ⴱⴱ (1.22–4.07) 2.62ⴱⴱ (1.34–5.11) 2.11ⴱ (1.18–3.76) 0.59 (0.27–1.31) 1.68 (0.87–3.26) 0.87 (0.44–1.99) 2.80ⴱⴱ (1.37–5.71)
Note. IVs ⫽ negative emotionality, positive emotionality, disconstraint, PTSD symptom severity; CI ⫽ confidence interval; AUD ⫽ alcohol use disorder; NEM ⫽ negative emotionality; PEM ⫽ positive emotionality; CON ⫽ disconstraint. Predeployment PTSD symptoms and marital status were controlled for in all models. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.
ing behavior and often precede substance use disorders (e.g., McFarlane, 1998). Among World War II and Vietnam veterans diagnosed with both PTSD and alcohol abuse, it was found that the PTSD emerged approximately 7 years before their alcohol abuse diagnosis (Davidson, Kudler, Saunders, & Smith, 1990). More recently, the Millennium Cohort Study, an ongoing longitudinal study of a large panel of military service members, found that PTSD symptoms predicted alcohol-related problems among Reserve–National Guard soldiers following deployment (Jacobson et al., 2008). PTSD’s unique association with new onset AUDs suggests that within our sample, a subset of soldiers may have begun drinking to manage PTSD symptoms following deployment to a combat zone. This is consistent with the self-medication hypothesis that posits
that following emotional disregulation, individuals may develop problematic drinking behaviors due to alcohol’s strong anesthetic properties (Khantzian, 1999). Further, our examination of the symptom clusters of PTSD found that avoidance was the only cluster associated with alcohol use category, with greater avoidance differentiating the new onset category from those with a persistent diagnosis of an AUD and those with no lifetime history of AUD. It has been suggested that among individuals with PTSD, alcohol use may function as a method of behavioral and emotional avoidance (Stewart, 1996). The behavioral avoidance function is congruent with Conger’s (1951) tension reduction theory of alcohol abuse, which posits that because alcohol use reduces tension (e.g., reduces anxiety), the use of alcohol prior to encountering a trauma-related cue is negatively reinforced, leading to continued
Table 3 Multinomial Logistic Regression of Marital Status, Personality, and Total Posttraumatic Stress Disorder (PTSD) Symptom Clusters as Predictors of Postdeployment Alcohol Use Category Prior AUD Comparator Never AUD
Persistent AUD
IVs NEM PEM CON Intrus Avoid Arousal Dysphor NEM PEM CON Intrus Avoid Arousal Dysphor
b 0.94 0.25 1.03 ⫺0.12 ⫺0.04 0.15 ⫺0.01 — — — — — — —
SE b 0.29 0.25 0.29 0.10 0.19 0.15 0.05 — — — — — — —
Wald 10.24 0.99 12.68 1.39 0.05 0.95 0.05 — — — — — — —
New onset AUD OR (95% CI) ⴱⴱ
2.56 (1.44–4.56) 1.28 (0.79–2.10) 2.79ⴱⴱⴱ (1.59–4.91) 0.89 (0.73–1.08) 0.96 (0.66–1.40) 1.16 (0.86–1.55) 0.99 (0.90–1.09) — — — — — — —
b
SE b
Wald
OR (95% CI)
0.40 0.73 0.88 0.07 0.50 ⫺0.03 ⫺0.05 ⫺0.55 0.48 ⫺0.15 0.19 0.54 ⫺0.18 ⫺0.04
0.42 0.35 0.36 0.12 0.21 0.19 0.07 0.44 0.39 0.41 0.15 0.25 0.23 0.07
0.90 4.51 5.97 0.32 5.97 0.03 0.48 1.55 1.58 0.13 1.68 4.61 0.61 0.23
1.49 (0.66–3.36) 2.08ⴱ (1.06–4.10) 2.41ⴱ (1.19–4.89) 1.07 (0.85–1.35) 1.65ⴱ (1.10–2.47) 0.97 (0.66–1.41) 0.96 (0.84–1.09) 0.58 (0.25–1.37) 1.62 (0.76–3.45) 0.86 (0.39–1.94) 1.21 (0.91–1.60) 1.72ⴱ (1.05–2.83) 0.84 (0.54–1.30) 0.97 (0.83–1.12)
Note. IVs ⫽ negative emotionality, positive emotionality, disconstraint, intrusion symptom cluster, avoidance symptom cluster, hyperarousal symptoms cluster, dysphoria symptom cluster; CI ⫽ confidence interval; AUD ⫽ alcohol use disorder; NEM ⫽ negative emotionality; PEM ⫽ positive emotionality; CON ⫽ disconstraint; Intrus ⫽ intrusion symptom cluster; Avoid ⫽ avoidance symptom cluster; Arousal ⫽ hyperarousal symptom cluster; Dysphor ⫽ dysphoria symptom cluster. Predeployment PTSD symptoms and marital status were controlled for in all models. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.
48
KEHLE ET AL.
use. For example, a soldier with PTSD may consume alcohol prior to driving because being in traffic triggers trauma-related memories. If the alcohol successfully diminishes the anxiety associated with driving, the alcohol use will be reinforced and the soldier will continue to drink. With regard to emotional avoidance, if soldiers avoid trauma cues to avoid the negative emotions that follow such exposure, alcohol may aid in diminishing the experience of negative emotions that result from reminders of the trauma (Kosten & Krystal, 1988). Krystal (1984) suggested that combat veterans with PTSD begin to dread the experience of such emotions and use alcohol to reduce or numb those experiences. Further research will be needed to clarify these possible functional relationships and explanatory mechanisms between PTSD-related avoidance and alcohol use following a combat deployment. Three predeployment personality variables (negative emotionality, positive emotionality, and disconstraint) were also significant predictors of AUD category. Higher levels of negative emotionality and disconstraint differentiated the persistent AUD group from those who have never met criteria for an AUD. This is consistent with our findings from this sample prior to deployment, in which both negative emotionality and disconstraint predicted predeployment binge drinking (Ferrier-Auerbach et al., 2009). This study, however, suggests that findings in regard to the relationship between personality and alcohol use problems may explain AUDs with predeployment onsets but may not apply to soldiers who develop new AUD diagnoses following deployment. Although disconstraint was associated with new onset AUD diagnoses, lowered positive emotionality, rather than heightened negative emotionality, differentiated those with new onset AUDs from the never AUD group. In fact, negative emotionality failed to distinguish the new onset AUD group from any others after accounting for the influence of PTSD symptoms. Research that examines the relationship between low positive emotionality and AUDs is limited. It has been suggested that individuals with low levels of positive emotionality are likely to show the internalizing form of PTSD, which is characterized by anhedonia and depression (Miller, 2003; Miller, Kaloupek, Dillon, & Keane, 2004). However, the externalizing form of PTSD, which is associated with disconstraint, is more likely to be comorbid with alcohol use problems and other problems associated with behavioral dyscontrol. The discrepancy between the Miller (2003) and Miller et al. (2004) findings may be accounted for by the cross sectional design of their study and the interval between the traumatic experience and assessment of personality. Nonetheless, further research that examines the role of positive emotionality in the development of postdeployment AUDs is warranted. This study advances the field of AUDs by separately examining soldiers’ postdeployment AUDs based on their time of onset (prevs. postcombat deployment). Further strengths of the study include the longitudinal design and the use of gold standard interviews to diagnose AUDs. The study does have several important limitations. First, although the data suggest that PTSD symptoms preceded alcohol use in the new onset group, we cannot rule out the possibility that the two developed simultaneously, given their concurrent measurement, or that the alcohol use disorder preceded the increase in PTSD symptomology. Although this seems unlikely given that the trauma likely occurred in-theater, where alcohol use is prohibited, it may be that soldiers did not develop symptoms of PTSD immediately following the trauma but rather after they
returned home and began using alcohol. Second, the modest internal validity of the abbreviated PSY-5 scale of disconstraint must be noted. Further, although the sample was demographically representative of the brigade (Polusny et al., 2011) participants were self-selected and were almost exclusively Caucasian, Midwestern, National Guard soldiers. Thus, it is possible that the findings might not generalize to the larger military population. In addition, although our analyses suggest few differences between responders and nonresponders, the findings may have been influenced by either postdeployment survey or interview response biases. Finally, the new onset AUD category had few participants, which could lead to unstable findings or limited power to identify differences of a small magnitude. Further validation in a larger sample is warranted. Despite these limitations, this study provides evidence that soldiers with postdeployment AUDs are a heterogeneous group. By examining the timing of AUD onset, findings of this study contribute to a better understanding of the etiology of postdeployment AUDs. In particular, we were able to demonstrate that combat-related PTSD, the PTSD symptom cluster of avoidance, and low positive emotionality were associated with greater risk for the development of new onset AUDs after return from a combat deployment. Although previous attempts at matching alcohol treatment have yielded disappointing results (e.g., Project MATCH Research Group, 1997), our findings may have implications for the treatment of soldiers with postdeployment AUDs. Broadly speaking, soldiers who develop new onset AUDs following deployment in the context of PTSD symptomotology may be more likely to benefit from concurrent substance use and PTSD treatment, with a focus on reducing trauma-specific avoidance, while those with persistent AUDs may benefit from traditional substance programs that focus more generally on management of negative mood states and impulse control.
References American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author. Blanchard, E. B., Jones-Alexander, J., Buckley, T. C., & Forneris, C. A. (1996). Psychometric properties of the PTSD Checklist (PCL). Behaviour Research and Therapy, 34, 669 – 673. Bradizza, C. M., Stasiewicz, P. R., & Paas, N. D. (2006). Relapse to alcohol and drug use among individuals diagnosed with co-occurring mental health and substance use disorders: A review. Clinical Psychology Review, 26, 162–178. Bray, R. M., & Hourani, L. L. (2007). Substance use trends among active duty military personnel: Findings from the United States Department of Defense Health Related Behavior Surveys, 1980 –2005. Addiction, 102, 1092–1101. Brennan, P. L., Moos, R. H., & Mertens, J. R. (1994). Personal and environmental risk factors as predictors of alcohol use, depression, and treatment-seeking: A longitudinal analysis of late-life problem drinkers. Journal of Substance Abuse, 6, 191–208. Cloninger, C. R. (1987). Neurogenetic adaptive mechanisms in alcoholism. Science, 236, 410 – 416. Coffey, S. F., Stasiewicz, P. R., Hughes, P. M., & Brimo, M. L. (2006). Trauma-focused imaginal exposure for individuals with comorbid posttraumatic stress disorder and alcohol dependence: Revealing mechanisms of alcohol craving in a cue reactivity paradigm. Psychology of Addictive Behaviors, 20, 425– 435. Conger, J. J. (1951). The effects of alcohol on conflict behavior in the albino rat. Quarterly Journal of Studies on Alcohol, 12, 1–29.
POSTDEPLOYMENT ALCOHOL USE Cooper, M., Russell, M., Skinner, J. B., & Windle, M. (1992). Development and validation of a three dimensional measure of drinking motives. Psychological Assessment, 4, 123–132. Davidson, J. R. T., Kudler, H. S., Saunders, W. B., & Smith, R. D. (1990). Symptom and comorbidity patterns in World War II and Vietnam veterans with posttraumatic stress disorder. Comprehensive Psychiatry, 31, 162–170. Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys: The tailored design method (3rd ed.). Hoboken, NJ : Wiley. Ferrier-Auerbach, A. G., Kehle, S. M., Erbes, C. R., Arbisi, P. A., Thuras, P., & Polusny, M. A. (2009). Predictors of alcohol use prior to deployment in National Guard Soldiers. Addictive Behaviors, 34, 625– 631. First, M. B., Spitzer, R. L., Gibbon, M., & Williams, J. B. W. (2002). Structured clinical interview for DSM–IV–TR Axis I disorders, Research Version, Non-patient Edition. (SCID-I/NP). New York, NY: Biometrics Research, New York State Psychiatric Institute. Graham, J. R., Ben-Porath, Y. S., & McNulty, J. (1999). Using the MMPI-2 in outpatient mental health settings. Minneapolis, MN: University of Minnesota Press. Harkness, A. R., McNulty, J. L., & Ben-Porath, Y. S. (1995). The Personality Psychopathology Five (PSY-5): Constructs and MMPI-2 scales. Psychological Assessment, 7, 104 –114. Harkness, A. R., McNulty, J. L., Ben-Porath, Y. S., & Graham, J. R. (2002). MMPI-2 Personality-Psychopathology Five (PSY-5) Scales: Gaining an overview for case conceptualization and treatment planning. Minneapolis, MN: University of Minnesota Press. Jacobson, I. G., Ryan, M. A. K., Hooper, T. I., Smith, T. C., Amoroso, P. J., Boyko, E. J., . . . Bell, N. S. (2008). Alcohol use and alcohol-related problems before and after military combat deployment. Journal of the American Medical Association, 300, 663– 675. Kehle, S. M., Reddy, M., Ferrier-Auerbach, A. G., Erbes, C. A., Arbisi, P. A., & Polusny, M. A. (2011). Psychiatric diagnoses, comorbidity, and functioning in National Guard troops deployed to Iraq. Journal of Psychiatric Research, 45, 126 –132. Kessler, R. C., Akiskal, H. S., Angst, J., Guyer, M., Hirschfeld, R. M., Merikangas, K. P., & Stang, P. E. (2006). Validity of the assessment of bipolar spectrum disorders in the WHO CIDI 3.0. Journal of Affective Disorders, 96, 259 –269. Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM–IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 593– 602. Khantzian, E. J. (1999). Treating addiction as a human process. Northvale, NJ: Jason Aronson. Kidorf, M., Brooner, R. K., King, V. L., Stoller, K. B., & Wertz, J. (1998). Predictive validity of cocaine, sedative, and alcohol dependence diagnoses. Journal of Consulting and Clinical Psychology, 66, 168 –173. Kilbey, M., Downey, K., & Breslau, N. (1998). Predicting the emergence and persistence of alcohol dependence in young adults: The role of expectancy and other risk factors. Experimental and Clinical Psychopharmacology, 6, 149 –156. King, D. W., Leskin, G. A., King, L. A., & Weathers, F. W. (1998). Confirmatory factor analysis of the Clinician-Administered PTSD Scale: Evidence for the dimensionality of posttraumatic stress disorder. Psychological Assessment, 10, 90 –96. Kosten, T. R., & Krystal, J. (1988). Biological mechanisms in posttraumatic stress disorder: Relevance for substance abuse. In M. Galanter (Ed.), Recent developments in alcoholism (Vol. 6, pp. 49 – 68). New York, NY: Plenum Press. Kranzler, H. R., Kadden, R. M., Babor, T. F., Tennen, H., & Rounsaville, B. J. (1996). Validity of the SCID in substance abuse patients. Addiction, 91, 859 – 868. Krueger, R. F., & Markon, K. E. (2006). Understanding psychopathology:
49
Melding behavior genetics, personality, and quantitative psychology to develop an empirically-based model. Current Directions in Psychological Science, 15, 113–117. Krueger, R. F., McGue, M., & Iacono, W. G. (2001). The higher-order structure of common DSM mental disorders: Internalization, externalization, and their connections to personality. Personality and Individual Differences, 31, 1245–1259. Krystal, H. (1984). Psychoanalytic views on human emotional damages. In B. A. Vander Kolk (Ed.), Posttraumatic stress disorders: Psychological and biological sequelae (pp. 1–28). Washington DC: American Psychiatric Press. McFarlane, A. C. (1998). Epidemiological evidence about the relationship between PTSD and alcohol abuse: The nature of the association. Addictive Behaviors, 23, 813– 825. Meis, L. A., Erbes, C. R., Kaler, M., Arbisi, P. A., & Polusny, M. A. (in press). The longitudinal latent structure of PTSD among two cohorts of OIF soldiers: Before, during, and following deployment to Iraq. Journal of Abnormal Psychology. Miller, M. W. (2003). Personality and the etiology and expression of PTSD: A three-factor model perspective. Clinical Psychology: Science and Practice, 10, 373–393. Miller, M. W., Kaloupek, D. G., Dillon, A. L., & Keane, T. M. (2004). Externalizing and internalizing subtypes of combat-related PTSD: A replication and extension using the PSY-5 scales. Journal of Abnormal Psychology, 113, 636 – 645. Miller, M. W., Vogt, D. S., Mozley, S. L., Kaloupek, D. G., & Keane, T. M. (2006). PTSD and substance-related problems: The mediating roles of disconstraint and negative emotionality. Journal of Abnormal Psychology, 115, 369 –379. Ouimette, P., Read, J. P., Wade, M., & Tirone, V. (2010). Modeling associations between posttraumatic stress symptoms and substance use. Addictive Behaviors, 35, 64 – 67. Parker, K. D., Weaver, G., & Calhoun, T. (1995). Predictors of alcohol and drug use: A multi-ethnic comparison. The Journal of Social Psychology, 135, 581–590. Polusny, M. A., Erbes, C. R., Murdoch, M., Arbisi, P. A., Thuras, P., & Rath, M. (2011). Prospective risk factors for new onset PTSD in National Guard soldiers deployed to Iraq. Psychological Medicine, 41, 687– 698. Project MATCH Research Group. (1997). Matching alcoholism treatments to client heterogeneity: Project MATCH posttreatment drinking outcomes. Journal of Studies on Alcohol, 58, 7–29. Read, J. P., Brown, P. J., & Kahler, C. W. (2004). Substance use and posttraumatic stress disorders: Symptom interplay and effects on outcome. Addictive Behaviors, 29, 1665–1672. Ruskin, P. E., Reed, S., Kumar, R., Kling, M. A., Siegel, E., Rosen, M., & Hauser, P. (1998). Reliability and acceptability of psychiatric diagnosis via telecommunication and audiovisual technology. Psychiatric Services, 49, 1086 –1088. Ruiz, M. A., Pincus, A. L., & Dickinson, K. A. (2003). NEO-PI-R predictors of alcohol use and alcohol-related problems. Journal of Personality Assessment, 81, 226 –236. Ruzek, J. I. (2003). Concurrent posttraumatic stress disorder and substance use disorder among veterans: Evidence and treatment issues. In P. Ouimette & P. J. Brown (Eds.), Trauma and substance abuse: Causes, consequences, and treatment of comorbid disorders (pp. 191–207). Washington DC: American Psychological Association. Saladin, M. E., Brady, K. T., Dansky, B. S., & Kilpatrick, D. G. (1995). Understanding comorbidity between PTSD and substance use disorders: Two preliminary investigations. Addictive Behaviors, 20, 643– 655. Shear, M. K., Greeno, C., Kang, J., Ludewig, D., Frank, E., Swartz, H. A., & Hanekamp, M. (2000). Diagnosis of nonpsychotic patients in community clinics. American Journal of Psychiatry, 157, 581–587. Sher, J. K., Grekin, E. R., & Williams, N. A. (2005). The development of
50
KEHLE ET AL.
alcohol use disorders. Annual Review of Clinical Psychology, 1, 493– 523. Sher, K. J., & Slutske, W. S. (2003). Disorders of impulse control. In G. Stricker & T. A. Widiger (Eds.). Handbook of psychology. Vol. 8: Clinical psychology (pp. 195–228). New York, NY: Wiley. Simms, L. J., Watson, D., & Doebbeling, B. N. (2002). Confirmatory factor analyses of posttraumatic stress symptoms in deployed and nondeployed veterans of the Gulf War. Journal of Abnormal Psychology, 111, 637– 647. Stewart, S. H. (1996). Alcohol abuse in individuals exposed to trauma: A critical review. Psychological Bulletin, 120, 83–112. Stewart, S. H., Conrod, P. J., Pihl, R. O., & Dongier, M. (1999). Relations between posttraumatic stress symptom dimensions and substance dependence in a community-recruited sample of substance-abusing women. Psychology of Addictive Behaviors, 13, 78 – 88. Watson, D., & Clark, L. A. (1997). Extraversion and its positive emotional core. In R. Hogan, J. Johnson, & S. Briggs (Eds.), Handbook of personality psychology (pp. 767–793). San Diego, CA: Academic Press.
Weathers, F. W., Litz, B. T., Herman, D. S., Huska, J. A., & Keane, T. M. (1993, October). The PTSD Checklist (PCL): Reliability, validity, and diagnostic utility. Poster presented at the 9th annual meeting of the International Society for Traumatic Stress Studies, San Antonio, TX. Wennberg, P. (2002). The development of alcohol habits in a Swedish male birth cohort. In S. P. Shohov (Ed.), Advances in psychology research (Vol. 15, pp. 121–155). Hauppauge, NY: Nova Science. Zanarini, M. C., Skodol, A. E., Bender, D., Dolan, R., Sanislow, C., Schaefer, E., . . . Gunderson, J. G. (2000). The collaborative longitudinal personality disorders study: Reliability of Axis I and II diagnoses. Journal of Personality Disorders, 14, 291–299.
Received November 4, 2010 Revision received June 7, 2011 Accepted June 8, 2011 䡲
