The Temporal Relationship Between Posttraumatic Stress Disorder andProblem Alcohol Use Following Traumatic Injury

Angela NickersonUNSW Australia

J. Ben BarnesUniversity of Delaware

Mark Creamer and David ForbesUniversity of Melbourne

Alexander C. McFarlaneUniversity of Adelaide

Meaghan O’DonnellUniversity of Melbourne

Derrick SiloveUNSW Australia

Zachary SteelUNSW Australia and Richmond Hospital,

North Richmond NSW, Australia

Richard A. BryantUNSW Australia

Chronic alcohol abuse is a major public health concern following trauma exposure; however, little is knownabout the temporal association between posttraumatic stress disorder (PTSD) symptoms and problem alcoholuse. The current study examined the temporal relationship between PTSD symptom clusters (re-experiencing,effortful avoidance, emotional numbing, and hyperarousal) and problem alcohol use following traumaexposure. This study was a longitudinal survey of randomly selected traumatic injury patients interviewed atbaseline, 3 months, 12 months, and 24 months following injury. Participants were 1,139 injury patientsrecruited upon admission from 4 Level 1 trauma centers across Australia. Participants were assessed using theClinician Administered PTSD Scale and Alcohol Use Disorders Identification Test. Results indicated that highlevels of re-experiencing, effortful avoidance, and hyperarousal symptoms at 12 months were associated withgreater increases (or smaller decreases) in problem alcohol use between 12 and 24 months. Findings alsosuggested that high levels of problem alcohol use at 12 months were associated with greater increases (orsmaller decreases) in emotional numbing symptoms between 12 and 24 months. These findings highlight thecritical importance of the chronic period following trauma exposure in the relationship between PTSDsymptoms and problem alcohol use.

Keywords: trauma, posttraumatic stress disorder, alcohol use, injury

Supplemental materials: http://dx.doi.org/10.1037/a0037920.supp

Alcohol use disorders and posttraumatic stress disorder (PTSD)commonly co-occur following exposure to traumatic events (Hel-zer, Robins, & McEvoy, 1987; Pietrzak, Goldstein, Southwick, &Grant, 2011). Alcohol abuse or dependence is the most common

disorder co-occurring with PTSD among traumatized men, and thesecond most common in women (Kessler, Sonnega, Bromet,Hughes, & Nelson, 1995). Compared with individual PTSD oralcohol/substance use diagnoses, co-occurring PTSD and alcohol

This article was published Online First October 6, 2014.Angela Nickerson, School of Psychology, UNSW Australia; J. Ben

Barnes, Department of Psychology, University of Delaware; MarkCreamer and David Forbes, Australian Center for Posttraumatic MentalHealth and Department of Psychiatry, University of Melbourne; AlexanderC. McFarlane, Center for Military and Veterans’ Health, University ofAdelaide; Meaghan O’Donnell, Australian Center for Posttraumatic MentalHealth and Department of Psychiatry, University of Melbourne; DerrickSilove, School of Psychiatry, UNSW Australia; Zachary Steel, School ofPsychiatry, UNSW Australia and St. John of God Professorial Chair ofTrauma and Mental Health, Richmond Hospital, North Richmond NSW,Australia; Richard A. Bryant, School of Psychology, UNSW Australia.

This study was supported by a National Health and Medical ResearchCouncil Program Grant (568970). Dr. Nickerson was supported by aNational Health and Medical Research Council Clinical Early CareerResearch Fellowship (1037091). The authors gratefully acknowledgeall the participants involved in this study, as well as the editor andanonymous reviewers for their helpful feedback on this article.The authors also gratefully acknowledge the assistance of ProfessorsDaniel and Lynda King with the statistical analyses reported in thisarticle.

Correspondence concerning this article should be addressed to AngelaNickerson, School of Psychology, UNSW Australia, Sydney NSW 2052,Australia. E-mail: anickerson@psy.unsw.edu.au

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Journal of Abnormal Psychology © 2014 American Psychological Association2014, Vol. 123, No. 4, 821–834 0021-843X/14/$12.00 http://dx.doi.org/10.1037/a0037920

821

or substance use disorders are associated with greater PTSD symp-tom severity and functional impairment, poorer treatment re-sponse, faster relapse, and greater psychosocial problems (Back etal., 2000; Breslau, Davis, Peterson, & Schultz, 1997; Read, Brown,& Kahler, 2004; Riggs, Rukstalis, Volpicelli, Kalmanson, & Foa,2003).

Research suggests that, following exposure to trauma, PTSDdevelops prior to substance abuse or problem alcohol use (Chilcoat& Breslau, 1998; Jacobsen, Southwick, & Kosten, 2001; Jacobsonet al., 2008; Keane, Gerardi, Lyons, & Wolfe, 1988; Stewart &Conrod, 2003). Accordingly, the self-medication hypothesis pro-poses that trauma survivors may use alcohol and other substancesto decrease PTSD symptoms (Khantzian, 1985; Leeies, Pagura,Sareen, & Bolton, 2010; McFarlane, 1998). Similarly, the affectiveprocessing model of negative reinforcement asserts that alcohol orsubstance use is motivated by avoidance of negative affect, such asthat elicited by PTSD symptoms (Baker, Piper, McCarthy,Majeskie, & Fiore, 2004; Dvorak, Arens, Kuvaas, Willians, &Kilwein, 2013). The subsequent reduction in negative affect po-tentially reinforces (and potentially increases) alcohol and/or sub-stances use. Accordingly, research suggests that alcohol use as acoping strategy is associated with PTSD symptoms in trauma-exposed groups (Kaysen et al., 2007; Leeies, Pagura, Sareen, &Bolton, 2010; Lehavot, Stappenbeck, Luterek, Kaysen, & Simp-son, 2014; Ullman, Filipas, Townsend, & Starzynski, 2006). Thesefindings indicate that PTSD symptoms may lead to increasedalcohol use as trauma survivors attempt to cope with symptom-related distress.

In contrast, the substance-induced anxiety model posits thatanxiety symptoms can result from chronic excessive alcohol con-sumption (Smith & Randall, 2012). It has been argued that, in thecontext of life stressors, alcohol use may prevent extinction-basedlearning, such that the combination of stress and poor coping skillsexacerbate anxiety (Smith & Randall, 2012). This is supported byresearch indicating that anxiety symptoms decrease significantly inpatients in inpatient alcohol abuse treatment programs (Brown,Irwin, & Schuckit, 1991; Kushner et al., 2005). Further, findingsfrom a longitudinal study of college students suggested that indi-viduals diagnosed with alcohol dependence evidenced signifi-cantly increased anxiety disorders over the subsequent 4 years(Kushner, Sher, & Erickson, 1999). These findings indicate thathigh levels of alcohol use may exacerbate distress, potentiallyleading to subsequent increases in PTSD symptoms.

Overall, research to date has failed to establish a clear temporalassociation between PTSD symptoms and problem alcohol usefollowing trauma, including whether these relationships are con-sistent over time. Investigation of the dynamic temporal sequenc-ing (i.e., directions of influence over time) of PTSD symptoms andproblem alcohol use is essential if we are to understand how PTSDsymptoms and problem alcohol use maintain and/or exacerbateone another, and consequently manage this interrelationship.

The few studies that have investigated the temporal associationbetween PTSD and problem alcohol use have been undertaken inthe context of psychological or pharmacological treatments. Thisresearch has yielded mixed findings regarding the temporal se-quencing of changes in alcohol and/or substance use and changesin PTSD symptoms, with some suggesting that reductions inproblem alcohol use precede changes in PTSD symptoms (Back,Brady, Sonne, & Verduin, 2006), while others indicate that PTSD

reactions change prior to substance dependence (Ouimette, Read,Wade, & Tirone, 2010).

The current study implements bivariate latent difference scorestructural equation modeling to examine the direction of temporalinfluence between problem alcohol use and PTSD symptom clus-ters over a period of two years following exposure to trauma.Previous research has been restricted to mental health treatmentcontexts in which particular symptoms have been the target ofpsychological or pharmacological interventions, potentially influ-encing the course of symptom change. This study is novel as itrepresents the first naturalistic study of temporal ordering ofchange in PTSD symptoms and problem alcohol use over time.

Integrating theoretical models and previous research on PTSDsymptoms, we hypothesize bidirectional relationships betweenPTSD symptoms and problem alcohol use. Specifically, we predictthat more severe re-experiencing, effortful avoidance, emotionalnumbing and hyperarousal symptoms will be associated with in-creases (or smaller decreases) in subsequent problem alcohol use.Additionally, based on the substance-induced anxiety model, wehypothesize that higher levels of problem alcohol use will beassociated with increases (or smaller decreases) in subsequentPTSD symptoms.

Method

Participants

Participants in this study were drawn from the Australian InjuryVulnerability Study (IVS), in which injury survivors were re-cruited upon admission to four Level 1 trauma centers in Australiabetween April 2004 and April 2006. Inclusion criteria for the studywere: 18 to 70 years of age, ability to communicate proficiently inEnglish, and hospital admission of longer than 24 hr followingtraumatic injury. Exclusion criteria included moderate or severehead injury; current psychotic symptoms or active suicidality,temporary visitor to Australia, cognitive impairment, and/or underpolice guard. Participants who met entry criteria were selectedusing an automated assignment procedure; stratified by length ofstay.

Of the 1,590 individuals who met inclusion criteria, 1,139(71.6%) agreed to participate and completed the initial assessment.Individuals who declined to participate did not differ from partic-ipants in terms of gender (�2 � .80, df � 1, p � .23), length ofhospital admission, t(df � 1,082) � .03, p � .88, injury severityscore (ISS), t(df � 1,419) � 1.1, p � .16, or age t(df � 1,475) �1.60, p � .14). At the 3-months follow-up assessment, 150 patientscould not be contacted or declined to participate; 989 were inter-viewed by telephone (86.8% of the initial sample). Of thesepatients, 865 participants of the initial 1,139 completed the 12-month assessment (76.0%) and 830 participants completed the24-month assessment (72.9%). Participants at the 24-monthfollow-up interview did not differ from those who did not partic-ipate in terms of gender (�2 � 1.91, df � 1, p � .17), length ofhospital admission, t(1,120) � .43, p � .67, or ISS, t(1,120) �1.69, p � .09. Those who did not participate in the follow-upassessment had significantly greater PTSD symptoms (M � 20.3,SD � 8.0 vs. M � 16.3, SD � 15.1, t(1,108) � 4.03, p � .001, d �0.2) and problem alcohol use (M � 7.2, SD � 7.2 vs. M � 6.1,SD � 5.5, t(1,045) � 2.75, d � 0.1) at baseline, and were

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822 NICKERSON ET AL.

significantly younger (M � 35.5 years, SD � 13.3 vs. 39.9 years,SD � 13.5, t(1,103) � 5.39, p � .001, d � 0.3) than those who didparticipate.

Measures

We assessed PTSD symptoms (based on the DSM–IV definition)using the Clinician Administered PTSD Scale (CAPS; Blake et al.,1995). At each time-point, all PTSD questions were asked specif-ically with reference to the trauma that resulted in the injury forwhich the participant was hospitalized. At the first time-point,PTSD symptoms were assessed since the injury. In the subsequenttime-points, PTSD symptoms were assessed over the past month.The CAPS is considered the gold standard PTSD measure and hasexcellent psychometric properties (Weathers, Keane, & Davidson,2001). Each of the 17 PTSD symptoms is rated on frequency andintensity. We conceptualized PTSD in terms of the four-factorsolution proposed by King, Leskin, King, and Weathers (1998)(re-experiencing, effortful avoidance, emotional numbing, and hy-perarousal symptoms). This factor structure has become one of thebenchmark models for the field (Elhai & Palmieri, 2011), and alsoaligns with recent revisions reflected within DSM-5 (AmericanPsychiatric Association, 2013). We obtained subscale scores foreach of these clusters by summing the frequency and intensityscores for each of the symptoms in each cluster. To calculatefrequency of endorsement of each PTSD symptom at each time-point (see Table A in Supplementary Materials), we used theconventional “1–2 rule”—that is, diagnostic criteria were consid-ered to be met for each symptom if frequency � 1 and intensity �2 (Weathers et al., 1999). The interrater reliability of the CAPSwas indexed at baseline (r � .98) and at 24 months (r � .98).

We assessed problem alcohol use using the Alcohol Use Dis-orders Identification Test (AUDIT; Babor, Fuente, Sanders, &Grant, 1989), a 10-item self-report measure designed to indexactive, hazardous, or harmful alcohol use. This scale has excellentpsychometric properties (Rumpf, Hapke, Meyer, & John, 2002;Selin, 2003). While the timeframe of the original scale (the past 12months) was used at the baseline assessment, we modified thescale for subsequent assessments to represent the time since pre-vious assessment. We used the total score (representing the sum ofall items) in the current study. We determined the proportion ofparticipants engaging in harmful/hazardous alcohol use using thecut-off score of 8 or greater on the AUDIT (Saunders et al., 1993).The internal consistency of the AUDIT in the current study was asfollows: baseline � � .85, 3 months � � .82, 12 months � � .82,24 months � � .85.

We assessed prior trauma exposure using the trauma historyinventory of the PTSD module of the Composite InternationalDiagnostic Interview (Andrews, Henderson & Hall, 2001), whichscreens for 11 traumatic life events, including combat, life-threatening injury, natural disaster, witnessing injury or death,rape, sexual molestation, physical assault, childhood neglect orabuse, threatened with weapon, great shock because of eventsoccurring to other, and “other.” We also added a question onexposure to “torture or terrorism.” Participants were asked toreport if they had been exposed to these events before the traumain which they were injured.

We used the Mini International Neuropsychiatric Interview(MINI), Version 5.5 (Sheehan et al., 1998) to assess prior diagno-

sis of alcohol abuse and/or dependence. This is a structured diag-nostic interview which yields lifetime prevalence of alcohol abuseand dependence based on the DSM–IV (American PsychiatricAssociation, 1994) criteria for these disorders.

Procedure

Research assistants interviewed traumatic injury survivors justprior to discharge from hospital. At 3 months, 12 months, and 24months after the trauma, interviews were conducted by telephone(CAPS), and self-report measures returned by post (AUDIT). Allparticipants completed written informed consent procedures. Themean duration between injury and the 3-month assessment was105.45 days (SD � 26.52). Interviewers were trained and super-vised by a clinical psychologist (MOD), and all interviews wereaudiotaped so that 5% could be rescored by an independent asses-sor. Overall, the interrater reliability was strong for both PTSDdiagnostic consistency and symptom severity at 3 months (1.00and 0.84, respectively), 12 months (0.98 and 0.85, respectively),and 24 months (0.96 and 0.82, respectively). Ethical approval forthis study was obtained from the Human Research Ethics Com-mittees for each of the trauma centers.

Data Analysis

We first used latent growth curve modeling (LGCM) to examinepatterns of change in each variable individually. This yielded fivemodels in total (re-experiencing, effortful avoidance, emotionalnumbing, hyperarousal, and problem alcohol use). As it was un-likely that these variables would evidence linear change, we im-plemented nonlinear spline models with factor loadings corre-sponding to each of the four time-points being specified as: 0, �, �,and 1 (where � represents a freely estimated parameter).

Next, we used latent difference score (LDS) structural equationmodeling for longitudinal change to investigate the relationshipbetween PTSD symptoms and problem alcohol use over the 2-yearcourse of this study (Ferrer & McArdle, 2010; King, King,McArdle, Shalev, & Doron-LaMarca, 2009). The LDS approach totime sequencing allows for the modeling of three sources ofchange in longitudinal data. These include (a) cross-lagged bivari-ate change, which measures the impact of scores on one variable(e.g., PTSD symptoms at baseline) on subsequent changes inscores on a second variable (e.g., changes in problem alcohol usebetween baseline and 3-month follow-up); (b) autoregressive ef-fects or autoproportional change, which represent the influence ofthe immediately preceding latent score on that same variable’ssubsequent difference score; and (c) nonstationarity or constantslope, which represents the natural course of change of the vari-ables of interest across time. The measurement of nonstationarity/constant slope is especially important when examining constructssuch as PTSD which have natural courses of change across time.The measurement of constant slope in LDS analyses represents asignificant advantage of this approach (i.e., compared with cross-lagged analyses, where constant slope is not modeled), as theseresults take into account the impact of unmeasured or unspecifiedconstructs on the variables included in the analysis after control-ling for autoregressive and cross-lagged effects.

Analyses were conducted using Mplus version 7.1 (Muthén &Muthén, 1998–2013). Mplus implements a robust full information

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823PTSD AND ALCOHOL USE FOLLOWING TRAUMATIC INJURY

maximum likelihood estimation procedure to account for missingdata. This type of analysis uses all available information to arriveat the most likely parameter estimates. Hence, the analysis is basedon information obtained from the full 1,139 respondents at base-line and any subsequent data obtained for this sample at the 3-, 12-,and 24-month assessments. This method has been demonstrated togenerate unbiased parameter estimates in models with substantialmissing data (Allison, 2003; Raykov, 2005). Consistent with rec-ommendations in the field, we used the following indices toevaluate model fit: (a) Root Mean Square Error of Approximation(RMSEA) � 0.06); (b) Standardized Root Mean Square Residual(SRMR) � 0.08; and (c) Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) values approaching .95 or greater (Hu &Bentler, 1999).

Following the analytic procedure used by Sbarra and Allen(2009), we first estimated a series of univariate change scoremodels to evaluate whether a single (autoproportional or con-stant change only) or dual (autoproportional and constantchange) model best fit the data for the four PTSD symptomclusters and the problem alcohol use variable. This also allowedus to describe the pattern of univariate change in each of thesevariables. We first estimated a dual change model for eachvariable, followed by an autoproportional change-only modeland a constant change-only model. In all models, error vari-ances were allowed to vary freely. If the dual change or auto-proportional only change models were found to fit the data best,we also tested the impact of constraining autoproportionalparameters to equality on model fit. Model fit of nested modelswas compared using the scaled Satorra-Bentler chi-square dif-ference test (Satorra & Bentler, 2001). A significant chi-squarestatistic represented significant model degradation and the best-fitting and most parsimonious model was used for subsequentanalyses. Therefore, if there was significant model degradationfor either the autoproportional or constant change models com-pared with the dual change model, the dual change model wasretained. Conversely, if either the autoproportional or constantchange models failed to show significant model degradation,these models were used for subsequent analyses.

Next, we conducted bivariate latent difference score analysesusing models derived from the univariate model testing phase. Thisencompassed four bivariate models examining the sequence ineach of the PTSD symptom clusters and problem alcohol use. Themodel is presented in Figure 1. In LDS, each observed variable ateach time-point is partitioned into a measurement error componentand a true score component (i.e., a latent variable). These truescore latent variables (represented by p1–4, and a1–4) are used tocalculate highly reliable change or difference scores (i.e., repre-sented by �p1–3 and �a1–3 in Figure 1). This method results inthree time-based scores (i.e., four time-points yielding three dif-ference scores). Bivariate change is modeled using cross-laggedpaths from the latent variable of one construct at time t-1 (e.g., p1)to the latent difference score of the other construct at time t(e.g.,�a1). Autoproportional change (the effects of previous latent vari-ables on subsequent latent difference scores of the same construct)is represented as alphas (i.e., aa and ap in Figure 1). Finally,nonstationarity or constant slope is represented as g0p for PTSD(constant slope was not modeled for alcohol) in Figure 1, with �pdenoting its effects. We estimated initial status for PTSD symp-toms (g0p) and initial status for problem alcohol use (g0a). We also

estimated variances of exogenous variables (�2) and covariances(�) between variables. For all bivariate LDS models, the errorvariances of the PTSD indicator variables were constrained toequality to facilitate convergence.

Results

Demographic characteristics of study participants collected atbaseline are presented in Table 1.

Prevalence of PTSD and Harmful/HazardousAlcohol Use

The prevalence of DSM–IV PTSD diagnosis at each time-pointwas as follows: baseline 5.1% (n � 58/1,139); 3 months 9.4% (n �93/989); 12 months 9.5% (n � 82/865), 24 months 12.1% (n �100/830). The proportion of participants who evidenced harmful/hazardous drinking was as follows: baseline 28.2% (n � 321/1,139); 3 months 19.9% (n � 197/989), 12 months 26.6% (n �230/865), 24 months 24.2% (n � 201/830). Participants in thisstudy had a lifetime alcohol dependence prevalence rate of 19.4%(n � 221) and a lifetime alcohol abuse prevalence rate of 33.8%(n � 380).

Trauma Characteristics

Frequencies of index trauma events that caused the injury lead-ing to hospital admission were as follows: motor vehicle accident65.9% (n � 758), fall 16.1% (n � 185), physical assault 6.3% (n �73), work accident 5.1% (n � 58), and other 6.7% (n � 77). Theaverage ISS was 11.0 (SD � 8.00), with 20.9% (n � 235) ofparticipants experiencing a severe injury (ISS � 15), 24.6% (n �276) experiencing a moderate injury (ISS 10 to 14), and 54.2%(n � 608) experiencing a mild injury (ISS 0 to 9). Participantsreported a mean of 3.2 (SD � 2.8, range � 0 to 13) types oftraumatic events throughout their lives (excluding the injury thatresulted in hospitalization).

Univariate Analyses

Latent growth curve models. In Table 2, we report estimatedmeans derived from the latent growth curve analyses, and actualand possible ranges for observed variables used in the analyses.Each of the univariate latent growth curve models evidenced goodfit (see Table 2 for fit statistics). Error variances were allowed tovary freely, with the exception of the re-experiencing and problemalcohol use models where they were constrained to equality to aidconvergence. Significant positive mean slopes were evidenced inthe active avoidance (mean slope � 0.69, standard error (SE) �0.12, p � .001) and emotional numbing models (mean slope �2.21, SE � 0.27, p � .001). Mean slopes were not significant inthe re-experiencing (mean slope � 0.06, SE � 0.22, p � .79),hyperarousal (mean slope � 0.01, SE � 0.27, p � .96), andproblem alcohol use (mean slope � 0.39, SE � 0.28, p � .17)models. These findings suggested that active avoidance and emo-tional numbing symptoms increased over time, while there was noevidence for temporal changes in re-experiencing symptoms, hy-perarousal symptoms, and problem alcohol use. LCGM meanslopes will be interpreted further in conjunction with LDS modelresults below.

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824 NICKERSON ET AL.

Univariate latent difference score models. Univariate latentdifference score models were fit for each of the PTSD symptomclusters. Table 3 presents the comparative model fit of autopro-portional change models and constant change models compared

with dual change models. For the effortful avoidance, emotionalnumbing, and hyperarousal symptom clusters, full dual-changescore model specifications with autoproportional change con-strained to equality best characterized the trajectories of change.For the re-experiencing symptom cluster, the dual change modelwith autoproportional change paths varying freely best fit the data(we could not obtain convergence with a dual change model withautoproportional change paths constrained to equality for re-experiencing symptoms). For each of the PTSD symptom clusters,the removal of the autoproportional parameters or the constantslope parameter significantly degraded model fit. These findingsindicated that change in PTSD symptom clusters over time can becharacterized by two components, namely a constant change com-ponent and an autoproportional change component.

When testing univariate change models for problem alcohol use, itwas necessary to center the variable to facilitate convergence for thedual change model (but not the autoproportional change model nor theconstant change model). Comparison of models using centered vari-ables revealed that the autoproportional change only model best fit thedata. As this model did not require centering for convergence, we

Table 1Demographic Characteristics of 1,139 Injury Patients Admittedto Hospital Following a Traumatic Event

Mean/N SD/%

Gender (male) 855 75.07%Age 37.87 13.55Marital status

Married/cohabiting 502 44.07%Single 526 46.18%

EducationHigh school only 401 35.21%Further education 578 50.75%

EmploymentNot employed 110 9.66%Employed 883 77.52%

Figure 1. LDS model of temporal relationship between PTSD symptoms (p) and problem alcohol use (a).

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825PTSD AND ALCOHOL USE FOLLOWING TRAUMATIC INJURY

reverted to the raw scores for further analyses. Findings indicated thatthe autoproportional change model with autoproportional changevarying freely best fit the data for the problem alcohol use variable.This finding indicated that change in problem alcohol use over timecan be best characterized by autoproportional change.

Parameters from each of the univariate LDS PTSD symptomand problem alcohol use models are presented in Table 4.Unstandardized coefficients and standard errors are presented,along with critical ratios. Significant critical ratios are repre-sented by values greater than 1.96 (coinciding with p � .05).For the effortful avoidance and emotional numbing LCGMmodels, the constant slope parameter was positive and signifi-cant, indicating a general trend to symptom increase over time.

For the effortful avoidance, emotional numbing, and hyper-arousal univariate LDS models, the constant slope parameterwas positive and significant, indicating a general trend to symp-tom increase over time. There were also significant negativeautoproportional change parameters at each time-point for eachof these symptom clusters, indicating that higher levels ofPTSD symptoms were associated with greater subsequent de-creases (or smaller decreases) in PTSD symptoms at eachtime-point. Overall, effortful avoidance, emotional numbingand hyperarousal showed a general trend to increase over time,and participants with higher levels of these symptoms evi-denced greater subsequent decreases in these symptoms overtime.

Table 2Estimated Means and Ranges for PTSD Symptom Scores and Problem Alcohol Use at Baseline, 3 Months, 12 Months, and 24 Months

Baseline mean 3 months mean 12 months mean24 months

meanActual range

of scoresPossible range

of scores

PTSD – Re-experiencing symptoms 4.56 4.86 4.58 4.36 0 to 38 0 to 40PTSD – Effortful avoidance symptoms 1.46 1.96 2.12 2.21 0 to 16 0 to 16PTSD – Emotional numbing symptoms 4.12 5.86 5.91 6.46 0 to 40 0 to 40PTSD – Hyperarousal symptoms 8.15 8.61 7.98 8.23 0 to 39 0 to 40AUDIT scores (Problem alcohol use) 6.68 5.17 6.15 6.23 0 to 38 0 to 40

Note. N participants � 1,139. Estimated means were derived from univariate latent growth curve models. Fit statistics for latent growth curve models:Re-experiencing model: �2(6) � 27.13, p � .01, RMSEA � 0.06, CFI � 0.96, TLI, � 0.96; Effortful avoidance model:. �2(3) � 2.11, p � .55, RMSEA �0.06, CFI � 0.96, TLI, � 0.96; Emotional numbing model: �2(3) � 8.60, p � .04, RMSEA � 0.04, CFI � 0.99, TLI, � 0.98; Hyperarousal model: �2(3) �10.90, p � .01, RMSEA � 0.05, CFI � 0.99, TLI, � 0.98; Problem alcohol use model: �2(6) � 32.45, p � .001, RMSEA � 0.06, CFI � 0.96, TLI, �0.96.

Table 3Fit Statistics for Univariate Latent Difference Score Models for PTSD Symptom Clusters and Problem Alcohol Use

�2 df p CFI RMSEA �2� df� p

Re-experiencing symptomsDual change model 16.98 2 �.001 0.97 0.08 — — —Autoproportional change model 44.42 5 �.001 0.93 0.08 26.89 3 �.001Constant change model 21.11 5 �.01 0.97 0.05 9.17 3 0.03Dual change model with autoproportional paths constrained to equality — — — — — — — —

Effortful avoidance symptomsDual change model 0.48 2 0.79 1.00 �.01 — —Autoproportional change model 15.18 5 0.01 0.97 0.04 15.62 3 �.01Constant change model 17.71 5 �.01 0.97 0.05 15.59 3 �.01Dual change model with autoproportional paths constrained to equality 1.96 4 0.74 1.00 �.001 1.36 2 .51

Emotional numbing symptomsDual change model 8.69 2 0.01 0.99 0.05 — — —Autoproportional change model 27.07 5 �.001 0.96 0.06 17.95 3 �.001Constant change model 36.37 5 �.001 0.95 0.07 25.14 3 �.001Dual change model with autoproportional paths constrained to equality 7.94 4 0.09 0.99 0.03 0.73 2 0.69

Hyperarousal symptomsDual change model 7.41 2 0.02 0.99 0.05 — — —Autoproportional change model 183.39 5 �.001 0.80 0.18 168.59 3 �.001Constant change model 49.11 5 �.001 0.95 0.09 39.13 3 �.001Dual change model with autoproportional paths constrained to equality 10.63 4 0.03 0.99 0.02 3.67 2 0.16

Problem alcohol useDual change model (centered values) 2.34 2 0.31 1.00 0.01 — — —Autoproportional change model (centered values) 4.79 5 0.44 1.00 �.001 2.02 3 0.57Constant change model (centered values) 22.43 5 �.01 0.97 0.06 25.92 3 �.001Autoproportional change model (raw scores) 11.34 5 0.05 0.99 0.03 — — —Autoproportional change model with autoproportional paths constrained

to equality (raw scores) 73.41 7 �.01 0.89 0.08 72.74 2 �.001

Note. N participants � 1,139; �2 � scaled Satorra-Bentler �2 statistic; CFI � Comparative Fit Index; RMSEA � Root Mean Square Error ofApproximation; �2� � scaled Satorra-Bentler �2 difference statistic relative to dual change model; df� � degrees of freedom relative to dual change model.

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826 NICKERSON ET AL.

There were no significant constant slope or autoproportionalchange parameters for the LCGM or LDS re-experiencing symp-toms models. This suggests that that re-experiencing symptomswere not changing over time at the univariate level.

For the problem alcohol use model, there was no significantslope parameter in the univariate LCGM. This is consistent withthe finding in the univariate LDS analyses that an autoproportionalchange-only model best fit the data for problem alcohol use. In theunivariate LDS analyses, a significant negative autoproportionalchange parameter indicated that high levels of problem alcohol useat baseline were associated with greater subsequent decreases (orsmaller increases) in problem alcohol use between 0 to 3 months.A significant positive autoproportional change parameter indicatedthat high levels of problem alcohol use at 3 months were associ-ated with greater subsequent increases (or smaller decreases) inproblem alcohol use between 3 and 12 months. Overall this sug-gests that there was no constant change over time in problemalcohol use, but that those with higher levels of problem alcoholuse immediately after the trauma showed greater subsequent de-creases in alcohol use in the subsequent three months, and thosewith higher levels of problem alcohol use 3 months after the

trauma showed greater increases in problem alcohol use between 3and 12 months.

Bivariate Change Score Models

Next we fit a series of bivariate change score models to the datato investigate dynamic associations between the PTSD symptomclusters and problem alcohol use. Building on the univariate find-ings, the bivariate models examined the relationship between theintercept and constant slope of the PTSD symptom trajectories andthe intercept of the problem alcohol use trajectory, as well ascross-lagged paths between PTSD symptom clusters and problemalcohol use. For the re-experiencing/problem alcohol use andhyperarousal/problem alcohol use models, the impact of constrain-ing the cross-lagged paths to equality within each variable (i.e., allPTSD to problem alcohol use paths constrained to be equal; and allproblem alcohol use to PTSD paths constrained to be equal),compared with letting them vary freely, was evaluated. This al-lowed us to test whether cross-lagged change varied across time-points. As the effortful avoidance and emotional numbing modelswould not converge when cross-lagged paths were constrained to

Table 4Parameter Estimates for the Best-Fitting Univariate Latent Difference Score Models for PTSDSymptom Clusters and Problem Alcohol Use

Estimate SE Critical value p

Re-experiencing symptomsDual change model

Constant slope mean 1.93 1.77 1.09 0.28Autoproportional change 0 to 3 months 0.48 0.53 0.91 0.36Autoproportional change 3 to 12 months 0.53 0.46 1.16 0.25Autoproportional change 12 to 24 months 0.64 0.48 1.34 0.18Intercept-slope correlation 0.63 0.13 4.87 �0.001Intercept-slope covariance 12.35 12.96 0.95 0.34

Effortful avoidance symptomsDual change model, prop change equal

Constant slope mean 0.89 0.15 5.96 �.001Autoproportional change 0.77 0.16 4.84 �.01Intercept-slope correlation 0.56 0.13 4.31 �.001Intercept-slope covariance 2.78 0.67 4.13 �.001

Emotional numbing symptomsDual change model, prop change equal

Constant slope mean 3.44 0.50 6.94 �.001Autoproportional change 0.63 0.11 5.47 �.001Intercept-slope correlation 0.64 0.09 7.12 �.001Intercept-slope covariance 11.75 2.24 5.25 �.001

Arousal symptomsDual change model, prop change equal

Constant slope mean 4.96 0.60 8.22 �.001Autoproportional change 0.68 0.08 8.83 �.001Intercept-slope correlation 0.54 0.07 7.59 �.001Intercept-slope covariance 15.44 2.31 6.68 �.001

Problem alcohol useAutoproportional change model

Constant slope mean � � � �Autoproportional change 0 to 3 months 0.22 0.03 6.41 �.001Autoproportional change 3 to 12 months 0.23 0.05 5.25 �.001Autoproportional change 12 to 24 months 0.01 0.03 0.15 0.88Intercept-slope correlation � � � �Intercept-slope covariance � � � �

Note. N participants � 1,139; Estimate � Unstandardized coefficient; SE � Standard error; critical value �Est/SE (�) indicates that the parameter was set to 0 and not estimated.

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827PTSD AND ALCOHOL USE FOLLOWING TRAUMATIC INJURY

equality, we allowed these to vary freely. As displayed in Table 5,constraining cross-lagged paths to equality resulted in significantlydegraded fit for the re-experiencing and problem alcohol usemodel, and the hyperarousal and problem alcohol use model,therefore we allowed cross-lagged paths to vary freely in subse-quent analyses.

Parameter estimates for the final bivariate models are presentedin Table 6. All models evidenced good fit to the data. Unstandard-ized coefficients are presented with critical ratios in parentheses,with significant critical ratios (greater than 1.96 coincide with p �.05) being presented in bold. It is important to note that all reportedparameters should be interpreted in the context of other parametersin the model. In each of the models, certain nonsignificant param-eters were set to zero to aid convergence (represented by “ � ” inTable 6). While all parameters of the bivariate models are pre-sented in Table 6, here we focus on the cross-lagged paths as theseare the parameters most central to the study hypotheses. Cross-lagged parameters represent the relationship between each variableand subsequent changes in the other variable, after controlling forsalient internal sources of change (constant slope and autopropor-tional change for PTSD symptoms, and autoproportional changefor problem alcohol use). For the re-experiencing model, there wasa significant positive association between re-experiencing symp-toms at 12 months and changes in problem alcohol use from 12months to 24 months (Est � 0.09, Crit � 2.67). This suggests thatgreater severity of re-experiencing symptoms at 12 months wasassociated with greater increases (or smaller decreases) in problemalcohol use between 12 and 24 months. There was no significantinfluence of re-experiencing symptoms on problem alcohol use atany other time-points, nor of problem alcohol use on subsequentchanges in re-experiencing symptoms at any time-point.

For the effortful avoidance model, there was a significant pos-itive association between effortful avoidance at 12 months andchanges in problem alcohol use from 12 months to 24 months(Est � 0.18, Crit � 2.04). This indicates that greater severity ofeffortful avoidance symptoms at 12 months associated with greaterincreases (or smaller decreases) in problem alcohol use between 12and 24 months. There was no significant influence of problemalcohol use on subsequent changes in effortful avoidance symp-toms.

For the emotional numbing model, there was a significant neg-ative association between emotional numbing at baseline and

changes in problem alcohol use between baseline and 3 months(Est � 0.16, Crit � 2.25). This suggests that greater severityof emotional numbing at baseline was associated with greaterdecreases (or smaller increases) in problem alcohol use betweenbaseline and 3 months. There was a significant positive relation-ship between problem alcohol use at baseline and emotional numb-ing symptoms between baseline and three months (Est � 0.15,Crit � 3.00). Further, there was a significant positive associationbetween problem alcohol use at 12 months and changes in emo-tional numbing symptoms between 12 and 24 months (Est � 0.17,Crit � 3.01). This indicates that greater problem alcohol use atbaseline and at 12 months were associated with greater increases(or smaller decreases) in emotional numbing symptoms betweenbaseline and 3 months, and between 12 and 24 months, respec-tively.

For the hyperarousal model, there was a significant negativeassociation between hyperarousal symptoms at baseline andchanges in problem alcohol use between baseline and 3 months(Est � 0.09, Crit � 2.87). This suggests that greater hyper-arousal symptoms at baseline were associated with greater de-creases (or smaller increases) in problem alcohol use betweenbaseline and three months. Further, there was a positive associa-tion between hyperarousal symptoms at 12 months and changes inproblem alcohol use from 12 months to 24 months (Est � 0.05,Crit � 2.16). This indicates that greater severity of hyperarousalsymptoms were associated with greater increases (or smaller de-creases) in problem alcohol use between 12 and 24 months.

Discussion

This study demonstrates, for the first time, the naturalisticlongitudinal relationship between PTSD symptom clusters andproblem alcohol use in a traumatized sample. Our hypotheses werepartly supported, such that high levels of PTSD symptoms wereassociated with greater increases (or smaller decreases) in problemalcohol use for re-experiencing, effortful avoidance and hyper-arousal symptoms; but only in the chronic posttrauma phase (be-tween 12 and 24 months). Contrary to our hypotheses, we foundthat high levels of emotional numbing symptoms were associatedwith greater decreases (or smaller increases) in problem alcoholuse in the acute phase (between baseline and 3 months). We alsofound that higher levels of problem alcohol use were associated

Table 5Fit Statistics for Alternative Bivariate Latent Difference Score Models for PTSD Symptom Clusters and Problem Alcohol Use

�2 df p CFI RMSEA �2� df� p

Re-experiencing symptoms/problem alcohol useCross-lagged paths vary freely 31.19 19 0.04 0.99 0.02 — — —Cross-lagged paths constrained to equality 40.58 23 0.01 0.99 0.03 10.13 4 .04

Effortful avoidance/problem alcohol useCross-lagged paths vary freely 98.62 32 �.01 0.95 0.06 — — —

Emotional numbing/problem alcohol useCross-lagged paths vary freely 45.75 21 �.01 0.98 0.03 — — —

Hyperarousal/problem alcohol useCross-lagged paths vary freely 19.61 20 .48 1.00 0.02 — — —Cross-lagged paths constrained to equality 36.74 24 .05 0.99 0.02 17.02 4 �.01

Note. N participants � 1,139; �2 � scaled Satorra-Bentler �2 statistic; CFI � Comparative Fit Index; RMSEA � Root Mean Square Error ofApproximation; �2� � scaled Satorra-Bentler �2 difference statistic relative to cross-lagged paths vary freely model; df� � degrees of freedom relativeto relative to cross-lagged paths vary freely model.

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828 NICKERSON ET AL.

Tab

le6

Par

amet

erE

stim

ates

and

Fit

Stat

isti

csfo

rth

eB

est-

Fit

ting

Lat

ent

Dif

fere

nce

Scor

eM

odel

sB

etw

een

PT

SDSy

mpt

omC

lust

ers

and

Pro

blem

Alc

ohol

Use

Re-

expe

rien

cing

&pr

oble

mal

coho

lus

eM

odel

Eff

ortf

ulav

oida

nce

&pr

oble

mal

coho

lus

em

odel

Em

otio

nal

num

bing

&pr

oble

mal

coho

lus

em

odel

Hyp

erar

ousa

l&

prob

lem

alco

hol

use

mod

el

PTSD

(Re-

exp)

Prob

lem

alco

hol

use

PTSD

(avo

idan

ce)

Prob

lem

alco

hol

use

PTSD

(num

b)Pr

oble

mal

coho

lus

ePT

SD(a

rous

al)

Prob

lem

alco

hol

use

Est

(SE

)E

st(S

E)

Est

(SE

)E

st(S

E)

Est

(SE

)E

st(S

E)

Est

(SE

)E

st(S

E)

Para

met

eres

timat

esIn

itial

stat

usm

eans

(g0

p,

g0a)

3.57

(167

4)5.

49(2

6.72

)0.

65(8

.93)

5.

56(�

27.7

9)3.

16(2

0.58

)5.

60(2

7.14

)7.

14(3

6.44

)5.

65(2

7.72

)In

itial

stat

usva

rian

ces

(�2

g0p,

�2

g0a)

34.1

6(9

.73)

30.5

2(1

2.33

)31

.99

(12.

49)

31.9

9(1

2.49

)9.

28(4

.33)

29.3

6(1

1.60

)20

.36

(9.4

0)28

.56

(11.

35)

Con

stan

tsl

ope

mea

ns(

g1p)

1.96

(3.2

4)�

��

2.59

(4.4

7)�

0.

01(

0.01

)�

Con

stan

tsl

ope

vari

ance

s(�

2g0

p,�

2g0

a)

11.4

4(1

.98)

�0.

21(1

.28)

�16

.97

(3.0

7)�

45.7

3(1

.63)

�In

itial

stat

usw

ithco

nsta

ntsl

ope

(�N

pp 1

)12

.76

(2.3

9)�

0.

52(0

.05)

�11

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(4.8

0)�

12.8

7(3

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�A

utop

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nal

chan

geE

st(S

E)

95%

CI

Est

(SE

)95

%C

IE

st(S

E)

95%

CI

Est

(SE

)95

%C

IP

TSD

(�p)

p¡�

p0

to3

mon

ths

0.

47(�

2.54

)[

0.78

,

0.17

]0.

25(5

.33)

[0.1

8,0.

33]

0.

59(�

4.13

)[

0.83

,

0.36

]

0.66

(�8.

38)

[0.

78,

0.

53]

PT

SD(�

p)

p¡�

p3

to12

mon

ths

0.

56(�

3.24

)[

0.85

,

0.28

]0.

25(5

.33)

[0.1

8,0.

33]

0.

59(�

4.13

)[

0.83

,

0.36

]

0.66

(�8.

38)

[0.

78,

0.

53]

PT

SD(�

p)

p¡�

p12

to24

mon

ths

0.

65(�

3.73

)[

0.94

,

0.36

]0.

25(5

.33)

[0.1

8,0.

33]

0.

59(�

4.13

)[

0.83

,

0.36

]

0.66

(�8.

38)

[0.

78,

0.

53]

Alc

ohol

(�s)

a¡

�a

0to

3m

onth

s

0.20

(�5.

77)

[0.

26,

0.

15]

0.

23(�

6.73

)[

0.29

,

0.17

]

0.16

(3.

65)

[0.

24,

0.

09]

0.

09(�

2.87

)[

0.23

,

0.08

]A

lcoh

ol(�

s)a¡

�a

3to

12m

onth

s0.

23(5

.03)

[0.1

5,0.

30]

0.20

(4.6

0)[0

.13,

0.28

]0.

22(4

.50)

[0.1

4,0.

30]

0.22

(4.3

0)[0

.14,

0.31

]A

lcoh

ol(�

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12to

24m

onth

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00)

[0.

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�

0.03

(0.

68)

[0.

09,

0.04

]

0.04

(1.

09)

[0.

10,

.02]

PTSD

-AL

Cas

soci

atio

nsE

st(S

E)

Est

(SE

)E

st(S

E)

Est

(SE

)In

itial

stat

us(p

)w

ithin

itial

stat

us(a

)co

vari

ance

(�a 1

s 1)

2.38

(1.5

2)�

4.55

(3.7

2)4.

58(3

.50)

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stan

tsl

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(p)

with

initi

alst

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(a)

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Cro

ss-l

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def

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95%

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%C

IE

st(S

E)

95%

CI

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(SE

)95

%C

Ip t

-1¡

�a t

(�p)

0to

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onth

s

0.05

(1.

22)

[0.

11,

0.02

]�

�

0.16

(�2.

25)

[0.

28,

0.

04]

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)[

0.14

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0.04

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-1¡

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(�p)

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829PTSD AND ALCOHOL USE FOLLOWING TRAUMATIC INJURY

with greater increases (or smaller decreases) in emotional numbingsymptoms in the acute phase (between baseline and 3 months) andthe chronic phase (between 12 and 24 months). We found thatthere was no significant association between problem alcohol useand subsequent changes in re-experiencing, effortful avoidance, orhyperarousal symptoms.

Overall, our results are in accordance with those of Ouimette, Read,Wade, and Tirone (2010) who found a trending association betweenincreases in PTSD symptoms and subsequent increases in alcoholdependence symptoms in a small study of patients in treatment forsubstance use disorder. The current results build on this evidence bysuggesting that, in the context of naturalistic recovery, high levels ofPTSD symptoms are associated with subsequent increases in problemalcohol use during the chronic posttrauma phase (i.e., 12 to 24 monthsfollowing trauma exposure). It may be that, as PTSD symptomsbecome more entrenched over time, maladaptive response patternsmay be established, leading to a relationship between PTSD symp-toms and problem alcohol use that is relatively consistent acrosssymptom clusters.

The findings are not consistent with the observations reportedby Back and colleagues, who found that alcohol use decreasedprior to change in PTSD symptoms (Back et al., 2006). It isimportant to note, however, that the study conducted by Back et al.took place in the context of a clinical trial investigating theefficacy of sertraline and cognitive behavior therapy for alcoholsymptoms; the treatment focus on reducing alcohol symptoms mayaccount for the temporal primacy of changes observed in alcoholuse in that study. Further, the authors noted that, while alcoholsymptoms generally changed first, improvement in PTSD symp-toms had a greater effect on alcohol symptoms than vice versa,thus providing evidence for the salience of PTSD symptoms inimpacting on alcohol use in comorbid PTSD and alcohol usedisorders.

Results from the current study provide support for the self-medication hypothesis (Khantzian, 1985; McFarlane, 1998), whichasserts that substances are used by individuals with psychiatricdisorders to manage their distress. These findings are also consis-tent with the affective processing model of negative reinforcement(Baker et al., 2004) which suggests that trauma survivors may usealcohol to avoid negative affect. According to these theories,participants in the current study may have been engaging inproblem alcohol use in attempt to cope with, or avoid, distressingPTSD symptoms. These results suggest that the use of alcohol toself-medicate or cope with PTSD symptoms may be most promi-nent in the chronic phase following trauma exposure. Accordingly,in the context of anxiety disorders, it has been argued that alcoholcan have a short-term anxiolytic effect which may reinforce (andincrease the frequency of) drinking behavior (i.e., the tension-reduction hypothesis; Conger, 1956; Kaysen et al., 2007; Miller,Vogt, Mozley, Kaloupek, & Keane, 2006). The design of thecurrent study precluded the examination of the efficacy of thisself-medication or avoidance strategy, as it was not possible toinvestigate the impact of this increase in problem alcohol usebetween 12 and 24 months on subsequent PTSD symptoms (i.e.,beyond 24 months). Further research should investigate whetherincreases in problem alcohol use in the chronic phase followingtrauma exposure is associated with long-term decreases in PTSDsymptom severity (suggesting that problem drinking is an effectivecoping strategy) or increases in symptom severity (suggesting that

self-medication has a paradoxical effect on symptom severity).Either way, the relationship is likely to be complex and influencedby the potentially deleterious impact of increased problem alcoholuse on social and occupational functioning.

The finding that greater emotional numbing and hyperarousalsymptoms at baseline were associated with greater decreases (orsmaller increases) in problem alcohol use between baseline and 3months is somewhat unexpected in the context of the subsequentpositive relationship between PTSD symptoms and problem alco-hol use. It may be that medical factors (particularly in the contextof hospitalization) obscure the relationship between PTSD symp-toms and problem alcohol use in the acute posttrauma phase. Lowor inconsistent levels of problem alcohol use are to be expected inthis acute phase given that patients (a) are not permitted to con-sume alcohol in hospital; (b) subsequent to discharge, are likely tobe taking medications that interact with alcohol; and (c) are ofteninstructed by physicians to minimize alcohol use in the acute phaseto facilitate rehabilitation. Further, other research has demon-strated that changes in alcohol use following trauma differ betweenindividuals, with some increasing their alcohol use and othersdecreasing their alcohol use (McFarlane, 1998). Results from thisstudy are consistent with those of Davydow, Zatzick, Hough, andKaton (2013), who found that, after admission into intensive care,problem alcohol use decreased from baseline to 3 months, andincreased from the 3-month to 12-month follow-up. The examina-tion of the interrelationship between PTSD symptoms and problemalcohol use at baseline is further complicated by the fact that PTSDsymptoms were assessed since the trauma (which occurred daysprior to the assessment), while problem alcohol use was assessedin the previous 12 months. Thus, it is difficult to draw conclusionsregarding the relationship between PTSD symptoms and problemalcohol use in the acute posttrauma phase with this sample.

We found that problem alcohol use at 12 months was associatedwith subsequent increases (or smaller decreases) in emotionalnumbing symptoms, and that there was no relationship betweenemotional numbing symptoms and subsequent problem alcoholuse in the chronic (12–24 month) posttrauma phase. This findingis consistent with the substance-induced anxiety model, whichsuggests that alcohol use may lead to increased psychologicalsymptoms over time, especially in the context of life stressors(Smith & Randall, 2012). Previous research has suggested thatemotional numbing symptoms of PTSD are especially stronglyassociated with problem alcohol use (Hellmuth et al., 2013; Jak-upcak et al., 2010; Scott et al., 2013). The finding in the currentstudy that emotional numbing symptoms may be exacerbated byproblem alcohol use is also consistent with the assertion thatalcohol use may increase emotional numbing symptoms by facil-itating detachment and emotional blunting (Jakupcak et al., 2010).As the problem alcohol use increases, the individual may becomemore disengaged from other people and activities, and have diffi-culty experiencing emotions; symptoms that are encompassed inthe emotional numbing cluster of PTSD.

The finding that the relationship between problem alcohol useand re-experiencing, effortful avoidance and hyperarousal symp-toms is unidirectional is also somewhat surprising, as thesubstance-induced anxiety model suggests that problem alcoholuse may impede recovery from these PTSD symptoms (Smith &Randall, 2012). Consistent with this theory, information process-ing models of PTSD posit that avoidance strategies, such as

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excessive alcohol use, can limit processing of trauma memorieswhich, in turn, contributes to symptom maintenance (Foa, Steke-tee, & Rothbaum, 1989). In the current study, we found no evi-dence that problem alcohol use significantly impacted on subse-quent changes in these clusters of PTSD symptoms. In contrast, itappears that it is these symptoms that drive changes in problemalcohol use. It may be the case that, following the establishment ofchronic alcohol use patterns and PTSD symptoms, this relationshipbecomes reciprocal; this should be investigated by future studieswith longer follow-up periods.

Rates of PTSD observed in the current study fell within ex-pected limits following traumatic injury, which range from 3% to42% in the 6 months after the injury (e.g., Michaels et al., 1999;O’Donnell, Creamer, Bryant, Schnyder, & Shalev, 2003;O’Donnell, Creamer, Pattison, & Atkin, 2004; Schnyder, Witt-mann, Friedrich-Perez, Hepp, & Moergeli, 2008; Shalev et al.,1998), and from 2% to 36% at 12-months postinjury (e.g.,O’Donnell et al., 2003; Schnyder et al., 2008; Zatzick, Jurkovich,Gentilello, Wisner, & Rivara, 2002). Rates of problem alcohol usein this study were also consistent with those reported by Zatzick,Jurkovich, Gentilello, Wisner, and Rivara (2002), who found thatapproximately 25% of individuals hospitalized due to injuryscored above the “problem drinking” cut-off on the AUDIT.

An advantage of the implementation of latent difference scoreanalyses in the current study is that this technique facilitates theexamination of different types of change in symptoms across time.This is in comparison to other longitudinal analytic techniques thatexamine changes in prevalence rates or average levels of symp-toms across time. Previous research examining prevalence rates ormean symptoms over time have yielded mixed findings, with somestudies reporting declining PTSD symptoms following traumaexposure (Cukor et al., 2011; Neria et al., 2010); while others havefound that symptom levels remained constant (Haagsma et al.,2012) or increased over time (Kessler et al., 2008; Wolfe et al.,1999). Other research has suggested that there are multiple trajec-tories of PTSD symptom change among trauma survivors (Bo-nanno & Mancini, 2012; Dickstein et al., 2010; Pietrzak et al.,2014), and that diagnostic classification shifts between time-points(Bryant et al., 2013), underscoring the heterogeneity of PTSDsymptom trajectories. Although we did not examine symptomtrajectories over time, results from this study suggested that thelongitudinal course of symptoms is complex, and varies betweensymptom groups. Symptom course is also likely strongly impactedby the posttrauma environment of the particular group under study.Overall, it is imperative that findings from the current study bereplicated using latent difference score analyses, to validate theserelationships with other trauma-affected groups.

This study has several limitations. First, all participants in thisstudy were traumatic injury patients who had been hospitalized forat least 24 hr. Research has suggested that trauma exposure typemay be associated with different profiles of comorbidity withproblem alcohol use (Fetzner, McMillan, Sareen, & Asmundson,2011; Schumacher, Coffey, & Stasiewicz, 2006; Stewart, 1996).This study focused on trauma injury survivors, and results may notbe generalizable to individuals exposed to other types of traumaticevents. Although PTSD was initially assessed using face-to-faceinterviews, subsequent assessments were performed over the tele-phone. There may be some differences between these two modesof interview, although previous studies suggest that there is strong

agreement between the face-to-face and telephone interviewing(Aziz & Kenford, 2004). Further, the absence of additional assess-ment points between baseline and 3 months represents a limitationof this study, as it precludes more detailed examination of therelationship between PTSD and problem alcohol use in the crucialacute period following trauma exposure.

Although we view the heterogeneity of the current sample inrelation to symptom severity as a strength of the study, it ispossible that the relationship between PTSD symptoms and prob-lem alcohol use is stronger among individuals with greater severityof PTSD symptoms who may be more likely to use alcohol forsymptom management. Future studies should investigate theserelationships in individuals with high levels of psychological dis-tress. In addition, we were unable to investigate the relationshipbetween symptoms of one type (i.e., PTSD or problem alcohol use)and the presentation of symptoms of the other type. For example,it is likely that heavy alcohol use may impact on the presentationof PTSD symptoms as a function of associated phenomena includ-ing withdrawal symptoms and neurological changes. Future re-search should examine the influence of these symptoms on thephenomenology of the other disorder. We did not consider theimpact of exposure to multiple types of traumatic events (eitherprior to or subsequent to the index trauma measured in this study)on the parameters in the model; this may represent a promisingdirection for future research as it would provide information onhow symptom change is influenced by a history of traumaticevents and subsequent trauma exposure. It may be the case, forexample, that increased problem alcohol use following traumaexposure increases the likelihood of retraumatization, thus increas-ing risk for developing PTSD. In addition, we did not assessreasons for problem alcohol use in participants in this study, andtherefore were unable to evaluate the extent to which alcohol usemay have been a conscious self-medication strategy in this sample.

Findings from this naturalistic longitudinal study indicate thatthere is a strong relationship between PTSD symptoms and sub-sequent changes in problem alcohol use in the chronic posttraumaperiod in trauma survivors. Enhanced understanding of the role ofPTSD symptoms in the exacerbation of problem alcohol use maycontribute to the alleviation of one of the most damaging publichealth costs of traumatic experiences.

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Received April 28, 2013Revision received July 24, 2014

Accepted July 28, 2014 �

New Editors Appointed, 2016–2021

The Publications and Communications Board of the American Psychological Association an-nounces the appointment of 9 new editors for 6-year terms beginning in 2016. As of January 1,2015, manuscripts should be directed as follows:

● History of Psychology (http://www.apa.org/pubs/journals/hop/), Nadine M. Weidman, PhD,Harvard University

● Journal of Family Psychology (http://www.apa.org/pubs/journals/fam/), Barbara H. Fiese,PhD, University of Illinois at Urbana—Champaign

● JPSP: Personality Processes and Individual Differences (http://www.apa.org/pubs/journals/psp/), M. Lynne Cooper, PhD, University of Missouri—Columbia

● Psychological Assessment (http://www.apa.org/pubs/journals/pas/), Yossef S. Ben-Porath,PhD, Kent State University

● Psychological Review (http://www.apa.org/pubs/journals/rev/), Keith J. Holyoak, PhD, Uni-versity of California, Los Angeles

● International Journal of Stress Management (http://www.apa.org/pubs/journals/str/), Oi LingSiu, PhD, Lingnan University, Tuen Mun, Hong Kong

● Journal of Occupational Health Psychology (http://www.apa.org/pubs/journals/ocp/), Peter Y.Chen, PhD, Auburn University

● Personality Disorders (http://www.apa.org/pubs/journals/per/), Thomas A. Widiger, PhD,University of Kentucky

● Psychology of Men & Masculinity (http://www.apa.org/pubs/journals/men/), William MingLiu, PhD, University of Iowa

Electronic manuscript submission: As of January 1, 2015, manuscripts should be submittedelectronically to the new editors via the journal’s Manuscript Submission Portal (see the websitelisted above with each journal title).

Current editors Wade E. Pickren, PhD, Nadine J. Kaslow, PhD, Laura A. King, PhD, Cecil R.Reynolds, PhD, John Anderson, PhD, Sharon Glazer, PhD, Carl W. Lejuez, PhD, and Ronald F.Levant, EdD, will receive and consider new manuscripts through December 31, 2014.

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834 NICKERSON ET AL.