Journal of Abnormal Psychology 2014, Vol. 123, No. 4, 821-834
© 2014 American Psychological Association 0021-843X714/$ 12.00 http://dx.doi.org/10.1037/a0037920
The Temporal Relationship Between Posttraumatic Stress Disorder and Problem Alcohol Use Following Traumatic Injury Angela Nickerson
J. Ben Barnes
IJNSW Australia
University of Delaware
Mark Creamer and David Forbes
Alexander C. McFarlane
University of Melbourne
University of Adelaide
Meaghan O’Donnell
Derrick Silove
University of Melbourne
UNSW Australia
Zachary Steel
Richard A. Bryant
UNSW Australia and Richmond Hospital, North Richmond NSW, Australia
UNSW Australia
Chronic alcohol abuse is a major public health concern following trauma exposure; however, little is known about the temporal association between posttraumatic stress disorder (PTSD) symptoms and problem alcohol use. The current study examined the temporal relationship between PTSD symptom clusters (re-experiencing, effortful avoidance, emotional numbing, and hyperarousal) and problem alcohol use following trauma exposure. This study was a longitudinal survey of randomly selected traumatic injury patients interviewed at baseline, 3 months, 12 months, and 24 months following injury. Participants were 1,139 injury patients recruited upon admission from 4 Level 1 trauma centers across Australia. Participants were assessed using the Clinician Administered PTSD Scale and Alcohol Use Disorders Identification Test. Results indicated that high levels of re-experiencing, effortful avoidance, and hyperarousal symptoms at 12 months were associated with greater increases (or smaller decreases) in problem alcohol use between 12 and 24 months. Findings also suggested that high levels of problem alcohol use at 12 months were associated with greater increases (or smaller decreases) in emotional numbing symptoms between 12 and 24 months. These findings highlight the critical importance of the chronic period following trauma exposure in the relationship between PTSD symptoms 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 (Helzer, 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 the second most common in women (Kessler, Sonnega, Bromet, Hughes, & Nelson, 1995). Compared with individual PTSD or alcohol/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; Mark Creamer and David Forbes, Australian Center for Posttraumatic Mental Health and Department of Psychiatry, University of Melbourne; Alexander C. McFarlane, Center for Military and Veterans’ Health, University of Adelaide; Meaghan O’Donnell, Australian Center for Posttraumatic Mental Health and Department of Psychiatry, University of Melbourne; Derrick Silove, School of Psychiatry, UNSW Australia; Zachary Steel, School of Psychiatry, UNSW Australia and St. John of God Professorial Chair of Trauma 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 Research Council Program Grant (568970). Dr. Nickerson was supported by a National Health and Medical Research Council Clinical Early Career Research Fellowship (1037091). The authors gratefully acknowledge all the participants involved in this study, as well as the editor and anonymous reviewers for their helpful feedback on this article. The authors also gratefully acknowledge the assistance of Professors Daniel and Lynda King with the statistical analyses reported in this article. Correspondence concerning this article should be addressed to Angela Nickerson, School of Psychology, UNSW Australia, Sydney NSW 2052, Australia. E-mail: [email protected]
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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 et al., 2000; Breslau, Davis, Peterson, & Schultz, 1997; Read, Brown, & Kahler, 2004; Riggs, Rukstalis, Volpicelli, Kalmanson, & Foa, 2003). Research suggests that, following exposure to trauma, PTSD develops prior to substance abuse or problem alcohol use (Chilcoat & Breslau, 1998; Jacobsen, Southwick, & Kosten, 2001; Jacobson et 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 substances to decrease PTSD symptoms (Khantzian, 1985; Leeies, Pagura, Sareen, & Bolton, 2010; McFarlane, 1998). Similarly, the affective processing model of negative reinforcement asserts that alcohol or substance use is motivated by avoidance of negative affect, such as that 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 a coping strategy is associated with PTSD symptoms in traumaexposed groups (Kaysen et al., 2007; Leeies, Pagura, Sareen, & Bolton, 2010; Lehavot, Stappenbeck, Luterek, Kaysen, & Simp son, 2014; Ullman, Filipas, Townsend, & Starzynski, 2006). These findings indicate that PTSD symptoms may lead to increased alcohol use as trauma survivors attempt to cope with symptomrelated distress. In contrast, the substance-induced anxiety model posits that anxiety symptoms can result from chronic excessive alcohol con sumption (Smith & Randall, 2012). It has been argued that, in the context of life stressors, alcohol use may prevent extinction-based learning, such that the combination of stress and poor coping skills exacerbate anxiety (Smith & Randall, 2012). This is supported by research indicating that anxiety symptoms decrease significantly in patients in inpatient alcohol abuse treatment programs (Brown, Irwin, & Schuckit, 1991; Kushner et al., 2005). Further, findings from 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 that high levels of alcohol use may exacerbate distress, potentially leading to subsequent increases in PTSD symptoms. Overall, research to date has failed to establish a clear temporal association between PTSD symptoms and problem alcohol use following 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 and problem alcohol use is essential if we are to understand how PTSD symptoms and problem alcohol use maintain and/or exacerbate one another, and consequently manage this interrelationship. The few studies that have investigated the temporal association between PTSD and problem alcohol use have been undertaken in the context of psychological or pharmacological treatments. This research has yielded mixed findings regarding the temporal se quencing of changes in alcohol and/or substance use and changes in PTSD symptoms, with some suggesting that reductions in problem 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 score structural equation modeling to examine the direction of temporal influence 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 treatment contexts in which particular symptoms have been the target of psychological or pharmacological interventions, potentially influ encing the course of symptom change. This study is novel as it represents the first naturalistic study of temporal ordering of change in PTSD symptoms and problem alcohol use over time. Integrating theoretical models and previous research on PTSD symptoms, we hypothesize bidirectional relationships between PTSD symptoms and problem alcohol use. Specifically, we predict that more severe re-experiencing, effortful avoidance, emotional numbing 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, we hypothesize that higher levels of problem alcohol use will be associated with increases (or smaller decreases) in subsequent PTSD symptoms.
Method Participants Participants in this study were drawn from the Australian Injury Vulnerability Study (IVS), in which injury survivors were re cruited upon admission to four Level 1 trauma centers in Australia between April 2004 and April 2006. Inclusion criteria for the study were: 18 to 70 years of age, ability to communicate proficiently in English, and hospital admission of longer than 24 hr following traumatic injury. Exclusion criteria included moderate or severe head injury; current psychotic symptoms or active suicidality, temporary visitor to Australia, cognitive impairment, and/or under police guard. Participants who met entry criteria were selected using an automated assignment procedure; stratified by length of stay. 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 (x2 = .80, d f = 1, p = .23), length of hospital admission, t(df = 1,082) = .03, p = .88, injury severity score (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 patients could not be contacted or declined to participate; 989 were inter viewed by telephone (86.8% of the initial sample). Of these patients, 865 participants of the initial 1,139 completed the 12month assessment (76.0%) and 830 participants completed the 24-month assessment (72.9%). Participants at the 24-month follow-up interview did not differ from those who did not partic ipate in terms of gender (x2 = 1.91, d f = 1, p = .17), length of hospital admission, /(1,120) = .43, p = .67, or ISS, /(1,120) = 1.69, p = .09. Those who did not participate in the follow-up assessment had significantly greater PTSD symptoms (M = 20.3, SD = 8.0 vs. M = 16.3, SD = 15.1, r(l,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, f( 1,045) = 2.75, d = 0.1) at baseline, and were
PTSD AND ALCOHOL USE FOLLOWING TRAUMATIC INJURY
significantly younger (M = 35.5 years, SD = 13.3 vs. 39.9 years, SD = 13.5, r(l,103) = 5.39,p < .001, d = 0.3) than those who did participate.
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sis of alcohol abuse and/or dependence. This is a structured diag nostic interview which yields lifetime prevalence of alcohol abuse and dependence based on the DSM-IV (American Psychiatric Association, 1994) criteria for these disorders.
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 for which the participant was hospitalized. At the first time-point, PTSD symptoms were assessed since the injury. In the subsequent time-points, PTSD symptoms were assessed over the past month. The CAPS is considered the gold standard PTSD measure and has excellent psychometric properties (Weathers, Keane, & Davidson, 2001). Each of the 17 PTSD symptoms is rated on frequency and intensity. We conceptualized PTSD in terms of the four-factor solution 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 the benchmark models for the field (Elhai & Palmieri, 2011), and also aligns with recent revisions reflected within DSM-5 (American Psychiatric Association, 2013). We obtained subscale scores for each of these clusters by summing the frequency and intensity scores for each of the symptoms in each cluster. To calculate frequency of endorsement of each PTSD symptom at each timepoint (see Table A in Supplementary Materials), we used the conventional “ 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 CAPS was 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 index active, hazardous, or harmful alcohol use. This scale has excellent psychometric properties (Rumpf, Hapke, Meyer, & John, 2002; Selin, 2003). While the timeframe of the original scale (the past 12 months) was used at the baseline assessment, we modified the scale for subsequent assessments to represent the time since pre vious assessment. We used the total score (representing the sum of all items) in the current study. We determined the proportion of participants engaging in harmful/hazardous alcohol use using the cut-off score of 8 or greater on the AUDIT (Saunders et al., 1993). The internal consistency of the AUDIT in the current study was as follows: baseline a = .85, 3 months a = .82, 12 months a = .82, 24 months a = .85. We assessed prior trauma exposure using the trauma history inventory of the PTSD module of the Composite International Diagnostic Interview (Andrews, Henderson & Hall, 2001), which screens for 11 traumatic life events, including combat, lifethreatening injury, natural disaster, witnessing injury or death, rape, sexual molestation, physical assault, childhood neglect or abuse, threatened with weapon, great shock because of events occurring to other, and “other.” We also added a question on exposure to “torture or terrorism.” Participants were asked to report if they had been exposed to these events before the trauma in which they were injured. We used the Mini International Neuropsychiatric Interview (MINI), Version 5.5 (Sheehan et al., 1998) to assess prior diagno
Procedure Research assistants interviewed traumatic injury survivors just prior to discharge from hospital. At 3 months, 12 months, and 24 months after the trauma, interviews were conducted by telephone (CAPS), and self-report measures returned by post (AUDIT). All participants completed written informed consent procedures. The mean duration between injury and the 3-month assessment was 105.45 days (SD = 26.52). Interviewers were trained and super vised by a clinical psychologist (MOD), and all interviews were audiotaped so that 5% could be rescored by an independent asses sor. Overall, the interrater reliability was strong for both PTSD diagnostic consistency and symptom severity at 3 months (1.00 and 0.84, respectively), 12 months (0.98 and 0.85, respectively), and 24 months (0.96 and 0.82, respectively). Ethical approval for this 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 examine patterns of change in each variable individually. This yielded five models in total (re-experiencing, effortful avoidance, emotional numbing, 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 equation modeling for longitudinal change to investigate the relationship between PTSD symptoms and problem alcohol use over the 2-year course of this study (Ferrer & McArdle, 2010; King, King, McArdle, Shalev, & Doron-LaMarca, 2009). The LDS approach to time sequencing allows for the modeling of three sources of change 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 in scores on a second variable (e.g., changes in problem alcohol use between baseline and 3-month follow-up); (b) autoregressive ef fects or autoproportional change, which represent the influence of the immediately preceding latent score on that same variable’s subsequent difference score; and (c) nonstationarity or constant slope, 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 constructs such as PTSD which have natural courses of change across time. The measurement of constant slope in LDS analyses represents a significant advantage of this approach (i.e., compared with crosslagged analyses, where constant slope is not modeled), as these results take into account the impact of unmeasured or unspecified constructs on the variables included in the analysis after control ling for autoregressive and cross-lagged effects. Analyses were conducted using Mplus version 7.1 (Muthen & Muthen, 1998-2013). Mplus implements a robust full information
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maximum likelihood estimation procedure to account for missing data. This type of analysis uses all available information to arrive at the most likely parameter estimates. Hence, the analysis is based on 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 to generate unbiased parameter estimates in models with substantial missing data (Allison, 2003; Raykov, 2005). Consistent with rec ommendations in the field, we used the following indices to evaluate 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 TuckerLewis 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 score models to evaluate whether a single (autoproportional or con stant change only) or dual (autoproportional and constant change) model best fit the data for the four PTSD symptom clusters and the problem alcohol use variable. This also allowed us to describe the pattern of univariate change in each of these variables. We first estimated a dual change model for each variable, followed by an autoproportional change-only model and 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 autoproportional parameters to equality on model fit. Model fit of nested models was compared using the scaled Satorra-Bentler chi-square dif ference test (Satorra & Bentler, 2001). A significant chi-square statistic represented significant model degradation and the best fitting and most parsimonious model was used for subsequent analyses. Therefore, if there was significant model degradation for either the autoproportional or constant change models com pared with the dual change model, the dual change model was retained. Conversely, if either the autoproportional or constant change models failed to show significant model degradation, these models were used for subsequent analyses. Next, we conducted bivariate latent difference score analyses using models derived from the univariate model testing phase. This encompassed four bivariate models examining the sequence in each of the PTSD symptom clusters and problem alcohol use. The model is presented in Figure 1. In LDS, each observed variable at each time-point is partitioned into a measurement error component and a true score component (i.e., a latent variable). These true score latent variables (represented by p,_4, and a t_4) are used to calculate highly reliable change or difference scores (i.e., repre sented by Ap,_3 and Aa, _3 in Figure 1). This method results in three time-based scores (i.e., four time-points yielding three dif ference scores). Bivariate change is modeled using cross-lagged paths from the latent variable of one construct at time t-1 (e.g., p,) to the latent difference score of the other construct at time /(e.g., Aa,). 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 |3p denoting 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 (O2) and covariances (fl) between variables. For all bivariate LDS models, the error variances of the PTSD indicator variables were constrained to equality to facilitate convergence.
Results Demographic characteristics of study participants collected at baseline are presented in Table 1.
Prevalence of PTSD and Harmful/Hazardous Alcohol Use The prevalence of DSM-IV PTSD diagnosis at each time-point was 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 this study 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 accident 65.9% (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). The average ISS was 11.0 (SD = 8.00), with 20.9% (n = 235) of participants experiencing a severe injury (ISS s 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). Participants reported a mean of 3.2 (SD = 2.8, range = 0 to 13) types of traumatic events throughout their lives (excluding the injury that resulted in hospitalization).
Univariate Analyses Latent growth curve models. In Table 2, we report estimated means derived from the latent growth curve analyses, and actual and possible ranges for observed variables used in the analyses. Each of the univariate latent growth curve models evidenced good fit (see Table 2 for fit statistics). Error variances were allowed to vary freely, with the exception of the re-experiencing and problem alcohol use models where they were constrained to equality to aid convergence. Significant positive mean slopes were evidenced in the active avoidance (mean slope = 0.69, standard error (S£) = 0.12, p < .001) and emotional numbing models (mean slope = 2.21, SE = 0.27, p < .001). Mean slopes were not significant in the re-experiencing (mean slope = —0.06, SE = 0.22, p = .79), hyperarousal (mean slope = 0.01, SE = 0.27, p = .96), and problem 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 no evidence for temporal changes in re-experiencing symptoms, hy perarousal symptoms, and problem alcohol use. LCGM mean slopes will be interpreted further in conjunction with LDS model results below.
PTSD AND ALCOHOL USE FOLLOWING TRAUMATIC INJURY
Figure 1.
LDS model of temporal relationship between PTSD symptoms (p) and problem alcohol use (a).
Univariate latent difference score models. Univariate latent difference score models were fit for each of the PTSD symptom clusters. Table 3 presents the comparative model fit of autopro portional change models and constant change models compared
Table 1 Demographic Characteristics o f 1,139 Injury Patients Admitted to Hospital Following a Traumatic Event
Gender (male) Age Marital status Married/cohabiting Single Education High school only Further education Employment Not employed Employed
825
Mean/N
SDI%
855 37.87
75.07% 13.55
502 526
44.07% 46.18%
401 578
35.21% 50.75%
110 883
9.66% 77.52%
with dual change models. For the effortful avoidance, emotional numbing, and hyperarousal symptom clusters, full dual-change score model specifications with autoproportional change con strained to equality best characterized the trajectories of change. For the re-experiencing symptom cluster, the dual change model with autoproportional change paths varying freely best fit the data (we could not obtain convergence with a dual change model with autoproportional change paths constrained to equality for re experiencing symptoms). For each of the PTSD symptom clusters, the removal of the autoproportional parameters or the constant slope parameter significantly degraded model fit. These findings indicated that change in PTSD symptom clusters over time can be characterized by two components, namely a constant change com ponent and an autoproportional change component. When testing univariate change models for problem alcohol use, it was necessary to center the variable to facilitate convergence for the dual change model (but not the autoproportional change model nor the constant change model). Comparison of models using centered vari ables revealed that the autoproportional change only model best fit the data. As this model did not require centering for convergence, we
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Table 2 Estimated Means and Ranges fo r PTSD Symptom Scores and Problem Alcohol Use at Baseline, 3 Months, 12 Months, and 24 Months
PTSD PTSD PTSD PTSD AUDIT
Re-experiencing symptoms Effortful avoidance symptoms Emotional numbing symptoms Hyperarousal symptoms scores (Problem alcohol use)
Baseline mean
3 months mean
12 months mean
24 months mean
Actual range of scores
Possible range of scores
4.56 1.46 4.12 8.15 6.68
4.86 1.96 5.86 8.61 5.17
4.58 2.12 5.91 7.98 6.15
4.36 2.21 6.46 8.23 6.23
0 to 38 Oto 16 0 to 40 Oto 39 0 to 38
Oto 40 Oto 16 0 to 40 0 to 40 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: x2(6) = 27.13,p < .01, RMSEA = 0.06, CFI = 0.96, TLI, = 0.96; Effortful avoidance model:. x2(3) = 2.11, p = .55, RMSEA = 0.06, CFI = 0.96, TLI, = 0.96; Emotional numbing model: x2(3) = 8.60, p = .04, RMSEA = 0.04, CFI = 0.99, TLI, = 0.98; Hyperarousal model: x2(3) = 10.90, p = .01, RMSEA = 0.05, CFI = 0.99, TLI, = 0.98; Problem alcohol use model: x2(6) = 32.45, p < .001, RMSEA = 0.06, CFI = 0.96, TLI, = 0.96.
reverted to the raw scores for further analyses. Findings indicated that the autoproportional change model with autoproportional change varying freely best fit the data for the problem alcohol use variable. This finding indicated that change in problem alcohol use over time can be best characterized by autoproportional change. Parameters from each of the univariate LDS PTSD symptom and 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 LCGM models, 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 parameter was positive and significant, indicating a general trend to symp tom increase over time. There were also significant negative autoproportional change parameters at each time-point for each of these symptom clusters, indicating that higher levels of PTSD symptoms were associated with greater subsequent de creases (or smaller decreases) in PTSD symptoms at each time-point. Overall, effortful avoidance, emotional numbing and 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 over time.
Table 3 Fit Statistics fo r Univariate Latent Difference Score Models fo r PTSD Symptom Clusters and Problem Alcohol Use
Re-experiencing symptoms Dual change model Autoproportional change model Constant change model Dual change model with autoproportional paths constrained to equality Effortful avoidance symptoms Dual change model Autoproportional change model Constant change model Dual change model with autoproportional paths constrained to equality Emotional numbing symptoms Dual change model Autoproportional change model Constant change model Dual change model with autoproportional paths constrained to equality Hyperarousal symptoms Dual change model Autoproportional change model Constant change model Dual change model with autoproportional paths constrained to equality Problem alcohol use Dual change model (centered values) Autoproportional change model (centered values) Constant change model (centered values) Autoproportional change model (raw scores) Autoproportional change model with autoproportional paths constrained to equality (raw scores)
x2
df
P
CFI
RMSEA
X2A
d/A
P
16.98 44.42 21.11
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© 2014 American Psychological Association 0021-843X714/$ 12.00 http://dx.doi.org/10.1037/a0037920
The Temporal Relationship Between Posttraumatic Stress Disorder and Problem Alcohol Use Following Traumatic Injury Angela Nickerson
J. Ben Barnes
IJNSW Australia
University of Delaware
Mark Creamer and David Forbes
Alexander C. McFarlane
University of Melbourne
University of Adelaide
Meaghan O’Donnell
Derrick Silove
University of Melbourne
UNSW Australia
Zachary Steel
Richard A. Bryant
UNSW Australia and Richmond Hospital, North Richmond NSW, Australia
UNSW Australia
Chronic alcohol abuse is a major public health concern following trauma exposure; however, little is known about the temporal association between posttraumatic stress disorder (PTSD) symptoms and problem alcohol use. The current study examined the temporal relationship between PTSD symptom clusters (re-experiencing, effortful avoidance, emotional numbing, and hyperarousal) and problem alcohol use following trauma exposure. This study was a longitudinal survey of randomly selected traumatic injury patients interviewed at baseline, 3 months, 12 months, and 24 months following injury. Participants were 1,139 injury patients recruited upon admission from 4 Level 1 trauma centers across Australia. Participants were assessed using the Clinician Administered PTSD Scale and Alcohol Use Disorders Identification Test. Results indicated that high levels of re-experiencing, effortful avoidance, and hyperarousal symptoms at 12 months were associated with greater increases (or smaller decreases) in problem alcohol use between 12 and 24 months. Findings also suggested that high levels of problem alcohol use at 12 months were associated with greater increases (or smaller decreases) in emotional numbing symptoms between 12 and 24 months. These findings highlight the critical importance of the chronic period following trauma exposure in the relationship between PTSD symptoms 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 (Helzer, 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 the second most common in women (Kessler, Sonnega, Bromet, Hughes, & Nelson, 1995). Compared with individual PTSD or alcohol/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; Mark Creamer and David Forbes, Australian Center for Posttraumatic Mental Health and Department of Psychiatry, University of Melbourne; Alexander C. McFarlane, Center for Military and Veterans’ Health, University of Adelaide; Meaghan O’Donnell, Australian Center for Posttraumatic Mental Health and Department of Psychiatry, University of Melbourne; Derrick Silove, School of Psychiatry, UNSW Australia; Zachary Steel, School of Psychiatry, UNSW Australia and St. John of God Professorial Chair of Trauma 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 Research Council Program Grant (568970). Dr. Nickerson was supported by a National Health and Medical Research Council Clinical Early Career Research Fellowship (1037091). The authors gratefully acknowledge all the participants involved in this study, as well as the editor and anonymous reviewers for their helpful feedback on this article. The authors also gratefully acknowledge the assistance of Professors Daniel and Lynda King with the statistical analyses reported in this article. Correspondence concerning this article should be addressed to Angela Nickerson, School of Psychology, UNSW Australia, Sydney NSW 2052, Australia. E-mail: [email protected]
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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 et al., 2000; Breslau, Davis, Peterson, & Schultz, 1997; Read, Brown, & Kahler, 2004; Riggs, Rukstalis, Volpicelli, Kalmanson, & Foa, 2003). Research suggests that, following exposure to trauma, PTSD develops prior to substance abuse or problem alcohol use (Chilcoat & Breslau, 1998; Jacobsen, Southwick, & Kosten, 2001; Jacobson et 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 substances to decrease PTSD symptoms (Khantzian, 1985; Leeies, Pagura, Sareen, & Bolton, 2010; McFarlane, 1998). Similarly, the affective processing model of negative reinforcement asserts that alcohol or substance use is motivated by avoidance of negative affect, such as that 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 a coping strategy is associated with PTSD symptoms in traumaexposed groups (Kaysen et al., 2007; Leeies, Pagura, Sareen, & Bolton, 2010; Lehavot, Stappenbeck, Luterek, Kaysen, & Simp son, 2014; Ullman, Filipas, Townsend, & Starzynski, 2006). These findings indicate that PTSD symptoms may lead to increased alcohol use as trauma survivors attempt to cope with symptomrelated distress. In contrast, the substance-induced anxiety model posits that anxiety symptoms can result from chronic excessive alcohol con sumption (Smith & Randall, 2012). It has been argued that, in the context of life stressors, alcohol use may prevent extinction-based learning, such that the combination of stress and poor coping skills exacerbate anxiety (Smith & Randall, 2012). This is supported by research indicating that anxiety symptoms decrease significantly in patients in inpatient alcohol abuse treatment programs (Brown, Irwin, & Schuckit, 1991; Kushner et al., 2005). Further, findings from 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 that high levels of alcohol use may exacerbate distress, potentially leading to subsequent increases in PTSD symptoms. Overall, research to date has failed to establish a clear temporal association between PTSD symptoms and problem alcohol use following 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 and problem alcohol use is essential if we are to understand how PTSD symptoms and problem alcohol use maintain and/or exacerbate one another, and consequently manage this interrelationship. The few studies that have investigated the temporal association between PTSD and problem alcohol use have been undertaken in the context of psychological or pharmacological treatments. This research has yielded mixed findings regarding the temporal se quencing of changes in alcohol and/or substance use and changes in PTSD symptoms, with some suggesting that reductions in problem 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 score structural equation modeling to examine the direction of temporal influence 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 treatment contexts in which particular symptoms have been the target of psychological or pharmacological interventions, potentially influ encing the course of symptom change. This study is novel as it represents the first naturalistic study of temporal ordering of change in PTSD symptoms and problem alcohol use over time. Integrating theoretical models and previous research on PTSD symptoms, we hypothesize bidirectional relationships between PTSD symptoms and problem alcohol use. Specifically, we predict that more severe re-experiencing, effortful avoidance, emotional numbing 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, we hypothesize that higher levels of problem alcohol use will be associated with increases (or smaller decreases) in subsequent PTSD symptoms.
Method Participants Participants in this study were drawn from the Australian Injury Vulnerability Study (IVS), in which injury survivors were re cruited upon admission to four Level 1 trauma centers in Australia between April 2004 and April 2006. Inclusion criteria for the study were: 18 to 70 years of age, ability to communicate proficiently in English, and hospital admission of longer than 24 hr following traumatic injury. Exclusion criteria included moderate or severe head injury; current psychotic symptoms or active suicidality, temporary visitor to Australia, cognitive impairment, and/or under police guard. Participants who met entry criteria were selected using an automated assignment procedure; stratified by length of stay. 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 (x2 = .80, d f = 1, p = .23), length of hospital admission, t(df = 1,082) = .03, p = .88, injury severity score (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 patients could not be contacted or declined to participate; 989 were inter viewed by telephone (86.8% of the initial sample). Of these patients, 865 participants of the initial 1,139 completed the 12month assessment (76.0%) and 830 participants completed the 24-month assessment (72.9%). Participants at the 24-month follow-up interview did not differ from those who did not partic ipate in terms of gender (x2 = 1.91, d f = 1, p = .17), length of hospital admission, /(1,120) = .43, p = .67, or ISS, /(1,120) = 1.69, p = .09. Those who did not participate in the follow-up assessment had significantly greater PTSD symptoms (M = 20.3, SD = 8.0 vs. M = 16.3, SD = 15.1, r(l,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, f( 1,045) = 2.75, d = 0.1) at baseline, and were
PTSD AND ALCOHOL USE FOLLOWING TRAUMATIC INJURY
significantly younger (M = 35.5 years, SD = 13.3 vs. 39.9 years, SD = 13.5, r(l,103) = 5.39,p < .001, d = 0.3) than those who did participate.
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sis of alcohol abuse and/or dependence. This is a structured diag nostic interview which yields lifetime prevalence of alcohol abuse and dependence based on the DSM-IV (American Psychiatric Association, 1994) criteria for these disorders.
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 for which the participant was hospitalized. At the first time-point, PTSD symptoms were assessed since the injury. In the subsequent time-points, PTSD symptoms were assessed over the past month. The CAPS is considered the gold standard PTSD measure and has excellent psychometric properties (Weathers, Keane, & Davidson, 2001). Each of the 17 PTSD symptoms is rated on frequency and intensity. We conceptualized PTSD in terms of the four-factor solution 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 the benchmark models for the field (Elhai & Palmieri, 2011), and also aligns with recent revisions reflected within DSM-5 (American Psychiatric Association, 2013). We obtained subscale scores for each of these clusters by summing the frequency and intensity scores for each of the symptoms in each cluster. To calculate frequency of endorsement of each PTSD symptom at each timepoint (see Table A in Supplementary Materials), we used the conventional “ 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 CAPS was 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 index active, hazardous, or harmful alcohol use. This scale has excellent psychometric properties (Rumpf, Hapke, Meyer, & John, 2002; Selin, 2003). While the timeframe of the original scale (the past 12 months) was used at the baseline assessment, we modified the scale for subsequent assessments to represent the time since pre vious assessment. We used the total score (representing the sum of all items) in the current study. We determined the proportion of participants engaging in harmful/hazardous alcohol use using the cut-off score of 8 or greater on the AUDIT (Saunders et al., 1993). The internal consistency of the AUDIT in the current study was as follows: baseline a = .85, 3 months a = .82, 12 months a = .82, 24 months a = .85. We assessed prior trauma exposure using the trauma history inventory of the PTSD module of the Composite International Diagnostic Interview (Andrews, Henderson & Hall, 2001), which screens for 11 traumatic life events, including combat, lifethreatening injury, natural disaster, witnessing injury or death, rape, sexual molestation, physical assault, childhood neglect or abuse, threatened with weapon, great shock because of events occurring to other, and “other.” We also added a question on exposure to “torture or terrorism.” Participants were asked to report if they had been exposed to these events before the trauma in which they were injured. We used the Mini International Neuropsychiatric Interview (MINI), Version 5.5 (Sheehan et al., 1998) to assess prior diagno
Procedure Research assistants interviewed traumatic injury survivors just prior to discharge from hospital. At 3 months, 12 months, and 24 months after the trauma, interviews were conducted by telephone (CAPS), and self-report measures returned by post (AUDIT). All participants completed written informed consent procedures. The mean duration between injury and the 3-month assessment was 105.45 days (SD = 26.52). Interviewers were trained and super vised by a clinical psychologist (MOD), and all interviews were audiotaped so that 5% could be rescored by an independent asses sor. Overall, the interrater reliability was strong for both PTSD diagnostic consistency and symptom severity at 3 months (1.00 and 0.84, respectively), 12 months (0.98 and 0.85, respectively), and 24 months (0.96 and 0.82, respectively). Ethical approval for this 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 examine patterns of change in each variable individually. This yielded five models in total (re-experiencing, effortful avoidance, emotional numbing, 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 equation modeling for longitudinal change to investigate the relationship between PTSD symptoms and problem alcohol use over the 2-year course of this study (Ferrer & McArdle, 2010; King, King, McArdle, Shalev, & Doron-LaMarca, 2009). The LDS approach to time sequencing allows for the modeling of three sources of change 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 in scores on a second variable (e.g., changes in problem alcohol use between baseline and 3-month follow-up); (b) autoregressive ef fects or autoproportional change, which represent the influence of the immediately preceding latent score on that same variable’s subsequent difference score; and (c) nonstationarity or constant slope, 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 constructs such as PTSD which have natural courses of change across time. The measurement of constant slope in LDS analyses represents a significant advantage of this approach (i.e., compared with crosslagged analyses, where constant slope is not modeled), as these results take into account the impact of unmeasured or unspecified constructs on the variables included in the analysis after control ling for autoregressive and cross-lagged effects. Analyses were conducted using Mplus version 7.1 (Muthen & Muthen, 1998-2013). Mplus implements a robust full information
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maximum likelihood estimation procedure to account for missing data. This type of analysis uses all available information to arrive at the most likely parameter estimates. Hence, the analysis is based on 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 to generate unbiased parameter estimates in models with substantial missing data (Allison, 2003; Raykov, 2005). Consistent with rec ommendations in the field, we used the following indices to evaluate 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 TuckerLewis 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 score models to evaluate whether a single (autoproportional or con stant change only) or dual (autoproportional and constant change) model best fit the data for the four PTSD symptom clusters and the problem alcohol use variable. This also allowed us to describe the pattern of univariate change in each of these variables. We first estimated a dual change model for each variable, followed by an autoproportional change-only model and 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 autoproportional parameters to equality on model fit. Model fit of nested models was compared using the scaled Satorra-Bentler chi-square dif ference test (Satorra & Bentler, 2001). A significant chi-square statistic represented significant model degradation and the best fitting and most parsimonious model was used for subsequent analyses. Therefore, if there was significant model degradation for either the autoproportional or constant change models com pared with the dual change model, the dual change model was retained. Conversely, if either the autoproportional or constant change models failed to show significant model degradation, these models were used for subsequent analyses. Next, we conducted bivariate latent difference score analyses using models derived from the univariate model testing phase. This encompassed four bivariate models examining the sequence in each of the PTSD symptom clusters and problem alcohol use. The model is presented in Figure 1. In LDS, each observed variable at each time-point is partitioned into a measurement error component and a true score component (i.e., a latent variable). These true score latent variables (represented by p,_4, and a t_4) are used to calculate highly reliable change or difference scores (i.e., repre sented by Ap,_3 and Aa, _3 in Figure 1). This method results in three time-based scores (i.e., four time-points yielding three dif ference scores). Bivariate change is modeled using cross-lagged paths from the latent variable of one construct at time t-1 (e.g., p,) to the latent difference score of the other construct at time /(e.g., Aa,). 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 |3p denoting 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 (O2) and covariances (fl) between variables. For all bivariate LDS models, the error variances of the PTSD indicator variables were constrained to equality to facilitate convergence.
Results Demographic characteristics of study participants collected at baseline are presented in Table 1.
Prevalence of PTSD and Harmful/Hazardous Alcohol Use The prevalence of DSM-IV PTSD diagnosis at each time-point was 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 this study 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 accident 65.9% (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). The average ISS was 11.0 (SD = 8.00), with 20.9% (n = 235) of participants experiencing a severe injury (ISS s 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). Participants reported a mean of 3.2 (SD = 2.8, range = 0 to 13) types of traumatic events throughout their lives (excluding the injury that resulted in hospitalization).
Univariate Analyses Latent growth curve models. In Table 2, we report estimated means derived from the latent growth curve analyses, and actual and possible ranges for observed variables used in the analyses. Each of the univariate latent growth curve models evidenced good fit (see Table 2 for fit statistics). Error variances were allowed to vary freely, with the exception of the re-experiencing and problem alcohol use models where they were constrained to equality to aid convergence. Significant positive mean slopes were evidenced in the active avoidance (mean slope = 0.69, standard error (S£) = 0.12, p < .001) and emotional numbing models (mean slope = 2.21, SE = 0.27, p < .001). Mean slopes were not significant in the re-experiencing (mean slope = —0.06, SE = 0.22, p = .79), hyperarousal (mean slope = 0.01, SE = 0.27, p = .96), and problem 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 no evidence for temporal changes in re-experiencing symptoms, hy perarousal symptoms, and problem alcohol use. LCGM mean slopes will be interpreted further in conjunction with LDS model results below.
PTSD AND ALCOHOL USE FOLLOWING TRAUMATIC INJURY
Figure 1.
LDS model of temporal relationship between PTSD symptoms (p) and problem alcohol use (a).
Univariate latent difference score models. Univariate latent difference score models were fit for each of the PTSD symptom clusters. Table 3 presents the comparative model fit of autopro portional change models and constant change models compared
Table 1 Demographic Characteristics o f 1,139 Injury Patients Admitted to Hospital Following a Traumatic Event
Gender (male) Age Marital status Married/cohabiting Single Education High school only Further education Employment Not employed Employed
825
Mean/N
SDI%
855 37.87
75.07% 13.55
502 526
44.07% 46.18%
401 578
35.21% 50.75%
110 883
9.66% 77.52%
with dual change models. For the effortful avoidance, emotional numbing, and hyperarousal symptom clusters, full dual-change score model specifications with autoproportional change con strained to equality best characterized the trajectories of change. For the re-experiencing symptom cluster, the dual change model with autoproportional change paths varying freely best fit the data (we could not obtain convergence with a dual change model with autoproportional change paths constrained to equality for re experiencing symptoms). For each of the PTSD symptom clusters, the removal of the autoproportional parameters or the constant slope parameter significantly degraded model fit. These findings indicated that change in PTSD symptom clusters over time can be characterized by two components, namely a constant change com ponent and an autoproportional change component. When testing univariate change models for problem alcohol use, it was necessary to center the variable to facilitate convergence for the dual change model (but not the autoproportional change model nor the constant change model). Comparison of models using centered vari ables revealed that the autoproportional change only model best fit the data. As this model did not require centering for convergence, we
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Table 2 Estimated Means and Ranges fo r PTSD Symptom Scores and Problem Alcohol Use at Baseline, 3 Months, 12 Months, and 24 Months
PTSD PTSD PTSD PTSD AUDIT
Re-experiencing symptoms Effortful avoidance symptoms Emotional numbing symptoms Hyperarousal symptoms scores (Problem alcohol use)
Baseline mean
3 months mean
12 months mean
24 months mean
Actual range of scores
Possible range of scores
4.56 1.46 4.12 8.15 6.68
4.86 1.96 5.86 8.61 5.17
4.58 2.12 5.91 7.98 6.15
4.36 2.21 6.46 8.23 6.23
0 to 38 Oto 16 0 to 40 Oto 39 0 to 38
Oto 40 Oto 16 0 to 40 0 to 40 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: x2(6) = 27.13,p < .01, RMSEA = 0.06, CFI = 0.96, TLI, = 0.96; Effortful avoidance model:. x2(3) = 2.11, p = .55, RMSEA = 0.06, CFI = 0.96, TLI, = 0.96; Emotional numbing model: x2(3) = 8.60, p = .04, RMSEA = 0.04, CFI = 0.99, TLI, = 0.98; Hyperarousal model: x2(3) = 10.90, p = .01, RMSEA = 0.05, CFI = 0.99, TLI, = 0.98; Problem alcohol use model: x2(6) = 32.45, p < .001, RMSEA = 0.06, CFI = 0.96, TLI, = 0.96.
reverted to the raw scores for further analyses. Findings indicated that the autoproportional change model with autoproportional change varying freely best fit the data for the problem alcohol use variable. This finding indicated that change in problem alcohol use over time can be best characterized by autoproportional change. Parameters from each of the univariate LDS PTSD symptom and 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 LCGM models, 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 parameter was positive and significant, indicating a general trend to symp tom increase over time. There were also significant negative autoproportional change parameters at each time-point for each of these symptom clusters, indicating that higher levels of PTSD symptoms were associated with greater subsequent de creases (or smaller decreases) in PTSD symptoms at each time-point. Overall, effortful avoidance, emotional numbing and 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 over time.
Table 3 Fit Statistics fo r Univariate Latent Difference Score Models fo r PTSD Symptom Clusters and Problem Alcohol Use
Re-experiencing symptoms Dual change model Autoproportional change model Constant change model Dual change model with autoproportional paths constrained to equality Effortful avoidance symptoms Dual change model Autoproportional change model Constant change model Dual change model with autoproportional paths constrained to equality Emotional numbing symptoms Dual change model Autoproportional change model Constant change model Dual change model with autoproportional paths constrained to equality Hyperarousal symptoms Dual change model Autoproportional change model Constant change model Dual change model with autoproportional paths constrained to equality Problem alcohol use Dual change model (centered values) Autoproportional change model (centered values) Constant change model (centered values) Autoproportional change model (raw scores) Autoproportional change model with autoproportional paths constrained to equality (raw scores)
x2
df
P
CFI
RMSEA
X2A
d/A
P
16.98 44.42 21.11
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