Psychiatry 77(3) Fall 2014

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Predictors of Length of Stay Among OEF/ OIF/OND Veteran Inpatient PTSD Treatment Noncompleters Derek D. Szafranski, Daniel F. Gros, Deleene S. Menefee, Jill L. Wanner, and Peter J. Norton

High rates of attrition occur in outpatient and inpatient evidence-based treatments (EBTs) targeting newly returning veterans from Operation Enduring Freedom (OEF), Operation Iraqi Freedom (OIF) and Operation New Dawn (OND) with posttraumatic stress disorder (PTSD). Traditionally, research has examined attrition as a dichotomous variable (i.e., noncompleters vs. completers) and focused almost exclusively on outpatient EBTs for PTSD. These studies have provided little information to inpatient psychiatric providers about timing-related predictors of treatment discontinuation. The present study attempted to mend these gaps by examining attrition as a continuous variable and investigated predictors of length of stay (LOS) among 282 OEF/OIF/OND male veterans, 69 of which did not complete the full 25-day intensive, multimodal inpatient PTSD EBT program. At admission, participants completed a series of clinician-rated, biological, and self-report assessments. Linear regression analyses were used to identify predictors of shorter LOS. The results demonstrated that less improvement in symptom reduction, overall functioning, and greater number of drugs used at admission were significant and unique predictors of shorter LOS. Overall, these findings reveal clinically relevant, timing-related predictors of attrition and provide generalizable clinical information to inpatient psychiatric providers.

Derek D. Szafranski, M.A., is affiliated with the Department of Psychology at the University of Houston in Houston, Texas, and with the Michael E. DeBakey Veterans Affairs Medical Center in Houston. Daniel F. Gros, Ph.D., is affiliated with the Ralph H. Johnson Veterans Affairs Medical Center in Charleston, South Carolina, and with the Department of Psychiatry and Behavioral Sciences at the Medical University of South Carolina in Charleston. Deleene S. Menefee, Ph.D., and Jill L. Wanner, Ph.D., are with the Michael E. DeBakey Veterans Affairs Medical Center in Houston and with the Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, in Houston. Peter J. Norton, Ph.D., is with the Department of Psychology at the University of Houston. This material is the result of work supported with resources and the use of facilities at the Michael E. DeBakey Veterans Affairs Medical Center in Houston, Texas, the South Central Mental Illness Research, Education and Clinical Centers (MIRECC), and the Traumatic Brain Injury Center of Excellence in Houston. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government. Address correspondence to Derek D. Szafranski, M.A., Department of Psychology, 126 Heyne Bldg., University of Houston, Houston, TX, 77204-5022. E-mail: [email protected] © 2014 Washington School of Psychiatry

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Posttraumatic stress disorder (PTSD) is highly prevalent among veterans returning from Operation Enduring Freedom (OEF), Operation Iraqi Freedom (OIF), and Operation New Dawn (OND) (12–17%; Erbes, Westermeyer, Engdahl, & Johnsen, 2007; Hoge et al., 2004). Individuals diagnosed with PTSD often display significant impairment in social, occupational, cognitive, and health functioning (Burriss, Ayers, Ginsberg, & Powell, 2008; Davidson, 2001) along with elevated suicide rates (Benda, 2005). Fortunately, a great deal of research suggests evidence-based treatments (EBTs), such as prolonged exposure (PE; Foa, Hembree, & Rothbaum, 2007) and cognitive processing therapy (CPT; Resick, Monson, & Chard, 2010) are effective in reducing PTSD symptoms in outpatient (Rizvi, Vogt, & Resick, 2009; Tuerk et al., 2012) and residential settings (Chard, Schumm, McIlvain, Bailey, & Parkinson, 2011). Regrettably, high rates of treatment discontinuation are found in the Veterans Affairs Medical Centers (VAMCs) outpatient (38–68%; Garcia, Kelley, Rentz, & Lee, 2011; Gros, Yoder, Tuerk, Lozano, & Acierno, 2011) and residential EBT programs targeting OEF/OIF/OND veterans with PTSD (11%; Chard et al., 2011). Attrition directly inhibits veterans’ ability to refine, crystallize, and implement therapeutic skills, thus diminishing the chances of symptom reduction. Within outpatient EBT studies, treatment noncompleters experience significantly less PTSD symptom reduction and require more future service utilization than treatment completers (Tuerk et al., 2012). As a result of high attrition rates and the negative impact associated with it, an effort has been made to find clinically relevant predictors of discontinuation from outpatient EBTs. Demographic predictors of attrition from outpatient EBTs for PTSD include male gender (van Minnen Arntz, & Keijsers, 2002), younger age (Garcia et al., 2011), and African American race (Lester, Artz, Resick, & Young-Xu, 2010). Lower intelligence and less education have also been linked to early

Predictors of Length of Stay

termination from outpatient EBTs (Rizvi et al., 2009). Higher PTSD symptom severity, problematic personality characteristics (Garcia et al., 2011), psychiatric comorbidity (Lu, Duckart, O’Malley, & Dobscha, 2011), and high alcohol use are clinical variables often related to attrition from outpatient EBTs for PTSD within veteran populations (van Minnen et al., 2002). Conversely, benzodiazepine use, although contraindicated for PTSD treatment (Abrams, Lund, Bernardy, & Friedman, 2013), is related to outpatient EBT completion, but no relationship has been found between depression and treatment discontinuation or completion (van Minnen et al., 2002). Military variables have been studied to a lesser extent and have produced contradictory findings. For example, one study identified disability status as a predictor of attrition from outpatient exposure therapy (Gros, Price, Yuen, & Acierno, 2013), whereas other studies show no relationship between disability status and attrition (Garcia et al., 2011; Gros et al., 2011). Differential findings may be a result of variations in populations, settings, and/or treatments. Additional gaps in the attrition literature are noted as well. Most studies examine attrition as a dichotomous variable (i.e., noncompleters vs. completers), eliminating the possibility of identifying when participants drop out or timing-related causes of attrition (e.g., pretreatment variables and introduction of treatment content). Second, research studies specifically examining predictors of attrition within OEF/OIF/OND veteran populations have been conducted only in outpatient EBT settings (Erbes, Curry, & Leskela, 2009; Garcia et al., 2011; Gros et al., 2011). In fact, only one study has examined predictors of attrition within Vietnam veterans receiving inpatient treatment (Munley, Bains, Frazee, & Schwartz, 1994). From a population of 117 veterans diagnosed with PTSD, Munley and colleagues compared 14 treatment noncompleters and 14 randomly selected treatment completers on a variety of measures. In addition to daily group therapy,

Szafranski et al. 265

participants partook in journal writing for self-development, relaxation training, leisure education, and employment workshops, but no specific details were provided about frequency, duration, or type of protocols used for any of the treatment modalities. Comparisons between treatment noncompleters and randomly selected completers displayed no significant findings and were likely underpowered to run such analyses. To the best of our knowledge, no study has examined attrition as a continuous variable or investigated timing-related predictors of attrition from a voluntary inpatient EBT program for PTSD consisting of OEF/OIF/ OND veterans. This is surprising given the multitude of reasons for treatment noncompletion and the marked differences between inpatient and outpatient treatment populations, protocols, and settings, along with the uniqueness of OEF/OIF/OND veterans. For example, OEF/OIF/OND veterans discontinue treatment at higher rates compared to Vietnam and Gulf War veterans (Erbes et al., 2009; Gros et al., 2011; Yoder et al., 2012). Patients who self-admit to an inpatient treatment program frequently report more severe pretreatment ratings across a variety of psychiatric disorders, including PTSD (Foa, Keane, Friedman, & Cohen, 2009). Further, outpatient settings regularly exclude veterans with substance abuse and acute suicidality (Teng et al., 2008). The general format of treatment also differs, as outpatient treatments commonly consistent of 10–20 weekly individual psychotherapy appointments dependent in part on patient/provider availability, scheduling, and transportation. On the other hand, inpatient programs offer more comprehensive and intensive massed treatments without limiting exclusionary criteria, repeat visits, and/or potential challenges in scheduling and transportation. As a result of these differences, predictors of attrition from outpatient EBT studies may not generalize to inpatient EBTs, leaving limited empirical evidence to guide inpatient psychiatric treatment.

The purpose of this study was to examine predictors of length of stay in treatment (LOS) among OEF/OIF/OND veterans who did not complete an integrated voluntary inpatient treatment program for PTSD—Returning OEF/OIF/OND Veterans’ Environment of Recovery (ROVER). Based on previous research, we hypothesized that race (Lester et al., 2010), less education (Rizvi et al., 2009), younger age, greater PTSD symptom severity (Garcia et al., 2011), greater number of drugs used at admission (van Minnen et al., 2002), and greater psychiatric comorbidity (Lu et al., 2011) would significantly predict shorter LOS. Similar to Tuerk and colleagues’ (2012) findings and in contrast to recent suggestions that OEF/OIF/ OND veterans drop out at higher rates due to quicker improvement during treatment (Erbes et al., 2009), we hypothesized that less improvement in symptomatology and fewer improvements in overall functioning would also be significant unique predictors of shorter treatment duration. Finally, suicidality and military-related factors have not been thoroughly examined as predictors of attrition and were explored without hypothesis. However, as this was the first study to investigate attrition in EBTs in an inpatient setting and with this number of predictor variables, no precise hypotheses were made regarding the potential interaction and overlap between the predictors. METHODS

Procedure Upon admission into ROVER, veterans were approached to participate in a program evaluation study using a protocol approved by the local institutional review board. Veterans were informed that not participating in the research would not hinder or enhance their treatment. Veterans who provided informed consent to participate in research were included in this study. Ap-

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proximately 10 participants were enrolled monthly. Upon admission, participants provided urine samples to screen for illicit drugs and alcohol currently in the participants’ system. Prior to treatment, all participants were assessed for PTSD via a structured clinical interview consisting of the Clinician-Administered PTSD Scale (CAPS; Blake et al., 1995). Veterans also completed self-report measures regarding demographic/military information, pretreatment symptom severity, and overall functioning utilizing a variety of psychological measures prior to treatment. All participants met with each member of the treatment staff (e.g., psychologist, psychiatrist, social worker, registered nurses, psychology interns and externs) and had an opportunity to ask programmatic and research study questions. Participants who terminated early completed a discharge interview consisting of a suicide risk assessment and answered open-ended questions pertaining symptomatology and overall functioning. Treatment Protocol ROVER is a 25-day comprehensive massed EBT program. Participants receive treatment from 8:00 am to 4:30 pm. The primary PTSD treatment utilized is a combined group and individual CPT full protocol (Resick et al., 2010) modified for the inpatient setting, along with extensive psychoeducation for building coping skills. Staff psychiatrists provide regular medication management throughout treatment. Psychiatrists communicate daily with participants and psychologists in order to find the most beneficial medication regimen. To address frequently co-occurring affect regulation and distress tolerance deficits associated with PTSD, participants receive group dialectical behavior therapy skills training (Linehan, 1993) plus group anger management (McKay & Rogers, 2000), occupational therapy, and group substance use treatment (Najavits, 2002). Participants are also provided times for exercise an average four times a

week (e.g., yoga, weight training, and cardio) and have access to VA equipment. Individual bi-weekly interdisciplinary treatment team rounds consisting of all treatment staff and each participant are provided for feedback and problems-solving purposes. Behavioral activation (Wagner, Zatzick, Ghesquiere, & Jurkovich, 2007) is provided in the form of weekday/weekend outings, such as sailing trips, movies, and kayaking classes, along with contingency-based unsupervised off-unit free time (Monteith, Menefee, Pettit, Leopoulos, & Vincent, 2013). Measures: Structured Diagnostic Assessment Clinician-Administered PTSD Scale (CAPS). The CAPS (Blake et al., 1995) is a 30-item structured interview based on Diagnostic and Statistical Manual’s (DSM-IV TR; American Psychiatric Association, 2000) criteria for PTSD. The CAPS uses a five-point scale to determine frequency (0 = none to 4 = daily or almost every day) and intensity (0 = none to 4 = extreme). The CAPS displays excellent internal consistency (α = .94), acceptable-to-excellent test-retest reliability (rs range from .77 to .96), and acceptableto-excellent convergent validity (r =.91) with other self-report measures of PTSD (Blake et al., 1995). Measures: Clinician-Rated Measures Rate of Improvement During Treatment Scale (RIDT). The RIDT is a 1-item measure that allows clinicians to assess overall response to treatment and symptom improvement from admission to discharge from treatment and utilizes a five-point Likert scale (1 = very much improved to 5 = slight deterioration). The interdisciplinary treatment team assigns the RIDT by group consensus (i.e., psychiatrist, psychologist, and social worker at a minimum) during diagnostic and clinical case conferencing concerning each patient prior to discharge. The RIDT was created

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for clinical and research purposes prior to the onset of this project. No psychometric properties have been reported for the RIDT. Global Assessment of Functioning Change Score (GAF-C). The Global Assessment of Function Scale (GAF; American Psychiatric Association, 2000) is a widely used measure of overall functioning. The GAF is often used in conjunction with standardized structured clinical assessments such as the CAPS. The GAF has a range of 0 to 100, with higher scores indicating more adaptive functioning. The GAF displays good interrater reliability within veteran populations (ICC = .82; Jovanović, GaSic, Ivković, Milovanović, & Damjanović, 2008). The GAF-C represents the difference between discharge and admission GAF scores, with higher numbers indicating greater improvement in adaptive functioning from admission to discharge. Axis I and II Diagnoses. At admission, the interdisciplinary treatment team summarizes the admission packet and formulates a diagnostic assessment of using the DSM-IV-TR (American Psychiatric Association, 2000). In the current sample, PTSD was most likely to co-occur with mood disorders (61%) and substance dependence (74%), and less likely to occur with anxiety (13%) and personality disorders (23%). Measures: Biological Measure Urine Drug Screen (UDS). The admission urine drug screen is administered at admission and assesses for biological evidence of drugs currently in veterans’ systems. Specifically, the UDS assesses for the presence (1 = yes) or absence (0 = no) of benzodiazepine, cannabis, methadone, opiates, ethanol, barbiturates, amphetamine, and cocaine at predetermined hospital-wide lab values. The VAMC at which this data was collected specifically tests for methadone, due to the high prevalence rates within the region and due to a large methadone clinic housed within

the facility. Tracking methadone separately from other opiates fulfills hospital mandates and helps physicians with compliance. The UDS variable was calculated by summing the number of the eight drugs identified and had a possible range of 0 to 8, with higher numbers indicating higher concurrent drug use at admission. Measures: Self-Report Measures PTSD Checklist Military Version (PCL-M). The PCL-M (Weathers & Ford, 1996) is a widely accepted17-item self-report measure of patients’ perceptions of PTSD re-experiencing, avoidance, and hyperarousal symptoms. Participants use a five-point scale (1 = not at all to 5 = extremely) to indicate how much they have been bothered by each of the 17 symptoms of the DSM-IV TR criteria for PTSD in the past month. Higher scores indicate greater perceptions of disturbance but are not indicative of a PTSD diagnosis unless other DSM-IV criteria are also met. The PCL displays good internal consistency (α > .80), acceptable test-retest reliability (rs > .70), and good convergent validity with the PTSD section of the Structured Clinical Interview for DSM-IV (Wilkins, Lang, & Norman, 2011). In the current study, the internal consistency estimate was α = .92. Beck Depression Inventory-II (BDI-II). The BDI-II (Beck, Steer & Brown, 1996) is a 21-item, self-report measure of depressive symptoms and depressogenic cognitions associated with depression. The BDI-II uses a four-point scale to determine frequency (0 = no presence of the identified symptoms to 3 = constant presence of the identified symptoms). The BDI-II demonstrates excellent one-week test-retest reliability (r = .93), excellent internal consistency (αs < .92), and convergent validity in multiple samples (Beck et al., 1996). In the current study, the internal consistency estimate was α = .92.

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Beck Scale for Suicide Ideation (BSS). The BSS (Beck & Steer, 1991) is a 21-item measure of suicidal cognitions. The BSS uses a three-point scale (0 = no presence of the identify symptom to 2 = constant presence of the identified symptom) on 19 items to determine the lethality of the suicidal ideation. Two items measure the number of prior suicidal attempts and the intensity of the wish to die during the last attempt. The BSS displays excellent internal consistency (α = .96), good reliability, and good concurrent validity (r = .90) with psychiatrist’s suicide ratings (Beck, Steer, & Ranieri, 1988). In the current study, the internal consistency estimate was α = .93. Analytic Plan The primary goal of this study was to identify predictors of LOS from a multifaceted inpatient PTSD treatment program. Similar to Garcia and colleagues (2011), a two-step model-building approach was used to identify predictors. In step 1, appropriate bivariate analyses and one-way ANOVA analyses were utilized to examine demographic (age, race, education level), military (military branch, number of deployments, total service connection rate, service connection rate for mental health reasons, distance away from home VA, and military rank), and clinical variables (CAPS-F+I, RIDT, GAF-C, UDS, PCL-M, BDI-II, and BSS) that previous literature identified as possible predictors of treatment noncompletion or have not been examined (e.g., military variables). The ratio of no more than one predictor per 10 participants is recommended for regression analyses (Peduzzi, Concato, Kemper, Holford, & Feinstein, 1996). And so, variables from the bivariate analyses with an α < .20 were deemed eligible predictors in order to meet ratio recommendations. In step 2, eligible predictors were entered into a standard linear regression (enter/default method). Missing data were filled via mean substitution.

RESULTS

Demographics and UDS Findings The majority of participants were referred by their mental health providers at their local VAMC in one of the six surrounding states. Of the 296 male participants admitted to ROVER, 14 (4.7%) did not consent to participate in research and were excluded from the study. Of the 282 remaining male participants, 69 (25%) did not complete the full treatment protocol (i.e., they discontinued treatment prior to graduation on day 25). The participants were predominantly young adults (M age = 29.7, SD = 5.2), white (79%), unemployed (62%), single (52%), did not have a college degree (83%) and were service connected/disabled (83%). Slightly more than half (57%) were service connected specifically for mental health reasons (e.g., PTSD), 48% reported experiencing a mild traumatic brain injury, and 10% indicated that they were homeless at the time of admission. Finally, the majority of participants served in the Army (67%). Results from the UDS revealed that 60% of participants tested positive for a substance. Cannabis was the most commonly found substance (40%), followed by benzodiazepine (29%), opiates (12%), methadone (3.0%), ethanol (1.5%), barbiturates (1.5%), amphetamine (1.5%), and cocaine (1.5%). Factors Associated With Shorter Length of Stay Bivariate correlations between LOS and continuous variables are presented in Table 1. Step 1 analyses identified five variables that met the α < .20 cutoff requirement for entry into linear regression analysis. Less symptom improvement during treatment (RIDT), less improvement in overall func-

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TABLE 1. Means, Standard Deviations, and Correlations of Predictor Variables With Length of Stay Among 69 Noncompleters Variables

M

SD

Length of Staya (LOS)

11.67

7.22

r

p

Age

29.66

5.24

–0.13

0.304

Service Connection Total (SC-T)

0.52

0.34

0.12

0.360

Service Connection for Mental Health (SC-MH)

0.40

0.34

0.12

0.415

Distance from VA

96.74

182.36

–0.12

0.432

Military Rank

4.70

1.14

0.10

0.419

Number of Deployments

1.75

0.88

0.07

0.580

Clinician-Administered PTSD Scale (CAPS)

78.26

20.17

–0.11

0.428

Rate of Improvement During Treatment (RIDT)

3.47

0.77

–0.35

0.004

Global Assessment of Functioning Change Score (GAF-C)

7.10

7.65

0.42

0.001

Urinary Drug Screening (UDS)

2.22

2.06

–0.28

0.025

The PTSD Checklist Military Version (PCL-M)

69.00

11.11

0.12

0.370

Beck Depression Inventory-II (BDI-II)

34.46

13.54

0.06

0.616

Total Comorbid Diagnoses (TCD)

3.46

1.01

0.24

0.047

Beck Scale for Suicidality (BSS)

5.91

7.22

–0.18

0.177

Note. ROVER program length of treatment stay for completers is 25 days. a

tioning (GAF-C), higher concurrent drug use at admission (UDS), higher suicidality, and fewer comorbid psychiatric conditions were associated with shorter LOS. One-way ANOVA analyses revealed no difference in LOS for levels of education, race, or military branch (ps > 0.05). Predictors of Shorter Length of Stay Linear regression results can be found in Table 2. A total of five variables met the α < .20 criteria (i.e., RIDT, GAF-C, UDS, total comorbid diagnoses [TCD], and BSS) and were eligible for entry into linear regression analysis. The overall model was significant, R2 = .361, F(5, 63), = 7.11, p < .001. Three of the five variables were found to be significant unique predictors of shorter LOS, including less improvement in overall symptomatology during treatment (RIDT), less improvement in overall functioning from admission to discharge (GAF-C), and higher concurrent drug use at admission (UDS). In order to assess

for evidence of multicollinearity of suppression, bivariate correlations were conducted between all predictor variables. Results revealed no significant correlations between variables, providing no evidence for multicollinearity issues (rs < .20). DISCUSSION

The present study examined predictors of length of stay (LOS) among OEF/ OIF/OND veterans who did not complete a voluntary inpatient EBT program for PTSD (ROVER). Prior to this study, research had yet to examine timing-related predictors of treatment discontinuation of inpatient services within this high-risk population. Three variables were found to be unique predictors of shorter LOS, namely lower overall symptom improvement during treatment (RIDT), less improvement in overall functioning from admission to discharge (GAF-C), and higher concurrent drug use at admission (UDS). The

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TABLE 2. Linear Regression Results Predicting Length of Stay Among Noncompleters (n = 69) B

SE for B

β

I

Partial r

RIDT

–3.00

0.99

–0.31

–3.02**

–0.36

GAF-C

0.28

0.10

0.29

2.73**

0.33

UDS

–1.00

0.37

–0.27

–2.69*

–0.32

TCD

1.31

0.76

0.18

1.72

0.21

BSS

–0.16

0.11

–0.14

–1.39

–0.17

Variable

Note: R2 = .36, F(5, 65) = 7.37, p < .001. RIDT = Rate of Improvement During Treatment; GAF-C = Global Assessment of Functioning Change Scores; UDS = Urinary Drug Screening total; TCD = Total Comorbid Diagnoses; BSS = Beck Scale for Suicidality. *p < .05, **p < .01.

lack of relationship for PTSD symptom severity and age (Garcia et al., 2011), as well as education (Rizvi et al., 2009), race (Lester et al., 2010), and disability status and social support (Gros et al., 2013) are of note. These findings provide insight into variables negatively effecting inpatient EBT completion for OEF/OIF/OND veterans with PTSD and suggest clinically relevant solutions that may result in higher completion rates and increased outcomes (Tuerk et al., 2012). The three unique predictors of shorter LOS yield important clinical implications regarding assessment and EBT protocols within inpatient PTSD treatment settings. These findings are similar to those reported in Tuerk and colleagues’ (2012) outpatient study, suggesting that OEF/OIF/OND veterans displaying fewer improvements in overall symptom severity and impairment are more likely to drop out of treatment early on. It also provides important evidence against a recent theory suggesting that, OEF/ OIF/OND veterans discontinue treatment at an increased rate compared to other war eras, due to quicker improvements in symptomatology (Erbes et al., 2009). As a result, assessment procedures should include brief, easy to administer clinician-rated impairment measures such as the RIDT and GAF. Throughout the course of treatment, providers should regularly assess these variables and pay special attention to participants who do not display improvements, especially early on in treatment. For these at-risk participants, altering treatment protocols by including motivational enhancement techniques such as motivational interviewing (Miller &

Rollnick, 2002) should be considered for future investigation into treatment adherence. Finally, future studies should include regularly administered measures of specific disorder-related symptomatology (e.g., PCL-M, BDI-II, etc.), in order to further elucidate the relationship between symptom change and timing of discontinuation from EBTs. Findings revealed that participants with high concurrent drug use at admission were more likely to discontinue treatment early on. These findings are similar to reports linking high alcohol use to treatment discontinuation and dissimilar to reports linking benzodiazepine use to treatment completion (van Minnen et al., 2002). Clinical observations and veteran statements suggest that many veterans discontinue treatment as a result of disagreement as to medication management on the unit. Due to the contraindications in the 2012 Institute of Medicine (IOM) report on PTSD treatment, veterans are safely medically tapered off contraindicated medications (e.g., benzodiazepines and opiates) upon admission into ROVER. Alcohol withdrawal is closely monitored and, if necessary, medical detoxification is used. This process is explained and veterans agreed to this prior to admission to the program. However, it is possible that veterans abusing multiple drugs are wary of this approach once implemented and may experience mild withdrawal symptoms and/or wish to continue to use these substances, which could ultimately lead to early termination from inpatient PTSD treatment. This finding is noteworthy to inpatient psychiatric providers that implement similar methods

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of treatment. Providing additional substance abuse treatments (e.g., MI for substance abuse or medical detoxification) early on in the treatment process and regular communication between psychologists and psychiatrists regarding management of withdrawal symptoms could reduce dropout among these high-risk patients. Given the relationship between PTSD, substance abuse, and increased suicide rates in veterans (Benda, 2005), increasing treatment adherence for this subgroup of OEF/OIF/OND veterans is particularly important. Although comorbidity approached statistical significance in step 2 analyses, it did not reach the p < .05 cutoff. This is dissimilar to previous findings that identified psychiatric comorbidity as a unique predictor of attrition (Lu et al., 2011). It is possible this null finding is a result of the small sample size and/or high occurrence of comorbidity in this study. Given that comorbidity displayed a significant positive correlation with LOS in step 1 analyses, approached statistical significance as a unique predictor in regression analyses (step 2), and previous literature has identified comorbidity as a predictor of attrition, inpatient treatment providers may consider referring individuals with fewer comorbid conditions to more tailored outpatient treatments such as PE or CPT alone. It is also possible that veterans diagnosed with a number of comorbid conditions are more likely to benefit from multifaceted inpatient programs or transdiagnostic outpatient treatments (Gros et al., 2012; Norton et al., 2013). Future studies should directly compare these types of inpatient and outpatient transdiagnostic and multifaceted EBTs with diagnostic-specific protocols for PTSD, in order to assess the effects of treatment modality/setting on attrition rates and outcomes. Surprisingly and contrary to our initial hypothesis, results indicated that age, PTSD symptom severity (Garcia et al., 2011), disability status, and social support (Gros et al., 2013), education (Rizvi et al., 2009), and race (Lester et al., 2010) were not predictors

of LOS and attrition. These contradictory findings highlight problems with generalizability of outpatient findings to inpatient EBT programs. Inpatient treatment providers should be cautious when utilizing outpatient studies to inform their assessment and treatment protocols, especially when trying to identify at-risk individuals. Clinicians from both inpatient and outpatient settings may find it advantageous to utilize studies more closely resembling their specific treatment setting and modality. These findings also show the importance and uniqueness of studies examining attrition as a continuous variable and those utilizing inpatient populations. Given the importance associated with treatment completion (Tuerk et al., 2012), more research is needed in these specific areas. Limitations Five primary limitations were noted in this study. First, the majority of data were collected at pre- and post-treatment instead of continually (e.g., once a week). Most participants who discontinued the inpatient program did not complete post-treatment questionnaires. As a result, the only change variables recorded were clinician oriented (RIDT and GAF-C). This limited the ability to examine specific symptomatic change as it relates to LOS. A second limitation is lack of a control and/or comparison group, which inhibited treatment modality comparisons. The lack of comparison group may inhibit generalizability of findings to other inpatient units utilizing different treatment protocols. Third, roughly half (48%) of participants reported experiencing a mild traumatic brain injury. Although clinical observations suggested that mild traumatic brain injuries did not affect attrition, future research should examine this more in depth. Fourth, this study consisted of only male OEF/OIF/ OND veteran participants. Clinicians treating female veterans should be cautious when implementing clinical suggestions resulting

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from these findings until similar studies with female samples are completed. Finally, Clinical Institute Withdrawal Assessments (CIWAs) were only completed when indicated by the attending psychiatrist, which led to an inconsistency in data collection. Future studies should include regular administrations of CIWAs in order to examine the relationship between withdrawal symptoms and treatment dropout. CONCLUSION

The present study examined attrition as a continuous variable and represents the first investigation of predictors of LOS in a standardized inpatient EBT program for

PTSD. Less improvement in overall symptomatology (RIDT), less improvement in overall functioning (GAF-C), and higher concurrent drug use at admission (UDS) were associated with shorter LOS in the population of treatment noncompleters. In order to reduce OEF/OIF/OND veterans’ attrition from PTSD inpatient treatments, clinicians should consider assessing and closely monitoring these clinical factors, especially early on in treatment, further investigating their standard treatment protocols to address related symptoms (e.g., drug abuse treatment for veterans testing positive for multiple drug use). With these types of adjustments to current inpatient practices, it may be possible to reduce attrition rates and improve LOS and therefore improve treatment outcomes in this high-risk population.

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