Journal of Consulting and Clinical Psychology 2014, Vol. 82, No. 4, 551–561

In the public domain http://dx.doi.org/10.1037/a0037075

Cognitive Processing Therapy for Veterans With Posttraumatic Stress Disorder: A Comparison Between Outpatient and Residential Treatment Kristen H. Walter

Ruth L. Varkovitzky

Veterans Medical Research Foundation, San Diego, California, and Veterans Affairs San Diego Healthcare System, San Diego, California

Veterans Affairs Puget Sound Healthcare System, American Lake Division, Tacoma, Washington

Gina P. Owens

Jennifer Lewis

University of Tennessee–Knoxville

Cincinnati Veterans Affairs Medical Center, Cincinnati, Ohio

Kathleen M. Chard Cincinnati Veterans Affairs Medical Center, Cincinnati, Ohio, and University of Cincinnati Objective: Across the Veterans Affairs (VA) Healthcare System, outpatient and residential posttraumatic stress disorder (PTSD) treatment programs are available to veterans of all ages and both genders; however, no research to date has compared these treatment options. This study compared veterans who received outpatient (n ⫽ 514) to those who received residential treatment (n ⫽ 478) within a VA specialty clinic on demographic and pretreatment symptom variables. Further, the study examined preto posttreatment symptom trajectories across the treatment programs. Method: All 992 veterans met diagnostic criteria for PTSD and attended at least 1 session of cognitive processing therapy (CPT) in either the outpatient or residential program. Bivariate analyses were utilized to investigate differences between samples on demographic variables and severity of pretreatment symptoms. Multilevel modeling (MLM) was used to investigate the change in symptomatology between the 2 samples from pre- to posttreatment. Results: Analyses indicated that the samples differed on all demographic and pretreatment symptom variables, with residential patients reporting higher scores on all assessment measures. MLM results demonstrated that symptom scores improved for all veterans across time, with outpatients consistently reporting fewer symptoms at both time points. The time by program interaction was significant for PTSD-related symptom trajectories, but not for the depression-related symptom trajectory. Conclusion: This is the 1st study to compare pretreatment characteristics and treatment outcome between veterans receiving outpatient and residential PTSD treatment. Findings may help clinicians select appropriate care for their patients by identifying relevant pretreatment characteristics and generally informing expectations of treatment outcome. Keywords: posttraumatic stress disorder, cognitive processing therapy, outpatient treatment, residential treatment, veterans

Many veterans seeking mental health care at the Department of Veterans Affairs (VA) have experienced various traumatic events, such as combat, childhood trauma, intimate partner violence, and sexual assault (Clancy et al., 2006). Such traumatic experiences may lead to development of posttraumatic stress disorder (PTSD), depression, other anxiety disorders, and related symptomatology (Hoge et

al., 2004). Estimates suggest that 19%–30% of Vietnam veterans have met lifetime criteria for PTSD (Dohrenwend et al., 2006), and as many as 22% of Operation Iraqi Freedom/Operation Enduring Freedom veterans seeking VA care met PTSD criteria (Seal et al., 2009). To meet these critical treatment needs, the VA provides a continuum of options for PTSD care, including outpatient and

This article was published Online First June 9, 2014. Kristen H. Walter, Health Services Research & Development, Veterans Medical Research Foundation, San Diego, California, and Research Service, Veterans Affairs San Diego Healthcare System, San Diego, California; Ruth L. Varkovitzky, PTSD Outpatient Clinic, Veterans Affairs Puget Sound Health Care System, American Lake Division, Tacoma, Washington; Gina P. Owens, Department of Psychology, University of Tennessee–Knoxville; Jennifer Lewis, Trauma Recovery Center, Cincinnati Veterans Affairs Medical Center, Cincinnati, Ohio; Kathleen M. Chard, Trauma Recovery Center, Cincinnati Veterans

Affairs Medical Center, Cincinnati, Ohio, and Department of Psychiatry, University of Cincinnati. We would like to thank the staff of the Trauma Recovery Center at the Cincinnati Veterans Affairs Medical Center, particularly Jeremiah Schumm, as well as the data preparation efforts of Lindsey Davidson and Misty Wolfe. Content of this article does not necessarily reflect the views of the United States government or the Department of Veterans Affairs. Correspondence concerning this article should be addressed to Kristen H. Walter, Veterans Medical Research Foundation, 3350 La Jolla Village Dr. (111N1), Building 13, San Diego, CA, 92161. E-mail: [email protected] 551

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residential treatment programs. The Veterans Health Administration (VHA) has produced guidelines for matching patient needs to the intensity of care required (U.S. Department of Veterans Affairs, 2010). According to these guidelines, outpatient treatment is intended to serve individuals with new onset or severe PTSD, while residential treatment is meant to provide a semistructured environment of rehabilitation where veterans can engage in PTSD treatment and sobriety efforts and address medical and psychological needs prior to full reintegration into the community (U.S. Department of Veterans Affairs, 2010). In part based on the intended population that residential programs aim to serve, a common assumption exists among providers that individuals in residential treatment present with greater symptom severity and functional impairment and, in turn, may not achieve as many treatment gains as outpatients. Despite this assumption, no empirical literature to date has compared patients in residential and outpatient treatment for PTSD.

Evidence-Based PTSD Treatment in the VA Two evidence-based treatments for PTSD are currently being disseminated through the VA system (Karlin et al., 2010), including cognitive processing therapy (CPT; Resick, Monson, & Chard, 2010) and prolonged exposure (PE; Foa, Hembree, & Rothbaum, 2007). Both CPT and PE are considered best practice models (Foa, Keane, Friedman, & Cohen, 2008) and have been shown to effectively reduce PTSD and depression symptoms among veterans (Monson et al., 2006; Schnurr et al., 2007; Tuerk et al., 2011). Further treatment outcome research has explored the use of CPT with veterans in residential and outpatient programs and has demonstrated that CPT effectively reduces symptoms of PTSD and depression for veterans receiving treatment in both types of settings (Alvarez et al., 2011; Monson et al., 2006). CPT (rather than PE) was the treatment of focus in the present study, as it was the primary treatment modality used in the residential program at the VA clinic in which this study was conducted. In an effort to make meaningful comparisons between residential and outpatient treatment, we included only veterans receiving CPT in the current examination. CPT can be delivered in several formats, including individual (Resick et al., 2010), group, and in a format which combines individual and group sessions received concurrently (Chard, Resick, Monson, & Kattar, 2009), with the various formats effectively reducing PTSD symptoms in veteran samples (Monson et al., 2006; Walter, Bolte, Owens, & Chard, 2012). Literature supporting the use of CPT in a group format was another reason CPT was selected as the trauma-focused treatment modality. To date, no treatment outcome studies have compared outpatient and residential samples in terms of either pretreatment individual differences or symptom change trajectories. Such comparisons may shed light on the implementation of VA levels of care and allow clinicians to identify and use specific patient characteristics to improve treatment planning. Based on review of the literature previously mentioned, the goal of the current study was to empirically examine whether veterans receiving CPT for PTSD in outpatient treatment (individual CPT format) versus residential treatment (combined individual and group CPT format) differed in terms of pretreatment demographic variables, symptom severity, and treatment outcome. We hypoth-

esized that as residential treatment is designed for veterans with more impairing symptoms and complex psychosocial stressors, residential patients would endorse greater PTSD and depression symptom severity at pretreatment compared with outpatients. We also hypothesized that veterans in both programs would benefit from treatment as evidenced by reductions in PTSD and depression symptoms. Due to the lack of preexisting research, analyses comparing treatment outcome trajectory across groups were exploratory.

Method Participants Participants included 992 male and female veterans admitted to either the outpatient (n ⫽ 514) or residential (n ⫽ 478) PTSD programs at a midwestern Veterans Affairs medical center between 2007 and 2011. All participants met full diagnostic criteria for PTSD as set forth in the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM–IV–TR; American Psychiatric Association, 2000) and as assessed by the ClinicianAdministered PTSD Scale (CAPS; Blake et al., 1995). All participants attended at least one, but no more than 15, sessions of individual CPT in either the outpatient or residential treatment program. A referral was the only eligibility criterion and was used to determine whether treatment was received in the outpatient or residential treatment program. To be eligible for the outpatient and residential PTSD programs, veterans could either be self-referred or referred by a care provider within the VA Healthcare System. Eligibility for the residential program did not require veterans to have comorbid diagnoses or to have received (or not responded to) prior treatment; however, veterans did commonly present with comorbid conditions and prior treatment experience. Participants were excluded from the study for the following reasons: active substance dependence, current unmanaged psychosis, a significant interfering medical condition (e.g., unmedicated seizure disorder), or the presence of suicidal or homicidal intentions (individuals with ideation but not intention were included). Eleven participants were excluded as they did not attend at least one CPT session after intake, and 14 were excluded because they attended 16 or more sessions. Seventy-five individuals presented to the clinic for at least two unique treatment periods (e.g., two outpatient treatment periods, two residential treatment periods, or one treatment period of each outpatient and residential). These cases were handled by including data from the first treatment period (whichever type of treatment was received first) and eliminating data from any subsequent treatment periods. This method was selected as a conservative approach to reduce the effects of previous treatment exposure. The mean age for the outpatient sample was 43.48 years (SD ⫽ 14.59), and the mean years of education was 13.21 (SD ⫽ 1.84). For the residential sample, the mean age was 47.87 years (SD ⫽ 10.96), and the mean years of education was 13.51 (SD ⫽ 2.43). Additional demographic information for the outpatient and residential treatment samples can be found in Table 1.

Measures The pre- and posttreatment assessment battery administered for both outpatient and residential programs included structured clin-

OUTPATIENT AND RESIDENTIAL PTSD TREATMENT

Table 1 Demographics Across Outpatient and Residential Groups Variable Sex Men Women Race/ethnicity White African American Latino Native American Multicultural Asian American Marital status Married Divorced Never married Separated Widowed Employment status Employed Unemployed Disabled Retired Student Service era OEF/OIF/OND Vietnam Persian Gulf Post-Vietnam Othera Index Traumab Combat Adult sexual assault Childhood sexual abuse Transportation accident Sudden unexpected death

Outpatient % (n ⫽ 514)

Residential % (n ⫽ 478)

88.5 11.5

63.4 36.6

81.8 15.2 1.8 0.6 0.4 0.2

61.9 34.3 1.9 1.0 0.7 0.2

53.1 23.3 17.9 4.3 1.4

28.1 46.0 18.4 5.2 2.3

43.0 25.0 16.0 9.0 7.0

12.6 37.6 39.3 9.2 1.3

43.4 32.9 12.3 9.7 1.7

17.8 32.2 15.7 32.4 1.9

71.9 6.9 3.3 3.3 2.8

38.2 32.5 8.8 2.5 2.9

Note. OEF/OIF/OND ⫽ Operation Enduring Freedom, Operation Iraqi Freedom/Operation New Dawn. a Other service eras include Korean War, between Korea and Vietnam, Somalia, Kosovo, World War II, Bosnia, and Lebanon. b The five most frequently reported types of index trauma.

ical interviews and self-report measures completed in approximately 2–3 hr. The measures used in the current study were derived from these larger pre- and posttreatment batteries. The summary scores used for the present analyses were obtained from chart review, and as a result, item-level data were unavailable. Clinician-Administered PTSD Scale (CAPS; Blake et al., 1995). The CAPS is a structured clinical interview for the assessment of PTSD based on the DSM–IV–TR. A PTSD symptom, as measured on the CAPS, counted toward meeting diagnostic criteria if the frequency (on a 0 – 4 scale) was rated as at least 1 (symptoms occur at least monthly) and intensity (on a 0 – 4 scale) was rated as at least 2 (moderate distress). This scoring procedure was used to determine PTSD diagnostic status based on response to CAPS items (Weathers, Ruscio, & Keane, 1999). A CAPS total severity score was also computed by summing ratings of the frequency and intensity of each PTSD symptom (higher scores indicate greater distress or impairment). Prior research with the CAPS has suggested that the interview is reliable and valid (Blake et al., 1995; Weathers et al., 1999), with excellent psychometric

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properties among veteran samples (Weathers, Keane, & Davidson, 2001). PTSD diagnostic status, as determined by the CAPS, was used for inclusion criteria, while the CAPS total severity scores at pre- and posttreatment were used for the current study analyses. At posttreatment, the period of assessment used for the CAPS was the previous week, which was intended for repeated assessment over a reasonably brief time interval (Weathers et al., 2001). The 1-week time frame at posttreatment was selected to ensure that the assessment period did not significantly overlap with the treatment period in either program. Structured Clinical Interview for DSM–IV Axis I Disorders (SCID–I; First, Spitzer, Gibbon, & Williams, 1996). The SCID–I is a semistructured interview designed to assess the presence of Axis I symptoms and disorders. The SCID–I was used in the present study to detect current and lifetime mood disorders, substance use disorders, and anxiety disorders other than PTSD, and to screen for psychotic symptoms. In the current study, pretreatment SCID–I diagnoses were used for descriptive purposes. Among veterans in the residential program, the most frequent current psychiatric conditions comorbid with PTSD, as diagnosed by the SCID–I, were major depressive disorder (66.7%), panic disorder (13.7%), bipolar I disorder (8.5%), social phobia (7.3%), and specific phobia (6.3%). Among veterans in the outpatient program, the most frequent current comorbid conditions were major depressive disorder (56.5%), panic disorder (8.2%), social phobia (4.5%), alcohol abuse (3.7%), and specific phobia (3.4%). PTSD Checklist–Stressor-Specific Version (PCL–S; Weathers, Huska, & Keane, 1991). The PCL–S is a widely used 17item self-report measure of PTSD symptomatology that corresponds with diagnostic criteria in the DSM–IV–TR. The PCL–S was used to assess PTSD symptom severity in relation to participants’ reported index trauma (i.e., worst identified trauma or the trauma that they reported as affecting them the most). PCL–S scale items are rated on a 5-point Likert-type scale ranging from 1 (not at all) to 5 (extremely), with total scores ranging from 17 to 85 (higher scores indicate greater distress). The PCL–S has demonstrated reliability and validity across various populations (Blanchard, Jones-Alexander, Buckley, & Forneris, 1996), as well as sensitivity to change over the course of psychological treatment (McDonald & Calhoun, 2010). PCL–S total scores from pre- and posttreatment were used for the current study analyses. Consistent with the CAPS assessment, the time period used for the PCL–S at posttreatment was the previous week. Beck Depression Inventory-II (BDI–II; Beck, Steer, & Brown, 1996). The BDI–II is a well-established 21-item selfreport measure used to assess the presence and severity of depressive symptoms. Items are rated on a 4-point Likert-type scale ranging from 0 to 3. Ratings are summed to yield a total severity index, with higher scores indicating more severe depressive symptoms. Research has demonstrated that the BDI–II has strong psychometric properties, including internal reliability, test–retest reliability, and convergent validity (Beck et al., 1996). For the current study, BDI–II total scores at pre- and posttreatment were used for the analyses and assessed symptoms over the past 2 weeks.

Procedure All data were collected as part of routine clinical care at a VA PTSD specialty clinic in the Midwest. A waiver of written consent based on archival data was obtained from a university institutional

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review board and the VA Research and Development Office. During admission into both outpatient and residential treatment programs, veterans were administered a series of assessment instruments to determine their pretreatment diagnostic status and functioning. All assessments were conducted by clinicians with extensive training and supervision in the provision of psychological tests. Diagnostic interviews and treatment sessions were not recorded in the clinic, precluding assessment of interrater reliability.

CPT Protocol Following the pretreatment assessment, veterans received either the 12-session individual standard CPT protocol (Resick et al., 2010) on an outpatient basis or the 12-session combined group and individual CPT protocol (Chard et al., 2009) within the residential PTSD treatment program. Prior work has demonstrated similar effect sizes for treatment outcome using various CPT protocols, including individual only and combined group and individual formats (see Chard, 2005; Resick, Nishith, Weaver, Astin, & Feuer, 2002). Veterans who received residential treatment were grouped in cohorts of approximately 10 people. Within both outpatient and residential programs, CPT treatment consisted of three stages: (a) an initial stage consisting of examination of the meaning of the trauma and the relationship between thoughts and emotions and identification of “stuck points” (i.e., disruptive cognitions about trauma that exacerbate PTSD symptoms); (b) a second stage that included the writing of a trauma account(s) to facilitate activation and normalizing natural emotions related to trauma, and further identification of stuck points; and (c) a final stage that focused on challenging stuck points and replacing them with more adaptive cognitions. Throughout treatment, cognitive techniques (including Socratic dialogue) were employed to facilitate further evaluation of potentially maladaptive beliefs. During the final CPT session, veterans were again asked to discuss the meaning of their trauma in order to highlight changes in their beliefs that may have emerged through the course of treatment. CPT was provided by licensed clinicians (i.e., nurse practitioners, social workers, psychiatrists, psychologists) or by trainees (i.e., psychiatry residents or psychology interns) supervised by a licensed clinician. Although providers varied in their levels of training, prior research (e.g., Foa et al., 2005; Okiishi et al., 2006) has suggested that therapist level of training does not significantly impact treatment outcome. All providers were trained by one of the developers of CPT and the co-author of this article, who provided weekly group supervision. Outpatient treatment. Veterans in the outpatient PTSD program received a CPT protocol designed for the military population (Resick et al., 2010). All therapy sessions were individual, inperson, and 60 min in duration. Veterans participating in outpatient CPT treatment attended an average of eight sessions (SD ⫽ 4.49). The course of treatment could either be shortened or lengthened (no outpatient in the sample had more than 15 sessions). Residential treatment. Veterans in the residential PTSD program received 7 weeks of CPT treatment designed for the military population (Chard et al., 2009), which was delivered in a combined group and individual format. As the protocol dictates, the group component of treatment provided veterans the opportunity to learn and practice skill development with other group members, while

individual sessions focused on processing trauma-related details and issues. The CPT group met twice per week for an average of 12 sessions (SD ⫽ 2.27), with each group session lasting 90 min. Participants also met with individual therapists for 60-min sessions twice per week, on average. Additional individual CPT sessions were offered to veterans as needed, with no veterans receiving more than 15 individual sessions. In addition to CPT, veterans in the residential PTSD treatment program attended various psychoeducational group sessions, lasting 60 –90 min each. These group sessions were held daily, with participants attending approximately 15 groups per week. Psychoeducation groups focused on cognitive behavioral principles and included topics such as anger management, PTSD education, communication skills, and relapse prevention. Additional groups, such as nutrition, recreational therapy, and spirituality, were also provided. Members within each cohort attended the same groups together, providing consistency in treatment received. Posttreatment. At posttreatment, patients in both outpatient and residential programs completed the same assessment battery they received at pretreatment in order to reassess psychological symptoms and diagnoses. In the outpatient program, posttreatment assessments were completed within 2 weeks of treatment completion. In the residential program, posttreatment assessments were completed during the final week of the treatment program (but after all treatment was completed). Posttreatment assessments were administered by a clinician other than the participant’s individual therapy clinician, who may have also differed from the clinician who administered the pretreatment assessment. No compensation was provided for completion of the assessments, as they were administered as part of routine clinical care and used to evaluate patient progress in the treatment program.

Data Analytic Plan Data comparing outpatient and residential groups at pretreatment were analyzed using t tests and Pearson chi-squares. Among covariates, age and years of education were examined as continuous variables. Sex (male and female), ethnicity (non-White and White), marital status (married and unmarried/divorced/widowed), and employment status (employed and unemployed/retired/disabled) were examined as dichotomous variables. Another covariate assessed at pretreatment was PTSD-related service connection. Within the VA Healthcare System, eligible veterans can apply for and receive service connection, which is a service-related financial disability compensation awarded based on severity of physical and psychological impairment. In the present study, service connection specifically linked to PTSD was examined categorically. Veterans were grouped into four categories based on their service-connection application status: (a) those who had never applied for service connection, (b) those in the process of applying for service connection who had not yet been approved, (c) those approved for service connection, and (d) those approved for service connection who were actively applying for an increase in their disability rating. Outcome variables included continuous scores on the CAPS, PCL–S, and BDI–II. Data comparing outpatient and residential trajectories across time were analyzed using multilevel (hierarchical) modeling (MLM) in Predictive Analytics software (PASW) Version 17 (SPSS). MLM was selected because it is designed for data con-

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(and centered) or dichotomous; outcomes (CAPS, PCL–S, and BDI–II) were not centered. See the Appendix for equations used at Levels 1 and 2 of each of the three MLM models.

taining dependent observations (e.g., repeated measures nested within veterans who are nested within a treatment program) and thus does not assume independence of errors. MLM also accommodates variations in temporal spacing of repeated measures (Feingold, 2009), which occurs in the current study, particularly within the outpatient sample. Further, MLM allows for examination of covariates and does not assume that the relationship between dependent variables and covariates is the same across groups (Quené & van den Bergh, 2004). Last, MLM accounts for missing data (typically present in treatment outcome research) without reducing power of the experimental design (Quené & van den Bergh, 2004). The present study used the restricted maximum likelihood (REML) approach to handle missing data and produce parameter estimates. REML was chosen because it is a preferred method for handling missing data within longitudinal models that yields unbiased variance and covariance parameter estimates (Graham, 2009). REML is well suited for handling large numbers of variables and accounting for data missing at random, completely at random, and not at random (Graham, 2009). In the current study, we conducted MLM analyses as two-level models (repeated measures within participants by program) using the SPSS mixed procedure. TIME was coded from 0 (pretreatment assessment) to 1 (posttreatment assessment), allowing the intercept to represent pretreatment. Age, years of education, service connection status (dummy coded), ethnicity, sex, marital status, and employment status were entered as fixed covariates. Continuous covariates (age and years of education) were grand mean centered. The intercept was specified as random, and the TIME variable was specified as repeated. For both levels of the models, the identity covariance structure was used. Predictors were either continuous

Results Cross-Sectional Analyses Across pretreatment variables, less than 5% of data were missing. Demographic information can be found in Table 1, with comparisons between the groups in Tables 2 and 3. Residential patients were older, had more years of education, and were more likely to be female, non-White, unemployed, unmarried, and from an earlier service era as well as to have completed more treatment sessions compared with outpatients. Chi-square analyses indicated that residential and outpatient groups differed significantly in their service connection status, ␹2 ⫽ 40.32, p ⬍ .001; ⌽ ⫽ .21. T tests conducted on pretreatment data indicated that residential patients reported significantly higher scores on the CAPS, t(989) ⫽ ⫺7.57, p ⬍ .001, d ⫽ 0.48; PCL–S, t(954) ⫽ ⫺7.06, p ⬍ .001, d ⫽ 0.45; and BDI–II, t(970) ⫽ ⫺5.09, p ⬍ .001, d ⫽ 0.33, when compared with outpatients.

Longitudinal Analyses Eighty-five percent of patients in the residential sample had complete data on all outcome measures while 36% of outpatients had complete data, yielding different rates of missing data between the two samples. The majority of missing data were due to veterans not completing treatment and, in turn, not participating in posttreatment assessments. Veterans in the residential program com-

Table 2 Cross-Sectional Demographic Comparisons Across Outpatient and Residential Groups Program Variable Sex Male Female Race/Ethnicity White Non-Whitea Service era World War II–Post-Vietnam Persian Gulf War–present Marital Status Married Unmarriedb Employment status Employed Not employedc Service connection status Not connected or seeking Seeking but not connected Connected not seeking increase Connected and seeking increase

Outpatient

Residential

␹2

⌽

455 (88.5%) 59 (11.5%)

303 (63.4%) 175 (36.6%)

86.79ⴱⴱⴱ

.30ⴱⴱⴱ

419 (81.5%) 95 (18.5%)

296 (61.9%) 182 (38.1%)

47.24ⴱⴱⴱ

⫺.22ⴱⴱⴱ

225 (43.8%) 289 (56.2%)

309 (64.6%) 169 (35.4%)

43.41ⴱⴱⴱ

.21ⴱⴱⴱ

273 (53.1%) 241 (46.9%)

134 (28.0%) 344 (72.0%)

64.39ⴱⴱⴱ

⫺.26ⴱⴱⴱ

210 (40.9%) 304 (59.1%)

59 (12.3%) 419 (87.7%)

110.88ⴱⴱⴱ

⫺.32ⴱⴱⴱ

259 (54.1%) 148 (29.4%) 50 (9.9%) 47 (9.3%)

161 (35.9%) 126 (28.1%) 100 (22.3%) 62 (13.8%)

40.32ⴱⴱⴱ

.21ⴱⴱⴱ

Note. Percentages within program appear in parentheses next to group sizes. a Non-White includes African Americans, Latinos, Native Americans, Asian Americans, and those identifying as multicultural. b Unmarried includes those who are divorced, separated, widowed, and never married. c Not employed includes those who are unemployed, retired, disabled, and students. ⴱⴱⴱ p ⬍ .001.

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Table 3 Means and Standard Deviation of the CAPS, PCL–S, and BDI–II at Pretreatment Program Variable Demographics Age Years of education Total no. of sessions Pretreatment assessment Clinician-Administered PTSD Scale PTSD Checklist–S Beck Depression Inventory–II

Outpatient M (SD)

Residential M (SD)

t

df

n

d

43.48 (14.59) 13.21 (1.84) 8.29 (4.49)

47.87 (10.96) 13.51 (2.43) 11.77 (2.27)

⫺5.39ⴱⴱⴱ ⫺2.20ⴱ ⫺15.56ⴱⴱⴱ

948.98a 978 770.18a

992 980 992

⫺0.35 ⫺0.14 ⫺1.21

67.12 (15.40) 59.84 (10.67) 31.62 (10.98)

74.76 (16.36) 64.68 (10.55) 35.20 (10.97)

⫺7.57ⴱⴱⴱ ⫺7.06ⴱⴱⴱ ⫺5.09ⴱⴱⴱ

989 954 970

991 956 972

⫺0.48 ⫺0.46 ⫺0.33

Note. PTSD ⫽ posttraumatic stress disorder; CAPS ⫽ Clinician-Administered PTSD Scale; PCL–S ⫽ PTSD Checklist–Stressor Specific Version; BDI–II ⫽ Beck Depression Inventory (2nd ed.); df ⫽ degrees of freedom. a Levene’s test for equality of variances was significant on these tests and therefore equal variances were not assumed. ⴱ p ⬍ .05. ⴱⴱⴱ p ⬍ .001.

pleted at a rate of 91.4% and those in the outpatient program completed treatment at a rate of 50.2%. Although the outpatient sample had a greater rate of missing data (i.e., posttreatment CAPS, PCL–S, and BDI–II scores), veterans in the outpatient program with missing data compared to those with complete data did not significantly differ on pretreatment CAPS, t(511) ⫽ 1.31, p ⫽ .19; PCL–S, t(492) ⫽ ⫺0.42, p ⫽ .68; or BDI–II scores, t(495) ⫽ 0.87, p ⫽ .39. Missing data were addressed using the restricted maximum likelihood (REML) approach. The estimated marginal means and standard errors for the CAPS, PCL–S, and BDI–II at pre- and posttreatment across groups are available in Table 4. Throughout the MLM analyses, unstandardized coefficients were used as they are considered ideal for comparing estimates across samples (Hox, 2002). Baseline models. Analyses were conducted to confirm that each of the dependent variables (CAPS, PCL–S, and BDI–II scores) significantly changed over time. In MLM, these baseline models must be significant in order to justify expanding the models with additional levels. The outcome measures evidenced significant decreases over

Table 4 Estimated Marginal Means and Standard Errors for CAPS, PCL-S, and BDI–II, at Pretreatment and Posttreatment Model CAPSa Outpatient Residential PCL–Sb Outpatient Residential BDI–II Outpatient Residential

Pretreatment M (SE)

Posttreatment M (SE)

69.11 (1.55) 78.88 (1.41)

34.52 (1.75) 47.41 (1.43)

62.78 (1.11) 66.52 (1.02)

40.52 (1.27) 52.23 (1.03)

31.60 (1.05) 35.05 (0.96)

19.14 (1.18) 24.04 (0.97)

Note. PTSD ⫽ posttraumatic stress disorder; CAPS ⫽ ClinicianAdministered PTSD Scale; PCL–S ⫽ PTSD Checklist–Stressor Specific Version; BDI–II ⫽ Beck Depression Inventory (2nd ed.). a The CAPS estimated marginal means controlled for the effects of age. b The PCL–S estimated marginal means controlled for the effects of age and education level.

time in scores on the CAPS (␤ ⫽ ⫺30.65, p ⬍ .001), PCL–S (␤ ⫽ ⫺16.68, p ⬍ .001), and BDI–II (␤ ⫽ ⫺11.32, p ⬍ .001). Control variables. We conducted analyses to determine if any of the following variables were associated with the trajectory of change on the CAPS, PCL–S, or BDI–II: age, sex, years of education, ethnicity, service connection status, marital status, and employment status. Although these variables were of central interest in the pretreatment cross-sectional analyses, within the longitudinal trajectory of change analyses, they were examined purely as control variables. The CAPS trajectory was significantly predicted by age (␤ ⫽ ⫺.10, p ⬍ .05), sex (␤ ⫽ 3.34, p ⬍ .05), and application for an increased service connection rating (␤ ⫽ ⫺7.15, p ⬍ .001). The PCL–S was significantly predicted by ethnicity (␤ ⫽ 2.06, p ⬍ .05), age (␤ ⫽ .08, p ⬍ .05), education (␤ ⫽ ⫺.34, p ⬍ .05), having service connection (␤ ⫽ ⫺2.33, p ⬍ .05), and application for an increased service connection rating (␤ ⫽ ⫺5.30, p ⬍ .001). The BDI–II was significantly predicted by application for an increased service connection rating (␤ ⫽ ⫺2.98, p ⬍ .05), and a trend emerged for employment status (␤ ⫽ 1.54, p ⬍ .08). Significant relationships between control variables and outcome variables were controlled for in all subsequent analyses. Multilevel models. All three models, for CAPS, PCL–S, and BDI–II, converged successfully (see Table 5 for results and, as mentioned earlier, Table 4 for the estimated marginal means and standard errors of the final models). Level-1 variables in all three models included control variables, as well as time. The Level-2 variable for all three models was program membership (outpatient or residential). An interaction between time and program was also included in all three models. Once all predictors were added into each model, the significant Wald Z for the CAPS (19.03, p ⬍ .001), PCL–S (18.70, p ⬍ .001), and BDI–II (18.34, p ⬍ .001) suggested there was still significant residual variance to be explained in initial intercepts. Clinician-assessed PTSD symptoms. When modeling CAPS scores, the covariates of age, sex, and application for increased service connection rating were significant. Younger patients and female patients demonstrated more improvement in their CAPS scores over time. Veterans who received service-connected disability and were in the process of applying for an increased

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Table 5 Unstandardized Coefficients Within CAPS, PCL–S, and BDI–II Multilevel Model Analyses 95% CI Outcome measure Clinician-Administered PTSD Scale Age Sex Ethnicity Education Employment status Marital status Applying for service connection Having service connection Increasing service connection Time Program Time ⫻ Program PCL–S Age Sex Ethnicity Education Employment status Marital status Applying for service connection Having service connection Increasing service connection Time Program Time ⫻ Program Beck Depression Inventory–II Age Sex Ethnicity Education Employment status Marital status Applying for service connection Having service connection Increasing service connection Time Program Time ⫻ Program

␤

SE

Lower

Upper

⫺0.10ⴱ 3.34ⴱ ⫺0.09 0.03 1.89 0.92 ⫺1.68 ⫺1.21 ⫺7.15ⴱⴱⴱ 29.47ⴱⴱⴱ ⫺12.89ⴱⴱⴱ 5.12ⴱⴱ

0.04 1.28 1.17 0.23 1.25 1.11 1.22 1.50 1.67 1.01 1.60 1.64

⫺0.18 0.82 ⫺2.38 ⫺0.43 ⫺0.56 ⫺1.26 ⫺4.07 ⫺4.16 ⫺10.43 27.49 ⫺16.03 1.90

⫺0.02 5.86 2.19 0.48 4.34 3.10 0.70 1.74 ⫺3.86 31.45 ⫺9.75 8.34

0.08ⴱ 1.75 2.06ⴱ ⫺0.34ⴱ 1.10 0.95 ⫺0.87 ⫺1.25 ⫺5.30ⴱⴱⴱ 14.29ⴱⴱⴱ ⫺11.71ⴱⴱⴱ 7.97ⴱⴱⴱ

0.03 0.92 0.84 0.17 0.90 0.80 0.88 1.08 1.20 0.74 1.16 1.20

0.02 ⫺0.07 0.41 ⫺0.67 ⫺0.67 ⫺0.62 ⫺2.59 ⫺3.38 ⫺7.66 12.84 ⫺13.98 5.62

0.14 3.56 3.71 ⫺0.01 2.86 2.51 0.85 0.87 ⫺2.94 15.74 ⫺9.44 10.32

0.01 1.16 ⫺0.82 ⫺0.09 1.54† 0.70 0.04 0.91 ⫺2.98ⴱ 11.01ⴱⴱⴱ ⫺4.90ⴱⴱⴱ 1.45

0.03 0.88 0.80 0.16 0.86 0.76 0.83 1.04 1.15 0.61 1.05 1.00

⫺0.05 ⫺0.56 ⫺2.39 ⫺0.41 ⫺0.14 ⫺0.79 ⫺1.59 ⫺1.12 ⫺5.24 9.81 ⫺6.95 ⫺0.52

0.06 2.89 0.75 0.22 3.22 2.19 1.67 2.94 ⫺0.73 12.21 ⫺2.84 3.41

Note. PTSD ⫽ posttraumatic stress disorder; CAPS ⫽ Clinician-Administered PTSD Scale; PCL–S ⫽ PTSD Checklist–Stressor Specific Version; BDI–II ⫽ Beck Depression Inventory (2nd ed.). p ⬍ .08. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.

†

disability rating reported less improvement in CAPS scores across time compared with all other veterans. Regarding variables of interest, time was a significant predictor of change in CAPS scores, with scores decreasing significantly from pre- to posttreatment. Program was a significant predictor of change, with residential patients reporting higher CAPS scores at both pre- and posttreatment. The time by program interaction was significant, indicating that outpatients had greater decreases in their CAPS scores compared with residential patients. Self-reported PTSD symptoms. When modeling PCL–S scores, age, years of education, ethnicity, and application for increased service connection rating were significant covariates. Older, less educated, and White patients reported greater improvement in PCL–S scores across time. Veterans who received serviceconnected disability and were in the process of applying for an increased disability rating reported less improvement in PCL–S scores over time compared with all other veterans.

Similar to the CAPS model, time was a significant predictor of change in PCL–S scores, with scores decreasing significantly from pre- to posttreatment. Program was a significant predictor of change, with residential patients reporting higher PCL–S scores at both pre- and posttreatment. The time by program interaction was significant, indicating that outpatients tended to report larger PCL–S score decreases when compared to residential patients. Self-reported depression symptoms. When modeling BDI–II scores, only application for increased service connection status was a significant covariate. Veterans who received service-connected disability and were in the process of applying for an increased disability rating reported less improvement in their BDI–II scores compared with all other veterans. Time was a significant predictor of change in BDI–II scores, with scores decreasing significantly from pre- to posttreatment. Program was a significant predictor of change, with residential patients reporting higher BDI–II scores at both pre- and posttreat-

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ment. The time by program interaction was not significant, indicating that outpatients and residential patients did not differ in the rate of their BDI–II score change across time. Intraclass correlation (ICC). The ICC was calculated to determine the variance accounted for by each level within each model. ICC refers to the degree of dependence of individuals on the program to which they belong or the proportion of total variance between groups (Roberts & Monaco, 2006). The following equation was used to calculate the ICC, ␳ ⫽ ␶00 ⁄ (␶00 ⫹ ␴2) where ␶00 represents the total explainable variance for program while ␴2 represents the total variance in outcomes. For the CAPS, ␳ ⫽ .31, which indicates that 31% of the variance is accounted for by program and 69% is accounted for by individual factors and time. For the PCL–S and BDI–II, ␳ ⫽ .30 and ␳ ⫽ .43, respectively.

Discussion There were two primary goals of the present study: (a) to examine whether veterans receiving CPT in either residential or outpatient programs differed with regard to demographic variables and pretreatment symptom severity, and (b) to examine whether there were differences in symptom change across time between veterans participating in these two programs. In terms of the first goal, study results demonstrated that the outpatient and residential treatment samples differed on all demographic variables and symptom severity measures. Specifically, veterans in outpatient treatment were significantly younger; had fewer years of education; and were more likely to be male, White, employed, married, and from a more recent service era than veterans in residential treatment. Analyses also revealed that outpatient and residential groups significantly differed with regard to their service connection status. Specifically, veterans in the residential program were more likely to be service connected than those in the outpatient program. The outpatient and residential treatment groups also significantly differed on pretreatment symptom severity and other treatment variables. In particular, patients in the residential treatment program reported significantly higher scores than outpatients on all symptom measures. As such, findings highlighting demographic and pretreatment symptom severity differences between the outpatient and residential treatment samples suggest that there are at least two subgroups of veterans who receive PTSD treatment at a VA healthcare facility. The second goal of the article was to examine differences between veterans in the residential and outpatient programs in terms of symptom change over time. Although demographic covariates were not of central interest to the longitudinal component of the study, they may provide important information for future research efforts. For example, on the CAPS, women reported more improvement across time compared with men. In terms of the PCL–S, less educated and White patients reported greater improvement in scores over time. Study analyses also showed that age was significantly related to CAPS and PCL–S scores, with older veterans reporting less improvement in CAPS scores over time and greater improvement in PCL–S scores over time. In further exploring these findings, we found that in the outpatient sample, older individuals had significantly lower scores on the CAPS but not the PCL–S at pretreatment. Among the residential

sample at pretreatment, older individuals had significantly lower scores on the PCL–S but not the CAPS. The age-related pretreatment differences may account for the divergent symptom trajectories. Across all three symptom measures, veterans applying for an increase in their service connection disability rating reported less improvement in their PTSD and depressive symptoms across time. Thus, it was not simply receiving financial service connection compensation that related to less symptom improvement but rather actively applying for an increase in service connection disability rating for PTSD (and in turn, increased financial compensation). Given that veterans may have access to information about the diagnosis and treatment of PTSD, as well as the process of applying for and receiving service connection disability compensation, it is possible that these veterans’ treatment choices (i.e., outpatient vs. residential; evidence-based; trauma-focused), as well as their clinical presentation in assessment and treatment sessions, could be influenced by information received regarding the service connection process. It is similarly plausible that veterans seeking an increase in service connection have greater symptom severity, which could account for the decreased symptom improvement. Longitudinal results involving the type of treatment program and the interaction between time and program were of particular interest in the present study. As expected, time was a significant predictor of all three outcome measures. In other words, all symptom severity scores improved from pre- to posttreatment. This finding suggests that cognitive processing therapy (CPT)—whether delivered in an individual format or group and individual combined format—whether in an outpatient or residential setting— effectively reduces PTSD and depression symptoms for veterans receiving care in VA specialty clinics. Effective intervention for reducing PTSD and depression symptoms is critical given the increasing numbers of veterans presenting to VA clinics with these diagnoses (Dohrenwend et al., 2006; Hoge et al., 2004; Seal et al., 2009). Program type was also a significant predictor of all three outcome measures, with outpatients reporting lower symptoms at both pretreatment and posttreatment compared with residential patients. This finding provides support for the continuum of PTSD treatment options available for veterans within the VA Healthcare System (Hoge et al., 2010). Although we could not determine whether veterans in the two programs had differing levels of prior unsuccessful treatment (e.g., residential patients more often having experienced unsuccessful outpatient treatment and thus seeking residential treatment), in our sample, residential patients tended to have greater symptom severity overall. When examining the interaction between time and program type, PTSD-related score trajectories (i.e., CAPS and PCL–S) significantly differed between residential and outpatient groups. These findings indicate that whether clinician-assessed or selfreported, greater PTSD symptom improvement occurred in outpatients compared with residential patients. Thus, veterans in residential treatment endorsed an overall higher PTSD symptom severity and did not experience the same proportion of symptom relief compared with veterans in outpatient treatment. Prior research suggests that pretreatment PTSD severity affects treatment outcome (e.g., Blanchard et al., 2003). Thus, it is possible that veterans in residential programs experience less symptom relief than outpatients because they initiate treatment with more severe PTSD symptoms.

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Previous research has demonstrated that individuals with PTSD are more likely than not to report comorbid psychiatric conditions (Kessler, Sonnega, Bromet, Hughes, & Nelson, 1995). In our study, veterans in residential treatment reported an increased frequency of psychiatric comorbidities compared with outpatients. These differences in both PTSD symptom severity and frequency of comorbid psychological disorders may also partially account for veterans in residential programs experiencing less PTSD symptom relief after treatment. Further understanding of the complex relationships between PTSD and other psychiatric comorbidities will be critical to examine in future outcome research. In terms of depressive symptoms (i.e., BDI–II), while both residential patients and outpatients improved across time, their rate of improvement did not differ. Although veterans in the residential program began treatment with greater depression symptom severity, they experienced a similar proportion of decline in the trajectory of their symptoms compared with veterans in the outpatient program. This decrease in depression symptoms could be accounted for by the fact that CPT shares many of the foundational principles of cognitive therapy for depression, as outlined by Beck and his colleagues Rush, Shaw, and Emery (1987). The parallel pattern of decline in depressive symptoms across treatment groups contrasts the PTSD symptom trajectories, in which, for both clinician-assessed and self-reported symptoms, residential patients reported less improvement than outpatients. These differences suggest that severe PTSD may be more difficult to treat than severe depression. In addition to more severe PTSD symptoms and increased psychiatric comorbidities, as suggested earlier, service connection may influence treatment outcomes, especially when considering the lower proportion of symptom improvement among veterans in the residential program. Veterans applying for a PTSD-related service connection increase may perceive that a more intensive level of treatment (i.e., residential) would improve the likelihood that their request for an increased disability rating will be approved. Additionally, veterans may need to maintain a certain level of symptomatology or diagnostic status in order to continue to receive benefits, which may in turn affect treatment outcomes. Future research would benefit from examining these potential factors (e.g., symptom severity, disability, compensation) to more precisely determine the role of service connection status in PTSD treatment response. The present study has a number of strengths, which contribute significantly to the existing literature. To begin, to our knowledge, this research is the first to compare pretreatment characteristics and treatment outcome between veterans receiving outpatient and residential PTSD treatment. Veterans in both programs received PTSD treatment within the same facility utilizing two similar empirically supported approaches to delivering CPT. While natural differences may exist within the facility, the relative constants of CPT and treatment providers likely served as controls, allowing for differences between treatment groups to be detected. The current study utilized a large and diverse clinical sample of treatment-seeking male and female veterans. This sample is likely to be representative of other treatment-seeking veteran populations and enhances the generalizability of study findings. Additionally, veterans with comorbid Axis I or Axis II conditions were not excluded, and treatment was conducted within a naturalistic setting, further contributing to the ecological validity of the study. The use of multilevel models to analyze the data also bolsters

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study findings, as MLM can effectively evaluate change between and within groups over time in the context of nested data. MLM specifically addressed the dependency of observations within the nested models, differing temporal spacing of assessments between programs, and missing follow-up data within our study. Well-validated, gold-standard psychological measures were utilized at pre- and posttreatment assessments. These assessment tools have strong psychometric properties and have been previously used to demonstrate change over the course of psychotherapy in veteran populations (e.g., Monson et al., 2006; Schnurr et al., 2007). Furthermore, assessments were intentionally administered by clinician raters who were not the veterans’ primary clinician, in an effort to reduce clinician bias in assessment. As with any research, limitations exist in the current study. First, veterans in the residential program received additional programming compared with outpatients, which may have influenced treatment outcome and differences between symptom trajectories across treatment groups. Furthermore, veterans in residential PTSD treatment received CPT in the combined group and individual format, while veterans in outpatient PTSD treatment only received CPT in an individual format. As it was not possible to examine the particular influence of the group CPT sessions in this study, an interesting area for future research would be to compare treatment outcome between individuals receiving individual CPT and those receiving the combined group and individual format. In addition to treatment factors, the greater frequency of missing posttreatment data for the outpatient sample (compared with the residential sample) may have influenced study findings. Outcome data may be skewed as residential patients may be less likely to drop out of treatment than outpatients, regardless of their level of treatment benefit. Residential patients may be more likely to complete treatment due to multiple reasons, including travel (e.g., veterans in the residential program may not be local and have traveled a significant distance to attend). In addition, reasons related to disability (e.g., veterans in the residential program are more likely to be disabled or unemployed and may be less likely to drop out of treatment due to employment demands; navigating the service connection process) may also account for greater retention in the residential treatment program. Because of these considerations, missing data techniques were utilized to provide best estimates of posttreatment data. Although the percentage of missing data varied between the treatment programs, it is not possible to determine the influence of differential rates of missing data on treatment outcome due to confounds created by betweengroup differences (e.g., veterans in outpatient and residential treatment programs significantly differed on all examined variables). The treatment completion rate for the outpatient sample found in the current study, which was the primary reason for missing data, was comparable to rates found among other outpatient treatmentseeking veteran populations (Garcia, Kelley, Rentz, & Lee, 2011; Harpaz-Rotem & Rosenheck, 2011) and suggests that findings may be generalizable to other outpatient VA clinics. An additional limitation of the study was that the timing of the posttreatment assessments varied by up to 2 weeks between the outpatient and residential treatment programs. Considering that certain assessment instruments (i.e., BDI–II) assess symptoms over a 2-week time period, the period of assessment may overlap to some degree with the treatment period in the outpatient or residential setting This is especially true within the residential

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program, as postassessments are conducted at the end of the last week of treatment, after the completion of all therapy sessions but prior to the veterans’ departure and return home. Thus, the slight difference in posttreatment assessment timing may have affected results and actual assessment of posttreatment symptoms. Related, posttreatment follow-up data were not available to determine the course of change after veterans disengaged from active treatment. Including follow-up data in future research is particularly important, as veterans who receive residential treatment may return home to an environment vastly different than that they experienced in treatment, which may in turn influence psychological symptoms. It would be informative if future researchers collected and analyzed follow-up data to better evaluate long-term outcomes of evidenced-based treatment for veterans with PTSD in both residential and outpatient settings. The current study contributes to the literature by identifying differences in demographic and symptom severity variables among veterans seeking outpatient or residential treatment for PTSD. Our findings suggest that there are at least two subgroups of veterans seeking treatment for PTSD, providing support for the differing levels of care set forth by VA policies (U.S. Department of Veterans Affairs, 2010) and offered within the VA Healthcare System. Examination of demographic and symptom variables may assist clinicians in providing or referring veterans to the most appropriate level of care. This study also demonstrated the divergence in PTSD treatment outcome between the two treatment programs. Specifically, outpatients experienced greater PTSD symptom relief than veterans in residential treatment, although outpatients initiated treatment with an overall lower level of symptom severity. Interestingly, veterans in outpatient and residential treatment experienced similar reductions in their depression symptoms. It is difficult to ascertain whether these findings may be accounted for by differences in symptom severity, psychiatric comorbidity, or service connection status. Further research is needed to examine the extent to which these factors influence treatment choice and outcome, particularly given potentially significant clinical and policy implications. It is our hope that this study and its findings increase knowledge about the PTSD treatment process for veterans, as well as highlight the need for continued examination of these critical issues.

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Appendix Equation for MLM Models The Level 1 equation can be written as follows: Y ij ⫽ ZB j ⫹ eij where Yij represents symptom levels (on either CAPS, BDI–II, or PCL–S) for time point i (either pretreatment or posttreatment) within individual j. Z is a matrix of known, constant variables (e.g., age, education, service connection status, sex, ethnicity, marital status, and employment status). Bj represents the mean response for subject j, and eij represents the residuals across trials. Bj can also be considered the mean response for subject j as a deviation from the grand mean ␥00, as follows: B j ⫽ y00 ⫹ u0j Where u0j represents residuals across individuals. Substituting the Level-1 submodel into the Level-2 submodel yields the following: Y ij ⫽ Zy00 ⫹ (Zu0j ⫹ eij) The model is then extended by the addition of treatment type (residential vs. outpatient) as an explanatory variable in outcome.

The pooled mean ␥00 is replaced by two coefficients ␥res00 and ␥out00 for each treatment condition. Selection of these conditions is done using dummy variables, here named TxRES and TxOUT. To allow for nonconstant variances among the treatment conditions, both between subjects and within subjects across pretreatment and posttreatment, the following final equation is used: Y ij ⫽ Zyres00TxRES ⫹ Zyout00TxOUT ⫹ (Zures0jTxRES ⫹ Zuout0jTxOUT ⫹ eresijTxRES ⫹ eoutijTxOUT) which can be simplified to the following equation: Y ij ⫽ TxRES [Zyres00 ⫹ (Zures0jTxRES ⫹ eresij)]⫹ TxOUT ⫹ [Zyout00 ⫹ (Zuout0jTxOUT ⫹ eoutij)] Received September 10, 2012 Revision received November 4, 2013 Accepted December 5, 2013 䡲