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. Author manuscript; available in PMC: 2026 Jul 1.
Published in final edited form as: J Anxiety Disord. 2025 May 14;113:103027. doi: 10.1016/j.janxdis.2025.103027

Who defines improvement? Patients’ global reports of improvement compared to standardized measures of improvement in cognitive processing therapy for posttraumatic stress disorder

Elizabeth Alpert a,b, Annie B Fox a,c, Tara E Galovski a,b
PMCID: PMC12147656  NIHMSID: NIHMS2083321  PMID: 40381493

Abstract

Standardized measures have typically been used to assess symptom change during treatment in psychological research and practice. However, standardized measures may not fully capture patients’ experiences of therapeutic change. Patients’ global reports of their improvement during treatment across domains of symptoms and functioning are also important and may provide distinct information from standardized measures. The current study compared both types of patient reports of improvement during cognitive processing therapy (CPT) for posttraumatic stress disorder (PTSD). We also examined process-level predictors of improvement assessed using both methods. Participants were 254 adult survivors of interpersonal violence receiving CPT. Patients’ global reports of improvement in each domain (PTSD symptoms, relationships, health concerns, sexual functioning, school/work performance, and life satisfaction), each rated on a Likert scale via the Treatment Outcome Questionnaire, were significantly correlated with the corresponding standardized measure of improvement in the same domain, with most effect sizes in the small-to-medium range. Patients’ perceptions of the therapy (helpfulness, likability) significantly predicted both global ratings and standardized measures of improvement, while patients’ perceptions of the therapeutic relationship, patients’ perceptions of barriers to therapy attendance, and objective indices of attendance did not predict improvement. Results highlight the importance of patients’ experiences with treatment and suggest that assessing patients’ global ratings of their improvement during treatment provides distinct information from standardized measures of improvement, and both are important to include when measuring therapeutic change.

Keywords: posttraumatic stress disorder, trauma-focused treatment, nonspecific factors, measurement, treatment process

1. Introduction

Posttraumatic stress disorder (PTSD) has wide-ranging consequences for people suffering from this mental health condition and for society more broadly (Watson, 2019). Fortunately, empirically-supported treatments (ESTs) for PTSD are available, with hundreds of randomized controlled trials supporting their efficacy (Norman, 2022). Clinical practice guidelines (American Psychological Association, 2017; Department of Veterans Affairs & Department of Defense, 2023; Forbes et al., 2020) consistently recommend trauma-focused treatments for PTSD, including top-tier therapies such as cognitive processing therapy (CPT; Resick et al., 2017) and prolonged exposure (PE; Foa et al., 2019). These treatments have demonstrated large effect sizes for PTSD symptom reduction, as well as high rates of loss of diagnosis by the end of treatment (Norman, 2022). The current study examines treatment outcomes in CPT.

1.1. Standardized Measures of Improvement

When assessing treatment effectiveness in research and clinical practice, standardized measures are typically used to assess specific constructs in precise ways and to measure symptom change over time. Such measures include clinician-administered interviews and self-report measures. Standardized measures are invaluable given their sound psychometric properties and applicability across patients. Indeed, estimates of treatment efficacy within and across research trials, and the clinical practice guidelines compiled using those estimates, are based on standardized measures of symptom reduction. Further, in clinical practice, routine outcome monitoring using standardized measures has been found to enhance care and is recommended in clinical care settings (Boswell et al., 2015; Lambert et al., 2018).

At the same time, standardized measures have limitations. They can be used in different ways that can result in differential and at times conflicting interpretations. For example, across a sample, researchers might observe a statistically significant average decrease in symptom scores while also observing that the majority of participants’ scores remain above a diagnostic threshold after treatment. Standardized measures also do not capture patients’ global perceptions of how therapy went for them (Sales & Alves, 2016). Patients often seek therapy not only to address DSM-defined symptoms, but also to address impairments in their functioning and quality of life (Galovski, Nixon, et al., 2024). Standardized assessments do not always fully capture these constructs or others patients may consider important when gauging their improvement.

1.2. Global Reports of Improvement

In addition to using standardized measures of symptom levels over time, it is also important to assess patients’ global perceptions of their improvement during treatment across broad domains (e.g., symptoms, functioning). Such measurement can capture the meaningfulness to patients of the change they have experienced and the translation of that change to their quality of life. Indeed, patients’ unstandardized, global reports of change in therapy sometimes diverge from their scores on standardized measures of change. Patients may report little perceived global improvement while standardized assessments suggest otherwise, and contrarily, patients may also report experiencing more change than that reflected by their standardized measure scores (Vincent et al., 2006). For example, in a sample of adults receiving trauma-focused treatment for PTSD, participants’ global reports of their improvement in PTSD symptoms were positively but only moderately correlated (r = .31) with improvement assessed using a standardized measure (Matthews et al., 2022).

Instead of solely relying on standardized measures, complementing the use of standardized measures with assessment of patients’ unstandardized global reports of their progress may better capture the complex nuances of change occurring during therapy. Such assessment would provide a more complete and holistic picture of change by including and moving beyond measures of the core symptoms of the presenting disorder to assess domains of functioning such as health and relationship functioning and general quality of life. As such, global reports of improvement can highlight the impact of therapy on the domains of functioning that are most important to the patient. Further, identifying predictors of improvement assessed via these varying methods can also elucidate treatment processes that are likely relevant not only to objective symptom alleviation, but also to patients’ subjective experiences of their progress in therapy.

1.3. Process-Level Predictors of Improvement

Both standardized measures and global reports of therapy outcomes can contribute to our understanding of interventions’ impacts on recovery, and examining predictors of these outcomes can further elucidate which patients are most likely to report improvement. The current study focuses on nonspecific treatment factors, which are processes that apply across psychotherapy protocols. Nonspecific factors are important predictors of reductions in symptoms and increases in functioning during treatment. Nonspecific process-level factors include the therapeutic alliance, patients’ views of the therapy, and patients’ engagement in treatment via session attendance and treatment completion, among others. A stronger therapeutic alliance has been shown to predict better symptom outcome in CPT and other PTSD treatments (Keefe et al., 2022; Sijercic et al., 2021; Sripada & Walters, 2022), as well as completion of PTSD treatment (Holdsworth et al., 2014; Hundt et al., 2017, 2020; Wells et al., 2022). Indeed, many completers of CPT and PE reported that a positive relationship with their therapist helped them continue engaging in treatment (Hundt et al., 2017), whereas some non-completers cited difficulty in their relationship with their therapist as contributing to their early discontinuation (Hundt et al., 2020; Wells et al., 2022).

Patients’ perceptions of the therapy (e.g., treatment helpfulness, treatment likability) are also relevant to treatment outcomes. Buy-in to the treatment rationale has been associated with better PTSD treatment outcomes (Litz et al., 2019; Price et al., 2015) and treatment completion (Hundt et al., 2020; Taylor, 2003; Wells et al., 2022). Some qualitative studies (Hundt et al., 2020; Wells et al., 2022) have specifically found that patients who discontinued CPT or PE early reported low buy-in to the rationale of treatment or its tasks as a contributing factor. Additionally, in PE, non-completers specifically reported disliking aspects of the treatment and that this contributed to their decision to discontinue treatment early (Wells et al., 2022).

Engagement in treatment (e.g., attending sessions and completing treatment) has also been found to predict patient outcomes. While premature discontinuation from treatment may, in some cases, be due to clinical improvement that patients view as sufficient (Szafranski et al., 2017), it has been found that on the whole, time in treatment tends to correspond to better clinical outcomes, and patients who discontinue PTSD treatment early do not improve to the same degree as patients who complete the full treatment protocol (Berke et al., 2019; Holmes et al., 2019; Taylor, 2003; Thompson-Hollands et al., 2023).

It may be the case that process-level factors, such as the therapeutic alliance, patients’ perceptions of the therapy, and patients’ therapy engagement (e.g., attendance, completion) also predict patients’ global reports of their improvement during treatment. There is some evidence to support such associations among patients receiving psychotherapies other than PTSD treatments. In a sample of outpatients seeking psychotherapy in community clinics, patient-rated therapeutic alliance was correlated with patients’ global reports of improvement in therapy (Clemence et al., 2005). Additionally, in a primary care sample of veterans receiving brief cognitive behavioral therapy for chronic pain, perceived usefulness of treatment content and treatment satisfaction were associated with global reports of improvement (Beehler et al., 2021). However, patients’ global reports of improvement, as well as relations among these reports and process-level predictors, have not been well-studied in PTSD treatments.

1.4. Current Study

The current study used data from two CPT efficacy trials to examine whether patients’ global reports of improvement across multiple domains correlated with standardized measures of improvement in the same domains, as well as to examine whether process-level treatment factors differentially predicted patient outcomes assessed via the two methods. We included not only measures of change in PTSD symptoms, but an array of measures capturing change across domains of symptomatology, functioning, and quality of life. We hypothesized that we would observe significant associations between patients’ global ratings of improvement in each domain with the corresponding standardized measure of improvement in the same domain. Because there have been no examinations of predictors of global reports of change vs. standardized measures of change, the predictor analysis did not have directional hypotheses.

2. Method

2.1. Data Sources

The present study is a secondary analysis of data from two randomized clinical trials funded by the National Institutes of Health. Both examined the efficacy of CPT among survivors of interpersonal violence (ClinicalTrials.gov Identifiers: NCT00630578 and NCT00725192). Please see Galovski et al. (2012) and Galovski et al. (2016) for details of study procedures and outcomes. These studies received Institutional Review Board (IRB) approval at the University of Missouri, St. Louis, and the present analysis received IRB approval at VA Boston Healthcare System.

2.2. Participants

Participants were 254 adults with PTSD who received CPT. To be included in the parent trials, participants had to be 18 years of age or older, meet DSM-IV criteria for PTSD due to interpersonal violence, and their index trauma must have occurred three months or more prior to enrolling. Participants were excluded if they met DSM-IV criteria for current substance dependence, reported current suicidal intent or behavior, reported currently experiencing intimate partner violence or stalking, had previously received CPT, or were currently engaged in another trauma-focused therapy. Participants were asked to maintain a stable dose of any psychotropic medication. One of the studies specifically included women who endorsed high levels of trauma-related sleep difficulty; the other study included both men and women, and participants happened to endorse similarly high levels of sleep difficulty.

Participants ranged in age from 18–70 years old (M = 38.23, SD = 11.57) and were predominantly female (n = 229, 90.2%). Participants were demographically diverse; 126 participants (49.6%) identified as Black or African American, 116 (45.7%) identified as White, seven (2.8%) identified as another race, one (0.4%) identified as American Indian or Alaska Native, and one (0.4%) identified as Asian. Twelve participants (4.7%) identified as Hispanic or Latino, 224 (88.2) identified as not Hispanic or Latino, and 14 (5.5%) did not report their ethnicity. Most participants (80.4%) were single, separated, divorced, or widowed; a minority (18.5%) were married or cohabitating. Participants reported on average 13.71 years of education (SD = 2.65, range 8–24). Most of the sample (68.9%) reported an annual income of $20,000 or less. Childhood sexual trauma was the most common index trauma type (41.0%), followed by adult sexual trauma (23.4%) and adult physical assault (23.4%), then childhood physical assault (11.7%). Participants attended an average of 7.98 treatment sessions (SD = 5.39), and 62.5% of participants completed treatment.

2.3. Procedure

After providing informed consent, participants completed standardized measures to assess baseline PTSD symptoms, relationship functioning, occupational functioning, physical health functioning, sexual functioning, and quality of life. Participants then received CPT. Starting at the second session, at the beginning of each session, participants completed a measure assessing their experience with therapy practice assignments since the prior session. After completing treatment, participants repeated the assessments administered at baseline and completed a measure assessing their perceptions of process-level factors during treatment (perceptions of the therapeutic relationship, the therapy, and barriers to therapy attendance), as well as global reports of their improvement during treatment across domains (PTSD symptoms, relationship functioning, occupational functioning, physical health functioning, sexual functioning, and quality of life). Participants were invited to complete the posttreatment assessment even if they did not complete the therapy protocol.

2.4. Therapy: Cognitive Processing Therapy (CPT)

CPT is a cognitive, trauma-focused treatment that traditionally includes 12 weekly 60-minute sessions. CPT uses Socratic dialogue, written assignments, and progressive worksheets to target patients’ stuck points, which are maladaptive beliefs that develop after traumatic experiences and maintain PTSD symptoms. The parent trials used the CPT protocol developed by Resick and colleagues (2010), which includes assignment of written trauma accounts. Please see Galovski et al. (2012) and Galovski et al. (2016) for additional details about therapy procedures and treatment fidelity.

2.5. Therapists

Therapists were eight masters- or doctoral-level providers who attended a CPT workshop facilitated by the principal investigator and then attended weekly case consultation.

2.6. Measures

2.6.1. Treatment Outcomes Questionnaire (TOQ)

The TOQ (Galovski et al., 2012) is a locally-constructed self-report measure that includes 20 items assessing patients’ perceptions of treatment and their global ratings of improvement during treatment. Some TOQ items were used as predictors in the present analysis, and some items were used as outcomes. Specifically, the measure includes four items assessing patients’ perceptions of the therapeutic relationship (having felt comfortable talking with the therapist about trauma, the therapist having been knowledgeable and competent, the therapist having been understanding, and the therapist having been supportive), two items assessing patients’ perceptions of the therapy (how helpful treatment was and how much they liked treatment), and two items assessing patients’ perceptions of their barriers to session attendance (to what extent trauma-related symptoms caused them to miss sessions and to what extent non-trauma-related stressors caused them to miss sessions), all of which were used as predictors. The TOQ also includes six items assessing patients’ global ratings of their improvement during treatment across domains (PTSD symptoms, relationships, health concerns, sexual functioning, school or work performance, and all areas of life functioning in general), which were used as outcomes. Items are rated on a scale from 0 (not at all) to 10 (completely). Other questions were open-ended and were not used in the present analysis. One hundred eleven participants (43.7%) completed the TOQ; of that subsample, 15 (13.5%) had not completed treatment but completed the posttreatment assessment.

2.6.2. Practice Assignment Review Form (PARF)

The PARF (Resick et al., 2014; Woolley et al., 2023) is a self-report measure of CPT homework completion and perceived helpfulness. The present study used the single item assessing perceived helpfulness of homework, rated on a five-point scale from 1 (not at all helpful) to 5 (extremely helpful), as a predictor. An average was taken of the perceived helpfulness of all assignments across all sessions attended; higher scores reflect greater perceived helpfulness of homework assignments.

2.6.3. Posttraumatic Stress Diagnostic Scale (PDS)

The PDS (Foa et al., 1997) is a self-report measure assessing the severity of the 17 DSM-IV PTSD symptoms (American Psychiatric Association, 2000), used in this study as an outcome. Participants completed the PDS with reference to their index trauma, which was an incident of interpersonal violence. Each item is scored on a 4-point scale from 0 (never) to 3 (5 times a week or more), with higher scores reflecting greater severity. The PDS has demonstrated good internal consistency, test-retest reliability, and convergent validity with the PTSD diagnosis from the Structured Clinical Interview for DSM-IV (Foa et al., 1997). In the present sample, internal consistency was good to excellent (Cronbach’s α = .87 pretreatment, .95 posttreatment).

2.6.4. Social Adjustment Scale – Self-Report (SAS-SR)

The SAS-SR (Weissman & Bothwell, 1976) is a 54-item self-report measure of social functioning, with higher scores reflecting greater functional impairment, and was used as an outcome. The SAS-SR has good psychometric properties (Weissman & Bothwell, 1976). The present study used an occupational functioning composite that averaged functioning scores across paid work, housework, and schoolwork domains (internal consistency was good to excellent; Cronbach’s α = .94 pretreatment, .89 posttreatment), as well as a relationship functioning composite that averaged functioning scores across social/leisure, extended family, significant other, children, and family unit domains (internal consistency was acceptable to excellent; Cronbach’s α = .95 pretreatment, .64 posttreatment).

2.6.5. Pennebaker Inventory of Limbic Languidness (PILL)

The PILL (Pennebaker, 1982) is a 54-item self-report measure of somatic symptoms assessing a broad array of physical sensations and symptoms and was used as an outcome. Each item is rated on a 5-point scale from 0 (have never or almost never experienced) to 4 (more than once every week); higher scores reflect greater somatic distress and lower physical functioning. The PILL has good internal consistency and test-retest reliability (Pennebaker, 2015). In the present sample, internal consistency was excellent (Cronbach’s α = .92 pretreatment, .93 posttreatment).

2.6.6. Sexual Distress Scale (SDS)

The SDS (Derogatis et al., 2002) is a 20-item self-report measure assessing sexual distress, with higher scores reflecting greater sexual distress and lower sexual functioning, and was used as an outcome. Each item is rated on a scale from 0 (never) to 4 (always). The SDS has demonstrated good psychometric properties among women and men (Santos-Iglesias et al., 2018). In the present sample, internal consistency was excellent (Cronbach’s α = .96 pretreatment, .97 posttreatment).

2.6.7. Quality of Life Inventory (QOLI)

The QOLI (Frisch et al., 1992) is a 32-item self-report measure of quality of life across 16 domains and was used as an outcome. Each domain is assessed with an importance item rated from 0 (not important at all) to 2 (extremely important) followed by a satisfaction item rated from −3 (very dissatisfied) to 3 (very satisfied). The QOLI produces a weighted score by multiplying each item’s importance score by its satisfaction score and then summing all items, with higher scores reflecting greater life satisfaction. The QOLI has good psychometric properties, including test-retest reliability and internal consistency (Frisch et al., 1992). In the present sample, internal consistency was good (Cronbach’s α = .85 pretreatment, .89 posttreatment)

2.7. Data Analytic Plan

Descriptive analyses were conducted in SPSS version 29. Structural equation modeling was conducted in R version 4.3.1 using the lavaan package (Rosseel, 2012). Missing data were handled using maximum likelihood estimation to make use of all available data. First, descriptive analyses (mean, standard deviation, range) were conducted on all observed variables of interest. Bivariate correlations were conducted to examine associations between observed variables capturing patients’ global ratings of improvement in each domain and corresponding standardized measures of the same domain. Table 1 presents the TOQ items used to assess patient ratings of improvement across domains alongside the corresponding standardized measures that were used to assess improvement in the same domains.

Table 1.

Items Assessing Global Ratings of Improvement and Corresponding Standardized Measures of Improvement

Domain Global Rating Item of the TOQ Standardized Measure and Meaning
PTSD symptoms “How much did your PTSD symptoms improve as a result of therapy?” The Posttraumatic Stress Diagnostic Scale (PDS) assesses the severity of the 17 DSM-IV PTSD symptoms.
Relationships “How much did your relationships (e.g., dating, friendship, family life) improve as a result of therapy?” The Social Adjustment Scale – Self-Report (SAS-SR) assesses functional impairment across life domains. A composite was used that averaged subscale scores across social/leisure, extended family, significant other, children, and family unit domains.
Health concerns “How much did your health concerns improve as a result of therapy?” The Pennebaker Inventory of Limbic Languidness (PILL) assesses a broad array of somatic sensations and symptoms reflecting somatic distress and low physical functioning.
Sexual functioning “How much did your sexual functioning improve as a result of therapy?” The Sexual Distress Scale (SDS) assesses sexual distress.
School or work performance “How much did your school or work performance improve as a result of therapy?” The Social Adjustment Scale – Self-Report (SAS-SR) assesses functional impairment across life domains. A composite was used that averaged subscale scores across paid work, housework, and schoolwork domains.
Quality of life “In general, how much improvement did you experience in all areas of life functioning (e.g., general life satisfaction) as a result of therapy?” The Quality of Life Inventory (QOLI) assesses life satisfaction across life domains.
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Note. TOQ = Treatment Outcome Questionnaire, PTSD = posttraumatic stress disorder, DSM = Diagnostic and Statistical Manual of Mental Disorders. Because the TOQ items assessed ratings of improvement, we captured improvement in standardized measures by computing change scores in which each posttreatment score was subtracted from its corresponding pretreatment score. For measures of symptoms and functional impairment, a more negative score reflected a greater decrease and therefore more improvement; for the quality of life measure, a higher score reflected a greater increase and therefore more improvement.

Next, to examine process-level factors as predictors of treatment outcomes, we first conducted a confirmatory factor analysis (CFA) to evaluate the structure of the proposed full structural equation model. The model included six latent factors; four were intended to serve as predictors in the final structural equation model (patients’ perceptions of the therapeutic relationship, patients’ perceptions of the therapy, patients’ perceptions of barriers to therapy attendance, and objective indices of attendance), and two were intended to serve as outcomes (global ratings of improvement during therapy and standardized measures of improvement during therapy). Unit variance identification was used, as some factors only had two indicators, and for factors with only two indicators, the loadings were constrained to be equal to achieve model identification.

Indicators of the latent variable capturing patients’ perceptions of the therapeutic relationship were the four items of the TOQ assessing participants’ perceptions of the therapeutic relationship, described in section 2.6.1 above. Indicators of the latent variable capturing patients’ perceptions of the therapy were the two items on the TOQ assessing the extent to which participants found treatment helpful and the extent to which participants liked treatment, as well as the average of PARF ratings of perceptions of homework’s helpfulness. Indicators of the latent variable capturing patients’ perceptions of barriers to therapy attendance were the two TOQ items assessing the extent to which trauma-related distress and non-trauma-related stressors caused participants to miss or cancel sessions. Indicators of the latent variable capturing objective markers of attendance were a dichotomous variable indicating treatment completion (1) vs. early dropout (0) and attendance rate, calculated as the proportion of sessions attended (as opposed to cancelled or no-showed) out of all sessions scheduled.

Indicators of the latent variable capturing global ratings of improvement during therapy were the six TOQ items assessing patients’ ratings of the extent to which they improved across domains due to therapy (PTSD symptoms, relationships, health concerns, sexual functioning, school or work performance, and life satisfaction). Indicators of the latent variable capturing standardized measures of improvement during therapy were six scores that corresponded to each domain captured by the global ratings. For these indicators, because the TOQ items assessed improvement, change scores were computed by subtracting each posttreatment score from its corresponding pretreatment score. For measures of symptoms and functional impairment, a more negative score reflected a greater decrease and therefore more improvement; for the quality of life measure, a higher score reflected a greater increase and therefore more improvement. The PDS total score captured PTSD symptoms, the SAS-SR relationships composite score captured relationship functioning, the PILL total score captured health concerns, the SDS total score captured sexual distress, the SAS-SR occupational composite score captured work/school functioning, and the QOLI total score captured life satisfaction.

Next, a full structural model was estimated including the same six latent factors with the addition of regression paths and covariances. Each of the two latent variables conceptualized as outcomes (global ratings of improvement and standardized measures of improvement) were regressed on each of the four latent variables conceptualized as predictors (patients’ perceptions of the therapeutic relationship, patients’ perceptions of the therapy, patients’ perceptions of barriers to therapy attendance, and objective indices of attendance). The model also estimated covariances among each pair of latent predictor variables, as well as a residual covariance among the two latent outcome variables.

3. Results

3.1. Descriptive Statistics and Correlations

Means, standard deviations, and ranges of observed variables are presented in Table 2. On average, patients’ scores on standardized measures capturing distress decreased from pretreatment to posttreatment, and scores on the standardized measure capturing quality of life increased. Average global ratings of improvement, which could range from 0 to 10 in each domain with higher scores reflecting greater improvement, ranged from 4.45 (sexual functioning) to 8.05 (PTSD symptoms); average ratings in all domains besides sexual functioning were > 6.

Table 2.

Descriptive Statistics for Observed Indicator Variables

Latent Variable Indicator Mean SD Range
Pt. Perc. Ther. Rel. TOQ: comfort talking with therapist 8.50 2.28 0 to 10
TOQ: confidence in therapist’s knowledge 9.23 1.69 0 to 10
TOQ: therapist was understanding 9.22 1.81 0 to 10
TOQ: therapist was supportive 9.47 1.49 0 to 10
Pt. Perc. Therapy TOQ: treatment helpful 8.62 2.08 0 to 10
TOQ: liked treatment 8.16 2.07 3 to 10
PARF: homework helpful 3.18 0.79 1.00 to 4.64
Pt. Perc. Bar. Att. TOQ: missed sessions due to stressors 6.99 2.88 0 to 10
TOQ: missed sessions due to PTSD-related symptoms 6.18 3.31 0 to 10
Obj. Att. Completer vs. early dropout 0.62 0.49 0 to 1
Attendance rate 0.61 0.32 0 to 1
Global Rat. Improv. TOQ: improvement in PTSD symptoms 8.05 2.31 0 to 10
TOQ: improvement in relationships 6.99 2.88 0 to 10
TOQ: improvement in health concerns 6.18 3.31 0 to 10
TOQ: improvement in sexual functioning 4.45 3.82 0 to 10
TOQ: improvement in school or work performance 6.12 3.65 0 to 10
TOQ: improvement in life satisfaction 7.75 2.44 0 to 10
Stand. Meas. Improv. Change in PDS −19.56 12.76 −49 to 9
Change in SAS-SR relationships composite −0.48 0.64 −2.25 to 1.07
Change in PILL total score −15.11 29.26 −101 to 53
Change in SDS total score −14.41 18.36 −55 to 40
Change in SAS-SR occupational composite −0.44 0.76 −2.01 to 3.00
Change in QOLI total score 19.26 30.90 −63 to 114
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Note. SD = standard deviation, Pt. Perc. Ther. Rel. = patients’ perceptions of the therapeutic relationship, Pt. Perc. Therapy = patients’ perceptions of the therapy, Pt. Perc. Bar. Att. = patients’ perceptions of barriers to therapy attendance, Obj. Att. = objective indices of attendance, Global Rat. Improv. = global ratings of improvement, Stand. Meas. Improv. = standardized measures of improvement, with change referring to a change in scores from pretreatment to posttreatment, TOQ = Treatment Outcome Questionnaire, PARF = Practice Assignment Review Form, PTSD = posttraumatic stress disorder, PDS = PTSD Diagnostic Scale for DSM-IV, SAS-SR = Social Adjustment Scale – Self-Report, PILL = Pennebaker Inventory of Limbic Languidness, SDS = Sexual Distress Scale, QOLI = Quality of Life Inventory.

Descriptive correlations among observed measures of attendance revealed that patients’ perceptions of barriers to therapy attendance were associated with objective indices of attendance. Specifically, patients’ perceptions of the extent to which PTSD-related distress caused them to miss sessions significantly correlated with lower likelihood of treatment completion (r = −.41, p < .001) and lower attendance rate (r = −.57, p < .001), and patients’ perceptions of the extent to which non-PTSD-related stressors caused them to miss sessions also correlated with lower likelihood of completing treatment (r = −.27, p < .01) and lower attendance rate (r = −.43, p < .001).

All correlations were significant among pairs of corresponding markers of improvement during treatment (global ratings of improvement with corresponding standardized measure change scores). Patients’ ratings of improvement in PTSD correlated with a reduction in the PDS (r = −.64, p < .001), patients’ ratings of improvement in relationships correlated with a reduction in the SAS-SR relationship impairment composite (r = −.43, p < .001), patients’ ratings of improvement in health concerns correlated with a reduction in health-related concerns assessed via the PILL (r = −.25, p = .012), patients’ ratings of improvement in sexual functioning correlated with a decrease in sexual distress captured by the SDS (r = −.22, p = .036), patients’ ratings of improvement in school/work performance correlated with a reduction in occupational functional impairment measured via the SAS-SR occupational composite (r = −.29, p = .010), and patients’ ratings of improvement in life satisfaction correlated with an increase in the QOLI total score from pretreatment to posttreatment (r = .34, p = .001). Correlations between global ratings and standardized measures of improvement in health functioning, sexual functioning, and school/work functioning had small effect sizes; correlations between measures of improvement in relationship functioning and quality of life had medium effect sizes; and the correlation between measures of improvement in PTSD symptoms had a large effect size.

3.2. Predictor Model: Confirmatory Factor Analysis

The CFA converged with good fit by most indices: χ2(217) = 331.60, p < .001; Comparative Fit Index (CFI) = .92, Tucker-Lewis Index (TLI) = .91, Root Mean Square Error of Approximation (RMSEA) = .06, Standardized Root Mean Square Residual (SRMR) = .10. Only the SRMR value was slightly out of range. All indicators loaded significantly onto their respective latent factors (all ps < .05). Full model results are presented in Table 3.

Table 3.

Confirmatory Factor Analysis Results

Latent Variable Indicator Estimate SE z p 95% CI Lower 95% CI Upper
Patients’ perceptions of the therapeutic relationship
Comfortable with therapist 1.29 0.20 6.32 <.001 0.89 1.69
Confident therapist knowledgeable 1.47 0.13 11.44 <.001 1.21 1.72
Therapist was understanding 1.61 0.14 11.93 <.001 1.34 1.87
Therapist was supportive 1.44 0.12 12.27 <.001 1.21 1.67
Patients’ perceptions of the therapy
Treatment helpful 2.05 0.17 12.23 <.001 1.72 2.38
Liked treatment 1.20 0.18 6.52 <.001 0.84 1.56
Homework helpful 0.24 0.11 2.12 .034 0.02 0.46
Patients’ perceptions of barriers to therapy attendance
Missed sessions due to stressors 3.05 0.28 10.79 <.001 2.50 3.61
Missed sessions due to PTSD 3.05 0.28 10.79 <.001 2.50 3.61
Objective indices of attendance
Complete vs. early drop 0.34 0.02 16.07 <.001 0.30 0.38
Attendance rate 0.34 0.02 16.07 <.001 0.30 0.38
Global ratings of improvement
PTSD symptoms 2.10 0.17 12.53 <.001 1.77 2.43
Relationships 2.31 0.23 10.17 <.001 1.87 2.76
Health concerns 2.31 0.28 8.30 <.001 1.77 2.86
Sexual functioning 1.86 0.36 5.15 <.001 1.15 2.57
School/work performance 2.56 0.31 8.29 <.001 1.96 3.17
Life satisfaction 2.28 0.17 13.08 <.001 1.94 2.62
Standardized measures of improvement
PTSD symptoms 11.18 1.13 9.91 <.001 8.97 13.39
Relationship functioning 0.37 0.06 5.93 <.001 0.25 0.49
Health functioning 13.46 2.89 4.66 <.001 7.79 19.13
Sexual distress 7.59 2.00 3.79 <.001 3.66 11.51
Occupational functioning 0.34 0.08 4.23 <.001 0.18 0.49
Quality of life −15.22 3.40 −4.48 <.001 −21.87 −8.56
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Note. SE = standard error, CI = confidence interval. Paths for indicators of latent variables with only two indicators were constrained to be equal.

3.3. Predictor Model: Full Structural Model

The full structural model had identical fit indices to the CFA. As with the CFA, all indicators loaded significantly onto their respective latent factors (all ps < .05). Full model results are presented in Table 4. Model results are also depicted visually in Figure 1; paths that are significant at a threshold of p < .05 are depicted in black, and paths that were not significant are depicted in gray.

Table 4.

Full Structural Model Results

Latent Variable Indicator Estimate SE z p 95% CI Lower 95% CI Upper
Patients’ perceptions of the therapeutic relationship
Comfortable with therapist 1.29 0.20 6.32 <.001 0.89 1.69
Confident therapist knowledgeable 1.47 0.13 11.44 <.001 1.21 1.72
Therapist was understanding 1.61 0.14 11.93 <.001 1.34 1.87
Therapist was supportive 1.44 0.12 12.27 <.001 1.21 1.67
Patients’ perceptions of the therapy
Treatment helpful 2.05 0.17 12.23 <.001 1.72 2.38
Liked treatment 1.20 0.18 6.52 <.001 0.84 1.56
Homework helpful 0.24 0.11 2.12 .034 0.02 0.46
Patients’ perceptions of barriers to therapy attendance
Missed sessions due to stressors 3.05 0.28 10.79 <.001 2.50 3.61
Missed sessions due to PTSD 3.05 0.28 10.79 <.001 2.50 3.61
Objective indices of attendance
Complete vs. early drop 0.34 0.02 16.07 <.001 0.30 0.38
Attendance rate 0.34 0.02 16.07 <.001 0.30 0.38
Global ratings of improvement
PTSD symptoms 1.20 0.17 7.26 <.001 0.88 1.52
Relationships 1.32 0.20 6.59 <.001 0.93 1.71
Health concerns 1.32 0.22 6.01 <.001 0.89 1.75
Sexual functioning 1.06 0.24 4.41 <.001 0.59 1.54
School/work performance 1.47 0.24 6.03 <.001 0.99 1.94
Life satisfaction 1.30 0.18 7.37 <.001 0.96 1.65
Standardized measures of improvement
PTSD symptoms 9.47 1.06 8.90 <.001 7.39 11.55
Relationship functioning 0.31 0.05 5.80 <.001 0.21 0.42
Health functioning 11.40 2.52 4.53 <.001 6.46 16.33
Sexual distress 6.42 1.72 3.74 <.001 3.06 9.79
Occupational functioning 0.28 0.07 4.13 <.001 0.15 0.42
Quality of life −12.89 2.88 −4.47 <.001 −18.53 −7.24
Outcome Predictor Estimate SE z p 95% CI Lower 95% CI Upper
Global ratings of improvement
Pt perceptions ther. relationship −0.10 0.26 −0.37 .715 −0.60 0.42
Pt perceptions therapy 1.52 0.44 3.47 .001 0.66 2.39
Pt perceptions barr. to th. attend. −0.04 0.16 −0.23 .816 −0.36 0.28
Objective attendance −0.17 0.16 −1.09 .278 −0.49 0.14
Standardized measures of improvement
Pt perception ther. relationship 0.15 0.20 0.74 .457 −0.24 0.54
Pt perception therapy −0.72 0.23 −3.17 .002 −1.16 −0.27
Pt perceptions barr. to th. attend. −0.16 0.18 −0.87 .386 −0.51 0.20
Objective attendance −0.15 0.18 −0.87 .382 −0.50 0.19
Covariate 1 Covariate 2 Estimate SE z p 95% CI Lower 95% CI Upper
Patients’ perceptions of the therapeutic relationship
Pt perception of the therapy 0.72 0.06 12.75 <.001 0.61 0.84
Pt perceptions barr. to th. attend. −0.11 0.12 −0.92 .360 −0.35 0.13
Objective indices of attendance 0.05 0.12 0.43 .668 −0.18 0.29
Patients’ perceptions of the therapy
Pt perceptions barr. to th. attend. −0.21 0.11 −1.93 .054 −0.43 0.00
Objective indices of attendance 0.20 0.11 1.83 .067 −0.01 0.42
Patients’ perceptions of barriers to therapy attendance
Objective indices of attendance −0.67 0.07 −9.73 <.001 −0.80 −0.53
Global ratings of improvement (residual covariance)
Std. measures of improvement −0.60 0.09 −6.47 <.001 −0.79 −0.42
Open in a new tab

Note. SE = standard error, CI = confidence interval, Pt = patient, ther. = therapeutic, Std. = standardized, Pt perceptions barr. to th. attend. = Patients’ perceptions of barriers to therapy attendance. Paths for indicators of latent variables with only two indicators were constrained to be equal.

Figure 1.

Figure 1

Open in a new tab

Full Structural Model Results

Note. Paths depicted in back were significant at a threshold of p < .05; paths depicted in gray were not significant. Th = therapist, Tx = treatment, Hw = homework, Pt = patient, Δ = change, PTSD = posttraumatic stress disorder, PDS = PTSD Diagnostic Scale for DSM-IV, SAS-SR = Social Adjustment Scale – Self-Report, PILL = Pennebaker Inventory of Limbic Languidness, SDS = Sexual Distress Scale, QOLI = Quality of Life Inventory.

Only one predictor emerged as significant: patients’ perceptions of the therapy significantly predicted both global ratings of improvement and standardized measures of improvement. Patients’ perceptions of the therapeutic relationship, patients’ perceptions of barriers to therapy attendance, and objective indices of attendance did not predict improvement measured via global ratings or standardized measures. Among the latent predictors, patients’ perceptions of the therapeutic relationship covaried with patients’ perceptions of the therapy, and patients’ perceptions of barriers to therapy attendance covaried with objective indices of attendance. The residual covariance between the two latent outcome variables capturing global ratings and standardized measures of improvement across domains was also significant.

4. Discussion

The present study examined associations between patients’ global ratings of improvement across domains of symptomatology and functioning over the course of CPT for PTSD with corresponding standardized measures of improvement, as well as process-level treatment factors as predictors of improvement assessed via both methods. Global ratings of improvement in each domain significantly correlated with change scores in standardized measures in the same domain with small-to-medium effect sizes, except for the correlation between PTSD improvement indicators, which had a large effect size. When process-level therapy factors were examined as predictors of global ratings and standardized measures of improvement, patients’ perceptions of the therapy emerged as a significant predictor of improvement measured using both methods, while patients’ perceptions of the therapeutic relationship, patients’ perceptions of barriers to therapy attendance, and objective indices of attendance did not predict improvement measured using either method.

Consistent with our hypothesis, global ratings of improvement in each domain were correlated with standardized measures of improvement in the same domain, although consistent with past research, the effect sizes were modest. Small effects were observed for pairs of measures assessing improvement in health functioning, sexual functioning, and school/work functioning; medium effects were observed for pairs of measures assessing improvement in relationship functioning and quality of life; and a large effect was only observed for the pair of measures assessing improvement in PTSD symptoms. The effect size found for the association for PTSD symptoms was larger than the medium effect found in a prior study (Matthews et al., 2022), which may be due to differences in how global ratings of improvement and standardized measures of improvement were used across the two studies. Matthews and colleagues calculated a reliable change index for both patients’ ratings of improvement and improvement using a self-report measure, whereas the present study used a single item assessing global ratings of improvement in each domain and a change score for self-report measures across time points. These differences in approaches and corresponding findings serve to illustrate the discrepancies that can occur when using measures slightly differently (e.g., global improvement rating, change score, reliable change index, diagnostic threshold). Overall, the fact that most associations between global ratings of improvement and standardized measures of improvement were small or medium in effect size is consistent with prior findings that improvement measured in these two ways do not directly correspond (Liebmann et al., 2022; Matthews et al., 2022; Vincent et al., 2006).

The present findings, together with prior literature, suggest that assessing patients’ global ratings of change during therapy captures different information than assessing change using standardized measures. Standardized measures generally include many items that assess a broad range of symptoms and experiences meant to apply broadly across patients, yet each experience may not necessarily be salient to every patient. For example, the SAS-SR includes items assessing the extent to which the respondent was able to talk about feelings and problems with relatives, avoided contact with relatives, and depended on relatives for help, advice, money, or friendship over the prior two weeks. Some patients with low scores on these items may report being bothered by these difficulties, and improvement in these areas during treatment may be quite salient to them, whereas other patents may not value these experiences and may not experience change or lack thereof in these areas as meaningful. Similarly, a divorce or job loss may be experienced by one patient as incredibly distressing and by another as an opportunity to make meaningful changes. Standardized assessments are both useful and ubiquitous in the field, and at the same time, patients’ global views of their difficulties and well-being are invaluable. Indeed, the primary goal of clinical research and practice is to help patients improve their mental health, and patients’ ratings of their own improvement matter.

Given that global ratings of change and standardized measures of change seem to provide overlapping yet distinct information, both types of assessments serve as meaningful indicators of improvement. In particular, global assessment of patients’ perceived improvement can highlight improvement in whatever domains of functioning are most important to a given patient. Rather than patients’ being constrained to the items on standardized measures, which may or may not accurately capture their specific experience of wellness or distress, this form of assessment allows patients to express the impact or lack thereof of treatment on their lives. It would be useful for future research studies to assess global ratings of improvement across domains, and clinicians might also incorporate assessment of patients’ subjective views of their improvement into clinical care.

The differences in correlations across different pairs of measures is noteworthy. The strongest correspondence was observed for improvement in PTSD symptoms. This is not surprising given that CPT and other ESTs for PTSD are primarily designed to treat the core symptoms of PTSD, and PTSD symptoms are more-often monitored and discussed than other outcomes, such as functional impairments and well-being (Galovski, Nixon, et al., 2024). Functional impairments are often considered secondary outcomes and targeted indirectly through relief in core symptoms. However, the fact that we observed small-to-moderate correspondence in global ratings and standardized measures of domains of functioning and quality of life could indicate that therapists and patients are less congruent in their perceptions of the patient’s improvement in important life domains. With increased focus on functioning as an intervention target within the context of ESTs, patients’ global reports of improvements across domains of functioning may correspond more closely to their reports on standardized measures, and patients may feel their needs in these areas are better met (Galovski, McSweeney, et al., 2024).

The present study also examined predictors of clinical improvement, and findings suggested that process-level therapy factors did not differentially predict global ratings of improvement and standardized measures of improvement. Rather, the latent variable capturing patients’ perceptions of the therapy was the only significant predictor of improvement assessed via both approaches. The predictive relationship between patients’ perceptions of the therapy and clinical improvement is consistent with previous findings linking buy-in to the treatment rationale (Litz et al., 2019; Price et al., 2015) and perceived usefulness of treatment content and treatment satisfaction (Beehler et al., 2021) to better treatment outcomes, including patients’ ratings of improvement (Beehler et al., 2021). These results suggest that positive views of treatment are important for treatment outcomes regardless of how the outcomes are measured, and it is critical for providers to personalize the explanation of the rationale for the treatment elements to individual patients’ needs and goals. Trauma-focused therapy, by definition, requires the patient to do precisely the thing that they most do not want to do – process the trauma. The rationale for engaging in this therapeutic process must be understood and accepted by the patient in order to maximize intervention benefit (Galovski et al., 2020).

The findings that patients’ perceptions of the therapeutic relationship, patients’ perceptions of barriers to therapy attendance, and objective indices of attendance did not predict either index of improvement was more surprising. These findings were inconsistent with prior findings linking the therapeutic alliance (Clemence et al., 2005; Keefe et al., 2022; Sijercic et al., 2021; Sripada & Walters, 2022) and engagement assessed via session attendance and treatment completion (Berke et al., 2019; Holmes et al., 2019; Taylor, 2003; Thompson-Hollands et al., 2023) to better treatment outcomes, including patients’ ratings of improvement (Clemence et al., 2005). At the same time, process-level factors can be interconnected, and indeed, some of the latent predictor variables significantly covaried. Additionally, the items assessing patients’ perceptions of the therapeutic relationship, more so than other items on the same measure, had particularly high values and low variability, so it is possible that ceiling effects contributed to null findings. Rather than concluding that patients’ perceptions of the therapeutic relationship and barriers to therapy attendance are not important for outcomes, it seems more likely that these variables’ lack of significance as predictors could have been due to their being included together in the same model with patients’ perceptions of the intervention’s helpfulness and likability.

4.1. Strengths, Limitations, and Future Directions

A strength of the present study is that improvement during CPT was assessed in multiple ways, including global ratings of improvement and standardized measures of improvement across symptoms, domains of functioning, and quality of life. This assessment strategy allowed us to paint a holistic picture of improvement and examine different approaches to assessing therapeutic change. The sample was large and demographically diverse, increasing the generalizability of the findings, although generalizability to samples with a higher proportion of males and non-interpersonal trauma is unknown, as well as to samples reporting symptoms using the updated PDS-5. Additionally, although the sample was large, the parent trials were not powered with these secondary analyses in mind, and these analyses may have been underpowered to detect some of the non-significant paths in the model.

A significant limitation of the present study is that the measure assessing patients’ ratings of the therapeutic relationship, the therapy, barriers to therapy attendance, and improvement was only administered at posttreatment. Therefore, only participants completing the posttreatment assessment, most of whom were treatment completers, provided these data, potentially introducing bias. Additionally, retrospective reporting could have been biased by treatment outcome. For example, while filling out the questionnaire after completing treatment, a patient who did not improve during treatment may have looked back and reported having had a more negative view of the therapy and the therapist than while going through treatment. The TOQ is also not yet validated nor widely used. Future research should use validated measures to assess patients’ ratings of symptoms, functioning, and process-level factors during the treatment course to better assess the temporality of perceptions of treatment processes and outcomes and to better capture the experiences of participants who do not complete treatment. Further, the measure used to assess perceptions of change listed global domains of symptoms and functioning, then asked patients to rate their improvement on a Likert scale. More nuanced assessment of patients’ experiences could also include coding of open-ended responses or discussion with the clinician of their experiences in therapy related to improvement or lack thereof in different domains and in their individual goals. If this discussion occurs with clinicians, therapists can encourage patients to generalize the skills from which they particularly benefitted to other areas of their life, perhaps contributing to more holistic, impactful outcomes and the maintenance of gains over time. Future research is needed to identify ways patients’ global ratings of improvement could be used to increase their clinical benefit.

Another strength of the present study is its focus on nonspecific, process-level factors as predictors of improvement. At the same time, this scope of focus means other important predictors were not included in the analysis, including treatment-specific processes such as cognitive change. Future research is needed to examine nonspecific and treatment-specific processes together as predictors of improvement assessed in various ways. Finally, future research should continue to integrate global ratings of treatment processes and outcomes to capture a fuller picture of treatment effectiveness that incorporates patients’ subjective experiences of treatment.

Highlights.

  • Assessing patients’ experiences of therapeutic change is important.

  • Patients rated global improvement across domains of functioning after CPT for PTSD.

  • Patients’ global ratings correlated modestly with standardized measures of change.

  • Patients’ perceptions of the therapy predicted improvement assessed both ways.

  • Patients’ perceptions of the therapist and attendance did not predict outcomes.

Funding:

This work was supported by National Institute of Mental Health Award R34-MH-074937 awarded to Tara E. Galovski, Ph.D. and National Center for Complementary and Integrative Health Award R21-AT-004079 awarded to Tara E. Galovski, Ph.D. Elizabeth Alpert’s work on this project was supported by National Institute of Mental Health Award K23-MH-132815 awarded to Elizabeth Alpert, Ph.D.

Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests. Tara E. Galovski reports financial support was provided by National Institute of Mental Health. Tara E. Galovski reports financial support was provided by National Center for Complementary and Integrative Health. Elizabeth Alpert reports financial support was provided by National Institute of Mental Health. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Footnotes

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Declarations of Interest: None

References

  1. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders: DSM-IV (4th ed.). American Psychiatric Association. [Google Scholar]
  2. American Psychological Association. (2017). Clinical practice guidelines for the treatment of PTSD. https://www.apa.org/ptsd-guideline/ptsd.pdf
  3. Beehler GP, Loughran TA, King PR, Dollar KM, Murphy JL, Kearney LK, & Goldstein WR (2021). Patients’ perspectives of brief cognitive behavioral therapy for chronic pain: Treatment satisfaction, perceived utility, and global assessment of change. Families, Systems, & Health, 39(2), 351–357. 10.1037/fsh0000606 [DOI] [PubMed] [Google Scholar]
  4. Berke DS, Kline NK, Wachen JS, McLean CP, Yarvis JS, Mintz J, Young-McCaughan S, Peterson AL, Foa EB, Resick PA, & Litz BT (2019). Predictors of attendance and dropout in three randomized controlled trials of PTSD treatment for active duty service members. Behaviour Research and Therapy, 118, 7–17. 10.1016/j.brat.2019.03.003 [DOI] [PubMed] [Google Scholar]
  5. Boswell JF, Kraus DR, Miller SD, & Lambert MJ (2015). Implementing routine outcome monitoring in clinical practice: Benefits, challenges, and solutions. Psychotherapy Research, 25(1), 6–19. 10.1080/10503307.2013.817696 [DOI] [PubMed] [Google Scholar]
  6. Clemence AJ, Hilsenroth MJ, Ackerman SJ, Strassle CG, & Handler L (2005). Facets of the therapeutic alliance and perceived progress in psychotherapy: Relationship between patient and therapist perspectives. Clinical Psychology & Psychotherapy, 12(6), 443–454. 10.1002/cpp.467 [DOI] [Google Scholar]
  7. Department of Veterans Affairs & Department of Defense. (2023). VA/DoD clinical practice guideline for the management of posttraumatic stress disorder and acute stress disorder. https://www.healthquality.va.gov/guidelines/MH/ptsd/VA-DoD-CPG-PTSD-Full-CPGAug242023.pdf
  8. Derogatis LR, Rosen R, Leiblum S, Burnett A, & Heiman J (2002). The Female Sexual Distress Scale (FSDS): Initial validation of a standardized scale for assessment of sexually related personal distress in women. Journal of Sex & Marital Therapy, 28(4), 317–330. 10.1080/00926230290001448 [DOI] [PubMed] [Google Scholar]
  9. Foa EB, Cashman L, Jaycox L, & Perry K (1997). The validation of a self-report measure of posttraumatic stress disorder: The Posttraumatic Diagnostic Scale. Psychological Assessment, 9(4), 445–451. 10.1037/1040-3590.9.4.445 [DOI] [Google Scholar]
  10. Foa EB, Hembree EA, Rothbaum BO, & Rauch S (2019). Prolonged exposure therapy for PTSD: Emotional processing of traumatic experiences - Therapist guide. Oxford University Press. https://www.oxfordclinicalpsych.com/view/10.1093/med-psych/9780190926939.001.0001/med-9780190926939 [Google Scholar]
  11. Forbes D, Bisson JI, Monson CM, & Berliner L (Eds.). (2020). Effective treatments for PTSD: Practice guidelines from the international society for traumatic stress studies (Third edition). The Guilford Press. [Google Scholar]
  12. Frisch MB, Cornell J, Villanueva M, & Retzlaff PJ (1992). Clinical validation of the Quality of Life Inventory. A measure of life satisfaction for use in treatment planning and outcome assessment. Psychological Assessment, 4(1), 92–101. 10.1037/1040-3590.4.1.92 [DOI] [Google Scholar]
  13. Galovski TE, Blain LM, Mott JM, Elwood L, & Houle T (2012). Manualized therapy for PTSD: Flexing the structure of cognitive processing therapy. Journal of Consulting and Clinical Psychology, 80(6), 968–981. 10.1037/a0030600 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Galovski TE, Harik JM, Blain LM, Elwood L, Gloth C, & Fletcher TD (2016). Augmenting cognitive processing therapy to improve sleep impairment in PTSD: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 84(2), 167–177. 10.1037/ccp0000059 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Galovski TE, McSweeney LB, Nixon RDV, Wachen JS, Smith BN, Noorbaloochi S, Vogt DS, Niles BL, & Kehle-Forbes SM (2024). Personalizing cognitive processing therapy with a case formulation approach to intentionally target impairment associated with psychosocial functioning associated with PTSD. Contemporary Clinical Trials, 42, 101385. 10.1016/j.conctc.2024.101385 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Galovski TE, Nixon RDV, & Kehle-Forbes S (2024). Walking the line between fidelity and flexibility: A conceptual review of personalized approaches to manualized treatments for posttraumatic stress disorder. Journal of Traumatic Stress, 37(5), 768–774. 10.1002/jts.23073 [DOI] [PubMed] [Google Scholar]
  17. Galovski TE, Nixon R, & Kaysen D (2020). Flexible applications of cognitive processing therapy evidence-based treatment methods. Academic Press. https://www.sciencedirect.com/science/book/9780128167151 [Google Scholar]
  18. Holdsworth E, Bowen E, Brown S, & Howat D (2014). Client engagement in psychotherapeutic treatment and associations with client characteristics, therapist characteristics, and treatment factors. Clinical Psychology Review, 34(5), 428–450. 10.1016/j.cpr.2014.06.004 [DOI] [PubMed] [Google Scholar]
  19. Holmes SC, Johnson CM, Suvak MK, Sijercic I, Monson CM, & Wiltsey Stirman S (2019). Examining patterns of dose response for clients who do and do not complete cognitive processing therapy. Journal of Anxiety Disorders, 68, 102120. 10.1016/j.janxdis.2019.102120 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Hundt NE, Barrera TL, Arney J, & Stanley MA (2017). “It’s worth it in the end”: Veterans’ experiences in prolonged exposure and cognitive processing therapy. Cognitive and Behavioral Practice, 24(1), 50–57. 10.1016/j.cbpra.2016.02.003 [DOI] [Google Scholar]
  21. Hundt NE, Ecker AH, Thompson K, Helm A, Smith TL, Stanley MA, & Cully JA (2020). “It didn’t fit for me:” A qualitative examination of dropout from prolonged exposure and cognitive processing therapy in veterans. Psychological Services, 17(4), 414–421. 10.1037/ser0000316 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Keefe JR, Hernandez S, Johanek C, Landy MSH, Sijercic I, Shnaider P, Wagner AC, Lane JEM, Monson CM, & Stirman SW (2022). Competence in delivering cognitive processing therapy and the therapeutic alliance both predict PTSD symptom outcomes. Behavior Therapy, 53(5), 763–775. 10.1016/j.beth.2021.12.003 [DOI] [PubMed] [Google Scholar]
  23. Lambert MJ, Whipple JL, & Kleinstäuber M (2018). Collecting and delivering progress feedback: A meta-analysis of routine outcome monitoring. Psychotherapy, 55(4), 520–537. 10.1037/pst0000167 [DOI] [PubMed] [Google Scholar]
  24. Liebmann EP, Resnick SG, Hoff RA, & Katz IR (2022). Interpreting patient reports of perceived change during treatment for depression: Findings from the Veterans Outcome Assessment survey. Psychiatry Research, 309, 114402. 10.1016/j.psychres.2022.114402 [DOI] [PubMed] [Google Scholar]
  25. Litz BT, Berke DS, Kline NK, Grimm K, Rusowicz-Orazem L, Resick PA, Foa EB, Wachen JS, McLean CP, Dondanville KA, Borah AM, Roache JD, Young-McCaughan S, Yarvis JS, Mintz J, & Peterson AL (2019). Patterns and predictors of change in trauma-focused treatments for war-related posttraumatic stress disorder. Journal of Consulting and Clinical Psychology, 87(11), 1019–1029. 10.1037/ccp0000426 [DOI] [PubMed] [Google Scholar]
  26. Matthews SR, Elizabeth M, Roberts LN, & Nixon RDV (2022). Client versus clinicians’ standards of clinically meaningful change and the effects of treatment expectations on therapeutic outcomes in individuals with posttraumatic stress disorder. Behavior Therapy, 53(3), 560–570. 10.1016/j.beth.2021.12.007 [DOI] [PubMed] [Google Scholar]
  27. Norman SB (2022). Effectiveness of currently available psychotherapies for post-traumatic stress disorder and future directions. World Psychiatry, 21(2), 309–310. 10.1002/wps.20974 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Pennebaker JW (1982). The psychology of physical symptoms. Springer-Verlag. [Google Scholar]
  29. Pennebaker JW (2015, November 9). Pennebaker Inventory of Limbic Languidness [Database record]. APA PsycTests. 10.1037/t05558-000 [DOI] [Google Scholar]
  30. Price M, Maples JL, Jovanovic T, Norrholm SD, Heekin M, & Rothbaum BO (2015). An investigation of outcome expectancies as a predictor of treatment response for combat veterans with PTSD: Comparison of clinician, self-report, and biological measures. Depression and Anxiety, 32(6), 392–399. 10.1002/da.22354 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Resick PA, Monson CM, & Chard KM (2010). Cognitive processing therapy veteran/military version: Therapist’s manual. Department of Veterans Affairs. [Google Scholar]
  32. Resick PA, Monson CM, & Chard KM (2014). Cognitive processing therapy veteran/military version: Therapist and patient materials manual. Department of Veterans Affairs. http://doi.apa.org/get-pe-doi.cfm?doi=10.1037/e514732018-001 [Google Scholar]
  33. Resick PA, Monson CM, & Chard KM (2017). Cognitive processing therapy for PTSD: A comprehensive manual (1st edition). The Guilford Press. [Google Scholar]
  34. Rosseel Y (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2). 10.18637/jss.v048.i02 [DOI] [Google Scholar]
  35. Sales CMD, & Alves PCG (2016). Patient-centered assessment in psychotherapy: A review of individualized tools. Clinical Psychology: Science and Practice, 23(3), 265–283. 10.1037/h0101737 [DOI] [Google Scholar]
  36. Santos-Iglesias P, Mohamed B, Danko A, & Walker LM (2018). Psychometric validation of the Female Sexual Distress Scale in male samples. Archives of Sexual Behavior, 47(6), 1733–1743. 10.1007/s10508-018-1146-2 [DOI] [PubMed] [Google Scholar]
  37. Sijercic I, Liebman RE, Stirman SW, & Monson CM (2021). The effect of therapeutic alliance on dropout in cognitive processing therapy for posttraumatic stress disorder. Journal of Traumatic Stress, 34(4), 819–828. 10.1002/jts.22676 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Sripada RK, & Walters HM (2022). “I wish people could come together like we have,” patient and provider perspectives on VA residential PTSD treatment. Psychological Services, 20(4), 809–819. 10.1037/ser0000713 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Szafranski DD, Smith BN, Gros DF, & Resick PA (2017). High rates of PTSD treatment dropout: A possible red herring? Journal of Anxiety Disorders, 47, 91–98. 10.1016/j.janxdis.2017.01.002 [DOI] [PubMed] [Google Scholar]
  40. Taylor S (2003). Outcome predictors for three PTSD treatments: Exposure therapy, EMDR, and relaxation training. Journal of Cognitive Psychotherapy, 17(2), 149–162. 10.1891/jcop.17.2.149.57432 [DOI] [Google Scholar]
  41. Thompson-Hollands J, Lunney CA, Sloan DM, Wiltsey Stirman S, & Schnurr PP (2023). Treatment length and symptom improvement in prolonged exposure and present-centered therapy for posttraumatic stress disorder: Comparing dose–response and good-enough level models in two manualized interventions. Journal of Consulting and Clinical Psychology. 10.1037/ccp0000834 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Vincent N, Penner S, & Lewycky S (2006). What predicts patients’ perceptions of improvement in insomnia? Journal of Sleep Research, 15(3), 301–308. 10.1111/j.1365-2869.2006.00529.x [DOI] [PubMed] [Google Scholar]
  43. Watson P (2019). PTSD as a public mental health priority. Current Psychiatry Reports, 21(7), 61. 10.1007/s11920-019-1032-1 [DOI] [PubMed] [Google Scholar]
  44. Weissman MM, & Bothwell S (1976). Assessment of social adjustment by patient self-report. Archives of General Psychiatry, 33(9), 1111. 10.1001/archpsyc.1976.01770090101010 [DOI] [PubMed] [Google Scholar]
  45. Wells SY, Morland LA, Hurst S, Jackson GL, Kehle-Forbes SM, Jaime K, & Aarons GA (2022). Veterans’ reasons for dropping out of prolonged exposure therapy across three delivery modalities: A qualitative examination. Psychological Services. Advanced online publication. 10.1037/ser0000714 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Woolley MG, Smith BN, Micol RL, Farmer CC, & Galovski TE (2023). Evaluating the relative contribution of patient effort and therapist skill in integrating homework into treatment for posttraumatic stress disorder. Psychological Trauma: Theory, Research, Practice, and Policy. 10.1037/tra0001459 [DOI] [PubMed] [Google Scholar]

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