A prognostic index to predict symptom and functional outcomes of a coached, web-based intervention for trauma-exposed veterans.

Researchers at the Department of Veterans Affairs (VA) have studied interventions for posttraumatic stress disorder and co-occurring conditions in both traditional and digital formats. One such empirically supported intervention is web skills training in affective and interpersonal regulation (webSTAIR), a coached, 10-module web program based on STAIR. To understand which patient characteristics were predictive of webSTAIR outcomes in a sample of trauma-exposed veterans (N = 189), we used machine learning (ML) to develop a prognostic index from among 18 baseline characteristics (i.e., demographic, military, trauma history, and clinical) to predict posttreatment posttraumatic stress disorder severity, depression severity, and psychosocial functioning impairment. We compared the ML models to a benchmark of linear regression models in which the only predictor was the baseline severity score of the outcome measure. The ML and "severity-only" models performed similarly, explaining 39%-45% of the variance in outcomes. This suggests that baseline symptom severity and functioning are strong indicators for webSTAIR outcomes in veterans, with higher severity indicating worse prognosis, and that the other variables examined did not contribute significant added predictive signal. Findings also highlight the importance of comparing ML models to an appropriate benchmark. Future research with larger samples could potentially detect smaller patient-level effects as well as effects driven by other types of variables (e.g., therapeutic process variables). As a transdiagnostic, digital intervention, webSTAIR can potentially serve a diverse veteran population with varying trauma histories and may be best conceptualized as a beneficial first step of a stepped care model for those with heightened symptoms or impairment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The PTSD Family Coach App in Veteran Family Members: Pilot Randomized Controlled Trial.

BACKGROUND: Posttraumatic stress disorder (PTSD) among US military veterans can adversely impact their concerned significant others (CSOs; eg, family members and romantic partners). Mobile apps can be tailored to support CSO mental health through psychoeducation, coping skills, and stress monitoring. OBJECTIVE: This study assessed the feasibility, acceptability, and potential efficacy of PTSD Family Coach 1.0, a free, publicly available app that includes psychoeducation, stress management tools, self-assessments, and features for connecting to alternative supports, compared with a psychoeducation-only version of the app for cohabitating CSOs of veterans with PTSD. METHODS: A total of 200 participants with an average age of 39 (SD 8.44) years, primarily female (193/200, 97%), and White (160/200, 80%) were randomized to self-guided use of either PTSD Family Coach 1.0 (n=104) or a psychoeducation-only app (n=96) for 4 weeks. Caregiver burden, stress, depression, anxiety, beliefs about treatment, CSO self-efficacy, and relationship functioning assessed using measures of dyadic adjustment, social constraints, and communication danger signs were administered via a web survey at baseline and after treatment. User satisfaction and app helpfulness were assessed after treatment. Data were analyzed using linear mixed methods. RESULTS: Overall, 50.5% (101/200) of randomized participants used their allocated app. Participants found PTSD Family Coach 1.0 somewhat satisfying (mean 4.88, SD 1.11) and moderately helpful (mean 2.99, SD 0.97) to use. Linear mixed effects models revealed no significant differences in outcomes by condition for caregiver burden (P=.45; Cohen d=0.1, 95% CI -0.2 to 0.4), stress (P=.64; Cohen d=0.1, 95% CI -0.4 to 0.6), depression (P=.93; Cohen d= 0.0, 95% CI -0.3 to 0.3), anxiety (P=.55; Cohen d=-0.1, 95% CI -0.4 to 0.2), beliefs about treatment (P=.71; Cohen d=0.1, 95% CI -0.2 to 0.3), partner self-efficacy (P=.59; Cohen d=-0.1, 95% CI -0.4 to 0.2), dyadic adjustment (P=.08; Cohen d=-0.2, 95% CI -0.5 to 0.0), social constraints (P=.05; Cohen d=0.3, 95% CI 0.0-0.6), or communication danger signs (P=.90; Cohen d=-0.0, 95% CI -0.3 to 0.3). Post hoc analyses collapsing across conditions revealed a significant between-group effect on stress for app users versus nonusers (ß=-3.62; t281=-2.27; P=.02). CONCLUSIONS: Approximately half of the randomized participants never used their allocated app, and participants in the PTSD Family Coach 1.0 condition only opened the app approximately 4 times over 4 weeks, suggesting limitations to this app version's feasibility. PTSD Family Coach 1.0 users reported moderately favorable impressions of the app, suggesting preliminary acceptability. Regarding efficacy, no significant difference was found between PTSD Family Coach 1.0 users and psychoeducation app users across any outcome of interest. Post hoc analyses suggested that app use regardless of treatment condition was associated with reduced stress. Further research that improves app feasibility and establishes efficacy in targeting the domains most relevant to CSOs is warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT02486705; https://clinicaltrials.gov/ct2/show/NCT02486705.

A Pilot Randomized Controlled Trial of the Insomnia Coach Mobile App to Assess Its Feasibility, Acceptability, and Potential Efficacy.

Insomnia is highly prevalent among military veterans but access to cognitive-behavioral therapy for insomnia (CBT-I) is limited. Thus, this study examined the feasibility, acceptability, and potential efficacy of Insomnia Coach, a CBT-I-based, free, self-management mobile app. Fifty U.S. veterans, who were mostly male (58%) and mean age 44.5 (range = 28-55) years with moderate insomnia symptoms were randomized to Insomnia Coach (n = 25) or a wait-list control condition (n = 25) for 6 weeks. Participants completed self-report measures and sleep diaries at baseline, posttreatment, and follow-up (12 weeks postrandomization), and app participants (n = 15) completed a qualitative interview at posttreatment. Findings suggest that Insomnia Coach is feasible to use, with three quarters of participants using the app through 6 weeks and engaging with active elements. For acceptability, perceptions of Insomnia Coach were very favorable based on both self-report and qualitative interview responses. Finally, for potential efficacy, at posttreatment, a larger proportion of Insomnia Coach (28%) than wait-list control participants (4%) achieved clinically significant improvement (p = .049) and there was a significant treatment effect on daytime sleep-related impairment (d = -0.6, p = .044). Additional treatment effects emerged at follow-up for insomnia severity (d = -1.1, p = .001), sleep onset latency (d = -0.6, p = .021), global sleep quality (d = -0.9, p = .002), and depression symptoms (d = -0.8, p = .012). These findings provide preliminary evidence that among veterans with moderate insomnia symptoms, a CBT-I-based self-management app is feasible, acceptable, and promising for improving insomnia severity and other sleep-related outcomes. Given the vast unmet need for insomnia treatment in the population, Insomnia Coach may provide an easily accessible, convenient public health intervention for individuals not receiving care.

PTSD Coach Version 3.1: A Closer Look at the Reach, Use, and Potential Impact of This Updated Mobile Health App in the General Public.

BACKGROUND: With widespread smartphone ownership, mobile health apps (mHealth) can expand access to evidence-based interventions for mental health conditions, including posttraumatic stress disorder (PTSD). Research to evaluate new features and capabilities in these apps is critical but lags behind app development. The initial release of PTSD Coach, a free self-management app developed by the US Departments of Veterans Affairs and Defense, was found to have a positive public health impact. However, major stakeholder-driven updates to the app have yet to be evaluated. OBJECTIVE: We aimed to characterize the reach, use, and potential impact of PTSD Coach Version 3.1 in the general public. As part of characterizing use, we investigated the use of specific app features, which extended previous work on PTSD Coach. METHODS: We examined the naturalistic use of PTSD Coach during a 1-year observation period between April 20, 2020, and April 19, 2021, using anonymous in-app event data to generate summary metrics for users. RESULTS: During the observation period, PTSD Coach was broadly disseminated to the public, reaching approximately 150,000 total users and 20,000 users per month. On average, users used the app 3 times across 3 separate days for 18 minutes in total, with steep drop-offs in use over time; a subset of users, however, demonstrated high or sustained engagement. More than half of users (79,099/128,691, 61.46%) accessed one or more main content areas of the app (ie, Manage Symptoms, Track Progress, Learn, or Get Support). Among content areas, features under Manage Symptoms (including coping tools) were accessed most frequently, by over 40% of users (53,314/128,691, 41.43% to 56,971/128,691, 44.27%, depending on the feature). Users who provided initial distress ratings (56,971/128,691, 44.27%) reported relatively high momentary distress (mean 6.03, SD 2.52, on a scale of 0-10), and the use of a coping tool modestly improved momentary distress (mean -1.38, SD 1.70). Among users who completed at least one PTSD Checklist for DSM-5 (PCL-5) assessment (17,589/128,691, 13.67%), PTSD symptoms were largely above the clinical threshold (mean 49.80, SD 16.36). Among users who completed at least two PCL-5 assessments (4989/128,691, 3.88%), PTSD symptoms decreased from the first to last assessment (mean -4.35, SD 15.29), with approximately one-third (1585/4989, 31.77%) of these users experiencing clinically significant improvements. CONCLUSIONS: PTSD Coach continues to fulfill its mission as a public health resource. Version 3.1 compares favorably with version 1 on most metrics related to reach, use, and potential impact. Although benefits appear modest on an individual basis, the app provides these benefits to a large population. For mHealth apps to reach their full potential in supporting trauma recovery, future research should aim to understand the utility of individual app features and identify strategies to maximize overall effectiveness and engagement.

Understanding indecisiveness: Dimensionality of two self-report questionnaires and associations with depression and indecision.

Indecisiveness is a prevalent and impairing symptom among individuals with major depressive disorder (MDD). However, the use of different self-report questionnaires and factor analysis methods in past research has been a barrier to understanding the nature of indecisiveness in depression. Addressing these barriers could help to elucidate the dimensionality and validity of indecisiveness questionnaires, which in turn would clarify the relation of indecisiveness to depression. In our study of an online sample of adults (N = 602), we administered two commonly used indecisiveness questionnaires, a depressive symptom questionnaire, and a behavioral task assessing indecision. Through confirmatory factor analysis, we found that the combined indecisiveness questionnaires were best characterized by a two-factor model, with one factor corresponding to straightforwardly worded items and the other corresponding to reverse-scored items. Based on post hoc analyses involving tests of discriminant validity, we think that these two factors represent indecisiveness and decision-making confidence, respectively. Indecisiveness, but not decision-making confidence, was strongly associated with depressive symptoms. Indecisiveness was also strongly associated with behavioral indecision, a finding that helps to validate indecisiveness as a construct. We posit that the assessment of indecisiveness could be enhanced by excluding the reverse-scored items because they appear to represent decision-making confidence, a distinct construct from indecisiveness. Excluding the reverse-scored items revealed a robust link between indecisiveness and depressive symptoms, highlighting the importance of targeting this symptom in depression research. (PsycInfo Database Record (c) 2022 APA, all rights reserved).