Engagement, Predictors, and Outcomes of a Trauma Recovery Digital Mental Health Intervention: Longitudinal Study.

BACKGROUND: Worldwide, exposure to potentially traumatic events is extremely common, and many individuals develop posttraumatic stress disorder (PTSD) along with other disorders. Unfortunately, considerable barriers to treatment exist. A promising approach to overcoming treatment barriers is a digital mental health intervention (DMHI). However, engagement with DMHIs is a concern, and theoretically based research in this area is sparse and often inconclusive. OBJECTIVE: The focus of this study is on the complex issue of DMHI engagement. On the basis of the social cognitive theory framework, the conceptualization of engagement and a theoretically based model of predictors and outcomes were investigated using a DMHI for trauma recovery. METHODS: A 6-week longitudinal study with a national sample of survivors of trauma was conducted to measure engagement, predictors of engagement, and mediational pathways to symptom reduction while using a trauma recovery DMHI (time 1: N=915; time 2: N=350; time 3: N=168; and time 4: N=101). RESULTS: Confirmatory factor analysis of the engagement latent constructs of duration, frequency, interest, attention, and affect produced an acceptable model fit (χ22=8.3; P=.02; comparative fit index 0.973; root mean square error of approximation 0.059; 90% CI 0.022-0.103). Using the latent construct, the longitudinal theoretical model demonstrated adequate model fit (comparative fit index 0.929; root mean square error of approximation 0.052; 90% CI 0.040-0.064), indicating that engagement self-efficacy (ß=.35; P<.001) and outcome expectations (ß=.37; P<.001) were significant predictors of engagement (R2=39%). The overall indirect effect between engagement and PTSD symptom reduction was significant (ß=-.065; P<.001; 90% CI -0.071 to -0.058). This relationship was serially mediated by both skill activation self-efficacy (ß=.80; P<.001) and trauma coping self-efficacy (ß=.40; P<.001), which predicted a reduction in PTSD symptoms (ß=-.20; P=.02). CONCLUSIONS: The results of this study may provide a solid foundation for formalizing the nascent science of engagement. Engagement conceptualization comprised general measures of attention, interest, affect, and use that could be applied to other applications. The longitudinal research model supported 2 theoretically based predictors of engagement: engagement self-efficacy and outcome expectancies. A total of 2 task-specific self-efficacies-skill activation and trauma coping-proved to be significant mediators between engagement and symptom reduction. Taken together, this model can be applied to other DMHIs to understand engagement, as well as predictors and mechanisms of action. Ultimately, this could help improve the design and development of engaging and effective trauma recovery DMHIs.

Predicting Change in Posttraumatic Distress Through Change in Coping Self-Efficacy After Using the My Trauma Recovery eHealth Intervention: Laboratory Investigation.

BACKGROUND: Technology offers a unique platform for delivering trauma interventions (ie, eHealth) to support trauma-exposed populations. It is important to evaluate mechanisms of therapeutic change in reducing posttraumatic distress in eHealth for trauma survivors. OBJECTIVE: This study evaluated a proactive, scalable, and individually responsive eHealth intervention for trauma survivors called My Trauma Recovery. My Trauma Recovery is an eHealth intervention aiming to support trauma survivors and consisting of 6 modules: relaxation, triggers, self-talk, professional help, unhelpful coping, and social support. It was designed to enhance trauma coping self-efficacy (CSE). We tested 3 hypotheses. First, My Trauma Recovery would decrease posttraumatic stress symptoms (PTSS). Second, My Trauma Recovery would increase CSE. And last, changes in CSE would be negatively correlated with changes in PTSS. METHODS: A total of 92 individuals exposed to trauma (78/92, 85% females, mean age 34.80 years) participated. Our study was part of a larger investigation and consisted of 3 sessions 1 week apart. Participants completed the baseline online survey assessing PTSS and CSE. Each session included completing assigned modules followed by the online survey assessing CSE. PTSS was remeasured at the end of the last module. RESULTS: PTSS significantly declined from T1 to T9 (F1,90=23.63, P<.001, η2p=.21) supporting the clinical utility of My Trauma Recovery. Significant increases in CSE for sessions 1 and 2 (F8,83=7.51, P<.001) were found. No significant change in CSE was found during session 3 (N=92). The residualized scores between PTSS T1 and T9 and between CSE T1 and T9 were calculated. The PTSS residualized score and the CSE residualized score were significantly correlated, r=-.26, P=.01. Results for each analysis with a probable PTSD subsample were consistent. CONCLUSIONS: The findings of our study show that participants working through My Trauma Recovery report clinically lower PTSS after 3 weeks. The results also demonstrate that CSE is an important self-appraisal factor that increased during sessions 1 and 2. These improvements are correlated with reductions in PTSS. Thus, changes in CSE may be an important mechanism for reductions in PTSS when working on a self-help trauma recovery website and may be an important target for eHealth interventions for trauma. These findings have important implications for trauma eHealth interventions.

If we build it, will they come? Issues of engagement with digital health interventions for trauma recovery.

Exposure to traumatic events is extremely common with nearly 75% reported to have experienced one or more traumatic events worldwide. A significant number of those exposed will develop posttraumatic stress disorder (PTSD) along with depression, anxiety, and substance use disorders. Globally, trauma-related mental health disorders are the leading cause of global disability burden, and many of these disorders are caused, or worsened, by exposure to wars, natural and human-caused disasters, and other traumatic events. Significant barriers to treatment exist including logistical, geographical, financial, stigma, and other attitudinal challenges. One opportune approach to overcoming these barriers is the provision of mental health interventions via technology that can be readily standardized for wide dissemination of evidence-based care. However, engagement with technology-based interventions is a concern and limited participation and high attrition rates are common. This may be especially true for trauma survivors who often experience symptoms of avoidance and hyperarousal. Engagement is regarded as an essential component of intervention efficacy and has been demonstrated to be associated with more positive clinical outcomes, yet theoretically based research in this area is sparse. This review focuses on the complex issue of engagement with digital health interventions (DHIs). Specifically, we review the conceptualization and measurement of engagement, predictors of engagement, and importantly, the relationship of engagement with intervention effectiveness. Finally, a theoretically based model of engagement is proposed that considers the unique challenges of trauma recovery. This review is not intended to provide a systematic or exhaustive set of recommendations, rather it is intended to highlight the challenges of engagement research including its definition, measurement, and modeling. Future engagement research that includes valid and reliable measures of engagement will enable consistent exploration of engagement predictors that can then inform methods for increasing engagement and, ultimately, intervention effectiveness.

Engagement With a Trauma Recovery Internet Intervention Explained With the Health Action Process Approach (HAPA): Longitudinal Study.

BACKGROUND: There has been a growing trend in the delivery of mental health treatment via technology (ie, electronic health, eHealth). However, engagement with eHealth interventions is a concern, and theoretically based research in this area is sparse. Factors that influence engagement are poorly understood, especially in trauma survivors with symptoms of posttraumatic stress. OBJECTIVE: The aim of this study was to examine engagement with a trauma recovery eHealth intervention using the Health Action Process Approach theoretical model. Outcome expectancy, perceived need, pretreatment self-efficacy, and trauma symptoms influence the formation of intentions (motivational phase), followed by planning, which mediates the translation of intentions into engagement (volitional phase). We hypothesized the mediational effect of planning would be moderated by level of treatment self-efficacy. METHODS: Trauma survivors from around the United States used the eHealth intervention for 2 weeks. We collected baseline demographic, social cognitive predictors, and distress symptoms and measured engagement subjectively and objectively throughout the intervention. RESULTS: The motivational phase model explained 48% of the variance, and outcome expectations (beta=.36), perceived need (beta=.32), pretreatment self-efficacy (beta=.13), and trauma symptoms (beta=.21) were significant predictors of intention (N=440). In the volitional phase, results of the moderated mediation model indicated for low levels of treatment self-efficacy, planning mediated the effects of intention on levels of engagement (B=0.89, 95% CI 0.143-2.605; N=115). CONCLUSIONS: Though many factors can affect engagement, these results offer a theoretical framework for understanding engagement with an eHealth intervention. This study highlighted the importance of perceived need, outcome expectations, self-efficacy, and baseline distress symptoms in the formation of intentions to use the intervention. For those low in treatment self-efficacy, planning may play an important role in the translation of intentions into engagement. Results of this study may help bring some clarification to the question of what makes eHealth interventions work.