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Engagement, Predictors, and Outcomes of a Trauma Recovery Digital Mental Health Intervention: Longitudinal Study.
Yeager, Carolyn M; Benight, Charles C.
  • Yeager CM; Lyda Hill Institute for Human Resilience, University of Colorado Colorado Springs, Colorado Springs, CO, United States.
  • Benight CC; Lyda Hill Institute for Human Resilience, University of Colorado Colorado Springs, Colorado Springs, CO, United States.
JMIR Ment Health ; 9(5): e35048, 2022 May 02.
Article in English | MEDLINE | ID: covidwho-1875282
ABSTRACT

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.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Language: English Journal: JMIR Ment Health Year: 2022 Document Type: Article Affiliation country: 35048

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Language: English Journal: JMIR Ment Health Year: 2022 Document Type: Article Affiliation country: 35048