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Engagement, Predictors, and Outcomes of a Trauma Recovery Digital Mental Health Intervention: Longitudinal Study
JMIR Mental Health ( IF 5.2 ) Pub Date : 2022-05-02 , DOI: 10.2196/35048
Carolyn M Yeager 1 , Charles C Benight 1
Affiliation  

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 (β=.35; P<.001) and outcome expectations (β=.37; P<.001) were significant predictors of engagement (R2=39%). The overall indirect effect between engagement and PTSD symptom reduction was significant (β=–.065; P<.001; 90% CI –0.071 to –0.058). This relationship was serially mediated by both skill activation self-efficacy (β=.80; P<.001) and trauma coping self-efficacy (β=.40; P<.001), which predicted a reduction in PTSD symptoms (β=−.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.

中文翻译:

创伤恢复数字心理健康干预的参与、预测因素和结果:纵向研究

背景:在世界范围内,接触潜在的创伤性事件极为普遍,许多人会出现创伤后应激障碍 (PTSD) 和其他疾病。不幸的是,治疗存在相当大的障碍。克服治疗障碍的一种有前途的方法是数字心理健康干预 (DMHI)。然而,与 DMHI 的接触是一个问题,该领域基于理论的研究很少,而且往往没有定论。目的:本研究的重点是 DMHI 参与的复杂问题。在社会认知理论框架的基础上,使用 DMHI 对参与的概念化以及基于理论的预测因素和结果模型进行了研究,以进行创伤恢复。方法:对全国创伤幸存者样本进行了一项为期 6 周的纵向研究,以测量参与度、参与度的预测因素以及在使用创伤恢复 DMHI 时减轻症状的中介途径(时间 1:N=915;时间 2:N=350 ;时间 3:N=168;和时间 4:N=101)。结果:对持续时间、频率、兴趣、注意力和情感的参与潜在结构的验证性因素分析产生了可接受的模型拟合(χ 2 2 =8.3;P=.02; 比较拟合指数 0.973;均方根误差近似为 0.059;90% CI 0.022-0.103)。使用潜在结构,纵向理论模型证明了足够的模型拟合(比较拟合指数 0.929;近似的均方根误差 0.052;90% CI 0.040-0.064),表明参与自我效能(β=.35;P <. 001) 和结果预期 (β=.37; P <.001) 是参与度的重要预测因子 ( R 2 =39%)。参与和 PTSD 症状减轻之间的总体间接影响是显着的(β=–.065;P< .001;90% CI –0.071 至 –0.058)。这种关系是由技能激活自我效能感连续介导的(β=.80;P<.001) 和创伤应对自我效能 (β=.40; P <.001),预测 PTSD 症状减少 (β=-.20; P =.02)。结论:这项研究的结果可能为新兴的参与科学形式化提供坚实的基础。参与概念化包括可应用于其他应用程序的注意力、兴趣、情感和使用的一般测量。纵向研究模型支持 2 个基于理论的敬业度预测指标:敬业度自我效能和结果预期。共有 2 个特定任务的自我效能感——技能激活和创伤应对——被证明是参与和症状减轻之间的重要中介。总而言之,该模型可以应用于其他 DMHI 以了解参与度以及预测因素和作用机制。最终,这可能有助于改进参与性和有效的创伤恢复 DMHI 的设计和开发。
更新日期:2022-05-02
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