Predictors of Engagement in a Virtual Support Intervention for Caregivers of Adults With Heart Failure: An Explanatory Sequential Mixed Methods Study

影响心力衰竭成人患者照护者参与虚拟支持干预的预测因素:一项解释性序贯混合方法研究

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Abstract

BACKGROUND: Ensuring that consumers are active partners in their personal healthcare is an important goal. We developed and tested a 10-session virtual self-care intervention delivered by health coaches (Virtual Caregiver Coach for You) to informal caregivers of patients with heart failure. Trial results were promising, yet caregivers were not uniformly engaged in the intervention. The aim of this study was to explore factors associated with intervention engagement. METHODS: This explanatory sequential mixed methods study was conducted in 3 steps. First, quantitative data on sociodemographic characteristics, caregiving, stress, burden, coping, and treatment credibility and expectancy were analyzed with respect to the number of completed sessions. We used multivariable logistic regression to identify salient predictors of intervention engagement operationalized as completing ≥ 8 of the 10 sessions. Then, 24 caregivers were interviewed to explore personal, intrapersonal, interpersonal, and situational factors associated with intervention engagement. Transcribed interviews were analyzed using content analysis and integrated with the quantitative data in step 3. RESULTS: Race (Black or other people of color), insufficient income, being a parent or grandparent caregiver, and a high number of daily caregiving hours reduced the odds of completing 8 or more sessions, while perceived intervention credibility increased the odds of completing the sessions. Interviews revealed 3 themes explaining the completion of relatively fewer sessions: (1) challenges with life balance, (2) practical day-to-day issues, and 3) not understanding the intervention. CONCLUSIONS: Major variables influencing the engagement of heart failure caregivers in this supportive self-care intervention were identified. Accounting for these issues in intervention design and refinement may promote engagement in support programs by the very populations who need such interventions the most.

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