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<p>Digital health technologies (DHTs) such as wearables, smartphones, and connected devices have immense potential for supporting self-care in chronic disease management, yet engagement remains highly variable and is often measured by usage metrics alone. Guided by the AIM-ACT framework, this mixed-methods study examined how psychosocial and contextual factors shape DHT engagement among 146 adults with heart failure who completed a 6-month digital intervention involving multiple devices (ClinicalTrials.gov ID NCT05056129). Using k-medoids clustering of survey, ecological momentary assessment, and device-log data, we identified three distinct psychosocial phenotypes—<i>Challenged Survivors</i>, <i>Activated Learners</i>, <i>Engaged Self-Regulators</i>—reflecting differences in motivation, psychosocial resources, and interaction with DHTs. Qualitative interviews with 26 participants contextualized these phenotypes and revealed mechanisms linking psychosocial traits to DHT engagement quality. Findings underscore the value of psychosocial phenotyping for understanding heterogeneity in DHT engagement to inform the design of adaptive and equitable digital interventions that remain effective as they scale across diverse populations.</p>

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Developing psychosocial phenotypes to understand engagement with digital health technologies for heart failure

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月4日

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  • Rachel Tunis,
  • Namuun Clifford,
  • Emily West,
  • Elizabeth Heitkemper,
  • Marissa Burgermaster,
  • Kavita Radhakrishnan

摘要

Digital health technologies (DHTs) such as wearables, smartphones, and connected devices have immense potential for supporting self-care in chronic disease management, yet engagement remains highly variable and is often measured by usage metrics alone. Guided by the AIM-ACT framework, this mixed-methods study examined how psychosocial and contextual factors shape DHT engagement among 146 adults with heart failure who completed a 6-month digital intervention involving multiple devices (ClinicalTrials.gov ID NCT05056129). Using k-medoids clustering of survey, ecological momentary assessment, and device-log data, we identified three distinct psychosocial phenotypes—Challenged Survivors, Activated Learners, Engaged Self-Regulators—reflecting differences in motivation, psychosocial resources, and interaction with DHTs. Qualitative interviews with 26 participants contextualized these phenotypes and revealed mechanisms linking psychosocial traits to DHT engagement quality. Findings underscore the value of psychosocial phenotyping for understanding heterogeneity in DHT engagement to inform the design of adaptive and equitable digital interventions that remain effective as they scale across diverse populations.