Paper Type
Complete
Abstract
User engagement (UE) is a critical determinant of the success of digital health interventions (DHIs), influencing user adherence, sustained participation, and health outcomes. However, inconsistencies in measuring UE, due to its multifaceted nature, pose significant challenges in DHI research. This narrative review synthesizes existing methods for measuring UE and categorizes them into three key dimensions: behavioral, cognitive, and emotional engagement. Common measurement approaches include self-report measures, cognitive measures (e.g., eye-tracking, EEG), and interaction-based measures (e.g., session duration, app usage logs), each with inherent strengths and limitations. To address these limitations, mixed-method approaches are recommended for comprehensive evaluations. Based on these findings, this review proposes an integrative framework that distinguishes between system engagement and intervention engagement and aligns UE dimensions with relevant measurement strategies and intervention goals. This framework provides a holistic approach to UE assessment, ensuring greater consistency in measurement and improving the evaluation of engagement in DHIs.
Paper Number
2192
Recommended Citation
Zhang, Lidan; Jewer, Jennifer; and Tulu, Bengisu, "Measuring User Engagement in Digital Health Interventions: A Narrative Review" (2025). AMCIS 2025 Proceedings. 17.
https://aisel.aisnet.org/amcis2025/health_it/sig_health/17
Measuring User Engagement in Digital Health Interventions: A Narrative Review
User engagement (UE) is a critical determinant of the success of digital health interventions (DHIs), influencing user adherence, sustained participation, and health outcomes. However, inconsistencies in measuring UE, due to its multifaceted nature, pose significant challenges in DHI research. This narrative review synthesizes existing methods for measuring UE and categorizes them into three key dimensions: behavioral, cognitive, and emotional engagement. Common measurement approaches include self-report measures, cognitive measures (e.g., eye-tracking, EEG), and interaction-based measures (e.g., session duration, app usage logs), each with inherent strengths and limitations. To address these limitations, mixed-method approaches are recommended for comprehensive evaluations. Based on these findings, this review proposes an integrative framework that distinguishes between system engagement and intervention engagement and aligns UE dimensions with relevant measurement strategies and intervention goals. This framework provides a holistic approach to UE assessment, ensuring greater consistency in measurement and improving the evaluation of engagement in DHIs.
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