ArticleMayo Clinic proceedings. Innovations, quality & outcomes2025
Mapping the Process of Engagement With Digital Health Interventions: A Cross-Case Synthesis.
Article in Mayo Clinic proceedings. Innovations, quality & outcomes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Clinical Investigation of an Autonomous Phone Conversational Agent for Cataract Surgery Follow-up
Acceptability and Usability of a Mobile Health App for Family Obesity Prevention and Management: A Mixed-methods Feasibility Study
Real World Testing of an Artificial Intelligence-enabled App as an Early Intervention and Support Tool in the Mental Health Referral Care Pathway
Who cites it
2 citing papers in PubMed.
- Digital health interventions for psychological outcomes among adolescents and young adults with cancer: a systematic review and meta-analysis.NPJ digital medicine · 2026Article
- Achieving clinically meaningful outcomes in digital health: a six-step, cyclical precision engagement framework (ENGAGE).Frontiers in digital health · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To map the associations between affective, cognitive, and behavioral components of engagement with digital health interventions to provide a framework to improve intervention design, evaluation, and impact. Patients and Methods: An exploratory multiple case study examined 3 studies evaluating a childhood obesity mobile application (NoObesity, data collection: from September 15, 2020 to June 23, 2021), a mental health conversational agent mobile application (Wysa, data collection: from December 13, 2022 to July 31, 2023), and a telephone-delivered conversational agent postsurgical assessment (Dora R1, data collection: from September 17, 2021 to January 31, 2022). Qualitative data from semi-structured interviews (NoObesity: n=15, Wysa: n=4, and Dora R1: n=20) was analyzed using a codebook thematic analysis approach to generate models mapping engagement. A cross-case analysis compared the 3 models with a hypothesized model. Results: The case studies highlighted close associations between affective, cognitive, and behavioral components throughout the engagement process. Similar patterns of engagement were generated from the case studies, but these patterns differed from the literature-based hypothesized model in the order of influence of cognitive and affective engagement. Conclusion: Understanding how different components of engagement interact is essential for designing interventions that mitigate barriers to engagement and maximize intervention impact. The framework provides a preliminary guide and recommendations for how to support particular components. Future research on the order of cognitive and affective components (or importance thereof) and testing the influence of particular features on engagement components could improve the framework and clinical impact. Trial Registration: clinicaltrials.gov Identifier: NoObesity: NCT05261555; Wysa: NCT05533190; Dora R1: NCT05213390.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.