ArticleInternational Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare2020
Understanding Participant Needs for Engagement and Attitudes towards Passive Sensing in Remote Digital Health Studies.
Article in International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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
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Who cites it
12 citing papers in PubMed, 42 citations in OpenAlex.
- "I had eyes on me to help me": a qualitative descriptive study on trust in passive monitoring systems among older adults with mild cognitive impairment.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- Testing the feasibility of passive sensing among adolescents: Implications for mental health.Journal of psychopathology and clinical science · 2025Article
- Long-Term Engagement of Diverse Study Cohorts in Decentralized Research: Longitudinal Analysis of "All of Us" Research Program Data.Interactive journal of medical research · 2025Article
- Participant Contributions to Person-Generated Health Data Research Using Mobile Devices: Scoping Review.Journal of medical Internet research · 2025Article
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- Multilevel Determinants of Digital Health Equity: A Literature Synthesis to Advance the Field.Annual review of public health · 2023Review
- Enrollment and Retention of Participants in Remote Digital Health Studies: Scoping Review and Framework Proposal.Journal of medical Internet research · 2022Article
- Clinical Targets and Attitudes Toward Implementing Digital Health Tools for Remote Measurement in Treatment for Depression: Focus Groups With Patients and Clinicians.JMIR mental health · 2022Article
- Participant retention in a fully remote trial of digital psychotherapy: Comparison of incentive types.Frontiers in digital health · 2022Article
- Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care.Frontiers in psychiatry · 2021Article
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Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Digital psychiatry is a rapidly growing area of research. Mobile assessment, including passive sensing, could improve research into human behavior and may afford opportunities for rapid treatment delivery. However, retention is poor in remote studies of depressed populations in which frequent assessment and passive monitoring are required. To improve engagement and understanding participant needs overall, we conducted semi-structured interviews with 20 people representative of a depressed population in a major metropolitan area. These interviews elicited feedback on strategies for long-term remote research engagement and attitudes towards passive data collection. Our results found participants were uncomfortable sharing vocal samples, need researchers to take a more active role in supporting their understanding of passive data collection, and wanted more transparency on how data were to be used in research. Despite these findings, participants trusted researchers with the collection of passive data. They further indicated that long term study retention could be improved with feedback and return of information based on the collected data. We suggest that researchers consider a more educational consent process, giving participants a choice about the types of data they share in the design of digital health apps, and consider supporting feedback in the design to improve engagement.
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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.