ArticleDigital health
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Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Effects of Peer- or Professional-Led Support in Enhancing Adherence to Wearable Monitoring Devices Among Community-Dwelling Older Adults: Systematic Review of Randomized Controlled Trials.Journal of medical Internet research · 2024Pooled it
- Perceptions of care home residents, families and staff about wearable devices: a scoping review.European geriatric medicine · 2026Article
- Lived Experiences of Older Adults Using Wearables With Real-Time Feedback: Phenomenological Study.JMIR mHealth and uHealth · 2026Article
- "It's like a toxic relationship": Examining internal conflict experienced in wearable activity tracker users.PLOS digital health · 2026Article
- User Perceptions of Wearability of Knitted Sensor Garments for Long-Term Monitoring of Breathing Health: Thematic Analysis of Focus Groups and a Questionnaire Survey.JMIR biomedical engineering · 2024Article
- Young Adults Journey with Digital Fitness Tools-A Qualitative Study on Use of Fitness Tracking Device.F1000Research · 2024Article
- Ladders to better health? Identifying the cognitive pathways and barriers to value attainment in wearable health device usage.Digital healthArticle
- Distal and proximal factors of wearable users' quantified-self dependence: A cognitive-behavioral model.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveWearable activity trackers hold potential as a research tool to increase physical activity. However, long-term wearable adherence is low among users, which may be due to the limited understanding of the factors related to use and relation to health behavior theory. The purpose of this study was to qualitatively explore the perceptions of wearables among active adult users and non-users. Findings will inform potential barriers and facilitators for the adherence and adoption of wearables through the application of the Self-Determination Theory.
methodsSix focus groups were conducted and equally stratified to wearable users (
resultsFor users, the wearables' feedback provided them with validation, a sense of achievement, and other-determined motivation. Users appreciated the functionality of wearables, particularly with simpler and newer models. They also reported improvements in health behaviors
conclusionsFindings show that while both adult users and non-users held positive perceptions of wearables and concerns for feelings of guilt and dependency, widespread adoption and adherence may be prevented by differences in motivation for physical activity and concerns for cost, materialism, and functionality.
Indexed as
Identifiers
What OpenQuestion holds
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.