ArticleJMIR mHealth and uHealth2019
Physical Activity Surveillance Through Smartphone Apps and Wearable Trackers: Examining the UK Potential for Nationally Representative Sampling.
Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
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
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
35 citing papers in PubMed, 2 syntheses or guidelines pooled it, 71 citations in OpenAlex.
- Inequalities in Exclusively Mobile Interventions Targeting Weight-Related Behaviors: Systematic Review of Observational Studies.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Pooled it
- Learning and Use of eHealth Among Older Adults Living at Home in Rural and Nonrural Settings: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation.The New England journal of medicine · 2019Trial
- Optimizing Usability of Digital Health Interventions for Nondigitally Native Adults: A Framework-Based Approach to Develop Just-in-Time Adaptive Interventions (JITAIs) and Other Adaptations.JMIR human factors · 2026Article
- Demographic and Socioeconomic Factors Associated with Fitbit Ownership in the NIHInternational journal of environmental research and public health · 2026Article
- Machine Learning and Arrhythmia: Advances in Atrial Fibrillation Detection and Management.Current atherosclerosis reports · 2025Review
- The use of consumer-grade physical activity monitors: Insight into psychosocial determinants and technology acceptance.Contemporary clinical trials communications · 2025Article
- Consumer Wearable Usage to Collect Health Data Among Adults Living in Germany: Nationwide Observational Survey Study.JMIR mHealth and uHealth · 2025Observational
- Feasibility of Wearable Digital Healthcare Devices Among Korean Male Seafarers: A Pilot Study.Healthcare (Basel, Switzerland) · 2025Article
- The Role of Wearable Devices in Chronic Disease Monitoring and Patient Care: A Comprehensive Review.Cureus · 2024Review
- Mapping Digital Public Health Interventions Among Existing Digital Technologies and Internet-Based Interventions to Maintain and Improve Population Health in Practice: Scoping Review.Journal of medical Internet research · 2024Article
- National digital strategies and innovative eHealth policies concerning older adults' dignity: a document analysis in three Scandinavian countries.BMC health services research · 2023Article
- Article
- Charting a Course for Smartphones and Wearables to Transform Population Health Research.Journal of medical Internet research · 2023Article
- Charting a course for smartphones and wearables to transform population health research.Journal of medical Internet research · 2023Article
- Initial Development of User-Based Quality Evaluation Questionnaire of Smartwatch Technology for Applying to Healthcare.Iranian journal of public health · 2023Article
- Technology engagement is associated with higher perceived physical well-being in stroke patients prescribed smartwatches for atrial fibrillation detection.Frontiers in digital health · 2023Article
- Remotely Conducted App-Based Intervention for Cardiovascular Disease and Diabetes Risk Awareness and Prevention: Single-Group Feasibility Trial.JMIR human factors · 2022Article
- Rating the Quality of Smartphone Apps Related to Shoulder Pain: Systematic Search and Evaluation Using the Mobile App Rating Scale.JMIR formative research · 2022Article
- Mapping Digital Public Health Interventions Among Existing Digital Technologies and Internet-Based Interventions to Maintain and Improve Population Health in Practice: Protocol for a Scoping Review.JMIR research protocols · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundSmartphones and wearable activity trackers present opportunities for large-scale physical activity (PA) surveillance that overcome some limitations of questionnaires or researcher-administered devices. However, it remains unknown whether current users of such technologies are representative of the UK population.
objectiveThe objective of this study was to investigate potential sociodemographic biases in individuals using, or with the potential to use, smartphone apps or wearable activity trackers for PA surveillance in the United Kingdom.
methodsWe used data of adults (aged ≥16 years) from two nationally representative surveys. Using the UK-wide 2018 Ofcom Technology Tracker (unweighted N=3688), we derived mutually adjusted odds ratios (ORs; 95% CI) of personal use or household ownership of a smartwatch or fitness tracker and personal use of a smartphone by age, sex, social grade, activity- or work-limiting disability, urban or rural, and home nation. Using the 2016 Health Survey for England (unweighted N=4539), we derived mutually adjusted ORs of the use of wearable trackers or websites or smartphone apps for weight management. The explanatory variables were age, sex, PA, deprivation, and body mass index (BMI). Furthermore, we stratified these analyses by BMI, as these questions were asked in the context of weight management.
resultsSmartphone use was the most prevalent of all technology outcomes, with 79.01% (weighted 2085/2639) of the Technology Tracker sample responding affirmatively. All other outcomes were <30% prevalent. Age ≥65 years was the strongest inverse correlate of all outcomes (eg, OR 0.03, 95% CI 0.02-0.05 for smartphone use compared with those aged 16-44 years). In addition, lower social grade and activity- or work-limiting disability were inversely associated with all Technology Tracker outcomes. Physical inactivity and male sex were inversely associated with both outcomes assessed in the Health Survey for England; higher levels of deprivation were only inversely associated with websites or phone apps used for weight management. The conclusions did not differ meaningfully in the BMI-stratified analyses, except for deprivation that showed stronger inverse associations with website or phone app use in the obese.
conclusionsThe sole use of PA data from wearable trackers or smartphone apps for UK national surveillance is premature, as those using these technologies are more active, younger, and more affluent than those who do not.
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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.