ArticleJMIR aging2023
Factors Influencing Continued Wearable Device Use in Older Adult Populations: Quantitative Study.
Article in JMIR aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Emerging technologies and vulnerabilities in older adults with cognitive impairments: a systematic review of qualitative evidence.BMC geriatrics · 2026Pooled it
- Interactive interfaces and wearable technologies for enhancing health management among older adults: a systematic review.Frontiers in medicine · 2025Pooled it
- Accelerated Brain Aging Identifies Functional Vulnerability Beyond Chronological Age in Multiple Sclerosis.Sensors (Basel, Switzerland) · 2026Trial
- Personalized nutrition interventions using digital technologies for older adults: a scoping review.Clinical nutrition research · 2026Article
- Article
- Strategic Management of Design and Conceptualization Factors for Wearable Postural Rehabilitation Devices: A Causal Interdependency Analysis.Biomimetics (Basel, Switzerland) · 2026Article
- Spontaneous speech enables scalable digital phenotyping of physical functional deficits in aging.npj aging · 2026Article
- Design Requirements for Gamified Exercise Apps for Adults With Prehypertension Based on the Octalysis Framework and Self-Determination Theory: Qualitative Interview Study.JMIR serious games · 2026Article
- Emerging Technologies and Vulnerabilities in Older Adults Without Cognitive Impairments: Systematic Review of Qualitative Evidence.Interactive journal of medical research · 2026Review
- Predicting first falls among older adults with chronic conditions and polypharmacy using routinely collected health records.Frontiers in artificial intelligence · 2026Article
- Monitoring the Residual Limb-Socket Interface: A Perspective on Clinical Needs and Challenges.Biomedical materials & devices (New York, N.Y.) · 2025Article
- Smart Healthcare at Home: A Review of AI-Enabled Wearables and Diagnostics Through the Lens of the Pi-CON Methodology.Sensors (Basel, Switzerland) · 2025Review
- Classifying Adverse Events from SOAP Notes and Sensor Features in a Clinical Trial of Older Adults.medRxiv : the preprint server for health sciences · 2025Article
- Developing an ecosystem of advanced digital services for healthy ageing by a co-creation methodology: preliminary results of the AGAPE project.Journal of public health research · 2025Article
- Wearable Technologies for Health Promotion and Disease Prevention in Older Adults: Systematic Scoping Review and Evidence Map.Journal of medical Internet research · 2025Article
- Surface Electromyography Combined with Artificial Intelligence in Predicting Neuromuscular Falls in the Elderly: A Narrative Review of Present Applications and Future Perspectives.Healthcare (Basel, Switzerland) · 2025Review
- Unraveling the triad of immunotherapy, tumor microenvironment, and skeletal muscle biomechanics in oncology.Frontiers in immunology · 2025Review
- A study on the relationship between technological affordance of age-appropriate smart wearable devices and the well-being of older adults.Frontiers in public health · 2025Article
- The acceptability of wearable devices for promoting adolescent mental wellbeing: A systematic review.Digital healthReview
- IoT-MT: Connected Care System For Elderly Anxiety Management Via Music Therapy.Healthcare technology lettersArticle
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe increased use of wearable sensor technology has highlighted the potential for remote telehealth services such as rehabilitation. Telehealth services incorporating wearable sensors are most likely to appeal to the older adult population in remote and rural areas, who may struggle with long commutes to clinics. However, the usability of such systems often discourages patients from adopting these services.
objectiveThis study aimed to understand the usability factors that most influence whether an older adult will decide to continue using a wearable device.
methodsOlder adults across 4 different regions (Northern Ireland, Ireland, Sweden, and Finland) wore an activity tracker for 7 days under a free-living environment protocol. In total, 4 surveys were administered, and biometrics were measured by the researchers before the trial began. At the end of the trial period, the researchers administered 2 further surveys to gain insights into the perceived usability of the wearable device. These were the standardized System Usability Scale (SUS) and a custom usability questionnaire designed by the research team. Statistical analyses were performed to identify the key factors that affect participants' intention to continue using the wearable device in the future. Machine learning classifiers were used to provide an early prediction of the intention to continue using the wearable device.
resultsThe study was conducted with older adult volunteers (N=65; mean age 70.52, SD 5.65 years) wearing a Xiaomi Mi Band 3 activity tracker for 7 days in a free-living environment. The results from the SUS survey showed no notable difference in perceived system usability regardless of region, sex, or age, eliminating the notion that usability perception differs based on geographical location, sex, or deviation in participants' age. There was also no statistically significant difference in SUS score between participants who had previously owned a wearable device and those who wore 1 or 2 devices during the trial. The bespoke usability questionnaire determined that the 2 most important factors that influenced an intention to continue device use in an older adult cohort were device comfort (τ=0.34) and whether the device was fit for purpose (τ=0.34). A computational model providing an early identifier of intention to continue device use was developed using these 2 features. Random forest classifiers were shown to provide the highest predictive performance (80% accuracy). After including the top 8 ranked questions from the bespoke questionnaire as features of our model, the accuracy increased to 88%.
conclusionsThis study concludes that comfort and accuracy are the 2 main influencing factors in sustaining wearable device use. This study suggests that the reported factors influencing usability are transferable to other wearable sensor systems. Future work will aim to test this hypothesis using the same methodology on a cohort using other wearable technologies.
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