Evidence mapPaperPMID 40106231Full record

ArticleJMIR aging2025

Exploring Smart Health Wearable Adoption Among Singaporean Older Adults Based on Self-Determination Theory: Web-Based Survey Study.

Hyunjin Kang, Tingting Yang, Nazira Banu, Sheryl Wei Ting Ng, Jeong Kyu Lee

Abstract read
In one paragraph

Article in JMIR aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Identifying Measurement Dimensions of Users' Benefit-Risk Perceptions of AI in Healthcare: A Scoping Review.Inquiry : a journal of medical care organization, provision and financing
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hyunjin KangWee Kim Wee School of Communication and Information, Nanyang Technological University, 31 Nanyang Link, Singapore, 637718, Singapore, 65 6908-3431.ORCID http://orcid.org/0000-0002-8076-7126
Tingting YangWee Kim Wee School of Communication and Information, Nanyang Technological University, 31 Nanyang Link, Singapore, 637718, Singapore, 65 6908-3431.ORCID http://orcid.org/0000-0002-6808-7590
Nazira BanuWee Kim Wee School of Communication and Information, Nanyang Technological University, 31 Nanyang Link, Singapore, 637718, Singapore, 65 6908-3431.ORCID http://orcid.org/0009-0004-6415-2203
Sheryl Wei Ting NgWee Kim Wee School of Communication and Information, Nanyang Technological University, 31 Nanyang Link, Singapore, 637718, Singapore, 65 6908-3431.ORCID http://orcid.org/0009-0003-2711-3099
Jeong Kyu LeeDepartment of Health and Exercise Science, University of Oklahoma, Norman, OK, United States.ORCID http://orcid.org/0000-0001-5534-7640

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Smart health wearables offer significant benefits for older adults, enabling seamless health monitoring and personalized suggestions based on real-time data. Promoting adoption and sustained use among older adults is essential to empower autonomous health management, leading to better health outcomes, improved quality of life, and reduced strain on health care systems. Objective: This study investigates how autonomy-related contextual factors, including artificial intelligence (AI) anxiety, perceived privacy risks, and health consciousness, are related to older adults' psychological needs of competence, autonomy, and relatedness (RQ1). We then examined whether the fulfillment of these needs positively predicts older adults' intentions to adopt these devices (H1), and how they mediate the relationship between these factors and older adults' intentions to use smart health wearables (RQ2). Additionally, it compares experienced and nonexperienced older adult users regarding the influence of these psychological needs on use intentions (RQ3). Methods: A web-based survey was conducted with individuals aged 60 years and above in Singapore, using a Qualtrics survey panel. A total of 306 participants (177 male; mean age of 65.47 years, age range 60-85 years) completed the survey. A structural equation model was used to analyze associations among AI anxiety, perceived privacy risks, and health consciousness, and the mediating factors of competence, autonomy, and relatedness, as well as their relationship to smart health wearable use intention. Results: Health consciousness positively influenced all intrinsic motivation factors-competence, autonomy, and relatedness-while perceived privacy risks negatively affected all three. AI anxiety was negatively associated with competence only. Both privacy risk perceptions and health consciousness were indirectly linked to older adults' intentions to use smart health wearables through competence and relatedness. No significant differences were found in motivational structures between older adults with prior experience and those without. Conclusions: This study contributes to the application of self-determination theory in promoting the use of smart technology for health management among older adults. The results highlight the critical role of intrinsic motivation-particularly competence-in older adults' adoption of smart health wearables. While privacy concerns diminish motivation, health consciousness fosters it. The study results offer valuable implications for designing technologies that align with older adults' motivations, potentially benefiting aging populations in other technologically advanced societies. Developers should focus on intuitive design, transparent privacy practices, and social features to encourage adoption, empowering older adults to use smart wearables for proactive health management.

Indexed as

Personal AutonomyWearable Electronic DevicesAgedAged, 80 and overArtificial IntelligenceFemaleHumansInternetMaleMiddle AgedPrivacyQuality of LifeSingaporeSurveys and QuestionnairesAI anxietyhealth consciousnessperceived privacy riskself-determination theorysmart health wearables

Identifiers

PMID40106231
PMCPMC11939025

What Socratic holds

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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 Socratic graph.