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Adoption barriers and facilitators of wearable health devices with AI integration: a patient-centred perspective.

作者信息

Alzghaibi Haitham

机构信息

Department of Health Informatics, College of Applied Medical Sciences, Qassim University, Buraydah, Saudi Arabia.

出版信息

Front Med (Lausanne). 2025 Apr 3;12:1557054. doi: 10.3389/fmed.2025.1557054. eCollection 2025.


DOI:10.3389/fmed.2025.1557054
PMID:40248075
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12003395/
Abstract

INTRODUCTION: Wearable devices that incorporate artificial intelligence (AI) have revolutionised healthcare through continuous monitoring, early detection, and tailored management of chronic diseases. METHODS: This cross-sectional study analysed patients' perceptions, trust, and awareness of AI-driven wearable health technologies, emphasising the identification of primary facilitators and barriers to adoption. A total of 455 participants, comprising individuals with chronic conditions, were recruited through convenience and stratified sampling methods. Data were collected via an online questionnaire that included demographic questions, Likert-scale items, and multiple-choice questions to evaluate awareness of particular AI features and the functionalities of wearable devices. RESULTS AND DISCUSSION: The findings indicated predominantly positive perceptions, with most participants concurring that wearable devices improve proactive care, facilitate remote consultations, and deliver precise health insights. Concerns regarding technical failures, data accuracy, and the potential reduction of human interaction were significant. No notable demographic differences were identified; however, participants with chronic conditions expressed more favourable perceptions. The research emphasises the necessity of user education, technical reliability, and professional oversight for the successful integration of AI-powered wearables in the management of chronic diseases.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/6c7fbbf15046/fmed-12-1557054-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/ef15365d8e43/fmed-12-1557054-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/74041aec7f53/fmed-12-1557054-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/1e688225f136/fmed-12-1557054-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/33f5ec71bfdf/fmed-12-1557054-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/d611c7b38774/fmed-12-1557054-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/6c7fbbf15046/fmed-12-1557054-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/ef15365d8e43/fmed-12-1557054-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/74041aec7f53/fmed-12-1557054-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/1e688225f136/fmed-12-1557054-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/33f5ec71bfdf/fmed-12-1557054-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/d611c7b38774/fmed-12-1557054-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ad9/12003395/6c7fbbf15046/fmed-12-1557054-g006.jpg

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Adoption barriers and facilitators of wearable health devices with AI integration: a patient-centred perspective.

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本文引用的文献

[1]
Beyond the Pain Management Clinic: The Role of AI-Integrated Remote Patient Monitoring in Chronic Disease Management - A Narrative Review.

J Pain Res. 2024-12-11

[2]
Advances in Wearable Biosensors for Healthcare: Current Trends, Applications, and Future Perspectives.

Biosensors (Basel). 2024-11-18

[3]
The Role of Wearable Devices in Chronic Disease Monitoring and Patient Care: A Comprehensive Review.

Cureus. 2024-9-8

[4]
Characteristics and Attitudes of Wearable Device Users and Nonusers in a Large Health Care System.

J Am Heart Assoc. 2024-1-2

[5]
Shaping the future of chronic disease management: Insights into patient needs for AI-based homecare systems.

Int J Med Inform. 2024-1

[6]
Machine Learning and Medication Adherence: Scoping Review.

JMIRx Med. 2021-11-24

[7]
Electrocardiogram Monitoring Wearable Devices and Artificial-Intelligence-Enabled Diagnostic Capabilities: A Review.

Sensors (Basel). 2023-5-16

[8]
The Influence of Wearables on Health Care Outcomes in Chronic Disease: Systematic Review.

J Med Internet Res. 2022-7-1

[9]
Machine Learning for Healthcare Wearable Devices: The Big Picture.

J Healthc Eng. 2022

[10]
Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review.

JMIR Mhealth Uhealth. 2022-3-10

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