ArticleJMIR mHealth and uHealth2017
Patients' Acceptance of Smartphone Health Technology for Chronic Disease Management: A Theoretical Model and Empirical Test.
Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 2 of them syntheses that pooled it.
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Who cites it
79 citing papers in PubMed, 2 syntheses or guidelines pooled it, 254 citations in OpenAlex.
- Improving Acceptability of mHealth Apps-The Use of the Technology Acceptance Model to Assess the Acceptability of mHealth Apps: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Theories Predicting End-User Acceptance of Telemedicine Use: Systematic Review.Journal of medical Internet research · 2019Pooled it
- Mobile Health App Acceptance in Japan's Aging Society: Multigroup Structural Equation Modeling Based on the Extended Unified Theory of Acceptance and Use of Technology and eHealth Literacy Frameworks.JMIR mHealth and uHealth · 2026Article
- Acceptance of Smart Contracts in Patients Receiving Primary Care: Exploratory Study.JMIR formative research · 2026Article
- Article
- Medication adherence barriers and digital support among Saudi adults with chronic conditions.Scientific reports · 2026Article
- Predictors of Acceptance of Smartphone Application among People with Hypertension in India: A Cross-Sectional Study.Wellcome open research · 2026Article
- How mental health status and attitudes toward mental health shape AI Acceptance in psychosocial care: a cross-sectional analysis.BMC psychology · 2025Article
- SEM model analysis of diabetic patients' acceptance of artificial intelligence for diabetic retinopathy.BMC medical informatics and decision making · 2025Article
- Understanding older adults' adoption of smart product-service systems for medication management in China: an extended UTAUT model approach.Frontiers in public health · 2025Article
- Understanding the Role of Technology Anxiety in the Adoption of Digital Health Technologies (DHTs) by Older Adults with Chronic Diseases in Shanghai: An Extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model.Healthcare (Basel, Switzerland) · 2024Article
- Technology acceptance model perspective on the intention to participate in medical talents training in China.Heliyon · 2024Article
- Patient experiences with patient-led, home-based follow-up after curative treatment for colorectal cancer: a qualitative study.BMJ open · 2024Article
- Factors influencing user's health information discernment abilities in online health communities: based on SEM and fsQCA.Frontiers in public health · 2024Article
- Individualised monitoring programme for pulmonary rehabilitation of patients with chronic obstructive pulmonary disease-study protocol for a randomised controlled trial.Journal of thoracic disease · 2023Article
- Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study.JMIR human factors · 2023Article
- Modelling the Predictors of Mobile Health (mHealth) Adoption among Healthcare Professionals in Low-Resource Environments.International journal of environmental research and public health · 2023Article
- Development of Automatic Portable Pathology Scanner and Its Evaluation for Clinical Practice.Journal of digital imaging · 2023Article
- Understanding Patient Beliefs in Using Technology to Manage Diabetes: Path Analysis Model From a National Web-Based Sample.JMIR diabetes · 2023Article
- Investigating Employees' Concerns and Wishes Regarding Digital Stress Management Interventions With Value Sensitive Design: Mixed Methods Study.Journal of medical Internet research · 2023Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChronic disease patients often face multiple challenges from difficult comorbidities. Smartphone health technology can be used to help them manage their conditions only if they accept and use the technology.
objectiveThe aim of this study was to develop and test a theoretical model to predict and explain the factors influencing patients' acceptance of smartphone health technology for chronic disease management.
methodsMultiple theories and factors that may influence patients' acceptance of smartphone health technology have been reviewed. A hybrid theoretical model was built based on the technology acceptance model, dual-factor model, health belief model, and the factors identified from interviews that might influence patients' acceptance of smartphone health technology for chronic disease management. Data were collected from patient questionnaire surveys and computer log records about 157 hypertensive patients' actual use of a smartphone health app. The partial least square method was used to test the theoretical model.
resultsThe model accounted for .412 of the variance in patients' intention to adopt the smartphone health technology. Intention to use accounted for .111 of the variance in actual use and had a significant weak relationship with the latter. Perceived ease of use was affected by patients' smartphone usage experience, relationship with doctor, and self-efficacy. Although without a significant effect on intention to use, perceived ease of use had a significant positive influence on perceived usefulness. Relationship with doctor and perceived health threat had significant positive effects on perceived usefulness, countering the negative influence of resistance to change. Perceived usefulness, perceived health threat, and resistance to change significantly predicted patients' intentions to use the technology. Age and gender had no significant influence on patients' acceptance of smartphone technology. The study also confirmed the positive relationship between intention to use and actual use of smartphone health apps for chronic disease management.
conclusionsThis study developed a theoretical model to predict patients' acceptance of smartphone health technology for chronic disease management. Although resistance to change is a significant barrier to technology acceptance, careful management of doctor-patient relationship, and raising patients' awareness of the negative effect of chronic disease can negate the effect of resistance and encourage acceptance and use of smartphone health technology to support chronic disease management for patients in the community.
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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.