ArticleJMIR mHealth and uHealth2020
Drivers of Mobile Health Acceptance and Use From the Patient Perspective: Survey Study and Quantitative Model Development.
Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Getting Connected to M-Health Technologies through a Meta-Analysis.International journal of environmental research and public health · 2023Pooled it
- Sociotechnical Factors Affecting Patients' Adoption of Mobile Health Tools: Systematic Literature Review and Narrative Synthesis.JMIR mHealth and uHealth · 2022Pooled it
- Acceptance, Perceived Usefulness, and Data Sharing in Mobile Health Apps Among Patients With Breast Cancer: Cross-Sectional Survey Study.JMIR cancer · 2026Article
- Article
- Patient and Clinician Attitudes Toward Mobile Health Apps: Qualitative Study.JMIR mHealth and uHealth · 2026Article
- Why health apps fail: the role of smartphone proficiency in mHealth resistance.Frontiers in public health · 2026Article
- User acceptance of telerehabilitation in Germany: a structural equation modeling approach based on the UTAUT2 model.Frontiers in digital health · 2026Article
- Exploring the Association Between Behavioral Determinants and Intention to Use a Chatbot-Led Parenting Intervention by Caregivers of Adolescent Girls in South Africa: Cross-Sectional Study.JMIR pediatrics and parenting · 2025Article
- Factors influencing the adoption of telemedicine services among middle-aged and older patients with chronic conditions in rural China: a multicentre cross-sectional study.BMC health services research · 2025Article
- Perception of recurrence risk in patients with IgG4-related disease: a descriptive phenomenological study.Rheumatology advances in practice · 2025Article
- Usage Behaviour and Adoption Criteria for Mobile Health Solutions in Patients with Chronic Diseases in Gastroenterology.Visceral medicine · 2024Article
- The Association of eHealth Literacy Skills and mHealth Application Use Among US Adults With Obesity: Analysis of Health Information National Trends Survey Data.JMIR mHealth and uHealth · 2024Article
- Acceptance of smart sensing, its determinants, and the efficacy of an acceptance-facilitating intervention in people with diabetes: results from a randomized controlled trial.Frontiers in digital health · 2024Article
- Intentions of Patients With Cancer and Their Relatives to Use a Live Chat on Familial Cancer Risk: Results From a Cross-Sectional Web-Based Survey.Journal of medical Internet research · 2023Article
- Predicting Habitual Use of Wearable Health Devices Among Middle-aged Individuals With Metabolic Syndrome Risk Factors in South Korea: Cross-sectional Study.JMIR formative research · 2023Article
- Patient Acceptance of Prescribed and Fully Reimbursed mHealth Apps in Germany: An UTAUT2-based Online Survey Study.Journal of medical systems · 2023Article
- Acceptance of smart sensing: a barrier to implementation-results from a randomized controlled trial.Frontiers in digital health · 2023Article
- Development of mobile health-based interventions to promote physical activity in patients with head and neck cancer: a qualitative study.Frontiers in public health · 2023Article
- Article
- Perceptions and Attitudes Toward an Interactive Voice Response Tool (Call for Life Uganda) Providing Adherence Support and Health Information to HIV-Positive Ugandans: Qualitative Study.JMIR formative research · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile health (mHealth) has potential to play a significant role in realizing a reversal of the current paradigm in health care toward a more patient-centric and more collaborative system to improve the outcomes obtained along with the quality and sustainability of health care systems.
objectiveThe aim of this study was to explore and understand individual mHealth acceptance drivers between two groups of users: those with chronic health conditions and those without.
methodsThe extended unified theory of acceptance and usage of technology (UTAUT2) was enhanced with a new health-related framework: behavior intention to recommend and new mediation effects. We applied partial least squares (PLS) causal modeling to test the research model.
resultsWe obtained 322 valid responses through an online questionnaire. The drivers of behavior intention with statistical significance were performance expectancy (β=.29, P<.001), habit (β=.39, P<.001), and personal empowerment (β=.18, P=.01). The precursors of use behavior were habit (β= .47, P<.001) and personal empowerment (β=.17, P=.01). Behavior intention to recommend was significantly influenced by behavior intention (β=.58, P<.001) and personal empowerment (β=.26, P<.001). The model explained 66% of the total variance in behavior intention, 54% of the variance in use behavior, and 70% of the variance in behavior intention to recommend.
conclusionsOur study demonstrates a significant role of personal empowerment, as a second-order construct, in the mHealth acceptance context. The presence of a chronic health condition predicates an impact on acceptance of this technology.
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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.