ArticleJournal of medical Internet research2019
Factors Affecting Patients' Use of Electronic Personal Health Records in England: Cross-Sectional Study.
Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 55 citations in OpenAlex.
- The Impact of Digital Patient Portals on Health Outcomes, System Efficiency, and Patient Attitudes: Updated Systematic Literature Review.Journal of medical Internet research · 2021Pooled it
- Functionalities and Issues in the Implementation of Personal Health Records: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Affordance Types and Their Determinants in Patient Mobile Health Portals Use: An Empirical Investigation.Journal of medical Internet research · 2025Article
- Patient Adoption of Digital Use Cases in Family Medicine and a Nuanced Implementation Approach for Family Doctors: Quantitative Web-Based Survey Study.JMIR formative research · 2025Article
- Consumer perspectives on the national electronic health record and barriers to its adoption in Germany: does health policy require a change in communication?BMC health services research · 2025Observational
- Intention to use personal health records and associated factors among healthcare providers in southwest Oromia region referral hospitals, Ethiopia: using the modified unified theory of acceptance and use technology 2 model.Frontiers in digital health · 2025Article
- Knowledge, Attitudes, and Practices about Electronic Personal Health Records: A Cross-Sectional Study in a Region of Northern Italy.Journal of medical systems · 2024Article
- Intention to use personal health record system and its predictors among chronic patients enrolled at public hospitals in Bahir Dar city, northwest Ethiopia: using modified UTAUT2 model.Frontiers in medicine · 2024Article
- Integrated personal health record (PHR) security: requirements and mechanisms.BMC medical informatics and decision making · 2023Review
- Early Adopters of Apple Health Records at a Large Academic Medical Center: Cross-sectional Survey of Users.Journal of medical Internet research · 2022Article
- Exploring the COVID-19 Pandemic as a Catalyst for Behavior Change Among Patient Health Record App Users in Taiwan: Development and Usability Study.Journal of medical Internet research · 2022Article
- Predicting Health Care Providers' Acceptance of a Personal Health Record Secure Messaging Feature.Applied clinical informatics · 2022Article
- Human-Technology Interaction Factors Associated With the Use of Electronic Personal Health Records Among Younger and Older Adults: Secondary Data Analysis.Journal of medical Internet research · 2021Article
- Health Care Providers' Acceptance of a Personal Health Record: Cross-sectional Study.Journal of medical Internet research · 2021Article
- Sociotechnical Drivers and Barriers in the Consumer Adoption of Personal Health Records: Empirical Investigation.JMIR medical informatics · 2021Article
- A Technology Acceptance Model for Deploying Masks to Combat the COVID-19 Pandemic in Taiwan (My Health Bank): Web-Based Cross-sectional Survey Study.Journal of medical Internet research · 2021Article
- Patients' Perspectives About Factors Affecting Their Use of Electronic Personal Health Records in England: Qualitative Analysis.Journal of medical Internet research · 2021Article
- Patients' Adoption of Electronic Personal Health Records in England: Secondary Data Analysis.Journal of medical Internet research · 2020Article
- Integrating People, Context, and Technology in the Implementation of a Web-Based Intervention in Forensic Mental Health Care: Mixed-Methods Study.Journal of medical Internet research · 2020Article
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Corrections and comments
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Authors and funding
4 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundElectronic personal health records (ePHRs) are secure Web-based tools that enable individuals to access, manage, and share their medical records. England recently introduced a nationwide ePHR called Patient Online. As with ePHRs in other countries, adoption rates of Patient Online remain low. Understanding factors affecting patients' ePHR use is important to increase adoption rates and improve the implementation success of ePHRs.
objectiveThis study aimed to examine factors associated with patients' use of ePHRs in England.
methodsThe unified theory of acceptance and use of technology was adapted to the use of ePHRs. To empirically examine the adapted model, a cross-sectional survey of a convenience sample was carried out in 4 general practices in West Yorkshire, England. Factors associated with the use of ePHRs were explored using structural equation modeling.
resultsOf 800 eligible patients invited to take part in the survey, 624 (78.0%) returned a valid questionnaire. Behavioral intention (BI) was significantly influenced by performance expectancy (PE; beta=.57, P<.001), effort expectancy (EE; beta=.16, P<.001), and perceived privacy and security (PPS; beta=.24, P<.001). The path from social influence to BI was not significant (beta=.03, P=.18). Facilitating conditions (FC) and BI significantly influenced use behavior (UB; beta=.25, P<.001 and beta=.53, P<.001, respectively). PE significantly mediated the effect of EE and PPS on BI (beta=.19, P<.001 and beta=.28, P=.001, respectively). Age significantly moderated 3 paths: PE→BI, EE→BI, and FC→UB. Sex significantly moderated only the relationship between PE and BI. A total of 2 paths were significantly moderated by education and internet access: EE→BI and FC→UB. Income moderated the relationship between FC and UB. The adapted model accounted for 51% of the variance in PE, 76% of the variance in BI, and 48% of the variance in UB.
conclusionsThis study identified the main factors that affect patients' use of ePHRs in England, which should be taken into account for the successful implementation of these systems. For example, developers of ePHRs should involve patients in the process of designing the system to consider functions and features that fit patients' preferences and skills to ensure systems are useful and easy to use. The proposed model accounted for 48% of the variance in UB, indicating the existence of other, as yet unidentified, factors that influence the adoption of ePHRs. Future studies should confirm the effect of the factors included in this model and identify additional factors.
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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 OpenQuestion graph.