ArticleJMIR medical education2023
Web-Based Learning for General Practitioners and Practice Nurses Regarding Behavior Change: Qualitative Descriptive Study.
Article in JMIR medical education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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
4 citing papers in PubMed, 7 citations in OpenAlex.
- Trial
- Primary Care Physicians' Interactions With a Novel Web-Based Active Learning Tool (The Community Fracture Capture Learning Hub): Qualitative Analysis.JMIR formative research · 2026Article
- Impact of Motivational Interviewing Education on General Practitioners' and Trainees' Learning and Diabetes Outcomes in Primary Care: Mixed Methods Study.JMIR medical education · 2025Article
- Factors related to feelings toward nursing practices for foreign pregnant and postpartum residents among midwives and nurses at perinatal medical centers in Osaka, Japan: A questionnaire survey.Global health & medicine · 2025Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSupporting patients to live well by optimizing behavior is a core tenet of primary health care. General practitioners and practice nurses experience barriers in providing behavior change interventions to patients for lifestyle behaviors, including low self-efficacy in their ability to enact change. Web-based learning technologies are readily available for general practitioners and practice nurses; however, opportunities to upskill in behavior change are still limited. Understanding what influences general practitioners' and practice nurses' adoption of web-based learning is crucial to enhancing the quality and impact of behavior change interventions in primary health care.
objectiveThis study aimed to explore general practitioners' and practice nurses' perceptions regarding web-based learning to support patients with behavior change.
methodsA qualitative, cross-sectional design was used involving web-based, semistructured interviews with general practitioners and practice nurses in Queensland, Australia. The interviews were recorded and transcribed using the built-in Microsoft Teams transcription software. Inductive coding was used to generate codes from the interview data for thematic analysis.
resultsIn total, there were 11 participants in this study, including general practitioners (n=4) and practice nurses (n=7). Three themes emerged from the data analysis: (1) reflecting on the provider of the Healthy Lifestyles suite; (2) valuing the web-based learning content and presentation; and (3) experiencing barriers and facilitators to using the Healthy Lifestyles suite.
conclusionsProvider reputation, awareness of availability, resources, content quality, usability, cost, and time influence adoption of web-based learning. Perceived quality is associated with culturally tailored information, resources, a balance of information and interactivity, plain language, user-friendly navigation, appealing visual presentation, communication examples, and simple models. Free web-based learning that features progress saving and module lengths of less than 2 hours alleviate perceived time and cost barriers. Learning providers may benefit by including these features in their future behavior change web-based learning for general practitioners and practice nurses.
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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.