Damar, Muhammet, Pinto, Andrew David, Hosseini, Benita et al. (4 more authors) (2026) Trends in health literacy discussions within primary health care research: A topic analysis using machine learning techniques. Atencion Primaria. 103441. ISSN: 1578-1275
Abstract
Objective To reveal the intellectual framework, research trends, and gaps, and evaluate effective health literacy tools in the field of primary healthcare services. Design Observational, machine learning-based bibliometric study. Site Analysis was conducted using records indexed in the Web of Science database. Participants A total of 1869 researchers from 823 institutions across 54 countries contributed to the 33 journals included in the dataset. Interventions Development of a bibliometric map and topic model in health literacy within primary healthcare. Bibliometric analysis was performed on review and research articles retrieved as of July 27, 2025. For each article, data on the journal, publication year, title, abstract, keywords, authors, affiliations, countries, cited sources, cited first authors, and references were collected. Latent Dirichlet Allocation topic modeling was applied to uncover thematic structures and trends in the research field. Main measurements Thematic structures, research trends, and knowledge gaps were measured through bibliometric indicators such as co-authorship networks, citation analysis, and topic modeling outputs. Results Emerging topics included health equity and sustainability, medication adherence, aging, management of lifestyle factors such as physical activity and diet, management of chronic diseases, physician-patient communication, sustainable learning, sociodemographic impact, rural health interventions, responses to pandemics akin to COVID-19, and the roles of health institutions, policymakers, and leadership. Conclusions Our findings highlight that health literacy is a multifaceted concept that not only enables healthier living and disease management but also prevents various severe health conditions, improving overall life quality and satisfaction with health services. The importance of sustained health literacy initiatives, effective communication, and the vested interests of both patients and healthcare professionals are highlighted, underscoring the need for ongoing commitment in this area.
Metadata
| Item Type: | Article |
|---|---|
| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2025 The Author(s). |
| Keywords: | Health care,Health literacy,Machine learning,Primary care,Text mining |
| Dates: |
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| Institution: | The University of York |
| Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
| Date Deposited: | 08 May 2026 14:10 |
| Last Modified: | 08 May 2026 14:10 |
| Published Version: | https://doi.org/10.1016/j.aprim.2025.103441 |
| Status: | Published |
| Refereed: | Yes |
| Identification Number: | 10.1016/j.aprim.2025.103441 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:240946 |
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Description: Trends in health literacy discussions within primary health care research: A topic analysis using machine learning techniques
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