ArticleInternational journal of environmental research and public health2023
The Intersection of Health Literacy and Public Health: A Machine Learning-Enhanced Bibliometric Investigation.
Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Influence of physical exercise on health improvement in older adult cancer patients: a systematic review.Frontiers in public health · 2025Pooled it
- Mapping the Landscape of Environmental Health Literacy: Trends, Gaps, and Future Directions.International journal of environmental research and public health · 2026Review
- Public Telemedicine Policy in Brazilian Unified Health System: An Impact Analysis.International journal of environmental research and public health · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent decades, health literacy has garnered increasing attention alongside a variety of public health topics. This study aims to explore trends in this area through a bibliometric analysis. A Random Forest Model was utilized to identify keywords and other metadata that predict average citations in the field. To supplement this machine learning analysis, we have also implemented a bibliometric review of the corpus. Our findings reveal significant positive coefficients for the keywords "COVID-19" and "Male", underscoring the influence of the pandemic and potential gender-related factors in the literature. On the other hand, the keyword "Female" showed a negative coefficient, hinting at possible disparities that warrant further investigation. Additionally, evolving themes such as COVID-19, mental health, and social media were discovered. A significant change was observed in the main publishing journals, while the major contributing authors remained the same. The results hint at the influence of the COVID-19 pandemic and a significant association between gender-related keywords on citation likelihood, as well as changing publication strategies, despite the fact that the main researchers remain those who have been studying health literacy since its creation.
Indexed as
Identifiers
What OpenQuestion holds
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.