Machine learning models in health prevention and promotion and labor productivity: A co-word analysis

Authors

  • Sergio Arturo Dominguez Miranda Universidad Panamericana
  • Roman Rodriguez Aguilar Universidad panamericana

DOI:

https://doi.org/10.47909/ijsmc.85

Keywords:

co-word analysis, research trends, bibliometrics, machine learning models, health prevention and promotion, labor productivity

Abstract

Objective: The objective of this article is to carry out a co-word study on the application of machine learning models in health prevention and promotion, and its effect on labor productivity.

Methodology: The analysis of the relevant literature on the proposed topic, identified in the last 15 years in Scopus, is considered. Articles, books, book chapters, editorials, conference papers and reviews refereed publications were considered. A thematic mapping analysis was performed using factor analysis and strategy diagrams to derive primary research approaches and identify frequent themes as well as thematic evolution.

Results: The results of this study show the selection of 87 relevant publications with an average annual growth rate of 23.25% in related production. The main machine learning algorithms used, the main research approaches and key authors, derived from the analysis of thematic maps, were identified.

Conclusions: This study emphasizes the importance of using co-word analysis to understand trends in research on the impact of health prevention and promotion on labor productivity. The potential benefits of using machine learning models to address this issue are highlighted and anticipated to guide future research focused on improvements in labor productivity through prevention and promotion of health.

Originality: The identification of the relationship between work productivity and health prevention and promotion through machine learning models is a relevant topic but little analyzed in recent literature. The analysis of co-words allows us to establish the reference point of the state of the art in this regard and future trends.

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Published

2024-04-07

How to Cite

Dominguez Miranda, S. A., & Rodriguez Aguilar , R. (2024). Machine learning models in health prevention and promotion and labor productivity: A co-word analysis. Iberoamerican Journal of Science Measurement and Communication, 4(1), 1–16. https://doi.org/10.47909/ijsmc.85

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Vol. 4 No. 1 (2024): Iberoamerican Journal of Science Measurement and Communication

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Original article

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Copyright (c) 2024 Sergio Arturo Dominguez Miranda, Roman Rodriguez Aguilar

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