Bibliometric Analysis of Global Research Trends on Digital Occupational Health Using Scopus Database

Er Rays, Youssef; Lequaddem, Hamid Ait; Ezzahiri, Mustapha

doi:10.1007/978-3-031-52388-5_1

Lecture Notes in Networks and Systems

2024

DOI: 10.1007/978-3-031-52388-5_1

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Bibliometric Analysis of Global Research Trends on Digital Occupational Health Using Scopus Database

Youssef Er Rays,

Hamid Ait Lequaddem,

Mustapha Ezzahiri

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2024

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Cited by 2 publications

References 11 publications

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Mapping Global Research Trends in Digital Occupational Health: A Bibliometric Analysis Utilizing the Scopus Database

Er-Rays,

M’dioud,

Lemqeddem

2024

Preprint

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The 2019 health crisis has underscored the imperative role of information and communications technology (ICT) in bolstering employees' health, well-being, and ameliorating health risks associated with artificial intelligence (AI) errors. Digital health technology facilitates remote healthcare delivery, employee health monitoring, and enhanced communication channels between workers and healthcare professionals. This paper conducts a comprehensive analysis of global trends in digital occupational health research over the past decade, with a specific focus on prolific authors, countries, academic institutions, and publications. Leveraging the PRISMA framework and VOSviewer software, relevant documents are extracted from the Scopus database. The findings underscore the significance of digital technology in the realm of occupational health and highlight the pressing need for further investigation, particularly encompassing emerging economies and employing robust methodologies to ensure the reliability of results. This study offers a valuable assessment of advancements in digital occupational health, serving as a foundation for future research endeavors aimed at optimizing workplace health and well-being on a global scale.

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Mapping Global Research Trends in Digital Occupational Health: A Bibliometric Analysis Utilizing the Scopus Database

Er-Rays,

M’dioud,

Lemqeddem

2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Analyzing the Efficiency of Moroccan Hospital Network Regions via DEA and Tobit Regression: Assessing DEAP 2.1 Software versus Generative AI ChatGPT 3.5

Er-Rays,

M'dioud

2024

Preprint

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This study aims to assess the technical efficiency of hospital networks in each health directorate region in Morocco and analyze the impact of staff personnel health on inefficiency. The study uses Data Envelopment Analysis Programming (DEAP) software version 2.1 and generative Artificial Intelligent ChatGPT 3.5 to analyze 12 hospital network health directorate regions. Tobit regression was employed to analyze the impact of worker health and hospital activity on inefficiency. Results showed that the average technical efficiency was more inefficient in generative AI ChatGPT 3.5 than in DEAP software version 2.1. Hospital activity and nurse staffing significantly impacted inefficiency levels. The study concludes that inefficiency in hospital networks and staff personnel health pose challenges for managers in health directorate regions, emphasizing the need for New Public Management principles based on contractualization, accountability, and managerial practices.

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Bibliometric Analysis of Global Research Trends on Digital Occupational Health Using Scopus Database

Cited by 2 publications

References 11 publications

Mapping Global Research Trends in Digital Occupational Health: A Bibliometric Analysis Utilizing the Scopus Database

Mapping Global Research Trends in Digital Occupational Health: A Bibliometric Analysis Utilizing the Scopus Database

Analyzing the Efficiency of Moroccan Hospital Network Regions via DEA and Tobit Regression: Assessing DEAP 2.1 Software versus Generative AI ChatGPT 3.5

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