ArticleHeliyon2023
Investigating the impact of artificial intelligence on human resource functions in the health sector of China: A mediated moderation model.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed.
- Is the Application of Artificial Intelligence-Based Competency Assessments for Selecting Clinical Nurses Acceptable? A Qualitative Study.The journal of nursing research : JNR · 2026Article
- Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach.MethodsX · 2025Article
- Article
- AI with agency: a vision for adaptive, efficient, and ethical healthcare.Frontiers in digital health · 2025Article
- Examining the influence of technological self-efficacy, perceived trust, security, and electronic word of mouth on ICT usage in the education sector.Scientific reports · 2024Article
- Article
- Effect of social influence, environmental awareness, and safety affordance on actual use of 5G technologies among Chinese students.Scientific reports · 2023Article
- Impact of gamification on green consumption behavior integrating technological awareness, motivation, enjoyment and virtual CSR.Scientific reports · 2023Article
- Identifying Measurement Dimensions of Users' Benefit-Risk Perceptions of AI in Healthcare: A Scoping Review.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is rapidly transforming the way human resources (HR) functions are carried out in the health sector of China. This study aims to scrutinize the impact of artificial intelligence on the human resource functions operating in the healthcare sector through technological awareness, social media influence, and personal innovativeness. Additionally, this study examines the moderating role of perceived risk between technological awareness and human resources functions. An online questionnaire was administered to human resources professionals in the health sector of China to gather data from 363 respondents. Partial least squares structural equation modeling (PLS-SEM), a statistical procedure, is implemented to investigate the hypothesis of the projected model of artificial intelligence and human resource functions. The research findings reveal that artificial intelligence significantly influences human resource functions through technological awareness, social media influence, and personal innovativeness. Furthermore, perceived risk significantly moderates the relationship between technological awareness and human resource functions. The findings of this study have important implications for HR practitioners and policymakers in the health sectors of China, who can leverage artificial intelligence technologies to optimize and improve organizational performance. However, its adoption needs to be carefully planned and managed to reap the full benefits of this transformative technology.
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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.