ArticleInternational journal of environmental research and public health2022
Promoting Healthcare Workers' Adoption Intention of Artificial-Intelligence-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human-Computer Trust.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictors of Health Care Practitioners' Intention to Use AI-Enabled Clinical Decision Support Systems: Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology.Journal of medical Internet research · 2024Pooled it
- Determinants of the Public's Behavioral Intention to Adopt AI-Assisted Lung Cancer Screening: An Extended UTAUT Model Integrating Trust and Risk.Healthcare (Basel, Switzerland) · 2026Article
- Cross-domain neural collaborative filtering for personalized herbal prescription recommendation.Chinese medicine · 2026Article
- Psychological responses and cognitive mechanisms of university teachers in using generative AI in teaching: a configurational path analysis based on the MOA framework.Frontiers in psychology · 2026Article
- Exploring fashion designers' acceptance of AIGC: A dual-pathway analysis from the stimulus-organism-response perspective.PloS one · 2026Article
- Understanding AI adoption through expert discourse: A UTAUT-based analysis on LinkedIn.PloS one · 2026Article
- Artificial intelligence in clinical microbiology: results from the first National survey by the Italian association of clinical microbiologists.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Article
- Beyond willingness: unpacking pharmacists' adoption of AI-driven clinical decision support systems through an extended UTAUT framework.Frontiers in public health · 2026Article
- AI in Fracture Detection: A Cross-Disciplinary Analysis of Physician Acceptance Using the UTAUT Model.Diagnostics (Basel, Switzerland) · 2025Article
- Structural equation modeling for influencing factors on behavioral intention to adopt medical AI among Chinese nurses: a nationwide cross-sectional study.BMC nursing · 2025Article
- Investigating the factors influencing users' adoption of artificial intelligence health assistants based on an extended UTAUT model.Scientific reports · 2025Article
- Perception and Knowledge of Hospital Workers Toward Using Artificial Intelligence: A Descriptive Study.Health science reports · 2025Article
- Exploring trust factors in AI-healthcare integration: a rapid review.Frontiers in artificial intelligence · 2025Review
- AI with agency: a vision for adaptive, efficient, and ethical healthcare.Frontiers in digital health · 2025Article
- Exploring the determinants of AIGC usage intention based on the extended AIDUA model: a multi-group structural equation modeling analysis.Frontiers in psychology · 2025Article
- Acceptance of artificial intelligence clinical assistant decision support system to prevent and control venous thromboembolism among healthcare workers: an extend Unified Theory of Acceptance and Use of Technology Model.Frontiers in medicine · 2025Article
- Personalized AI for workplace health promotion: performance management and healthcare worker engagement through digital analytics.Frontiers in public health · 2025Review
- Trust in machines: how personality trait shapes static and dynamic trust across different human-machine interaction modalities.Frontiers in psychology · 2025Article
- Perceptions and attitudes of nurse practitioners toward artificial intelligence adoption in health care.Health science reports · 2024Article
- Applying the UTAUT2 framework to patients' attitudes toward healthcare task shifting with artificial intelligence.BMC health services research · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Artificial intelligence (AI)-assisted diagnosis and treatment could expand the medical scenarios and augment work efficiency and accuracy. However, factors influencing healthcare workers' adoption intention of AI-assisted diagnosis and treatment are not well-understood. This study conducted a cross-sectional study of 343 dental healthcare workers from tertiary hospitals and secondary hospitals in Anhui Province. The obtained data were analyzed using structural equation modeling. The results showed that performance expectancy and effort expectancy were both positively related to healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Social influence and human-computer trust, respectively, mediated the relationship between expectancy (performance expectancy and effort expectancy) and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Furthermore, social influence and human-computer trust played a chain mediation role between expectancy and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Our study provided novel insights into the path mechanism of healthcare workers' adoption intention of AI-assisted diagnosis and treatment.
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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.