ArticleBMC medical informatics and decision making2022
Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model.
Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Exploring the role of professional identity in the implementation of clinical decision support systems-a narrative review.Implementation science : IS · 2024Pooled it
- Evaluation of a Decision Mining Tool for Nursing Quality Improvement by Hospital Nurses: Theory-Guided Qualitative Study.JMIR formative research · 2026Article
- Digital Health Technology Adoption Readiness Among Doctoral Nursing Students in Saudi Arabia: An Exploratory Qualitative Study.Healthcare (Basel, Switzerland) · 2026Article
- A Systematic Review of Factors Affecting Utilization of Decision Support Systems: The Interplay Between Technology, Users, and the Healthcare Environment.Health science reports · 2026Review
- Determining the adoption intention and influencing factors of telerehabilitation by people with rehabilitation needs: a cross-sectional survey.BMC public health · 2026Article
- Construction of a public health emergency information system framework: A case study of Zhuhai city, China.PloS one · 2026Article
- Acceptance of Electronic Medical Records Among Practitioner Nurses and Nurse Managers Using the UTAUT Framework in Hospital Settings: A Scoping Review.Journal of multidisciplinary healthcare · 2026Review
- Factors associated with intention to use generative artificial intelligence in nursing practice: a cross-sectional study.BMC nursing · 2025Article
- Mental health practitioners' perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study.BMC health services research · 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
- Development and evaluation of a clinical nursing decision support system for the prevention of neonatal hypoglycaemia.BMC medical informatics and decision making · 2024Article
- Understanding the predictors of health professionals' intention to use electronic health record system: extend and apply UTAUT3 model.BMC health services research · 2024Article
- Successful Electronic Consultation Service Initiative in Quebec, Canada With Primary Care Physicians' and Specialists' Experiences on Acceptance and Use of Technological Innovation: Cross-Sectional Exploratory Study.JMIR formative research · 2024Article
- AI in medical education: medical student perception, curriculum recommendations and design suggestions.BMC medical education · 2023Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVenous thromboembolism has been a major public health problem and caused a heavy disease burden. Venous thromboembolism clinical decision support system was proved to have a positive influence on the prevention and management of venous thromboembolism. As the direct users, nurses' acceptance of this system is of great importance to support the successful implementation of it. However, there are few relevant studies to investigate nurses' acceptance and the associated factors are still unclear.
objectiveTo investigate the determinant factors of nurses' acceptance of venous thromboembolism clinical decision support system with the modified Unified Theory of Acceptance and Use of Technology.
methodsWe designed a questionnaire based on the modified Unified Theory of Acceptance and Use of Technology and then a cross-sectional survey was conducted among nurses in a tertiary hospital in Nanjing, China. Statistically, a Structural Equation Modeling -Partial Least Squares path modeling approach was applied to examine the research model.
resultsA total of 1100 valid questionnaires were recycled. The modified model explained 74.7%, 83.0% and 86% of the variance in user satisfaction, behavioral intention and user behavior, respectively. The results showed that performance expectancy (β = 0.254, p = 0.000), social influence (β = 0.136, p = 0.047), facilitating conditions (β = 0.245, p = 0.000), self-efficacy (β = 0.121, p = 0.048) and user satisfaction (β = 0.193, p = 0.001) all had significant effects on nurses' intention. Although effort expectancy (β = 0.010, p = 0.785) did not have a direct effect on nurses' intention, it could indirectly influence nurses' intention with user satisfaction as the mediator (β = 0.296, p = 0.000). User behavior was significantly predicted by facilitating conditions (β = 0.298, p = 0.000) and user intention (β = 0.654, p = 0.001).
conclusionThe research enhances our understanding of the determinants of nurses' acceptance of venous thromboembolism clinical decision support system. Among these factors, performance expectancy was considered as the top priority. It highlights the importance of optimizing system performance to fit the users' needs. Generally, the findings in our research provide clinical technology designers and administrators with valuable information to better meet users' requirements and promote the implementation of venous thromboembolism clinical decision support system.
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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.