CTRI/2025/10/095667已完成不适用
Acceptability of Clinical Care Enhanced by Predictive Technologies - AI Evaluating Doctors’ and Nurses’ Acceptance of AI-Driven Clinical Tools Using the Unified Theory of Acceptance and Use of Technology (UTAUT)
Medanta- The Medicity1 个研究点 分布在 1 个国家目标入组 240 人开始时间: 2025年10月15日最近更新:
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 240
- 试验地点
- 1
- 主要终点
- Mean scores and proportions of high responses across the four UTAUT constructs (Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions) among doctors and nurses.
研究概览
简要总结
The study aims to evaluate the acceptance of AI-based clinical decision-making tools among doctors and nurses in North India using the UTAUT framework. We hypothesize that healthcare professionals with greater knowledge and favorable attitudes toward AI are more likely to adopt and utilize AI tools in clinical practice.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 18.00 Year(s) 至 50.00 Year(s)（—）
- 性别
- All
入选标准
- •MBBS doctors and registered nurses working full-time.
- •Minimum 1 year of clinical experience.
- •Willingness to give informed consent.
排除标准
- •Healthcare workers in administrative/non-clinical roles.
- •Those unwilling to participate or incomplete responses.
结局指标
主要结局
Mean scores and proportions of high responses across the four UTAUT constructs (Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions) among doctors and nurses.
时间窗: At baseline (single time point – during questionnaire administration)
次要结局
- • Comparison of mean UTAUT scores between professional groups (doctors vs. nurses) using tests, as appropriate based on data distribution.(• Correlation analyses between UTAUT construct scores and independent variables such as age, years of experience, prior AI/HIS exposure, and AI training.)
研究者
Dr Sushila Kataria
Medanta The Medicity
研究点 (1)
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