Doctors-AICDSS
Description
This dataset contains survey responses from a two-wave study examining how clinicians in tertiary-care hospitals evaluate AI-enabled Clinical Decision Support Systems (AI-CDSS) and whether their initial evaluations predict subsequent self-reported use of such systems. Study design: At Wave 1 (baseline), 212 practising physicians in public and private tertiary-care hospitals in Delhi-NCR, India, completed a scenario-based questionnaire after reviewing a standardised AI-CDSS clinical vignette. Measures captured benefit perceptions (usefulness, ease of use, diagnostic confidence), sacrifice perceptions (performance risk, mistrust, perceived lack of regulatory standards, professional-substitution concern), personal innovativeness, perceived value, and behavioural intention to use AI-CDSS. At Wave 2, conducted 8-12 weeks later, 152 of the original respondents (71.7% retention) were re-contacted and reported whether they had subsequently used an AI-based clinical decision support tool in practice, along with four supplementary post-use items among those reporting use. Sample: N = 212 at Wave 1; n = 152 retained at Wave 2 (54 reporting subsequent use, 98 non-use). Respondents were general-duty clinicians (MBBS) and postgraduate specialists (MD/MS/DM) recruited from participating hospitals. File contents: A single spreadsheet (212 rows) containing demographic/background variables (age, gender, education, specialisation code, AI knowledge, AI familiarity); item-level Likert responses for all Wave 1 constructs; Wave 2 outcome variables including the binary subsequent-use indicator and four post-use items; and PLS-SEM latent variable scores for each construct, including the personal-innovativeness x perceived-value interaction term used to test moderation.
Files
Institutions
- Jamia HamdardDelhi, New Delhi