Knowledge, trust attitudes, and behaviors towards AI and their association with critical thinking disposition in Chinese undergraduate medical students
A cross-sectional study
Bibliographic Data
| ID | 22424997 |
|---|---|
| Authors | Songhua Ma (Nantong University, corresponding author), Yuyuan Lu (0000-0002-4073-678X, Nantong University), Huiqun Wu (0000-0001-5837-6199, Nantong University), Qing Zhou (0000-0002-2100-8840, Nantong University), Huiwei Huang (Nantong University), Jian Song (0000-0002-0364-9628, Nantong University), Song Jian (0000-0002-3849-4056) |
| Year | 2026 |
| Volume | 26 |
| Issue | 1 |
| Publication date | 2026-04-28 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Medical Education (JOURNAL) |
| Journal identifiers | ISSN: 1472-6920 • E-ISSN: 1472-6920 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1186/s12909-026-09318-0 |
| PMID | 42050524 |
| OpenAlex | W7157079516 |
| Language | EN |
| References cited | 21 |
OBJECTIVE: The increasing use of artificial intelligence (AI) in medical education offers potential learning benefits but also raises concerns about its potential impact on critical thinking (CT) development. This study aims to examine the associations between medical undergraduates’ AI usage (frequency and duration), perceived trust attitudes towards AI, AI knowledge, responsible usage behaviors (verification and ethical considerations), and their CT disposition. METHODS: A cross-sectional study was conducted at a Chinese medical school. Participants completed the Chinese version of Critical Thinking Disposition Inventory (CTDI-CV) and a structured questionnaire assessing AI usage, knowledge, perceived trust attitudes, responsible usage behaviors, and other related variables. Data were analyzed using Pearson correlation and multiple linear regression to identify predictors of CT disposition. RESULTS: The mean CTDI-CV score was 292.19 (SD = 39.25), with 60.6% of participants showing a positive CT disposition. AI usage frequency and duration had no significant associations with CT disposition. Significant differences in CTDI-CV scores were found across majors (t = 5.244, p < 0.001), grade levels (F = 13.574, p < 0.001) and academic performance (F = 5.354, p < 0.01). Multiple linear regression revealed that responsible usage behavior was a significant positive predictor of CT disposition (Beta = 0.140, p < 0.05), whereas higher perceived trust attitude towards AI was a negative predictor (Beta = -0.129, p < 0.05). CONCLUSIONS: The findings indicate that responsible usage behavior toward AI is positively associated with CT disposition, while perceived trust attitudes toward AI emerge as a negative predictor. These results suggest that medical education should place greater emphasis on cultivating critical engagement and verification skills rather than focusing solely on technical AI proficiency.
Critical thinking · Disposition · Linear regression · MEDLINE · Pearson product-moment correlation coefficient · Positive relationship · Regression analysis · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Simulation-Based Education in Healthcare
| Highly cited | No |
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