Influencing factors of alexithymia in Chinese medical students: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: A much higher prevalence of alexithymia has been reported in medical students compared with the general population, and alexithymia is a risk factor that increases vulnerability to mental disorders. Our aim was to evaluate the level of alexithymia in Chinese medical students and to explore its influencing factors. METHODS: A cross-sectional study of 1,950 medical students at Shenyang Medical College was conducted in May 2014 to evaluate alexithymia in medical students using the Chinese version of the 20-item Toronto Alexithymia Scale (TAS-20). The reliability of the questionnaire was assessed by Cronbach's α coefficient and mean inter-item correlations. Confirmatory factor analysis (CFA) was used to evaluate construct validity. The relationships between alexithymia and influencing factors were examined using Student's t-test, analysis of variance, and multiple linear regression analysis. Statistical analysis was performed using SPSS 21.0. RESULTS: Of the 1,950 medical students, 1,886 (96.7%) completed questionnaires. Overall, Cronbach's α coefficient of the TAS-20 questionnaire was 0.868. The results of CFA showed that the original three-factor structure produced an acceptable fit to the data. By univariate analysis, gender, grade (academic year of study), smoking behavior, alcohol use, physical activity, history of living with parents during childhood, and childhood trauma were influencing factors of TAS-20 scores (p < 0.05). Multiple linear regression analysis showed that gender, physical activity, grade, living with parents, and childhood trauma also had statistically significant association with total TAS-20 score (p < 0.05). CONCLUSIONS: Gender, physical activity, grade, history of living with parents during childhood, and childhood trauma were all factors determining the level of alexithymia. To prevent alexithymia, it will be advisable to promote adequate physical activity and pay greater attention to male medical students and those who are in the final year of training.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".