Cross-Cultural Construct Validity Study of Professionalism of Vietnamese Medical Students
Bibliographic record
Abstract
BACKGROUND: Although many studies have made efforts to define and assess medical professionalism, few have addressed issues of construct validity. PURPOSES: The purpose of this article is to explore further construct validity of medical professionalism employing exploratory and confirmatory factor analysis. METHODS: The 32-item instrument by the American Board of Internal Medicine (ABIM) was adapted to assess the perceptions on medical professionalism of Vietnamese medical students. A sample of 1,196 (487 first-year, 341 third-year, 368 sixth-year) medical students participated voluntarily in the completion of the instrument. The data were randomly divided into three samples to assess the construct validity of medical professionalism by empirically deriving and confirming a model of professionalism. RESULTS: Exploratory and confirmatory factor analytic techniques resulted in a six-factor well-fitting model with a comparative fit index of .963 and root mean square error approximation of .029, 90% confidence interval [016, .039]: integrity, social responsibility, professional practice habits, ensuring quality care, altruism, and self-awareness. Social responsibility was perceived least important, and self-awareness was perceived most important by Vietnamese medical students. These constructs of medical professionalism were relatively similar with those found in Taiwanese medical students and the ABIM definitions but with some Vietnamese cultural differences. CONCLUSIONS: Although the results confirm that medical professionalism is a somewhat culturally sensitive construct, it nonetheless has many elements of medical professionalism that are universal. Future research should be conducted to test the generalizability of our six-factor model of professionalism with various samples (e.g., residents, physicians), cultures, and language groups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".