Attitudes towards psychiatry among undergraduate medical students
Bibliographic record
Abstract
Mental health is the most neglected and stigmatized branch of medical science in Bangladesh. Attitudes towards psychiatry are an important determination for selection of the subject as career by the undergraduate medical students. The objective of this study was to determine the attitudes of undergraduate medical students towards psychiatry and related factors. It was across sectional study conducted from May 2013 to September 2013 among 1st and 5th year medical students of Rajshahi Medical College, Rajshashi and Shaheed Shahrawardi Medical College, Dhaka. Results showed that only 2.6% of 5th year medical students wanted to be specialized in psychiatry and none of 1st year medical students wanted to be specialized in psychiatry. All of them (100% and 98.7%) agreed with the statement that psychiatric research has made good strides in advancing care of major mental disorder and majority students of both groups were (96% and 86.6% respectively) with the statement that psychiatry was a rapidly expanding frontier of medicine. Around two-third of the students (79.3% and 82.7% respectively) perceived psychiatric treatment as being helpful. Fifty nine (76.6%) of 5th year students and forty one (55.7%) of 1st year students did not agree that psychiatrists frequently abuse their legal power to hospitalize patients against their will. Positive opinions on attitudes of undergraduate medical students towards psychiatry became strengthen further following exposure to psychiatry lectures and clerkship in psychiatry ward.Bang J Psychiatry Dec 2014; 28(2): 45-49
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".