Teaching evolution to psychiatrists in Venezuela: comparison with medical students and other medical specialists: a pilot study
Bibliographic record
Abstract
INTRODUCTION: The teaching of Evolution Theory (ET) in medical programs has received scant attention in the literature. In this report, we first describe the main applications of ET in medicine. Second, we present the evaluation of an interactive seminar on ET given to groups of medical students, psychiatrists, and other medical specialists. METHODS: A two-hour, four-module, interactive seminar was conducted with separate groups of 27 psychiatrists, 15 family doctors, 18 neurologists, 13 physiatrists, 12 internists, and 24 sixth-year medical students without formal training in ET. Their knowledge of ET before and after the seminar was rated on a validated analogical scale (0-12). In addition, the perceived relevance of the information for the participants' professional activity was assessed. RESULTS: Score averages and medians before the seminar were below 6, suggesting low to moderate knowledge. The students' scores did not differ significantly from those of the physicians except on the Hominization item, where they scored lower than the physicians (p < 0.05). The psychiatrists' scores did not differ from those of the other groups before the seminar, but after the seminar the increase in their scores on a number of items was significantly smaller than that of the other groups. While all groups scored 10 or more when assessing the relevance of the information, the psychiatrists had the lowest score (p < 0.05). DISCUSSION: The results show the adequacy of short programs to enhance knowledge on ET. This may assist medical educators to develop comprehensive and compulsory courses. Future studies must explore whether psychiatrists are relatively reluctant or ambivalent to accept evolution concepts and proposals.
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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 | 0.002 | 0.003 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".