Nonverbal Communication in a Caribbean Medical School: “Touch Is a Touchy Issue”
Bibliographic record
Abstract
BACKGROUND: The heath communication curriculum at the Trinidad campus of the University of the West Indies was developed out of practices advocated in large Western countries. Many students and tutors observed that the nonverbal skills advocated in these approaches did not fit the complex cultural dynamics of the Caribbean. PURPOSE: A study was developed to understand the problems Caribbean students faced with these nonverbal communication practices. METHODS: Thirty-six students representing different Caribbean territories were randomly selected from the two compulsory communication skills courses: Communication Skills for Health Personnel and Communication Skills for the Health Professions class list. These students participated in 4 focus group discussions (FGD). The FGD questions were formulated on the nonverbal skills advanced in the Calgary-Cambridge Guide to the doctor-patient interview. RESULTS: The findings supported the view that recommended nonverbal skills were in conflict with expected doctor-patient behavior in different Caribbean territories. Students felt that nonverbal communication needed to be treated with greater cultural sensitivity. CONCLUSIONS: These findings stimulated changes to the health communication program. this article identifies changes made to the communication skills program in response to cultural difference.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".