Faculty attitudes towards medical communication and their perceptions of students’ communication skills training at Dalhousie University
Bibliographic record
Abstract
SETTING: Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada. OBJECTIVES: (1) To assess the attitudes of full-time clinical faculty members towards medical communication using the newly developed Attitudes Towards Medical Communication Scale; (2) to determine faculty members' perceptions of communications training for students and residents. METHODS: An anonymous self-completion survey was sent to 233 full-time clinical faculty members. The questionnaire asked about faculty attitudes towards medical communication, and assessed faculty members' views of student and resident training in communication. RESULTS: Faculty scored highly in the Attitudes Towards Medical Communication Scale, with a mean score of 51.5 (SD 4.1) out of a possible 60. In univariate analysis, rating of personal enjoyment of teaching, rating of the importance of teaching, and having attended at least one faculty communications workshop in the previous 5 years were significantly associated with higher scale scores. When these factors were assessed using linear regression, only having attended a workshop and higher rating of the importance of teaching remained significant. Faculty assessed student training in communications skills poorly overall. When assessing seven specific communications areas, more than 20% rated this training as poor for six of the areas for third- and fourth-year students and for five of the areas for residents. CONCLUSIONS: Clinical faculty at Dalhousie have very positive attitudes towards medical communication, and more highly positive attitudes are found in those who have attended a communications workshop. Despite this evidence that faculty appreciate the importance of medical communication skills, many assessed students' training in this curriculum area as poor.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".