1. Communication skills training in orthopaedics
Bibliographic record
Abstract
Communication skills have been identified as a key component of medical education by the CanMEDS Project. The objectives of this study were to identify the perceived key components of communication skills from the perspectives of both orthopaedic residents and their program directors, and to understand how these skills are currently taught. This study utilized a mixed methods design. Quantitative data was collected using a 30-item questionnaire, which was distributed to all Canadian orthopaedic residents. Qualitative data was collected through focus groups with orthopaedic residents and semi-structured interviews with orthopaedic program directors. One hundred and nineteen out of three hundred and twenty-five questionnaires were completed (response rate = 37%), twelve residents participated in two focus groups, and 9/16 program directors from across the country were interviewed. The questionnaire reliability had an internal consistency of Cronbach’s alpha = 0.72. An ANOVA of the questionnaire data showed gender and International vs. Canadian medical graduate status to be independent variables to several item responses (P < 0.01). The factor analysis produced a five-factor model accounting for 50% of the variance. Both program directors and residents identified communication skills as being the accurate and appropriate use of language (ie, content skills), not how the communication was presented (ie, process skills). Perceived barriers to communication included time constraints and the need to adapt to the many personalities and types of people encountered daily in the hospital. Residents lack explicit communication skill training, but value developing communication skills in the clinical environment through experiential learning and role modeling. Resident education should focus on developing residents’ process skills in communication. Care should be taken to avoid large-group didactic teaching sessions, which are perceived as ineffective.
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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 | 0.004 | 0.014 |
| 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 | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".