Interactive Genetic Counseling Role‐Play: A Novel Educational Strategy for Family Physicians
Bibliographic record
Abstract
BACKGROUND: Family physicians (FPs) are increasingly involved in delivering genetic services. Familiarization with aspects of genetic counseling may enable FPs to help patients make informed choices. PURPOSE: Exploration of interactive role-play as a means to raise FPs' awareness of the process and content of genetic counseling. METHODS: FPs attending two large Canadian family medicine conferences in 2005 were eligible -- 93 participated. FPs discussed a case during a one-on-one session with a genetic counselor. Evaluation involved pre and post intervention questionnaires RESULTS: FPs' baseline genetic knowledge was self-rated as uniformly poor. Baseline confidence was highest in eliciting family history and providing psychosocial support and lowest in discussing risks/benefits of genetic testing and counseling process. Post-intervention, 80% of FPs had better appreciation of family history and 97% indicated this was an effective learning experience. CONCLUSIONS: Role-play with FPs is effective in raising awareness of the process and content of genetic counseling and may be applied to other health disciplines.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".