The Certificate of Added Competence credentialling program in family medicine: a descriptive survey of the family physician perspective of enhanced skill practices in Canada
Bibliographic record
Abstract
Introduction: The College of Family Physicians of Canada (CFPC) offers the Certificate of Added Competence (CAC) program to designate a family physician with enhanced skills. In 2015, the College expanded its program to introduce enhanced certification in four new domains: Palliative Care, Care of the Elderly, Sports and Exercise Medicine, and Family Practice Anesthesia. In this study, we elicited perceptions from Canadian family physicians with and without the CAC on practice impacts associated with the program. Methods: Active family physicians in Canada with and without CACs were surveyed between November 2019 to January 2020. Descriptive statistics were generated to describe the perceptions of family physicians regarding the CAC program and its impacts on practice. Results: Respondents agreed with several benefits of the program including enhancing the capacity to deliver comprehensive care, alleviating the burden of patient travel by increasing the availability of care in rural and remote communities, and providing opportunities to engage in various collaborative care models and new leadership roles. All respondents perceived CAC holders to pursue the certificate to meet both professional interests and community needs. Conclusions: There is a need for strong and continued investment in systemic practice improvements that incentivize the delivery of comprehensive family medicine practice.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".