Changing Clinical Practice
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to explore the factors that contributed to the adoption of opportunistic salpingectomies (removal of fallopian at the time of hysterectomy or in lieu of tubal ligation) by gynecologic surgeons in British Columbia (where a knowledge translation initiative took place) and in Ontario (a comparator where no knowledge translation initiative took place). We aimed to understand why the knowledge translation initiative undertaken by OVCARE in British Columbia resulted in such a dramatic uptake in opportunistic salpingectomy. METHODS: We undertook a qualitative evaluation of clinicians' decisions about whether or not they should adopt the practice of opportunistic salpingectomy based on interviews with gynecologic surgeons in British Columbia and Ontario (n = 28). The analysis draws from the Consolidated Framework for Implementation Research. RESULTS: Regional cohesion combined with practice change information exposure and thought leader support were important in explaining differences in adoption levels between participants. The British Columbian knowledge translation campaign was successful because provincial thought leaders exposed gynecologic surgeons to recommendations through multiple sources within a highly socially cohesive environment wherein clinicians felt pressure to adopt the recommendations. In both provinces, high adopters often believed that the workload and surgical risk associated with the adoption was low and the potential benefit-because of limited ovarian cancer detection and treatment options-was high. CONCLUSION: This research points to the important role that local professional networks can play in encouraging clinicians to change their practice by creating a cohesive regional environment where clinicians are repeatedly exposed to important information and supported in their practice change by local thought leaders.
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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 | 0.016 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".