Strategies used in managing conversations about prostate-specific antigen (PSA) testing among family physicians (FPs): a qualitative study
Bibliographic record
Abstract
OBJECTIVES: Screening for prostate cancer in healthy asymptomatic men using the prostate-specific antigen (PSA) test is controversial due to conflicting recommendations from and a lack of strong evidence regarding the benefit of population-based screening. In Canada and internationally, there is variability in how family physicians (FPs) approach PSA testing in asymptomatic men. The purpose of our study was to explore how family FPs approach discussions with their male patients around PSA testing in Manitoba, Canada. DESIGN: Qualitative descriptive study. SETTING AND PARTICIPANTS: High-ordering and median-ordering FPs were invited to participate in an interview. In addition to exploring practice behaviours around PSA testing, participants were asked to elaborate on their typical discussion with asymptomatic men who request a PSA test or other tests and procedures that they do not feel are clinically warranted. Data were analysed inductively using a constant-comparison approach. RESULTS: There were important variations between high-ordering and median-ordering FP's approaches to discussing PSA testing. Strategies to facilitate conversations were more frequently identified by median-ordering physicians and often included methods to facilitate assessing their patient's understanding and values. In addition to decision aids, median-ordering FPs used motivational interviewing to tailor a discussion, organised their practice structure and workflow habits in a way that enhanced patient-provider discussions and leveraged 'new' evidence and other aids to guide conversations with men. CONCLUSION: We found that high-ordering FPs tended to use the PSA test for screening asymptomatic men with limited shared decision-making. Median-ordering FPs used conversational strategies that emphasised uncertainty of benefit and potential risk and did not present the test as a recommendation.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".