Patient Communication Preferences for Prostate Cancer Screening Discussions: A Scoping Review
Bibliographic record
Abstract
PURPOSE: Prostate cancer screening guidelines have changed as new evidence showing an equivocal mortality benefit led many organizations to relax recommendations for this screening and instead suggest shared decision making. Presently, it is unknown how successfully these conversations happen. Our objective was to understand men's communication preferences when they discuss prostate cancer screening. METHODS: In this scoping review, we searched 4 electronic databases (Medline, Embase, PsycINFO, and CINAHL) and the gray literature. Additional studies were obtained from reference lists of included studies and relevant review articles. We included qualitative studies reporting patient perspectives relevant to the research question and published in English. Two independent researchers screened titles and abstracts based on these criteria, conducted a full-text review for final inclusion, evaluated the remaining articles for validity, extracted data, and used thematic analysis to build a thematic framework. A subgroup analysis was performed for Black men as many studies elicited their perspectives. RESULTS: Analyses were based on 29 studies. We identified 4 main themes that men described as critical for successful prostate cancer screening risk discussions with their primary care clinician: using everyday language, receiving a sufficient quantity of information, spending enough time, and having a trusting and respectful relationship. Three additional themes emerged that prohibited men from having any discussions at all: having already decided to pursue prostate cancer screening, being passive in medical encounters, and perceiving threat to one's well-being. Black men faced racism, which impacted medical interactions. CONCLUSIONS: Our findings point to strategies to support men's communication preferences and address preconceptions surrounding prostate cancer screening. More studies are needed in certain underrepresented populations given the propensity for disparity in health outcomes.
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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 | 0.025 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".