Perspectives and Misconceptions of an Online Adult Male Cohort Regarding Prostate Cancer Screening
Bibliographic record
Abstract
Introduction: Congruent with most guideline publishers, the Canadian Urological Association (CUA) recommends shared decision-making (SDM) on PSA screening (PSAS) for prostate cancer (PCa) following a discussion of its benefits and harms. However, there are limited data on how the general male population feels about these topics. Methods: A survey was completed by 906 male-identifying participants (age > 18) recruited via Amazon Mechanical Turk (MTurk), which is a crowdsourcing platform providing minimal compensation. Participants answered questions regarding demographics (15), personal/family history (9), PCa/PSA knowledge (41), and opinions regarding PSAS (45). Results: The median age was 38.2 (SD = 12.0), with 22% reporting a family history of PCa and 20% reporting personally undergoing PSAS. Although most participants had heard of PCa (85%) and that they could be screened for it (81%), they generally did not feel knowledgeable about PCa or PSAS guidelines. Most want to talk to their clinician about PCa and PSAS (74%) and are supportive of SDM (48%) or patient-centered decision-making (25%). In general, participants thought PSAS was still worthwhile, even if it led to additional testing or side effects. Similarly, participants thought higher-risk patients should be screened earlier (p < 0.001). A number of misconceptions were evident in the responses. Conclusions: Men approaching the age of PSAS do not feel knowledgeable about PCa or PSAS and want their clinician to discuss these topics with them. The majority believe in PSAS and would like to undergo this screening following SDM. Clinicians also have a role in correcting common misconceptions about PCa.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".