Prostate Cancer Treatment and Work: A Scoping Review
Bibliographic record
Abstract
Prostate cancer is the most common malignancy diagnosed in North American men. Although medical advances have improved survival rates, men treated for prostate cancer experience side-effects that can reduce their work capacity, increase financial stress, and affect their career and/or retirement plans. Working-age males comprise a significant proportion of new prostate cancer diagnoses. It is important, therefore, to understand the connections between prostate cancer and men's work lives. This scoping review aimed to summarize and disseminate current research evidence about the impact of prostate cancer treatment on men's work lives. Electronic databases were searched to identify peer-reviewed articles published between 2006 and 2020 that reported on the impact of prostate cancer treatment on men's work. Following scoping review guidelines, 21 articles that met inclusion criteria were identified and analyzed. Evidence related to the impact of prostate cancer on work was grouped under three themes: (1) work outcomes after prostate cancer treatment; (2) return to work considerations, and (3) impact of prostate cancer treatment on men's finances. Findings indicate that men's return to work may be more gradual than expected after prostate cancer treatment. Some men may feel pressured by financial stressors and masculine ideals to resume work. Diverse factors including older age and social benefits appear to play a role in shaping men's work-related plans after prostate cancer treatment. The findings provide direction for future research and offer clinicians a synthesis of current knowledge about the challenges men face in resuming work in the aftermath of prostate cancer treatment.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.014 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".