Understanding Prostate Cancer Patients’ Support Needs: How Do They Manage Living With Cancer?
Bibliographic record
Abstract
Survivorship concerns are common after prostate cancer with many survivors experiencing long-term and late effects of treatment. Patient navigation has been promoted to improve continuity of care. While many studies have examined the potential benefits of patient navigation by health-care professionals for the screening and diagnostic phase, few are focused on peer navigation for prostate cancer patients in the treatment and posttreatment survivorship phase. The purpose of this qualitative descriptive study was to explore the perceptions of men with prostate cancer and the partners of such men regarding their support needs and experiences. In depth, semistructured interviews were conducted with 20 men who were prostate cancer survivors and 4 partners. Qualitative thematic analysis was used to identify themes and patterns across the interviews. According to the results, participants had experienced uncertainty regarding their test results and treatment options. Many participants had dealt with these challenges by researching information and seeking support from health-care professionals, family members, and fellow prostate cancer patients. Four themes are highlighted: (a) dealing with the unknown, (b) everyone is different, (c) keep looking forward, and (d) getting on with it. Overall participants held favorable views of peer support. Sharing one’s experiences with an empathic peer who has completed treatment can reassure the patient that he is not alone. Knowing what to expect empowers men and their partners to manage the illness and effects of treatment. This research provides insights into the scope of patients’ and partners’ informational and psychosocial needs and preferred coping strategies.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| 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".