Canadian Nurses’ Perspectives on Prostate Cancer Support Groups
Bibliographic record
Abstract
BACKGROUND: Prostate cancer support groups (PCSGs) are community-based organizations that offer information and psychosocial support to men who experience prostate cancer and their families. Nurses are well positioned to refer men to a range of psychosocial resources to help them adjust to prostate cancer; however, little is known about nurses' perspectives on PCSGs. OBJECTIVE: The aim of this study was to describe nurses' views about PCSGs as a means to making recommendations for advancing the effectiveness of PCSGs. METHODS: A convenience sample of 101 Canadian nurses completed a 43-item Likert-scale questionnaire with the additional option of providing comments in response to an open-ended question. Univariate descriptive statistics and content analysis were used to analyze the quantitative and qualitative data, respectively. RESULTS: Participants held positive views about the roles and potential impact of PCSGs. Participants strongly endorsed the benefits of support groups in disseminating information and providing support to help decrease patient anxiety. Online support groups were endorsed as a practical alternative for men who are reluctant to participate in face-to-face groups. CONCLUSIONS: Findings suggest that nurses support the value of Canadian face-to-face and online PCSGs. This is important, given that nurses can help connect individual patients to community-based sources providing psychosocial support. IMPLICATIONS FOR PRACTICE: Many men benefit from participating in PCSGs. Aside from positively endorsing the work of PCSGs, nurses are important partners for raising awareness of these groups among potential attendees and can directly contribute to information sharing in face-to-face and online PCSGs.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".