Experiences of Australian men diagnosed with advanced prostate cancer: a qualitative study
Bibliographic record
Abstract
OBJECTIVE: To explore men's lived experience of advanced prostate cancer (PCa) and preferences for support. DESIGN: Cross-sectional qualitative study applying open-ended surveys and interviews conducted between June and November 2016. Interviews audio-recorded and transcribed verbatim and analysed from an interpretive phenomenological perspective. SETTING: Australia, nation-wide. PARTICIPANTS: 39 men diagnosed with advanced PCa (metastatic or castration-resistant biochemical regression) were surveyed with 28 men subsequently completing a semistructured in depth telephone interview. RESULTS: Thematic analysis of interviews identified two organising themes: lived experience and supportive care. Lived experience included six superordinate themes: regret about late diagnosis and treatment decisions, being discounted in the health system, fear/uncertainty about the future, acceptance of their situation, masculinity and treatment effects. Supportive care included five superordinate themes: communication, care coordination, accessible care, shared experience/peer support and involvement of their partner/family. CONCLUSIONS: Life course and the health and social context of PCa influence men's experiences of advanced disease. Multimodal interventions integrating peer support and specialist nurses are needed that more closely articulate with men's expressed needs.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".