The Landscape of Supportive Care Needs Among Prostate Cancer Patients in New Zealand: A Cross‐Ethnic Analysis
Bibliographic record
Abstract
BACKGROUND: Prostate cancer (PCa) is a significant health burden within New Zealand (NZ). Survival gains from prostate cancer have created a shift in focus from survival towards quality of life (QoL) and supportive care during extended survivorship. METHOD: We launched a nation-wide cross-sectional survey and recruited three cohorts of 1000 men with prostate cancer (men diagnosed with prostate cancer within 1 year, between 1 and 3 years, and between 3 and 5 years) as well as an additional Māori men group (N = 4000 in total). The survey instruments measured quality of life, supportive care needs, and care service utilization. RESULTS: Analysis of 1075 responses revealed that Māori men experienced lower quality of life and reported greater unmet supportive care needs. Information and psychology needs were mostly reported in both Māori and non- Māori groups. Key predictors of these needs included mental health conditions, hormonal imbalances, and employment status. CONCLUSION: The study highlights significant ethnic disparities in the supportive care needs of New Zealand prostate cancer survivors (PCS), emphasizing the necessity for tailored, culturally sensitive healthcare interventions. Addressing the complex determinants of these needs is crucial for enhancing the well-being of all PCS. IMPLICATIONS FOR CANCER SURVIVORS: Actively seeking health information and mental health counselling would significantly benefit PCS by reducing unmet supportive care needs and improving overall quality of life. This approach encourages survivors to take an active role in their healthcare, potentially leading to better health outcomes and enhanced well-being.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".