Assessing the Impact of the Prostate Cancer Patient Empowerment Program (PC-PEP) on Relationship Satisfaction, Quality of Life, and Support Group Participation: A Randomized Clinical Trial
Bibliographic record
Abstract
Background/Objectives: The Prostate Cancer Patient Empowerment Program (PC-PEP) is a 6-month, home-based intervention aimed at enhancing mental health in men undergoing curative prostate cancer treatment. This exploratory secondary analysis evaluates PC-PEP’s impact on relationship satisfaction, quality of life, and support group attendance among partnered participants. Methods: In a crossover randomized clinical trial ClinicalTrials.gov identifier: NCT03660085) of 128 men aged 50–82 scheduled for curative prostate cancer surgery or radiotherapy, 119 participants in relationships were included. Of these, 59 received the 6-month PC-PEP intervention, while 60 were randomized to a waitlist-control arm, receiving standard care for 6 months before starting PC-PEP. The intervention included daily emails with video instructions on mental and physical health, diet, social support, fitness, stress reduction, and intimacy. Outcomes were assessed using the Dyadic Adjustment Scale (DAS) and the Functional Assessment of Cancer Therapy–Prostate (FACT-P). Results: While relationship satisfaction remained stable, a significant improvement in emotional well-being was observed at 12 months in participants undergoing radiation therapy (p = 0.045). The PC-PEP intervention also led to significantly higher support group attendance at both 6 months (p = 0.001) and 12 months (p = 0.003), emphasizing its role in fostering social support and community engagement. Conclusions: The PC-PEP program effectively maintains relationship satisfaction and enhances emotional well-being, particularly in patients with fewer physical side effects. Its design promotes comprehensive care by integrating physical, psychological, and social support, making it a valuable resource for improving the quality of life in prostate cancer patients and potentially applicable to other cancer types.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".