Social support and quality of life of prostate cancer patients after radiotherapy treatment
Bibliographic record
Abstract
Research suggests that social support can have an impact on health-related quality of life (HRQOL). Social support can be structural support (SSS) or functional support (FSS). Our study was designed to clarify the relationships between HRQOL, FSS and SSS. We conducted a cross-sectional survey and a detailed chart review. The study population was men attending a follow-up clinic after receiving radiotherapy for prostate cancer. Functional social support was measured by using the MOS Social Support Survey. Structural social support was measured by using questions adapted from the 1994-1995 National Population Health Survey conducted by Statistics Canada. Health-related quality of life was measured by using the European Organization for Research and Treatment of Cancer's QLQ-C30. We found a statistically significant positive correlation between FSS and HRQOL but no association between overall SSS and HRQOL. Worsening urinary symptoms were significantly associated with lower levels of FSS and with lower HRQOL. This study underscores that the perception of support (functional) is more important than the amount or size of support (structural). We also identified a subgroup of men who have lower FSS and lower HRQOL that suffer from urinary side effects of their treatment. Further research to clarify the relationship between FSS and urinary symptoms will also clarify how an intervention could improve the HRQOL of these men.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".