The role of self‐help groups in educating and supporting patients with prostate cancer and interstitial cystitis
Bibliographic record
Abstract
OBJECTIVES: To identify and compare the needs of patients with prostate cancer or interstitial cystitis (IC), and to evaluate the role of self-help groups (SHGs) in meeting those needs, as SHGs are thought to be an important source of information and social support for such patients. METHODS: The authors attended SHG meetings for prostate cancer and IC from September 2000 to May 2001. Issues related to SHGs were addressed by combining their experiences with those published previously. RESULTS: Patients with prostate cancer appear to use SHGs primarily as a medium for advocacy and information sharing about the disease, whereas patients with IC seem to use SHGs for social support and coping skills. Patients perceive SHGs as being useful, but many do not attend these meetings. Urologists' attitudes toward SHGs are identified as a potential factor contributing to the under-use of SHGs by both groups of patients. CONCLUSIONS: The inherent differences in disease and patient characteristics result in both groups of patients using SHGs for different reasons. The differences in therapeutic objectives are reflected in the format and content of SHG meetings. Issues related to not participating in SHGs and areas of future research are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".