Effects of training and support programs for leaders of illness-based support groups: commentary and updated evidence
Bibliographic record
Abstract
BACKGROUND: Peer-led support groups play an important role in supporting people with chronic diseases. They may be particularly important for people with rare diseases who typically do not have access to professional support options that focus on their disease-specific needs. Many peer-led support groups in rare diseases, however, are not sustained, and many patients do not have access to support groups. Training and education for peer support group leaders could address barriers to initiating and sustaining groups, but there is little evidence on the effectiveness of support group leader training programs. A previous systematic review evaluated the effects of training programs for peer leaders of support groups for people with medical illness on leader and support group outcomes, but it identified only one randomized controlled trial (RCT) that compared high- and low-resource training programs for cancer support group leaders. The trial did not find evidence that the high-resource program was more effective, but was limited by a small sample size and serious methodological limitations. To meet the needs of people living with the rare autoimmune connective tissue disease scleroderma, the Scleroderma Patient-centered Intervention Network has partnered with patient organizations to develop the Scleroderma Support group Leader EDucation Program, and a full-scale RCT to test the effectiveness of the program is planned. To verify the need for such a trial, we updated the previous systematic review. UPDATED EVIDENCE: Review methods for the update were unchanged from the initial review. The updated database search yielded 1504 unique citations in addition to the 9757 assessed for eligibility in the previous review. All additional citations identified in the updated search were excluded at the title and abstract review stage. CONCLUSIONS: Our systematic review update found that there is presently insufficient evidence on the effectiveness of training and support programs for peer leaders of disease-based support groups, highlighting the need for well-designed and rigorously conducted RCTs to examine the effects of training for peer leaders of support groups, especially in a rare disease context. The Scleroderma Patient-centered Intervention Network's trial of the Scleroderma Support group Leader EDucation Program will serve as such a trial. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018096369.
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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 | 0.012 | 0.122 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 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".