Education and Social Support as Key Factors in Osteoarthritis Management Programs: A Scoping Review
Bibliographic record
Abstract
Systematic reviews of self-management programs for osteoarthritis suggest minimal evidence of benefit and indicate substantial heterogeneity in interventions. The purpose of this scoping review was to describe the nature of self-management interventions provided to patients with osteoarthritis focusing on the inclusion and type of education and social support components. We searched PsycINFO, EMBASE, MEDLINE, and Cochrane Library databases from 1990 to 2016 to identify studies addressing community-based management strategies for osteoarthritis that included aspects of disease-specific education and ongoing social support. Results are presented as a narrative synthesis to facilitate integration of diverse evidence. Data were extracted from 23 studies that met our inclusion and exclusion criteria, describing complex, multicomponent interventions for osteoarthritis. All studies included education components, and 18 of these were osteoarthritis-specific. Social support was most often offered through peers and health care professionals, but also through exercise trainers/instructors and researchers, and lasted between 5 and 52 weeks. We charted positive social interaction offered by peers in group settings and emotional/informational support offered by health care professionals. Overall, descriptions of self-management provided limited documentation of the rationale or content of the programs. This suggests that more precise definitions of the theoretical underpinnings, components, and mechanisms would be useful for greater insight into best practices for osteoarthritis self-management programs.
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 | 0.016 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".