Systematic literature review informing the EULAR points to consider for patient education in physical activity and self-management of pain during transitional care
Bibliographic record
Abstract
OBJECTIVES: To synthesise existing evidence on transitional care programmes for young people with juvenile-onset rheumatic and musculoskeletal diseases (jRMDs), focusing on their structure and implementation, the qualitative experiences and perceptions of those involved, and the quantitative outcomes associated with these programmes. Together with additional information, these insights have informed the European Alliance of Associations for Rheumatology (EULAR) Points to Consider for patient education in physical activity and self-management of pain in jRMDs during transitional care. METHODS: A systematic literature review was conducted with a broadened scope beyond patient education in physical activity and self-management of pain to provide a comprehensive overview of transitional care in rheumatology, aiming to optimise current strategies, support evidence-based approaches, and identify areas for clinical improvement. The search was conducted in PubMed and the Cochrane Library from inception until November 1, 2023. Descriptive, qualitative, and quantitative studies were included. Two researchers independently conducted the search, screening, data extraction, and quality assessment. RESULTS: From 31 studies, we identified 18 transitional care programmes with key approaches, including individualised and developmentally appropriate plans that often integrate educational strategies. These programmes, which generally aim to increase readiness to transfer, health-related quality of life, and continuity of care, frequently involved multidisciplinary teams and early intervention strategies. Young people with jRMDs and their families reported satisfaction with these transitional care experiences, particularly valuing early self-management support. While these programmes showed potential in promoting positive health outcomes and clinical practices, quantitative evidence supporting their effectiveness is limited, with few experimental studies confirming consistent benefits. CONCLUSIONS: This systematic review highlights the diverse yet fragmented approaches in transitional care for jRMDs, emphasising the need for stronger quantitative evidence. Thus, it is important to conduct further experimental research to optimise existing programmes or develop new ones, ultimately contributing to a smoother transition to adult care and improved long-term outcomes.
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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 | 0.057 | 0.172 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.027 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".