Complex regional pain syndrome: Facilitating the use of self-management strategies
Bibliographic record
Abstract
Aims: While several interventions are used to treat complex regional pain syndrome (CRPS), patient adherence to recommended care including self-management is challenging. To understand the barriers and facilitators to using self-management strategies among CRPS patients; to explore educational tools used to enable self-management; and to develop knowledge translation interventions to address potential barriers using intervention mapping. Methods: Semi-structured interviews of patients were conducted to identify the determinants of self-management. Findings informed the development of a tailored theory-based intervention to increase adherence. Result: Theoretical domains identified were: Social influence, Beliefs about capabilities, Beliefs about consequences, Environmental context and resources. Various educational tools were provided by treating clinicians. Interventions should consider increasing knowledge about treatment outcomes, identifying health antecedents and promoting self-monitoring. Conclusion: Online educational interventions focusing on patient advice, self-monitoring, and techniques to increase the quality of the clinician-patient relationship may successfully address patient barriers to using self-management strategies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".