Self‐management approaches to reduce the ill‐health burden associated with musculoskeletal foot and ankle problems: A scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: The high ill-health burden associated with musculoskeletal (MSK) disease has been widely reported, and various treatment approaches proposed. Increasingly, treatments have sought to reflect personalised care and incorporate self-management (SM). However, the range of SM approaches proposed for foot and ankle MSK problems, and their relative clinical or cost-effectiveness, has not been reviewed. A scoping review is required to understand the need/appropriateness of a systematic review on this topic. METHODS AND ANALYSIS: The scoping review will be conducted in line with the PRISMA-ScR framework. We will perform an initial search across two databases to confirm search syntax. We will then complete a full search across three databases (Embase [Ovid], CINAHL [EBSCO], and Medline [EBSCO]) and grey literature (Cochrane Library, The British Library, The Canadian Agency for Drugs and Technologies in Health [CADTH], The Health Foundation, The Kings Fund, and MedNar). We will use a snowballing strategy to review the reference list of retrieved texts, as per inclusion criteria, to identify previously unretrieved texts of potential relevance. In an iterative process, the protocol outlined above will be refined and repeated as new key terms come to light. ETHICS AND DISSEMINATION: The scoping review will synthesise what is known and not known about SM approaches for MSK foot and ankle problems. The review will form the first step in outlining future research recommendations and areas of potentially unmet clinical need. The findings will be submitted for publication and shared in written form with stakeholder groups involved in the design of future research.
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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 | 0.138 | 0.107 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.014 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.086 | 0.022 |
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".