Scoping review protocol of the use of codesign methods in stroke intervention development
Bibliographic record
Abstract
INTRODUCTION: Codesign is an emerging research method to enhance intervention development by actively engaging non-researchers (eg, people who have had a stroke, caregivers and clinicians) in research. The involvement of non-researchers in research is becoming increasingly popular within health studies as it may produce more relevant and effective findings. The stroke population commonly exhibits challenges such as aphasia and cognitive changes that may limit their participation in codesign. However, the use of codesign within the stroke literature has not been comprehensively reviewed. This scoping review will determine: (1) what is the extent, range and nature of stroke research that has used codesign methods? (2) What codesign methods have been used to develop stroke interventions? (3) What considerations for codesigning interventions with people who have stroke are not captured in the findings? METHODS AND ANALYSIS: This is a protocol for a scoping review to identify the literature relating to stroke, and codesign will be conducted on OVID Medline, OVID Embase, OVID PsychINFO, EBSCO CINAHL, the Cochrane Library, Scopus, PEDro-Physiotherapy Evidence Database and Global Index Medicus. Studies of any design and publication date will be included. Title and abstract and full-text review will be conducted independently by two reviewers. Data will be extracted, collated and then summarised descriptively using quantitative (eg, numerical descriptions) and qualitative (eg, textual descriptions) methods. Numerical summaries will map the extent (eg, number of studies), range (eg, types of studies) and nature (eg, types of interventions developed) of the literature on this topic. A thematic analysis will provide insights into the codesign methods (eg, activities, non-researchers), including heterogeneity across and within studies. ETHICS AND DISSEMINATION: This review protocol does not require ethics approval as data has not been collected/analysed. The findings will highlight opportunities and recommendations to inform future codesign research in stroke and other populations who exhibit similar challenges/disabilities, and they will be disseminated via publications, presentations and stakeholder meetings. TRIAL REGISTRATION NUMBERREGISTRATION: Open Science Framework: 10.17605/OSF.IO/NSD2W.
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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 | 0.209 | 0.228 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.011 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.148 | 0.045 |
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".