Stakeholder involvement in a Cochrane review of physical rehabilitation after stroke: Description and reflections
Bibliographic record
Abstract
Introduction: It is good practice to involve stakeholders in systematic reviews, but it is not clear how best to involve them. Aim: To describe and reflect on the stakeholder involvement within an update of a Cochrane review of physical rehabilitation after stroke. Methods: A stakeholder group, comprising 15 stroke survivors, carers, and physiotherapists from across the United Kingdom, were recruited and contributed throughout the process of the review. A framework was used to describe when and how stakeholders were involved. Stakeholders provided feedback on their involvement after meetings. An amended version of a validated patient engagement tool was used to collect reflections on the stakeholder involvement process. Results: Five stakeholder meetings were held throughout the review process, supplemented by additional communication. Several changes were made to the review structure, analyses, and wording as a direct result of the stakeholder involvement. Stakeholders and researchers agreed that stakeholders' contributions were taken seriously and influenced the review. Stakeholders felt that they were given the chance to share their views and that information was shared well before, during, and after each meeting to help them to contribute knowledgeably in the process. Stakeholder reflections highlighted a number of key lessons relating to stakeholder involvement, including process of reflection and feedback, use of remote/virtual meetings, need for adequate time and funding, tensions experienced by clinicians, and recruitment considerations. Conclusions: We describe and reflect on stakeholder involvement in a systematic review and explores practical ways to support meaningful engagement during systematic review production. Our experience supports the view that coproducing reviews with stakeholders can make systematic reviews more relevant and meaningful. Our approach and experiences can be used to inform future review coproduction, supporting development of useful reviews that will improve clinical practice.
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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 | 0.367 | 0.561 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.012 | 0.023 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.010 | 0.018 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".