Participatory development of a framework to actively involve people living with dementia and those from their social network, and healthcare professionals in conducting a systematic review: the DECIDE-SR protocol
Bibliographic record
Abstract
Abstract Background Systematic reviews summarize and evaluate relevant studies to contribute to evidence-based practice. Internationally, researchers have reached a consensus that the active involvement of the public leads to better research. Despite this agreement, there are many reviews of research concerning healthcare interventions intended to promote the care of people living with dementia and those from their social network (e.g., close contacts, both family and non-family members) primarily involve only healthcare professionals and other experts. Due to the lack of a dementia-sensitive framework to actively involve people living with dementia and those from their social network, and healthcare professionals as co-researchers in systematic reviews, it is important to develop a framework to inform practice. Methods For this framework development process, we will recruit four people living with dementia and a total of four people from their social network, and three healthcare professionals working in acute or long-term care settings. We will conduct regular meetings with these groups of the public and healthcare professionals to include them in all stages of the systematic review. We will also identify and develop methods necessary to ensure meaningful involvement. The results will be documented and analyzed for the development of a framework. For the planning and preparation for these meetings, as well as the conduct of the meetings themselves, we will be guided by the principles of the INVOLVE approach. In addition, the ACTIVE framework will be used to guide the degree of involvement and the stage in the review process. Discussion We assume that our transparent approach to the development of a framework to support the active involvement of people living with dementia and those from their social network, and healthcare professionals in systematic reviews will serve as an impetus for and provide guidance to other researchers with the goal of increasing researchers’ focus on this topic and facilitating systematic reviews that apply participatory approaches. Trial registration: Trial registration is unnecessary as no intervention study will be conducted.
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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 | 0.470 | 0.494 |
| Meta-epidemiology (narrow) | 0.006 | 0.008 |
| Meta-epidemiology (broad) | 0.010 | 0.015 |
| Bibliometrics | 0.018 | 0.012 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.009 | 0.018 |
| Research integrity | 0.016 | 0.014 |
| Insufficient payload (model declined to judge) | 0.035 | 0.010 |
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".