Involving individuals with dementia as co-researchers in analysis of findings from a qualitative study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Patient and public involvement is widely accepted as good practice in dementia research contributing substantial benefits to research quality. Reports detailing involvement of individuals with dementia as co-researchers, more specifically in analysis of findings are lacking. This paper reports an exercise involving individuals with dementia as co-researchers in a qualitative analysis. Data was from anonymised extracts of interviews with people with dementia who had participated in a multistage study on risk communication in dementia care, relating to concepts and communication of risk. Co-researchers were involved in deriving meaning from the data, identifying and connecting themes. The analysis process is described, reflections on the exercise provided and impact discussed. The session improved overall research quality by enhancing validity of the findings through application of multiple perspectives while also generating sub-themes for exploration in subsequent interviews. Development of guidance for involving individuals with dementia in analysis of research findings is needed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it