Protocol for the Rare Dementia Support Impact study: RDS Impact
Bibliographic record
Abstract
OBJECTIVES: The Rare Dementia Support (RDS) Impact study will be the first major study of the value of multicomponent support groups for people living with or supporting someone with a rare form of dementia. The multicentre study aims to evaluate the impact of multicomponent support offered and delivered to people living with a rare form of dementia, comprising the following five work packages (WPs): (a) longitudinal cohort interviews, (b) theoretical development, (c) developing measures, (d) novel interventions, and (e) economic analysis. METHODS: This is a mixed-methods design, including a longitudinal cohort study (quantitative and qualitative) and a feasibility randomised control trial (RCT). A cohort of more than 1000 individuals will be invited to participate. The primary and secondary outcomes will be in part determined through a co-design nominal groups technique prestudy involving caregivers to people living with a diagnosis of a rare dementia. Quantitative analyses of differences and predictors will be based on prespecified hypotheses. A variety of quantitative (eg, analysis of variance [ANOVA] and multiple linear regression techniques), qualitative (eg, thematic analysis [TA]), and innovative analytical methods will also be developed and applied by involving the arts as a research method. RESULTS: The UCL Research Ethics Committee have approved this study. Data collection commenced in January 2020. CONCLUSIONS: The study will capture information through a combination of longitudinal interviews, questionnaires and scales, and novel creative data collection methods. The notion of "impact" in the context of support for rare dementias will involve theoretical development, novel measures and methods of support interventions, and health economic analyses.
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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 | 0.068 | 0.069 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.167 | 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".