“If it helps someone, then I want to do it”: Perspectives of persons living with dementia on research registry participation
Bibliographic record
Abstract
Registries are an important platform to which persons with dementia and other cognitive impairments can contribute to research studies. Registries also provide an opportunity for patients to stay informed about current studies. Engaging patients in registry development can increase sustainability of a registry and patient retention in clinical registries. We sought the perspective of persons with dementia and their accompanying family members about their registry participation experiences, barriers and facilitators to participation, and potential avenues for improvement of registry processes such as recruitment, data collection, and knowledge translation. Two semi-structured focus groups with persons with dementia and their family members ( n = 18) were conducted and analyzed using thematic content analysis. Participants were recruited from an existing patient registry made up of patients currently being seen in a dementia assessment clinic. The main themes identified included altruistic motives with regards to registry participation; and access to and privacy of personal health information. As electronic health records are becoming more common, understanding barriers and facilitators from the perspectives of people with dementia is essential to inform the future development of cognitive condition-related registries. The results from our focus groups identified engagement strategies and solutions to overcome perceived barriers for individuals experiencing progressive cognitive decline to participate in longitudinal registry projects.
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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 | 0.033 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".