Social, ethical, and epistemological aspects of dementia prevention: the three-country BEAD study
Bibliographic record
Abstract
Objective: According to a 2024 Lancet report, there are at least 14 modifiable risk factors for dementia, the management of which could reduce dementia cases by almost 50%. Most of these risk factors are overrepresented among disadvantaged groups. This social etiology and its consequences, however, are not always acknowledged by stakeholders, with prevention often articulated as the responsibility of the individual. The objective of this study was to better understand how dementia prevention is articulated among stakeholders and how “the social” plays out in experts’ accounts. Methods: This exploratory study employed opportunistic and snowball sampling and was based on a total of 64 semi-structured interviews with dementia experts from three countries (Germany, Canada, and Switzerland). Results: In expert models of dementia prevention, social factors were often recognized, but recommendations for change were mostly limited to educational interventions rather than structural changes that would allow preventing risk factors. Conclusion: Current public health campaigns targeting the “preventive individual” should be rethought.
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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 | 0.037 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| 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; 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".