Issues in Recruitment, Retention, and Data Collection in a Longitudinal Nutrition Study of Community-Dwelling Older Adults With Early-Stage Alzheimer's Dementia
Bibliographic record
Abstract
The Nutrition-Memory Study (NMS) followed evolution of nutrition status among elderly community-dwelling individuals with Alzheimer's disease (AD). Participants, age-matched to cognitively intact controls, were recruited from three university hospital memory clinics. Incentives encouraged retention; flexible procedures and caregiver collaboration permitted collection of nutrition information from AD patients. Of 71 patients referred by the clinics, 55 (77.5%) were eligible, 42 (76.4% of eligible) were recruited with their caregivers, and 40 (72.7%) completed the baseline. Thirty-two patient—caregiver dyads completed the first three interviews (58.1% of eligible; 80% of recruited); 26 of the 32 dyads (81.3% of recruited) completed four of the five interviews, and 14 (43.8% of recruited) were seen at all five study visits. Ensuring successful recruitment and retention in this clientele requires strong links between the research team and target community, ensuring relevance of the study to participants, and being mindful of the burden levied on patient—caregiver dyads.
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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 | 0.400 | 0.357 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".