A COMPREHENSIVE ALZHEIMER’S AND DEMENTIA CARE PROGRAM (ADCP) FOR PATIENTS AND CAREGIVERS
Bibliographic record
Abstract
Abstract Background Alzheimer’s and related dementias (ADRD) are progressive and associated with behavioral and psychological symptoms (BPSD) contributing to caregiver stress. We report initial impact of implementing UCLA-designed ADCP to support ADRD patients and caregivers. The program centralizes care, utilizing a nurse dementia-care specialist. Methods Prospective repeated measures of ADRD patient/caregiver dyads from 3/2021–7/2022. Measures: BPSD, ADL/IADL, cognition, and caregiver burden, distress and depression. Results Total of 154 patient/caregiver dyads enrolled to-date. 42 have been enrolled for one-year: 23 with complete data, 5 pending follow-up, 14 disenrolled (2 expired, 3 to hospice, 2 moved, 7 lost contact). For 23 patients with baseline and follow up, Neuropsychiatric Inventory Questionnaire decreased from 16.3 to 13.1 (p=0.170), Patient Health Questionnaire-9 (PHQ-9) for caregivers decreased (3.5 to 2.2, p=0.044), Montreal Cognitive Assessment decreased from 11.3 to 8.4 (p=0.045), and Dementia Burden Scale (DBS) showed nonsignificant decrease, 20.6 to 18.4 (p=0.312). Cornell Scale for Depression in Dementia was unchanged, 5.67 to 5.14 (p=0.380), and ADL and IADL decreased one year after enrollment, from 4.05 to 2.36 (p < 0.01) and 1.38 to 0.238 (p < 0.01) respectively. Conclusion Although attrition rate was high for the small sample (1/3 of dyads enrolled in the program for a year), there were improvements in some metrics for both patients and caregivers, despite the expected decline in cognitive function and ADL/IADL. As data is accrued, we anticipate it will identify patients and support resources that will be most beneficial.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".