Goal setting and attainment in Alzheimer's disease patients treated with donepezil
Bibliographic record
Abstract
OBJECTIVES: To understand the treatment goals of Alzheimer's disease (AD) patients, carers, and physicians; to estimate whether clinically important goals are met during treatment with donepezil; and to compare a measure of goal attainment with standard measures used to evaluate AD treatment. METHODS: In a 12 month phase IV trial, 108 patients with mild to moderate AD, their primary carers, and treating physicians set goals assigned to five domains, using Goal Attainment Scaling (GAS) as the primary outcome. Goal attainment was assessed quarterly. GAS scores were correlated with standard outcomes, including the Alzheimer's Disease Assessment Scale-Cognitive (ADAS-cog), and the Clinician's Interview-Based Impression of Change-Plus (CIBIC-plus). RESULTS: Physicians set fewer goals (342, mean (SD) per patient=3 (1)) than patients/carers (855, mean=9 (3)), particularly in leisure (20% by physicians compared with 76% by patients/carers), and social interaction (24% versus 49%). Physicians observed statistically significant improvement in global goal attainment for six months, and patients/carers for nine months. Patients/carers described consistent goal attainment, whereas physicians observed variable effects, such as decline in cognition but improved social interaction and behaviour. Physician global GAS scores correlated highly with the CIBIC-plus at weeks 12 (r= -0.82) and 52 (r=-0.80), but not with the ADAS-cog (r=0.12 and r=-0.45, respectively). Patient/carer global GAS scores correlated moderately with the physician's CIBIC-plus (week 12 r=-0.51; week 52 r=-0.56), and nominally with the ADAS-cog. CONCLUSIONS: Patients/carers and physicians differ in their expectations and impressions of treatment effects. Clinically important changes correlated only modestly with psychometric tests. Attainment of treatment goals does not accord with a simplistic model in which successful AD treatment means that all declines uniformly improve.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".