A Prospective Study of Caregiver Burden in an Outpatient Comprehensive Geriatric Assessment Program
Bibliographic record
Abstract
Abstract This study examined the determinants of caregiver burden on admission to a comprehensive geriatric assessment (CGA) program and identified the predictors of a reduction in caregiver burden at four-month follow-up. A total of 141 patient/caregiver dyads participated (76.6% of patients had a diagnosis of dementia). Using multiple regression analysis, four variables emerged as the determinants of caregiver burden on admission: lower caregiver well-being, higher frequency of patient dysfunctional behaviors, providing assistance with personal care tasks, and dissatisfaction with help received (R2 = 0.55, P < 0.001). At follow-up, there was a statistically significant reduction in caregiver burden only among those who expressed “high” burden on admission (P < 0.05). Higher baseline burden, providing less than 15 hours of weekly assistance, a positive change in caregiver well-being, and the caregivers' perception of sufficiency of help received from informal sources predicted a reduction in burden (R2 = 0.45, P < 0.001). The results inform future risk appraisal and targeting strategies in this setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 teacher head, 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".