Comparison of ADL and Symptoms in Elders with Dementia according to Family Resiliency
Bibliographic record
Abstract
Purpose: The purpose of this study was to identify family resiliency, ADL in elders with dementia, and symptom for families with an elder with dementia. Method: The participants were 102 people who were caregivers to elders with dementia and who visited the out-patient department at S. hospital for follow up care. Data were collected from August to October 2003 using a questionnaire. The collected data were analyzed using descriptive statistics and t-test aided by the SPSS/PC. Result: Family resiliency for the whole sample was within normal limits but when the sample was quarter-divided by good and poor family resiliency, based on established cut-off scores, there were differences for some characteristics according to good/poor family resiliency. These differences were for perceived health state of caregivers (t=-2.78, p=.008), economic state of family (t=-3.34, p=.002), and ADL (t=-2.56, p=.014). Conclusion: Future research should focus on the way in which family resiliency can be enhanced and on the effects of interventions for those caregivers who report poor family resiliency.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 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".