Reliability generalization of responses by care providers to the Zarit Burden Interview
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Zarit Burden Interview (ZBI) is believed to be the most commonly used measure of caregiver burden. Originally developed more than 20 years ago for use with informal caregivers of community dwelling persons with Alzheimer disease, it has subsequently been administered to a diverse range of patient populations, formal or paid caregivers, and translated into numerous languages. Given that the ZBI is now used more broadly than it was initially intended and first validated, the current study applies the reliability generalization meta-analytic procedure to examine the psychometric properties of responses to the ZBI across populations. Multiple regression with categorical variables was performed to identify factors associated with error variance in ZBI reliability estimates (N=138 data points). Number of items, residence of the care recipient (community) and the Hebrew version each contributed significantly to prediction of internal consistency. These differences, however, were found to be relatively small and within accepted parameters. Generally, responses to the ZBI appear reliable across populations of caregivers and patients. Only versions of the ZBI with more or less than 22-items (nonstandard formats) reflect both statistical and meaningful differences in reliability. Where feasible, it is recommended that the 22-item version of the ZBI be used in future research and clinical practice.
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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) | 0.000 | 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 it