Measuring negative and positive caregiving experiences: a psychometric analysis of the Caregiver Strain Index Expanded
Bibliographic record
Abstract
OBJECTIVE: To compare the psychometric properties of the Caregiver Strain Index Expanded with those of the original Caregiver Strain Index among partners of stroke patients. DESIGN AND SUBJECTS: Cross-sectional validation study among 173 caregivers of stroke patients six months post-stroke. OUTCOME MEASURE: Caregiver Strain Index Expanded. Reference measures: Hospital Anxiety and Depression Scale, two questions on life satisfaction, Barthel Index and Montreal Cognitive Assessment. Additionally, National Institutes of Health Stroke Scale. RESULTS: Neither the Caregiver Strain Index Expanded nor the original Caregiver Strain Index showed floor or ceiling effects. The sum score of the positive items showed a ceiling effect and was skewed to the right (2.20). Principal component analysis revealed no clear underlying item clustering. Alpha values of the Caregiver Strain Index Expanded and the original Caregiver Strain Index were good (0.82 and 0.83), but the alpha value of the positive subscale of the Caregiver Strain Index Expanded was too low (0.51). Convergent validity was confirmed for the Caregiver Strain Index Expanded, the original Caregiver Strain Index and the positive subscale. The Caregiver Strain Index Expanded and the original Caregiver Strain Index showed nearly identical correlations with the reference measures. Negative caregiving experiences were more strongly related to partners' mood and life satisfaction than positive caregiving experiences. In the regression analyses, the positive subscale showed little added value in predicting partners' mood and life satisfaction. CONCLUSION: The addition of five positively phrased items does not improve the psychometric properties of the Caregiver Strain Index.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".