Factor Structure and Reliability of the Brain Impairment Behavior Scale
Bibliographic record
Abstract
Stroke is a leading cause of adult disability because of its physical and cognitive consequences. Cognitive changes are important contributors to family caregivers' experiences of emotional distress. To date, measures to assess cognition treat it as a global construct, but it is more likely that unique domains differentially affect family caregivers. The research objectives in this study were to: (1) identify the different domains of cognitive changes in the form of behavioral and psychological symptoms after stroke, and (2) establish the reliability of the Brain Impairment Behavior Scale (BIBS) in measuring cognitive domains. Family caregivers of stroke survivors (N = 300) completed the BIBS as part of cross-sectional and longitudinal studies. A subsample of caregivers completed the BIBS twice, 2 weeks apart, to examine the scale's test-retest reliability. We used exploratory factor analysis to identify four domains of behavioral and psychological symptoms in the BIBS: apathy, depression/emotional distress, comprehension/memory problems, and irritability. Internal consistency for the subscales representing each identified domain ranged from .78 to .91, and the 2-week intra-class correlation coefficients ranged from .75 to .88. Future research and clinical use of this measure will increase our understanding of how specific domains of stroke survivors' behavioral and psychological symptoms affect the well-being of family caregivers.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".