Behavioural Measures in Frontotemporal Lobar Dementia and Other Dementias: The Utility of the Frontal Behavioural Inventory and the Neuropsychiatric Inventory in a National Cohort Study
Bibliographic record
Abstract
BACKGROUND: Distinguishing between patients with frontotemporal lobar dementia (FTLD) and other dementing illnesses remains a difficult task for many clinicians. In this study, we aimed to provide further evidence for the construct validity of the frontal behavioural inventory (FBI) and assess its utility in differentiating FTLD patients from other groups using data from the Canadian Collaborative Cohort of Related Dementias (ACCORD) study. METHOD: Baseline scores on the FBI and neuropsychiatric inventory (NPI) were compared among several clinical groups (n = 177). RESULTS: The FBI discriminated a higher percentage of FTLD patients (>75% correct classification) from Alzheimer's disease and other groups compared to the NPI (54.2%). CONCLUSION: This study provides good evidence for convergent validity between the FBI and NPI (r = 0.72), indicating that both measures capture similar psychopathology in this nationwide cohort.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".