The Behavioural Neurology Assessment
Bibliographic record
Abstract
BACKGROUND: We present information regarding the standardization, reliability and clinical validity of two versions of the Behavioural Neurology Assessment (BNA). The BNA-Long Form consists of 24 subtests within separate domains: Attention, Memory, Language, Visuospatial Function, Executive Function, and Praxis. The BNA-Short Form consists of 13 subtests within the domains of Attention, Memory, Naming, Visuospatial Function and Executive Function. In addition to individual domain indices, a Grand Total score was calculated for both BNA versions. OBJECTIVE: To standardize the administration and scoring and validate the BNA for detection of dementia. METHODS: Standardized normative data were obtained on 115 healthy subjects ranging in age from 50 to 95. Test-retest stability was obtained on 19 subjects and clinical validity was investigated by administering the BNA and Mini-Mental Status Examination (MMSE) to 29 patients with dementia and 29 age-matched healthy subjects (controls). RESULTS: Age had a significant effect on all but the Visuospatial and Praxis indices of the BNA-Long Form and an effect on Naming and Grand Total score of the Short-Form. Internal consistency (Cronbach's coefficient alpha) was .87 and .67 for the Long and Short Forms (.95 and .96 for dementia and control groups combined). Test-retest stability was acceptable. Grand Total indices of both BNA versions showed significant, positive correlations with the MMSE. Both BNA versions had superior sensitivity to dementia relative to the MMSE (.93 versus .79). Specificity was equivalent to the MMSE (.93 versus .97). CONCLUSIONS: Positive predictive values of the BNA and MMSE are equivalent but the BNA provides superior negative predictive value.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.017 | 0.008 |
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".