Preliminary Validation Study of the French-Quebec Version of the Mild Behavioral Impairment Checklist
Bibliographic record
Abstract
BACKGROUND: Alzheimer disease dementia may be preceded by cognitive stages during which behavioral and psychological changes can occur. More precisely, behavioral symptoms may be observed during the subjective cognitive decline (SCD) or the mild cognitive impairment (MCI) stages; these symptoms can be measured using the Mild Behavioral Impairment Checklist (MBI-C). OBJECTIVE: To validate the French-Quebec version of the MBI-C in individuals ages 60-85 years. METHOD: The sample included 60 participants (20 MCI, 20 SCD, 20 cognitively healthy) and their informants. To assess the discriminant validity of the MBI-C, a Kruskal-Wallis analysis with a multiple comparisons test was performed on the MBI-C Total score. To determine convergent validity, Spearman correlations were calculated between the MBI-C subscales and a set of validation tools. Finally, test-retest reliability was assessed with Spearman correlations of MBI-C scores between two test sessions. RESULTS: All of the analyses indicated satisfactory psychometric properties for the French-Quebec version of the MBI-C. CONCLUSION: This validation study reveals that the MBI-C can be used successfully in dementia risk assessments. From now on, the use of a validated MBI-C will be possible in the French-Quebec population.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".