P1‐277: THE ROLE OF THE MILD BEHAVIORAL IMPAIRMENT‐CHECKLIST IN PREDICTING FUNCTIONALITY IN THE CONTINUUM FROM NORMAL AGING TO MILD COGNITIVE IMPAIRMENT
Bibliographic record
Abstract
Instrumental Activities of Daily Living (IADL) are necessary for independent functioning in society (Sikkes et al., 2009). Neuropsychiatric symptoms (NPS) may produce functional impairments. The Mild Behavioral Impairment checklist (MBI-C) is an instrument to valuate neurobehavioral symptoms on the following domains: decreased motivation, emotional dysregulation, and impulse dyscontrol, social inappropriateness and abnormal perception or thought content (Ismail et al., 2017). Our objective was to explore the role of NPS predicting IADL in the continuum from normal aging to Mild Cognitive Impairment (MCI). Three hundred five participants, recruited from primary care health centers, performed an extensive neuropsychological evaluation. One hundred seventy-five were diagnosed as Cognitively Unimpaired, 23 as Subjective Cognitive Decline, and 107 as MCI. Sociodemographic and morbidity (Charlson Comorbidity Index -CCI-) data were collected. Functionality was measured with the Spanish version of the Amsterdam IADL-Questionnaire (A-IADL-Q), a 70-items informant-based computerized questionnaire that assesses extended IADL (Facal et al., 2018). Cognitive performance was measured with the Cambridge Cognitive Assessment-Revised (CAMCOG-R). NPS were measured with the MBI-C, a case ascertainment instrument operationalizing the MBI criteria (Ismail et al., 2017), and with the Geriatric Depression Scale-15 (GDS-15). Multiple linear regression analyzes were performed to explore the predicting value of these sociodemographic, cognitive and behavioral measures on A-IADL-Q total score. A-IADL-Q total score was significantly predicted by the CAMCOG-R and the MBI-C. CCI and GDS-15 were not significant, and age and years of education did not remain significant when the variables CAMCOG-R (Fig. 1) and, to a lesser extent, MBI-C (Fig. 2) were included in the model. Model 6 (Table 1) showed the higher percentage of explained variance (33%) and an acceptable fit pattern (Fig. 3).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".