Mild Behaviour Impairment Checklist (MBI‐C): Is there a difference in ratings between patient and close informant?
Bibliographic record
Abstract
Abstract Background Mild Behavioural Impairment‐Checklist (MBI‐C) is a validated questionnaire that measures sustained later‐life emergent neuropsychiatric symptoms among people with prodromal dementia. Using this checklist as a MBI case ascertainment instrument, the prevalence of MBI was found to be 5.8% in subjective cognitive decline (SCD) and 14.2% in mild cognitive impairment (MCI). While the MBI‐C can be self‐administered or administered through a close informant via face‐to‐face or phone interviews, it is unknown whether patients and close‐informants differentially report on the MBI‐C. Here, we aim to examine the differences in self‐administered and close‐informant administered MBI‐C scores in a specialty clinic population. Method 87 (25 SCD and 62 MCI) patients from the Singapore National Neuroscience Institute memory clinic completed the MBI‐C and Geriatric Depression Scale (GDS)4. Close‐informants completed the MBI‐C and Zarit caregiver burden scale (Zarit)5. The MBI‐C is a 34‐item questionnaire organized into five domains; 1) motivation, 2) emotional regulation, 3) impulse control, 4) social cognition, and 5) abnormal thoughts. MBI is defined by an MBI‐C total score of >6.5 in MCI 3 and a >8.5 total score in SCI2. Paired sample T‐test evaluated the difference in MBI‐C scores between patients and close‐informants. Pearson correlation test evaluated the associations between MBI‐C with GDS and Zarit scores. Result Out of 87 participants (Mage= 67.62, SD=9.08), 29 participants were diagnosed with MBI. The frequency of MBI did not differ between SCI and MCI (40% in SCI and 30% in MCI). We found that MBI‐C domain scores did not differ significantly between patients and close‐informants (p>0.05). GDS scores positively correlated with MBI total score (p<0.01), motivation (p<0.01), emotional regulation (p<0.01), impulse control (p<0.01), social cognition (p=0.001) and abnormal thoughts (p=0.018). Zarit scores positively correlated with MBI total score (p=0.017) and impulse control (p=0.009). Conclusion MBI is common in our Asian clinic population with preclinical prodromal dementia diagnosed using the MBI‐C and was associated with greater caregiver burden and depressive symptoms. Importantly, we found that patients and their close‐informants do not report differently on the MBI‐C. Our findings suggest that both patients and close‐informants may provide reliable measures of the patient’s neuropsychiatric symptoms using the MBI‐C.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.004 | 0.001 |
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".