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Record W7117308555 · doi:10.1002/alz70857_106800

Assessment of the mild behavioral impairment checklist in individuals with subjective cognitive decline and mild cognitive impairment in the BRASCODE cohort

2025· article· en· W7117308555 on OpenAlexaff
Victória Tizeli Souza, Bárbara Loeblein Uebel, Gabriela Raquel Paz Rivas, Simone Sieben da Mota, Bruno de Oliveira De Marchi, Guilherme Da Silva Carvalho, Haniel Bispo De Souza, Lucas Bastos Beltrami, Rhaná Carolina Santos, Sarah Vitória Bristot Carnevalli, Ana Letícia Amorim de Albuquerque, Leonardo Martins de Paula, Manuella Edler Zandoná Giordani, Wyllians Vendramini Borelli, Giovanna Carello‐Collar, Marcia L. Fagundes Chaves, Eduardo R. Zimmer, Raphael Machado Castilhos

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsCognitive impairmentCognitive declineAnxietyCohortChecklistCognitionDepression (economics)Depressive symptoms

Abstract

fetched live from OpenAlex

BACKGROUND: Mild Behavioral Impairment (MBI) is characterized by neuropsychiatric symptoms that may precede cognitive decline in the early stages of neurodegenerative diseases. In Brazil, the study of MBI in individuals with cognitive complaints remains limited. This study aims to evaluate the MBI-Checklist (MBI-C) in individuals with Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI) in the Brazilian Subjective Cognitive Decline (BRASCODE) cohort in southern Brazil. METHODS: Cognitively unimpaired adults >65 years old with cognitive complaints, but no severe clinical or neuropsychiatric illness, are enrolled in the BRASCODE cohort. This analysis includes data from participants who completed the 12-month follow-up. The applied scales included: Mild Behavioral Impairment Checklist (MBI-C) and Memory Complaint Scale (MCS) (participant and informant); Neuropsychiatric Inventory-Questionnaire (NPI-Q) (informant); Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory (GAI), Mini-Mental State Examination (MMSE) (participant); and Clinical Dementia Rating (CDR). We performed a correlation analysis between continuous variables. We considered a p-value < 0.05 as statistically significant. RESULTS: A total of 100 participants completed the 12-month follow-up, of whom 13 were diagnosed with MCI. Table 1 presents demographic and clinical characteristics. MBI-C participant scores correlated positively with depressive (GDS, rho = 0.695, p < 0.0001) and anxiety symptoms (GAI, rho = 0.519, p < 0.0001). MBI-C informant scores showed a strong correlation with NPI-Q (rho = 0.743, p < 0.0001) and the informant's perception of cognitive decline (rho = 0.364, p = 0.0004). A significant correlation was also found between MBI-C informant scores and CDR-SOB (rho = 0.283, p = 0.007). Additionally, MBI-C participant scores were negatively correlated with formal education (rho = -0.387, p = 0.009). No significant correlation was found between MBI-C-participant and MBI-informant scores. CONCLUSION: The MBI-C identified neuropsychiatric symptoms in individuals with SCD and MCI, showing a strong correlation with anxiety and depressive symptoms. Additionally, MBI-C-informant scores were significantly correlated with neuropsychiatric symptoms and cognitive impairment measures. These findings bring attention to the relevance of MBI-C in the behavioral assessment of this population. Research with larger samples is needed to better understand the associations between MBI and cognitive decline in individuals with SCD and MCI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.358
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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