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Record W4406050917 · doi:10.1002/alz.090525

The Association Between Mild Behavioral Impairment‐Apathy Symptoms and Cognitive Symptoms

2024· article· en· W4406050917 on OpenAlexaffabout
Daniella Vellone, Dylan X. Guan, Zahinoor Ismail

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsApathyExecutive dysfunctionDementiaPsychologyCognitionClinical psychologyContext (archaeology)Quality of life (healthcare)PsychiatryNeuropsychologyDiseaseMedicineInternal medicinePsychotherapist

Abstract

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BACKGROUND: Apathy may appear as a less acute late-life syndrome; however, it is associated with accelerated progression to dementia and contributes to adverse outcomes for patients and caregivers. These findings are not surprising since apathy can cause individuals to forego activities that improve cardiovascular and cognitive health (e.g., exercise), while inadvertently engaging in behaviors associated with greater dementia risk (e.g., social isolation). The objective of this research was to investigate the association between apathy symptoms (in the context of mild behavioral impairment [MBI)]) and cognitive symptoms. We hypothesized that greater MBI-apathy severity would be significantly associated with greater severity of cognitive symptoms. METHOD: All participants enrolled in the Canadian Platform for Research Online to Investigate Health, Quality of Life, Cognition, Behaviour, Function, and Caregiving in Aging (CAN-PROTECT) aged ≥50 years who had complete MBI-Checklist (MBI-C) and Everyday Cognition (ECog-II) scores were included (n = 1339). Apathy domain scores for interest, initiative, and emotional reactivity were also generated using the six MBI-C apathy items, and total apathy severity was the sum of all three domain scores. Likewise, ECog-II domain scores for memory, language, visual-spatial, and executive function were calculated as the sum of domain items, and total ECog-II severity was the sum of all domains. Negative binomial regressions (zero-inflated, if appropriate) assessed associations between total apathy severity and ECog-II total scores. Domain-specific analyses were also conducted. Covariates included age, sex, years of education, and non-apathy MBI (affective dysregulation, impulse dyscontrol, social inappropriateness, psychosis) score. RESULT: Across all participants (mean age = 64.5±7.4; 79.5% female), higher MBI-apathy scores were associated with more severe cognitive symptoms (standardized β [95%CI], 7.2% [4.3-10.2%]; p<0.001). Higher interest (16.5% [9.4-24.1%]; p<0.01) and initiative (18.4% [11.9-25.4%]; p<0.001) apathy domain scores were associated with more severe cognitive symptoms. Total apathy score was also associated with ECog-II memory (4.9% [2.4-7.4%]; p<0.001), language (5.6% [2.5-8.6%]; p<0.001), visual-spatial (8.3% [3.3-13.2%]; p<0.01), and executive (10.7% [6.7-14.7%]; p<0.001) domain scores. CONCLUSION: These findings provide valuable insight into the complex interplay between apathy and cognitive function, with potential implications for the development of targeted interventions for those affected by apathy-related cognitive deficits.

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 score0.079
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.330
Teacher spread0.306 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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