Latent variables in cognitive decline: introducing a behavioral-relational factor

Introduction Latent variable analyses have been used to model the cognitive and functional (cf) decline associated with cognitive changes. The present study replicated and expanded upon this latent variable approach to include a second factor reflecting caregiver burden and behavioral and psychological symptoms of dementia (br).Methods This study used ADNI data from 422 consented Wave 4 participants who had completed a MoCA, Functional Activity Questionnaire, Logical Memory II (delayed memory task), Trails Making Test – Part B, Neuropsychiatric Inventory, and Geriatric Depression Scale. Of the participants included in the analysis, 239 were considered cognitively normal, 110 had a diagnosis of MCI and 27 had a diagnosis of dementia.Results Confirmatory factor analysis supported a two-factor model (CFI = .964; RMSEA = .091). All cognitive and functional measures loaded significantly on the cf factor (range: r = -.707 to .747; ps < .0001). All behavioral-relational measures loaded significantly on the br factor (range: r = .237 to .760; ps < .0001). Additionally, both latent variables were significantly associated with diagnosis type, such that cf declined and br increased with diagnosis severity.Discussion This current study findings emphasize the importance of assessing cognitive performance from a whole-person perspective. Future research should focus on using these factors to predict dementia-related outcomes (e.g. nursing home placement, progression of decline).

Authors

Institutions

Publication Details

Journal
Journal of Clinical and Experimental Neuropsychology
Published
2026-07-23
DOI
https://doi.org/10.1080/13803395.2026.2703678
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Latent variables in cognitive decline: introducing a behavioral-relational factor

Benjamin T. Mast, Peeples Lg, Lauren Chrzanowski, For the Alzheimer’s Disease Neuroimaging Initiative
Journal of Clinical and Experimental Neuropsychology
Dementia and Cognitive Impairment Research
article

Latent variables in cognitive decline: introducing a behavioral-relational factor

Benjamin T. Mast, Peeples Lg, Lauren Chrzanowski, For the Alzheimer’s Disease Neuroimaging Initiative
article en

Abstract

Introduction Latent variable analyses have been used to model the cognitive and functional (cf) decline associated with cognitive changes. The present study replicated and expanded upon this latent variable approach to include a second factor reflecting caregiver burden and behavioral and psychological symptoms of dementia (br).Methods This study used ADNI data from 422 consented Wave 4 participants who had completed a MoCA, Functional Activity Questionnaire, Logical Memory II (delayed memory task), Trails Making Test – Part B, Neuropsychiatric Inventory, and Geriatric Depression Scale. Of the participants included in the analysis, 239 were considered cognitively normal, 110 had a diagnosis of MCI and 27 had a diagnosis of dementia.Results Confirmatory factor analysis supported a two-factor model (CFI = .964; RMSEA = .091). All cognitive and functional measures loaded significantly on the cf factor (range: r = -.707 to .747; ps < .0001). All behavioral-relational measures loaded significantly on the br factor (range: r = .237 to .760; ps < .0001). Additionally, both latent variables were significantly associated with diagnosis type, such that cf declined and br increased with diagnosis severity.Discussion This current study findings emphasize the importance of assessing cognitive performance from a whole-person perspective. Future research should focus on using these factors to predict dementia-related outcomes (e.g. nursing home placement, progression of decline).

Journal of Clinical and Experimental Neuropsychology
University of Louisville Hospital (US)
Openalex Percentile: Top 8%
Dementia and Cognitive Impairment Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.