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The stability of neuropsychiatric subsyndromes in Alzheimer's disease
Author(s) -
Connors Michael H.,
Seeher Katrin M.,
Crawford John,
Ames David,
Woodward Michael,
Brodaty Henry
Publication year - 2018
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2018.02.006
Subject(s) - confirmatory factor analysis , disease , time point , psychology , principal component analysis , alzheimer's disease , clinical psychology , factor analysis , intervention (counseling) , medicine , psychiatry , structural equation modeling , econometrics , statistics , computer science , artificial intelligence , philosophy , mathematics , economics , aesthetics
Abstract Introduction Neuropsychiatric symptoms are common in Alzheimer's disease. Previous research has attempted to identify subsyndromes—sets of symptoms related to one another—to clarify underlying mechanisms and treatment targets. We examined the stability of these subsyndromes over time. Methods We administered the Neuropsychiatric Inventory annually for 3 years to 447 patients with Alzheimer's disease recruited from memory clinics. We conducted principal component analyses at each time point and multiple‐group confirmatory factor analyses across time. Results Principal component analyses showed that no two time points shared the same factor structure. Factor solutions did not exhibit strong simple structures and substantial cross‐loadings were common. Confirmatory analysis revealed significant differences in factor loadings and model fit over time. Discussion Symptoms cannot be neatly partitioned into discrete clusters that are stable over time. The findings highlight the significant challenges that clinicians and caregivers face and may help explain the lack of success in intervention studies.