Abstract
AbstractBackgroundNeuropsychiatric symptoms are behavioural manifestations highly prevalent along the Alzheimer’s disease (AD) continuum, including at the stage of Mild Cognitive Impairment (MCI). Although various projects have investigated the factors that underpin these symptoms, the most stable clustering pattern is still matter for debate; furthermore, to our knowledge, no study has investigated, longitudinally, how clusters might change due to development of AD pathology. Therefore, our objective is to investigate neuropsychiatric clusters over time, in a large sample of MCI and AD dementia patients.MethodsSamples were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu), using data from the Neuropsychiatric Inventory (NPI), from the baseline assessment visit, followed up yearly until data recorded at month 72. The samples included MCI and AD dementia patients (based on ADNI’s inclusion criteria), presenting with at least one neuropsychiatric symptom at the time‐point selected. Using SPSS (Version 28), we performed a series of exploratory principal components analyses (PCA), Varimax rotation, and principal axis factor analyses (FA), comparing Promax and Direct Oblimin rotations.ResultsThe best‐fitting structure was interpreted at each time‐point, based on: Eigenvalues>1, items’ loadings>0.4, scree plot patterns, minimum 40% of variance explained by the model, and independence of factors. Results from both PCA and FA indicated that a unique structure could not be identified, as factors were not stable over time; however, some symptoms tended to load on the same factors across most measurements (i.e. delusions with hallucinations; agitation with depression, anxiety and irritability; to a lesser extent elation with disinhibition; apathy with aberrant motor behaviour, sleep disturbances and appetite disorder).ConclusionsThe available evidence reveals that factors underlying the neuropsychiatric symptoms in a sample of AD and MCI patients are not consistent across the time‐points. However, some symptoms tend to co‐occur across time, with implications, for example, that an investigation into one of those symptoms should consider the presence of the other; furthermore, as clear theoretically driven factors are not distinctively identified at every time‐point, this illustrates the potential importance of sample selection (e.g., disease stage, and/or heterogeneity) on studies of neuropsychiatric symptoms.
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