The Role of Individual Characteristics in Predicting Short- and Long-Term Cognitive and Psychological Benefits of Cognitive Stimulation Therapy for Mild-to-Moderate Dementia

Abstract

Introduction: This study examined the role of individual characteristics in predicting short- and long-term benefits of the Italian version of Cognitive Stimulation Therapy (CST-IT), an evidence-based intervention for people with mild-to-moderate dementia.Materials and Methods: Data were drawn from a sample (N = 123) of people with dementia (PwD) who took part in a multicenter controlled clinical trial of CST-IT. Assessments at pre-test, immediately after completing the treatment, and 3 months later investigated the following outcomes: general cognitive functioning and language, mood and behavior, everyday functioning, and quality of life. Age, education and baseline (pre-test) cognitive functioning, mood (depression) and behavioral and neuropsychiatric symptoms were considered as predictors of any short- and long-term benefits.Results: Linear mixed-effects models showed that different individual characteristics -particularly education and age- influenced the benefits of CST-IT, depending on the outcome measures considered. Higher education predicted larger gains in general cognitive functioning and, along with less severe depressive symptoms, in language (magnification effects). Older age was associated with positive changes in mood (compensation effects). Albeit very modestly, older age was also associated with larger gains in everyday functioning (compensation effects). Gains in quality of life were predicted by older age and lower education (compensation effects). Baseline cognitive functioning, mood and/or behavioral symptoms broadly influenced performance too, but their role again depended on the outcomes considered.Discussion: These findings underscore the importance of considering and further exploring how psychosocial interventions like CST are affected by individual characteristics in order to maximize their efficacy for PwD.