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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Evaluating the Effectiveness of Cognitive Interventions for Healthy and Mild Cognitive Impairment Adults: A
Giuseppe Forte1, Francesca Favieri1, Ilaria Corbo1
1Department of Dynamic and Clinical Psychology, and Health Studies, Sapienza University of Rome, Rome, Italy.
Abstract:
Extensive research indicates that cognitive interventions can lead to a general improvement in cognitive functioning throughout the lifespan. In this study, we evaluate the causal evidence supporting this relationship in healthy older adults and older adults with mild cognitive impairment (MCI) by means of an umbrella meta-analysis of meta-analyses. The meta-analytic studies were identified through systematic searches in electronic databases (CINAHL, Cochrane Library, PsycINFO, PubMed, Scopus, and Web of Science) and were included in this umbrella meta-analysis if they examined the effects of cognitive interventions, not mixed with other approaches, in healthy older adults and individuals with MCI. Of the 9734 publications that were screened, 25 met the inclusion criteria and reported comprehensive data suitable for statistical analysis. Findings showed that although the effect-sizes across studies were variable, they were consistently positive, indicating a significant impact of different cognitive interventions on global cognitive functioning, memory, executive functions, visuospatial ability, and processing speed compared to control groups. This finding suggests that the efficacy of cognitive treatments is the best option for preclinical forms of aging, such as MCI. The underlying mechanisms of the observed improvements and their implications for further studies and clinical practice are discussed.
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