Anja Ophey1, Mandy Roheger1, Ann-Kristin Folkerts1, Nicole Skoetz2, Elke Kalbe1. 1. Department of Medical Psychology | Neuropsychology & Gender Studies, Center for Neuropsychological Diagnostics and Intervention (CeNDI), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany. 2. Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany.
Abstract
Background: Research on predictors of working memory training responsiveness, which could help tailor cognitive interventions individually, is a timely topic in healthy aging. However, the findings are highly heterogeneous, reporting partly conflicting results following a broad spectrum of methodological approaches to answer the question "who benefits most" from working memory training. Objective: The present systematic review aimed to systematically investigate prognostic factors and models for working memory training responsiveness in healthy older adults. Method: Four online databases were searched up to October 2019 (MEDLINE Ovid, Web of Science, CENTRAL, and PsycINFO). The inclusion criteria for full texts were publication in a peer-reviewed journal in English/German, inclusion of healthy older individuals aged ≥55 years without any neurological and/or psychiatric diseases including cognitive impairment, and the investigation of prognostic factors and/or models for training responsiveness after targeted working memory training in terms of direct training effects, near-transfer effects to verbal and visuospatial working memory as well as far-transfer effects to other cognitive domains and behavioral variables. The study design was not limited to randomized controlled trials. Results: A total of 16 studies including n = 675 healthy older individuals with a mean age of 63.0-86.8 years were included in this review. Within these studies, five prognostic model approaches and 18 factor finding approaches were reported. Risk of bias was assessed using the Quality in Prognosis Studies checklist, indicating that important information, especially regarding the domains study attrition, study confounding, and statistical analysis and reporting, was lacking throughout many of the investigated studies. Age, education, intelligence, and baseline performance in working memory or other cognitive domains were frequently investigated predictors across studies. Conclusions: Given the methodological shortcomings of the included studies, no clear conclusions can be drawn, and emerging patterns of prognostic effects will have to survive sound methodological replication in future attempts to promote precision medicine approaches in the context of working memory training. Methodological considerations are discussed, and our findings are embedded to the cognitive aging literature, considering, for example, the cognitive reserve framework and the compensation vs. magnification account. The need for personalized cognitive prevention and intervention methods to counteract cognitive decline in the aging population is high and the potential enormous. Registration: PROSPERO, ID CRD42019142750.
Background: Research on predictors of working memory training responsiveness, which could help tailor cognitive interventions individually, is a timely topic in healthy aging. However, the findings are highly heterogeneous, reporting partly conflicting results following a broad spectrum of methodological approaches to answer the question "who benefits most" from working memory training. Objective: The present systematic review aimed to systematically investigate prognostic factors and models for working memory training responsiveness in healthy older adults. Method: Four online databases were searched up to October 2019 (MEDLINE Ovid, Web of Science, CENTRAL, and PsycINFO). The inclusion criteria for full texts were publication in a peer-reviewed journal in English/German, inclusion of healthy older individuals aged ≥55 years without any neurological and/or psychiatric diseases including cognitive impairment, and the investigation of prognostic factors and/or models for training responsiveness after targeted working memory training in terms of direct training effects, near-transfer effects to verbal and visuospatial working memory as well as far-transfer effects to other cognitive domains and behavioral variables. The study design was not limited to randomized controlled trials. Results: A total of 16 studies including n = 675 healthy older individuals with a mean age of 63.0-86.8 years were included in this review. Within these studies, five prognostic model approaches and 18 factor finding approaches were reported. Risk of bias was assessed using the Quality in Prognosis Studies checklist, indicating that important information, especially regarding the domains study attrition, study confounding, and statistical analysis and reporting, was lacking throughout many of the investigated studies. Age, education, intelligence, and baseline performance in working memory or other cognitive domains were frequently investigated predictors across studies. Conclusions: Given the methodological shortcomings of the included studies, no clear conclusions can be drawn, and emerging patterns of prognostic effects will have to survive sound methodological replication in future attempts to promote precision medicine approaches in the context of working memory training. Methodological considerations are discussed, and our findings are embedded to the cognitive aging literature, considering, for example, the cognitive reserve framework and the compensation vs. magnification account. The need for personalized cognitive prevention and intervention methods to counteract cognitive decline in the aging population is high and the potential enormous. Registration: PROSPERO, ID CRD42019142750.
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