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Background: Even though investigating predictors of intervention success (e.g Cognitive Training, CT) is gaining more and more interest in the light of an individualized medicine, results on specific predictors of intervention success in the overall field are mixed and inconsistent due to different and sometimes inappropriate statistical methods used. Therefore, the present paper gives a guidance on the appropriate use of multiple regression analyses to identify predictors of CT and similar non-pharmacological interventions., Methods: We simulated data based on a predefined true model and ran a series of different analyses to evaluate their performance in retrieving the true model coefficients. The true model consisted of a 2 (between: experimental vs. control group) × 2 (within: pre- vs. post-treatment) design with two continuous predictors, one of which predicted the success in the intervention group and the other did not. In analyzing the data, we considered four commonly used dependent variables (post-test score, absolute change score, relative change score, residual score), five regression models, eight sample sizes, and four levels of reliability., Results: Our results indicated that a regression model including the investigated predictor, Group (experimental vs. control), pre-test score, and the interaction between the investigated predictor and the Group as predictors, and the absolute change score as the dependent variable seemed most convenient for the given experimental design. Although the pre-test score should be included as a predictor in the regression model for reasons of statistical power, its coefficient should not be interpreted because even if there is no true relationship, a negative and statistically significant regression coefficient commonly emerges., Conclusion: Employing simulation methods, theoretical reasoning, and mathematical derivations, we were able to derive recommendations regarding the analysis of data in one of the most prevalent experimental designs in research on CT and external predictors of CT success. These insights can contribute to the application of considered data analyses in future studies and facilitate cumulative knowledge gain.

Identifying factors predicting effects of cognitive trainings (CT) is important for developing trainings for individuals with specific profiles. The objective of the present study was to evaluate predictors of CT success in several cognitive domains directly after and 1 year after a 7-week group CT in healthy older adults. Sociodemographic variables, baseline cognitive performance, physical activity parameters, apolipoprotein E-4 (apoE-4), levels of insulin-like growth factor 1 (IGF-1), brain-derived neurotrophic factor (BDNF), and vascular endothelial growth factor (VEGF) were analysed as possible predictors of CT success. Outcomes were assessed directly after training  and 1 year after CT. Results indicate that lower initial baseline performance was a significant predictor for CT success in most of the investigated domains. All tested predictors (except age and BDNF) predicted CT success in different domains. Our data indicate that healthy older adults with lower cognitive baseline scores show stronger benefits of a CT group intervention.

Background: Cognitive training has been shown to improve cognitive functions in healthy older adults. However, little is known about which specific variables are responsible for the improvement., Objective: Our aim was to evaluate whether healthy older adults benefit more from a structured cognitive training program than an unstructured brain jogging program and to identify possible predictors for training success, including apolipoprotein E4 (apoE4)., Methods: In a randomized controlled trial, participants completed either a 6-week structured cognitive training program (n=35) or a 6-week unstructured brain jogging program (n=35). A control group received no training and was not part of the randomization procedure (n=35). Overall, 105 participants were included in the training data analyses, focusing on verbal memory, attention, and executive functions. Data from an additional 45 previously trained, healthy older adults were used for the predictor analysis., Results: A significant Time×Training interaction in favor of the structured cognitive training program was found in verbal memory. Low baseline performance on neuropsychological tests was a significant predictor for benefits in verbal memory, attention, and executive functions. A subgroup analysis (n=35) revealed that only noncarriers of the apoE4 allele showed significant gains in long-term verbal memory and attention., Conclusions: Our results support the greater effectiveness of structured cognitive training on verbal memory compared with brain jogging and no training. The success of this type of training program may be predicted by sociodemographic, cognitive, and genetic variables.

Background: Cognitive dysfunction is one of the most prevalent non-motor symptoms in Parkinson's disease (PD), often experienced as more debilitating for patients and caregivers than motor problems. Therefore, a deeper understanding of the course of cognitive decline and the identification of valid progression markers for Parkinson's disease dementia (PDD) is essential., Objective: This systematic review summarizes the current state of knowledge on cognitive decline over time by reporting effect sizes of cognitive changes in neuropsychological tests., Methods: 1368 studies were identified by a PubMed database search and 25 studies by additionally scanning previous literature. After screening all records, including 69 full-text article reviews, 12 longitudinal studies on the progression of cognitive decline in PD met our criteria (e.g., sample size ≥50 patients)., Results: Only a few studies monitored cognitive decline over a longer period (>4 years). Most studies focused on the evaluation of change in global cognitive state by use of the Mini-Mental State Examination, whereas the use of neuropsychological tests was highly heterogenic among studies. Only one study evaluated patients' cognitive performance in all specified domains (executive function, attention & working memory, memory, language, and visual-spatial function) allowing for diagnosis of cognitive impairment according to consensus guidelines. Medium to strong effect sizes could only be observed in studies with follow-up intervals of four years or longer., Conclusions: The results emphasize the need for the assessment of larger PD cohorts over longer periods of follow-up with a comprehensive neuropsychological battery.