Simple Brain Training Cuts Dementia Risk Decades Later, Study Finds Speed-of-processing cognitive training in older adults significantly reduced dementia risk over 20 years, outperforming memory and reasoning training. Its adaptive, implicit learning approach may explain the benefit.

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Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults Using Source-Free Domain Adaptation: Algorithm Development and Validation Background: Cognitive decline in the aging population presents an unprecedented challenge worldwide. Recent research has shown the potential of cognitive training programs to mitigate cognitive decline. However, these interventions require sustained adherence to be effective, which can be challenging. Objective: In this study, we aim to enhance the accuracy of predicting adherence patterns in cognitive training programs for older adults, with the goal of developing personalized support systems that promote adherence and improve cognitive outcomes. Methods: A major challenge in developing deep neural networks for predicting adherence patterns is the limited availability of individual participants’ training data. Although domain adaptation techniques can address this issue by leveraging training data from other clinical studies, our research considers a more practical scenario where the use of such data from other studies is restricted due to privacy and confidentiality concerns. Therefore, we used source-free domain adaptation (SFDA), which uses models trained on other cognitive studies without requiring access to the corresponding datasets. To the best of our knowledge, this is the first effort to use SFDA to predict older adults’ daily adherence to cognitive training programs. Results: Using data from 3 previously conducted cognitive training intervention studies, our results demonstrated the efficacy of deep learning models combined with SFDA to accurately predict adherence lapses while addressing data privacy concerns. Conclusions: Our findings indicate that deep learning and SFDA techniques can be useful in the development of adherence support systems for computerized cognitive training, aimed at improving the health and well-being of older adults.

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Long-term follow-up suggests targeted speed training may reduce dementia diagnoses later in life, raising new questions for prevention policy.

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Full article: doi.org/10.1007/s41465-025-00342-4

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New preregistered study: A week of cognitive training can reduce automatic avoidance tendencies—showing that Pavlovian biases aren’t fixed, but flexible and trainable: https://psycnet.apa.org/fulltext/2027-02467-001.html #CognitiveTraining #DecisionMaking #ComputationalPsychi

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Long-Term Effects of Mobile-Based Metamemory Cognitive Training in Older Adults With Mild Cognitive Impairment: 15-Month Prospective Single-Arm Longitudinal Study Background: Mild cognitive impairment (MCI) is an intermediate state between normal aging and dementia, characterized by subjective cognitive decline and objective memory impairment. Cognitive training has consistently shown short-term benefits for individuals with MCI, but evidence on the long-term effectiveness is extremely limited. Given the progressive nature of MCI and the need for sustainable strategies to delay cognitive decline, research on the long-term impact of cognitive training is necessary and timely. Mobile-based platforms offer a promising solution by enhancing accessibility and adherence, but their durability of effect over extended periods remains underexplored. Objective: This study aimed to evaluate the long-term effects of a mobile-based cognitive training app on the cognitive function of older adults with MCI. Methods: In total, 28 older adults with MCI used Cogthera, a mobile cognitive training app based on metamemory training. Participants completed 2 training sessions daily for 3 months, and 9 (32%) continued for an additional 12 months. Cognitive function and quality of life were assessed using the Alzheimer’s Disease Assessment Scale-Cognitive Subscale 14 and EQ-5D-5L. Results: Cognitive function improved over 15 months, as measured by Alzheimer’s Disease Assessment Scale-Cognitive Subscale (F2,35.56=7.08; P=.003). EQ-5D-5L scores increased at 3 months but did not show sustained change at 15 months (F2,42.14=3.40; P=.04). Greater cognitive improvements were associated with younger age, higher functional status, and lower baseline cognitive function. Conclusions: This study showed that long-term use of a mobile-based metamemory cognitive training app was associated with cognitive improvements over 15 months. Although limited by the small sample size and the absence of a control group, these findings suggest potential for mobile cognitive training as a sustainable intervention that warrants validation in larger trials.

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