Objectives: Lifelong learning facilitates active ageing, and intragenerational learning-the process by which older adults learn from their peers-is an effective means of achieving this goal. The present research aims to elucidate the mechanisms and differences between intergenerational and intragenerational learning models for older adults as evidenced by brain-to-brain synchrony.
Methods: Fifty-six instructor-learner dyads completed a study comparing intergenerational and intragenerational learning models, as well as task difficulty. The study utilized a block puzzle task and functional near-infrared spectroscopy (fNIRS) for hyperscanning.
Results: The instructor-learner dyads showed greater interpersonal neural synchrony (INS) and learning acquisition in the intragenerational learning model in the difficult task condition (t (54) = 3.49, p < 0.01), whereas the two learning models yielded similar results in the easy condition (t (54) = 1.96, p = 0.06). In addition, INS and self-efficacy mediated the association between learning models and learning acquisition in older adults (b = 0.14, SEM = 0.04, 95 % CI [0.01 0.16]).
Discussion: This study is the first to provide evidence of interbrain synchrony in an investigation of the intragenerational learning model in older adults. Our findings suggest that intra-learning is as effective as traditional inter-learning and may be more effective in certain contexts, such as difficult tasks. Encouraging intra-learning in community service or educational activities can effectively mitigate the challenge of limited volunteers and enhance learning acquisition among older adults.
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http://dx.doi.org/10.1016/j.exger.2024.112499 | DOI Listing |
Med Sci Sports Exerc
January 2025
Energy Metabolism Section, National Institute of Diabetes, Digestive and Kidney Diseases, Diabetes, Endocrinology, and Obesity Branch, National Institutes of Health (NIH), Bethesda, MD.
Introduction: ActiGraph accelerometers are used extensively to objectively assess physical activity, sedentary behavior, and sleep. Here, we present an objective validation of five generations of ActiGraph sensors to characterize potential differences in output arising from changes to hardware or firmware.
Methods: An orbital shaker generated accelerations from 0 to 3700 milli-g in a randomized order to test the wGT3X-BT, GT9X, CentrePoint Insight Watch (CPIW) 1.
Psychol Aging
January 2025
Department of Psychology, National Taiwan University.
The Socioemotional Selectivity Theory (SST) posits that older and younger adults have different life goals due to differences in perceived remaining lifetime. Younger adults focus more on future-oriented knowledge exploration and forming new friendships, while older adults prioritize present-focused emotional regulation and maintaining close relationships. While previous research has found these age differences manifest in autobiographical textual expressions, their presence in verbal communication remains unexplored.
View Article and Find Full Text PDFJ Nutr
January 2025
School of Public Health, University of California, Berkeley, Berkeley, CA, United States.
Background: Food insecurity (FI) continues to be a significant public health concern and is associated with myriad physical and mental health consequences. Increased understanding of conditions around its occurrence throughout the life course are needed. However, research has been limited due to inadequate measurement tools and study length.
View Article and Find Full Text PDFExp Gerontol
September 2024
Faculty of Psychology, Southwest University, Chongqing, China. Electronic address:
Objectives: Lifelong learning facilitates active ageing, and intragenerational learning-the process by which older adults learn from their peers-is an effective means of achieving this goal. The present research aims to elucidate the mechanisms and differences between intergenerational and intragenerational learning models for older adults as evidenced by brain-to-brain synchrony.
Methods: Fifty-six instructor-learner dyads completed a study comparing intergenerational and intragenerational learning models, as well as task difficulty.
Biophys Physicobiol
September 2023
Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo 153-8505, Japan.
Adaptability to changing environments is one of the universal characteristics of living organisms. Because individual modes of adaptation are diverse, a unified understanding of these diverse modes is essential to comprehend adaptation. Adaptations can be categorized from at least two perspectives with respect to information.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!