Construction of movement-sleep-study (MSS) collaborative intervention model based on biological rhythm regulation

Authors

  • BINYANG LI Krirk University, Bangkok, Thailand

DOI:

https://doi.org/10.47197/retos.v67.114907

Keywords:

Biological rhythms, cognitive performance, movement-sleep-study model, academic achievement, intervention strategy

Abstract

Introduction: Biological rhythms regulating movement, sleep, and study significantly impact cognitive function and academic performance. However, conventional educational models often overlook their integration, leading to cognitive fatigue and reduced learning efficiency. This study develops and evaluates the Movement-Sleep-Study (MSS) collaborative intervention model, designed to synchronize these rhythms for optimized learning.

Objective: This study examines the effectiveness of the MSS model in enhancing cognitive performance, attentional capacity, and academic achievement.

Methodology: A quasi-experimental study was conducted with 120 junior high school students (mean age = 13.6 ± 0.7 years), randomly assigned to either an intervention group (MSS model) or a control group (traditional learning). The intervention combined structured physical activity, sleep optimization, and cognitive engagement strategies over one semester. Cognitive performance was measured using a computerized executive function test battery, academic achievement through standardized subject-based assessments, and sleep quality via the Pittsburgh Sleep Quality Index (PSQI) and Fitbit Inspire HR trackers. Data were analyzed using ANOVA and Pearson’s correlation.

Results: The MSS intervention group exhibited significant improvements in cognitive performance, attentional focus, and memory retention compared to the control group (p < 0.05). Strong correlations were found between sleep quality, movement engagement, and academic achievement, alongside a notable reduction in cognitive fatigue.

Discussion: These findings underscore the value of integrating biological rhythm regulation into educational practice. The MSS model not only enhances learning efficiency but also supports students’ psychophysiological well-being, offering a practical framework for holistic academic development.

Conclusion: The MSS model offers a scientifically validated approach to enhancing learning through biological rhythm regulation. By synchronizing movement, sleep, and study schedules, it improves cognitive and academic outcomes. Future research should explore its long-term effects and scalability across educational settings.

References

Anatürk, M., Demnitz, N., Ebmeier, K. P., & Sexton, C. E. (2018). A systematic review and meta-analysis of structural magnetic resonance imaging studies investigating cognitive and social activity lev-els in older adults. Neuroscience & Biobehavioral Reviews, 93, 71-84. https://doi.org/10.1016/j.neubiorev.2018.06.012

Beattie, L., Kyle, S. D., Espie, C. A., & Biello, S. M. (2015). Social interactions, emotion, and sleep: A sys-tematic review and research agenda. Sleep Medicine Reviews, 24, 83–100. https://doi.org/10.1016/j.smrv.2014.12.005

Cezário, R. R., Freitas, D., & Chahad-Ehlers, S. (2023). Chronotype as a predictor of scholar performance in a full-time middle school. Brazilian Journal of Biology, 83, e272072. https://doi.org/10.1590/1519-6984.272072

Davies, A., & Christie, N. (2018). The experiences of parents with children with disabilities travelling on planes: An exploratory study. Journal of Transport & Health, 11, 122-129. https://doi.org/10.1016/j.jth.2018.10.002

de Moraes Junior, F. B., Tadiotto, M. C., Corazza, P. R. P., de Menezes Junior, F. J., Brand, C., Mota, J., & Leite, N. (2025). Social isolation during the covid-19 pandemic impaired vitamin d concentra-tions, motor performance and physical fitness in adolescents. Retos: nuevas tendencias en edu-cación física, deporte y recreación, (62), 715-724. https://doi.org/10.47197/retos.v62.109217

De Zambotti, M., Goldstein, C., Cook, J., Menghini, L., Altini, M., Cheng, P., & Robillard, R. (2024). State of the science and recommendations for using wearable technology in sleep and circadian re-search. Sleep, 47(4), zsad325. https://doi.org/10.1093/sleep/zsad325

Falck, R. S., Davis, J. C., Best, J. R., Chan, P. C., Li, L. C., Wyrough, A. B., ... & Liu-Ambrose, T. (2020). Effect of a multimodal lifestyle intervention on sleep and cognitive function in older adults with prob-able mild cognitive impairment and poor sleep: a randomized clinical trial. Journal of Alz-heimer’s Disease, 76(1), 179-193. https://doi.org/10.3233/JAD-200383

Fischer, D., Lombardi, D. A., Marucci-Wellman, H., & Roenneberg, T. (2017). Chronotypes in the US–influence of age and sex. PloS one, 12(6), e0178782. https://doi.org/10.1371/journal.pone.0178782

Galán-Arroyo, C., Díaz-Torres, R. A., Castillo-Paredes, A., & Rojo-Ramos, J. Sleep Quality in Spanish Box-ers after the COVID-19 Pandemic. Retos, 52, 457-463.

Hale, L., & Guan, S. (2015). Screen time and sleep among school-aged children and adolescents: a sys-tematic literature review. Sleep medicine reviews, 21, 50-58. https://doi.org/10.1016/j.smrv.2014.07.007

Hirshkowitz, M., Whiton, K., Albert, S. M., Alessi, C., Bruni, O., DonCarlos, L., ... & Croft, J. B. (2015). Na-tional Sleep Foundation’s sleep time duration recommendations: Methodology and results summary. Sleep Health, 1(1), 40–43. https://doi.org/10.1016/j.jth.2014.12.010

Intelangelo, L., Gutiérrez, N. M., Bevacqua, N., Mendoza, C., Guzmán, I. P. G., & Mayorga, D. J. (2022). Ef-fect of confinement by covid-19 on the lifestyle of the university population of Argentina: Eval-uation of physical activity, food and sleep. Retos: nuevas tendencias en educación física, deporte y recreación, (43), 274-282. https://doi.org/10.47197/retos.v43i0.88461

Khan, N. A., & Hillman, C. H. (2014). The relation of childhood physical activity and aerobic fitness to brain function and cognition: a review. Pediatric exercise science, 26(2), 138-146. https://doi.org/10.1123/pes.2013-0125

Lo, J. C., Ong, J. L., Leong, R. L., Gooley, J. J., & Chee, M. W. (2016). Cognitive performance, sleepiness, and mood in partially sleep-deprived adolescents: The need for sleep study. Sleep, 39(3), 687–698. https://doi.org/10.5665/sleep.5552

Ong, H. S., Lim, C. S., Png, A. L. C., Kong, J. W., & Peh, A. L. H. (2021). Chronobiology and the case for sleep health interventions in the community. Singapore Medical Journal, 62(5), 220. https://doi.org/10.11622/smedj.2021058

Otero, T. M., Barker, L. A., & Naglieri, J. A. (2014). Executive function treatment and intervention in schools. Applied Neuropsychology: Child, 3(3), 205-214. https://doi.org/10.1080/21622965.2014.897903

ÖZEL, H. F. (2024). NEUROPHYSIOLOGY OF ACUTE AND CHRONIC STRESS ON LEARNING AND. The Science of Neurolearning from Neurobiology to Education, 1.

Renke, M. B., Marcinkowska, A. B., Kujach, S., & Winklewski, P. J. (2022). A systematic review of the impact of physical exercise-induced increased resting cerebral blood flow on cognitive func-tions. Frontiers in aging neuroscience, 14, 803332. https://doi.org/10.3389/fnagi.2022.803332

Sabaoui, I., Lotfi, S., & Talbi, M. (2024). THE ASSOCIATION OF CIRCADIAN RHYTHMS WITH ACADEMIC, PHYSICAL, AND COGNITIVE PERFORMANCE: A SYSTEMATIC REVIEW. Образование и наука, 26(1), 133-170.

Saconi, B., Polomano, R. C., Compton, P. C., McPhillips, M. V., Kuna, S. T., & Sawyer, A. M. (2021). The influence of sleep disturbances and sleep disorders on pain outcomes among veterans: a sys-tematic scoping review. Sleep Medicine Reviews, 56, 101411. https://doi.org/10.1016/j.smrv.2020.101411

Sillau, K. I. M., León, M. T. C., & Campos, J. E. V. (2025). Impact of sleep quality on anthropometric pro-file in school-age children from a sports academy. Retos: nuevas tendencias en educación física, deporte y recreación, (62), 140-146. https://doi.org/10.47197/retos.v62.109084

Walch, O. J., Cochran, A., & Forger, D. B. (2016). A global quantification of “normal” sleep schedules using smartphone data. Science advances, 2(5), e1501705. https://doi.org/10.1126/sciadv.1501705

Wheaton, A. G., Ferro, G. A., & Croft, J. B. (2015). School start times for middle school and high school students—United States, 2011–12 school year. Morbidity and Mortality Weekly Report, 64(30), 809.

Xu, Y., Lin, N., Wu, C., Wen, X., Zhong, F., Yu, K., ... & Huang, C. (2023). The Effect of Classroom-Based Physical Activity Elements on Academic Performance in Children and Adolescents: A Meta-Analysis. Journal of Teaching in Physical Education, 43(1), 79-92. https://doi.org/10.1123/jtpe.2022-0175

Yip, T., Wang, Y., Xie, M., Ip, P. S., Fowle, J., & Buckhalt, J. (2022). School start times, sleep, and youth outcomes: a meta-analysis. Pediatrics, 149(6), e2021054068. https://doi.org/10.1542/peds.2021-054068

Yusuf, A., Yasin, M., PK, R. F., Aditya, R. S., Solikhah, F. K., Kotijah, S., ... & Alrazeeni, D. M. (2024). Differ-ential impacts of high and low-intensity physical exercise on brain wave activity and functional connectivity in professional athletes: a systematic review. Retos: nuevas tendencias en educa-ción física, deporte y recreación, (60), 1356-1364. https://doi.org/10.47197/retos.v60.108998

Donnelly, Joseph E., et al. "Physical activity, fitness, cognitive function, and academic achievement in children: a systematic review." Medicine and science in sports and exercise 48.6 (2016): 1197. https://doi.org/10.1249/MSS.0000000000000901

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Published

13-05-2025

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Original Research Article

How to Cite

LI, B. (2025). Construction of movement-sleep-study (MSS) collaborative intervention model based on biological rhythm regulation. Retos, 67, 1211-1220. https://doi.org/10.47197/retos.v67.114907