Sangeetha Poolayulla Chelottillam

Sangeetha Chelottillam

Master's thesis

Machine learning analysis of factors affecting motivation and performance in recreational running

Advisors

Rebecca Lennartz (M. Sc.), Dr.-Ing. Eva Dorschky, Prof. Dr. Björn Eskofier

Duration

06 / 2024 – 12/ 2024

Abstract

Regular physical activity yields many benefits, encompassing mental well-being, self-assurance, graceful aging, and overall life satisfaction [1]. Yet, the motivation to engage in sports is complex and crucial in shaping individuals’ commitment to an active lifestyle. Running is not merely a physical exercise but an effective way to uplift mood, alleviate stress, and sharpen cognitive abilities [2].

Various factors influence runners’ motivation and performance. Miller and Donohue [3] observed performance improvements in high school distance runners who listened to personalized motivational scripts or music before races. Also, factors such as sleep [4], running experience, marital status [5,6], and environmental conditions [7] impact runners’ motivation and performance. Social influences, including running partners, have also been shown to affect motivation [8]. The field of running science has traditionally concentrated on separating individual factors that impact a runner’s motivation and performance. By conducting a comprehensive study that considers the aforementioned factors, we can gain a better understanding of how these elements collectively influence running experience. This approach allows us to uncover complex interactions and potentially identify novel insights that may have been overlooked in studies focusing on individual factors alone.

To comprehensively explore the dynamics of long-term motivation and performance in recreational running, we plan to conduct a questionnaire-based longitudinal study to capture the various dimensions of running experience. This study aims to investigate the relationship between personal characteristics—including age, gender, relationships, and parental status, along with factors such as experience of running, running partners, and daily influences such as sleep or self-perceived stress on motivation and running performance among recreational runners. The primary research question explores whether there is a relation between the aforementioned factors and long-term motivation and long-term performance, to understand how these factors collectively impact long-term motivation and long-term performance over time. Complementing this, the secondary research question examines whether a machine learning-based recommendation system could be built, utilizing supervised algorithms to influence motivation and performance at an individual level [9]. The goal of this thesis is to deepen the insights into the dynamics of long-term motivation and long-term performance in recreational running while exploring novel approaches for personalized support and improvement.

References

[1] Holtermann, A., Marott, J. L., Gyntelberg, F., Schnohr, P., & et al. (2013). Does the Benefit on Survival from Leisure Time Physical Activity Depend on Physical Activity at Work? A Prospective Cohort Study. PLOS ONE, 8(1), e54548. https://doi.org/10.1371/journal.pone.0054548

[2] Damrongthai, C., Kuwamizu, R., Suwabe, K., et al. (2021). Benefit of human moderate running boosting mood and executive function coinciding with bilateral prefrontal activation. Scientific Reports, 11(1), 22657. DOI: 10.1038/s41598-021-01654-z: https://doi.org/10.1038/s41598-021-01654-z

[3] Miller, A., & Donohue, B. (2003). The Development and Controlled Evaluation of Athletic Mental Preparation Strategies in High School Distance Runners. Journal of Applied Sport Psychology, 15(4), 321-334. https://doi.org/10.1080/714044200

[4] Kay, D. B., Dzierzewski, J. M., & Kerkhof, G. A. (2023). What role do sleep and circadian rhythms play in psychological functioning including motivation, emotion, cognition, and performance?. Research Directions Sleep Psychology, 1(1), 1-4. DOI: 10.1017/slp.2023.5

[5] Menheere D, Janssen M, Funk M, van der Spek E, Lallemand C, Vos S. Runner’s Perceptions of Reasons to Quit Running: Influence of Gender, Age and Running-Related Characteristics. Int J Environ Res Public Health. 2020 Aug 20;17(17):6046. doi: 10.3390/ijerph17176046. PMID: 32825266; PMCID: PMC7503581.

[6] León-Guereño, P., Tapia Serrano, M. A., Castañeda, A., & Malchrowicz-Mośko, E. (2020). Do Sex, Age and Marital Status Influence the Motivations of Amateur Marathon Runners? The Poznan Marathon Case Study. Frontiers in Psychology, 11, 2151. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7488354/

[7] Campos-Uscanga, Y., Reyes-Rincón, H., Pineda, E., Gibert-Isern, S., Ramirez-Colina, S., & Argüelles-Nava, V. G. (2022). Running in Natural Spaces: Gender Analysis of Its Relationship with Emotional Intelligence, Psychological Well-Being, and Physical Activity. International Journal of Environmental Research and Public Health, 19(10), 6019. https://www.mdpi.com/1660-4601/19/10/6019

[8] Franken, R., Bekhuis, H., & Tolsma, J. (2022). Running Together: How Sports Partners Keep You Running. Frontiers in Sports and Active Living, 4. DOI: 10.3389/fspor.2022.643150: doi:10.3389/fspor.2022.643150.

[9] Haller, N., Kranzinger, S., Kranzinger, C., Blumkaitis, J. C., Strepp, T., Simon, P., … Stöggl, T. (2023). Predicting Injury and Illness with Machine Learning in Elite Youth Soccer: A Comprehensive Monitoring Approach over 3 Months. Journal of Sports Science and Medicine, 22(3), 476-487. https://pubmed.ncbi.nlm.nih.gov/37711721/