Journal of Physical Activity Research
ISSN (Print): 2576-1919 ISSN (Online): 2574-4437 Website: https://www.sciepub.com/journal/jpar Editor-in-chief: Peter Hart
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Journal of Physical Activity Research. 2025, 10(1), 1-6
DOI: 10.12691/jpar-10-1-1
Open AccessArticle

Physical Activity Behaviors among College Students Enrolled in Online Fitness Courses: An Application of Ajzen’s Theory of Planned Behavior

Amy D. Linder1, , Jerono Rotich2 and Andrea Woodson-Smith1

1Department of Kinesiology and Recreation Administration, North Carolina Central University, Durham, USA

2Department of Kinesiology, Indiana University, Bloomington, USA

Pub. Date: February 18, 2025

Cite this paper:
Amy D. Linder, Jerono Rotich and Andrea Woodson-Smith. Physical Activity Behaviors among College Students Enrolled in Online Fitness Courses: An Application of Ajzen’s Theory of Planned Behavior. Journal of Physical Activity Research. 2025; 10(1):1-6. doi: 10.12691/jpar-10-1-1

Abstract

Despite numerous studies linking physical and emotional well-being to exercise, more than 50% of U.S. adults and approximately 37% of college students are physically inactive. As college demographics shift to include more non-traditional students (ages 25 and older), it becomes significant to understand their physical activity behaviors. In addition, the surge in online education due to the COVID-19 pandemic underscores the need to study physical activity behaviors among diverse populations, including both traditional and non-traditional students in online settings. This study examines the physical activity behaviors among college students enrolled in an online fitness course at a historically black college and university (HBCU). Participants included twenty non-traditional and twenty traditional college students from a southeastern HBCU, who completed the Theory of Planned Behavior and Godin Leisure-Time questionnaires over two semesters. One-way ANOVA analysis found a significant difference between non-traditional and traditional college students in their intentions (p = .003) and attitudes (p = .003) toward engaging in physical activity. Specifically, non-traditional students demonstrated higher intentions and more positive attitudes compared to traditional peers, even though both groups showed similar levels of actual physical activity participation. Universities should consider revising Physical Activity curricula to enhance the motivation of non-traditional students and foster greater participation through targeted interventions and ongoing research. This approach aims to bridge the gap between students' intentions and their actual physical activity participation and create a supportive environment that fosters sustained physical activity among diverse college populations.

Keywords:
college students physical activity behaviors online fitness classes HBCU exercise

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References:

[1]  Zhang, Y., Brackhill, J., Yang, C., & Centola, D. (2015). Physical activity and technology: Investigating barriers among college students. Journal of Health and Technology, 9(4), 377–389.
 
[2]  American College Health Association. (2016). National College Health Assessment: Reference group executive summary spring 2016. American College Health Association.
 
[3]  Linder, D. A., Liu, H., Woodson-Smith, A., & Jung, J. (2018). Physical activity behaviors and well-being among traditional and non-traditional college students: An application of the Theory of Planned Behavior. College Student Journal, 52(2), 181–193.
 
[4]  Ransdell, L. B., Rice, C. H., Snelson, C. D., & Decola, J. (2008). Online education and physical activity: Addressing sedentary behaviors in distance learners. Journal of Physical Education Recreation & Dance, 79(2), 45–52.
 
[5]  National Center for Education Statistics. (1999). Distance education at postsecondary education Institutions: 1997–98. U.S. Department of Education, Office of Educational Research and Improvement.
 
[6]  Kirtman, L. (2009). Online versus in-class courses: An examination of differences in learning outcomes. International Journal for the Scholarship of Teaching and Learning, 3(1), Article 6.
 
[7]  Armstrong, A., & Burcin, M. (2016). Growth of online distance education and its impact on the modern college student. Journal of Distance Learning, 8(3), 47–59.
 
[8]  Dennis, K., Toledo, A., Bates, J., & Lathan, C. (2011). Understanding determinants of physical activity behaviors among online students. Journal of College Health, 59(5), 385–394.
 
[9]  Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
 
[10]  La Barbera, F., & Ajzen, I. (2021). Moderating role of perceived behavioral control in the theory of planned behavior: A preregistered study. Journal of Theoretical Social Psychology, 5, 35-45.
 
[11]  Cho, S., & Tian, Y. (2021). Investigating the role of communication between descriptive norms and exercise intentions and behaviors: findings among fitness tracker users. Journal of American College Health, 69 (4), 452-458.
 
[12]  Sok, J., Borges, J., Schmidt, P., & Ajzen, I. (2020). Farmer behavior as reasoned action: A critical review of research with the theory of planned behavior. Journal of Agricultural Economics, 72 (2), 388-412.
 
[13]  La Barbera, F., & Ajzen, I. (2020). Control interactions in the Theory of Planned Behavior: Rethinking the role of subjective norm. Eur J Psychol 2020 Aug 31; 16(3): 401–417.
 
[14]  Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control: From cognition to behavior (pp. 11–39). Springer.
 
[15]  Burger, T. (2023). Controlling for false discoveries subsequently to large-scale one-way ANOVA testing in proteomics: practical considerations. Proteomics, 1-12.
 
[16]  Johnson, R. (2022). Alternate forms of the one-way ANOVA F and kruskal-wallis tests statistics. Journal of Statistics and Data Science Education, 30 (1), 82-85.