The Influence of Digital Fitness Tools on High School Students' Physical Activity and Exercise

Authors

DOI:

https://doi.org/10.57125/FED.2025.12.07

Keywords:

digital fitness tools, physical activity, adolescents, action research, sedentary behaviour

Abstract

This action research study investigated the impact of digital fitness tools on adolescents’ physical activity behaviours and perceptions through a five-month blended learning intervention conducted in a public Greek high school. The study aimed to explore whether a structured educational program, incorporating fitness apps and wearable devices, could effectively promote healthier activity patterns and more positive attitudes toward exercise. A total of 48 students (24 boys, 24 girls) from two randomly selected 10th-grade classes participated in the intervention. The program followed a single-cycle action research design consisting of planning, implementation, and reflection phases. Weekly sessions alternated between in-class instruction, physical activity in the schoolyard using digital tools, and synchronous online teaching via Webex. Educational materials were also uploaded to an asynchronous e-Class platform. Data collection involved a validated and culturally adapted questionnaire administered pre- and post-intervention to measure device usage, physical activity frequency, exercise attitudes, and app-related perceptions. Quantitative data were analysed using paired-sample t-tests and Cohen’s d in SPSS, with significance set at p < 0.05. Qualitative feedback was also gathered from collaborative projects and class discussions. Findings revealed a statistically significant increase in students’ use of fitness apps and smartwatches, as well as a reduction in sedentary behaviour. Students reported more favourable perceptions of exercise, particularly regarding enjoyment, socialisation, and self-monitoring. The intervention demonstrated the value of integrating digital health tools into school curricula and emphasised the importance of combining technology with pedagogical strategies tosustain engagement. These results suggest that contextually grounded blended learning models can be effective vehicles for promoting active lifestyles among youth. Future research should examine long-term outcomes and adaptation across diverse school settings.

References

Ajzen, I. (1991). The theory of planned behaviour. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Baig, W. S., Elahib, H., & Hashmi, N. U. (2023). Impact of social media fitness contents on health and fitness motivation of the users. Global Digital & Print Media Review, 6(4), Article 60. https://doi.org/10.31703/gdpmr.2023(vi-iv).05

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice Hall.

Chen, H., Schoefer, K., Manika, D., & Tzemou, E. (2023). The “dark side” of general health and fitness-related self-service technologies: A systematic review of the literature and directions for future research. Journal of Public Policy & Marketing, 43(2). https://doi.org/10.1177/07439156231224731

Chen, Y., Tzeng, Y., & Gau, B. (2024). Mobile health-based health literacy weight management intervention using smart devices for adolescents: A convergent mixed-methods pilot study. Nursing & Health Sciences, 26(4), Article e13172. https://doi.org/10.1111/nhs.13172

Domin, A., Uslu, A., Schulz, A., Ouzzahra, Y., & Vögele, C. (2022). A theory-informed, personalized mHealth intervention for adolescents (mobile app for physical activity): Development and pilot study. JMIR Formative Research, 6, Article e35118. https://doi.org/10.2196/35118

Du, H., Venkatakrishnan, A., Youngblood, G. M., Ram, A., & Pirolli, P. (2016). A group-based mobile application to increase adherence in exercise and nutrition programs: A factorial design feasibility study. JMIR MHealth and UHealth, 4(1), Article e4. https://doi.org/10.2196/mhealth.4900

Dyrstad, S. M., Hansen, B. H., Holme, I. M., & Anderssen, S. A. (2014). Comparison of self-reported versus accelerometer-measured physical activity. Medicine & Science in Sports & Exercise, 46(1), 99–106. https://doi.org/10.1249/MSS.0b013e3182a0595f

Eikey, E. V. (2021). Effects of diet and fitness apps on eating disorder behaviours: Qualitative study. BJPsych Open, 7(5), Article e1011. https://doi.org/10.1192/bjo.2021.1011

Fabbrizio, A., et al. (2023). Smart devices for health and wellness applied to tele-exercise: An overview of new trends and technologies such as IoT and AI. Healthcare, 11(12), Article 1805. https://doi.org/10.3390/healthcare11121805

Franklin, B. A., et al. (2022). Physical activity, cardiorespiratory fitness, and cardiovascular health: A clinical practice statement of the American Society for Preventive Cardiology Part II. American Journal of Preventive Cardiology, 12, Article 100425. https://doi.org/10.1016/j.ajpc.2022.100425

Gao, Z., & Lee, J. E. (2019). Emerging technology in promoting physical activity and health: Challenges and opportunities. Journal of Clinical Medicine, 8(11), Article 1830. https://doi.org/10.3390/jcm8111830

Gómez-Cuesta, N., et al. (2024). A mobile app-based intervention improves anthropometry, body composition and fitness: A randomized controlled trial. Frontiers in Public Health. https://doi.org/10.3389/fpubh.2024.1380621

Lewis, Z. H., et al. (2020). The utility of wearable fitness trackers and implications for increased engagement: An exploratory, mixed methods observational study. Digital Health, 6, Article 2055207619900059. https://doi.org/10.1177/2055207619900059

Liu, Y., Hong-xue, Z., & Xu, R. (2023). The impact of technology on promoting physical activities and mental health: A gender-based study. BMC Psychology, 11, Article 1. https://doi.org/10.1186/s40359-023-01348-3

Liu, Z., Zhang, Y., Zhang, J., & Song, X. (2024). Run for the group: Examining the effects of group-level social interaction features of fitness apps. Decision Support Systems, 187, Article 114335. https://doi.org/10.1016/j.dss.2024.114335

Mittelstadt, B. D., et al. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2). https://doi.org/10.1177/2053951716679679

Ozdamli, F., & Milrich, F. (2023). Positive and negative impacts of gamification on the fitness industry. European Journal of Investigation in Health, Psychology and Education, 13(8), 1411–1422. https://doi.org/10.3390/ejihpe13080103

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68

Shei, R.-J., et al. (2022). Wearable activity trackers – Advanced technology or advanced marketing? European Journal of Applied Physiology, 122(9). https://doi.org/10.1007/s00421-022-04951-1

Shin, G., et al. (2018). Beyond novelty effect: A mixed-methods exploration into the motivation for long-term activity tracker use. JAMIA Open, 2(1), 62–72. https://doi.org/10.1093/jamiaopen/ooy048

Shin, Y., Kim, S., & Lee, M. (2019). Mobile phone interventions to improve adolescents' physical health: A systematic review and meta-analysis. Public Health Nursing. https://doi.org/10.1111/phn.12655

Telford, R. M., et al. (2016). The influence of sport club participation on physical activity and body fat: The LOOK longitudinal study. Journal of Science and Medicine in Sport, 19(5), 400–406. https://doi.org/10.1016/j.jsams.2015.04.008

Tenenbaum, G., et al. (2025). Smart sport watch usage: The dominant role of technology readiness. Technologies, 13(1), Article 24. https://doi.org/10.3390/technologies13010024

Valach, P., et al. (2020). Effects of a project based on mobile applications and pedometers on adolescent exercise perceptions. Physical Activity Review, 8(1), 41–48. https://doi.org/10.16926/par.2020.08.05

Wang, X., Zhu, Y., & Li, R. (2024). Effectiveness of mHealth app–based interventions for adolescent physical activity: A meta-analysis. International Journal of Behavioral Nutrition and Physical Activity. https://doi.org/10.2196/51478

Woessner, M. N., et al. (2021). The evolution of technology and physical inactivity: The good, the bad, and the way forward. Frontiers in Public Health, 9, Article 655491. https://doi.org/10.3389/fpubh.2021.655491

World Health Organization. (2023). Physical activity. https://www.who.int/health-topics/physical-activity#tab=tab_2

World Health Organization. (2024). Physical activity. https://www.who.int/initiatives/behealthy/physical-activity

Yang, Y., & Koenigstorfer, J. (2021). Determinants of fitness app usage and impacts of app features on physical activity intentions. Journal of Medical Internet Research, 23(7), Article e26063. https://doi.org/10.2196/26063

Zheng, E. L. (2021). Interpreting fitness: Self-tracking with fitness apps through a postphenomenology lens. AI & Society. https://doi.org/10.1007/s00146-021-01146-8

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Published

2025-12-09

How to Cite

Kanaros, D., & Bourdaniotis, P. (2025). The Influence of Digital Fitness Tools on High School Students’ Physical Activity and Exercise. Futurity Education, 5(4), 121–137. https://doi.org/10.57125/FED.2025.12.07