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Prediction model of intention to use digital fitness services for health promotion during the COVID-19 pandemic: a gender-based multi-group analysis

  • Dong-Kyu Kim1
  • Sung-Un Park2,*,

1Department of Sports Science, College of Creative Convergence, Chungwoon University, 32244 Hongsung-gun, Republic of Korea

2Department of Sports and Health, College of Arts & Physical Education, Hwasung Medi-Science University, 18274 Hwaseong-si, Republic of Korea

DOI: 10.22514/jomh.2022.001 Vol.19,Issue 1,January 2023 pp.23-32

Submitted: 25 August 2022 Accepted: 14 November 2022

Published: 30 January 2023

*Corresponding Author(s): Sung-Un Park E-mail: psu@hsmu.ac.kr

Abstract

As the number of people infected with COVID-19 in Korea is increasing, several measures have been implemented to gradually restrict outdoor activities and indoor gatherings while promoting a non-face-to-face social culture. In this study, we performed a gender-based multi-group analysis using a technology acceptance model (TAM) as an external variable for COVID-19 risk perception to verify the model’s predictive ability to increase participation behavior toward digital fitness services. We analyzed the data of 433 Koreans using an online survey consisting of 23 items. A structural equation model was used to verify the perceived ease of use (PEOU), perceived usefulness (PU), intention to use and exercise participation behavior of the TAM with COVID-19 risk perception as an external variable. First, our results showed that COVID-19 risk perception had a statistically higher significant and positive effect on PEOU (β = 0.170, t = 3.296, p < 0.001) than on PU (β = 0.130, t = 2.848, p = 0.004) of digital fitness services. Second, the PEOU of the digital fitness service was found to have a statistically higher significant positive effect on PU (β = 0.512, t = 9.728, p < 0.001) than on intention to use (β = 0.130, t = −2.774, p = 0.006). Third, the PU of digital fitness services was found to have a statistically significant positive effect on the intention to use (β = 0.684, t = 12.909, p < 0.001). Fourth, the intention to use the digital fitness service was found to have a statistically significant positive effect on exercise participation behavior (β = 0.796, t = 16.248, p < 0.001). Lastly, we observed a significant difference between men and women in COVID-19 risk perception and PEOU among the six paths established. Digital environments that encourage participation in exercises could promote health during a pandemic. This study highlighted the need to consider digital environments that encourage exercise participation in creating physical exercise contents as there was no significant difference in the intention to use digital fitness services between men and women.


Keywords

Technology acceptance model; Digital fitness; Exercise participation behavior; Gender differences


Cite and Share

Dong-Kyu Kim,Sung-Un Park. Prediction model of intention to use digital fitness services for health promotion during the COVID-19 pandemic: a gender-based multi-group analysis. Journal of Men's Health. 2023. 19(1);23-32.

References

[1] Yonsei University. Facing anxiety and depression amid COVID-19: the “corona blue” message. 2020. Available at: https://www.yonsei.ac. kr/en_sc/yonsei_news.jsp?article_no=189487&mode=view (Accessed: 13 October 2020).

[2] World Health Organization. WHO coronavirus (COVID-19) dashboard. 2022. Available at: https://covid19.who.int/table (Accessed: 15 August 2022).

[3] World Health Organization. A guide to WHO’S guidance. 2020. Available at: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance (Accessed: 17 July 2020).

[4] Korea Ministry of the Interior and Safety. Guidelines for distance in life. 2020. Available at: https://www.mois.go.kr/frt/bbs/type001/commonSelectBoardArticle.do?bbsId=BBSMSTR_ 000000000012&nttId=78178 (Accessed: 25 June 2020).

[5] Korea Ministry of Health and Welfare. COVID-19 promotes strengthening social distancing. 2021. Available at: http: //www.mohw.go.kr/react/al/sal0301vw.jsp?PAR_MENU_ID= 04&MENU_ID=0403&CONT_SEQ=368947 (Accessed: 17 December 2021).

[6] Korea Ministry of Health and Welfare. About COVID-19. 2022. Available at: http://ncov.mohw.go.kr/baroView.do?brdId=4&brdGubun= 41 (Accessed: 03 March 2021).

[7] Bender L. Key messages and actions for COVID-19 prevention and control in schools. 2020.

[8] Kaushal S, Rajput AS, Bhattacharya S, Vidyasagar M, Kumar A, Prakash MK, et al. Estimating the herd immunity threshold by accounting for the hidden asymptomatics using a COVID-19 specific model. PLoS One. 2020; 15: e0242132.

[9] Hayes SC, Strosahl, KD., Wilson, KG. Acceptance and commitment therapy: The process and practice of mindful change. 2nd edn. The Guilford Press: New York. 2012.

[10] Gao J, Zheng P, Jia Y, Chen H, Mao Y, Chen S, et al. Mental health problems and social media exposure during COVID-19 outbreak. PLoS One. 2020; 15: e0231924.

[11] Jang D, Kim I, Kwon S. Motivation and intention toward physical activity during the COVID-19 pandemic: perspectives from integrated model of self-determination and planned behavior theories. Frontiers in Psychology. 2021; 12: 714865.

[12] Vancini RL, Viana RB, Andrade MS, Lira CA, Nikolaidis PT, Almeida AA, et al. YouTube as a source of information about physical exercise during COVID-19 outbreak. International Journal of Sport Studies for Health. 2022; 2: e123312.

[13] Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. The Lancet. 2020; 395: 912–920.

[14] Maugeri G, Castrogiovanni P, Battaglia G, Pippi R, D’Agata V, Palma A, et al. The impact of physical activity on psychological health during Covid-19 pandemic in Italy. Heliyon. 2020; 6: e04315.

[15] Meyer MN, Gjorgjieva T, Rosica D. Healthcare worker intentions to receive a COVID-19 vaccine and reasons for hesitancy: a survey of 16,158 health system employees on the eve of vaccine distribution. medRxiv. 2020.

[16] Rohmad A, Adi S. Effectiveness of online learning and physical activities study in physical education during pandemic COVID 19. Kinestetik: Journal Ilmiah Pendidikan Jasmani. 2021; 5: 64–70.

[17] Sui W, Rush J, Rhodes RE. Engagement with web-based fitness videos on youtube and instagram during the COVID-19 pandemic: longitudinal study. JMIR Formative Research. 2022; 3: 25055.

[18] Back JH, Yang JH, Hyun J. Research on the Actual Condition of Sports Activities by COVID-19 and improvements of sports activities. Journal of the Korea Convergence Society. 2020; 12: 343–351.

[19] Health plus. While we might be confined to improvised home workouts, let’s make do with what’s available to us, and keep these tips in mind to avoid getting injured. 2020. Available at: https://www.parkwayeast.com.sg/healthplus/article/how-to-avoid-injuries-while-doing-home-workouts (Accessed: 01 July 2020).

[20] Karen A. 10 must-follow strategies for preventing injuries while working out at home. 2020. Available at: https://www.realsimple.com/health/fitness-exercise/exercising-at-home-injury-prevention (Accessed: 01 July 2020).

[21] Davis FD. A technology acceptance model for empirically testing new end-user information systems: theory and results. Sloan School of Management, Massachusetts Institute of Technology. 1986.

[22] Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: a comparison of two theoretical models. Management Science. 1989; 35: 982–1003.

[23] Ibrahim H. Technology acceptance model: extension to sport consump-tion. Procedia Engineering. 2014; 69: 1534–1540.

[24] Park SU, Kim DK, Ahn H. Predictive model on the intention to accept taekwondo electronic protection devices. Applied Sciences. 2021; 11: 1845.

[25] van Uffelen JGZ, Khan A, Burton NW. Gender differences in physical activity motivators and context preferences: a population-based study in people in their sixties. BMC Public Health. 2017; 17: 624.

[26] Molanorouzi K, Khoo S, Morris T. Motives for adult participation in physical activity: type of activity, age, and gender. BMC Public Health. 2015; 15: 66.

[27] Silva KS, Barbosa Filho VC, Del Duca GF, de Anselmo Peres MA, Mota J, Lopes ADS, et al. Gender differences in the clustering patterns of risk behaviours associated with non-communicable diseases in Brazilian adolescents. Preventive Medicine. 2014; 65: 77–81.

[28] Schorr M, Dichtel LE, Gerweck AV, Valera RD, Torriani M, Miller KK, et al. Sex differences in body composition and association with cardiometabolic risk. Biology of Sex Differences. 2018; 9: 28.

[29] Toselli S. Body composition and physical health in sports practice: an editorial. International Journal of Environmental Research and Public Health. 2021; 18: 4534.

[30] Karastergiou K, Smith SR, Greenberg AS, Fried SK. Sex differences in human adipose tissues—the biology of pear shape. Biology of Sex Differences. 2012; 3: 13.

[31] Rashid AT. Digital inclusion and social inequality: gender differences in ICT access and use in five developing countries. Gender, Technology and Development. 2016; 20: 306–332.

[32] Goswami A, Dutta S. Gender differences in technology usage—a literature review. Open Journal of Business and Management. 2016; 04: 51–59.

[33] Siddiq F, Scherer R. Is there a gender gap? a meta-analysis of the gender differences in students’ ICT literacy. Educational Research Review. 2019; 27: 205–217.

[34] Gómez-Ruiz AA, Gálvez-Ruiz P, Grimaldi-Puyana M, Lara-Bocanegra A, García-Fernández J. Investigating the intention to use fitness app: the role of the perceived attractiveness of fitness center customers. Sport, Business and Management: an International Journal. 2022; 12: 537–553.

[35] Beldad AD, Hegner SM. Expanding the technology acceptance model with the inclusion of trust, social influence, and health valuation to determine the predictors of german users’ willingness to continue using a fitness app: a structural equation modeling approach. International Journal of Human-Computer Interaction. 2018; 34: 882–893.

[36] Lee J, Lee C, Kim D. Relationship between the service quality of O2O fitness app, perceived value and flow experience: moderating effects of gender. The Korean Journal of Physical Education. 2021; 60: 403–417.

[37] König J, Jäger-Biela DJ, Glutsch N. Adapting to online teaching during COVID-19 school closure: teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education. 2020; 43: 608–622.

[38] Müller AM, Alley S, Schoeppe S, Vandelanotte C. The effectiveness of e-& mHealth interventions to promote physical activity and healthy diets in developing countries: a systematic review. International Journal of Behavioral Nutrition and Physical Activity. 2016; 13: 109.

[39] Vijayasarathy LR. Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & Management. 2004; 41: 747–762.

[40] Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science. 2000; 46: 186–204.

[41] Frederick C, Ryan R. Differences in motivation for sport and exercise and their relations with participation and mental health. Journal of Sport Behavior. 1993; 16: 124–146.

[42] Weinberg R, Tenenbaum G, McKenzie A, Jackson S, Anshel M, Grove R, et al. Motivation for youth participation in sport and physical activity: relationships to culture, self-reported activity levels, and gender. International Journal of Sport and Exercise Psychology. 2000; 31: 321–346.

[43] Hartmann AS, Rieger E, Vocks S. Sex and gender differences in body image. Frontiers in Psychology. 2019; 10: 1696.

[44] Román ML, de la Vega R, Jiménez-Castuera R. Motivation and commitment to sports practice during the lockdown caused by Covid-19. Frontiers in Psychology. 2021; 11: 622595.

[45] Park TH, Kim WI, Park S, Ahn J, Cho MK, Kim S. Public interest in acne on the internet: comparison of search information from google trends and naver. Journal of Medical Internet Research. 2020; 22: e19427.

[46] Statistics Korea. Case in Korea. 2022. Available at: https://kosis. kr/covid_eng/covid_index.do (Accessed: 17 October 2022).

[47] Korean Ministry of Culture, Sports and Tourism. 2019 Sport white paper. 2021. Available at: https://www.mcst.go.kr/kor/s_policy/dept/deptView.jsp?pSeq=1527&pDataCD=0417000000&pType= 07 (Accessed: 14 October 2022).

[48] World Health Organization (WHO). Development of the World Health Organization WHOQOL-BREF quality of life assessment The WHOQOL group. Psychological Medicine. 1998; 28: 551–558.

[49] Choi EPH, Hui BPH, Wan EYF, Kwok JYY, Tam THL, Wu C. COVID-19 and health-related quality of life: a community-based online survey in Hong Kong. International Journal of Environmental Research and Public Health. 2021; 18: 3228.

[50] Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 1989; 13: 319.

[51] Yu JH, Ku GCM, Lo YC, Chen CH, Hsu CH. Identifying the antecedents of university students’ usage behaviour of fitness apps. Sustainability. 2021; 13: 9043.

[52] Jarvenpaa SL, Tractinsky N, Vitale M. Consumer trust in an Internet store. Information Technology and Management. 2000; 1: 45–71.

[53] Kline RB. Principles and practice of structural equation modeling. 1st ed. The Guilford Press: New York. 1998.

[54] Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research. 1981; 18: 39–50.

[55] Nunnally JC, Bernstein IH. Psychometric theory. 3rd ed. MaGraw-Hill. Inc: New York. 1994.

[56] West SG, Finch JF, Curran, PJ. Structural equation models with non-normal variables: problems and remedies. In Hoyle RH (ed.). Structural Equation Modeling: Concepts, issue, and application (pp. 56–75). Sage Publications: Thousand Oaks, CA. 1995.

[57] MacCallum RC, Roznowski M, Mar CM, Reith JV. Alternative strategies for cross-validation of covariance structure models. Multivariate Behavioral Research. 1994; 29: 1–32.

[58] Byrne BM. Structural equation modeling with AMOS, EQS, and LISREL: comparative approaches to testing for the factorial validity of a measuring instrument. International Journal of Testing. 2001; 1: 55–86.

[59] United Nations news [UN news]. The impact of COVID-19 on sport, physical activity and well-being and its effects on social development. 2020. Available at: https://www.un.org/development/desa/dspd/2020/05/covid-19-sport/ (Accessed: 18 October 2022).

[60] Korea Ministry of Culture, Sports and Tourism. 2021 Korea national physical education survey. 2022. Available at: https: //www.mcst.go.kr/kor/s_policy/dept/deptView.jsp?pSeq= 1573&pDataCD=0417000000&pType= (Accessed: 18 October 2022).

[61] Craft BB, Carroll HA, Lustyk MK. Gender differences in exercise habits and quality of life reports: assessing the moderating effects of reasons for exercise. International Journal of Liberal Arts and Social Science. 2014; 2: 65–76.


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