The prevalence of mobile fitness apps has led to a substantial increase in their market size and download rates. However, in practical situations, consistently high dropout rates and limited usage of mobile fitness apps continue to pose significant challenges for successful post-adoption. Therefore, the current study aimed to evaluate the instrument's reliability and validity for the proposed model of users' continuance intention toward using mobile fitness apps. The model comprises 10 constructs derived from the Expectation Confirmation Model (ECM), guilt of temporary discontinuance of the mobile fitness app, four Neutralization Techniques, and switching costs. The pilot study was conducted in Malaysia through social media platforms. The data analysis was conducted using the Partial Least Squares-Structural Equation Modelling (PLS-SEM) technique for 65 valid respondents to assess the reliability and validity of the questionnaire. SmartPLS 4 software was utilized to perform the analysis. The findings indicated good reliability and construct validity. This pilot study provides a foundation for further research on continuance intention to use mobile fitness apps and validates the measurement instrument for future large-scale studies.
Ali, F., Rasoolimanesh, S. M., Sarstedt, M., Ringle, C. M., & Ryu, K. (2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, 30(1), 514-538. https://doi.org/10.1108/ijchm-10-2016-0568
Aljabali, R. N., & Ahmad, N. (2022). Profile of Fitness and Diet App Users in Online Wellness Social Communities in Malaysia: Cross-Sectional Pilot Study. The International Conference of Advanced Computing and Informatics.
Amagai, S., Pila, S., Kaat, A. J., Nowinski, C. J., & Gershon, R. C. (2022, Apr 26). Challenges in Participant Engagement and Retention Using Mobile Health Apps: Literature Review. J Med Internet Res, 24(4), e35120. https://doi.org/10.2196/35120
Aydin, S., Ozer, G., & Arasil, O. (2005). Customer loyalty and the effect of switching costs as a moderator variable. Marketing Intelligence & Planning, 23(1), 89-103. https://doi.org/10.1108/02634500510577492
Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921
Cheng, L. K., Huang, H.-L., & Lai, C.-C. (2021). Continuance intention in running apps: the moderating effect of relationship norms. International Journal of Sports Marketing and Sponsorship, ahead-of-print(ahead-of-print). https://doi.org/10.1108/ijsms-08-2020-0143
Ding, Y. (2019). Looking forward: The role of hope in information system continuance. Computers in Human Behavior, 91, 127-137.
https://doi.org/10.1016/j.chb.2018.09.002
Flake, J. K., Davidson, I. J., Wong, O., & Pek, J. (2022). Construct validity and the validity of replication studies: A systematic review. American Psychologist, 77, 576-588. https://doi.org/10.1037/amp0001006
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Franke, G., & Sarstedt, M. (2019). Heuristics versus statistics in discriminant validity testing: A comparison of four procedures. Internet Research, 29(3), 430-447. https://doi.org/10.1108/IntR-12-2017-0515
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications.
https://books.google.com.my/books?id=JDWmCwAAQBAJ
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
https://doi.org/10.1108/ebr-11-2018-0203
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2022). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer Nature.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
Huang, C.-K., Chen, S.-H., Tang, C.-P., & Huang, H.-Y. (2019). A trade-off dual-factor model to investigate discontinuous intention of health app users: From the perspective of information disclosure. Journal of Biomedical Informatics, 100. https://doi.org/10.1016/j.jbi.2019.103302
Huang, G., & Ren, Y. (2020). Linking technological functions of fitness mobile apps with continuance usage among Chinese users: Moderating role of exercise self-efficacy. Computers in Human Behavior, 103, 151-160.
https://doi.org/https://doi.org/10.1016/j.chb.2019.09.013
Kim, M.-K., Park, M.-C., Park, J.-H., Kim, J., & Kim, E. (2018). The role of multidimensional switching barriers on the cognitive and affective satisfaction-loyalty link in mobile communication services: Coupling in moderating effects. Computers in Human Behavior, 87, 212-223. https://doi.org/10.1016/j.chb.2018.05.024
Kwon, J. Y., Lee, J. S., & Park, T. S. (2022). Analysis of Strategies to Increase User Retention of Fitness Mobile Apps during and after the COVID-19 Pandemic. Int J Environ Res Public Health, 19(17). https://doi.org/10.3390/ijerph191710814
Li, A., Sun, Y., Guo, X., Guo, F., & Guo, J. (2021). Understanding how and when user inertia matters in fitness app exploration: A moderated mediation model. Information Processing & Management, 58(2), 102458.
https://doi.org/10.1016/j.ipm.2020.102458
Lowe, N. K. (2019). What Is a Pilot Study? J Obstet Gynecol Neonatal Nurs, 48(2), 117-118. https://doi.org/10.1016/j.jogn.2019.01.005
Research, G. V. (2023). mHealth Apps Market Size, Share & Trends Analysis Report By Type (Fitness, Medical), By Region (North America, Europe, Asia Pacific, Latin America, Middle East & Africa), And Segment Forecasts, 2023 - 2030. Retrieved 25-03-2023 from https://www.grandviewresearch.com/industry-analysis/mhealth-app-market
Silic, M., Barlow, J. B., & Back, A. (2017). A new perspective on neutralization and deterrence: Predicting shadow IT usage. Information & Management, 54(8), 1023-1037. https://doi.org/10.1016/j.im.2017.02.007
Siponen, M., Puhakainen, P., & Vance, A. (2020). Can individuals’ neutralization techniques be overcome? A field experiment on password policy. Computers & Security, 88. https://doi.org/10.1016/j.cose.2019.101617
Soliman, W., & Rinta-Kahila, T. (2020). Toward a refined conceptualization of IS discontinuance: Reflection on the past and a way forward. Information & Management, 57(2), 103167. https://doi.org/10.1016/j.im.2019.05.002
Statista. (2021). Global health and fitness app downloads as of Q2 2020. https://www.statista.com/statistics/1127248/health-fitness-apps-downloads-worldwide/
Sykes, G. M., & Matza, D. (1957). Techniques of neutralization: A theory of delinquency. American sociological review, 22(6), 664-670.
Taherdoost, H. (2016). Validity and reliability of the research instrument; how to test the validation of a questionnaire/survey in a research. How to test the validation of a questionnaire/survey in a research (August 10, 2016).
Taherdoost, H. (2019). What is the best response scale for survey and questionnaire design; review of different lengths of rating scale/attitude scale/Likert scale. Hamed Taherdoost, 1-10.
Turel, O. (2017). Untangling the complex role of guilt in rational decisions to discontinue the use of a hedonic Information System. European Journal of Information Systems, 25(5), 432-447. https://doi.org/10.1057/s41303-016-0002-5
Van Teijlingen, E., & Hundley, V. (2001). The importance of pilot studies. Social research update(35), 1-4.
Vance, A., Siponen, M., & Pahnila, S. (2012). Motivating IS security compliance: Insights from Habit and Protection Motivation Theory. Information & Management, 49(3-4), 190-198. https://doi.org/10.1016/j.im.2012.04.002
Vinnikova, A., Lu, L. D., Wei, J. C., Fang, G. B., & Yan, J. (2020, Oct). The Use of Smartphone Fitness Applications: The Role of Self-Efficacy and Self-Regulation. International Journal of Environmental Research and Public Health, 17(20). https://doi.org/10.3390/ijerph17207639
Wang, K. (2015). Determinants of mobile value-added service continuance: The mediating role of service experience. Information & Management, 52(3), 261-274. https://doi.org/10.1016/j.im.2014.11.005
Ye, Q., Luo, Y., Chen, G., Guo, X., Wei, Q., & Tan, S. (2019, 2019/02/01). Users Intention for Continuous Usage of Mobile News Apps: the Roles of Quality, Switching Costs, and Personalization. Journal of Systems Science and Systems Engineering, 28(1), 91-109. https://doi.org/10.1007/s11518-019-5405-0
Yin, Q., Li, L., Yan, Z., & Guo, C. (2021). Understanding the effects of self-peer-platform incentives on users' physical activity in mobile fitness apps: the role of gender. Information Technology & People, ahead-of-print(ahead-of-print). https://doi.org/10.1108/itp-10-2020-0705
Yousaf, A., Mishra, A., & Gupta, A. (2021). ‘From technology adoption to consumption’: Effect of pre-adoption expectations from fitness applications on usage satisfaction, continual usage, and health satisfaction. Journal of Retailing and Consumer Services, 62, 102655. https://doi.org/10.1016/j.jretconser.2021.102655
Yusoff, M. S. B. (2019). ABC of Content Validation and Content Validity Index Calculation. Education in Medicine Journal, 11(2), 49-54.
https://doi.org/10.21315/eimj2019.11.2.6
Zhang, X. X., & Xu, X. G. (2020, Sep). Continuous use of fitness apps and shaping factors among college students: A mixed-method investigation. International Journal of Nursing Sciences, 7, 580-587. https://doi.org/10.1016/j.ijnss.2020.07.009
Zheng, L. (2019). The role of consumption emotions in users’ mobile gaming application continuance intention. Information Technology & People, 33(1), 340-360. https://doi.org/10.1108/itp-04-2018-0197
