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Articles
DOI: 10.14254/1795-6889.2023.19-1.6
Submitted: 2023-05-22
Published: 2023-05-22

Thematic analysis of google play reviews of lifestyle apps

Department of Leadership and Marketing, University of Győr, Hungary
Department of Leadership and Marketing, University of Győr, Hungary
m-health market lifestyle app content analysis Google Play reviews

Abstract

Worldwide, numerous studies have been conducted on m-health applications and the results show that, if well-designed, they can regulate and track medication and reduce healthcare costs. The aim of this research is to analyze the experiences of users connected to different lifestyle apps, in particular (1) to explore the negative, neutral and positive topics in the reviews, and (2) to discover the role of health improvement among the comments. The present paper is part of a complex empirical research project. A qualitative and quantitative content analysis was conducted of the user reviews in the Google Play store for the 16 lifestyle apps selected during the first phase of the empirical research (quasi experiment). All in all, 2,835 comments were analyzed. The negative comments mentioned unreliable tracking functions, problems with updates, or high prices. The neutral comments outlined some missing functions or problems with the operation of the app. The positive comments were related to health improvement, usefulness, ease of use, engagement and willingness to recommend the app. Physical activity, facilitating a specific diet, weight loss, wellbeing, tracking progress and health awareness were among the common health aspects of the lifestyle apps. The results of this research will be particularly useful for consumers, app developers and service providers who focus on health awareness and health promotion.

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References

  1. Banerjee, P., Mendu, V.V.R., Korrapati, D., & Gavaravarapu, S. M. (2020). Calorie counting smartphone apps: Effectiveness in nutritional awareness, lifestyle modification and weight management among young Indian adults. Health Informatics Journal, 26(2), 816-828. doi: 10.1177/1460458219852531 DOI: https://doi.org/10.1177/1460458219852531
  2. Bavota, G., Linares-Vasquez, M., Bernal-Cardenas, C.E., Di Penta, M., Oliveto, R., & Poshyvanyk, D. (2015). The Impact of Api Change-and Fault-Proneness on the User Ratings of Android Apps. IEEE Transactions on Software Engineering, 41(4), 384-407. DOI: https://doi.org/10.1109/TSE.2014.2367027
  3. Briggs, T., Quick, V. & Hallman, W.K. (2021). Feature Availability Comparison in Free and Paid Versions of Popular Smartphone Weight Management Applications. Journal of Nutrition Education and Behavior, 53(9), 732-741. https://doi.org/10.1016/j.jneb DOI: https://doi.org/10.1016/j.jneb.2021.05.010
  4. Chandy, R., & Gu, H. (2012). Identifying spam in the ios app store. In Proceedings of the 2nd Joint WICOW/airweb Workshop on Web Quality (56-59). ACM, 10.1145/2184305.2184317. DOI: https://doi.org/10.1145/2184305.2184317
  5. Desveaux, L., Shaw, J., Saragosa, M., Soobiah, C., Marani, H., Hensel, J., Agarwal, P., Onabajo, N., Bhatia, R.S., & Jeffs, L. A. (2018). A mobile app to improve self-management of individuals with type 2 diabetes: qualitative realist evaluation. Journal of Medical Internet Research, 20(3), e81, doi: 10.2196/jmir.8712 DOI: https://doi.org/10.2196/jmir.8712
  6. Franco, R.Z, Fallaize, R, Lovegrove, J.A., & Hwang, F. (2016). Popular Nutrition-Related Mobile Apps: A Feature Assessment. JMIR Mhealth Uhealth, 4(3), e85, doi: 10.2196/mhealth.5846 DOI: https://doi.org/10.2196/mhealth.5846
  7. Fu, B., Lin, J., Li, L., Faloutsos, C., Hong, J. & Sadeh, N. (2013, August). Why people hate your app: Making sense of user feedback in a mobile app store. In Proceedings of the 19th ACM SIGKDD international conference on knowledge discovery and data mining (1276–1284). KDD ’13. ACM, New York, doi:10.1145/2487575.2488202 DOI: https://doi.org/10.1145/2487575.2488202
  8. Huckvale, K., Prieto, J.T., Tilney, M., Benghozi, P.J., & Car, J. (2015). Unaddressed privacy risks in accredited health and wellness apps: a cross-sectional systematic assessment. BMC Med, 13(214). https://doi.org/10.1186/s12916-015-0444-y DOI: https://doi.org/10.1186/s12916-015-0444-y
  9. Jaana, M., Sherrard, H., & Paré, G. (2019). A prospective evaluation of telemonitoring use by seniors with chronic heart failure: adoption, self-care, and empowerment. Health Informatics Journal, 25(4), 1800-1814. doi:10.1177/1460458218799458 DOI: https://doi.org/10.1177/1460458218799458
  10. Maringer, M., Van't Veer, P., Klepacz, N., Verain, M.C.D., Normann, A., Ekman, S., Timotijevic, L., Raats, M.M., & Geelen, A. (2018). User-documented food consumption data from publicly available apps: an analysis of opportunities and challenges for nutrition research. Nutrition Journal, 17(1):59, doi: 10.1186/s12937-018-0366-6 DOI: https://doi.org/10.1186/s12937-018-0366-6
  11. Martin, W., Harman, M., Jia, Y., Sarro, F., & Zhang, Y. (2015, May). The app sampling problem for app store mining. In Proceedings of the 12th working conference on mining software repositories (123-133). MSR ’15. IEEE Press, Florence, Italy. DOI: https://doi.org/10.1109/MSR.2015.19
  12. McKay, F.H., Wright, A., Shill, J., Stephens, H., & Uccellini, M. (2019). Using Health and Well-Being Apps for Behavior Change: A Systematic Search and Rating of Apps. JMIR Mhealth Uhealth, 7(7),e11926, doi: 10.2196/11926 DOI: https://doi.org/10.2196/11926
  13. Mendiola, M.F., Kalnicki, M., & Lindenauer, S. (2015). Valuable Features in Mobile Health Apps for Patients and Consumers: Content Analysis of Apps and User Ratings. JMIR mHealth and uHealth, 3(2),e40. doi: 10.2196/mhealth.4283 DOI: https://doi.org/10.2196/mhealth.4283
  14. MobileAction (2022). Top Health and Fitness Apps in Hungary of Google Play Store. Retrieved November 22, 2022, from https://www.mobileaction.co/top-apps/health-and-fitness-7/android/hu
  15. Pagano, D., & Maalej, W. (2013, July). User feedback in the app store: An empirical study. 21st IEEE International Requirements Engineering Conference (RE), (125-134). Rio de Janeiro, Brazil. DOI: 10.1109/RE.2013.6636712 DOI: https://doi.org/10.1109/RE.2013.6636712
  16. Pires, I.M., Marques, G., Garcia, N.M., Flórez-Revuelta, F., Ponciano, V., & Oniani, S. A. (2020). Research on the Classification and Applicability of the Mobile Health Applications. Journal of Personalized Medicine, 10(1), 11. doi: 10.3390/jpm10010011 DOI: https://doi.org/10.3390/jpm10010011
  17. Ross, E.L, Jamison, R.N, Nicholls, L., Perry, B.M., & Nolen, K.D. (2020). Clinical integration of a smartphone app for patients with chronic pain: retrospective analysis of predictors of benefits and patient engagement between clinic visits, Journal of Medical Internet Research, 22(4), e16939 doi: 10.2196/16939 DOI: https://doi.org/10.2196/16939
  18. Schmidt-Kraepelin, M., Toussaint, P.A., Thiebesm S., Hamari, J., & Sunyaev, A. (2020). Archetypes of Gamification: Analysis of mHealth Apps. JMIR Mhealth Uhealth, 8(10), e19280, doi: 10.2196/19280 DOI: https://doi.org/10.2196/19280
  19. Schumer, H., Amadi, C., & Joshi, A. (2018). Evaluating the Dietary and Nutritional Apps in the Google Play Store. Healthc Inform Res., 24(1), 38-45. doi: 10.4258/hir DOI: https://doi.org/10.4258/hir.2018.24.1.38
  20. Shabir, H., D’Costa, M., Mohiaddin, Z., Moti, Z., Rashid, H., Sadowska, D., Alam, B., & Cox, B. (2022). The Barriers and Facilitators to the Use of Lifestyle Apps: A Systematic Review of Qualitative Studies. Eur. J. Investig. Health Psychol. Educ., 12(2), 144-165. doi: 10.3390/ejihpe12020012 DOI: https://doi.org/10.3390/ejihpe12020012
  21. Shah, A. M., Yan, X., Tariq, S., & Ali, M. (2021). What patients like or dislike in physicians: Analyzing drivers of patient satisfaction and dissatisfaction using a digital topic modeling approach. Information Processing & Management, 58(3), 102516, https://doi.org/10.1016/j.ipm.2021.102516 DOI: https://doi.org/10.1016/j.ipm.2021.102516
  22. Statista (2021). Smartphone users in Europe 2020, by country. Retrieved March 24, 2022, from https://www.statista.com/forecasts/1168910/smartphone-users-in-europe-by-country
  23. Statista (2022a). Digital Fitness & Well-Being Apps. Retrieved March 24, 2022, from https://www.statista.com/outlook/dmo/digital-health/digital-fitness-well-being/digital-fitness-well-being-apps/worldwide
  24. Statista (2022b). Most popular fitness and sport apps worldwide 2022, by downloads, Google Play and Apple App Store. Retrieved November 10, 2022. from https://www.statista.com/statistics/1239771/top-fitness-and-sport-apps-downloads
  25. Statista (2022c). Leading Android health apps worldwide 2022, by downloads. Retrieved November 10, 2022. from https://www.statista.com/statistics/690887/leading-google-play-health-worldwide-downloads/
  26. Stoyanov, S. R., Hides, L., Kavanagh, D. J., & Wilson, H. (2016). Development and validation of the user version of the Mobile Application Rating Scale (uMARS). JMIR mHealth and uHealth, 4(2),e72. doi: 10.2196/mhealth.5849 DOI: https://doi.org/10.2196/mhealth.5849
  27. Stoyanov, S.R., Hides, L., Kavanagh, D.J., Zelenko, O., Tjondronegoro, D., & Mani, M. (2015). Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR Mhealth Uhealth, 3(1),e27. doi: 10.2196/mhealth.3422 DOI: https://doi.org/10.2196/mhealth.3422
  28. West, J.H., Hall, P.C., Hanson, C.L., Barnes, M.D., Giraud Carrier, C., & Barrett, J. (2012). There’s an app for that: content analysis of paid health and fitness apps. J. Med. Internet Res., 14(3),e72, doi: 10.2196/jmir.1977 DOI: https://doi.org/10.2196/jmir.1977
  29. Zhou, L., Bao, J., Setiawan, I. M. A., Saptono, A., & Parmanto, B. (2019). The mHealth app usability questionnaire (MAUQ): development and validation study. JMIR Mhealth Uhealth, 7(4),e11500, doi: 10.2196/11500 DOI: https://doi.org/10.2196/11500

How to Cite

Keller, V., & Ercsey, I. (2023). Thematic analysis of google play reviews of lifestyle apps. Human Technology, 19(1), 82–102. https://doi.org/10.14254/1795-6889.2023.19-1.6