In 2020, Covid-19 was spread all around the world, it affects all the aspect in human life, like: lock-down, social distancing, work from home (WFH), all the activity must done at home, even people were not allowed to visits a doctors/ hospital, Indonesia one of the severe case of corona virus, one of the ways for people to maintained their health is by using m-health. This study about customer experience when they using m-health using MACE (Mobile Application Customer Experience) Framework, the out come from this study is user’s continuance intentions. The research was conduct by spread the questionnaire to people in Indonesia who using m-health. Total valid respondents are 443 random respondents. The result showed there are three Hypothesis that were not supported: Health Concern and Perceived Usefulness, Perceived Usefulness and Customer Experience, and Environmental Turbulence and Continuance Intentions. However researcher found from this study , there are two direct significant effect to continuance intentions, satisfaction customer experience and continuance intentions and trust to application and continuance intentions. Some implications and limitations from this research will discuss.

Abdullah, I. (2020). COVID-19: Threat and Fear in Indonesia. Psychological Trauma: Theory, Research, Practice, and Policy, 12(5), 488–490. https://doi.org/10.1037/tra0000878
Agarwal, S., Lefevre, A. E., Lee, J., L’engle, K., Mehl, G., Sinha, C., Labrique, A., Vasudevan, L., Tamrat, T., Kallander, K., Mitchell, M., Aziz, M. A., Froen, F., Ormel, H., Muniz, M., & Asangansi, I. (2016). Guidelines for reporting of health interventions using mobile phones: Mobile health (mHealth) Evidence reporting and assessment (mERA) checklist. BMJ (Online), 352, 1–10. https://doi.org/10.1136/bmj.i1174
Akter, S., D’Ambra, J., & Ray, P. (2013). Development and validation of an instrument to measure user perceived service quality of mHealth. Information and Management, 50(4), 181–195. https://doi.org/10.1016/j.im.2013.03.001
Akter, S., Ray, P., & D’Ambra, J. (2013). Continuance of mHealth services at the bottom of the pyramid: The roles of service quality and trust. Electronic Markets, 23(1), 29–47. https://doi.org/10.1007/s12525-012-0091-5
Al-Mamary, Y. H., & Shamsuddin, A. (2015). Testing of the technology acceptance model in context of Yemen. Mediterranean Journal of Social Sciences, 6(4S1), 268–273. https://doi.org/10.5901/mjss.2015.v6n4s1p268
Anwar, F. (2020, May 4). Ragu Cek Kesehatan ke RS karena Wabah Corona? Ini Saran Dokter. https://health.detik.com/berita-detikhealth/d-5001767/ragu-cek-kesehatan-ke-rs-karena-wabah-corona-ini-saran-dokter
Bartik, A. W., Bertrand, M., Cullen, Z., Glaeser, E. L., Luca, M., & Stanton, C. (2020). The impact of COVID-19 on small business outcomes and expectations. Proceedings of the National Academy of Sciences of the United States of America, 117(30), 17656–17666. https://doi.org/10.1073/pnas.2006991117
Barton, A. J. (2012). The regulation of mobile health applications. BMC Medicine, 10, 2–5. https://doi.org/10.1186/1741-7015-10-46
Bhattacherjee. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation. MIS Quarterly, 53(9), 1689–1699.
Biduski, D., Bellei, E. A., Rodriguez, J. P. M., Zaina, L. A. M., & De Marchi, A. C. B. (2020). Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire. Computers in Human Behavior, 104(October 2019). https://doi.org/10.1016/j.chb.2019.106169
Buonsenso, D., Pata, D., & Chiaretti, A. (2020). COVID-19 outbreak: less stethoscope, more ultrasound. The Lancet Respiratory Medicine, 8(5), e27. https://doi.org/10.1016/S2213-2600(20)30120-X
Calantone, R., Garcia, R., & Dröge, C. (2003). The effects of environmental turbulence on new product development strategy planning. Journal of Product Innovation Management, 20(2), 90–103. https://doi.org/10.1111/1540-5885.2002003
Chen, Y., Yang, L., Zhang, M., & Yang, J. (2018). Central or peripheral? Cognition elaboration cues’ effect on users’ continuance intention of mobile health applications in the developing markets. International Journal of Medical Informatics, 116(April), 33–45. https://doi.org/10.1016/j.ijmedinf.2018.04.008
Cho, J. (2016). The impact of post-adoption beliefs on the continued use of health apps. International Journal of Medical Informatics, 87, 75–83. https://doi.org/10.1016/j.ijmedinf.2015.12.016
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
Emanuel, E. J., Persad, G., Upshur, R., Thome, B., Parker, M., Glickman, A., Zhang, C., Boyle, C., Smith, M., & Phillips, J. P. (2020). Fair allocation of scarce medical resources in the time of covid-19. New England Journal of Medicine, 382(21), 2049–2055. https://doi.org/10.1056/NEJMsb2005114
Forza, C., & Filippini, R. (1998). TQM impact on quality conformance and customer satisfaction: A causal model. International Journal of Production Economics, 55(1), 1–20. https://doi.org/10.1016/S0925-5273(98)00007-3
Gössling, S., Scott, D., & Hall, C. M. (2020). Pandemics, tourism and global change: a rapid assessment of COVID-19. Journal of Sustainable Tourism, 1–20.
Grant, R. M. (2009). Prospering in dynamically- Competitive environments: Orginizational capability as knowledge integration. Knowledge and Strategy, August 2015, 133–154. https://doi.org/10.1016/b978-0-7506-7088-3.50011-5
Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A global perspective (Vol. 7). Upper Saddle River, NJ: Pearson.
Hammami, A., Harrabi, B., Mohr, M., & Krustrup, P. (2020). Physical activity and coronavirus disease 2019 (COVID-19): specific recommendations for home-based physical training. Managing Sport and Leisure, 0(0), 1–6. https://doi.org/10.1080/23750472.2020.1757494
Homburg, C., Jozić, D., & Kuehnl, C. (2017). Customer experience management: toward implementing an evolving marketing concept. Journal of the Academy of Marketing Science, 45(3), 377–401. https://doi.org/10.1007/s11747-015-0460-7
Hsiao, J. L., & Chen, R. F. (2019). Understanding determinants of health care professionals’ perspectives on mobile health continuance and performance. Journal of Medical Internet Research, 21(3), 1–16. https://doi.org/10.2196/12350
Hussein, Z., Oon, S. W., & Fikry, A. (2017). Consumer Attitude: Does It Influencing the Intention to Use mHealth? Procedia Computer Science, 105(December 2016), 340–344. https://doi.org/10.1016/j.procs.2017.01.231
Jap, S. D. (2001). Perspectives on joint competitive advantages in buyer-supplier relationships. International Journal of Research in Marketing, 18(1–2), 19–35. https://doi.org/10.1016/S0167-8116(01)00028-3
Jaworski, B. J., & Kohli, A. K. (1993). Market Orientation : Antecedents. Journal of Marketing, 57(July), 53–70.
Judd E. Hollander, M.D., and Brendan G. Carr, M. D. (2020). Responding to Covid-19 — A Once-in-a-Century Pandemic? New England Journal of Medicine, 382(18), 1677–1679. https://doi.org/10.1056/nejmp2003762
Karalis Noel, T. (2020). Conflating culture with COVID-19: Xenophobic repercussions of a global pandemic. Social Sciences & Humanities Open, 2(1), 100044. https://doi.org/10.1016/j.ssaho.2020.100044
Khairat, S., Liu, S., Zaman, T., Edson, B., & Gianforcaro, R. (2019). Factors determining patients’Choice between mobile health and telemedicine: Predictive analytics assessment. Journal of Medical Internet Research, 21(6), 1–10. https://doi.org/10.2196/13772
Kim, K. H., Kim, K. J., Lee, D. H., & Kim, M. G. (2019). Identification of critical quality dimensions for continuance intention in mHealth services: Case study of onecare service. International Journal of Information Management, 46(March 2018), 187–197. https://doi.org/10.1016/j.ijinfomgt.2018.12.008
Kumar, S., Nilsen, W. J., Abernethy, A., Atienza, A., Patrick, K., Pavel, M., Riley, W. T., Shar, A., Spring, B., Spruijt-Metz, D., Hedeker, D., Honavar, V., Kravitz, R., Craig Lefebvre, R., Mohr, D. C., Murphy, S. A., Quinn, C., Shusterman, V., & Swendeman, D. (2013). Mobile health technology evaluation: The mHealth evidence workshop. American Journal of Preventive Medicine, 45(2), 228–236. https://doi.org/10.1016/j.amepre.2013.03.017
Lee, E., Han, S., & Jo, S. H. (2017). Consumer choice of on-demand mHealth app services: Context and contents values using structural equation modeling. International Journal of Medical Informatics, 97, 229–238. https://doi.org/10.1016/j.ijmedinf.2016.10.016
Lemke, F., Clark, M., & Wilson, H. (2011). Customer experience quality: An exploration in business and consumer contexts using repertory grid technique. Journal of the Academy of Marketing Science, 39(6), 846–869. https://doi.org/10.1007/s11747-010-0219-0
Lin, C. P., Tsai, Y. H., & Chiu, C. K. (2009). Modeling customer loyalty from an integrative perspective of self-determination theory and expectation-confirmation theory. Journal of Business and Psychology, 24(3), 315–326. https://doi.org/10.1007/s10869-009-9110-8
Mangkunegara, C. N., Azzahro, F., & Handayani, P. W. (2019). Analysis of factors affecting user’s intention in using mobile health application: A case study of halodoc. 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018, 87–92. https://doi.org/10.1109/ICACSIS.2018.8618174
Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002
Mattioli, A. V., Sciomer, S., Cocchi, C., Maffei, S., & Gallina, S. (2020). Quarantine during COVID-19 outbreak: Changes in diet and physical activity increase the risk of cardiovascular disease. Nutrition, Metabolism and Cardiovascular Diseases, 30(9), 1409–1417. https://doi.org/10.1016/j.numecd.2020.05.020
McLean, G., Al-Nabhani, K., & Wilson, A. (2016). the Customer Experience ... Is There an App for That? a Conceptual Understanding of the Customer Experience With M-Commerce Mobile Applications. What’S Ahead in Service Research?: New Perspectives for Business and Society, 1088–1099.
McLean, G., Al-Nabhani, K., & Wilson, A. (2018). Developing a Mobile Applications Customer Experience Model (MACE)- Implications for Retailers. Journal of Business Research, 85(January), 325–336. https://doi.org/10.1016/j.jbusres.2018.01.018
Miele, G., Straccia, G., Moccia, M., Leocani, L., Tedeschi, G., Bonavita, S., Lavorgna, L., & Digital Technologies, Web and Social Media Study Group of the Italian Society of Neurology. (2020). Telemedicine in Parkinson’s Disease: How to Ensure Patient Needs and Continuity of Care at the Time of COVID-19 Pandemic. Telemedicine Journal and E-Health : The Official Journal of the American Telemedicine Association, 00(00), 1–4. https://doi.org/10.1089/tmj.2020.0184
Ming, L. C., Untong, N., Aliudin, N. A., Osili, N., Kifli, N., Tan, C. S., Goh, K. W., Ng, P. W., Al-Worafi, Y. M., Lee, K. S., & Goh, H. P. (2020). Mobile Health Apps on COVID-19 Launched in the Early Days of the Pandemic: Content Analysis and Review. JMIR MHealth and UHealth, 8(9), e19796. https://doi.org/10.2196/19796
Morgan, R. M., & Hunt, S. D. (1994). The Commitment-Trust Theory of. Journal of Marketing, 58(July), 20–38. https://journals.sagepub.com/doi/full/10.1177/002224299405800302
Morris, M. H., Hansen, S. D., & Pitt, L. F. (1995). Environmental turbulence and organizational buying: The case of health benefits in South Africa. Industrial Marketing Management, 24(4), 305–315. https://doi.org/10.1016/0019-8501(95)00014-2
Moser, C., & Yared, P. (2020). Pandemic Lockdown: The Role of Government Commitment. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3581412
Oliver R. L. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17(4)(November), 460–469.
Pavlou, P. A., & El Sawy, O. A. (2006). From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development. Information Systems Research, 17(3), 198–227. https://doi.org/10.1287/isre.1060.0094
Qiang, C. Z. (2011). Mobile Applications for the Health Sector.[Online] Available at: http://siteresources. worldbank. org/INFORMATIONANDCOMMUNICATIONANDTECHNOLOGIES. Resources/MHealth_report. Pdf [Accessed 12/05/2014].
Qin, C., Zhou, L., Hu, Z., Zhang, S., Yang, S., Tao, Y., Xie, C., Ma, K., Shang, K., Wang, W., & Tian, D. S. (2020). Dysregulation of Immune Response in Patients With Coronavirus 2019 (COVID-19) in Wuhan, China. Clinical Infectious Diseases : An Official Publication of the Infectious Diseases Society of America, 71(15), 762–768. https://doi.org/10.1093/cid/ciaa248
Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of Human Computer Studies, 64(8), 683–696. https://doi.org/10.1016/j.ijhcs.2006.01.003
Rose, S., Clark, M., Samouel, P., & Hair, N. (2012). Online Customer Experience in e-Retailing: An empirical model of Antecedents and Outcomes. Journal of Retailing, 88(2), 308–322. https://doi.org/10.1016/j.jretai.2012.03.001
Sheth, J. N., Newman, B. I., & Gross, B. L. (1991). Why We Buy What We Buy: A Theory of Consumption Values: Discovery Service for Air Force Institute of Technology. Journal of Business Research, 22(2), 159–170. http://eds.b.ebscohost.com.afit.idm.oclc.org/eds/detail/detail?vid=3&sid=c553a916-c484-4f2b-8f4a-263242c3e223%40sessionmgr120&bdata=JnNpdGU9ZWRzLWxpdmU%3D#AN=17292155&db=bth
Song, J. H., & Zinkhan, G. M. (2008). Determinants of perceived Web site interactivity. Journal of Marketing, 72(2), 99–113. https://doi.org/10.1509/jmkg.72.2.99
Sun, S., Lu, S. (Feng), & Rui, H. (2019). Does Telemedicine Reduce ED Congestion? Evidence from New York State. Proceedings of the 52nd Hawaii International Conference on System Sciences, August. https://doi.org/10.24251/hicss.2019.816
Tebeje, T. H., & Klein, J. (2020). Applications of e-Health to Support Person-Centered Health Care at the Time of COVID-19 Pandemic. Telemedicine and E-Health, 00(00), 1–9. https://doi.org/10.1089/tmj.2020.0201
Venkatesh, V. (2000). Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 342–365. https://doi.org/10.1287/isre.11.4.342.11872
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information technology: Toward a Unified View. 27(3), 425–478.
Verhoef, P. C., Lemon, K. N., Parasuraman, A., Roggeveen, A., Tsiros, M., & Schlesinger, L. A. (2009). Customer Experience Creation: Determinants, Dynamics and Management Strategies. Journal of Retailing, 85(1), 31–41. https://doi.org/10.1016/j.jretai.2008.11.001
Waizenegger, L., McKenna, B., Cai, W., & Bendz, T. (2020). An affordance perspective of team collaboration and enforced working from home during COVID-19. European Journal of Information Systems, 29(4), 429–442. https://doi.org/10.1080/0960085X.2020.1800417
Weinstein, R. S., Lopez, A. M., Joseph, B. A., Erps, K. A., Holcomb, M., Barker, G. P., & Krupinski, E. A. (2014). Telemedicine, telehealth, and mobile health applications that work: Opportunities and barriers. American Journal of Medicine, 127(3), 183–187. https://doi.org/10.1016/j.amjmed.2013.09.032
Wolf, M., Beck, R., & Pahlke, I. (2012). Mindfully resisting the bandwagon: Reconceptualising IT innovation assimilation in highly turbulent environments. Journal of Information Technology, 27(3), 213–235. https://doi.org/10.1057/jit.2012.13
Zhang, Y., Liu, C., Luo, S., Xie, Y., Liu, F., Li, X., & Zhou, Z. (2019). Factors influencing patients’ intention to use diabetes management apps based on an extended unified theory of acceptance and use of technology model: Web-based survey. Journal of Medical Internet Research, 21(8), 1–17. https://doi.org/10.2196/15023