Examining the Factors for Wearable Healthcare Devices Adoption in the Event of COVID-19: A Classification and Regression Tree Approach

Mehrbakhsh Nilashi, Motahareh Yousefnejad Lazarjani, Eko Supriyanto, Fahad Ghabban, Shahla Asadi, Rabab Abumalloh, Sarminah Samad

Abstract


Wearable devices have attracted a great deal of attention and popularity among academics and industry in the last decade. The potential of wearable technology to improve health efficiency and cut healthcare costs has been demonstrated. Wearable devices are believed to be of a very strong value, both for detection and for the tracking and control of the spread of infectious diseases such as COVID-19. Regardless of whether this technology is imported, inadequate scientists focused on the factors impacting the acceptability of wearable medical devices. Using the model for confirmation of expectations and technology acceptance, this study has developed a theoretical model to study user perceptions about wearable healthcare devices and introduces an extensive research model that uses mainly extracted factors. The data collected from 163 study samples were examined using Classification and Regression Tree (CART) technique. The study results showed that security and privacy is an important factor for the adoption of wearable healthcare devices in the event of COVID-19.


Keywords


Consumer continuance intention, Wearable healthcare devices, Security and privacy, Adoption

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Abstract

References


Ahani, A., & Nilashi, M. (2020). Coronavirus outbreak and its impacts on global economy: the role of social network sites. Journal of Soft Computing and Decision Support Systems, 7(2), 19-22.

Anderson, C. L., & Agarwal, R. (2011). The digitization of healthcare: boundary risks, emotion, and consumer willingness to disclose personal health information. Information Systems Research, 22(3), 469-490.

Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339-370.

Asadi, S., Abdullah, R., Safaei, M., & Nazir, S. (2019). An integrated SEM-Neural Network approach for predicting determinants of adoption of wearable healthcare devices. Mobile Information Systems, 2019.

Asadi, S., Nilashi, M., Safaei, M., Abdullah, R., Saeed, F., Yadegaridehkordi, E., & Samad, S. (2019). Investigating factors influencing decision-makers’ intention to adopt Green IT in Malaysian manufacturing industry. Resources, Conservation and Recycling, 148, 36-54.

Asadi, S., Nilashi, M., Samad, S., Abdullah, R., Mahmoud, M., Alkinani, M. H., & Yadegaridehkordi, E. (2021). Factors impacting consumers’ intention toward adoption of electric vehicles in Malaysia. Journal of Cleaner Production, 282, 124474.

Asadi, S., Pourhashemi, S. O., Nilashi, M., Abdullah, R., Samad, S., Yadegaridehkordi, E., . . . Razali, N. S. (2020). Investigating influence of green innovation on sustainability performance: A case on Malaysian hotel industry. Journal of Cleaner Production, 258, 120860.

Asadi, S., Safaei, M., Yadegaridehkordi, E., & Nilashi, M. (2019). Antecedents of consumers’ intention to adopt Wearable Healthcare Devices. Journal of Soft Computing and Decision Support Systems, 6(2), 6-11.

Chiarugi, F., Karatzanis, I., Zacharioudakis, G., Meriggi, P., Rizzo, F., Stratakis, M., . . . Di Rienzo, M. (2008). Measurement of heart rate and respiratory rate using a textile-based wearable device in heart failure patients. Paper presented at the 2008 Computers in Cardiology.

Dalvi-Esfahani, M., Alaedini, Z., Nilashi, M., Samad, S., Asadi, S., & Mohammadi, M. (2020). Students’ green information technology behavior: Beliefs and personality traits. Journal of Cleaner Production, 257, 120406.

Davenport, A., Gura, V., Ronco, C., Beizai, M., Ezon, C., & Rambod, E. (2007). A wearable haemodialysis device for patients with end-stage renal failure: a pilot study. The Lancet, 370(9604), 2005-2010.

Deng, Z., Mo, X., & Liu, S. (2014). Comparison of the middle-aged and older users’ adoption of mobile health services in China. International Journal of Medical Informatics, 83(3), 210-224.

Fotiadis, D. I., Glaros, C., & Likas, A. (2006). Wearable medical devices. Wiley Encyclopedia of Biomedical Engineering.

Giansanti, D., Macellari, V., & Maccioni, G. (2008). Telemonitoring and telerehabilitation of patients with Parkinson’s disease: health technology assessment of a novel wearable step counter. Telemedicine and e-Health, 14(1), 76-83.

Granado-Font, E., Flores-Mateo, G., Sorlí-Aguilar, M., Montaña-Carreras, X., Ferre-Grau, C., Barrera-Uriarte, M.-L., . . . Satué-Gracia, E.-M. (2015). Effectiveness of a Smartphone application and wearable device for weight loss in overweight or obese primary care patients: protocol for a randomised controlled trial. BMC Public Health, 15(1), 531.

Guo, X., Sun, Y., Wang, N., Peng, Z., & Yan, Z. (2013). The dark side of elderly acceptance of preventive mobile health services in China. Electronic Markets, 23(1), 49-61.

Haghi, M., Thurow, K., & Stoll, R. (2017). Wearable devices in medical internet of things: scientific research and commercially available devices. Healthcare informatics research, 23(1), 4-15.

Islam, S. R., Kwak, D., Kabir, M. H., Hossain, M., & Kwak, K.-S. (2015). The internet of things for health care: a comprehensive survey. IEEE Access, 3, 678-708.

Johnson, M. P., Zheng, K., & Padman, R. (2014). Modeling the longitudinality of user acceptance of technology with an evidence-adaptive clinical decision support system. Decision Support Systems, 57, 444-453.

Keller, J. (2013). Rapid pace of commercial technology complicates Army plans for wearable computing. Military & Aerospace Electronics, 24(11), 28-29.

Konty, K. J., Bradshaw, B., Ramirez, E., Lee, W.-N., Signorini, A., & Foschini, L. (2019). Influenza Surveillance Using Wearable Mobile Health Devices. Online Journal of Public Health Informatics, 11(1).

Lee, Y.-D., & Chung, W.-Y. (2009). Wireless sensor network based wearable smart shirt for ubiquitous health and activity monitoring. Sensors and Actuators B: Chemical, 140(2), 390-395.

Li, Y. (2014). The impact of disposition to privacy, website reputation and website familiarity on information privacy concerns. Decision Support Systems, 57, 343-354.

Li, Y., Crossler, R. E., & Compeau, D. (2019). Regulatory Focus in the Context of Wearable Continuance.

Lim, S., Xue, L., Yen, C. C., Chang, L., Chan, H. C., Tai, B. C., . . . Choolani, M. (2011). A study on Singaporean women's acceptance of using mobile phones to seek health information. International Journal of Medical Informatics, 80(12), e189-e202.

Lin, C.-S., Hsu, H. C., Lay, Y.-L., Chiu, C.-C., & Chao, C.-S. (2007). Wearable device for real-time monitoring of human falls. Measurement, 40(9-10), 831-840.

Lishan, X., Chiuan, Y. C., Choolani, M., & Chuan, C. H. (2009). The perception and intention to adopt female-focused healthcare applications (FHA): A comparison between healthcare workers and non-healthcare workers. International Journal of Medical Informatics, 78(4), 248-258.

Maass, W., & Varshney, U. (2012). Design and evaluation of Ubiquitous Information Systems and use in healthcare. Decision Support Systems, 54(1), 597-609.

Manimaraboopathy, M., Vijayalakshmi, S., Hemavathy, D., & Priya, A. (2017). A Wearable Multiparameter Medical Monitoring And Alert System With First Aid. International Journal on Smart Sensing & Intelligent Systems, 10.

Marakhimov, A., & Joo, J. (2017). Consumer adaptation and infusion of wearable devices for healthcare. Computers in Human Behavior, 76, 135-148.

Miltgen, C. L., Popovič, A., & Oliveira, T. (2013). Determinants of end-user acceptance of biometrics: Integrating the “Big 3” of technology acceptance with privacy context. Decision Support Systems, 56, 103-114.

Mishra, A. N., Anderson, C., Angst, C. M., & Agarwal, R. (2012). Electronic health records assimilation and physician identity evolution: An identity theory perspective. Information Systems Research, 23(3-part-1), 738-760.

Moores, T. T. (2012). Towards an integrated model of IT acceptance in healthcare. Decision Support Systems, 53(3), 507-516.

Moran, S., Nishida, T., & Nakata, K. (2013). Comparing British and Japanese perceptions of a wearable ubiquitous monitoring device. IEEE Technology and Society Magazine, 32(4), 45-49.

Nilashi, M., Ahani, A., Esfahani, M. D., Yadegaridehkordi, E., Samad, S., Ibrahim, O., . . . Akbari, E. (2019). Preference learning for eco-friendly hotels recommendation: A multi-criteria collaborative filtering approach. Journal of Cleaner Production, 215, 767-783.

Nilashi, M., Asadi, S., Abumalloh, R. A., Samad, S., & Ibrahim, O. (2020). Intelligent recommender systems in the COVID-19 outbreak: the case of wearable healthcare devices. Journal of Soft Computing and Decision Support Systems, 7(4), 8-12.

Nilashi, M., Asadi, S., Minaei-Bidgoli, B., Abumalloh, R. A., Samad, S., Ghabban, F., & Ahani, A. (2021). Recommendation agents and information sharing through social media for coronavirus outbreak. Telematics and Informatics, 61, 101597.

Nilashi, M., Rupani, P. F., Rupani, M. M., Kamyab, H., Shao, W., Ahmadi, H., . . . Aljojo, N. (2019). Measuring sustainability through ecological sustainability and human sustainability: A machine learning approach. Journal of Cleaner Production, 240, 118162.

Nilashi, M., Samad, S., Manaf, A. A., Ahmadi, H., Rashid, T. A., Munshi, A., . . . Ahmed, O. H. (2019). Factors influencing medical tourism adoption in Malaysia: A DEMATEL-Fuzzy TOPSIS approach. Computers & Industrial Engineering, 137, 106005.

Nilashi, M., Samad, S., Minaei-Bidgoli, B., Ghabban, F., & Supriyanto, E. (2021). Online Reviews Analysis for Customer Segmentation through Dimensionality Reduction and Deep Learning Techniques. Arabian Journal for Science and Engineering, 1-13.

Nilashi, M., Samad, S., Yusuf, S. Y. M., & Akbari, E. (2020). Can complementary and alternative medicines be beneficial in the treatment of COVID-19 through improving immune system function? Journal of infection and public health, 13(6), 893.

Nilashi, M., Yadegaridehkordi, E., Ibrahim, O., Samad, S., Ahani, A., & Sanzogni, L. (2019). Analysis of travellers’ online reviews in social networking sites using fuzzy logic approach. International Journal of Fuzzy Systems, 21(5), 1367-1378.

Ozdemir, Z., Barron, J., & Bandyopadhyay, S. (2011). An analysis of the adoption of digital health records under switching costs. Information Systems Research, 22(3), 491-503.

Radin, J. M., Wineinger, N. E., Topol, E. J., & Steinhubl, S. R. (2020). Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study. The Lancet Digital Health.

Rupani, P., Nilashi, M., Abumalloh, R., Asadi, S., Samad, S., & Wang, S. (2020). Coronavirus pandemic (COVID-19) and its natural environmental impacts. International Journal of Environmental Science and Technology, 1-12.

Samson, S. I., Lee, W.-N., Quisel, T., Foschini, L., Liska, J., MILLS, H. G., . . . Beal, A. C. (2018). Using Claims and Consumer Wearable Devices Data to Quantify Influenza-Related Outcomes among Type 2 Diabetes Patients—A Large Population Study. In: Am Diabetes Assoc.

Sun, Y., Wang, N., Guo, X., & Peng, Z. (2013). Understanding the acceptance of mobile health services: a comparison and integration of alternative models. Journal of Electronic Commerce Research, 14(2), 183.

Weng, M. (2016). The acceptance of wearable devices for personal healthcare in China. Msc Thesis, University of Oulu,

Wu, L., Li, J.-Y., & Fu, C.-Y. (2011). The adoption of mobile healthcare by hospital's professionals: An integrative perspective. Decision Support Systems, 51(3), 587-596.

Yadegaridehkordi, E., Nilashi, M., Shuib, L., Nasir, M. H. N. B. M., Asadi, S., Samad, S., & Awang, N. F. (2020). The impact of big data on firm performance in hotel industry. Electronic Commerce Research and Applications, 40, 100921.

Yadegaridehkordi, E., Shuib, L., Nilashi, M., & Asadi, S. (2019). Decision to adopt online collaborative learning tools in higher education: A case of top Malaysian universities. Education and Information Technologies, 24(1), 79-102.

Yang, Z., Zhou, Q., Lei, L., Zheng, K., & Xiang, W. (2016). An IoT-cloud based wearable ECG monitoring system for smart healthcare. Journal of medical systems, 40(12), 286.


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