Behavioral Intention to Use IoT Technology in Healthcare Settings

M. H. Alanazi, B. Soh

Abstract


Rapid scaling of using the Internet of Things (IoT) technology has been seen recently in numerous applications in healthcare to deliver proper services. This was motivated by the declining size and cost of the employed IoT devices. Developing such technology has been well investigated in the literature; however, few studies have explored the factors influencing its adaptation in the healthcare setting. In this study, we investigate the core factors that influence the acceptance of using IoT for Healthcare Purposes in the Kingdom of Saudi Arabia (KSA). Accordingly, a theoretical framework, based on the Technology Acceptance Model (TAM), was developed and tested empirically. The modified model added variables that provide a better explanation of the acceptance of healthcare technology. To ground our conceptual idea, a survey was designed and performed on 407 patients (207 males, 200 females). The Partial Least Square Structural Equation Modeling (SEM) technique was applied to analyze the effect of eight hypothesized predicting constructs on the collected data. Results revealed that cost, privacy concerns, and perceived usefulness were the most significant predictors of behavioral intention to use. However, attitude and perceived connectedness were found to be irrelevant in predicting the intention to use IoT. Ultimately, results found that there is no correlation between gender and behavioral intention.


Keywords


Internet of Things; healthcare; technology acceptance model (TAM); structural equation model

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References


R. Minerva, A. Biru, D. Rotondi, Towards a Definition of the Internet of Things (IoT), IEEE Internet Initiative, 2015

A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, M. Ayyash, “Internet of things: a survey on enabling technologies, protocols, and applications”, IEEE Communications Surveys & Tutorials, Vol. 17, No. 4, pp. 2347-2376, 2015

C. A. da Costa, C. F. Pasluosta, B. Eskofier, D. B. da Silva, R. da Rosa Righi, “Internet of health things: toward intelligent vital signs monitoring in hospital wards”, Artificial Intelligence in Medicine, Vol. 89, pp. 61-69, 2018

M. Ersue, D. Romascanu, J. Schonwalder, A. Sehgal, Management of Networks with Constrained Devices: Use Cases, RFC 7548, available at: https://tools.ietf.org/html/rfc7548, 2015

A. Dillon, M. Morris, “User acceptance of new information technology: Theories and models”, Annual Review of Information Science and Technology, Vol. 14, No. 4, pp. 3-33, 1996

L. Gao, X. Bai, “A unified perspective on the factors influencing consumer acceptance of internet of things technology”, Asia Pacific Journal of Marketing and Logistics, Vol. 26, No. 2, pp. 211-231, 2014

F. D. Davis, “Perceived Usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13, No. 3, pp. 319-340, 1989

V. Venkatesh, J. Y. L. Thong, X. Xu, “Unified theory of acceptance and use of technology: A synthesis and the road ahead”, Journal of the Association for Information Systems, Vol. 17, No. 5, pp. 328-376, 2016

B. H. Sheppard, J. Hartwick, P. R. Warshaw, “The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research”, Journal of Consumer Research, Vol. 15, No. 3, pp. 325-343, 1988

S. Y. Yousafzai, G. R. Foxall, J. G. Pallister, “Technology acceptance: a meta-analysis of the TAM: Part 2”, Journal of Modelling in Management, Vol. 2, No. 3, pp. 281-304, 2007

R. J. Holden, B. T. Karsh, “The technology acceptance model: its past and its future in health care”, Journal of Biomedical Informatics, Vol. 43, No. 1, pp. 159-172, 2010

A. K. Yarbrough, T. B. Smith, “Technology acceptance among physicians: a new take on TAM”, Medical Care Research and Review, Vol. 64, No. 6, pp. 650- 672, 2007

V. Venkatesh, H. Bala, “Technology acceptance model 3 and a research agenda on interventions”, Decision Sciences, Vol. 39, No. 2, pp. 273-315, 2008

T. Teo, C. B. Lee, “Attitudes towards computers among students in higher education: A case study in Singapore”, British Journal of Educational Technology, Vol. 39, No. 1, pp. 160-162, 2008

T. Teo, “A structural equation modeling of factors influencing student teachers' satisfaction with e-learning”, British Journal of Educational Technology, Vol. 41, No. 6, pp. E150-E152, 2010

S. McCoy, A. Everard, B. M. Jones, “An examination of the technology acceptance model in Uruguay and the US: A focus on culture”, Journal of Global Information Technology Management, Vol. 8, No. 2, pp. 27-45, 2005

M. Srite, E. Karahanna, “The role of espoused national cultural values in technology acceptance”, MIS Quarterly, Vol. 30, No. 3, pp. 679-704, 2006

J. Charan, T. Biswas, “How to calculate sample size for different study designs in medical research?”, Indian Journal of Psychological Medicine, Vol. 35, No. 2, pp. 121-126, 2013

D. George, SPSS for Windows Step by Step: A Simple Guide and Reference, Pearson Education India, 2011

M. Tenehaus, V. E. Vinzi, Y. M. Chatelin, C. Lauro, “PLS path modeling”, Computational Statistics & Data Analysis, Vol. 48, No. 1, pp. 159-205, 2005

M. Wetzels, G. Odekerken-Schroder, C. Van Oppen, “Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration”, MIS Quarterly, Vol. 33, No. 1, pp. 177-195, 2009

J. F. Hair Jr, G. T. M. Hult, C. Ringle, M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), SAGE Publications, 2016.

P. H. Westfall, S. S. Young, Resampling-based Multiple Testing: Examples and Methods for p-value Adjustment, John Wiley & Sons, 1993

Y. Zhao, Q. Ni, R. Zu, “What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age”, International Journal of Information Management, Vol. 43, pp. 342-350, 2018

M. Weng. The Acceptance of Wearable Devices for Personal Healthcare in China, Msc Thesis, University of Oulu, 2016

M. I. Cahita, N. A. Hodgson, C. Budhathoki, H. R. Han, “Intention to use mHealth in older adults with heart failure”, The Journal of Cardiovascular Nursing, Vol. 32, No. 6, pp. E1-E7, 2017

A. M. AlBar, M. R. Hoque, “Patient acceptance of e-health services in Saudi Arabia: An integrative perspective”, Journal of Telemedicine and e-Health, 2018

N. Hossain, F. Yokota, N. Sultana, A. Ahmed, “Factors influencing rural end-users' acceptance of e-health in developing countries: A study on portable health clinic in Bangladesh”, Telemedicine and e-Health, Vol. 25, No. 3, pp. 221-229, 2019

N. Sun, P. L. P. Rau, “The acceptance of personal health devices among patients with chronic conditions”, International Journal of Medical Informatics, Vol. 84, No. 4, pp. 288-297, 2015

M. R. Hoque, Y. Bao, G. Sorwar, “Investigating factors influencing the adoption of e-health in developing countries: A patient’s perspective”, Informatics for Health and Social Care, Vol. 42, No. 1, pp. 1-17, 2017

A. J. E. de Veer, J. M. Peeters, A. E. M. Brabers, F. G. Schellevis, J. J. D. J. M. Rademakers, A. L. Francke, “Determinants of the intention to use e-Health by community dwelling older people”, BMC Health Services Research, Vol. 15, 2015

D. Pal, S. Funilkul, N. Charoenkitkarn, P. Kanthamanon, “Internet-of-things and smart homes for elderly healthcare: An end-user perspective”, IEEE Access, Vol. 6, pp. 10483-10496, 2018

V. Dutot, F. Bergeron, K. Rozhkova, N. Moreau, “Factors affecting the adoption of connected objects in e-health: A mixed methods approach”, Systemes d'Information et Management, Vol. 23, No. 4, 2019

H. Emad, H. M. El-Bakry, A. Asem, “A modified technology acceptance model for health informatics”, International Journal of Artificial Intelligence and Mechatronics, Vol. 4, No. 4, pp. 153-161, 2016

S. Dunnebeil, A. Sunyaev, I. Blohm, J. M. Leimeister, H. Krcmar, “Determinants of physicians’ technology acceptance for e-health in ambulatory care”, International Journal of Medical Informatics, Vol. 81, No. 11, pp. 746-760, 2012

M. Alanazi1, B. Soh, “Internet-of-Things for healthcare purposes: extending the technology acceptance model for Saudi Arabia patients”, International Journal of Computer Science and Network Security, Vol. 19, No. 2, pp. 74-81, 2019

F. E. Idachaba, E. M. Idachaba, “Robust e-health communication architecture for rural communities in developing countries”, Engineering, Technology & Applied Science Research, Vol. 2, No. 3, pp. 237-240, 2012

D. Virmani, P. Girdhar, P. Jain, P. Bamdev, “FDREnet: face detection and recognition pipeline”, Engineering, Technology & Applied Science Research, Vol. 9, No. 2, pp. 3933-3938, 2019

P. Shayan, E. Iscioglu, “An assessment of students’ satisfaction level from learning management systems: case study of Payamnoor and Farhangian Universities”, Engineering, Technology & Applied Science Research, Vol. 7, No. 4, pp. 1874-1878, 2017




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