Empirical Investigation of User Attitudes towards Emerging Technologies in Healthcare: Using the SOHI Model
DOI:
https://doi.org/10.54741/ssjar.4.1.3Keywords:
attitude, healthcare information, performance expectancy, social influence, satisfaction, sohi, usersAbstract
The advancement of technology and the internet have increased social media platforms' popularity in recent years. Intending to extend the social media healthcare information [SOHI] model, this study incorporates attitudes toward social media [ATTSM] to extend the model. The model was tested using SmartPLS in a quantitative study with 310 participants. The results reveal that performance expectancy of social media (PESM) has a positive and significant influence on ATTSM and satisfaction with social media (SATSM), respectively. The findings show that both ATTSM and SATSM are significantly impacted by social influence on social media (SISM). In addition, ATTSM and SATSM significantly affected the behavioural intention of social media (BISM). Furthermore, the outcome indicated that BISM has a major effect on how people use SOHI. By testing SOHI with the integration of ATTSM, it has been proven that attitude plays a critical role in users’ decisions to use social media for healthcare.
Downloads
References
Adov L, Pedaste M, & Leijen Ä, et al. (2020) Does it have to be easy, useful, or do we need something else? STEM teachers’ attitudes towards mobile device use in teaching. Technology, Pedagogy and Education. Routledge, pp. 511–526. doi:10.1080/1475939X.2020.1785928.
Afrizal D. (2021). Attitude on intention to use e- government in Indonesia. Indonesian Journal of Electrical Engineering and Computer Science, 435–441. doi:10.11591/ijeecs.v22.i1.pp435-441.
Ajzen I, & Fishbein M. (2000) Attitudes and the attitude-behavior relation : Reasoned and automatic processes. European Review of Social Psychology, 11(1). Taylor and Francis Inc., pp. 1–33. doi:10.1080/14792779943000116.
Altalhi M. (2020). Toward a model for acceptance of MOOCs in higher education : the modified UTAUT model for Saudi Arabia. Education and Information Technologies, 26(2), 1589–1605. doi:10.1007/s10639-020-10317-x.
Chatterjee S, & Bhattacharjee KK. (2020) Adoption of artificial intelligence in higher education: a quantitative analysis using structural equation modelling. Education and Information Technologies. doi:10.1007/s10639-020-10159-7.
Chatterjee S, & Kumar Kar A. (2020). Why do small and medium enterprises use social media marketing and what is the impact: Empirical insights from India. International Journal of Information Management, 53. Elsevier: 102103. doi:10.1016/j.ijinfomgt.2020.102103.
Chen X, Hay JL, & Waters EA, et al. (2018) Health literacy and use and trust in health information health literacy and use and trust in health information. Journal of Health Communication, 00(00), 1–11. doi:10.1080/10810730.2018.1511658.
Chin WW. (1998). The partial least squares approach for structural equation modeling. Modern methods for business research. Methodology for business and management. Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.
Dai B, Larnyo E, & Tetteh EA, et al. (2019) Factors affecting caregivers’ acceptance of the use of wearable devices by patients with dementia: An extension of the unified theory of acceptance and use of technology model. American Journal of Alzheimer’s Disease and other Dementias, 35, 1–11. doi:10.1177/1533317519883493.
Davis FD, Bagozzi RP, & Warshaw PR. (1989) User acceptance of computer technology : A comparison of two theoretical models. Management Science, 35(8), 982–1003. doi:10.1287/mnsc.35.8.982.
Deng L, Turner DE, & Gehling R, et al. (2010) User experience, satisfaction, and continual usage intention of IT. European Journal of Information Systems, 19(1), 60–75. doi:10.1057/ejis.2009.50.
DeVries DL, & Ajzen I. (1971). The relationship of attitudes and normative beliefs to cheating in college. Journal of Social Psychology, 83(2), 199–207. doi:10.1080/00224545.1971.9922463.
Eagly AH, & Chaiken S. (1993) The psychology of attitudes. Orlando, FL, US: Harcourt Brace Jovanovich College Publishers.
Fornell C, & Larcker DF. (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. doi:10.1177%2F002224378101800104.
Geisser S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101–107. doi:10.1093/biomet/61.1.101.
Godin G, Valois P, & Lepage L. (1993) The pattern of influence of perceived behavioral control upon exercising behavior: An application of Ajzen’s theory of planned behavior. Journal of Behavioral Medicine, 16(1), 81–102. doi:10.1007/BF00844756.
Gruzd A, Staves K, & Wilk A. (2012) Connected scholars: Examining the role of social media in research practices of faculty using the UTAUT model. Computers in Human Behavior, 28(6), 2340–2350. doi:10.1016/j.chb.2012.07.004.
Hair J, Hult TMG, & Ringle CM, et al. (2016) A primer on partial least squares structural equation modeling (PLS-SEM). International Journal of Research & Method in Education, 38(2), 220–221. doi:10.1080/1743727x.2015.1005806.
Hair JF, Ringle CM, & Sarstedt M. (2011) PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. doi:10.2753/MTP1069-6679190202.
Hee S, Chil C, & Kim S. (2019). Consumer attitudes, intention to use technology, purchase intention of Korean 20’s women on the acceptance of fashion augmented reality (FAR) with the application of the UTAUT. 43(1), 125–137.
Henseler J, Ringle CM, & 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. doi:10.1007/s11747-014-0403-8.
Hernandez B, Montaner T, & Sese FJ, et al. (2011). Computers in human behavior the role of social motivations in e-learning : How do they affect usage and success of ICT interactive tools?. Computers in Human Behavior, 27(6), 2224–2232. doi:10.1016/j.chb.2011.07.001.
Hoque R, & Sorwar G. (2017). Understanding factors influencing the adoption of mhealth by the elderly : An extension of the UTAUT model. International Journal of Medical Informatics, 101, 75–84. doi:10.1016/j.ijmedinf.2017.02.002.
Hsu MH, & Chiu CM. (2004). Predicting electronic service continuance with a decomposed theory of planned behaviour. Behaviour and Information Technology, 23(5), 359–373. doi:10.1080/01449290410001669969.
Ifinedo P. (2016). Applying uses and gratifications theory and social influence processes to understand students ’ pervasive adoption of social networking sites : Perspectives from the Americas. International Journal of Information Management, 36, 192–206.
Ikpi NE, Undelikwo VA, & Ubi LO. (2022). Social media use for patient care: an evaluation of health practitioners in Cross River state, Nigeria. International Journal of Public Health Science, 11(4), 1249–1256. doi:10.11591/ijphs.v11i4.21765.
Jaks R, Baumann I, & Juvalta S, et al. (2019) Parental digital health information seeking behavior in Switzerland : a cross-sectional study. BMC Public Health, 1–11.
Jin XL, Zhou Z, & Yu X. (2019). Predicting users’ willingness to diffuse healthcare knowledge in social media: A communicative ecology perspective?. Information Technology and People, 32(4), 1044–1064. doi:10.1108/ITP-03-2018-0143.
Jung HJ, Choi YJ, & Oh KW. (2020). Influencing factors of chinese consumers’ purchase intention to sustainable apparel products: Exploring consumer “attitude–behavioral intention” gap. Sustainability (Switzerland), 12(5), 1–14. doi:10.3390/su12051770.
Kapoor A, Guha S, & Kanti Das M, et al. (2020) Digital healthcare: The only solution for better healthcare during COVID-19 pandemic?. Indian Heart Journal, 72(2), 61–64. doi:10.1016/j.ihj.2020.04.001.
Karimy M, Rezaee-Momtaz M, & Tavousi M, et al. (2019) Risk factors associated with self-medication among women in Iran. BMC Public Health, 19(1), 1–7. doi:10.1186/s12889-019-7302-3.
Khatoon S, Zhengliang X, & Hussain H. (2020) The mediating effect of customer satisfaction on the relationship between electronic banking service quality and customer purchase intention: Evidence from the Qatar banking sector. SAGE Open, 10(2), 1–12. doi:10.1177/2158244020935887.
Kim SS, & Malhotra NK. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management Science, 51(5), 741–755. doi:10.1287/mnsc.1040.0326.
Li X, & Liu Q. (2020). Social media use, eHealth literacy, disease knowledge, and preventive behaviors in the COVID-19 pandemic: Cross-sectional study on chinese netizens. Journal of Medical Internet Research, 22(10). doi:10.2196/19684.
Liu R, Zhang R, & Lu X. (2018). An empirical study on the relationship between the satisfaction of internet health information and patient compliance-Based on trust perspective. ACM International Conference Proceeding Series, 61–66. doi:10.1145/3268891.3268900.
Lopez P, Kalinic Z, & Higueras-castillo E, et al. (2019) A multi-analytical approach to modeling of customer satisfaction and intention to use in Massive Open Online Courses (MOOC). Interactive Learning Environments, 0(0), 1–19. doi:10.1080/10494820.2019.1636074.
Malik FS, Panlasigui N, & Gritton J, et al. (n.d.) Adolescent perspectives on the use of social media to support type 1 diabetes management. doi:10.2196/12149.
Marar SD, Al-madaney MM, & Almousawi FH. (2019) Health information on social media. Perceptions, attitudes, and practices of patients and their companions. Saudi Medical Journal, 40(12), 1294–1298. doi:10.15537/smj.2019.12.24682.
Marinković V, Đorđević A, & Kalinić Z. (2019). The moderating effects of gender on customer satisfaction and continuance intention in mobile commerce : A UTAUT-based perspective. Technology Analysis & Strategic Management, 0(0), 1–13. doi:10.1080/09537325.2019.1655537.
Mclean G. (2020). Examining consumer attitudes towards retailers ’ m-commerce mobile applications – An initial adoption vs . continuous use perspective. Journal of Business Research, 106, 139–157. doi:10.1016/j.jbusres.2019.08.032.
Mhina JRA, Md Johar MG, & Alkawaz MH. (2019). The influence of perceived confidentiality risks and attitude on Tanzania government employees’ intention to adopt web 2.0 and social media for work-related purposes. International Journal of Public Administration, 42(7), 558–571. doi:10.1080/01900692.2018.1491596.
Nurhayati S, Anandari D, & Ekowati W. (2019). Unified theory of acceptance and usage of technology (UTAUT) model to predict health information system adoption. Jurnal Kesehatan Masyarakat, 15(1), 89–97. doi:10.15294/kemas.v15i1.12376.
Ofori PP, & Oduro-Asante A. (2022). Using extraversion to investigate social media purchase adoption. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 8(4), 91–104. doi:10.32628/cseit22849.
Ofori PP, & Wang W. (2022). Emerging technologies adoption in healthcare: A SOHI model. Information Development, 1–19. doi:10.1177/02666669221113766.
Ofori Philomina P, Antwi EA, & Asante-oduro A. (2021). The behavioral intention in accessing digital healthcare information on social media. International Journal of Scientific Research in Science and Technology, 8(6), 510–521. doi:10.32628/IJSRST218673.
Ofori Philomina P., Antwi EA, & Owusu-Ansah KA. (2021). The mediating effects of satisfaction and attitude on consumers’ intent toward adoption of social media healthcare information. Journal of Health and Social Sciences, 6(3), 391–402. doi:10.19204/2021/thmd5.
Passafaro P. (2019). Attitudes and tourists’ sustainable behavior : An overview of the literature and discussion of some theoretical and methodological issues. Journal of Travel Research. doi:10.1177/0047287519851171.
Praveena K, & Thomas S. (2018). Explaining user acceptance and usage of social networking sites: The role of trust, social connectedness and visibility in extending UTAUT2. International Journal of Management Practice, 11(3), 318–334. doi:10.1504/IJMP.2018.092855.
Puspitasari I, & Firdauzy A. (2019). Characterizing consumer behavior in leveraging social media for e-patient and health-related activities. International Journal of Environmental Research and Public Health, 16(18), 3–5. doi:10.3390/ijerph16183348.
Rahman MF, Persada SF, & Nadlifatin R, et al. (2020). Measuring the consumers’ satisfaction and behavior intention on games marketplace technology platform: A perspective of two combination behavior models. International Journal of Scientific and Technology Research, 9(1), 193–197.
Reinartz W, Haenlein M, & Henseler J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. International Journal of Research in Marketing, 26(4), 332–344. doi:10.1016/j.ijresmar.2009.08.001.
Ryu JS, & Fortenberry S. (2021). Performance expectancy and effort expectancy in omnichannel retailing. Journal of Industrial Distribution & Business, 12(4), 27–34.
Shang L, Zhou J, & Zuo M. (2020). Understanding older adults’ intention to share health information on social media: the role of health belief and information processing. Internet Research, 31(1), 1066–2243. doi:10.1108/INTR-12-2019-0512.
Silver RA, Subramaniam C, & Stylianou A. (2020). The impact of portal satisfaction on portal use and health-seeking behavior: Structural equation analysis. Journal of Medical Internet Research, 22(3), 1–13. doi:10.2196/16260.
Stone M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B (Methodological), 36(2), 111–133. doi:10.1111/j.2517-6161.1974.tb00994.x.
Tachie SA, & Brenya B. (2022). Lecturers’ perceptions of students’ social media exposure and its influence on mathematics performance. International Journal of Research in Business and Social Science, 11(6), 487–499. doi:10.20525/ijrbs.v11i6.1929.
Tan SSL, & Goonawardene N. (2017). Internet health information seeking and the patient-physician relationship: A systematic review. Journal of Medical Internet Research, 19(1). doi:10.2196/jmir.5729.
Tran TP. (2017). Personalized ads on Facebook: An effective marketing tool for online marketers. Journal of Retailing and Consumer Services, 230–242. doi:10.1016/j.jretconser.2017.06.010.
Venkatesh V, & Davis FD. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. doi:10.1287/mnsc.46.2.186.11926.
Venkatesh V, Morris MG, & Davis GB, et al. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. doi:10.1016/j.inoche.2016.03.015.
Wang N, & Sun Y. (2016). Social influence or personal preference? Examining the determinants of usage intention across social media with different sociability. Information Development, 32(5), 1442–1456. doi:10.1177/0266666915603224.
Wang Z, Wang J, & Maercker A. (2016). Program use and outcome change in a web-based trauma intervention: Individual and social factors. Journal of medical Internet research, 18(9), e243. doi:10.2196/jmir.5839.
Wu T, Deng Z, & Zhang D, et al. (2018). Seeking and using intention of health information from doctors in social media: The effect of doctor-consumer interaction. International Journal of Medical Informatics, 115, 106–113. doi:10.1016/j.ijmedinf.2018.04.009.
Zaremohzzabieh Z, Ismail N, & Ahrari S, et al. (2021) The effects of consumer attitude on green purchase intention: A meta-analytic path analysis. Journal of Business Research, 132, 732–743. doi:10.1016/j.jbusres.2020.10.053.
Zhang L, Jung EH, & Chen Z. (2019). Modeling the pathway linking health information seeking to psychological well-being on wechat. Health Communication, 0(00), 1–12. doi:10.1080/10410236.2019.1613479.
Zhang X, Wen D, & Liang J, et al. (2017) How the public uses social media wechat to obtain health information in china: a survey study. BMC Medical Informatics and Decision Making, 17(2), 66. doi:10.1186/s12911-017-0470-0.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Philomina Ofori, Ethel Asante Antwi, Boahemaa Brenya, Abigail Wiafe
This work is licensed under a Creative Commons Attribution 4.0 International License.
