IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-03090-6.html
   My bibliography  Save this article

Exploring the resistance to e-health services in Nigeria: an integrative model based upon the theory of planned behavior and stimulus-organism-response

Author

Listed:
  • Mingyue Fan

    (Jiangsu University)

  • Brendan Chukwuemeka Ezeudoka

    (Jiangsu University)

  • Sikandar Ali Qalati

    (Liaocheng University)

Abstract

Despite the evident advantages of electronic health services (eHS), there is a noticeable opposition to their acceptance, which has raised a crucial question about why people, particularly in developing nations, oppose the acceptance of eHS. This study was designed to obtain a comprehensive understanding of the factors that influence the rigid opposition to eHS by integrating two theoretical models: the Stimulus-Organism-Response theory and the Theory of Planned Behavior. In our detailed survey, 543 respondents over 18 years old from various regions of Nigeria participated. We evaluated the proposed model using partial least squares structural equation modeling (PLS-SEM). The findings indicated that lower health literacy was associated with a greater opposition to using eHS. In addition, communication and choice overload and perceived risk contributed to a negative attitude toward eHS. Subjective norms played a significant role in influencing the intention not to use eHS, which highlights social pressure’s effect. Further, a greater perception of behavioral control reduced the intention not to use eHS. Ultimately, the intention not to use eHS affected eHS rejection behavior significantly, which makes resistance to it a substantial problem. This research unveils factors that contribute to this behavior and provides insights for policymakers in the health field, with the goal to improve people’s acceptance of eHS. Further research is recommended in different geographical samples and contexts to gain a better understanding of the factors related to eHS rejection behavior.

Suggested Citation

  • Mingyue Fan & Brendan Chukwuemeka Ezeudoka & Sikandar Ali Qalati, 2024. "Exploring the resistance to e-health services in Nigeria: an integrative model based upon the theory of planned behavior and stimulus-organism-response," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03090-6
    DOI: 10.1057/s41599-024-03090-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-03090-6
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-024-03090-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Roger A Atinga & Patience Aseweh Abor & Saratu Jenepha Suleman & Emmanuel Anongeba Anaba & Bii Kipo, 2020. "e-health usage and health workers’ motivation and job satisfaction in Ghana," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-10, September.
    2. Keller, Kevin Lane & Staelin, Richard, 1987. "Effects of Quality and Quantity of Information on Decision Effectiveness," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(2), pages 200-213, September.
    3. Liu, Yanfeng & Cai, Lanhui & Ma, Fei & Wang, Xueqin, 2023. "Revenge buying after the lockdown: Based on the SOR framework and TPB model," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    4. Wu, Ing-Long & Chiu, Mai-Lun & Chen, Kuei-Wan, 2020. "Defining the determinants of online impulse buying through a shopping process of integrating perceived risk, expectation-confirmation model, and flow theory issues," International Journal of Information Management, Elsevier, vol. 52(C).
    5. Yuanyuan Cao & Junjun Li & Xinghong Qin & Baoliang Hu, 2020. "Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective," IJERPH, MDPI, vol. 17(18), pages 1-23, September.
    6. Ackerman, Sara L. & Tebb, Kathleen & Stein, John C. & Frazee, Bradley W. & Hendey, Gregory W. & Schmidt, Laura A. & Gonzales, Ralph, 2012. "Benefit or burden? A sociotechnical analysis of diagnostic computer kiosks in four California hospital emergency departments," Social Science & Medicine, Elsevier, vol. 75(12), pages 2378-2385.
    7. Courtney Suess & Makarand Mody, 2018. "The influence of hospitable design and service on patient responses," The Service Industries Journal, Taylor & Francis Journals, vol. 38(1-2), pages 127-147, January.
    8. Mariusz Duplaga, 2020. "The Acceptance of Key Public Health Interventions by the Polish Population Is Related to Health Literacy, But Not eHealth Literacy," IJERPH, MDPI, vol. 17(15), pages 1-19, July.
    9. Sabrina Zeike & Kyung-Eun Choi & Lara Lindert & Holger Pfaff, 2019. "Managers’ Well-Being in the Digital Era: Is it Associated with Perceived Choice Overload and Pressure from Digitalization? An Exploratory Study," IJERPH, MDPI, vol. 16(10), pages 1-15, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peng Cheng & Zhe Ouyang & Yang Liu, 0. "The effect of information overload on the intention of consumers to adopt electric vehicles," Transportation, Springer, vol. 0, pages 1-20.
    2. Liu, Chih-Hsing & Dong, Tse-Ping & Vu, Ho Tran, 2023. "Transformed virtual concepts into reality: Linkage the viewpoint of entrepreneurial passion, technology adoption propensity and advantage to usage intention," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    3. Swait, Joffre & Adamowicz, Wiktor, 2001. "Choice Environment, Market Complexity, and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 86(2), pages 141-167, November.
    4. Uddin, Md Hamid & Mollah, Sabur & Islam, Nazrul & Ali, Md Hakim, 2023. "Does digital transformation matter for operational risk exposure?," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    5. Zhang, Yufei & Voorhees, Clay M. & Lin, Chen & Chiang, Jeongwen & Hult, G.Tomas M. & Calantone, Roger J., 2022. "Information Search and Product Returns Across Mobile and Traditional Online Channels," Journal of Retailing, Elsevier, vol. 98(2), pages 260-276.
    6. Stephane Hess & Andrew Daly & Maria Börjesson, 2020. "A critical appraisal of the use of simple time-money trade-offs for appraisal value of travel time measures," Transportation, Springer, vol. 47(3), pages 1541-1570, June.
    7. Janssen, Marijn & van der Voort, Haiko & Wahyudi, Agung, 2017. "Factors influencing big data decision-making quality," Journal of Business Research, Elsevier, vol. 70(C), pages 338-345.
    8. J. Miguel Villas-Boas, 2009. "Product Variety and Endogenous Pricing with Evaluation Costs," Management Science, INFORMS, vol. 55(8), pages 1338-1346, August.
    9. Zafar, Abaid Ullah & Shahzad, Mohsin & Ashfaq, Muhammad & Shahzad, Khuram, 2023. "Forecasting impulsive consumers driven by macro-influencers posts: Intervention of followers' flow state and perceived informativeness," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    10. Peng Cheng & Zhe Ouyang & Yang Liu, 2020. "The effect of information overload on the intention of consumers to adopt electric vehicles," Transportation, Springer, vol. 47(5), pages 2067-2086, October.
    11. Aksoy, Lerzan & Cooil, Bruce & Lurie, Nicholas H., 2011. "Decision Quality Measures in Recommendation Agents Research," Journal of Interactive Marketing, Elsevier, vol. 25(2), pages 110-122.
    12. Collins, J. Michael & Simon, Kosali I. & Tennyson, Sharon, 2013. "Drug withdrawals and the utilization of therapeutic substitutes: The case of Vioxx," Journal of Economic Behavior & Organization, Elsevier, vol. 86(C), pages 148-168.
    13. Jeongwook Khang & Yung-Mok Yu & Hong-Hee Lee, 2014. "Moderating effects of the fit between service tangibilization and organizational performance," Service Business, Springer;Pan-Pacific Business Association, vol. 8(2), pages 239-266, June.
    14. Anna Hryniewicz & Dominika Wilczyńska & Daniel Krokosz & Konrad Hryniewicz & Mariusz Lipowski, 2022. "Well-Being of High-Level Managers during the Pandemic: The Role of Fear of Negative Appearance, Anxiety, and Eating Behaviors," IJERPH, MDPI, vol. 20(1), pages 1-9, December.
    15. DeShazo, J. R. & Fermo, German, 2002. "Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency," Journal of Environmental Economics and Management, Elsevier, vol. 44(1), pages 123-143, July.
    16. Huan-Ming Chuang & Yi-Deng Liao, 2021. "Sustainability of the Benefits of Social Media on Socializing and Learning: An Empirical Case of Facebook," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    17. Dmitriy Volinskiy & Wiktor L. Adamowicz & Michele Veeman & Lorie Srivastava, 2009. "Does Choice Context Affect the Results from Incentive-Compatible Experiments? The Case of Non-GM and Country-of-Origin Premia in Canola Oil," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 57(2), pages 205-221, June.
    18. Pathak, Kanishka & Prakash, Gyan, 2023. "Exploring the role of augmented reality in purchase intention: Through flow and immersive experience," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    19. Adam Sanjurjo, 2015. "Search, Memory, and Choice Error: An Experiment," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-16, June.
    20. Pokpong Amornvit & Sasiwimol Sanohkan, 2019. "The Accuracy of Digital Face Scans Obtained from 3D Scanners: An In Vitro Study," IJERPH, MDPI, vol. 16(24), pages 1-13, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03090-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.