Journal Press India^®

Author Details ( * ) denotes Corresponding author

This study explores factors influencing health-related social media use using the Analytic Hierarchy Process (AHP), with the goal of determining and ranking these factors by influence. The concepts of Uses and Gratification (U&G), Social Influence (SI), and Brand Credibility were investigated. The U&G paradigm, which is dominant, highlights the significance consumers place on platforms that provide knowledge and happiness. SI emphasized peer perspectives, whereas BC emphasized brand trustworthiness and expertise. Further research indicates that the “Identification” sub-factor of the Social Identity (SI) theory and the “Information Seeking” sub-factor of the Uses and Gratifications (U&G) theory are relevant. “Trustworthiness” and “Expertise” were used to build the brand’s credibility. In conclusion, this study reveals complex factors that influence people’s reliance on social media for health information, providing healthcare practitioners with useful insights for optimizing their online interactions.

Keywords

Social Media; Health Information; Analytic Hierarchy Process; Multi-Criteria Decision Making; Brand Credibility; Social Influence; Uses and Gratification

1. Ajzen, I. (1980). Understanding attitudes and predictiing social behavior. Englewood Cliffs, NJ: Prentice Hall.
2. Al Riyami, F., & Ashrafi, R. (2016). Factors impacting social media adoption in public sector organizations: Case of Oman. International Journal of Computing & Information Sciences, 12(2), 167-177.
3. Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ: Prentice Hall.
4. Blumler, J. G., & Katz, E. (1974). The uses of mass communications: Current perspectives on gratifications research. Sage Annual Reviews of Communication Research Volume III. Retrieved from https://www.scirp.org/reference/referencespapers?referenceid=2097913
5. Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55(1), 591-621.
6. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
7. Erdem, T., & Swait, J. (2004). Brand credibility, brand consideration, and choice. Journal of Consumer Research, 31(1), 191-198.
8. Fogg, B. J., Marshall, J., Laraki, O., & Osipovich, A. (2001, March). What makes web sites credible? A report on a large quantitative study. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 61-68).
9. French, J. R., Raven, B., & Cartwright, D. (1959). The bases of social power. Classics of Organization Theory, 7(1), 311-320.
10. George, D. R., Rovniak, L. S., & Kraschnewski, J. L. (2013). Dangers and opportunities for social media in medicine. Clinical Obstetrics and Gynecology, 56(3), 453-462.
11. Global Social Media Stats (2021). Retrieved from https://datareportal.com/social-media-users
12. Haythornthwaite, C. (2005). Social networks and internet connectivity effects. Information, Community & Society, 8(2), 125-147.
13. Hovland, C. I., Janis, I. L., & Kelley, H. H. (1953). Communication and persuasion; psychological studies of opinion change. Retrieved from https://psycnet.apa.org/record/1953-15071-000
14. IBEF (2021). Healthcare industry in India. Retrieved from https://www.ibef.org/industry/healthcare-india.aspx
15. Kaira, V. & Ahire, N. (2020). Social media usage in Indian hospitals-current scenarios and way ahead. Annals of Tropical Medicine and Public Health, 23(23). Retrieved from https://www.academia.edu/73921886/Social_media_usage_in_Indian_Hospitals_Current_scenarios_and_way_ahead
16. Kelman, H. C. (2017). Processes of opinion change. In Attitude change (pp. 205-233). Routledge.
17. Kumar, P., & Sharma, D. (2023). Benchmarking the financial performance of Indian commercial banks by a hybrid MCDM approach. International Journal of Process Management and Benchmarking, 15(3), 285-309.
18. Kumar, P., Sharma, D., & Singh, R. K. (2020). Financial performance evaluation of commercial banks by AHP: An evidence from India. Pacific Business Review International, 12(12), 21-37.
19. Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709-734.
20. Mitsutake, S., Takahashi, Y., Otsuki, A., Umezawa, J., Yaguchi-Saito, A., Saito, J., Fujimori, M., Shimazu, T. & INFORM Study Group. (2023). Chronic diseases and sociodemographic characteristics associated with online health information seeking and using social networking sites: Nationally representative cross-sectional survey in Japan. Journal of Medical Internet Research, 25, e44741. Retrieved from https://www.jmir.org/2023/1/e44741/
21. Park, T., Ju, I., Ohs, J. E., Hinsley, A., & Muzumdar, J. (2023). Information seeking during the COVID-19 pandemic: Application of the risk information seeking and processing model. Research in Social and Administrative Pharmacy, 19(6), 956-964.
22. PwC (2016). Indian healthcare on the cusp of a digital transformation. Retrieved from https://www.pwc.in/assets/pdfs/publications/2016/indian-healthcare-on-the-cusp-of-a-digital-transformation.pdf
23. Referral MD (2017). 24 Outstanding statistics and figures on how social media has impacted the health care industry. Retrieved from https://getreferralmd.com/2013/09/healthcare-social-media-statistics/
24. Rosenstock, I. M. (1974). Historical origins of the health belief model. Health Education Monographs, 2(4), 328-335.
25. Rubin, A. M. (1981). An examination of television viewing motivations. Communication research, 8(2), 141-165.
26. Rubin, A. M. (1983). Television uses and gratifications: The interactions of viewing patterns and motivations. Journal of Broadcasting & Electronic Media, 27(1), 37-51.
27. Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Communication & Society, 3(1), 3-37.
28. Saaty, T. L. (1991). Some mathematical concepts of the analytic hierarchy process. Behaviormetrika, 18(29), 1-9.
29. Shao, G. (2009). Understanding the appeal of user‐generated media: A uses and gratification perspective. Internet Research, 19(1), 7-25.
30. Shrestha, R. K., Alavalapati, J. R., & Kalmbacher, R. S. (2004). Exploring the potential for silvopasture adoption in south-central Florida: An application of SWOT–AHP method. Agricultural Systems, 81(3), 185-199.
31. Singh, R. K. (2013). Prioritizing the factors for coordinated supply chain using analytic hierarchy process (AHP). Measuring Business Excellence, 17(1), 80-97.
32. Statista (Jun 30, 2021). Size of the healthcare market in India from 2008 to 2017, with estimates until 2022. Retrieved from https://www.statista.com/statistics/701556/healthcare-sector-size-india/
33. Sundar, S. S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility (pp. 73-100). Cambridge, MA: MacArthur Foundation Digital Media and Learning Initiative.
34. Turner, J. C. (2010). Towards a cognitive redefinition of the social group. In Research Colloquium on Social Identity of the European Laboratory of Social Psychology, Dec, 1978, Université de Haute Bretagne, Rennes, France; This chapter is a revised version of a paper first presented at the aforementioned colloquium.. Psychology Press.
35. Turner, J. C., Hogg, M. A., Oakes, P. J., Reicher, S. D., & Wetherell, M. S. (1987). Rediscovering the social group: A self-categorization theory. Basil Blackwell.
36. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3), 425-478.
37. Ventola, C. L. (2014). Social media and health care professionals: Benefits, risks, and best practices. Pharmacy and Therapeutics, 39(7), 491.
38. Whiting, A., & Williams, D. (2013). Why people use social media: a uses and gratifications approach. Qualitative Market Research: An International Journal, 16(4), 362-369.
39. Wilson, T. D. (1997). Information behaviour: an interdisciplinary perspective. Information Processing & Management, 33(4), 551-572.
40. Zhou, T., & Xie, Y. (2023). Examining social media users’ information avoidance: An integration of cognitive dissonance and psychological empowerment. International Journal of Human–Computer Interaction, 1-10.