The Behavioral Intention in Accessing Digital Healthcare Information on Social Media
DOI:
https://doi.org/10.32628/IJSRST218673Keywords:
Healthcare, social media, satisfaction, UTAUT modelAbstract
Purpose: Social media healthcare is becoming increasingly important in healthcare as many individuals seek healthcare information and support through online social media platforms. Social media healthcare is an emerging field; however, it is not clear what factors influence an individual’s acceptance of its usage. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the study explores the factors that influence acceptance of social media usage for healthcare by consumers. Design/Method: Using a purposive sampling approach, the researchers sent a validated questionnaire link to participants through social media platforms. A total of 260 responses from respondents were analyzed using SmartPLS3. Results: Analysis of the data revealed that performance expectancy, effort expectancy, social influence, and satisfaction significantly impact consumers’ behavior intention to embrace social media health information. The effect of four identified factors: “PE” (β = .415, t-value = 3.194, p < .001), “EE” (β = -. 3.98, t-value = 2.443, p < .015), “SI” (β = .593, t-value = 3.774, p < .000), “SAT” (β = .312, t-value = 2.676, p < .008). Conclusions: Social media health is vital to healthcare seekers, especially where it enables consumers to manage their health. On implication, the study provides healthcare givers and professionals insight on how to approach and advance social media healthcare education and interaction with consumers.
References
Purpose: Social media healthcare is becoming increasingly important in healthcare as many individuals seek healthcare information and support through online social media platforms. Social media healthcare is an emerging field; however, it is not clear what factors influence an individual’s acceptance of its usage. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the study explores the factors that influence acceptance of social media usage for healthcare by consumers.
Design/Method: Using a purposive sampling approach, the researchers sent a validated questionnaire link to participants through social media platforms. A total of 260 responses from respondents were analyzed using SmartPLS3.
Results: Analysis of the data revealed that performance expectancy, effort expectancy, social influence, and satisfaction significantly impact consumers’ behavior intention to embrace social media health information. The effect of four identified factors: “PE” (β = .415, t-value = 3.194, p < .001), “EE” (β = -. 3.98, t-value = 2.443, p < .015), “SI” (β = .593, t-value = 3.774, p < .000), “SAT” (β = .312, t-value = 2.676, p < .008).
Conclusions: Social media health is vital to healthcare seekers, especially where it enables consumers to manage their health. On implication, the study provides healthcare givers and professionals insight on how to approach and advance social media healthcare education and interaction with consumers.
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