A behavioral intention model of Gen Z female’ health information behavior on social media
Purpose This study aims to develop and validate a behavioral intention model for understanding the health information behavior of Generation Z females on social media. The model integrates variables such as familiarity, e-health literacy, trust and altruistic motivation. Design/methodology/approach Conducted in Indonesia, the online survey involved 516 active female Generation Z respondents (aged 17–26) seeking health information on social media in the past six months. Utilizing the partial least squares structural equation model (PLS-SEM), the study employed Smart PLS Version 4.0 for rigorous model validation and hypothesis testing in two stages: measurement and structural model analyses. This encompassed evaluating reliability, convergent validity and discriminant validity. Findings Results indicate that familiarity, e-health literacy, trust and altruistic motivation significantly influence the health information behavior of Generation Z females on social media. Furthermore, both familiarity and e-health literacy positively impact trust in social media as a reliable health information source. The study explores theoretical, managerial and policy implications. Originality/value Social media has become a crucial platform for health-related information, particularly among Generation Z females. Despite this, there is a significant research gap in the behavioral intention model for Generation Z females’ health information behavior on social media. This study introduces a unique information behavioral intention model shedding light on this behavior.
Authors
- Sik Sumaedi (ORCID: https://orcid.org/0000-0003-3616-5977)
- Subhan Afifi (ORCID: https://orcid.org/0000-0001-7597-6655)
- Aris Yaman (ORCID: https://orcid.org/0000-0002-0305-9054)
- Iriana Bakti
Publication Details
- Journal
- Aslib Journal of Information Management
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1108/ajim-08-2024-0665
- Citations
- 4
- Primary Topic
- Digital Marketing and Social Media
- Type
- article
- Field-Weighted Citation Impact
- 16.81