Gong L, Jiang H, Wu X, Kong Y, Gao Y, Liu H, Guo Y, Hu D. Exploring Users' Health Behavior Changes in Online Health Communities: Heuristic-Systematic Perspective Study.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022;
19:ijerph191811783. [PMID:
36142055 PMCID:
PMC9517559 DOI:
10.3390/ijerph191811783]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 09/14/2022] [Accepted: 09/16/2022] [Indexed: 06/10/2023]
Abstract
(1) Background: With the continuous advancement of internet technology, use of the internet along with medical service provides a new solution to solve the shortage of medical resources and the uneven distribution of available resources. Online health communities (OHCs) that emerged at this historical moment have flourished with various advantages, such as being free from location and time constraints. Understanding users' behavior changes via engagement in OHCs is necessary to support the development of internet medicine and promote public health. (2) Methods: The hypotheses of our research model were developed based on the protective action decision model (PADM) and heuristic-systematic model (HSM). A questionnaire was developed with seven constructs through previous studies and verified using a presurvey. Our survey respondents are online health community users. We used structural equation modelling to test the research hypotheses. (3) Results: The results of the analysis of 290 valid samples showed that the research model fit the data collected well. The perceived benefits (PB) positively affect information needs (IN) (beta = 0.280, p < 0.001, R2 = 0.252), thereby promoting users' engagement in OHCs (EOHCs) (beta = 0.353, p < 0.001, R2 = 0.387); EOHCs has a significant positive impact on health behavior change (HBC) (beta = 0.314, p < 0.001), and it also significantly positively affects users' health behavior change through systematic processing indirectly (beta = 0.252, p < 0.001, R2 = 0.387). (4) Conclusions: Our study offers support for the usefulness of the PADM and HSM in explaining users' health behavior changes. For practitioners, this study introduces influence processes as policy tools that managers can employ for health-promoting with mHealth.
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