Generation Mechanism of Health-related Video Coping Behaviors Among the Elderly Population in Beijing
DOI:
https://doi.org/10.18063/lne.v3i6.1165Keywords:
Health Communication, Elderly Population, WeChat ChannelsAbstract
With the accelerating global aging process, the health management needs of China's elderly population have become increasingly prominent. WeChat Channels, with its unique social attributes and short-video features, has emerged as a key platform for the elderly to access health information. However, there is a lack of systematic analysis of the coping behavior mechanisms of the elderly when engaging with health-related videos on this platform. Using snowball sampling, this research surveyed 125 elderly users in Beijing and found that content quality and outcome expectations positively influenced coping behaviors, while self-risk perception showed an overall positive effect but with concerns about false information negatively correlating with certain behaviors. The research expands theoretical applications and provides references for policy-making and platform optimization.
References
National Bureau of Statistics, 2025, Steady Progress in Economic Operations in 2024,with Major Development Goals Successfully Achieved. [2025-4-2].https://www.stats.gov.cn/sj/zxfb/202501/t20250117_1958332.html.
Fu S, Zeng Y, & Sun L, 2024, Influencing Factors of False Health Information Dissemination in Short Video: A Configuration Perspective. Library Journal, 43(404), 103.
Blumler J G, Katz E, 1974, The uses of mass communications: Current perspectives on gratifications research. Utilization of mass communication by the individual/BeverlyHills, CA: Sage.
Slater M D, Rouner D, 1996, How message evaluation and source attributes may influence credibility assessment and belief change. Journalism & Mass Communication Quarterly, 73(4), 974-991.
Lv Y, 2021, A Study on the Susceptibility of the Elderly to WeChat False Information in the Post-truth Era (Master’s thesis, Yunnan University of Finance and Economics). https://link.cnki.net/doi/10.27455/d.cnki.gycmc.2021.000391doi:10.27455/d.cnki.gycmc.2021.000391.
Ran X, Hu H, 2022, Urban-Rural Disparity, Digital Divide and Health Inequality of the Elderly. Population Journal, (03), 46-58. doi:10.16405/j.cnki.1004-129X.2022.03.004.
Avery E., Lariscy R., Amador E., et al., 2010, Diffusion of Social Media Among Public Relations Practitioners in Health Departments Across Various Community Population Sizes. Journal of Public Relations Research, 22(3), 336–358. https://doi.org/10.1080/10627261003614427.
Bol N., Vromans R D., Wezel M C., et al., 2024, A longitudinal analysis of adherence to COVID-19 preventive measures, media use, and risk perceptions in a Dutch population-based sample. Health Literacy and Communication Open, 2(1). https://doi.org/10.1080/28355245.2024.2355084.
Cao Q, Yuan C, 2013, A Literature Review of the Uses and Gratifications Theory. Southeast Communication, (12), 18-20.
Clayman M L., Manganello J A., Viswanath K., Hesse B W., & Arora N K., 2010, Providing Health Messages to Hispanics/Latinos: Understanding the Importance of Language, Trust in Health Information Sources, and Media Use. Journal of Health Communication, 15(sup3), 252–263. https://doi.org/10.1080/10810730.2010.522697.
Compeau D., Higgins C A., Huff S., 1999, Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study. MIS Quarterly, 23(2), 145–158. https://doi.org/10.2307/249749.
Perks L G, 2018, Media Marathoning and Health Coping. Communication Studies, 70(1), 19–35. https://doi.org/10.1080/10510974.2018.1519837.
Riley M W, 1954, Review of Communication and Persuasion: Psychological Studies of Opinion Change., by C. I. Hovland, I. L. Janis, & H. H. Kelley]. American Sociological Review, 19(3), 355–357. https://doi.org/10.2307/2087772.