Cancer-Prevention Messages on Chinese Social Media: A Content Analysis Grounded in the Extended Parallel Process Model and Attribution Theory Model and Attribution Theory

Authors

  • Jingyuan Shi Hong Kong Baptist University
  • Xiaohui Wang Hong Kong Baptist University
  • Tai-Quan Peng Michigan State University
  • Liang Chen Sun Yat-sun University

Keywords:

extended parallel process model, attribution theory, cancer-prevention messages, social media, Weibo

Abstract

To elucidate the Chinese public’s awareness of cancer and its possible prevention, we investigated cancer-prevention messages presented on Weibo, a Twitter-like Chinese social media platform, with reference to the extended parallel process model (EPPM) and attribution theory. With a sample of 16,654 cancer-related messages, we analyzed whether the messages acknowledged cancer’s threat, indicated collective or individual efficacy in preventing cancer, and attributed cancer to known causes. Results revealed that 4,545 of the messages (27.3%) mentioned cancer prevention, 127 (2.8%) described the severity of the threat of cancer, and 1,622 (35.7%) emphasized people’s susceptibility to cancer. Relative to messages indicating collective efficacy in cancer prevention (n = 523, 11.5%) and environmental causes of cancer (n = 34, 0.75%), messages indicating individual efficacy (n = 3,647, 79.8%) and individual causes (n = 1,505, 33.3%) were far more prevalent. Our findings illuminate Chinese people’s beliefs about cancer prevention as well as indicate potential effects of social media messages on individuals’ cancer-prevention beliefs and behaviors according to the premises of the EPPM and attribution theory. In closing, we discuss what our findings imply for theory construction and cancer-prevention campaigns.

Author Biographies

Jingyuan Shi, Hong Kong Baptist University

Assistant Professor, Hong Kong Baptist University

Xiaohui Wang, Hong Kong Baptist University

Research Assistant Professor, Hong Kong Baptist University

Tai-Quan Peng, Michigan State University

Associate Professor, Michigan State University

Liang Chen, Sun Yat-sun University

Associate Professor, Sun Yat-sun University

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Published

2019-04-29

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Section

Articles