Abstract
This paper focuses on the prevention of cervical cancer as a case lestudy, exploring the impact and role of health information on public health and individual health concepts, and further strengthening women’s concerns about their own health. Based on 2 × 2 online random experiment, the experimental materials about cervical cancer are designed with different degree of fear appeals (Low Threat/High Threat Intensity) and different types of information (Narrative/Statistical Evidence). 300 women in appropriate age are the target research participant. The results show that the threat intensity and the type of evidence have impact on the attitude of the participants. The experimentally pre-set randomized four scenes found a significant difference after the pairwise comparison, and the willingness to prevent of the four scenes present a high trend in the comparison results with the control group. Individuals’ perceptions of disease fear and their willingness to prevent cervical cancer are influenced by the intensity of the threat and the type of evidence. For the perception of fear effectiveness, the two types of evidentiary changes in the level of the threat of narrative evidence and the message of the high threat level will significantly affect the fear efficacy score. However, in the measurement of prevention intention, the persuasive effect of narrative evidence under the high threat intensity is significantly higher than that of statistical evidence and vice versa. By measuring the participants’ perceptions of fear effectiveness and degree of prevention intention, the media health massage design strategy and the content structure of media health information to maximize the persuasive effect in the limited conditions could be concluded.
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We thank the women who participated in this research study.
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Ran, H., Geng, S., Xiao, D. (2018). Media Message Design via Health Communication Perspective: A Study of Cervical Cancer Prevention. In: Chen, H., Fang, Q., Zeng, D., Wu, J. (eds) Smart Health. ICSH 2018. Lecture Notes in Computer Science(), vol 10983. Springer, Cham. https://doi.org/10.1007/978-3-030-03649-2_27
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DOI: https://doi.org/10.1007/978-3-030-03649-2_27
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