Rao Qingmao, Zhang Zuyue, Lv Yalan, Zhao Yong, Bai Li, Hou Xiaorong
College of Medical Informatics, Chongqing Medical University, Chongqing, China.
Medical Data Science Academy, Chongqing Medical University, Chongqing, China.
JMIR Med Inform. 2020 Oct 9;8(10):e20558. doi: 10.2196/20558.
Social media is a powerful tool for the dissemination of health messages. However, few studies have focused on the factors that improve the influence of health messages on social media.
To explore the influence of goal-framing effects, information organizing, and the use of pictures or videos in health-promoting messages, we conducted a case study of Sina Weibo, a popular social media platform in China.
Literature review and expert discussion were used to determine the health themes of childhood obesity, smoking, and cancer. Web crawler technology was employed to capture data on health-promoting messages. We used the number of retweets, comments, and likes to evaluate the influence of a message. Statistical analysis was then conducted after manual coding. Specifically, binary logistic regression was used for the data analyses.
We crawled 20,799 Sina Weibo messages and selected 389 health-promoting messages for this study. Results indicated that the use of gain-framed messages could improve the influence of messages regarding childhood obesity (P<.001), smoking (P=.03), and cancer (P<.001). Statistical expressions could improve the influence of messages about childhood obesity (P=.02), smoking (P=.002), and cancer (P<.001). However, the use of videos significantly improved the influence of health-promoting messages only for the smoking-related messages (P=.009).
The findings suggested that gain-framed messages and statistical expressions can be successful strategies to improve the influence of messages. Moreover, appropriate pictures and videos should be added as much as possible when generating health-promoting messages.
社交媒体是传播健康信息的有力工具。然而,很少有研究关注能提高健康信息在社交媒体上影响力的因素。
为探究目标框架效应、信息组织以及图片或视频在健康促进信息中的使用所产生的影响,我们对中国流行的社交媒体平台新浪微博进行了一项案例研究。
采用文献综述和专家讨论来确定儿童肥胖、吸烟和癌症等健康主题。运用网络爬虫技术收集健康促进信息的数据。我们使用转发数、评论数和点赞数来评估一条信息的影响力。然后在人工编码后进行统计分析。具体而言,使用二元逻辑回归进行数据分析。
我们抓取了20799条新浪微博信息,并为本研究选取了389条健康促进信息。结果表明,采用获益框架信息能够提高关于儿童肥胖(P<.001)、吸烟(P=.03)和癌症(P<.001)的信息的影响力。统计表述能够提高关于儿童肥胖(P=.02)、吸烟(P=.002)和癌症(P<.001)的信息的影响力。然而,视频的使用仅对与吸烟相关的信息显著提高了健康促进信息的影响力(P=.009)。
研究结果表明,获益框架信息和统计表述可以成为提高信息影响力的成功策略。此外,在生成健康促进信息时应尽可能添加合适的图片和视频。