Department of Behavioral and Community Health Sciences, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Center for Social Dynamics and Community Health, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
J Health Commun. 2023 May 4;28(5):282-291. doi: 10.1080/10810730.2023.2201814. Epub 2023 Apr 14.
Previous research has found an association between awareness of e-cigarette, or vaping, product-use associated lung injury (EVALI) and lower intention to use e-cigarettes among young people. This study utilized Twitter data to evaluate if the January 2020 depiction of EVALI on New Amsterdam, Chicago Med, and Grey's Anatomy-three popular primetime medical dramas-could be a potential innovative avenue to raise awareness of EVALI. We obtained tweets containing e-cigarette-related search strings from 1/21/2020 to 02/18/2020 and filtered these with storyline-specific keywords, resulting in 1,493 tweets for qualitative coding by two trained human coders. Content codes were informed by prior research, theories of narrative influence, and e-cigarette related outcomes. Of 641 (42.9%) relevant tweets, the most frequent content codes were perceived realism ( = 292, 45.6%) and negative response ( = 264, 41.2%). A common theme among these tweets was that storylines were unrealistic because none of the characters with EVALI used THC-containing products. Approximately 12% of tweets ( = 78) mentioned e-cigarette knowledge and 28 (4.4%) mentioned behavior, including quitting e-cigarettes because of viewing the storylines. Implications for health communication research utilizing social media data and maximizing the achievement of positive health-related outcomes for storylines depicting current health topics are discussed.
先前的研究发现,年轻人对电子烟或蒸气产品相关肺损伤(EVALI)的认识与使用电子烟的意愿呈负相关。本研究利用 Twitter 数据评估 2020 年 1 月在《新阿姆斯特丹》《芝加哥急救》和《实习医生格蕾》这三部热门黄金时段医学剧中描述的 EVALI 是否可能成为提高 EVALI 意识的潜在创新途径。我们从 2020 年 1 月 21 日至 2 月 18 日获取了包含电子烟相关搜索词的推文,并使用故事情节特定的关键词对这些推文进行了筛选,结果有 1493 条推文由两位经过培训的人类编码员进行了定性编码。内容编码的依据是先前的研究、叙事影响理论和电子烟相关结果。在 641 条(42.9%)相关推文中,最常见的内容编码是感知的真实性( = 292,45.6%)和负面反应( = 264,41.2%)。这些推文中的一个常见主题是故事情节不真实,因为没有一个患有 EVALI 的角色使用含有 THC 的产品。约 12%的推文( = 78)提到了电子烟知识,28 条(4.4%)提到了行为,包括因为观看故事情节而戒烟。讨论了利用社交媒体数据进行健康传播研究并最大限度地实现描述当前健康主题的故事情节的积极健康相关结果的意义。