PDF(Pubmed)
Abstract：
UNASSIGNED: Health warnings in tobacco advertisements provide health information while also increasing the perceived risks of tobacco use. However, existing federal laws requiring warnings on advertisements for tobacco products do not specify whether the rules apply to social media promotions.
UNASSIGNED: This study aims to examine the current state of influencer promotions of little cigars and cigarillos (LCCs) on Instagram and the use of health warnings in influencer promotions.
UNASSIGNED: Instagram influencers were identified as those who were tagged by any of the 3 leading LCC brand Instagram pages between 2018 and 2021. Posts from identified influencers, which mentioned one of the three brands were considered LCC influencer promotions. A novel Warning Label Multi-Layer Image Identification computer vision algorithm was developed to measure the presence and properties of health warnings in a sample of 889 influencer posts. Negative binomial regressions were performed to examine the associations of health warning properties with post engagement (number of likes and comments).
UNASSIGNED: The Warning Label Multi-Layer Image Identification algorithm was 99.3% accurate in detecting the presence of health warnings. Only 8.2% (n=73) of LCC influencer posts included a health warning. Influencer posts that contained health warnings received fewer likes (incidence rate ratio 0.59, P<.001, 95% CI 0.48-0.71) and fewer comments (incidence rate ratio 0.46, P<.001, 95% CI 0.31-0.67).
UNASSIGNED: Health warnings are rarely used by influencers tagged by LCC brands\' Instagram accounts. Very few influencer posts met the US Food and Drug Administration\'s health warning requirement of size and placement for tobacco advertising. The presence of a health warning was associated with lower social media engagement. Our study provides support for the implementation of comparable health warning requirements to social media tobacco promotions. Using an innovative computer vision approach to detect health warning labels in influencer promotions on social media is a novel strategy for monitoring health warning compliance in social media tobacco promotions.
UNASSIGNED: This study aims to examine the current state of influencer promotions of little cigars and cigarillos (LCCs) on Instagram and the use of health warnings in influencer promotions.
UNASSIGNED: Instagram influencers were identified as those who were tagged by any of the 3 leading LCC brand Instagram pages between 2018 and 2021. Posts from identified influencers, which mentioned one of the three brands were considered LCC influencer promotions. A novel Warning Label Multi-Layer Image Identification computer vision algorithm was developed to measure the presence and properties of health warnings in a sample of 889 influencer posts. Negative binomial regressions were performed to examine the associations of health warning properties with post engagement (number of likes and comments).
UNASSIGNED: The Warning Label Multi-Layer Image Identification algorithm was 99.3% accurate in detecting the presence of health warnings. Only 8.2% (n=73) of LCC influencer posts included a health warning. Influencer posts that contained health warnings received fewer likes (incidence rate ratio 0.59, P<.001, 95% CI 0.48-0.71) and fewer comments (incidence rate ratio 0.46, P<.001, 95% CI 0.31-0.67).
UNASSIGNED: Health warnings are rarely used by influencers tagged by LCC brands\' Instagram accounts. Very few influencer posts met the US Food and Drug Administration\'s health warning requirement of size and placement for tobacco advertising. The presence of a health warning was associated with lower social media engagement. Our study provides support for the implementation of comparable health warning requirements to social media tobacco promotions. Using an innovative computer vision approach to detect health warning labels in influencer promotions on social media is a novel strategy for monitoring health warning compliance in social media tobacco promotions.
摘要：
■烟草广告中的健康警告提供了健康信息，同时也增加了烟草使用的感知风险。然而,现有的联邦法律要求在烟草制品广告上发出警告，但没有规定这些规则是否适用于社交媒体促销。
■本研究旨在研究Instagram上小雪茄和小雪茄（LCC）的影响者促销活动的现状以及在影响者促销中使用健康警告的情况。
■Instagram影响者被确定为在2018年至2021年之间被3个领先的LCC品牌Instagram页面中的任何一个标记的人。来自确定的影响者的帖子，其中提到三个品牌之一被认为是LCC影响者促销。开发了一种新颖的警告标签多层图像识别计算机视觉算法，以测量889个影响者帖子样本中健康警告的存在和属性。进行负二项回归以检查健康警告属性与参与后（喜欢和评论的数量）的关联。
■在检测健康警告的存在时，警告标签多层图像识别算法的准确率为99.3％。只有8.2%(n=73)的LCC影响者帖子包含健康警告。包含健康警告的影响者帖子收到的喜欢较少（发生率比0.59，P<.001，95％CI0.48-0.71）和评论较少（发生率比0.46，P<.001，95％CI0.31-0.67）。
■由LCC品牌\'Instagram帐户标记的影响者很少使用健康警告。很少有影响者的帖子符合美国食品和药物管理局关于烟草广告的大小和位置的健康警告要求。健康警告的存在与较低的社交媒体参与度有关。我们的研究为实施与社交媒体烟草促销类似的健康警告要求提供了支持。使用创新的计算机视觉方法来检测社交媒体上的影响者促销活动中的健康警告标签是一种用于监控社交媒体烟草促销活动中健康警告合规性的新颖策略。
■本研究旨在研究Instagram上小雪茄和小雪茄（LCC）的影响者促销活动的现状以及在影响者促销中使用健康警告的情况。
■Instagram影响者被确定为在2018年至2021年之间被3个领先的LCC品牌Instagram页面中的任何一个标记的人。来自确定的影响者的帖子，其中提到三个品牌之一被认为是LCC影响者促销。开发了一种新颖的警告标签多层图像识别计算机视觉算法，以测量889个影响者帖子样本中健康警告的存在和属性。进行负二项回归以检查健康警告属性与参与后（喜欢和评论的数量）的关联。
■在检测健康警告的存在时，警告标签多层图像识别算法的准确率为99.3％。只有8.2%(n=73)的LCC影响者帖子包含健康警告。包含健康警告的影响者帖子收到的喜欢较少（发生率比0.59，P<.001，95％CI0.48-0.71）和评论较少（发生率比0.46，P<.001，95％CI0.31-0.67）。
■由LCC品牌\'Instagram帐户标记的影响者很少使用健康警告。很少有影响者的帖子符合美国食品和药物管理局关于烟草广告的大小和位置的健康警告要求。健康警告的存在与较低的社交媒体参与度有关。我们的研究为实施与社交媒体烟草促销类似的健康警告要求提供了支持。使用创新的计算机视觉方法来检测社交媒体上的影响者促销活动中的健康警告标签是一种用于监控社交媒体烟草促销活动中健康警告合规性的新颖策略。
