Compliance With the US Food and Drug Administration's Guidelines for Health Warning Labels and Engagement in Little Cigar and Cigarillo Content: Computer Vision Analysis of Instagram Posts.

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES
JMIR infodemiology Pub Date : 2023-03-14 eCollection Date: 2023-01-01 DOI:10.2196/41969
Jiaxi Wu, Juan Manuel Origgi, Lynsie R Ranker, Aruni Bhatnagar, Rose Marie Robertson, Ziming Xuan, Derry Wijaya, Traci Hong, Jessica L Fetterman
{"title":"Compliance With the US Food and Drug Administration's Guidelines for Health Warning Labels and Engagement in Little Cigar and Cigarillo Content: Computer Vision Analysis of Instagram Posts.","authors":"Jiaxi Wu, Juan Manuel Origgi, Lynsie R Ranker, Aruni Bhatnagar, Rose Marie Robertson, Ziming Xuan, Derry Wijaya, Traci Hong, Jessica L Fetterman","doi":"10.2196/41969","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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, <i>P</i><.001, 95% CI 0.48-0.71) and fewer comments (incidence rate ratio 0.46, <i>P</i><.001, 95% CI 0.31-0.67).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10132024/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR infodemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/41969","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Background: 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.

Objective: 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.

Methods: 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).

Results: 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).

Conclusions: 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.

Abstract Image

Abstract Image

Abstract Image

美国食品和药物管理局健康警示标签指南的合规性与小雪茄和雪茄烟内容的参与度:Instagram 帖子的计算机视觉分析。
背景:烟草广告中的健康警示在提供健康信息的同时,也增加了人们对烟草使用风险的认知。然而,要求在烟草产品广告中使用健康警示的现行联邦法律并未明确规定这些规则是否适用于社交媒体促销:本研究旨在考察Instagram上小雪茄和雪茄烟(LCC)影响者促销的现状,以及健康警示在影响者促销中的使用情况:在 2018 年至 2021 年期间,Instagram 上的影响者被 3 个主要 LCC 品牌 Instagram 页面中的任何一个标记。从已识别的影响者发布的帖子中提及这三个品牌之一的帖子被视为 LCC 影响者促销活动。我们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,用于测量 889 个影响者帖子样本中健康警告的存在和属性。对健康警告属性与帖子参与度(点赞数和评论数)之间的关联进行了负二项回归分析:警告标签多层图像识别算法检测健康警告的准确率为 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获得的点赞数较少(发生率比为 0.59,PPConclusions.PPConclusions.PPConclusions.PPConclusions.PPConclusions):被 LCC 品牌 Instagram 账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对烟草广告健康警告尺寸和位置的要求。健康警告的出现与社交媒体参与度较低有关。我们的研究为在社交媒体烟草促销中实施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有影响力的促销活动中的健康警示标签,是监测社交媒体烟草促销活动中健康警示合规性的一种新策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.80
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信