Suppr超能文献

研究纽约州口味禁令对推特上电子烟相关讨论的影响:观察性研究。

Investigating the Impact of the New York State Flavor Ban on e-Cigarette-Related Discussions on Twitter: Observational Study.

机构信息

University of Rochester Medical Center, Rochester, NY, United States.

出版信息

JMIR Public Health Surveill. 2022 Jul 8;8(7):e34114. doi: 10.2196/34114.

Abstract

BACKGROUND

On May 18, 2020, the New York State Department of Health implemented a statewide flavor ban to prohibit the sales of all flavored vapor products, except for tobacco or any other authorized flavor.

OBJECTIVE

This study aims to investigate the discussion changes in e-cigarette-related tweets over time with the implementation of the New York State flavor ban.

METHODS

Through the Twitter streaming application programming interface, 59,883 e-cigarette-related tweets were collected within the New York State from February 6, 2020, to May 17, 2020 (period 1, before the implementation of the flavor ban), May 18, 2020-June 30, 2020 (period 2, between the implementation of the flavor ban and the online sales ban), July 1, 2020-September 15, 2020 (period 3, the short term after the online sales ban), and September 16, 2020-November 30, 2020 (period 4, the long term after the online sales ban). Sentiment analysis and topic modeling were conducted to investigate the changes in public attitudes and discussions in e-cigarette-related tweets. The popularity of different e-cigarette flavor categories was compared before and after the implementation of the New York State flavor ban.

RESULTS

Our results showed that the proportion of e-cigarette-related tweets with negative sentiment significantly decreased (4305/13,246, 32.5% vs 3855/14,455, 26.67%, P<.001), and tweets with positive sentiment significantly increased (5246/13,246, 39.6% vs 7038/14,455, 48.69%, P<.001) in period 4 compared to period 3. "Teens and nicotine products" was the most frequently discussed e-cigarette-related topic in the negative tweets. In contrast, "nicotine products and quitting" was more prevalent in positive tweets. The proportion of tweets mentioning mint and menthol flavors significantly increased right after the flavor ban and decreased to lower levels over time. The proportions of fruit and sweet flavors were most frequently mentioned in period 1, decreased in period 2, and dominated again in period 4.

CONCLUSIONS

The proportion of e-cigarette-related tweets with different attitudes and frequently discussed flavor categories changed over time after the implementation of the New York State ban of flavored vaping products. This change indicated a potential impact of the flavor ban on public discussions of flavored e-cigarettes.

摘要

背景

2020 年 5 月 18 日,纽约州卫生署实施了全州范围内的口味禁令,禁止销售所有口味的蒸气产品,烟草或其他经授权的口味除外。

目的

本研究旨在探讨随着纽约州口味禁令的实施,与电子烟相关的推文在时间上的讨论变化。

方法

通过 Twitter 流媒体应用程序编程接口,在 2020 年 2 月 6 日至 5 月 17 日(第 1 期,在实施口味禁令之前)、2020 年 5 月 18 日至 6 月 30 日(第 2 期,在实施口味禁令和在线销售禁令之间)、2020 年 7 月 1 日至 9 月 15 日(第 3 期,在线销售禁令后的短期)和 2020 年 9 月 16 日至 11 月 30 日(第 4 期,在线销售禁令后的长期),在纽约州内收集了 59883 条电子烟相关推文。进行情绪分析和主题建模,以调查电子烟相关推文的公众态度和讨论的变化。比较了在实施纽约州口味禁令前后不同电子烟口味类别的受欢迎程度。

结果

我们的结果表明,具有负面情绪的电子烟相关推文的比例显著下降(4305/13246,32.5%比 3855/14455,26.67%,P<.001),而具有积极情绪的推文比例显著增加(5246/13246,39.6%比 7038/14455,48.69%,P<.001)在第 4 期比第 3 期。“青少年和尼古丁产品”是负面推文最常讨论的电子烟相关话题。相比之下,“尼古丁产品和戒烟”在积极的推文中更为常见。薄荷醇和薄荷醇口味的推文比例在口味禁令实施后立即显著增加,然后随着时间的推移逐渐下降。水果和甜味口味的比例在第 1 期最常被提及,在第 2 期减少,然后在第 4 期再次占主导地位。

结论

在实施纽约州禁止调味电子烟产品的禁令后,与电子烟相关的推文在不同态度和经常讨论的口味类别上的比例随时间发生了变化。这一变化表明口味禁令可能对公众对调味电子烟的讨论产生了影响。

相似文献

引用本文的文献

6
Vaping: Public Health, Social Media, and Toxicity.电子烟:公共卫生、社交媒体与毒性
Online J Public Health Inform. 2024 Apr 11;16:e53245. doi: 10.2196/53245.
8
Public perceptions of the FDA's marketing authorization of Vuse on Twitter/X.公众对 FDA 批准 Vuse 在 Twitter/X 上营销的看法。
Front Public Health. 2023 Nov 3;11:1280658. doi: 10.3389/fpubh.2023.1280658. eCollection 2023.

本文引用的文献

7
Menthol e-cigarette sales rise following 2020 FDA guidance.薄荷醇电子烟销量在 2020 年 FDA 指导意见出台后上升。
Tob Control. 2021 Nov;30(6):700-703. doi: 10.1136/tobaccocontrol-2020-056053. Epub 2020 Sep 23.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验