4.2 Article

Content and trend analysis of user-generated nicotine sickness tweets: A retrospective infoveillance study

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Medicine, General & Internal

Retrospective review of nicotine exposures in California from 2012 to 2018 and analysis of the impacts of e-cigarette regulations

Gabrielle Driller et al.

Summary: The study found that despite previous suggestions, the Child Nicotine Poisoning Prevention Act did not significantly reduce e-cigarette exposures. Conversely, there was a 30% increase in California e-cigarette exposures following the 2017 Compliance Policy. Current regulations are insufficient to reduce nicotine toxicities due to e-cigarette use.

BMJ OPEN (2021)

Article Public, Environmental & Occupational Health

Characterizing Self-Reported Tobacco, Vaping, and Marijuana-Related Tweets Geolocated for California College Campuses

Raphael E. Cuomo et al.

Summary: A study focused on smoking-related tweets from California college campuses found that a significant portion discussed tobacco use, marijuana use, and vaping. The majority of tweets expressed positive sentiment towards smoking behaviors, with noticeable variability between different college campuses.

FRONTIERS IN PUBLIC HEALTH (2021)

Article Health Care Sciences & Services

Topics of Nicotine-Related Discussions on Twitter: Infoveillance Study

Jon-Patrick Allem et al.

Summary: The study found that prevalent topics on Twitter regarding nicotine included smoking, nicotine health risks, and cessation methods, while social bots spread unsubstantiated health claims. Health education efforts should correct this misinformation and direct the public towards evidence-based cessation methods.

JOURNAL OF MEDICAL INTERNET RESEARCH (2021)

Article Public, Environmental & Occupational Health

Tweets About Acute Nicotine Toxicity Due to e-Liquid Exposure

Sarah Trigger et al.

Summary: This study analyzed ANTEE information on Twitter to investigate conditions associated with exposure to e-liquids. The research identified potential health effects and seeking assistance behaviors related to accidental exposures, while also noting the presence of hypothetical exposure scenarios and informational tweets in the non-exposure category. Tweets were found to be a useful data source for understanding e-liquid exposures.

TOBACCO REGULATORY SCIENCE (2021)

Article Health Care Sciences & Services

Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study

Myeong Gyu Kim et al.

JOURNAL OF MEDICAL INTERNET RESEARCH (2020)

Review Health Care Sciences & Services

Infodemiology and Infoveillance: Scoping Review

Amaryllis Mavragani

JOURNAL OF MEDICAL INTERNET RESEARCH (2020)

Article Public, Environmental & Occupational Health

Investigating the Attitudes of Adolescents and Young Adults Towards JUUL: Computational Study Using Twitter Data

Ryzen Benson et al.

JMIR PUBLIC HEALTH AND SURVEILLANCE (2020)

Article Public, Environmental & Occupational Health

Cloud chasers and substitutes: e-cigarettes, vaping subcultures and vaper identities

Rikke Tokle et al.

SOCIOLOGY OF HEALTH & ILLNESS (2019)

Article Substance Abuse

#Vapelife: An Exploratory Study of Electronic Cigarette Use and Promotion on Instagram

Linnea I. Laestadius et al.

SUBSTANCE USE & MISUSE (2016)

Review Medicine, General & Internal

Metabolism and biochemical effects of nicotine for primary care providers

CN Metz et al.

MEDICAL CLINICS OF NORTH AMERICA (2004)