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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Oct 4, 2021
Date Accepted: Feb 4, 2022

The final, peer-reviewed published version of this preprint can be found here:

Content Analysis of Nicotine Poisoning (Nic Sick) Videos on TikTok: Retrospective Observational Infodemiology Study

Purushothaman V, McMann T, Nali M, Li Z, Cuomo RE, Mackey T

Content Analysis of Nicotine Poisoning (Nic Sick) Videos on TikTok: Retrospective Observational Infodemiology Study

J Med Internet Res 2022;24(3):e34050

DOI: 10.2196/34050

PMID: 35353056

PMCID: 9008518

Content Analysis of Nicotine Poisoning “Nic-Sick” Videos on TikTok: A Retrospective Observational Infodemiology Study:

  • Vidya Purushothaman; 
  • Tiana McMann; 
  • Matthew Nali; 
  • Zhuoran Li; 
  • Raphael E. Cuomo; 
  • Tim Mackey

ABSTRACT

Background:

TikTok is a micro-video social media platform experiencing rapid growth with 60% of its monthly users between ages 16-24. Recent studies have found that increased exposure to e-cigarette content on social media may influence patterns of use including the risk of overconsumption leading to possible nicotine poisoning when users engage in trending online challenges. However, there is limited research assessing the characteristics of nicotine poisoning-related content posted on social media.

Objective:

To assess the characteristics of nicotine-related content on TikTok specific to a popular nicotine-poisoning-related hashtag.

Methods:

The study collected TikTok posts associated with the #nicsick hashtag using the Python programming package Selenium and used an inductive coding approach to conduct content analysis of video characteristics of interest. Videos were manually annotated to generate a codebook of nicotine sickness-related themes detected. Statistical analysis was used to compare characteristics of user engagement and length of videos that were detected with and without active nicotine sickness TikTok topics.

Results:

A total of 132 TikTok videos with the hashtag #nicsick were manually coded, with 52.3% (n=69) identified as discussing first-hand and second-hand reports of suspected nicotine poisoning symptoms and experiences. Among these videos were users who documented their experiences with adverse events and users actively vaping. More than one third of nicotine poisoning-related content (37.68%, n=26) portrayed active vaping by users, which included content with vaping behavior such as vaping tricks and overconsumption. Forty three percent (n=30) of recorded users self-reported experiencing nicotine sickness, poisoning, and/or adverse events such as vomiting following nicotine consumption. The mean follower count of users posting content related to nicotine sickness was significantly higher than those posting content unrelated to nicotine sickness (2,350.5, p=0.03).

Conclusions:

TikTok users openly discuss experiences, both firsthand and secondhand, with nicotine adverse events via the #nicsick hashtag including reports of overconsumption resulting in sickness. These study results point to the need to assess the utility of digital surveillance on emerging social media platforms for vaping adverse events, particularly on sites popular among youth and young adults. As vaping product use patterns continue to evolve, digital adverse event detection likely represents an important tool to supplement traditional methods of public health surveillance such as reports made to poison control centers.


 Citation

Please cite as:

Purushothaman V, McMann T, Nali M, Li Z, Cuomo RE, Mackey T

Content Analysis of Nicotine Poisoning (Nic Sick) Videos on TikTok: Retrospective Observational Infodemiology Study

J Med Internet Res 2022;24(3):e34050

DOI: 10.2196/34050

PMID: 35353056

PMCID: 9008518

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