Hate speech, professional denigration and incitement to violence in comments under Italian nursing-related TikTok content: a mixed-method observational study

Read full text
Authors: Flavio Gheri, Diego Ruggiero
Cited by: 0

Abstract

This preregistered mixed-method observational study aims to examine the prevalence and characteristics of negative discourse within publicly available comments posted under Italian nursing-related TikTok content. Social media platforms increasingly shape public perceptions of healthcare professionals, including nurses, and may contribute to professional stereotyping, normalization of hostility, and identity-based hate speech. The study will analyze 30 publicly accessible Italian nursing-related TikTok videos selected using a stratified engagement-based sampling approach. For each video, the first 200 comments ranked as “Most Relevant” at the time of extraction will be analyzed. Primary outcome: proportion of negative comments. Secondary outcomes: prevalence of professional denigration/stereotyping, explicit or implicit incitement to violence, and identity-based hate speech (racial/ethnic or homophobic). Quantitative content analysis and qualitative Framework Method analysis will be conducted. All data will be fully anonymized and reported only in aggregate form.

Fields of Study & Subjects

Hate Speech and Cyberbullying Detection Workplace Violence and Bullying Social Media in Health Education

Publication details

Journal / source
Open Science Framework
Publication date
1 January 2026
Language
EN