Stigma surrounding mental health significantly hinders help-seeking behaviors. Its rapid dissemination through digital spaces creates an urgent need for intervention. This study focuses on developing and validating the Cyber-Stigmatization Bystander Intervention Scale (CSBIS), a tool designed to measure and promote proactive responses to online stigma.

In Study 1, an exploratory factor analysis (EFA) was conducted with 250 participants to identify the scale's dimensions. The analysis revealed five key factors: noticing cyber-stigmatization, interpreting the event as an emergency, taking personal responsibility to help, deciding on an intervention method, and implementing the intervention.

In Study 2, a confirmatory factor analysis (CFA) with a separate sample of 250 participants successfully validated the five-factor structure. Furthermore, the CSBIS demonstrated strong convergent validity, correlating significantly with measures of empathy and stigma toward mental disorders. Specifically, a greater likelihood of bystander intervention was associated with higher levels of empathy and lower levels of personal stigma.

The CSBIS provides a rigorously validated tool for assessing proactive bystander behaviors in digital contexts. These findings establish a foundation for future interventions aimed at reducing mental health stigma online. By fostering more supportive and compassionate digital communities, such interventions can empower individuals facing mental health challenges to seek the help they need.

Authors:
Ka Shing Kevin Chan, The Education University of Hong Kong, Hong Kong

About the Presenter(s)
Professor Kevin Ka Shing Chan is a Professor of the Department of Psychology and the Associate Dean (Research and Postgraduate Studies) of the Faculty of Education and Human Development at The Education University of Hong Kong in Hong Kong.

Connect on Linkedin
https://www.linkedin.com/in/kevin-ka-shing-chan-64a29356/

Connect on ResearchGate
https://www.researchgate.net/profile/Kevin-Ka-Shing-Chan-2

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