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Mental health stigma and emotional face processing: An ERP study
Jillian Grose-Fifer1,2, Denice Vidals1
1Department of Psychology , John Jay College of Criminal Justice, City University of New York, New York, NY, USA.
Social Neuroscience
|August 27, 2021
Summary
This study introduces an event-related potential (ERP) measure to detect bias against individuals with mental illness. Findings show that schizophrenia labels increase perceived danger and alter attention to facial expressions.
Area of Science:
- Cognitive Neuroscience
- Social Psychology
- Psychiatry
Background:
- Stigma surrounding mental illness influences social perception and judgment.
- Objective measures are needed to quantify automatic biases toward individuals with mental health conditions.
Purpose of the Study:
- To develop and validate an event-related potential (ERP) measure for assessing bias toward people with mental illnesses.
- To investigate how facial expressions interact with mental health labels in modulating early and late neural responses.
Main Methods:
- Electroencephalography (EEG) was used to record brain activity.
- Participants viewed faces with either a 'mentally healthy' or 'schizophrenia' label.
- Facial expressions (happy, angry) were manipulated, and participants rated perceived dangerousness.
Main Results:
- Faces labeled with schizophrenia were rated as more dangerous.
- Facial expression and mental health label interacted significantly for N170 and P3 amplitudes.
- Angry faces with schizophrenia labels elicited larger N170s, indicating heightened initial attention.
- Happy faces with schizophrenia labels elicited larger P3s, suggesting later attentional engagement.
Conclusions:
- ERP measures can capture automatic biases related to mental illness stigma.
- The findings highlight distinct neural processing differences for faces associated with schizophrenia, influenced by expression.
- This research provides a foundation for objective assessment of mental illness bias.
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