Associations between public and self-stigma of help-seeking with help-seeking attitudes and intention: A meta-analytic structural equation modeling approach.

Ben C L Yu, Floria H N Chio, Kelly K Y Chan, Winnie W S Mak, Gengrui Zhang, David Vogel, Mark H C Lai
Author Information
  1. Ben C L Yu: Department of Psychology. ORCID
  2. Floria H N Chio: Department of Counselling and Psychology. ORCID
  3. Kelly K Y Chan: Department of Psychology.
  4. Winnie W S Mak: Department of Psychology. ORCID
  5. Gengrui Zhang: Department of Psychology.
  6. David Vogel: Department of Psychology.
  7. Mark H C Lai: Department of Psychology.

Abstract

The present study examined the association between help-seeking public stigma and help-seeking self-stigma (i.e., internalization of stigma) and the relative association of both types of stigma with help-seeking attitude and intention using a full-information meta-analytic structural equation modeling approach. We also investigated the moderating effect of gender, age, collectivism, and social group in the internalization process. Results from 115 independent samples containing data from 54,793 individuals showed that public stigma of help-seeking was strongly and positively associated with self-stigma of help-seeking. Moreover, after controlling for the effect of each other, self-stigma, but not public stigma, remained significantly associated with help-seeking attitude and help-seeking intention. Gender, age, collectivism, and social group did not significantly moderate the association between public and self-stigma. The findings highlight that people who perceive more stigma of help-seeking from others tend to have higher levels of self-stigma. Compared with help-seeking public stigma, help-seeking self-stigma might have a larger impact on one's help-seeking attitude and intention. Help-seeking promotion campaigns should be devised to tackle both types of stigma to foster positive help-seeking attitude and intention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Grants

  1. /Chinese University of Hong Kong

MeSH Term

Humans
Latent Class Analysis
Social Stigma
Attitude
Intention
Patient Acceptance of Health Care
Help-Seeking Behavior

Word Cloud

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