Invisible Man: Mental Health Providers and How Implicit Bias Manifests When Treating African American Men
Abstract
African American men continue to face disproportionate barriers to engagement, accurate diagnosis, and equitable nonbiased treatment in mental health settings. The purpose of the qualitative narrative inquiry was to explore how implicit bias and sociocultural assumptions manifest among mental health providers who diagnose and treat African American men. Bronfenbrenner’s ecological systems theory, which considers the influences of all the systems that shape an individual’s lived experiences, was the study’s theoretical framework. Semi-structured interviews were conducted with five licensed mental health providers who worked in large hospital systems, private practice, or community-based clinics. The interview data were analyzed using Braun and Clarke’s six-phase thematic analysis to identify patterns, meaning, and contextual influences in participant narratives. Three major themes emerged: implicit bias and ethical dilemmas, medical mistrust, and stigma and masculinity and seven sub-themes, two include African American men lack trust due to fear and lack of knowledge leads to bias. The ecological systems framework helped reveal how these influences operate across multiple levels—from individual provider awareness to institutional policies and macrosystem. The findings suggest that implicit bias remains a contributing factor to mental health disparities among African American men. The study highlights the need for culturally relevant modalities, bias training, reflective supervision, and cultural competency training. Implications for positive social change include elevating provider voices and demonstrating how implicit bias can be recognized and mitigated through grounded ecological approaches to care.
Fields of Study & Subjects
Racial and Ethnic Identity Research
Cultural Competency in Health Care
Counseling Practices and Supervision
Publication details
- Journal / source
- ScholarWorks (Walden University)
- Publication date
- 11 February 2026
- Language
- EN
- Document type
- Thesis