Predicting the Behavioral Health Needs of Asian Americans in Public Mental Health Treatment: A Classification Tree...

Area of Science:

• Behavioral Health
• Mental Health Disparities
• Public Health

Background:

• Pandemic-related hardship and racial discrimination negatively impact Asian American mental health.
• Existing research often overlooks the specific behavioral health needs of Asian Americans within publicly funded systems.
• Understanding race-specific differences in mental health is critical for equitable service delivery.

Purpose of the Study:

• To compare the unique behavioral health needs of Asian Americans with White and Black Americans receiving publicly funded services.
• To identify specific demographic, pandemic-related, and clinical factors influencing these differences.
• To explore the intersection of needs and strengths in differentiating mental health functioning across racial groups.

Main Methods:

• Utilized 2019-2020 Adults Needs and Strengths Assessment (ANSA) data from Indiana.
• Included 544 Asian Americans, 78,704 White Americans, and 11,252 Black Americans eligible for public behavioral health services.
• Employed Chi-squared automatic interaction detection (CHAID) to analyze race-specific differences.

Main Results:

• Asian Americans consistently reported greater struggles with cultural-related factors compared to White and Black Americans, irrespective of age, gender, or pandemic status.
• Psychosis, recovery involvement, residential stability, decision-making, medical/physical health, job history, and interpersonal/spiritual strengths differentiated Asian Americans' mental health functioning.
• CHAID effectively identified complex, race-specific behavioral health needs and strengths.

Conclusions:

• Asian Americans exhibit distinct behavioral health needs, particularly concerning cultural factors, within publicly funded systems.
• Intersectional analysis of needs and strengths is vital for a nuanced understanding of mental health disparities.
• Classification tree algorithms show promise for identifying population-specific mental health challenges and strengths.