Association of Race and Receiving Mental Health Counseling in Patients Diagnosed with Depression




Powell, Dillon
Mayfield, Katherine
Kellerlee, Joel
Lee, Hannah


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Context: High prevalence of depression in the United States population is a rising issue, which warrants the need for understanding how to best target behavioral therapy as a treatment option for populations who are least likely to have received or to seek out such intervention.

Purpose: To determine if there is a significant relationship between race and frequency of mental health counseling as a treatment option in patients with depression.

Methods: This cross-sectional study included 949 patients diagnosed with depression, retrieved from the 2018 NAMCS (National Ambulatory Medical Care Survey) database. These patients were stratified by race as given in the NAMCS variable as "White”, "Black”, and "Others”. Of those 949 patients, 97 subjects sought out mental health counseling. We performed statistical analyses to determine if race was a predictor for seeking out mental health treatment.

Results: An ANOVA statistical analysis demonstrated a significant difference in those who sought out mental health counseling and race (p = .009) amongst those patients diagnosed with depression. Age (p <.001) was another significant factor affecting whether these patients sought mental health counseling. 12/42 "Other” subjects (9.1%, p <.001) with depression sought mental health treatment, followed by 9/69 Black subjects (13%, p = .024), followed by 76/838 White subjects (9.1%, p <.001).

Conclusions: The results contradicted our initial prediction, which anticipated that the white population would show higher rates of receiving mental health counseling than black and other race populations. We attribute these findings to the differences in severity and perception of depression symptoms among different races. Limitations to the study include sample size availability, inconsistencies in what each physician constitutes as mental health treatment, coding inaccuracies, and confounding variables including socioeconomic status and age.