Factors Associated with Mental Health Counseling Utilization Among Adults with Anxiety Disorders in the United States

Background and Purpose: Anxiety disorders are the most prevalent psychiatric condition in the United States, affecting an estimated 19.1% of adults annually and contributing significantly to suicide rates among those diagnosed with this disorder. Various psychological treatments are available, such as counseling and therapy, stress management techniques, and antidepressant medications. Despite the effectiveness of these treatments, only 25% of individuals in need receive care for anxiety disorders. This study examined how social determinants of health, including age, marital status, education, employment, and the cost of counseling, influence the utilization of mental health counseling among adults with anxiety disorders.

Methods: This cross-sectional study utilized secondary data from the 2023 National Health Interview Survey (NHIS). The sample included 4,966 adults aged 18 to 85 (M=49.11, SD=18.10), representing the civilian non-institutionalized population residing in the 50 states and the District of Columbia at the time of the interview. Descriptive statistics characterized the study sample, while multivariate logistic regression analysis identified predictors of mental health counseling utilization in this population. All statistical analyses were performed using SPSS version 29, with a significance level set at p< 0.05.

Results: The study participants were aged 18 and older, with 85.6% identifying as Hispanic, 37.7% married, 63.3% holding a bachelor's degree or higher, and 52.5% employed. Bivariate analyses revealed significant associations between most independent variables and the outcome variable, except for transportation and gender. Our findings indicate a strong, statistically significant association between age and mental health counseling use, wherein older individuals (OR = 4.117, 95% CI [3.283, 5.164], p < .001) were significantly more likely to seek or receive counseling compared to younger adults. Similarly, delays in counseling due to cost (OR = 2.052, 95% CI [1.523, 2.765], p < .001), employment (OR = 0.688, 95% CI [0.593, 0.799], p < .001), health insurance coverage (OR = 0.328, 95% CI [0.235, 0.459], p < .001), education (OR = 0.712, 95% CI [0.540, 0.940], p < .001), and marital status (OR = 0.766, 95% CI [0.572, 0.800], p < .001) were associated with receiving mental health counseling. The overall logistic regression model was statistically significant (χ² (12) = 495.35, p < .001), indicating that the predictors reliably distinguished between whether an individual utilized mental health counseling services. The model explained approximately 14% of the variance in mental health counseling use (Nagelkerke R² = 0.14).

Conclusions and Implications: The findings underscore that age, education level, marital status, healthcare insurance, and cost-related barriers significantly influence the use of mental health counseling among individuals with anxiety disorders. These results highlight the need for targeted efforts by policymakers and healthcare practitioners, including social workers, to enhance access to and utilization of mental health services among underserved groups.