Predictors of Telehealth Services for Mental Health: Using Andersen's Behavioral Model to Examine Young Adult Service Use

Background: Young adulthood is a critical time for understanding mental health needs, as reports suggest that young adults experience anxiety and depressive symptoms at alarmingly increased rates. Nationally representative data finds that approximately 36% and 29% of young adults experience anxiety and depression, respectively. With the impacts of the COVID-19 pandemic, telehealth services came to the forefront of care for all ages, with rates of utilization increasing four-fold between 2018 to 2022. Despite increased use of telehealth services to address mental health needs, there continues to be a gap between service need and service use among youth adults. Informed by Andersen’s Behavioral Model of Health Care Utilization as a framework, the current study aimed to examine predisposing, enabling, and need-related factors for tele-mental health service utilization among young adults.

Methods: The present study was conducted with data from the 2021 National Survey of Drug Use and Health (NSDUH). To encompass youth adults, participants ranged from ages 18 to 25 (N = 13979. The dependent variable was the use of telehealth services for mental health needs (0=no, 1=yes). Predictors included sociodemographic characteristics, enabling factors (income, geographic location), and need (anxiety and depressive symptoms). A hierarchical logistic regression was run to determine the relative contributions of predisposing, enabling, and need variables on telehealth use over the past year.

Results: Model 1 (predisposing) was statistically significant (p < .001) and explained 5.9% of the variance. In this model, being female and being enrolled in school increased the probability of using telehealth services at p < .001. The same effect was seen for Blacks and Hispanics when compared to non-white Hispanics (p < .001). Model 2 (enabling) was also statistically significant (p < .001) and helped predict 6.6% of the variance. All variables in model 1 remained significant at p < .001 in model 2. Finally, model 3 (need) was significant and helped explain 15.4% of the variance. All variables from model 1 remained significant in model 3. Other variables that also significantly predicted telehealth use in model 3 included having health insurance (p < .001), mental health (p < .001), and physical health (p < .001). Specifically, those with higher depression/anxiety symptoms and worse health were more likely to have used telehealth services over the past year

Implications and Conclusions: This study is one of few empirical studies providing important evidence regarding factors that influence the use of tele-mental health services among young adults. Specifically, Andersen’s framework continues to be an important foundation for our understanding of services utilization. Mental health providers for young adults should consider the sustained use of telehealth services to continue meeting the needs of young adults. As many young adults are in post-secondary education settings, colleges and universities should also continue to seek opportunities for expanding their capacity to meet the mental health of their students, including telehealth services.