Assessing Depression Outcomes in Teletherapy for Underserved Residents in Central Texas: Telehealth's Move to Treatment-as-Usual

Telehealth is a flexible and cost-effective solution for providing psychotherapy services. The present study examines teletherapy outcomes data using two methodological frameworks: a categorical outcome approach, clinically significant change (CSC), and a continuous outcome approach, latent growth mixture modeling (LGMM). Archival data from 424 rural-residing clients were analyzed. Kaplan-Meier survival curves were fitted in two ways of comparison. The level of change was also explored and was modeled at five points as well as six points. A latent growth mixture model was fitted to assess depression severity over time. Clients achieved either CSC or overall improvement on the Patient Health Questionnaire-9 after three-seven sessions. Session-to-session results indicated that change took longer (10-11 sessions). Reliable deterioration was infrequently experienced and, thus, difficult to model. The LGMM fit best with three classes, of which two started clinically and varied in their improvement rates. The third class started nonclinically and showed little improvement over time. This study advances the literature regarding outcomes for rural clients by utilizing the frame of treatment-as-usual psychotherapy effectiveness and providing more generalizability to this specific population. Public Health Significance Statement This study contributes to the growing evidence for telehealth as an effective psychotherapy modality, evaluated in a treatment-as-usual clinic setting. These rural-residing clients, faced with barriers to quality mental health care, were served through telehealth and experienced positive reliable change within the first three-seven sessions on average and decreased depression severity over time. Examining outcomes at the individual clinic level provides generalizable information for that specific clinic/population and can help inform clinic policies utilizing the best available data.