Predictors for Interest to Participate in Digital Mental Health Therapy: A Cross-Sectional Survey of Individuals with Anxiety and Depression

Abstract

Abstract Background: Due to a multitude of factors, the onset of the COVID-19 pandemic resulted in a significant increase in mental health issues within society, including depression and anxiety. Due to the increased trend of mental health disorders in society, digital mental health therapies are more useful than ever. With the emergence of programs utilizing Internet Cognitive Behavioral Therapy (iCBT), mental health resources are easily accessible and can be widely implemented to those in need. The aim of this study was to identify predictors for interest to participate in SilverCloud Digital Mental Health Therapy among individuals with mild to severe anxiety and/or depression based on preliminary findings from the COVIDsmart study. Methods: COVIDsmart study participants who indicated they would like to participate in future studies derived from COVIDsmart findings and who had moderate to severe anxiety and/or depression, were invited to complete a needs assessment survey to determine eligibility for the SilverCloud study using Research Electronic Data Capture (REDCap). The needs assessment was used to evaluate reasons for high levels of anxiety and/or depression during COVID-19. Additionally, participants were asked to indicate if they would be interested in receiving free digital mental health services. Descriptive statistics were used to analyze the demographics of participants. Furthermore, a logistic regression was used to find predictors for interest in participation in SilverCloud. SAS 9.4 was used and p values <0.05 were considered significant. Results: Out of the COVIDsmart participants who took part in the SilverCloud needs assessment, 120 individuals completed it. The largest demographic among these participants were females (70.83%) who identified as White (80.83%). The mean age was 48.74 years (SD = 14.66). Results revealed that having a mental health comorbidity significantly predicted the likelihood of interest in participating in the SilverCloud digital mental health program (p= 0.027). Conclusions: Individuals with pre-existing mental health conditions should receive additional screening and treatment to detect the possibility of newly emerging depression and/or anxiety. These results have significant implications for healthcare settings and mental health clinics regarding the utilization of screenings and treatment.