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Previously submitted to: JMIR Mental Health (no longer under consideration since Mar 28, 2023)

Date Submitted: Mar 28, 2023
Open Peer Review Period: Mar 27, 2023 - Mar 28, 2023
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Predictors for Interest to Participate in Digital Mental Health Therapy: A Cross-Sectional Survey of Individuals with Anxiety and Depression

  • Tharidu Gunawardena; 
  • Marilyn Bartholmae; 
  • Matvey Karpov; 
  • Rohan Dod; 
  • Kripa Ahuja; 
  • Aishwarya Rajendran; 
  • Mayuri Kathrotia; 
  • Sunita Dodani

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.

Objective:

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 and evaluate reasons for high levels of anxiety and/or depression during COVID-19. Participants were asked to indicate if they would be interested in receiving free digital mental health services.

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 (81.73%) who identified as White (84.17%). 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.


 Citation

Please cite as:

Gunawardena T, Bartholmae M, Karpov M, Dod R, Ahuja K, Rajendran A, Kathrotia M, Dodani S

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

JMIR Preprints. 28/03/2023:47635

DOI: 10.2196/preprints.47635

URL: https://preprints.jmir.org/preprint/47635

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