Predicting non-initiation of care and dropout in a blended care CBT intervention: Impact of early digital engagement, sociodemographic, and clinical factors

Monica S. Wu, Shih Yin Chen, Robert E. Wickham, Yan Leykin, Alethea Varra, Connie Chen, Anita Lungu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Objective: This study examines predictors of non-initiation of care and dropout in a blended care CBT intervention, with a focus on early digital engagement and sociodemographic and clinical factors. Methods: This retrospective cohort analysis included 3566 US-based individuals who presented with clinical levels of anxiety and depression and enrolled in a blended-care CBT (BC-CBT) program. The treatment program consisted of face-to-face therapy sessions via videoconference and provider-assigned digital activities that were personalized to the client's presentation. Multinomial logistic regression and Cox proportional hazard survival analysis were used to identify predictors of an increased likelihood of non-initiation of therapy and dropout. Results: Individuals were more likely to cancel and/or no-show to their first therapy session if they were female, did not disclose their ethnicity, reported poor financial status, did not have a college degree, endorsed more presenting issues during the onboarding triage assessment, reported taking antidepressants, and had a longer wait time to their first appointment. Of those who started care, clients were significantly more likely to drop out if they did not complete the digital activities assigned by their provider early in treatment, were female, reported more severe depressive symptoms at baseline, reported taking antidepressants, and did not disclose their ethnicity. Conclusions: Various sociodemographic and clinical predictors emerged for both non-initiation of care and for dropout, suggesting that clients with these characteristics may benefit from additional attention and support (especially those with poor early digital engagement). Future research areas include targeted mitigation efforts to improve initiation rates and curb dropout.

Original languageEnglish (US)
JournalDigital Health
Volume8
DOIs
StatePublished - 2022

Keywords

  • Blended care
  • CBT
  • digital
  • dropout
  • engagement

ASJC Scopus subject areas

  • Health Policy
  • Health Informatics
  • Computer Science Applications
  • Health Information Management

Fingerprint

Dive into the research topics of 'Predicting non-initiation of care and dropout in a blended care CBT intervention: Impact of early digital engagement, sociodemographic, and clinical factors'. Together they form a unique fingerprint.

Cite this