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Accepted for/Published in: JMIR Human Factors

Date Submitted: Oct 13, 2025
Open Peer Review Period: Nov 13, 2025 - Jan 8, 2026
Date Accepted: May 29, 2026
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Risk Factors for Noninitiation and Dropout in Blended Therapy in Inpatient Psychiatric Patients: Retrospective Cohort Study

Gupta N, Gardin F, Berger T, Kawohl W

Risk Factors for Noninitiation and Dropout in Blended Therapy in Inpatient Psychiatric Patients: Retrospective Cohort Study

JMIR Hum Factors 2026;13:e85816

DOI: 10.2196/85816

PMID: 42372259

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Risk Factors for Non-Initiation and Dropout in Blended Therapy in Inpatient Psychiatric Patients - A Retrospective Cohort Study

  • Nikita Gupta; 
  • Fabian Gardin; 
  • Thomas Berger; 
  • Wolfram Kawohl

ABSTRACT

This multicentric retrospective observational study investigates factors associated with the risk of non-initiation and dropout in the use of blended therapy (BT) among inpatients. In this study, data from 278 inpatients were analysed to examine the influence of sociodemographic variables, comorbidities, and symptom severity on the uptake and continued use of BT. Multivariate regression analyses were conducted to identify significant predictors of non-initiation and dropout. The results indicate that different factors are associated with each. Specifically, increasing age was linked to a lower risk of non-initiation (OR (per year age difference) = 0.98, 95% CI [0.96, 1.00], p = 0.013), while the presence of a comorbid anxiety disorder was associated with a reduced risk of dropout (OR = 0.23, 95% CI [0.08, 0.66], p = 0.007). The age-related finding aligns with existing literature suggesting that older adults show higher willingness to continue with internet-based treatment. Explanations for this could be having more realistic expectations regarding treatment, greater persistence, or the likelihood that only intrinsically motivated older adults choose to even engage in digital therapies. Regarding comorbid anxiety disorders, previous literature provides no consistent conclusions about its role in dropout. However, the lower dropout rates observed in this subgroup may reflect specific personality traits or indicate that these patients benefit more from the highly structured nature of BT. It is possible that the modules offered on the platform are particularly well-suited to addressing core mechanisms of anxiety disorders, thereby enhancing perceived relevance and user engagement. In conclusion, the findings highlight the importance of identifying patient characteristics that predict successful engagement with BT. Tailoring the use of BT to those more likely to adhere may support more effective and resource-conscious implementation in clinical inpatient settings.


 Citation

Please cite as:

Gupta N, Gardin F, Berger T, Kawohl W

Risk Factors for Noninitiation and Dropout in Blended Therapy in Inpatient Psychiatric Patients: Retrospective Cohort Study

JMIR Hum Factors 2026;13:e85816

DOI: 10.2196/85816

PMID: 42372259

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