Accepted for/Published in: JMIR Mental Health
Date Submitted: May 24, 2020
Date Accepted: Oct 28, 2020
Warning: This is an author submission that is not peer-reviewed or edited.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.
Leveraging the Power of Non-disruptive Technologies to Optimize Mental Health Treatment: A Scoping Review and a Case Example
ABSTRACT
Background:
Regular assessment of the effectiveness of behavioral interventions is a potent tool for improving its relevance to patients. However, poor provider and patient adherence characterize most measurement-based care tools. Therefore, a new approach for measuring intervention effects and communicating them to providers in seamless manner is warranted.
Objective:
This scoping review paper provides a summary of the importance, considerations, and tools pertinent to analyzing interventions through non-disruptive methodologies.
Methods:
We provide an overview of the available research evidence on novel ways to measure the effects of behavioral treatments, integrating both objective and subjective data. We focus on tools analyzing the therapeutic conversations through natural language processing. We further explore the usefulness of these tools to inform clinical decision making. We then apply the evidence in exploring a new tool to integrate the content of therapeutic conversations and patients’ self-reports.
Results:
We present a case study of how both subjective and objective measures of treatment effects were implemented in cognitive-behavioral treatment for depression and anxiety and then utilized in treatment planning, delivery, and termination. In this tool, called Eleos, the patient completes standardized measures of depression and anxiety. The content of the treatment sessions was evaluated using non-disruptive, independent measures of conversation content, fidelity to the treatment model, and the back-and-forth of patient-therapist dialogue.
Conclusions:
Innovative applications of advances in digital health are needed to disseminate empirically supported interventions and measure them in a non-cumbersome way. Eleos appears to be a feasible, sustainable, and effective way to assess behavioral healthcare. Clinical Trial: N/A
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Copyright
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