Leveraging the Power of Nondisruptive Technologies to Optimize Mental Health Treatment: Case Study

Shiri Sadeh-Sharvit, Steven D Hollon, Shiri Sadeh-Sharvit, Steven D Hollon

Abstract

Regular assessment of the effectiveness of behavioral interventions is a potent tool for improving their 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 a seamless manner is warranted. This paper provides a brief overview of the available research evidence on novel ways to measure the effects of behavioral treatments, integrating both objective and subjective data. We highlight the importance of analyzing therapeutic conversations through natural language processing. We then suggest a conceptual framework for capitalizing on data captured through directly collected and nondisruptive methodologies to describe the client's characteristics and needs and inform clinical decision-making. We then apply this context in exploring a new tool to integrate the content of therapeutic conversations and patients' self-reports. 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 nondisruptive, independent measures of conversation content, fidelity to the treatment model, and the back-and-forth of client-therapist dialogue. Innovative applications of advances in digital health are needed to disseminate empirically supported interventions and measure them in a noncumbersome way. Eleos appears to be a feasible, sustainable, and effective way to assess behavioral health care.

Keywords: Eleos Health; anxiety; behavioral health; depression; digital health; mental health; natural language processing.

Conflict of interest statement

Conflicts of Interest: SSS is the Chief Clinical Officer of the commercial entity Eleos Health Inc that created the platform that is the subject of this case report. SDH is an unpaid advisor to Eleos Health Inc.

©Shiri Sadeh-Sharvit, Steven D Hollon. Originally published in JMIR Mental Health (http://mental.jmir.org), 26.11.2020.

Figures

Figure 1
Figure 1
Screenshots illustrating some of the Eleos Health platform process features. CBT: cognitive behavioral therapy; Speaking Ratio: proportion (%) of time spent speaking during the session; Speech Rate: speed of words per minute; Techniques Used: intervention strategies employed by the therapist during the session and automatically identified by the platform. Techniques used 3 times or more are indicated with a black checkmark, techniques used once or twice are denoted with a grey checkmark, and interventions not employed in the session do not have a checkmark.
Figure 2
Figure 2
Patient self-monitoring data graphed on the Eleos platform. GAD-7: Generalized Anxiety Disorder-7; PHQ-9: Patient Health Questionnaire-9.

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