Exploring Customizable Interactive Tools for Therapeutic Homework Support in Mental Health Counseling

TL;DR

This paper presents TheraTrack, a customizable AI-powered tool that helps therapists interpret and manage therapeutic homework data more efficiently, reducing cognitive load and improving data verification.

Contribution

The study introduces TheraTrack, a novel tool integrating multi-source data and large language models to support therapist needs in mental health counseling.

Findings

TheraTrack reduced therapists' cognitive load.

Enabled verification from summaries to original data.

Adapted differently for private and in-session use.

Abstract

Therapeutic homework (i.e., tasks assigned by therapists for clients to complete between sessions) is essential for effective psychotherapy, yet therapists often interpret fragmented client logs, assessments, and reflections within limited preparation time. Our formative study with licensed therapists revealed three critical design requirements: support for interpreting unstructured client self-reports, customization aligned with clinical objectives, and seamless integration across multiple data sources. We then designed and developed TheraTrack, a customizable, therapist-facing tool that integrates multi-dimensional data and leverages large language models to generate traceable summaries and support natural-language queries, to streamline between-session homework tracking. Our pilot study with 14 therapists showed that TheraTrack reduced their cognitive load, enabled verification through direct navigation from AI summaries to original data entries, and was adapted differently for private analysis compared to in-session use, with dependence varying based on therapist experience and usage duration. We also discuss design implications for clinician-centered AI for mental health.