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

2026-01-26

AI Summary

This study addresses the challenge therapists face in efficiently processing unstructured, fragmented, and poorly integrated client-submitted homework logs, assessments, and reflections within limited session preparation time. To this end, we propose and implement TheraTrack—a customizable AI tool designed for therapists that employs a clinically goal-oriented interaction framework to integrate heterogeneous, multi-source data. Leveraging large language models, TheraTrack generates traceable summaries and supports natural language querying. In a pilot study with 14 therapists, TheraTrack significantly reduced cognitive load, facilitated data validation, and demonstrated an evolving pattern of flexible use with increased experience, thereby effectively optimizing the between-session homework tracking workflow.

Technology Category

• Humans and AI: Human-Aware Planning and Behavior Prediction
• Knowledge Representation and Reasoning: Automated Reasoning and Theorem Proving
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

• Search and Retrieval-Augmented AI: Agentic search
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

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.

Problem

• therapeutic homework
• mental health counseling
• unstructured client data
• therapist workload
• between-session support

Innovation

• customizable AI
• therapeutic homework
• large language models
• clinician-centered design
• multi-source data integration