Exploring Customizable Interactive Tools for Therapeutic Homework Support in Mental Health Counseling
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866915755685052416 |
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| author | Wang, Yimeng Escamilla, Liabette Wang, Yinzhou Augustine, Bianca R. Zhang, Yixuan |
| author_facet | Wang, Yimeng Escamilla, Liabette Wang, Yinzhou Augustine, Bianca R. Zhang, Yixuan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_18179 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Exploring Customizable Interactive Tools for Therapeutic Homework Support in Mental Health Counseling Wang, Yimeng Escamilla, Liabette Wang, Yinzhou Augustine, Bianca R. Zhang, Yixuan Human-Computer Interaction 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. |
| title | Exploring Customizable Interactive Tools for Therapeutic Homework Support in Mental Health Counseling |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2601.18179 |