@inproceedings{garg-etal-2026-designing,
title = "Designing Structured Conversational Support for Tuberculosis Treatment Adherence and Patient Coping",
author = "Garg, Priyanshi and
Iribarren, Sarah and
Pentyala, Sikha and
Rodriguez, Yvette and
Carmiol-Rodriguez, Priscilla and
Vidrio, Alfie and
Kwanin, Charles and
Sprecher, Jennifer and
Roberti, Javier",
editor = "Zirikly, Aya and
Bar, Kfir and
MacAvaney, Sean and
Ireland, Molly and
Ophir, Yaakov and
Atzil-Slonim, Dana and
Varadarajan, Vasudha and
Bedrick, Steven and
Desmet, Bart",
booktitle = "Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology ({CLP}sych 2026)",
month = jul,
year = "2026",
address = "San Diego, California, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.clpsych-1.12/",
pages = "153--163",
ISBN = "979-8-89176-421-7",
abstract = "Tuberculosis (TB) remains a major global health challenge, and treatment adherence continues to be difficult despite the availability of effective medication. While Digital Adherence Technologies (DATs) have improved monitoring and care coordination, prior deployments highlight unmet needs for timely, personalized, and emotionally supportive communication outside clinical settings. We develop and iteratively refine a Spanish-language TB treatment-support chatbot through multiple rounds of internal expert evaluation. The system separates three core functions: (i) TB information support grounded in curated resources, (ii) coping-oriented support inspired by Dialectical Behavior Therapy (DBT), and (iii) safety-critical crisis handling via a deterministic, non-generative pathway. These components are implemented within a routed architecture with shared conversational state. Iterative evaluation identified recurring failure modes in unstructured conversational systems, including weak grounding, poor multi-turn continuity, and inconsistent safety behavior. Addressing these issues motivated explicit routing, state tracking, and task-specific prompting. Our findings suggest that in clinical support settings, reliable conversational behavior depends on structured interaction design and explicit control over routing, memory, and safety, rather than on model capability alone."
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<abstract>Tuberculosis (TB) remains a major global health challenge, and treatment adherence continues to be difficult despite the availability of effective medication. While Digital Adherence Technologies (DATs) have improved monitoring and care coordination, prior deployments highlight unmet needs for timely, personalized, and emotionally supportive communication outside clinical settings. We develop and iteratively refine a Spanish-language TB treatment-support chatbot through multiple rounds of internal expert evaluation. The system separates three core functions: (i) TB information support grounded in curated resources, (ii) coping-oriented support inspired by Dialectical Behavior Therapy (DBT), and (iii) safety-critical crisis handling via a deterministic, non-generative pathway. These components are implemented within a routed architecture with shared conversational state. Iterative evaluation identified recurring failure modes in unstructured conversational systems, including weak grounding, poor multi-turn continuity, and inconsistent safety behavior. Addressing these issues motivated explicit routing, state tracking, and task-specific prompting. Our findings suggest that in clinical support settings, reliable conversational behavior depends on structured interaction design and explicit control over routing, memory, and safety, rather than on model capability alone.</abstract>
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%0 Conference Proceedings
%T Designing Structured Conversational Support for Tuberculosis Treatment Adherence and Patient Coping
%A Garg, Priyanshi
%A Iribarren, Sarah
%A Pentyala, Sikha
%A Rodriguez, Yvette
%A Carmiol-Rodriguez, Priscilla
%A Vidrio, Alfie
%A Kwanin, Charles
%A Sprecher, Jennifer
%A Roberti, Javier
%Y Zirikly, Aya
%Y Bar, Kfir
%Y MacAvaney, Sean
%Y Ireland, Molly
%Y Ophir, Yaakov
%Y Atzil-Slonim, Dana
%Y Varadarajan, Vasudha
%Y Bedrick, Steven
%Y Desmet, Bart
%S Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-421-7
%F garg-etal-2026-designing
%X Tuberculosis (TB) remains a major global health challenge, and treatment adherence continues to be difficult despite the availability of effective medication. While Digital Adherence Technologies (DATs) have improved monitoring and care coordination, prior deployments highlight unmet needs for timely, personalized, and emotionally supportive communication outside clinical settings. We develop and iteratively refine a Spanish-language TB treatment-support chatbot through multiple rounds of internal expert evaluation. The system separates three core functions: (i) TB information support grounded in curated resources, (ii) coping-oriented support inspired by Dialectical Behavior Therapy (DBT), and (iii) safety-critical crisis handling via a deterministic, non-generative pathway. These components are implemented within a routed architecture with shared conversational state. Iterative evaluation identified recurring failure modes in unstructured conversational systems, including weak grounding, poor multi-turn continuity, and inconsistent safety behavior. Addressing these issues motivated explicit routing, state tracking, and task-specific prompting. Our findings suggest that in clinical support settings, reliable conversational behavior depends on structured interaction design and explicit control over routing, memory, and safety, rather than on model capability alone.
%U https://aclanthology.org/2026.clpsych-1.12/
%P 153-163
Markdown (Informal)
[Designing Structured Conversational Support for Tuberculosis Treatment Adherence and Patient Coping](https://aclanthology.org/2026.clpsych-1.12/) (Garg et al., CLPsych 2026)
ACL
- Priyanshi Garg, Sarah Iribarren, Sikha Pentyala, Yvette Rodriguez, Priscilla Carmiol-Rodriguez, Alfie Vidrio, Charles Kwanin, Jennifer Sprecher, and Javier Roberti. 2026. Designing Structured Conversational Support for Tuberculosis Treatment Adherence and Patient Coping. In Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2026), pages 153–163, San Diego, California, USA. Association for Computational Linguistics.