@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://preview.aclanthology.org/ingest-acl-workshops/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."
}