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Updated: Sep 24, 2026

The MODS method for diagnosis of tuberculosis and multidrug resistant tuberculosis
Published on: August 11, 2008
User needs and design opportunities for a conversational agent for tuberculosis treatment: A mixed-methods study
Joon Sang Baek1, Sehwa Choi1,2, Seojin Sung1,3
1Department of Integrated Design, Yonsei University, Seoul, South Korea.
Abstract:
Tuberculosis (TB) remains a major global health challenge requiring prolonged treatment that is often complicated by adverse drug reactions (ADRs), stigma, and poor treatment adherence. Although digital health interventions show promise in supporting TB care, patients' needs, expectations, and design requirements for conversational agents remain poorly understood. This study identified challenges experienced by healthcare professionals and patients with TB and explored opportunities for designing a user-centered conversational agent for TB care. A mixed-methods approach was adopted, comprising surveys of 107 healthcare professionals and 31 patients with TB, followed by in-depth interviews with 10 patients. The survey assessed treatment challenges, adherence barriers, and digital health needs. The interview data explored participants' treatment experiences and expectations for conversational agent-based support. Quantitative data were analyzed using descriptive statistics, and qualitative data were analyzed using inductive thematic analysis. Healthcare professionals reported ADR (25.1%), multidrug-resistant TB (17.1%), drug interaction management (15.6%), and low treatment adherence (15.6%) as key challenges. Patients' needs focused on ADR consultation (35%), TB information (21.7%), and diagnostics (20%). The majority wanted to use mHealth (62.1%), with specific interests in side effect guidance (20.4%), self-diagnosis (13%), and treatment information (12.5%). The interviews revealed patients' multifaceted needs related to TB treatment, including consistent communication with healthcare providers, effective ADR management, accurate and accessible TB information, social and psychological support during treatment, usable and accessible digital health solutions, and affordable services. These findings identified key design opportunities, including TB awareness, timely and personalized information, treatment adherence support, transparent treatment progress, psychosocial support, accessible digital services, and affordability. Healthcare professionals and patients reported unmet needs that conversational agents could potentially address. These findings provide user-centered guidance for developing conversational agents and contribute to evidence on digital health interventions for TB treatment support.
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