Preferences of Patients With Tuberculosis for AI-Assisted Remote Health Management: Discrete Choice Experiment

Patients with tuberculosis expressed a clear preference for high-quality, human-integrated remote health management services, emphasizing the importance of physician involvement and personalized, interactive care. These findings suggest that fully AI-driven models may face resistance and that hybrid models combining AI efficiency with professional oversight are more acceptable. Policymakers and service designers should prioritize affordability, provide targeted financial support for populations considered vulnerable, and invest in digital literacy initiatives to enhance equitable access. This study provides critical evidence to support the development of AI-assisted tuberculosis management strategies that align with patient preferences and improve treatment adherence in low-resource settings.

Authors

Institutions

Publication Details

Journal
Journal of Medical Internet Research
Published
2025-09-26
DOI
https://doi.org/10.2196/77491
Primary Topic
Vaccine Coverage and Hesitancy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Preferences of Patients With Tuberculosis for AI-Assisted Remote Health Management: Discrete Choice Experiment

Fu Qian, Xu Luo, Xiaojun Wang
Journal of Medical Internet Research
Vaccine Coverage and Hesitancy
article

Preferences of Patients With Tuberculosis for AI-Assisted Remote Health Management: Discrete Choice Experiment

Fu Qian, Xu Luo, Xiaojun Wang
article en

Abstract

Patients with tuberculosis expressed a clear preference for high-quality, human-integrated remote health management services, emphasizing the importance of physician involvement and personalized, interactive care. These findings suggest that fully AI-driven models may face resistance and that hybrid models combining AI efficiency with professional oversight are more acceptable. Policymakers and service designers should prioritize affordability, provide targeted financial support for populations considered vulnerable, and invest in digital literacy initiatives to enhance equitable access. This study provides critical evidence to support the development of AI-assisted tuberculosis management strategies that align with patient preferences and improve treatment adherence in low-resource settings.

Journal of Medical Internet ResearchVol. 27
Jianghan University (CN), Wuhan Sixth Hospital (CN), Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 67%
Vaccine Coverage and Hesitancy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.