Abstract BackgroundAcute lower respiratory infections (ALRIs) are a leading cause of child mortality globally, with timely recognition of increased work of breathing (WOB) critical for early intervention. In low-resource settings, WOB assessment is often subjective and inconsistent, contributing to delays in care. Digital health tools using artificial intelligence (AI) offer promising solutions to standardize detection of increased WOB through video and audio analysis. We are developing an AI-based tool to support assessment of increased WOB in children. This pilot study explores its feasibility and acceptability before its prototype is developed.MethodsThis qualitative study was conducted in March–April 2025 in Zakiganj, Sylhet, Bangladesh. Data were collected through four focus group discussions and four in-depth interviews with caregivers, community health care providers (CHCPs), community leaders, policymakers and health administrators. They followed a semi-structured guide tailored to participant roles. Participants were verbally introduced to the concept of an AI-based tool for assessing WOB in children to guide discussion; no demonstrations or recordings were used.ResultsThe findings demonstrate broad support for the feasibility of implementing AI-supported tools - digital stethoscopes and video-based respiratory assessments—for identifying increased WOB in children, particularly in rural and resource-constrained settings. Stakeholders emphasized that these tools offer practical solutions to address critical gaps in skilled personnel and diagnostic infrastructure, with strong endorsement for their use by CHCPs to facilitate task-shifting. Prior experience with similar technologies, such as digital stethoscopes for pneumonia, further reinforced their confidence in feasibility. Policymakers noted its alignment with national digital health strategies and child mortality reduction goals, indicating potential for scale-up through pilot initiatives and public-private partnerships. Caregivers also expressed positive perceptions, highlighting improved diagnostic accuracy, enhanced understanding through visual and audio feedback, and greater accessibility at local clinics. Nevertheless, concerns were raised about child cooperation, need for trained operators, time constraints, equitable access, and trust in technology.ConclusionAI-driven video and digital auscultation tools are considered feasible and acceptable for assessing increased WOB in children with ALRIs in rural Bangladesh. Their adoption will require training, technical support, community trust-building, and equitable access, with potential for scale-up to strengthen child health services.
Sharmin et al. (Wed,) studied this question.