Efficacy of an AI-enabled Mobile Application for Safe Eating in Community-dwelling Older Adults With Dysphagia: a Randomized Controlled Trial

Dysphagia (swallowing impairment) is a highly prevalent condition in older adults and is associated with increased risks of aspiration, malnutrition, dehydration, and reduced quality of life. While the International Dysphagia Diet Standardization Initiative (IDDSI) framework provides standardized terminology and practical methods for modifying food and liquid textures, ensuring accurate and consistent adherence to prescribed texture levels remains challenging in community settings. In particular, adherence is often limited by the lack of real-time feedback, variable caregiver skills, and difficulties in verifying food texture during routine meal preparation.

This study evaluates a novel, implementation-oriented digital health intervention designed to address these barriers. The intervention is an AI-enabled mobile application that supports real-time classification of food and liquid textures using smartphone-based image capture. The application incorporates a safety-first decision logic, providing conservative classification outputs alongside prompts encouraging users to verify textures using established IDDSI field tests (e.g., flow test, fork pressure test) when classification uncertainty is detected. The system is designed to function within everyday meal preparation workflows, thereby targeting behavioral adherence at the point of consumption rather than relying solely on retrospective education.

The trial adopts a pragmatic, community-based randomized controlled design to assess real-world effectiveness under typical home-use conditions. The intervention is delivered over a defined period of active use, during which participants and/or caregivers may engage with the application during meal preparation, food purchase, or consumption. The application records usage metrics (e.g., frequency of image captures, classification outputs, and uncertainty prompts), enabling evaluation of engagement and fidelity. The intervention is supported by structured onboarding and ongoing technical support to ensure usability among older adults and their caregivers.

The comparator reflects current standard practice in community dysphagia management and allows evaluation of the incremental benefit of digital decision support beyond education alone. The study is designed under a superiority framework to determine whether access to the AI-enabled tool results in meaningful improvements in behavioral adherence, which is considered the proximal mechanism linking dietary modification to downstream clinical outcomes. By focusing on adherence as the primary target, the study aligns with an implementation science perspective, recognizing that efficacy of dietary recommendations depends on their consistent and correct application in daily life.

In addition to assessing behavioral outcomes, the trial incorporates a multidimensional evaluation framework spanning symptom burden, functional oral intake, health-related quality of life, and safety events. These domains provide a comprehensive understanding of both intended benefits and potential unintended consequences, including risks related to misclassification, over-reliance on automated guidance, or increased user burden. A subsample will undergo instrumental swallowing assessments to explore potential changes in swallowing physiology associated with improved adherence, thereby linking behavioral and mechanistic outcomes.