AI-Enabled Mobile App for Safe Eating in Older Adults With Dysphagia

ConditionsDeglutition Disorders Dysphagia

Trial statusNot yet recruiting

Trial phaseNot applicable

Trial typeInterventional

Biological sexAll

Age60+

SponsorKAM Chi Shan Anna

About this trial

Difficulty swallowing (called dysphagia) is common in older adults and can make eating and drinking unsafe. It may lead to serious problems such as choking, lung infections, poor nutrition, and reduced quality of life. One common way to reduce these risks is to modify food and drink textures (for example, making foods softer or liquids thicker). However, people often find it difficult to prepare food at the correct texture level in everyday life, especially at home, which may reduce the effectiveness of this approach.

This study aims to test whether a smartphone application powered by artificial intelligence (AI) can help older adults with swallowing difficulties eat more safely. The app allows users (or their caregivers) to take a photo of food or drinks, and the app then estimates the texture level and provides guidance to help ensure it is safe to swallow. It also gives simple prompts to double-check food texture when needed.

In this clinical trial, community-dwelling adults aged 60 years or above with swallowing difficulties will be randomly assigned to one of two groups. One group will receive usual care, which includes education about safe swallowing and written instructions on appropriate food textures. The other group will receive the same usual care plus access to the AI-enabled mobile app for 16 weeks. Participants will continue their daily eating routines at home.

The main question this study is trying to answer is: Does using the AI-enabled mobile app improve how often people eat foods that match their recommended safe texture level compared with usual care alone?

The study will also examine whether the app helps reduce swallowing-related problems (such as choking), improves quality of life, and supports better overall eating ability. In addition, the study will evaluate how easy the app is to use and whether it places any burden on users.

Hypothesis: The researchers hypothesize that participants who use the AI-enabled app, in addition to usual care, will more consistently follow recommended food texture guidelines and experience safer eating compared with those who receive usual care alone.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Adults aged 60 years or above

Community-dwelling (living in a home or community setting)

Suspected or clinically identified oropharyngeal dysphagia

Currently consuming food or liquids orally at texture-modified levels

Disqualifiers

Exclusive dependence on non-oral feeding (e.g., tube feeding)

Severe cognitive impairment or severe visual impairment that prevents meaningful participation

Medical conditions or circumstances that make participation unsafe

Life expectancy less than 6 months

Trial design

Design model

Parallel

Treatments tested in this trial

AI-Enabled Mobile Application plus Standard Care
Device
A smartphone-based application that uses artificial intelligence to classify food and liquid textures from images captured by the user. The application provides real-time guidance aligned with standardized dysphagia diet levels and delivers safety-focused prompts to verify texture using simple methods when needed. The tool is designed to support safe meal preparation and improve adherence to prescribed texture-modified diets in daily home settings. Participants receive onboarding and use the application during meals throughout the intervention period.
Standard Dysphagia Education
Behavioral
A structured education session providing guidance on safe swallowing practices and preparation of texture-modified foods and liquids. Participants receive printed educational materials describing appropriate food textures and simple methods for checking consistency. This reflects usual care in community dysphagia management and does not include digital or automated decision support.

Treatment groups

332 Participants

are divided into 2 treatment groups

Group A: AI-Enabled Mobile Application plus Standard CareExperimental treatment 1 intervention

Group B: Standard Care EducationActive comparator 1 intervention

Trial outcomes

Primary outcomes

Proportion of Meals Adhering to Prescribed Texture Level

The participant-level proportion of meals that correctly match the prescribed food and liquid texture level, based on standardized dysphagia diet guidelines, during a defined assessment period. In the intervention group, classification is supported by the mobile application and verification procedures; in the control group, adherence is determined using structured dietary logs with verification. Measure Type / Units: Proportion (0 to 1, or percentage 0-100%) Interpretation: Higher values indicate better adherence to prescribed diet texture

Time frame

Week 16

Secondary outcomes

Swallowing-Related Quality of Life

Swallowing-related quality of life measured using the Swallowing Quality of Life Questionnaire (SWAL-QOL). Domains include physical, emotional, and social aspects of eating and drinking. Scale Range: 0 to 100 Interpretation: Higher scores indicate better quality of life

Time frame

Baseline, Week 16, Week 24

Functional Oral Intake

Functional oral intake will be assessed using the Functional Oral Intake Scale (FOIS), a 7-level ordinal scale. Change in the level of oral intake, reflecting the degree to which participants can consume food and liquids safely and independently. Scale Range: 1 to 7 Interpretation: Higher levels indicate better oral intake and less reliance on modified diets or non-oral feeding

Time frame

Baseline, Week 16, Week 24

Incidence of Dysphagia-Related Adverse Events

Incidence of swallowing-related safety events, including choking, near-choking episodes, emergency department visits, and hospitalizations associated with swallowing difficulties.

Time frame

Baseline to Week 16; Week 16 to Week 24

mHealth App Usability Questionnaire (MAUQ) Score

Usability of the mobile application will be assessed using the mHealth App Usability Questionnaire (MAUQ). User-reported usability of the mobile application, including ease of use, usefulness, and satisfaction, will be assessed. Scale Range: Typically 1 to 7 per item (mean total score reported) Interpretation: Higher scores indicate better usability

Time frame

Week 16

Other outcomes

Dynamic Imaging Grade of Swallowing Toxicity (DIGEST) Score

Swallowing safety and efficiency will be assessed using the Dynamic Imaging Grade of Swallowing Toxicity (DIGEST) scale during instrumental evaluation. Scale Range: 0 to 4 Interpretation: Higher scores indicate more severe swallowing impairment

Time frame

Baseline, Week 16

Mobile Application Engagement (Usage Frequency)

Engagement with the application will be measured by system-generated logs, including participant interaction with the mobile application, frequency of use, number of food scans performed, and response to system prompts. Measure Type / Units: Count (number of scans per participant) Interpretation: Higher values indicate greater engagement

Time frame

During the intervention period (Weeks 1-16)

Response to Application Prompts

Frequency of responses to application-generated prompts for texture verification will be recorded. Measure Type / Units: Count and proportion Interpretation: Higher values indicate greater interaction with system guidance

Time frame

Weeks 1-16

International Dysphagia Diet Standardization Initiative (IDDSI) Adherence at Intermediate and Follow-Up Time Points

Changes in dietary adherence patterns at intermediate and follow-up time points will be measured to explore sustainability of behavior change. Proportion of meals adhering to prescribed IDDSI level at additional time points will be measured. All meals in the whole week 8 and week 24 will be included in the measurement. Measure Type / Units: Proportion (0-1 or 0-100%) Interpretation: Higher values indicate better adherence

Time frame

Week 8, Week 24

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

KAM Chi Shan Anna

Lead sponsor

Education University of Hong Kong

Sponsor institution

Source ClinicalTrials.gov

This trial is not recruiting at the moment. You can still explore other options: