NCT07654088

Brief Summary

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.

Trial Health

63
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
332

participants targeted

Target at P75+ for not_applicable

Timeline
36mo left

Started Jan 2028

Typical duration for not_applicable

Geographic Reach
1 country

1 active site

Status
not yet recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

June 5, 2026

Completed
12 days until next milestone

First Posted

Study publicly available on registry

June 17, 2026

Completed
1.5 years until next milestone

Study Start

First participant enrolled

January 1, 2028

Expected
2.9 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 1, 2030

Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

December 1, 2030

Last Updated

June 17, 2026

Status Verified

June 1, 2026

Enrollment Period

2.9 years

First QC Date

June 5, 2026

Last Update Submit

June 12, 2026

Conditions

Keywords

DysphagiaDeglutition disordersSwallowing disordersTexture modified dietFood texture assessmentArtificial intelligence in health careClinical decision support systemsDigital health interventionOlder adultsAging populationMobile health applications

Outcome Measures

Primary Outcomes (1)

  • 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

    Week 16

Secondary Outcomes (5)

  • Swallowing-Related Quality of Life

    Baseline, Week 16, Week 24

  • Functional Oral Intake

    Baseline, Week 16, Week 24

  • Incidence of Dysphagia-Related Adverse Events

    Baseline to Week 16; Week 16 to Week 24

  • mHealth App Usability Questionnaire (MAUQ) Score

    Week 16

  • NASA Task Load Index (NASA-TLX) Global Score

    Week 16

Other Outcomes (4)

  • Dynamic Imaging Grade of Swallowing Toxicity (DIGEST) Score

    Baseline, Week 16

  • Mobile Application Engagement (Usage Frequency)

    During the intervention period (Weeks 1-16)

  • Response to Application Prompts

    Weeks 1-16

  • +1 more other outcomes

Study Arms (2)

AI-Enabled Mobile Application plus Standard Care

EXPERIMENTAL

Participants receive access to an artificial intelligence-enabled mobile application designed to support real-time classification of food and liquid textures according to standardized dysphagia diet levels. The application provides safety-oriented guidance and prompts for verification of food texture during daily meal preparation and consumption. Participants also receive standard dysphagia education materials and training. The intervention is used in a home setting over the study period to support adherence to prescribed dietary recommendations. Intervention used: AI-Enabled Mobile Application plus Standard Care

Device: AI-Enabled Mobile Application plus Standard Care

Standard Care Education

ACTIVE COMPARATOR

Participants receive standard dysphagia education, including guidance on safe swallowing practices and instructions for preparing texture-modified foods and liquids. Educational materials and training are provided, reflecting usual community care. No digital or application-based decision support is provided.

Behavioral: Standard Dysphagia Education

Interventions

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.

AI-Enabled Mobile Application plus Standard Care

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.

Standard Care Education

Eligibility Criteria

Age60 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • 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
  • Able to provide informed consent, or with caregiver support if mild cognitive impairment is present
  • Access to a smartphone or tablet, either independently or with caregiver assistance
  • Willing and able to participate in study procedures and follow-up assessments

You may not qualify if:

  • 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
  • Current participation in another dysphagia-related interventional study
  • Use of other digital tools specifically designed for food texture classification during the study period

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

The Education University of Hong Kong

Hong Kong, Hong Kong

Location

MeSH Terms

Conditions

Deglutition Disorders

Condition Hierarchy (Ancestors)

Esophageal DiseasesGastrointestinal DiseasesDigestive System DiseasesPharyngeal DiseasesOtorhinolaryngologic Diseases

Study Officials

  • Anna Kam, AuD

    The Education University of Hong Kong

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Anna Kam, AuD

CONTACT

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
OUTCOMES ASSESSOR
Purpose
TREATMENT
Intervention Model
PARALLEL
Model Details: This is a two-arm, parallel-group, randomized controlled trial. Participants are individually assigned in a 1:1 ratio to either (1) an intervention group receiving access to an artificial intelligence-enabled mobile application in addition to standard dysphagia education, or (2) a control group receiving standard dysphagia education alone. Participants remain in their assigned group for the entire study duration, including the intervention and follow-up periods. Randomization is stratified by baseline functional status, cognitive status, and living arrangement to ensure balance between groups. Outcome assessors are blinded to group allocation to minimize bias, while participants and intervention staff are not blinded due to the nature of the intervention.
Sponsor Type
OTHER
Responsible Party
SPONSOR INVESTIGATOR
PI Title
Associate Professor

Study Record Dates

First Submitted

June 5, 2026

First Posted

June 17, 2026

Study Start (Estimated)

January 1, 2028

Primary Completion (Estimated)

December 1, 2030

Study Completion (Estimated)

December 1, 2030

Last Updated

June 17, 2026

Record last verified: 2026-06

Data Sharing

IPD Sharing
Will not share

Individual participant data will not be shared due to data privacy considerations and institutional data protection policies. De-identified, aggregate results will be reported in publications and presentations, and summaries of findings may be made available upon reasonable request.

Locations