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cMIND AI Web Tool Usability Study (Hong Kong)

2026년 7월 24일 업데이트: Hong Kong Metropolitan University

Development and Validation of a Web-Based AI System for Assessing the Cantonese-Style Mediterranean Diet (cMIND) Index

This study is testing a new web-based tool that uses artificial intelligence (AI) to help older adults in Hong Kong check how healthy their Cantonese-style meals are for brain health. The tool is based on the cMIND diet, a Chinese-adapted version of a known healthy eating pattern that may support memory and thinking skills.

Participants will use the web app to take photos of their usual meals for at least 10 days over two weeks. The AI will automatically identify ingredients and give a score showing how well the meal follows the cMIND diet. The study will also ask participants to complete a short questionnaire and a brief interview to find out how easy and useful the tool is for older adults.

The purpose of this small study is to see whether the AI tool is user-friendly and acceptable for older people. Results will help improve the tool for future use to support healthy ageing and brain health.

연구 개요

상세 설명

Mild cognitive impairment (MCI) is common among older adults and can progress to dementia. Diet plays an important role in brain health. The cMIND diet is a culturally adapted Chinese version of the Mediterranean-DASH diet, designed to support cognitive function. However, many older adults find it difficult to track their adherence to this diet using traditional methods.

This study is developing and testing a simple web-based AI tool to help older adults in Hong Kong monitor their Cantonese-style meals. Users take photos of their meals (such as dim sum, stir-fries, or congee) using the web app. The AI automatically identifies ingredients in mixed dishes and calculates a cMIND adherence score (0-12), giving immediate personalised feedback on how well the meal supports brain health.

The main part of the study is a small usability and acceptability test. We will recruit 20 community-dwelling older adults aged 60 years and above who regularly eat Cantonese-style meals. Participants should not have a self-reported diagnosis of dementia or Alzheimer's disease, or other psychiatric/medical conditions that would interfere with participation or valid outcome assessment.

Eligible participants will receive a 20-minute training session on how to use the web tool. They will then use the app to photograph their usual meals for at least 10 days over a two-week period, without changing their normal eating habits.

At the end of the two weeks, participants will complete a short online questionnaire about the ease of use and usefulness of the tool. They will also take part in one short individual interview (about 20 minutes, audio-recorded) to share their experiences and suggestions.

This low-risk study aims to understand whether older adults find the AI tool easy and acceptable to use in daily life. The results will help improve the prototype for future larger studies. All data will be kept strictly confidential, and ethics approval has been obtained from the Hong Kong Metropolitan University Research Ethics Committee (Reference: HE-FRSE/2026/08).

연구 유형

관찰

등록 (추정된)

20

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 연락처

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 성인
  • 고령자

건강한 자원 봉사자를 받아들입니다

예

샘플링 방법

비확률 샘플

연구 인구

Community-dwelling older adults aged 60 years and above in Hong Kong who regularly consume Cantonese-style meals.

설명

Inclusion Criteria:

  • Aged 60 years or above
  • Community-dwelling in Hong Kong
  • Able to provide informed consent
  • Basic ability to use a smartphone or tablet (with assistance if needed)
  • Consuming Cantonese-style meals as the primary dietary pattern for ≥ 5 days per week for the past 3 months or longer)

Exclusion Criteria:

  • Severe visual or motor impairment that prevents taking meal photos even with assistance
  • Self-reported diagnosis of dementia or Alzheimer's disease, or other psychiatric/medical conditions that would interfere with participation or valid outcome assessment
  • Current participation in other interventional nutrition or technology studies

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

코호트 및 개입

그룹/코호트
개입 / 치료
cMIND Usability Group
Community-dwelling older adults aged 60 years and above in Hong Kong who regularly consume Cantonese-style meals. This single-group feasibility and usability study evaluates the ease of use and acceptability of a web-based AI tool that analyses meal photos and calculates a cMIND (Cantonese-style Mediterranean Diet) adherence score to support cognitive health monitoring.
A web-based AI software prototype designed specifically for older adults in Hong Kong. Users upload photographs of their usual Cantonese-style mixed meals (e.g., dim sum assortments, stir-fries with overlapping ingredients, or congee with toppings). The AI system automatically recognises multiple ingredients and sauces, estimates nutritional content using local food composition data, and calculates a cMIND adherence score (range 0-12). Immediate personalised feedback on dietary quality for brain health is provided. The tool is intended for dietary self-monitoring and does not involve any drug, physical device, or medical treatment.

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
측정값 설명
기간
Usability and Acceptability of the Web-Based AI Tool
기간: Assessed at the end of the 2-week testing period
Participants' perceived ease of use and acceptability of the AI web tool for photographing Cantonese meals and receiving cMIND dietary feedback.
Assessed at the end of the 2-week testing period

2차 결과 측정

결과 측정
측정값 설명
기간
Feasibility of Meal Photo-Taking
기간: Over the 2-week testing period
Proportion of participants able to complete at least 10 days of meal photos over the two-week period.
Over the 2-week testing period
Qualitative User Feedback
기간: At the end of the 2-week testing period
Participants' experiences, challenges, and suggestions regarding the web tool, collected through semi-structured interviews.
At the end of the 2-week testing period

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

수사관

  • 수석 연구원: Chow Ka-Man, Ph.D., Hong Kong Metropolitan University

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (추정된)

2027년 9월 1일

기본 완료 (추정된)

2028년 1월 1일

연구 완료 (추정된)

2028년 2월 1일

연구 등록 날짜

최초 제출

2026년 7월 24일

QC 기준을 충족하는 최초 제출

2026년 7월 24일

처음 게시됨 (실제)

2026년 7월 29일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 7월 29일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 7월 24일

마지막으로 확인됨

2026년 7월 1일

추가 정보

이 연구와 관련된 용어

개별 참가자 데이터(IPD) 계획

개별 참가자 데이터(IPD)를 공유할 계획입니까?

예

IPD 계획 설명

De-identified individual participant data (including meal photos, cMIND scores, and usability questionnaire responses) will be made available upon reasonable request after publication of the main results. A data dictionary will be provided.

IPD 공유 기간

Start Date: 6 months after publication of the main study results End Date: 5 years after study completion (January 2033)

IPD 공유 액세스 기준

IPD and supporting documents (study protocol, informed consent form, and data dictionary) will be made available to qualified researchers upon reasonable request for the purpose of academic research or meta-analysis. Requests should be directed to the Principal Investigator (Dr. Ariel Chow Ka Man) via email.

A formal data sharing agreement will be required. The agreement will specify the purpose of data use, data security requirements, and prohibition of re-identification of participants. Requests will be reviewed by the Principal Investigator and co-investigators to ensure scientific merit and compliance with ethics requirements. Data will be provided in de-identified format.

IPD 공유 지원 정보 유형

  • 연구_프로토콜
  • ICF

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

아니

미국 FDA 규제 기기 제품 연구

아니

이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .

구독하다