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cMIND AI Web Tool Usability Study (Hong Kong)

24 juillet 2026 mis à jour par: 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.

Aperçu de l'étude

Statut

Pas encore de recrutement

Description détaillée

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).

Type d'étude

Observationnel

Inscription (Estimé)

20

Contacts et emplacements

Cette section fournit les coordonnées de ceux qui mènent l'étude et des informations sur le lieu où cette étude est menée.

Coordonnées de l'étude

Critères de participation

Les chercheurs recherchent des personnes qui correspondent à une certaine description, appelée critères d'éligibilité. Certains exemples de ces critères sont l'état de santé général d'une personne ou des traitements antérieurs.

Critère d'éligibilité

Âges éligibles pour étudier

  • Adulte
  • Adulte plus âgé

Accepte les volontaires sains

Oui

Méthode d'échantillonnage

Échantillon non probabiliste

Population étudiée

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

La description

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

Plan d'étude

Cette section fournit des détails sur le plan d'étude, y compris la façon dont l'étude est conçue et ce que l'étude mesure.

Comment l'étude est-elle conçue ?

Détails de conception

Cohortes et interventions

Groupe / Cohorte
Intervention / Traitement
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.

Que mesure l'étude ?

Principaux critères de jugement

Mesure des résultats
Description de la mesure
Délai
Usability and Acceptability of the Web-Based AI Tool
Délai: 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

Mesures de résultats secondaires

Mesure des résultats
Description de la mesure
Délai
Feasibility of Meal Photo-Taking
Délai: 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
Délai: 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

Collaborateurs et enquêteurs

C'est ici que vous trouverez les personnes et les organisations impliquées dans cette étude.

Les enquêteurs

  • Chercheur principal: Chow Ka-Man, Ph.D., Hong Kong Metropolitan University

Dates d'enregistrement des études

Ces dates suivent la progression des dossiers d'étude et des soumissions de résultats sommaires à ClinicalTrials.gov. Les dossiers d'étude et les résultats rapportés sont examinés par la Bibliothèque nationale de médecine (NLM) pour s'assurer qu'ils répondent à des normes de contrôle de qualité spécifiques avant d'être publiés sur le site Web public.

Dates principales de l'étude

Début de l'étude (Estimé)

1 septembre 2027

Achèvement primaire (Estimé)

1 janvier 2028

Achèvement de l'étude (Estimé)

1 février 2028

Dates d'inscription aux études

Première soumission

24 juillet 2026

Première soumission répondant aux critères de contrôle qualité

24 juillet 2026

Première publication (Réel)

29 juillet 2026

Mises à jour des dossiers d'étude

Dernière mise à jour publiée (Réel)

29 juillet 2026

Dernière mise à jour soumise répondant aux critères de contrôle qualité

24 juillet 2026

Dernière vérification

1 juillet 2026

Plus d'information

Termes liés à cette étude

Plan pour les données individuelles des participants (IPD)

Prévoyez-vous de partager les données individuelles des participants (DPI) ?

OUI

Description du régime IPD

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.

Délai de partage IPD

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

Critères d'accès au partage IPD

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.

Type d'informations de prise en charge du partage d'IPD

  • PROTOCOLE D'ÉTUDE
  • CIF

Informations sur les médicaments et les dispositifs, documents d'étude

Étudie un produit pharmaceutique réglementé par la FDA américaine

Non

Étudie un produit d'appareil réglementé par la FDA américaine

Non

Ces informations ont été extraites directement du site Web clinicaltrials.gov sans aucune modification. Si vous avez des demandes de modification, de suppression ou de mise à jour des détails de votre étude, veuillez contacter register@clinicaltrials.gov. Dès qu'un changement est mis en œuvre sur clinicaltrials.gov, il sera également mis à jour automatiquement sur notre site Web .

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