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Updated: Mar 16, 2026

Control of Eating Behavior Using a Novel Feedback System

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

The EAT Algorithm: A Visual Tool to De-escalate Food Avoidance Anxiety in Parents.

Kam Lun Hon¹, Alexander K C Leung², Gilbert Chua³

¹Department of Paediatrics, CUHK Medical Centre, Chinese University of Hong Kong, Hong Kong, China.

Current Pediatric Reviews

|March 14, 2026

Summary

This study introduces the EAT graphic algorithm to help clinicians manage parental food avoidance anxiety, especially for children with atopic disease. The algorithm successfully guided dietary decisions and reduced unnecessary food avoidance.

Keywords:

EAT algorithm Food artificial intelligence clinical decision support system (CDSS)food avoidance anxiety food-induced anaphylaxis formula milk milk allergy parental anxiety personalized medicine.phobia precision medicine

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Control of Eating Behavior Using a Novel Feedback System

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A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Area of Science:

Pediatric Allergy and Immunology
Behavioral Pediatrics
Clinical Nutrition

Background:

Parental anxiety regarding children's food intake, particularly those with atopic conditions, presents significant clinical challenges.
Food avoidance anxiety can lead to suboptimal dietary patterns and unnecessary medical interventions.

Purpose of the Study:

To present a schematic algorithm, the EAT (Ensuring Access to Nutrition) graphic algorithm, for counseling food-phobic parents.
To illustrate the algorithm's utility in managing parental concerns about food avoidance anxiety.

Main Methods:

The study describes the application of the EAT graphic algorithm in counseling parents.
Anonymized case studies are used to demonstrate the algorithm's effectiveness.

Main Results:

The EAT algorithm successfully guided dietary decisions in five diverse cases.
Its application led to a reduction in unnecessary food avoidance.
Parental management strategies were aligned with current clinical evidence.

Conclusions:

The EAT algorithm offers a clear visual tool for clinicians to effectively counsel parents.
It has the potential to decrease unnecessary diagnostic testing and promote normalized eating patterns in children.