Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Assessment of the Gastrointestinal System II: Health Perception Pattern01:29

Assessment of the Gastrointestinal System II: Health Perception Pattern

115
Assessing the gastrointestinal (GI) system is a complex process that begins with collecting subjective data. This data, collected through patient interviews, provides crucial insights into the patient's health history, perception patterns, and lifestyle habits, all contributing significantly to GI health.
Health Perception Patterns
Health perception patterns offer valuable insights into a patient's lifestyle habits and how they may impact their GI health. These patterns include:
115
Assessment of the Gastrointestinal System I: Subjective Data01:17

Assessment of the Gastrointestinal System I: Subjective Data

197
Assessing the gastrointestinal (GI) system is a complex process that begins with collecting subjective data. This data, collected through patient interviews, provides crucial insights into the patient's health history, perception patterns, and lifestyle habits, all contributing significantly to GI health.
Health History
The initial step in assessing the GI system is obtaining a comprehensive health history. This includes inquiring about the patient's history or presence of problems...
197

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluation of an AI-Supported Nutrition Application (WiseFood) in a Living Lab Context: Protocol for a User Needs Assessment, Co-Design, and Feasibility Testing.

JMIR research protocols·2026
Same author

Healthy and sustainable diets defined.

Nature food·2025
Same author

An Evaluation of ChatGPT for Nutrient Content Estimation from Meal Photographs.

Nutrients·2025
Same author

Expansion and Assessment of a Web-Based 24-Hour Dietary Recall Tool, Foodbook24, for Use Among Diverse Populations Living in Ireland: Comparative Analysis.

Online journal of public health informatics·2025
Same author

Bovine dairy products and flow mediated dilation (FMD): a systematic review of the published evidence.

European journal of nutrition·2025
Same author

The effects of saturated fat intake from dairy on CVD markers: the role of food matrices.

The Proceedings of the Nutrition Society·2024

Related Experiment Video

Updated: Jul 3, 2025

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
04:46

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake

Published on: September 18, 2018

7.2K

Dietary Intake Assessment Using a Novel, Generic Meal-Based Recall and a 24-Hour Recall: Comparison Study.

Cathal O'Hara1,2,3, Eileen R Gibney1,2,3

  • 1University College Dublin Institute of Food and Health, Science Centre South, University College Dublin, Dublin, Ireland.

Journal of Medical Internet Research
|February 14, 2024
PubMed
Summary

A new meal-based dietary assessment method provides nutrient intake estimates comparable to traditional 24-hour recalls. This approach simplifies intake reporting, making it a user-friendly alternative for dietary tracking.

Keywords:
24-hour recalldietary intake assessmenteating behaviorseating occasionsmeal patternsnutrition assessmentrelative validity

More Related Videos

Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq
04:54

Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq

Published on: March 19, 2021

4.6K
Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
06:21

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method

Published on: February 19, 2021

5.7K

Related Experiment Videos

Last Updated: Jul 3, 2025

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
04:46

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake

Published on: September 18, 2018

7.2K
Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq
04:54

Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq

Published on: March 19, 2021

4.6K
Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
06:21

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method

Published on: February 19, 2021

5.7K

Area of Science:

  • Nutrition Science
  • Dietary Assessment Methods
  • Public Health

Background:

  • Traditional food-based dietary intake assessments are time-consuming and burdensome for users.
  • Ease of use is paramount for individuals using nutrition or diet applications.
  • Reporting whole meals offers a less burdensome alternative to individual food logging.

Purpose of the Study:

  • To develop and evaluate a novel, meal-based dietary intake assessment method.
  • To compare the accuracy of nutrient intake estimation against a web-based 24-hour recall (24HR).

Main Methods:

  • Participants used a web-based tool to select meal images representing their previous day's intake.
  • A crossover design was employed, with participants completing both the meal-based recall and a web-based 24HR.
  • Nutrient intake estimates and categorization according to guidelines were compared between the two methods.

Main Results:

  • The median percentage difference in nutrient intake between the meal-based method and 24HR was 7.6%.
  • Effect sizes for nutrient differences were small for 83% of variables.
  • Correlation coefficients were statistically significant for 78% of nutrient variables, with a median correlation of 0.32.

Conclusions:

  • The generic meal-based method offers comparable nutrient intake estimates to web-based 24HR.
  • Varying levels of agreement were observed among different nutrients.
  • Further research is needed to refine the method and explore features like image recognition for whole meals.