Research News

AR portion size application

Using a 3D food model, participants tested the tool’s ability to teach appropriate dietary portion sizes. 

Credit: Osaka Metropolitan University

Evidence on the effectiveness of augmented reality (AR)-based tools for portion size estimation as an educational aid remains limited. In this pilot study, Osaka Metropolitan University researchers developed a 3D food model using AR and assessed the feasibility of using this application to teach portion size estimation skills.

This intervention study involved 43 students (including 38 females) from two dietetic education institutions. Participants were randomly assigned into four groups: (1) text only, (2) text and pictures, (3) food model and (4) AR. Learning effectiveness was evaluated using a pretest of 10 different foods, followed by a 10-min instructional session with the assigned tool, and then a post-test. Participants rated each learning tool for enjoyment, usefulness and recommendation to others on an 11-point Likert scale. Outcomes included the change in the number of correct answers within ± 10% or ± 20% of the true food weight.

Mean acceptability ratings for the text only, text and picture, food model and AR groups were enjoyment (4.1, 5.6, 7.0 and 7.9), usefulness (5.5, 7.4, 8.4 and 8.3) and recommendation to others (3.6, 6.3, 6.3 and 7.1), respectively. The mean changes in correct answers for text only, text and picture, food model and AR groups were 0.7, −1.1, 1.5 and 0.1, respectively, within a 10% error margin, and 1.2, −1.9, 2.0 and 0.8, respectively, within a 20% error margin.

This pilot study suggests that AR-based tools have potential as educational aids for portion size estimation among future dietitians, with acceptability ratings comparable to conventional methods, such as text only, text and pictures, and food models.

Paper information

Journal: Journal of Human Nutrition and Dietetics
Title: Can augmented reality be used as a portion size estimation aid tool? A pilot randomized controlled trial 
DOI: 10.1111/jhn.70125
Authors: Yoshinari Matsumoto, Genya Okada, Masaya Ohta
Published: 11 September 2025
URL: https://doi.org/10.1111/jhn.70125

Contact

Yoshinari Matsumoto
Graduate School of Human Life and Ecology
Email: y-matsumoto[at]omu.ac.jp

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