Usability of Food Size Aids in Mobile Dietary Reporting Apps for Young Adults: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Young adults are more likely to use self-managed dietary reporting apps. However, there is scant research examining the user experience of different measurement approaches for mobile dietary reporting apps when dealing with a wide variety of food shapes and container sizes. OBJECTIVE: Field user experience testing was conducted under actual meal conditions to assess the accuracy, efficiency, and subjective reaction of three food portion measurement methods embedded in a developed mobile app. Key-in-based aid (KBA), commonly used in many current apps, relies on the user's ability to key in volumes or weights. Photo-based aid (PBA) extends traditional assessment methods, allowing users to scroll, observe, and select a reduced-size image from a set of options. Gesture-based aid (GBA) is a new experimental approach in which the user makes finger movements on the screen to roughly describe food portion boundaries accompanied by a background reference. METHODS: A group of 124 young adults aged 19 to 26 years was recruited for a head-to-head randomized comparison and divided into 3 groups: a KBA (n=42) control group and PBA (n=41) and GBA (n=41) experimental groups. In total, 3 meals (ie, breakfast, lunch, and dinner) were served in a university cafeteria. Participants were provided with 25 dishes and beverages for selection, with a variety of food shapes and containers that reflect everyday life conditions. The accuracy of and time spent on realistic interaction during food portion estimation and the subjective reaction of each aid were recorded and analyzed. RESULTS: Participants in the KBA group provided the highest accuracy in terms of hash brown weight (P=.004) and outperformed PBA or GBA for many soft drinks in cups. PBA had the best results for a cylindrical hot dog (P<.001), irregularly shaped pork chop (P<.001), and green tea beverage (660 mL; P<.001). GBA outperformed PBA for most drinks, and GBA outperformed KBA for some vegetables. The GBA group spent significantly more time assessing food items than the KBA and PBA groups. For each aid, the overall subjective reaction based on the score of the System Usability Scale was not significantly different. CONCLUSIONS: Experimental results show that each aid had some distinguishing advantages. In terms of user acceptance, participants considered all 3 aids to be usable. Furthermore, users' subjective opinions regarding measurement accuracy contradicted the empirical findings. Future work will consider the use of each aid based on food or container shape and integrate the various advantages of the 3 different aids for better results. Our findings on the use of portion size aids are based on realistic and diverse food items, providing a useful reference for future app improvement of an effective, evidence-based, and acceptable feature. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Registry ISRCTN36710750; http://www.controlled-trials.com/ISRCTN36710750.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".