ArticleDigital health
Crowdsourcing for self-monitoring: Using the Traffic Light Diet and crowdsourcing to provide dietary feedback.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Defining Adherence to Mobile Dietary Self-Monitoring and Assessing Tracking Over Time: Tracking at Least Two Eating Occasions per Day Is Best Marker of Adherence within Two Different Mobile Health Randomized Weight Loss Interventions.Journal of the Academy of Nutrition and Dietetics · 2019Trial
- Leveraging recreational activities to reduce obesity-related behaviors in children from lower-income households.Appetite · 2025Article
- NutriColoring: designing a doodling toolkit to support daily self-reported dietary assessment among office workers.Frontiers in psychology · 2023Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSmartphone photography and crowdsourcing feedback could reduce participant burden for dietary self-monitoring.
objectivesTo assess if untrained individuals can accurately crowdsource diet quality ratings of food photos using the Traffic Light Diet (TLD) approach.
methodsParticipants were recruited via Amazon Mechanical Turk and read a one-page description on the TLD. The study examined the participant accuracy score (total number of correctly categorized foods as red, yellow, or green per person), the food accuracy score (accuracy by which each food was categorized), and if the accuracy of ratings increased when more users were included in the crowdsourcing. For each of a range of possible crowd sizes (
resultsParticipants (
conclusionsNutrition-novice users can be trained easily to rate foods using the TLD. Since feedback from crowdsourcing relies on the agreement of the majority, this method holds promise as a low-burden approach to providing diet-quality feedback.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.