ArticleJMIR mHealth and uHealth2016
"Smart" RCTs: Development of a Smartphone App for Fully Automated Nutrition-Labeling Intervention Trials.
Article in JMIR mHealth and uHealth, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mobile Apps for Dental Caries Prevention: Systematic Search and Quality Evaluation.JMIR mHealth and uHealth · 2021Pooled it
- Trial
- Considerations for evaluating digital mental health tools remotely- reflections after a randomized trial of Thought Spot.General hospital psychiatryTrial
- A pragmatic double blind remote pilot feasibility randomised controlled trial of a self-management app for people with Sjögren disease.Frontiers in digital health · 2025Article
- Predicting Unreported Micronutrients From Food Labels: Machine Learning Approach.Journal of medical Internet research · 2023Article
- Manaaki - a cognitive behavioral therapy mobile health app to support people experiencing gambling problems: a randomized control trial protocol.BMC public health · 2020Article
- Article
- Characteristics of Smartphone Applications for Nutrition Improvement in Community Settings: A Scoping Review.Advances in nutrition (Bethesda, Md.) · 2017Article
- An Evaluation of an eHealth Tool Designed to Improve College Students' Label-Reading Skills and Feelings of Empowerment to Choose Healthful Foods.Frontiers in public health · 2017Article
- mHealth and Application Technology Supporting Clinical Trials: Today's Limitations and Future Perspective of smartRCTs.Frontiers in oncology · 2017Article
- mHealth technologies in clinical trials: Opportunities and challenges.Indian journal of pharmacologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundThere is substantial interest in the effects of nutrition labels on consumer food-purchasing behavior. However, conducting randomized controlled trials on the impact of nutrition labels in the real world presents a significant challenge.
objectiveThe Food Label Trial (FLT) smartphone app was developed to enable conducting fully automated trials, delivering intervention remotely, and collecting individual-level data on food purchases for two nutrition-labeling randomized controlled trials (RCTs) in New Zealand and Australia.
methodsTwo versions of the smartphone app were developed: one for a 5-arm trial (Australian) and the other for a 3-arm trial (New Zealand). The RCT protocols guided requirements for app functionality, that is, obtaining informed consent, two-stage eligibility check, questionnaire administration, randomization, intervention delivery, and outcome assessment. Intervention delivery (nutrition labels) and outcome data collection (individual shopping data) used the smartphone camera technology, where a barcode scanner was used to identify a packaged food and link it with its corresponding match in a food composition database. Scanned products were either recorded in an electronic list (data collection mode) or allocated a nutrition label on screen if matched successfully with an existing product in the database (intervention delivery mode). All recorded data were transmitted to the RCT database hosted on a server.
resultsIn total approximately 4000 users have downloaded the FLT app to date; 606 (Australia) and 1470 (New Zealand) users met the eligibility criteria and were randomized. Individual shopping data collected by participants currently comprise more than 96,000 (Australia) and 229,000 (New Zealand) packaged food and beverage products.
conclusionsThe FLT app is one of the first smartphone apps to enable conducting fully automated RCTs. Preliminary app usage statistics demonstrate large potential of such technology, both for intervention delivery and data collection.
trial registrationAustralian New Zealand Clinical Trials Registry ACTRN12614000964617. New Zealand trial: Australian New Zealand Clinical Trials Registry ACTRN12614000644662.
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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.