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“Smart” RCTs: Development of a Smartphone App for Fully Automated Nutrition-Labeling Intervention Trials


Volkova, Ekaterina; Li, Nicole; Dunford, Elizabeth K.; Eyles, Helen; Crino, Michelle; Michie, Jo; & Ni Mhurchu, Cliona (2016). “Smart” RCTs: Development of a Smartphone App for Fully Automated Nutrition-Labeling Intervention Trials. JMIR mHealth and uHealth, 4(1), e23. PMCID: PMC4816928


BACKGROUND: There 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.
OBJECTIVE: The 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.
METHODS: Two 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.
RESULTS: In 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.
CONCLUSIONS: The 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.


Reference Type

Journal Article

Year Published


Journal Title

JMIR mHealth and uHealth


Volkova, Ekaterina
Li, Nicole
Dunford, Elizabeth K.
Eyles, Helen
Crino, Michelle
Michie, Jo
Ni Mhurchu, Cliona