title: "Smart" RCTs: Development of a Smartphone App for Fully Automated Nutrition-Labeling Intervention Trials.
abstract: 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.
  
  
  BACKGROUND
  Australian New Zealand Clinical Trials Registry ACTRN12614000964617. New Zealand trial: Australian New Zealand Clinical Trials Registry ACTRN12614000644662.
authors.affiliation: National Institute for Health Innovation, School of Population Health, University of Auckland, Auckland, New Zealand. k.volkova@auckland.ac.nz.
authors.forename: Ekaterina
authors.identifier: http://orcid.org/0000-0002-0266-3698
authors.initials: E
authors.lastname: Volkova
authors.forename: Nicole
authors.identifier: http://orcid.org/0000-0002-0873-7328
authors.initials: N
authors.lastname: Li
authors.forename: Elizabeth
authors.identifier: http://orcid.org/0000-0003-4505-3256
authors.initials: E
authors.lastname: Dunford
authors.forename: Helen
authors.identifier: http://orcid.org/0000-0002-9521-3513
authors.initials: H
authors.lastname: Eyles
authors.forename: Michelle
authors.identifier: http://orcid.org/0000-0003-2941-8147
authors.initials: M
authors.lastname: Crino
authors.forename: Jo
authors.identifier: http://orcid.org/0000-0002-7172-8002
authors.initials: J
authors.lastname: Michie
authors.forename: Cliona
authors.identifier: http://orcid.org/0000-0002-1144-9167
authors.initials: C
authors.lastname: Ni Mhurchu
keywords: nutrition labeling; public health; randomized controlled trial; smartphone