Published on in Vol 4 , No 1 (2016) :Jan-Mar

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

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

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

Journals

  1. Miller L, Sutter C, Wilson M, Bergman J, Beckett L, Gibson T. 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 2018;5 View
  2. Humphrey G, Chu J, Dowling N, Rodda S, Merkouris S, Parag V, Newcombe D, Ho E, Nosa V, Ruwhui-Collins R, Whittaker R, Bullen C. Manaaki – a cognitive behavioral therapy mobile health app to support people experiencing gambling problems: a randomized control trial protocol. BMC Public Health 2020;20(1) View
  3. Holmes W, Moorhead S, Coates V, Bond R, Zheng H. Impact of digital technologies for communicating messages on weight loss maintenance: a systematic literature review. European Journal of Public Health 2019;29(2):320 View
  4. Ni Mhurchu C, Eyles H, Jiang Y, Blakely T. Do nutrition labels influence healthier food choices? Analysis of label viewing behaviour and subsequent food purchases in a labelling intervention trial. Appetite 2018;121:360 View
  5. Fuchs K, Haldimann M, Grundmann T, Fleisch E. Supporting food choices in the Internet of People: Automatic detection of diet-related activities and display of real-time interventions via mixed reality headsets. Future Generation Computer Systems 2020;113:343 View
  6. Dunford E, Poti J, Xavier D, Webster J, Taillie L. Color-Coded Front-of-Pack Nutrition Labels—An Option for US Packaged Foods?. Nutrients 2017;9(5):480 View
  7. Maramis C, Moulos I, Ioakimidis I, Papapanagiotou V, Langlet B, Lekka I, Bergh C, Maglaveras N. A smartphone application for semi-controlled collection of objective eating behavior data from multiple subjects. Computer Methods and Programs in Biomedicine 2020;194:105485 View
  8. Vogel M, Combs S, Kessel K. mHealth and Application Technology Supporting Clinical Trials: Today’s Limitations and Future Perspective of smartRCTs. Frontiers in Oncology 2017;7 View
  9. Zhang M, Ho R. Smartphone application for multi-phasic interventional trials in psychiatry: Technical design of a smart server. Technology and Health Care 2017;25(2):373 View
  10. Volkova E, Michie J, Corrigan C, Sundborn G, Eyles H, Jiang Y, Mhurchu C. Effectiveness of recruitment to a smartphone-delivered nutrition intervention in New Zealand: analysis of a randomised controlled trial. BMJ Open 2017;7(6):e016198 View
  11. Calegari L, Barbosa J, Marodin G, Fettermann D. A conjoint analysis to consumer choice in Brazil: Defining device attributes for recognizing customized foods characteristics. Food Research International 2018;109:1 View
  12. Chen R, Santo K, Wong G, Sohn W, Spallek H, Chow C, Irving M. Mobile Apps for Dental Caries Prevention: Systematic Search and Quality Evaluation. JMIR mHealth and uHealth 2021;9(1):e19958 View
  13. Lo B, Shi J, Wong H, Abi-Jaoudé A, Johnson A, Hollenberg E, Chaim G, Cleverley K, Henderson J, Levinson A, Robb J, Sanches M, Voineskos A, Wiljer D. Considerations for evaluating digital mental health tools remotely- reflections after a randomized trial of Thought Spot. General Hospital Psychiatry 2021;70:76 View

Books/Policy Documents

  1. Gabel A, Schiering I, Müller S, Ertas F. Privacy and Identity Management. The Smart Revolution. View
  2. Jäckle A, Couper M, Gaia A, Lessof C. Advances in Longitudinal Survey Methodology. View