Published on in Vol 11 (2023)

This is a member publication of University College London (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38342, first published .
How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial

How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial

How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial

Journals

  1. Alnooh G, Alessa T, Noorwali E, Albar S, Williams E, de Witte L, Hawley M. Identification of the Most Suitable Mobile Apps to Support Dietary Approaches to Stop Hypertension (DASH) Diet Self-Management: Systematic Search of App Stores and Content Analysis. Nutrients 2023;15(15):3476 View
  2. Liu X, Qian T, Bell L, Chakraborty B. Incorporating nonparametric methods for estimating causal excursion effects in mobile health with zero-inflated count outcomes. Biometrics 2024;80(2) View
  3. Prentice C, Peven K, Zhaunova L, Nayak V, Radovic T, Klepchukova A, Potts H, Ponzo S. Methods for evaluating the efficacy and effectiveness of direct-to-consumer mobile health apps: a scoping review. BMC Digital Health 2024;2(1) View
  4. Bao Y, Bell L, Williamson E, Garnett C, Qian T. Estimating causal effects for binary outcomes using per-decision inverse probability weighting. Biostatistics 2024 View
  5. Patra E, Kokkinopoulou A, Wilson-Barnes S, Hart K, Gymnopoulos L, Tsatsou D, Solachidis V, Dimitropoulos K, Rouskas K, Argiriou A, Lalama E, Csanalosi M, Pfeiffer A, Cornelissen V, Decorte E, Dias S, Oikonomidis Y, María Botana J, Leoni R, Russell D, Mantovani E, Aleksić M, Brkić B, Hassapidou M, Pagkalos I. Personal Goals, User Engagement, and Meal Adherence within a Personalised AI-Based Mobile Application for Nutrition and Physical Activity. Life 2024;14(10):1238 View