Cited by 35Mobile Health and mHealth ApplicationsDigital Mental Health InterventionsSubstance Abuse Treatment and Outcomes

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

Open access
Bell, Lauren, Garnett, Claire, Bao, Yihan, Cheng, Zhaoxi, Qian, Tianchen, Perski, Olga, Potts, Henry W W, Williamson, Elizabeth·2023·JMIR mHealth and uHealth

Published version of a preprint

Abstract

Background: Drink Less is a behavior change app to help higher-risk drinkers in the United Kingdom reduce their alcohol consumption. The app includes a daily notification asking users to “Please complete your drinks and mood diary,” yet we did not understand the causal effect of the notification on engagement nor how to improve this component of Drink Less. We developed a new bank of 30 new messages to increase users’ reflective motivation to engage with Drink Less. This study aimed to determine how standard and new notifications affect engagement. Objective: Our objective was to estimate the causal effect of the notification on near-term engagement, to explore whether this effect changed over time, and to create an evidence base to further inform the optimization of the notification policy. Methods: We conducted a micro-randomized trial (MRT) with 2 additional parallel arms. Inclusion criteria were Drink Less users who consented to participate in the trial, self-reported a baseline Alcohol Use Disorders Identification Test score of ≥8, resided in the United Kingdom, were aged ≥18 years, and reported interest in drinking less alcohol. Our MRT randomized 350 new users to test whether receiving a notification, compared with receiving no notification, increased the probability of opening the app in the subsequent hour, over the first 30 days since downloading Drink Less. Each day at 8 PM, users were randomized with a 30% probability of receiving the standard message, a 30% probability of receiving a new message, or a 40% probability of receiving no message. We additionally explored time to disengagement, with the allocation of 60% of eligible users randomized to the MRT (n=350) and 40% of eligible users randomized in equal number to the 2 parallel arms, either receiving the no notification policy (n=98) or the standard notification policy (n=121). Ancillary analyses explored effect moderation by recent states of habituation and engagement. Results: Receiving a notification, compared with not receiving a notification, increased the probability of opening the app in the next hour by 3.5-fold (95% CI 2.91-4.25). Both types of messages were similarly effective. The effect of the notification did not change significantly over time. A user being in a state of already engaged lowered the new notification effect by 0.80 (95% CI 0.55-1.16), although not significantly. Across the 3 arms, time to disengagement was not significantly different. Conclusions: We found a strong near-term effect of engagement on the notification, but no overall difference in time to disengagement between users receiving the standard fixed notification, no notification at all, or the random sequence of notifications within the MRT. The strong near-term effect of the notification presents an opportunity to target notifications to increase “in-the-moment” engagement. Further optimization is required to improve the long-term engagement. International Registered Report Identifier (IRRID): RR2-10.2196/18690

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References 79 · Cited by 35

Authors
Bell, L., Garnett, C., Bao, Y., Cheng, Z., Qian, T., Perski, O., Potts, H. W. W., & Williamson, E.
Affiliations
  • University of Cambridge (GB)
  • University College London (GB)
  • Yale University (US)
  • Harvard University (US)
  • University of California, Irvine (US)
  • London School of Hygiene & Tropical Medicine (GB)
Corresponding author
Potts, Henry W W
Venue
JMIR mHealth and uHealth
Published
2023-06-09
Volume
11
Pages
e38342
ISSN
2291-5222 (ISSN-L)
OpenAlex
W4361984316
Cited by
35
References
79
Citations by year
2026: 15 · 2025: 12 · 2024: 6 · 2023: 1 · 2021: 1
FWCI
12.04
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR mhealth and uhealth (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • Bristol Research (University of Bristol) (publishedVersion, cc-by)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Explore Bristol Research (submittedVersion, cc-by)
Funders
  • Wellcome Trust (224485/Z/21/Z)
  • United Kingdom Clinical Research Collaboration
  • Cancer Research UK ((C1417/A22962), C1417, A22962)
  • National Institute for Health and Care Research (NIHR127651, C1417/A22962)
  • British Heart Foundation
  • Department of Health and Social Care (C1417/A22962)
  • University College London
  • National University of Singapore
  • Public Health England
  • National Institutes of Health
  • Medical Research Council (MR/S01442X/1, C1417/A22962, MR/L004933/2, MR/L004933/2-R18)
  • Economic and Social Research Council
  • School for Public Health Research (C1417/A22962)
  • National Institute on Alcohol Abuse and Alcoholism (R01AA023187)
  • National Institute on Drug Abuse (P50DA039838)
  • National Cancer Institute (U01CA229437)
  • National Institute of Biomedical Imaging and Bioengineering (U54EB020404)
  • Division of Mathematical Sciences
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
Keywords
notifications, mobile health apps, alcohol consumption reduction, app engagement, reflective motivation, habituation, micro-randomized trial, mood diary, alcohol use disorder screening
MeSH terms
Adolescent, Adult, Alcohol Drinking, Alcoholism, United Kingdom, Humans, Self Report, Mobile Applications

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