ORCID Profile
0000-0002-5408-8525
Current Organisations
Monash University
,
Queen Mary University of London
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Publisher: Wiley
Date: 23-04-2018
DOI: 10.1002/PST.1863
Publisher: American Medical Association (AMA)
Date: 07-2020
Publisher: Springer Science and Business Media LLC
Date: 13-06-2017
Publisher: JMIR Publications Inc.
Date: 07-08-2020
DOI: 10.2196/18690
Abstract: Drink Less is a behavior change app that aims to help users in the general adult population reduce hazardous and harmful alcohol consumption. The app includes a daily push notification, delivered at 11 am, asking users to “Please complete your mood and drinking diaries.” Previous analysis of Drink Less engagement data suggests the current notification strongly influences how users engage with the app in the subsequent hour. To exploit a potential increase of vulnerability of excess drinking and opportunity to engage with the app in the evenings, we changed the delivery time from 11 am to 8 pm. We now aim to further optimise the content and sequence of notifications, testing 30 new evidence-informed notifications targeting the user’s perceived usefulness of the app. The primary objective is to assess whether sending a notification at 8 pm increases behavioral engagement (opening the app) in the subsequent hour. Secondary objectives include comparing the effect of the new bank of messages with the standard message and effect moderation over time. We also aim to more generally understand the role notifications have on the overall duration, depth, and frequency of engagement with Drink Less over the first 30 days after download. This is a protocol for a micro-randomized trial with two additional parallel arms. Inclusion criteria are Drink Less users who (1) consent to participate in the trial (2) self-report a baseline Alcohol Use Disorders Identification Test score of 8 or above (3) reside in the United Kingdom (4) age ≥18 years and (5) report interest in drinking less alcohol. In the micro-randomized trial, participants will be randomized daily at 8 pm to receive no notification, a notification with text from the new message bank, or the standard message. The primary outcome is the time-varying, binary outcome of “Did the user open the app in the hour from 8 pm to 9 pm?”. The primary analysis will estimate the marginal relative risk for the notifications using an estimator developed for micro-randomized trials with binary outcomes. Participants randomized to the parallel arms will receive no notifications (Secondary Arm A), or the standard notification delivered daily at 11 am (Secondary Arm B) over 30 days, allowing the comparison of overall engagement between different notification delivery strategies. Approval was granted by the University College of London’s Departmental Research Ethics Committee (CEHP/2016/556) on October 11, 2019, and The London School of Hygiene and Tropical Medicine Interventions Research Ethics Committee (17929) on November 27, 2019. Recruitment began on January 2, 2020, and is ongoing. Understanding how push notifications may impact engagement with a behavior change app can lead to further improvements in engagement, and ultimately help users reduce their alcohol consumption. This understanding may also be generalizable to other apps that target a variety of behavior changes. DERR1-10.2196/18690
Publisher: JMIR Publications Inc.
Date: 12-03-2020
Abstract: lt i Drink Less /i is a behavior change app that aims to help users in the general adult population reduce hazardous and harmful alcohol consumption. The app includes a daily push notification, delivered at 11 am, asking users to “Please complete your mood and drinking diaries.” Previous analysis of i Drink Less /i engagement data suggests the current notification strongly influences how users engage with the app in the subsequent hour. To exploit a potential increase of vulnerability of excess drinking and opportunity to engage with the app in the evenings, we changed the delivery time from 11 am to 8 pm. We now aim to further optimise the content and sequence of notifications, testing 30 new evidence-informed notifications targeting the user’s perceived usefulness of the app. he primary objective is to assess whether sending a notification at 8 pm increases behavioral engagement (opening the app) in the subsequent hour. Secondary objectives include comparing the effect of the new bank of messages with the standard message and effect moderation over time. We also aim to more generally understand the role notifications have on the overall duration, depth, and frequency of engagement with i Drink Less /i over the first 30 days after download. his is a protocol for a micro-randomized trial with two additional parallel arms. Inclusion criteria are i Drink Less /i users who (1) consent to participate in the trial (2) self-report a baseline Alcohol Use Disorders Identification Test score of 8 or above (3) reside in the United Kingdom (4) age ≥18 years and (5) report interest in drinking less alcohol. In the micro-randomized trial, participants will be randomized daily at 8 pm to receive no notification, a notification with text from the new message bank, or the standard message. The primary outcome is the time-varying, binary outcome of i “Did the user open the app in the hour from 8 pm to 9 pm?” /i . The primary analysis will estimate the marginal relative risk for the notifications using an estimator developed for micro-randomized trials with binary outcomes. Participants randomized to the parallel arms will receive no notifications (Secondary Arm A), or the standard notification delivered daily at 11 am (Secondary Arm B) over 30 days, allowing the comparison of overall engagement between different notification delivery strategies. pproval was granted by the University College of London’s Departmental Research Ethics Committee (CEHP/2016/556) on October 11, 2019, and The London School of Hygiene and Tropical Medicine Interventions Research Ethics Committee (17929) on November 27, 2019. Recruitment began on January 2, 2020, and is ongoing. nderstanding how push notifications may impact engagement with a behavior change app can lead to further improvements in engagement, and ultimately help users reduce their alcohol consumption. This understanding may also be generalizable to other apps that target a variety of behavior changes. ERR1-10.2196/18690
Publisher: JMIR Publications Inc.
Date: 09-06-2023
DOI: 10.2196/38342
Abstract: 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. 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. 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. 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. 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. RR2-10.2196/18690
Publisher: JMIR Publications Inc.
Date: 10-08-2020
Abstract: ehavior change apps can develop iteratively, where the app evolves into a complex, dynamic, or personalized intervention through cycles of research, development, and implementation. Understanding how existing users engage with an app (eg, frequency, amount, depth, and duration of use) can help guide further incremental improvements. We aim to explore how simple visualizations can provide a good understanding of temporal patterns of engagement, as usage data are often longitudinal and rich. his study aims to visualize behavioral engagement with i Drink Less /i , a behavior change app to help reduce hazardous and harmful alcohol consumption in the general adult population of the United Kingdom. e explored behavioral engagement among 19,233 existing users of i Drink Less /i . Users were included in the s le if they were from the United Kingdom were 18 years or older were interested in reducing their alcohol consumption had a baseline Alcohol Use Disorders Identification Test score of 8 or above, indicative of excessive drinking and had downloaded the app between May 17, 2017, and January 22, 2019 (615 days). Measures of when sessions begin, length of sessions, time to disengagement, and patterns of use were visualized with heat maps, timeline plots, k-modes clustering analyses, and Kaplan-Meier plots. he daily 11 AM notification is strongly associated with a change in engagement in the following hour reduction in behavioral engagement over time, with 50.00% (9617/19,233) of users disengaging (defined as no use for 7 or more consecutive days) 22 days after download identification of 3 distinct trajectories of use, namely engagers (4651/19,233, 24.18% of users), slow disengagers (3679/19,233, 19.13% of users), and fast disengagers (10,903/19,233, 56.68% of users) and limited depth of engagement with 85.076% (7,095,348/8,340,005) of screen views occurring within the i Self-monitoring and Feedback /i module. In addition, a peak of both frequency and amount of time spent per session was observed in the evenings. isualizations play an important role in understanding engagement with behavior change apps. Here, we discuss how simple visualizations helped identify important patterns of engagement with i Drink Less /i . Our visualizations of behavioral engagement suggest that the daily notification substantially impacts engagement. Furthermore, the visualizations suggest that a fixed notification policy can be effective for maintaining engagement for some users but ineffective for others. We conclude that optimizing the notification policy to target both effectiveness and engagement is a worthwhile investment. Our future goal is to both understand the causal effect of the notification on engagement and further optimize the notification policy within i Drink Less /i by tailoring to contextual circumstances of in iduals over time. Such tailoring will be informed from the findings of our micro-randomized trial (MRT), and these visualizations were useful in both gaining a better understanding of engagement and designing the MRT.
Publisher: JMIR Publications Inc.
Date: 29-03-2022
Abstract: lt i Drink Less /i 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 i “ /i Please complete your drinks and mood diary, i ” /i yet we did not understand the causal effect of the notification on engagement nor how to improve this component of i Drink Less /i . We developed a new bank of 30 new messages to increase users’ reflective motivation to engage with i Drink Less /i . This study aimed to determine how standard and new notifications affect engagement. ur 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. e conducted a micro-randomized trial (MRT) with 2 additional parallel arms. Inclusion criteria were i Drink Less /i 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 i Drink Less /i . 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. eceiving 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 i already engaged /i 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. e 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. R2-10.2196/18690
Publisher: JMIR Publications Inc.
Date: 11-12-2020
DOI: 10.2196/23369
Abstract: Behavior change apps can develop iteratively, where the app evolves into a complex, dynamic, or personalized intervention through cycles of research, development, and implementation. Understanding how existing users engage with an app (eg, frequency, amount, depth, and duration of use) can help guide further incremental improvements. We aim to explore how simple visualizations can provide a good understanding of temporal patterns of engagement, as usage data are often longitudinal and rich. This study aims to visualize behavioral engagement with Drink Less, a behavior change app to help reduce hazardous and harmful alcohol consumption in the general adult population of the United Kingdom. We explored behavioral engagement among 19,233 existing users of Drink Less. Users were included in the s le if they were from the United Kingdom were 18 years or older were interested in reducing their alcohol consumption had a baseline Alcohol Use Disorders Identification Test score of 8 or above, indicative of excessive drinking and had downloaded the app between May 17, 2017, and January 22, 2019 (615 days). Measures of when sessions begin, length of sessions, time to disengagement, and patterns of use were visualized with heat maps, timeline plots, k-modes clustering analyses, and Kaplan-Meier plots. The daily 11 AM notification is strongly associated with a change in engagement in the following hour reduction in behavioral engagement over time, with 50.00% (9617/19,233) of users disengaging (defined as no use for 7 or more consecutive days) 22 days after download identification of 3 distinct trajectories of use, namely engagers (4651/19,233, 24.18% of users), slow disengagers (3679/19,233, 19.13% of users), and fast disengagers (10,903/19,233, 56.68% of users) and limited depth of engagement with 85.076% (7,095,348/8,340,005) of screen views occurring within the Self-monitoring and Feedback module. In addition, a peak of both frequency and amount of time spent per session was observed in the evenings. Visualizations play an important role in understanding engagement with behavior change apps. Here, we discuss how simple visualizations helped identify important patterns of engagement with Drink Less. Our visualizations of behavioral engagement suggest that the daily notification substantially impacts engagement. Furthermore, the visualizations suggest that a fixed notification policy can be effective for maintaining engagement for some users but ineffective for others. We conclude that optimizing the notification policy to target both effectiveness and engagement is a worthwhile investment. Our future goal is to both understand the causal effect of the notification on engagement and further optimize the notification policy within Drink Less by tailoring to contextual circumstances of in iduals over time. Such tailoring will be informed from the findings of our micro-randomized trial (MRT), and these visualizations were useful in both gaining a better understanding of engagement and designing the MRT.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Lauren Bell.