ORCID Profile
0000-0002-6589-299X
Current Organisations
University College London
,
Universitetet i Bergen
,
University of Bristol
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Publisher: Public Library of Science (PLoS)
Date: 10-10-2023
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: 02-2021
DOI: 10.2196/26578
Publisher: American Geophysical Union (AGU)
Date: 05-2023
DOI: 10.1029/2023JA031394
Abstract: Inverse modeling has become one of the primary methods for studying ionospheric electrodynamics, especially when using magnetic field measurements from below the ionosphere. We present a method for quantifying the spatial resolution in an inverse model for non‐uniformly s led spatial data. This method provides a tool for assessing if a model can resolve the physical phenomena of interest. We quantify the spatial resolution for the Spherical Elementary Current System basis functions to model the ionospheric dynamics. Our results apply to models with spatially confined model parameters, unlike spherical harmonics where the model parameters describe the litude of global surface functions. The method is demonstrated for the upcoming Electrojet Zeeman Imaging Explorer cubesat mission which will provide spatially distributed remote sensing measurements of the magnetic field in the mesosphere. We show that, including measurements from a single ground magnetometer can significantly improve the spatial resolution. However, the impact of including a ground magnetometer depends on the relative position of the station with respect to the mesospheric measurements. In addition, a method for reducing two regularization parameters to one is presented. Reducing the amount of regularization parameters simplifies the optimization problem and facilitates a fair comparison between the models with and without a ground magnetometer.
Publisher: JMIR Publications Inc.
Date: 26-11-2020
DOI: 10.2196/24175
Abstract: A core outcome set (COS) for trials and evaluations of the effectiveness and efficacy of alcohol brief interventions (ABIs) has recently been established through international consensus to address the variability of outcomes evaluated. This is a protocol for studies to assess if there are order effects among the questions included in the COS. The 10 items of the COS are organized into 4 clusters. A factorial design will be used with 24 arms, where each arm represents 1 order of the 4 clusters. In iduals searching online for help will be asked to complete a questionnaire, and consenting participants will be randomized to 1 of the 24 arms (double-blind with equal allocation). Participants will be included if they are 18 years or older. The primary analyses will (1) estimate how the order of the clusters of outcomes affects how participants respond and (2) investigate patterns of abandonment of the questionnaire. Data collection is expected to commence in November 2020. A Bayesian group sequential design will be used with interim analyses planned for every 50 participants completing the questionnaire. Data collection will end no more than 24 months after commencement, and the results are expected to be published no later than December 2023. Homogenizing the outcomes evaluated in studies of ABIs is important to support synthesis, and the COS is an important step toward this goal. Determining whether there may be issues with the COS question order may improve confidence in using it and speed up its dissemination in the research community. We encourage others to adopt the protocol as a study within their trial as they adopt the ORBITAL (Outcome Reporting in Brief Intervention Trials: Alcohol) COS to build a worldwide repository and provide materials to support such analysis. ISRCTN Registry ISRCTN17954645 www.isrctn.com/ISRCTN17954645 PRR1-10.2196/24175
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: American Geophysical Union (AGU)
Date: 12-2018
DOI: 10.1029/2018JA025877
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: 17-12-2020
Abstract: core outcome set (COS) for trials and evaluations of the effectiveness and efficacy of alcohol brief interventions (ABIs) has recently been established through international consensus to address the variability of outcomes evaluated. his is a protocol for studies to assess if there are order effects among the questions included in the COS. he 10 items of the COS are organized into 4 clusters. A factorial design will be used with 24 arms, where each arm represents 1 order of the 4 clusters. In iduals searching online for help will be asked to complete a questionnaire, and consenting participants will be randomized to 1 of the 24 arms (double-blind with equal allocation). Participants will be included if they are 18 years or older. The primary analyses will (1) estimate how the order of the clusters of outcomes affects how participants respond and (2) investigate patterns of abandonment of the questionnaire. ata collection is expected to commence in November 2020. A Bayesian group sequential design will be used with interim analyses planned for every 50 participants completing the questionnaire. Data collection will end no more than 24 months after commencement, and the results are expected to be published no later than December 2023. omogenizing the outcomes evaluated in studies of ABIs is important to support synthesis, and the COS is an important step toward this goal. Determining whether there may be issues with the COS question order may improve confidence in using it and speed up its dissemination in the research community. We encourage others to adopt the protocol as a study within their trial as they adopt the ORBITAL (Outcome Reporting in Brief Intervention Trials: Alcohol) COS to build a worldwide repository and provide materials to support such analysis. SRCTN Registry ISRCTN17954645 www.isrctn.com/ISRCTN17954645
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: SAGE Publications
Date: 2023
DOI: 10.1177/20552076231155684
Abstract: A core outcome set (COS) has been developed in alcohol brief intervention (ABI) research through international consensus. This study aimed to estimate order effects among questions in the COS. In iduals aged 18 or older who searched online for alcohol-related help were invited to complete the COS. The order of questions was randomised following a factorial design. Primary outcomes were order effects among the COS items and patterns of attrition. Between 21/10/2020 and 26/11/2020, we randomised 7334 participants, of which 5256 responded to at least one question and were available for analyses. Current non-drinkers were excluded. We found evidence of higher self-reported average consumption and odds of harmful and hazardous drinking was found among those who first answered questions on recent consumption and impact of alcohol use. Lower self-reported recent consumption was found among those first asked about average consumption. Quality of life (QoL) was reported lower among those who first responded to when questions on impact of alcohol use were asked first, which in turn was lower among those who first answered question on when average consumption and QoL were asked first. Attrition was lowest when average consumption was asked first, and highest when QoL or impact of alcohol use was asked first. Median completion time for the COS was 4.3 min. Question order affects outcomes and attrition. If the aim is to minimize attrition, consumption measures should be asked before QoL and impact of alcohol use however, this order impacts self-reported alcohol consumption and so researchers should be guided by study priorities. At a minimum, all participants should be asked the same questions in the same order. The trial was prospectively registered (ISRCTN17954645).
Publisher: American Astronomical Society
Date: 31-07-2023
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.
Publisher: JMIR Publications Inc.
Date: 07-09-2020
Abstract: core outcome set (COS) for trials and evaluations of the effectiveness and efficacy of alcohol brief interventions (ABIs) has recently been established through international consensus to address the variability of outcomes evaluated. his is a protocol for studies to assess if there are order effects among the questions included in the COS. he 10 items of the COS are organized into 4 clusters. A factorial design will be used with 24 arms, where each arm represents 1 order of the 4 clusters. In iduals searching online for help will be asked to complete a questionnaire, and consenting participants will be randomized to 1 of the 24 arms (double-blind with equal allocation). Participants will be included if they are 18 years or older. The primary analyses will (1) estimate how the order of the clusters of outcomes affects how participants respond and (2) investigate patterns of abandonment of the questionnaire. ata collection is expected to commence in November 2020. A Bayesian group sequential design will be used with interim analyses planned for every 50 participants completing the questionnaire. Data collection will end no more than 24 months after commencement, and the results are expected to be published no later than December 2023. omogenizing the outcomes evaluated in studies of ABIs is important to support synthesis, and the COS is an important step toward this goal. Determining whether there may be issues with the COS question order may improve confidence in using it and speed up its dissemination in the research community. We encourage others to adopt the protocol as a study within their trial as they adopt the ORBITAL (Outcome Reporting in Brief Intervention Trials: Alcohol) COS to build a worldwide repository and provide materials to support such analysis. SRCTN Registry ISRCTN17954645 www.isrctn.com/ISRCTN17954645 RR1-10.2196/24175
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Claire Garnett.