Personalized Policy Learning using Longitudinal Mobile Health Data

Quantitative Synthesis of Personalized Trials Studies: Meta-Analysis of Aggregated Data Versus Individual Patient Data

We have entered an era in which scientific knowledge and evidence increasingly inform research practice and policy. As there is an exponential increase in the use of personalized trials, there is a remarkable growing interest in the quantitative synthesis of personalized trials. One technique that is developed and can be applied for this purpose is meta-analysis. Meta-analysis involves the quantitative integration of effect sizes from several personalized trials. In this study, aggregated data (AD) and individual patient data (IPD) methods for meta-analysis of personalized trials are discussed, together with an empirical demonstration using a subset of a real meta-analytic data set. For the empirical demonstration, 26 personalized trials received usual care and yoga intervention in a randomized sequence. Results show a general consensus between the AD and IPD approach in terms of conclusions-that both usual care and the yoga intervention are effective in reducing pain. However, the IPD approach provides more information about the intervention effectiveness and intervention heterogeneity. IPD is a more flexible modeling approach, allowing for a variety of modeling options.

Notifications to Improve Engagement With an Alcohol Reduction App: Protocol for a Micro-Randomized Trial

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/18690.