Reinforcement learning to personalize message framing for health habits (REINFORCE)
The impact of using reinforcement learning to personalize communication on medication adherence: findings from the REINFORCE trial
Lauffenburger JC, Yom-Tov E, Keller PA, McDonnell ME, Crum KL, Bhatkhande G, Sears ES, Hanken K, Bessette LG, Fontanet CP, Haff N, Vine S, Choudhry NK
NPJ Digit Med
2024 February 19
REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial
Lauffenburger LC, Yum-Tov E, Keller PA, McDonnell ME, Bessette LG, Fontanet CP, Sears ES, Kim E, Hanken K, Buckley JJ, Barlev RA, Haff N, Choudhry NK
BMJ Open
2021 December 3
Using Cues and Rewards in Patients with Arthritis and Rheumatic Disease
Personalizing intervention to reduce clinical inertia in the treatment of hypertension
Testing interventions to reduce clinical inertia in the treatment of hypertension: rationale and design of a pragmatic randomized controlled trial
Haff N, Sreedhara SK, Wood W, Yom-Tov E, Horn DM, Hoover M, Low G, Lauffenburger JC, Chaitoff A, Russo M, Hanken K, Crum KL, Fontanet CP, Choudhry NK
Am Heart J
2023 November 13
Novel application of simulation for providers to overcome the hot-cold empathy gap in high-risk medication prescribing
Overcoming decisional gaps in high-risk prescribing by junior physicians using simulation-based training: Protocol for a randomized controlled trial
Lauffenburger JC, DiFrancesco MF, Barlev RA, Robertson T, Kim E, Coll MD, Haff N, Fontanet CP, Hanken K, Oran R, Avorn J, Choudhry NK
JMIR Res Protoc
2022 April