Skip to main content


Swipe om te navigeren naar een ander artikel

25-08-2018 | Uitgave 2/2019

Journal of Behavioral Medicine 2/2019

Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss?

Journal of Behavioral Medicine > Uitgave 2/2019
Evan M. Forman, Stephanie G. Kerrigan, Meghan L. Butryn, Adrienne S. Juarascio, Stephanie M. Manasse, Santiago Ontañón, Diane H. Dallal, Rebecca J. Crochiere, Danielle Moskow


Behavioral weight loss (WL) trials show that, on average, participants regain lost weight unless provided long-term, intensive—and thus costly—intervention. Optimization solutions have shown mixed success. The artificial intelligence principle of “reinforcement learning” (RL) offers a new and more sophisticated form of optimization in which the intensity of each individual’s intervention is continuously adjusted depending on patterns of response. In this pilot, we evaluated the feasibility and acceptability of a RL-based WL intervention, and whether optimization would achieve equivalent benefit at a reduced cost compared to a non-optimized intensive intervention. Participants (n = 52) completed a 1-month, group-based in-person behavioral WL intervention and then (in Phase II) were randomly assigned to receive 3 months of twice-weekly remote interventions that were non-optimized (NO; 10-min phone calls) or optimized (a combination of phone calls, text exchanges, and automated messages selected by an algorithm). The Individually-Optimized (IO) and Group-Optimized (GO) algorithms selected interventions based on past performance of each intervention for each participant, and for each group member that fit into a fixed amount of time (e.g., 1 h), respectively. Results indicated that the system was feasible to deploy and acceptable to participants and coaches. As hypothesized, we were able to achieve equivalent Phase II weight losses (NO = 4.42%, IO = 4.56%, GO = 4.39%) at roughly one-third the cost (1.73 and 1.77 coaching hours/participant for IO and GO, versus 4.38 for NO), indicating strong promise for a RL system approach to weight loss and maintenance.

Log in om toegang te krijgen

Met onderstaand(e) abonnement(en) heeft u direct toegang:

BSL Psychologie Totaal

Met BSL Psychologie Totaal blijft u als professional steeds op de hoogte van de nieuwste ontwikkelingen binnen uw vak. Met het online abonnement heeft u toegang tot een groot aantal boeken, protocollen, vaktijdschriften en e-learnings op het gebied van psychologie en psychiatrie. Zo kunt u op uw gemak en wanneer het u het beste uitkomt verdiepen in uw vakgebied.

Over dit artikel

Andere artikelen Uitgave 2/2019

Journal of Behavioral Medicine 2/2019 Naar de uitgave