Publication

Personalizable intervention systems to promote healthy behavior change

Igor Kulev
2020
EPFL thesis
Abstract

Adopting healthy behaviors can prevent the onset of many adverse health conditions. However, behavior changes are difficult to make, and often, people who like to improve their behaviors do not know how to do that. Personalizable intervention systems could assist them to achieve healthy behavior change. These systems decide what would be the optimal intervention for the target user based on his or her characteristics, including current and past behavior patterns. In this thesis, we propose novel solutions that address the main challenges in building a personalizable intervention system to promote healthy behavior change. First, we propose a system based on a Bayesian mixture model to identify subpopulations with different behavior changes from longitudinal data. This system is especially suitable when the amount of data is limited, and when there are unobserved factors that might affect behavior change. Second, we propose CLINT, a system based on a latent-variable model, to discover and predict behavior change patterns from fine-grained sensor data. The novelty of this system is that it produces interpretable patterns that could be used to suggest successful behavior change strategies from the existing users similar to the target user. Third, we propose a personalizable intervention system to improve the physical activeness of senior adults. The main novelty of this system is that it uses historical time series fitness data to decide which intervention to recommend. Finally, we propose ACFR, an adversarial approach to reduce intervention bias in observational data. This approach learns a balanced representation of the covariates that allows personalizable intervention systems to make a better estimate of the intervention effect. Our solutions turn existing human behavior data into actionable insights for future users who may have unhealthy lifestyles.

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Related concepts (35)
Behavior
Behavior (American English) or behaviour (British English) is the range of actions and mannerisms made by individuals, organisms, systems or artificial entities in some environment. These systems can include other systems or organisms as well as the inanimate physical environment. It is the computed response of the system or organism to various stimuli or inputs, whether internal or external, conscious or subconscious, overt or covert, and voluntary or involuntary.
Behavior modification
Behavior modification is an early approach that used respondent and operant conditioning to change behavior. Based on methodological behaviorism, overt behavior was modified with consequences, including positive and negative reinforcement contingencies to increase desirable behavior, or administering positive and negative punishment and/or extinction to reduce problematic behavior. It also used Flooding desensitization to combat phobias.
Applied behavior analysis
Applied behavior analysis (ABA), also called behavioral engineering, is a psychological intervention that applies empirical approaches based upon the principles of respondent and operant conditioning to change behavior of social significance. It is the applied form of behavior analysis; the other two forms are radical behaviorism (or the philosophy of the science) and the experimental analysis of behavior (or basic experimental laboratory research).
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