People on weight loss plans often experience lapses, which can prevent successful weight loss or even lead to weight regain, according to the study published in the journal, 'Translational Behavioural Medicine'.
The study evaluated the effectiveness of the app among weight loss program participants, individuals attempting to follow a structured online weight management plan from WW (previously known as Weight Watchers) for eight weeks.
OnTrack uses advanced statistical methods -- machine learning -- to learn over time a user's individual patterns of eating. Specifically, it learns patterns that are predictive of staying on one's weight loss plan and patterns that are predictive of lapsing from one's plan.
When the algorithm detected the risk of lapsing is high, it sends a special coaching message that matches the reasons that someone is at risk. For example, the app can predict a person is eating late at night because of being bored at home with tempting food. The predictions got better over time as the app learns a user's behavioural patterns.
"This study is part of a line of research devoted to helping people become more adherent to a dietary prescription, which leads to more successful weight loss," said Forman.
Results showed the study was successful in three separate areas. First, participants reported high levels of satisfaction with the app. Second, OnTrack was successful at predicting lapse.
Finally, over the course of the study, participants averaged a 3.13 per cent weight loss and reduction in unplanned lapses.
Since the study was successful, the next step is a randomised clinical trial to confirm the app's efficacy as a weight-loss tool.
"Apps are particularly useful for predicting and preventing individual health behaviors. OnTrack could be utilized to facilitate greater success during self-directed weight loss attempts," said Forman.