SlipBuddy: A Mobile Health Intervention to Prevent Overeating

Tulu, Bengisu; Ruiz, Carolina; Allard, Joshua; Acheson, Joseph; Busch, Andrew M.; Roskuski, Andrew; Heeringa, Gage; Jaskula, Victor; Oleski, Jessica L.; Pagoto, Sherry L.

doi:10.24251/hicss.2017.436

Cited by 17 publications

(22 citation statements)

References 9 publications

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“…One study to date has utilized machine learning to predict overeating episodes with 71.3% accuracy based on self-reported data of 16 non-treatment-seeking adults with overweight/obesity. 7 The current project sought to replicate and extend this prior work by evaluating an algorithm specifically targeting lapses from a weight loss diet among a treatment-seeking sample. Our methods are novel in that we investigate the utility of combining group- and individual-level data to efficiently generate real-time lapse predictions.…”

mentioning

confidence: 94%

Application of Machine Learning to Predict Dietary Lapses During Weight Loss

Goldstein

Zhang

Thomas

et al. 2018

J Diabetes Sci Technol

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mentioning

confidence: 94%

Application of Machine Learning to Predict Dietary Lapses During Weight Loss

Goldstein

Zhang

Thomas

et al. 2018

J Diabetes Sci Technol

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“…SlipBuddy was recently developed to inform overeaters of the distinct patterns in their overeating ( Tulu et al., 2017 ). For example, a special, individualized model was developed for one overeater who tended to overeat when she was tired.…”

Section: Discussionmentioning

confidence: 99%

Toward the prevention of alcohol use disorders: Overdrinking (unintentional binge drinking) in a community sample

Bishop

Orjuela

2018

Health Psychology Open

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Approximately 64,000,000 people in the United States report binge drinking at least once in the past month. Unlike overeating and oversleeping, “overdrinking”—defined as drinking more than a person intends to drink—does not exist in the literature. Terms such as binge and problem drinking do not consider the intent of the drinker. The results of this pilot study suggest that most people drink more than they intend to drink. Moreover, they also report often being surprised that they overdrank. Smartphones may help overdrinkers be less often surprised by overdrinking and may prevent drinkers from developing an alcohol use disorder.

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“…There is also mounting evidence that they are effective (Giroux et al, 2017;Haskins et al, 2017;Hester et al, 2005Hester et al, , 2009. Recently, Tulu et al (2017) reported on the effectiveness of an app for overeating. Thomas et al (2011) also reported that 6 months of weekly email contacts plus monthly weight reports from the participants helped speed up weight loss and maintain it.…”

Section: Primary Maintenance Strategiesmentioning

confidence: 99%

Self-guided Change: The most common form of long-term, maintained health behavior change

Bishop

2018

Health Psychology Open

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Millions of people change risky, health-related behaviors and maintain those changes. However, they often take years to change, and their unhealthy behaviors may harm themselves and others and constitute a significant cost to society. A review—similar in nature to a scoping review—was done of the literature related to long-term health behavior change in six areas: alcohol, cocaine and heroin misuse, gambling, smoking, and overeating. Based on the limited research available, reasons for change and strategies for changing and for maintaining change were also reviewed. Fifty years of research clearly indicate that as people age, in the case of alcohol, heroin and cocaine misuse, smoking, and gambling, 80–90 percent moderate or stop their unhealthy behaviors. The one exception is overeating; only 20 percent maintain their weight loss. Most of these changes, when they occur, appear to be the result of self-guided change. More ways to accelerate self-guided, health-related behavior change need to be developed and disseminated.

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SlipBuddy: A Mobile Health Intervention to Prevent Overeating

Abstract: Obesity is one of the top health issues around the

Cited by 17 publications

References 9 publications

Application of Machine Learning to Predict Dietary Lapses During Weight Loss

Application of Machine Learning to Predict Dietary Lapses During Weight Loss

Toward the prevention of alcohol use disorders: Overdrinking (unintentional binge drinking) in a community sample

Self-guided Change: The most common form of long-term, maintained health behavior change

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