OnTrack: development and feasibility of a smartphone app designed to predict and prevent dietary lapses. Issue 2 (29th March 2018)
- Record Type:
- Journal Article
- Title:
- OnTrack: development and feasibility of a smartphone app designed to predict and prevent dietary lapses. Issue 2 (29th March 2018)
- Main Title:
- OnTrack: development and feasibility of a smartphone app designed to predict and prevent dietary lapses
- Authors:
- Forman, Evan M
Goldstein, Stephanie P
Zhang, Fengqing
Evans, Brittney C
Manasse, Stephanie M
Butryn, Meghan L
Juarascio, Adrienne S
Abichandani, Pramod
Martin, Gerald J
Foster, Gary D - Abstract:
- Abstract : A new type of smartphone app-based intervention is able to provide in-the-moment suggestions to prevent dietary lapses and to facilitate weight loss. Abstract: Given that the overarching goal of weight loss programs is to remain adherent to a dietary prescription, specific moments of nonadherence known as "dietary lapses" can threaten weight control via the excess energy intake they represent and by provoking future lapses. Just-in-time adaptive interventions could be particularly useful in preventing dietary lapses because they use real-time data to generate interventions that are tailored and delivered at a moment computed to be of high risk for a lapse. To this end, we developed a smartphone application (app) called OnTrack that utilizes machine learning to predict dietary lapses and deliver a targeted intervention designed to prevent the lapse from occurring. This study evaluated the feasibility, acceptability, and preliminary effectiveness of OnTrack among weight loss program participants. An open trial was conducted to investigate subjective satisfaction, objective usage, algorithm performance, and changes in lapse frequency and weight loss among individuals ( N = 43; 86% female; body mass index = 35.6 kg/m 2 ) attempting to follow a structured online weight management plan for 8 weeks. Participants were adherent with app prompts to submit data, engaged with interventions, and reported high levels of satisfaction. Over the course of the study, participantsAbstract : A new type of smartphone app-based intervention is able to provide in-the-moment suggestions to prevent dietary lapses and to facilitate weight loss. Abstract: Given that the overarching goal of weight loss programs is to remain adherent to a dietary prescription, specific moments of nonadherence known as "dietary lapses" can threaten weight control via the excess energy intake they represent and by provoking future lapses. Just-in-time adaptive interventions could be particularly useful in preventing dietary lapses because they use real-time data to generate interventions that are tailored and delivered at a moment computed to be of high risk for a lapse. To this end, we developed a smartphone application (app) called OnTrack that utilizes machine learning to predict dietary lapses and deliver a targeted intervention designed to prevent the lapse from occurring. This study evaluated the feasibility, acceptability, and preliminary effectiveness of OnTrack among weight loss program participants. An open trial was conducted to investigate subjective satisfaction, objective usage, algorithm performance, and changes in lapse frequency and weight loss among individuals ( N = 43; 86% female; body mass index = 35.6 kg/m 2 ) attempting to follow a structured online weight management plan for 8 weeks. Participants were adherent with app prompts to submit data, engaged with interventions, and reported high levels of satisfaction. Over the course of the study, participants averaged a 3.13% weight loss and experienced a reduction in unplanned lapses. OnTrack, the first Just-in-time adaptive intervention for dietary lapses was shown to be feasible and acceptable, and OnTrack users experienced weight loss and lapse reduction over the study period. These data provide the basis for further development and evaluation. … (more)
- Is Part Of:
- Translational behavioral medicine. Volume 9:Issue 2(2019)
- Journal:
- Translational behavioral medicine
- Issue:
- Volume 9:Issue 2(2019)
- Issue Display:
- Volume 9, Issue 2 (2019)
- Year:
- 2019
- Volume:
- 9
- Issue:
- 2
- Issue Sort Value:
- 2019-0009-0002-0000
- Page Start:
- 236
- Page End:
- 245
- Publication Date:
- 2018-03-29
- Subjects:
- Weight -- Lapses -- Smartphone app -- Diet -- Digital
Medicine and psychology -- Periodicals
616.0019 - Journal URLs:
- http://www.springerlink.com/content/1869-6716 ↗
http://www.springer.com/gb/ ↗ - DOI:
- 10.1093/tbm/iby016 ↗
- Languages:
- English
- ISSNs:
- 1869-6716
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9024.050000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16295.xml