Schema : an open-source, distributed mobile platform for deploying mHealth research tools and interventions
- Shatte, Adrian, Teague, Samantha
- Authors: Shatte, Adrian , Teague, Samantha
- Date: 2020
- Type: Text , Journal article
- Relation: BMC Medical Research Methodology Vol. 20, no. 1 (2020), p.
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- Description: Background: Mobile applications for health, also known as 'mHealth apps', have experienced increasing popularity over the past ten years. However, most publicly available mHealth apps are not clinically validated, and many do not utilise evidence-based strategies. Health researchers wishing to develop and evaluate mHealth apps may be impeded by cost and technical skillset barriers. As traditionally lab-based methods are translated onto mobile platforms, robust and accessible tools are needed to enable the development of quality, evidence-based programs by clinical experts. Results: This paper introduces schema, an open-source, distributed, app-based platform for researchers to deploy behavior monitoring and health interventions onto mobile devices. The architecture and design features of the platform are discussed, including flexible scheduling, randomisation, a wide variety of survey and media elements, and distributed storage of data. The platform supports a range of research designs, including cross-sectional surveys, ecological momentary assessment, randomised controlled trials, and micro-randomised just-in-time adaptive interventions. Use cases for both researchers and participants are considered to demonstrate the flexibility and usefulness of the platform for mHealth research. Conclusions: The paper concludes by considering the strengths and limitations of the platform, and a call for support from the research community in areas of technical development and evaluation. To get started with schema, please visit the GitHub repository: Https://github.com/schema-app/schema. © 2020 The Author(s).
- Authors: Shatte, Adrian , Teague, Samantha
- Date: 2020
- Type: Text , Journal article
- Relation: BMC Medical Research Methodology Vol. 20, no. 1 (2020), p.
- Full Text:
- Reviewed:
- Description: Background: Mobile applications for health, also known as 'mHealth apps', have experienced increasing popularity over the past ten years. However, most publicly available mHealth apps are not clinically validated, and many do not utilise evidence-based strategies. Health researchers wishing to develop and evaluate mHealth apps may be impeded by cost and technical skillset barriers. As traditionally lab-based methods are translated onto mobile platforms, robust and accessible tools are needed to enable the development of quality, evidence-based programs by clinical experts. Results: This paper introduces schema, an open-source, distributed, app-based platform for researchers to deploy behavior monitoring and health interventions onto mobile devices. The architecture and design features of the platform are discussed, including flexible scheduling, randomisation, a wide variety of survey and media elements, and distributed storage of data. The platform supports a range of research designs, including cross-sectional surveys, ecological momentary assessment, randomised controlled trials, and micro-randomised just-in-time adaptive interventions. Use cases for both researchers and participants are considered to demonstrate the flexibility and usefulness of the platform for mHealth research. Conclusions: The paper concludes by considering the strengths and limitations of the platform, and a call for support from the research community in areas of technical development and evaluation. To get started with schema, please visit the GitHub repository: Https://github.com/schema-app/schema. © 2020 The Author(s).
Optimizing prediction of binge eating episodes : A comparison approach to test alternative conceptualizations of the affect regulation model
- Fuller-Tyszkiewicz, Matthew, Richardson, Ben, Skouteris, Helen, Austin, David, Castle, David, Busija, Lucy, Klein, Britt, Holmes, Milllicent, Broadbent, Jaclyn
- Authors: Fuller-Tyszkiewicz, Matthew , Richardson, Ben , Skouteris, Helen , Austin, David , Castle, David , Busija, Lucy , Klein, Britt , Holmes, Milllicent , Broadbent, Jaclyn
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Eating Disorders Vol. 2, no. 1 (2014), p. 1-8
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- Description: Background: Although a wealth of studies have tested the link between negative mood states and likelihood of a subsequent binge eating episode, the assumption that this relationship follows a typical linear dose-response pattern (i.e., that risk of a binge episode increases in proportion to level of negative mood) has not been challenged. The present study demonstrates the applicability of an alternative, non-linear conceptualization of this relationship, in which the strength of association between negative mood and probability of a binge episode increases above a threshold value for the mood variable relative to the slope below this threshold value (threshold dose response model).Methods: A sample of 93 women aged 18 to 40 completed an online survey at random intervals seven times per day for a period of one week. Participants self-reported their current mood state and whether they had recently engaged in an eating episode symptomatic of a binge.Results: As hypothesized, the threshold approach was a better predictor than the linear dose-response modeling of likelihood of a binge episode. The superiority of the threshold approach was found even at low levels of negative mood (3 out of 10, with higher scores reflecting more negative mood). Additionally, severity of negative mood beyond this threshold value appears to be useful for predicting time to onset of a binge episode.Conclusions: Present findings suggest that simple dose-response formulations for the association between negative mood and onset of binge episodes miss vital aspects of this relationship. Most notably, the impact of mood on binge eating appears to depend on whether a threshold value of negative mood has been breached, and elevation in mood beyond this point may be useful for clinicians and researchers to identify time to onset. © 2014 Fuller-Tyszkiewicz et al.; licensee BioMed Central Ltd.
- Authors: Fuller-Tyszkiewicz, Matthew , Richardson, Ben , Skouteris, Helen , Austin, David , Castle, David , Busija, Lucy , Klein, Britt , Holmes, Milllicent , Broadbent, Jaclyn
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Eating Disorders Vol. 2, no. 1 (2014), p. 1-8
- Full Text:
- Reviewed:
- Description: Background: Although a wealth of studies have tested the link between negative mood states and likelihood of a subsequent binge eating episode, the assumption that this relationship follows a typical linear dose-response pattern (i.e., that risk of a binge episode increases in proportion to level of negative mood) has not been challenged. The present study demonstrates the applicability of an alternative, non-linear conceptualization of this relationship, in which the strength of association between negative mood and probability of a binge episode increases above a threshold value for the mood variable relative to the slope below this threshold value (threshold dose response model).Methods: A sample of 93 women aged 18 to 40 completed an online survey at random intervals seven times per day for a period of one week. Participants self-reported their current mood state and whether they had recently engaged in an eating episode symptomatic of a binge.Results: As hypothesized, the threshold approach was a better predictor than the linear dose-response modeling of likelihood of a binge episode. The superiority of the threshold approach was found even at low levels of negative mood (3 out of 10, with higher scores reflecting more negative mood). Additionally, severity of negative mood beyond this threshold value appears to be useful for predicting time to onset of a binge episode.Conclusions: Present findings suggest that simple dose-response formulations for the association between negative mood and onset of binge episodes miss vital aspects of this relationship. Most notably, the impact of mood on binge eating appears to depend on whether a threshold value of negative mood has been breached, and elevation in mood beyond this point may be useful for clinicians and researchers to identify time to onset. © 2014 Fuller-Tyszkiewicz et al.; licensee BioMed Central Ltd.
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