schema: an open-source, distributed mobile platform for deploying mHealth research tools and interventions
Shatte, Adrian B.R., and Teague, Samantha J. (2020) schema: an open-source, distributed mobile platform for deploying mHealth research tools and interventions. BMC Medical Research Methodology, 20. 91.
|
PDF (Published Version)
- Published Version
Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
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.
| Item ID: | 73666 |
|---|---|
| Item Type: | Article (Research - C1) |
| ISSN: | 1471-2288 |
| Copyright Information: | © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
| Date Deposited: | 09 Feb 2023 00:03 |
| FoR Codes: | 52 PSYCHOLOGY > 5201 Applied and developmental psychology > 520105 Psychological methodology, design and analysis @ 100% |
| SEO Codes: | 20 HEALTH > 2001 Clinical health > 200105 Treatment of human diseases and conditions @ 100% |
| Downloads: |
Total: 519 Last 12 Months: 6 |
| More Statistics |
Actions (Repository Staff Only)
 |
Item Control Page |