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Citation
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Soomro N, Chhaya M, Soomro M, Asif N, Saurman E, Lyle D, Sanders R. JMIR Mhealth Uhealth 2019; 7(1): e10978. |
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Affiliation
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Discipline of Exercise and Sport Science, Faculty of Health Sciences, The University of Sydney, Lidcombe, Australia. |
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Abstract
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BACKGROUND: Injury surveillance and workload monitoring are important aspects of professional sports, including cricket. However, at the community level, there is a dearth of accessible and intelligent surveillance tools. Mobile apps are an accessible tool for monitoring cricket-related injuries at all levels.
OBJECTIVE: The objective of this paper is to share the novel methods associated with the development of the free TeamDoc app and provide evidence from an evaluation of the user experience and perception of the app regarding its functionality, utility, and design.
METHODS: TeamDoc mobile app for Android and Apple smartphones was developed using 3 languages: C++, Qt Modeling Language, and JavaScript. For the server-side connectivity, Hypertext Preprocessor (PHP) was used as it is a commonly used cross-platform language. PHP includes components that interact with popular database management systems, allowing for secure interaction with databases on a server level. The app was evaluated by administrating a modified user version of the Mobile App Rating Scale (uMARS; maximum score: 5).
RESULTS: TeamDoc is the first complementary, standalone mobile app that records cricket injuries through a smartphone. It can also record cricketing workloads, which is a known risk factor for injury. The app can be used without the need for supplementary computer devices for synchronization. The uMARS scores showed user satisfaction (overall mean score 3.6 [SD 0.5]), which demonstrates its acceptability by cricketers.
CONCLUSIONS: Electronic injury surveillance systems have been shown to improve data collection during competitive sports. Therefore, TeamDoc may assist in improving injury reporting and may also act as a monitoring system for coaching staff to adjust individual training workloads. The methods described in this paper provide a template for researchers to develop similar apps for other sports.
©Najeebullah Soomro, Meraj Chhaya, Mariam Soomro, Naukhez Asif, Emily Saurman, David Lyle, Ross Sanders. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 22.01.2019.
Language: en |