Information about project titled 'ostRc: a toolbox for handling self-reported injury data'
ostRc: a toolbox for handling self-reported injury data
| Details about the project - category | Details about the project - value |
|---|---|
| Project status: | Ongoing |
| Project manager: | Lena Kristin Bache-Mathiesen |
| Coworker(s): | Ben Clarsen |
Description
Background: Overuse injuries are common in many sports. Such injuries have a gradual onset, unlike acute injuries. They are identified through symptoms of pain and stiffness, and in many cases, the athlete can still perform their sport even though they have an overuse injury. Therefore, it is common to collect data on overuse injuries through self-reported questionnaires.
Self-reported data have a different structure than data from a classic injury surveillance system. They can be cumbersome to work with, and difficult to arrange in the manner needed to ensure correct estimates of incidence, prevalence and burden. This can lead to errors in such estimates.
Aims: Develop an R-package which makes it easier to calculate incidence, prevalence and burden on self-reported data, and ensure these calculations are correct.
Methods: We develop an R-package through Test-Driven Development (TTD). Tests are developed before functions. The package is documented continuously. The code will be available and version-controlled at all times during development. The package will be tested on several sources of real self-reported injury data. It will also be user-tested by users who have not been part of developing the package. At launch, the package will be disseminated through social media, articles, reports and workshops at conferences.
Implications: Studies on self-reported injuries will be conducted faster, and report incidence, prevalence and burden estimates based on best-practice calculations.