e-space
Manchester Metropolitan University's Research Repository

    Editorial: Methods matter: Clinical prediction models will benefit sports medicine practice, but only if they are properly developed and validated

    Bullock, GS, Hughes, T, Sergeant, JC, Callaghan, MJ ORCID logoORCID: https://orcid.org/0000-0003-3540-2838, Riley, R and Collins, G (2021) Editorial: Methods matter: Clinical prediction models will benefit sports medicine practice, but only if they are properly developed and validated. British Journal of Sports Medicine, 55 (23). pp. 1319-1321. ISSN 0306-3674

    [img]
    Preview
    Accepted Version
    Available under License Creative Commons Attribution Non-commercial.

    Download (219kB) | Preview

    Abstract

    Sports medicine clinicians are expected to make accurate diagnoses, estimate prognoses and identify athletes at risk of sustaining an injury. These complex decisions are dependent on clinical reasoning, which is informed by, and often biased toward, a practitioner’s scientific knowledge and experience. Clinical prediction models are developed by researchers to help facilitate such decisions in practice; data for multiple predictor variables are combined to estimate an individual’s risk of a health outcome either being present (diagnosis) or whether it will occur in future (prognosis). Despite being employed widely in clinical medicine, clinical prediction models are uncommon in sports medicine. Clinical prediction models can offer benefits to both practitioners and athletes, but only if they are developed and validated using rigorous methods and transparently reported so that potential users can judge their accuracy and usefulness. Therefore, the purpose of this editorial is to describe the recommended steps for clinical prediction development and validation and to guide practitioners using and interpreting prediction models in sports medicine.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    72Downloads
    6 month trend
    31Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Repository staff only

    Edit record Edit record