How (not) to interpret a non-causal association in sports injury science

The "impacts cause injury" hypothesis: Running in circles or making new strides?

Some of the earliest biomechanics research focused on running and the ground reaction forces generated with each step. Research in running gait accelerated in the 1970's as the growing popularity in running increased attention to the musculoskeletal injuries sustained by runners. Despite decades of high-quality research, running remains the most common cause of exercise-related musculoskeletal injuries and rates of overuse running-related injuries (RRI) have not appreciably declined since the research began. One leading area of running gait research focuses on discrete variables derived from the vertical ground reaction force, such as the vertical loading rate. Across sub-disciplines of running gait research, vertical loading rate is often discussed as the primary and undisputed variable associated with RRI despite only low to moderate evidence that retrospectively or prospectively injured runners generate greater vertical loading rates than uninjured counterparts. The central thesis of this review is that relying on vertical loading rate is insufficient to establish causal mechanisms for RRI etiology. To present this argument, this review examines the history of the 'impacts cause injury' hypothesis, including a historical look at ground reaction forces in human running and the research from which this hypothesis was generated. Additionally, a synthesis of studies that have tested the hypothesis is provided and recommendations for future research are discussed. Although it is premature to reject or support the 'impacts cause injury' hypothesis, new knowledge of biomechanical risk factors for RRI will remain concealed until research departs from the current path or adopts new approaches to previous paradigms.

Biomechanical and Musculoskeletal Measurements as Risk Factors for Running-Related Injury in Non-elite Runners: A Systematic Review and Meta-analysis of Prospective Studies

BACKGROUND

Running-related injury (RRI) is highly prevalent among recreational runners and is a key barrier to participation. Atypical lower limb alignment and mechanical function have been proposed to play a role in development of lower extremity injury. The purpose of this study was to investigate relationships between incidence of running-related injury (RRI) in non-elite runners with biomechanical and musculoskeletal variables.

METHODS

A systematic review and meta-analysis of prospective studies. Published research indexed in MEDLINE, EMBASE, CINAHL, SPORTDiscus, AMED, and The Cochrane library until 13th January 2021, grey literature, and reference lists of included studies were screened to identify prospective studies of non-elite adult runners that measured a relationship between biomechanical or musculoskeletal measures and incidence of RRI.

RESULTS

Thirty studies (3404 runners), testing over 100 discrete biomechanical and musculoskeletal risk factors for RRI, were included. Nineteen studies were pooled in twenty-five separate meta-analyses. Meta-analysis of four studies detected significantly less knee extension strength among runners who developed a RRI (SMD - 0.19, 95% CI - 0.36 to - 0.02, p = 0.03), though this may not be clinically important. A meta-analysis of two studies detected significantly lower hip adduction velocity among runners who developed a RRI (MD - 12.80, 95% CI - 25.22 to - 0.38, p = 0.04). Remaining meta-analyses found no significant relationship between biomechanical or musculoskeletal variables and RRI.

CONCLUSION

This systematic review and meta-analysis found the currently available literature does not generally support biomechanical or musculoskeletal measures as risk factors for RRI in non-elite runners. While meta-analysis findings for knee extension strength and hip adduction velocity as risk factors for RRI were statistically significant, the associated trivial to small effects sizes suggest these findings should be treated with caution. Until further evidence emerges, recommendations for injury prevention in non-elite runners cannot be made based on biomechanical and musculoskeletal measurements alone.

Training Load and Injury Part 2: Questionable Research Practices Hijack the Truth and Mislead Well-Intentioned Clinicians

BACKGROUND

In this clinical commentary, we highlight issues related to conceptual foundations and methods used in training load and injury research. We focus on sources of degrees of freedom that can favor questionable research practices such as P hacking and hypothesizing after the results are known, which can undermine the trustworthiness of research findings.

CLINICAL QUESTION

Is the methodological rigor of studies in the training load and injury field sufficient to inform training-related decisions in clinical practice?

KEY RESULTS

The absence of a clear conceptual framework, causal structure, and reliable methods can promote questionable research practices, selective reporting, and confirmation bias. The fact that well-accepted training principles (eg, overload progression) are in line with some study findings may simply be a consequence of confirmation bias, resulting from cherry picking and emphasizing results that align with popular beliefs. Identifying evidence-based practical applications, grounded in high-quality research, is not currently possible. The strongest recommendation we can make for the clinician is grounded in common sense: "Do not train too much, too soon"-not because it has been confirmed by studies, but because it reflects accepted generic training principles.

CLINICAL APPLICATION

The training load and injury research field has fundamental conceptual and methodological weaknesses. Therefore, making decisions about planning and modifying training programs for injury reduction in clinical practice, based on available studies, is premature. Clinicians should continue to rely on best practice, experience, and well-known training principles, and consider the potential influence of contextual factors when planning and monitoring training loads. J Orthop Sports Phys Ther 2020;50(10):577-584. Epub 1 Aug 2020. doi:10.2519/jospt.2020.9211.

Statement on methods in sport injury research from the 1st METHODS MATTER Meeting, Copenhagen, 2019

High quality sports injury research can facilitate sports injury prevention and treatment. There is scope to improve how our field applies best practice methods—methods matter (greatly!). The 1st METHODS MATTER Meeting, held in January 2019 in Copenhagen, Denmark, was the forum for an international group of researchers with expertise in research methods to discuss sports injury methods. We discussed important epidemiological and statistical topics within the field of sports injury research. With this opinion document, we provide the main take-home messages that emerged from the meeting.

Statement on Methods in Sport Injury Research From the First METHODS MATTER Meeting, Copenhagen, 2019

High-quality sports injury research can facilitate sports injury prevention and treatment. There is scope to improve how our field applies best-practice methods-methods matter (greatly!). The first METHODS MATTER meeting, held in January 2019 in Copenhagen, Denmark, was the forum for an international group of researchers with expertise in research methods to discuss sports injury methods. We discussed important epidemiological and statistical topics within the field of sports injury research. With this opinion document, we provide the main take-home messages that emerged from the meeting. Meeting participants agreed that the definition of sport injury depends on the research question and context. It was considered essential to be explicit about the goal of the research effort and to use frameworks to illustrate the assumptions that underpin measurement and the analytical strategy. Complex systems were discussed to illustrate how potential risk factors can interact in a nonlinear way. This approach is often a useful alternative to identifying single risk factors. Investigating changes in exposure status over time is important when analyzing sport injury etiology, and analyzing recurrent injury, subsequent injury, or injury exacerbation remains challenging. The choice of statistical model should consider the research question, injury measure (eg, prevalence, incidence), type and granularity of injury data (categorical or continuous), and study design. Multidisciplinary collaboration will be a cornerstone for future high-quality sport injury research. Working outside professional silos in a diverse, multidisciplinary team benefits the research process, from the formulation of research questions and designs to the statistical analyses and dissemination of study results in implementation contexts. This article has been copublished in the British Journal of Sports Medicine and the Journal of Orthopaedic & Sports Physical Therapy. J Orthop Sports Phys Ther 2020;50(5):226-233. doi:10.2519/jospt.2020.9876.