A Systems Analysis Critique of Sport-Science Research

Where do we intervene to optimize sports systems? Leverage Points the way

Sport and sports research are inherently complex systems. This appears to be somewhat at odds with the current research paradigm in sport in which interventions are aimed are fixing or solving singular broken components within the system. In any complex system, such as sport, there are places where we can intervene to change behaviour and, ideally, system outcomes. Meadows influential work describes 12 different points with which to intervene in complex systems (termed "Leverage Points"), which are ordered from shallow to deeper based on their potential effectiveness to influence transformational change. Whether research in sport is aimed at shallow or deeper Leverage Points is unknown. This study aimed to assess highly impactful research in sports science, sports nutrition/metabolism, sports medicine, sport and exercise psychology, sports management, motor control, sports biomechanics and sports policy/law through a Leverage Points lens. The 10 most highly cited original-research manuscripts from each journal representing these fields were analysed for the Leverage Point with which the intervention described in the manuscript was focused. The results indicate that highly impactful research in sports science, sports nutrition/metabolism, sports biomechanics and sports medicine is predominantly focused at the shallow end of the Leverage Points hierarchy. Conversely, the interventions drawn from journals representing sports management and sports policy/law were focused on the deeper end. Other journals analysed had a mixed profile. Explanations for these findings include the dual practitioner/academic needing to "think fast" to solve immediate questions in sports science/medicine/nutrition, limited engagement with "working slow" systems and method experts and differences in incremental vs. non-incremental research strategies.

The top sports medicine influencers on X (formerly Twitter)

BACKGROUND

With increasing sports medicine content on social media, we sought to identify the top sports medicine influencers on X (formerly Twitter) and analyse their common characteristics.

METHODS

X influence scores for "Sports Medicine" were collected in November 2021 from Right Relevance. Accounts were then screened in a blind, duplicate manner for personal and X profile characteristics.

RESULTS

Physical therapists/physiotherapists made up 48% of the top sports science and medicine influencers. Locations in the U.S. and U.K. were listed for half of the influencers. The mean h-index was 30.2 (95% CI = [24.8-35.6]) with a median of 22.0 (range = 1-101). Most individuals reported multiple practice settings (63%), with 60% associated with an academic setting. Professional (62%) and Olympic (49%) level athletics were most frequently mentioned, with soccer (48%) and rugby (30%) as the most common sports. Among 76 profiles with URLs, most were linked to personal websites (57.9%).

CONCLUSION

The top influencers on X consisted of accredited sports science and medicine professionals across various locations and occupations, providing ample networking and collaboration opportunities. The relatively high h-index in this study suggests sports science and medicine influencers on X are notable contributors to academic literature.

Using human factors and ergonomics methods to challenge the status quo: Designing for gender equitable research outcomes

There have been recent calls for Human Factors and Ergonomics (HFE) to expand its reach and focus to address larger scale societal and global issues. An area of growing awareness is the issue of the gender data gap, whereby women are under-represented in research data, leading to inequitable outcomes when research findings are used to design real world technologies, products, environments, processes, and policies. The aim of this paper is to showcase how structured HFE methods can be used to address the gender data gap. We applied the Sociotechnical Systems Design Toolkit which involved using causal loop diagrams and abstraction hierarchy modelling from Cognitive Work Analysis to understand the system in which the issue occurs and key pain points, followed by the application of the Design with Intent Toolkit to generate design ideas. A total of 43 ideas were developed that could be implemented by universities to address the research data gap. The application demonstrates the utility of HFE methods in tackling complex issues and offers an opportunity for the HFE community to reflect upon the importance of gender sensitive research practices and gender equity more broadly.