Methods matter and the ‘too much, too soon’ theory (part 2): what is the goal of your sports injury research? Are you describing, predicting or drawing a causal inference?
Rasmus Oestergaard Nielsen, Nina Sjoerup Simonsen, Martí Casals, Emmanuel Stamatakis, Mohammad Alì Mansournia
Abstract
Imagine a sports injury researcher who gets a bright idea in relation to the ‘too much, too soon’ theory (too much training, too soon, leads to injury).1 Then, the researcher proposes the following aim: to examine the association between workload and sports injury. Think twice: Does the word ‘association’ truly assist you, the reader, in understanding the underlying goal? Every researcher should be clear on the goal of their research. The goal should be immediately clear to the intended readers. Failure to be clear about goals may lead to inappropriate, misleading and flawed conclusions.2 Hernan, an expert epidemiologist, declared in 2018 that ‘…being explicit about the goal of the analysis is a prerequisite for good science ’ ,3 since being explicit about the objective of a study reduces ambiguity in the scientific question, errors in the data analysis, and excesses in the interpretation of the results. Possibly, using the term ‘association’ (above) is ambiguous as we are unaware of the underlying goal. Although definitions may vary depending on the source,4 5 research into sports injury usually has one of three goals: To describe, to predict or to explain. To describe, for example, how athletes train and/or how many athletes sustains sports injury over time (eg, injury risk), without investigating their relationship. In contrast to describing, researchers can also examine relationships, or so-called associations, which can have two vastly different goals: to predict groups at risk of sustaining sport injury (here referred to as predicting) or to explain why some athletes sustain workload-related injury (here referred to as causal inference). In the first educational piece in this ‘too much, too soon’ series,6 we provided readers with examples of causal research questions, described analytical concepts and outlined the main differences between population-based prevention and personalised prevention. This …