Perceptions of experts on key injury risk factors in alpine ski racing as a function of stakeholder role and associated level of competition

Abstract

Objectives(1) To update experts’ priorities of perceived key injury risk factors in alpine ski racing based on a framework and list derived 10 years ago, (2) to identify additionally emerging risk factors since then and (3) to compile a list with countermeasure suggestions.MethodsA sample of 532 expert stakeholders (athletes, coaches, team medical staff, Ski Racing Suppliers (SRS) and International Ski Federation (FIS) representatives) from the World Cup (WC), European Cup (EC) and FIS-race level participated in a cross-sectional online survey. Experts were asked to name those risk factors with the highest believed impact on injury risk and rank them according to their current priority from a predefined list. In addition, experts were encouraged to name additional (not listed) risk factors and to suggest countermeasures.ResultsRegardless of stakeholder role and competition level, snow-related factors appeared to have the highest perceived priority. However, WC athletes’ and coaches’ perceptions were also related to equipment, while at the EC and FIS-race level fatigue and physical fitness-related factors were considered important. Athletes’ perceptions were largely in agreement with SRS (ie, snow-related and equipment-related factors). At the same time, while coaches, team medical staff and FIS representatives additionally emphasised fatigue and physical fitness-related factors.ConclusionExperts’ perceptions on key injury risk factors in alpine ski racing depend on the stakeholder role and differ between the competition levels. Thus, to develop effective prevention measures and to successfully implement them, all relevant stakeholders should be given a voice, and prevention efforts should be targeted to the specific level.

We know a lot about little and little about a lot: A contextualized scoping review on injury prevention in alpine ski racing

“…Three authors (OBM, EV, and JS) elaborated a tailored table for data extraction from the included studies after agreement within the study team and based on relevant alpine skiing injury and conceptual papers. 1,4,13,[29][30][31][32][33] The data we extracted from the included full-text articles were (a…”

“…For instance, based on the current research on injury etiology, more than half of the studies investigated athlete-related risk factors, whereas only 10% covered snow-related factors. Conversely, Kiers et al 29 investigated and updated the stakeholders' priorities of perceived key injury risk factor categories in alpine ski racing based on a framework from Spörri et al 4 Hence, based on stakeholders' perspectives, the most important risk factor entailed snow conditions, and three more snowrelated aspects were rated within the top 10 features. 29 Additionally, equipment-and course setting-related aspects were rated on top of athlete-related factors, which include fatigue, physical aspects, and athletes' race preparation and crash behavior.…”

“…Conversely, Kiers et al 29 investigated and updated the stakeholders' priorities of perceived key injury risk factor categories in alpine ski racing based on a framework from Spörri et al 4 Hence, based on stakeholders' perspectives, the most important risk factor entailed snow conditions, and three more snowrelated aspects were rated within the top 10 features. 29 Additionally, equipment-and course setting-related aspects were rated on top of athlete-related factors, which include fatigue, physical aspects, and athletes' race preparation and crash behavior. Thus, the available literature on injury risk factors does not agree with what alpine ski racing stakeholders perceived as the highest priority among all risk factors.…”

“…Classification of the included studies into the Translating Research into Injury Prevention Practice (TRIPP) framework. Injury surveillance (n = 62) [1-3,5,8,9,18,19,40-94] Establish the etiology and mechanisms of injury (n = 72) [10,13,14,22,24,46,51,54,65,75,79,84,92,95-154] Develop preventive measures (n = 19) [20,100,110,124,133,135,138,155-165]Stage 4: "Ideal conditions"/scientific evaluation (n = 3)[18,163,166] Describe the intervention context to inform implementation strategies (n = 6)[21,29,[167][168][169][170] Stage 6: Evaluate the effectiveness of preventive measures in the implementation context (n = 3)[12,171,172] …”

Extracting decision models for ski injury prediction from data

“…For example, injuries such as knee injuries can lead to temporary or permanent movement disabilities, and sometimes injuries can be fatal (Bianchi et al., 2017). Papers from the ski injury research area (Ruedl et al., 2016; Posch et al., 2017; Faulhaber et al., 2020; Carus and Castillo, 2021; Kiers et al., 2021) try to identify risk factors and propose interventions to reduce the risk of injury. Usually, this is done using experience (or expert knowledge), which is often suboptimal due to a complex relationship between the slope properties, weather conditions, skiing behavior, etc.…”