Injury and illness surveillance, and epidemiological studies, are fundamental elements of concerted efforts to protect the health of the athlete. To encourage consistency in the definitions and methodology used, and to enable data across studies to be compared, research groups have published 11 sport-specific or setting-specific consensus statements on sports injury (and, eventually, illness) epidemiology to date. Our objective was to further strengthen consistency in data collection, injury definitions and research reporting through an updated set of recommendations for sports injury and illness studies, including a new Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist extension. The IOC invited a working group of international experts to review relevant literature and provide recommendations. The procedure included an open online survey, several stages of text drafting and consultation by working groups and a 3-day consensus meeting in October 2019. This statement includes recommendations for data collection and research reporting covering key components: defining and classifying health problems; severity of health problems; capturing and reporting athlete exposure; expressing risk; burden of health problems; study population characteristics and data collection methods. Based on these, we also developed a new reporting guideline as a STROBE Extension—the STROBE Sports Injury and Illness Surveillance (STROBE-SIIS). The IOC encourages ongoing in- and out-of-competition surveillance programmes and studies to describe injury and illness trends and patterns, understand their causes and develop measures to protect the health of the athlete. Implementation of the methods outlined in this statement will advance consistency in data collection and research reporting.

Background One common model utilized to understand clinical staff and patients' technology adoption is the technology acceptance model (TAM). Objective This article reviews published research on TAM use in health information systems development and implementation with regard to application areas and model extensions after its initial introduction. Method An electronic literature search supplemented by citation searching was conducted on February 2017 of the Web of Science, PubMed, and Scopus databases, yielding a total of 492 references. Upon eliminating duplicates and applying inclusion and exclusion criteria, 134 articles were retained. These articles were appraised and divided into three categories according to research topic: studies using the original TAM, studies using an extended TAM, and acceptance model comparisons including the TAM. Results The review identified three main information and communication technology (ICT) application areas for the TAM in health services: telemedicine, electronic health records, and mobile applications. The original TAM was found to have been extended to fit dynamic health service environments by integration of components from theoretical frameworks such as the theory of planned behavior and unified theory of acceptance and use of technology, as well as by adding variables in specific contextual settings. These variables frequently reflected the concepts subjective norm and self-efficacy, but also compatibility, experience, training, anxiety, habit, and facilitators were considered. Conclusion Telemedicine applications were between 1999 and 2017, the ICT application area most frequently studied using the TAM, implying that acceptance of this technology was a major challenge when exploiting ICT to develop health service organizations during this period. A majority of the reviewed articles reported extensions of the original TAM, suggesting that no optimal TAM version for use in health services has been established. Although the review results indicate a continuous progress, there are still areas that can be expanded and improved to increase the predictive performance of the TAM.

Background Movement towards sport safety in Athletics through the introduction of preventive strategies requires consensus on definitions and methods for reporting epidemiological data in the various populations of athletes. Objective To define health-related incidents (injuries and illnesses) that should be recorded in epidemiological studies in Athletics, and the criteria for recording their nature, cause and severity, as well as standards for data collection and analysis procedures. Methods A 1-day meeting of 14 experts from eight countries representing a range of Athletics stakeholders and sport science researchers was facilitated. Definitions of injuries and illnesses, study design and data collection for epidemiological studies in Athletics were discussed during the meeting. Two members of the group produced a draft statement after this meeting, and distributed to the group members for their input. A revision was prepared, and the procedure was repeated to finalise the consensus statement. Results Definitions of injuries and illnesses and categories for recording of their nature, cause and severity were provided. Essential baseline information was listed. Guidelines on the recording of exposure data during competition and training and the calculation of prevalence and incidences were given. Finally, methodological guidance for consistent recording and reporting on injury and illness in athletics was described. Conclusions This consensus statement provides definitions and methodological guidance for epidemiological studies in Athletics. Consistent use of the definitions and methodological guidance would lead to more reliable and comparable evidence.

Objective:To compare injury risk in elite football played on artificial turf compared with natural grass.Design:Prospective two-cohort study.Setting:Male European elite football leagues.Participants:290 players from 10 elite European clubs that had installed third-generation artificial turf surfaces in 2003–4, and 202 players from the Swedish Premier League acting as a control group.Main outcome measure:Injury incidence.Results:The incidence of injury during training and match play did not differ between surfaces for the teams in the artificial turf cohort: 2.42v2.94 injuries/1000 training hours and 19.60v21.48 injuries/1000 match hours for artificial turf and grass respectively. The risk of ankle sprain was increased in matches on artificial turf compared with grass (4.83v2.66 injuries/1000 match hours; rate ratio 1.81, 95% confidence interval 1.00 to 3.28). No difference in injury severity was seen between surfaces. Compared with the control cohort who played home games on natural grass, teams in the artificial turf cohort had a lower injury incidence during match play (15.26v23.08 injuries/1000 match hours; rate ratio 0.66, 95% confidence interval 0.48 to 0.91).Conclusions:No evidence of a greater risk of injury was found when football was played on artificial turf compared with natural grass. The higher incidence of ankle sprain on artificial turf warrants further attention, although this result should be interpreted with caution as the number of ankle sprains was low.

Objective To estimate the incidence, type and severity of musculoskeletal injuries in youth and adult elite athletics athletes and to explore risk factors for sustaining injuries. Design Prospective cohort study conducted during a 52-week period. Setting Male and female youth and adult athletics athletes ranked in the top 10 in Sweden (n=292). Results 199 (68%) athletes reported an injury during the study season. Ninety-six per cent of the reported injuries were non-traumatic (associated with overuse). Most injuries (51%) were severe, causing a period of absence from normal training exceeding 3 weeks. Log-rank tests revealed risk differences with regard to athlete category (p=0.046), recent previous injury (>3 weeks time-loss; p=0.039) and training load rank index (TLRI; p=0.019). Cox proportional hazards regression analyses showed that athletes in the third (HR 1.79; 95% CI 1.54 to 2.78) and fourth TLRI quartiles (HR 1.79; 95% CI 1.16 to 2.74) had almost a twofold increased risk of injury compared with their peers in the first quartile and interaction effects between athlete category and previous injury; youth male athletes with a previous serious injury had more than a fourfold increased risk of injury (HR=4.39; 95% CI 2.20 to 8.77) compared with youth females with no previous injury. Conclusions The injury incidence among both youth and adult elite athletics athletes is high. A training load index combing hours and intensity and a history of severe injury the previous year were predictors for injury. Further studies on measures to quantify training content and protocols for safe return to athletics are warranted.

Background: Traditional obesity prevention programs are time- and cost-intensive. Mobile phone technology has been successful in changing behaviors and managing weight; however, to our knowledge, its potential in young children has yet to be examined.