Study design of 'Move More': Development and feasibility of a social-prescribing intervention to increase physical activity among inactive Danes.

AIM: This paper describes the design of the 'Move More' study, which aims to develop and assess the feasibility of a social-prescribing intervention to increase physical activity among physically inactive Danes. BACKGROUND: Physical inactivity constitutes a public-health challenge in Denmark. Social prescribing may be a promising tool to tackle physical inactivity by linking physical activity support from general practitioners with community-based activities in sports clubs, as this may help physically inactive citizens become more physically active. Given the range of stakeholders and behaviours required for social prescribing of physical activity, an intervention that harnesses this approach may constitute a complex intervention. The methods and decisions made in the stages of developing complex interventions are seldom reported. The present study enabled us to describe how co-creation can be used in a pragmatic development process for a complex intervention that considers the needs of stakeholders and the conditions of the delivery context. METHODS: The study is based on the core elements of the development and feasibility phases of the Medical Research Council Framework for Developing and Evaluating Complex Interventions. Additionally, it is informed by a framework for the co-creation and prototyping of public-health interventions, drawing from a scoping review, stakeholder consultations and co-creation workshops. Ultimately, a feasibility study will be conducted to refine the programme theory by introducing the proposed intervention in case studies. PERSPECTIVES: The study will result in a prototype intervention manual and recommendations for implementation of an adapted social-prescribing intervention targeting physical inactivity in Denmark.

A CHecklist for statistical Assessment of Medical Papers (the CHAMP statement): explanation and elaboration.

Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have expert knowledge of statistics or may be unconvinced about the importance of applying correct statistics in medical research. Although there are guidelines on reporting statistics in medical papers, a checklist on the more general and commonly seen aspects of statistics to assess when peer-reviewing an article is needed. In this article, we propose a CHecklist for statistical Assessment of Medical Papers (CHAMP) comprising 30 items related to the design and conduct, data analysis, reporting and presentation, and interpretation of a research paper. While CHAMP is primarily aimed at editors and peer reviewers during the statistical assessment of a medical paper, we believe it will serve as a useful reference to improve authors' and readers' practice in their use of statistics in medical research. We strongly encourage editors and peer reviewers to consult CHAMP when assessing manuscripts for potential publication. Authors also may apply CHAMP to ensure the validity of their statistical approach and reporting of medical research, and readers may consider using CHAMP to enhance their statistical assessment of a paper.

Methods matter: exploring the 'too much, too soon' theory, part 1: causal questions in sports injury research.

BACKGROUND: It is widely accepted that athletes sustain sports injury if they train 'too much, too soon'. However, not all athletes are built the same; some can tolerate more training than others. It is for this reason that prescribing the same training programme to all athletes to reduce injury risk is not optimal from a coaching perspective. Rather, athletes require individualised training plans. In acknowledgement of athlete diversity, it is therefore essential to ask the right causal research question in studies examining sports injury aetiology. PURPOSE: In this first part of a British Journal of Sports Medicine educational series, we present four different causal research questions related to the 'too much, too soon' theory and critically discuss their relevance to sports injury prevention. CONTENT: If it is true that there is no 'one size fits all' training programme, then we need to consider by how much training can vary depending on individual athlete characteristics. To provide an evidence-base for subgroup-specific recommendations, a stronger emphasis on the following questions is needed: (1) How much training is 'too much' before athletes with different characteristics sustain sports-related injury? and (2) Does the risk of sports injury differ among athletes with a certain characteristic (eg, high experience) compared with athletes with other characteristics (eg, low experience) depending on how much training they perform? CONCLUSION: We recommend that sports injury researchers aiming to examine the 'too much, too soon' theory should carefully consider how they, assisted by coaches, athletes and clinicians, pose their causal research question. In the light of the limitations of population-based prevention that intends to provide all athletes with the same advice, we argue that a stronger emphasis on research questions targeting subgroups of athletes is needed. In doing so, researchers may assist athletes, clinicians and coaches to understand what training advice/programme works best, for whom and under what circumstances.

Randomised controlled trials (RCTs) in sports injury research: authors-please report the compliance with the intervention.

BACKGROUND: In randomised controlled trials (RCTs) of interventions that aim to prevent sports injuries, the intention-to-treat principle is a recommended analysis method and one emphasised in the Consolidated Standards of Reporting Trials (CONSORT) statement that guides quality reporting of such trials. However, an important element of injury prevention trials-compliance with the intervention-is not always well-reported. The purpose of the present educational review was to describe the compliance during follow-up in eight large-scale sports injury trials and address compliance issues that surfaced. Then, we discuss how readers and researchers might consider interpreting results from intention-to-treat analyses depending on the observed compliance with the intervention. METHODS: Data from seven different randomised trials and one experimental study were included in the present educational review. In the trials that used training programme as an intervention, we defined full compliance as having completed the programme within ±10% of the prescribed running distance (ProjectRun21 (PR21), RUNCLEVER, Start 2 Run) or time-spent-running in minutes (Groningen Novice Running (GRONORUN)) for each planned training session. In the trials using running shoes as the intervention, full compliance was defined as wearing the prescribed running shoe in all running sessions the participants completed during follow-up. RESULTS: In the trials that used a running programme intervention, the number of participants who had been fully compliant was 0 of 839 (0%) at 24-week follow-up in RUNCLEVER, 0 of 612 (0%) at 14-week follow-up in PR21, 12 of 56 (21%) at 4-week follow-up in Start 2 Run and 8 of 532 (1%) at 8-week follow-up in GRONORUN. In the trials using a shoe-related intervention, the numbers of participants who had been fully compliant at the end of follow-up were 207 of 304 (68%) in the 21 week trial, and 322 of 423 (76%), 521 of 577 (90%), 753 of 874 (86%) after 24-week follow-up in the other three trials, respectively. CONCLUSION: The proportion of runners compliant at the end of follow-up ranged from 0% to 21% in the trials using running programme as intervention and from 68% to 90% in the trials using running shoes as intervention. We encourage sports injury researchers to carefully assess and report the compliance with intervention in their articles, use appropriate analytical approaches and take compliance into account when drawing study conclusions. In studies with low compliance, G-estimation may be a useful analytical tool provided certain assumptions are met.

Improved reporting of overuse injuries and health problems in sport: an update of the Oslo Sport Trauma Research Center questionnaires.

In 2013, the Oslo Sports Trauma Research Center Overuse Injury Questionnaire (OSTRC-O) was developed to record the magnitude, symptoms and consequences of overuse injuries in sport. Shortly afterwards, a modified version of the OSTRC-O was developed to capture all types of injuries and illnesses-The Oslo Sports Trauma Research Center Questionnaire on Health Problems (OSTRC-H). Since then, users from a range of research and clinical environments have identified areas in which these questionnaires may be improved. Therefore, the structure and content of the questionnaires was reviewed by an international panel consisting of the original developers, other user groups and experts in sports epidemiology and applied statistical methodology. Following a review panel meeting in October 2017, several changes were made to the questionnaires, including minor wording alterations, changes to the content of one question and the addition of questionnaire logic. In this paper, we present the updated versions of the questionnaires (OSTRC-O2 and OSTRC-H2), assess the likely impact of the updates on future data collection and discuss practical issues related to application of the questionnaires. We believe this update will improve respondent adherence and improve the quality of collected data.

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.

Towards a complex systems approach in sports injury research: simulating running-related injury development with agent-based modelling.

OBJECTIVES: There have been recent calls for the application of the complex systems approach in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. Therefore, our objective was to use a computational modelling method and develop a dynamic simulation in sports injury research. METHODS: Agent-based modelling (ABM) was used to model the occurrence of sports injury in a synthetic athlete population. The ABM was developed based on sports injury causal frameworks and was applied in the context of distance running-related injury (RRI). Using the acute:chronic workload ratio (ACWR), we simulated the dynamic relationship between changes in weekly running distance and RRI through the manipulation of various 'athlete management tools'. RESULTS: The findings confirmed that building weekly running distances over time, even within the reported ACWR 'sweet spot', will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a 'hard ceiling' dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads. CONCLUSIONS: The presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM and other simulation-based techniques could be considered as a complementary and alternative methodological approach in sports injury research.

Time-to-event analysis for sports injury research part 1: time-varying exposures.

BACKGROUND: 'How much change in training load is too much before injury is sustained, among different athletes?' is a key question in sports medicine and sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous injury, biomechanics, sleep/stress) when studying sports injury aetiology. AIM: To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and injury-related outcomes. CONTENT: Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills. CONCLUSION: To increase knowledge about the association between changes in training load and injury, we encourage sports injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective sports injury data. This will ensure appropriate interpretation of time-to-event data.

Time-to-event analysis for sports injury research part 2: time-varying outcomes.

BACKGROUND: Time-to-event modelling is underutilised in sports injury research. Still, sports injury researchers have been encouraged to consider time-to-event analyses as a powerful alternative to other statistical methods. Therefore, it is important to shed light on statistical approaches suitable for analysing training load related key-questions within the sports injury domain. CONTENT: In the present article, we illuminate: (i) the possibilities of including time-varying outcomes in time-to-event analyses, (ii) how to deal with a situation where different types of sports injuries are included in the analyses (ie, competing risks), and (iii) how to deal with the situation where multiple subsequent injuries occur in the same athlete. CONCLUSION: Time-to-event analyses can handle time-varying outcomes, competing risk and multiple subsequent injuries. Although powerful, time-to-event has important requirements: researchers are encouraged to carefully consider prior to any data collection that five injuries per exposure state or transition is needed to avoid conducting statistical analyses on time-to-event data leading to biased results. This requirement becomes particularly difficult to accommodate when a stratified analysis is required as the number of variables increases exponentially for each additional strata included. In future sports injury research, we need stratified analyses if the target of our research is to respond to the question: 'how much change in training load is too much before injury is sustained, among athletes with different characteristics?' Responding to this question using multiple time-varying exposures (and outcomes) requires millions of injuries. This should not be a barrier for future research, but collaborations across borders to collecting the amount of data needed seems to be an important step forward.

The design of the run Clever randomized trial: running volume, -intensity and running-related injuries.

BACKGROUND: Injury incidence and prevalence in running populations have been investigated and documented in several studies. However, knowledge about injury etiology and prevention is needed. Training errors in running are modifiable risk factors and people engaged in recreational running need evidence-based running schedules to minimize the risk of injury. The existing literature on running volume and running intensity and the development of injuries show conflicting results. This may be related to previously applied study designs, methods used to quantify the performed running and the statistical analysis of the collected data. The aim of the Run Clever trial is to investigate if a focus on running intensity compared with a focus on running volume in a running schedule influences the overall injury risk differently. METHODS/DESIGN: The Run Clever trial is a randomized trial with a 24-week follow-up. Healthy recreational runners between 18 and 65 years and with an average of 1-3 running sessions per week the past 6 months are included. Participants are randomized into two intervention groups: Running schedule-I and Schedule-V. Schedule-I emphasizes a progression in running intensity by increasing the weekly volume of running at a hard pace, while Schedule-V emphasizes a progression in running volume, by increasing the weekly overall volume. Data on the running performed is collected by GPS. Participants who sustain running-related injuries are diagnosed by a diagnostic team of physiotherapists using standardized diagnostic criteria. The members of the diagnostic team are blinded. The study design, procedures and informed consent were approved by the Ethics Committee Northern Denmark Region (N-20140069). DISCUSSION: The Run Clever trial will provide insight into possible differences in injury risk between running schedules emphasizing either running intensity or running volume. The risk of sustaining volume- and intensity-related injuries will be compared in the two intervention groups using a competing risks approach. The trial will hopefully result in a better understanding of the relationship between the running performed and possible differences in running-related injury risk and the injuries developed. TRIAL REGISTRATION: Clinical Trials NCT02349373 - January 23, 2015.

Foot pronation is not associated with increased injury risk in novice runners wearing a neutral shoe: a 1-year prospective cohort study.

OBJECTIVE: To investigate if running distance to first running-related injury varies between foot postures in novice runners wearing neutral shoes. DESIGN: A 1-year epidemiological observational prospective cohort study. SETTING: Denmark. PARTICIPANTS: A total of 927 novice runners equivalent to 1854 feet were included. At baseline, foot posture on each foot was evaluated using the foot-posture index and categorised into highly supinated (n=53), supinated (n=369), neutral (n=1292), pronated (n=122) or highly pronated (n=18). Participants then had to start running in a neutral running shoe and to use global positioning system watch to quantify the running distance in every training session. MAIN OUTCOME MEASURE: A running-related injury was defined as any musculoskeletal complaint of the lower extremity or back caused by running, which restricted the amount of running for at least 1 week. RESULTS: During 1 year of follow-up, the 1854 feet included in the analyses ran a total of 326 803 km until injury or censoring. A total of 252 participants sustained a running-related injury. Of these, 63 were bilateral injuries. Compared with a neutral foot posture, no significant body mass index-adjusted cumulative risk differences (RD) were found after 250 km of running for highly supinated feet (RD=11.0% (-10% to 32.1%), p=0.30), supinated feet (RD=-1.4% (-8.4% to 5.5%), p=0.69), pronated feet (RD=-8.1% (-17.6% to 1.3%), p=0.09) and highly pronated feet (RD=9.8% (-19.3% to 38.8%), p=0.51). In addition, the incidence-rate difference/1000 km of running, revealed that pronators had a significantly lower number of injuries/1000 km of running of -0.37 (-0.03 to -0.70), p=0.03 than neutrals. CONCLUSIONS: The results of the present study contradict the widespread belief that moderate foot pronation is associated with an increased risk of injury among novice runners taking up running in a neutral running shoe. More work is needed to ascertain if highly pronated feet face a higher risk of injury than neutral feet.