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OBJECTIVE: To investigate the association between the acute:chronic workload ratio (ACWR) and running-related injuries (RRI).METHODS: This is a secondary analysis using a database composed of data from three studies conducted with the same RRI surveillance system. Longitudinal data comprising running exposure (workload) and RRI were collected biweekly during the respective cohorts' follow-up (18-65 weeks). ACWR was calculated as the most recent (i.e., acute) external workload (last 2 weeks) divided by the average external (i.e., chronic) workload of the last 4, 6, 8, 10 and 12 weeks. Three methods were used to calculate the ACWR: uncoupled, coupled and exponentially weighted moving averages (EWMA). Bayesian logistic mixed models were used to analyse the data.RESULTS: The sample was composed of 435 runners. Runners whose ACWR was under 0.70 had about 10% predicted probability of sustaining RRI (9.6%; 95% credible interval [CrI] 7.5-12.4), while those whose ACWR was higher than 1.38 had about 1% predicted probability of sustaining RRI (1.3%; 95% CrI 0.7-1.7). The association between the ACWR and RRI was significant, varying from a small to a moderate association (1-10%). The higher the ACWR, the lower the RRI risk.CONCLUSIONS: The ACWR showed an inversely proportional association with RRI risk that can be represented by a smooth L-shaped, second-order, polynomial decay curve. The ACWR using hours or kilometres yielded similar results. The coupled and uncoupled methods revealed similar associations with RRIs. The uncoupled method presented the best discrimination for ACWR strata. The EWMA method yielded sparse and non-significant results.

Objectives To investigate the proportion of individuals who practice running, its temporal trend, and to describe the runners’ characteristics. Design Population-based repeated cross-sectional study. Methods The data from the Protective and Risk Factors for Chronic Diseases by Telephone Survey (Vigitel) from Brazil were used. Telephone interviews were conducted with adults from the Brazilian capitals (27 cities) between 2006–2017. The interviewer read the questions and recorded the participants’ responses immediately in a questionnaire. Data analyses were conducted using a Bayesian approach. Results The Vigitel database consisted of 625,460 Brazilian participants composed of 295,681 exercisers and within them 15,529 runners. The mean yearly proportion of runners was about 2.45% (95% Bayesian credible interval [CrI] 1.93 to 3.11) and 5.32% (95%CrI 4.29 to 6.54) in the entire study population and within exercisers, respectively. The absolute increase in the proportion of runners per year over the 12-year period was 0.13% and 0.17% in the entire study population and within exercisers, respectively. Runners were more likely to be younger, men, within normal body mass index, highly educated, moderate alcohol drinkers, non-smokers, less exposed to TV, living near physical activity/sports facilities and less exposed to health conditions such as arterial hypertension, diabetes and dyslipidaemia. Conclusion There was a 95% probability that the yearly proportion of runners lies between 1.93% and 3.11% in the population of the 27 Brazilian capitals, and between 4.29% and 6.54% within exercisers. There has been an increase in the proportion of runners over time. Runners were associated with healthier characteristics compared to non-runners and non-exercisers.

BackgroundRunning is an important type of exercise to keep people physically active. However, running also carries a risk of developing running-related injuries (RRI). Therefore, effective and evidence-based RRI prevention programmes are desirable, but are scarce in practice. An approach to face this problem might be the application of methods to develop RRI prevention programmes based on theories of behaviour change.ObjectiveThe purpose of the study was to develop an RRI prevention programme based on perspectives of behavioural and social science theories, as well as taking a framework development approach.MethodsThis was a qualitative study using the Intervention Mapping (IM) framework held between February and March 2018 in São Paulo, Brazil. The participants were involved in running practice. The data collection was conducted during focus group meetings. The data analysis was based on semantic thematic approach using a content analysis orientation based on inductive reasoning.ResultsThe target population of the RRI prevention programme identified was ‘adult recreational runners’. The objectives of the RRI prevention programme were established in two broad actions: (1) to provide feedback on individual training characteristics and RRI risk; and (2) provide/enhance knowledge, skills and self-efficacy on RRI preventive behaviours. The programme is aimed to be delivered through an online system.ConclusionAn RRI prevention programme was developed using the IM framework and a participatory approach. The programme was named ‘RunIn3’, and it is based on providing feedback on running volume and RRI risk, as well as providing knowledge, skills and self-efficacy on RRI preventive behaviours.

Musculoskeletal pain in athletes is common, but not always associated with injury (ie, tissue damage).1 Damage occurs when load exceeds tissue tolerance, such as ligament tear or a fracture. However, pain in athletes that occurs in the absence of trauma and tissue damage is still often labelled an ‘injury’ by clinicians, coaches and athletes themselves. This highlights a gap between knowledge (tissue damage is not necessary for pain) and practice (assuming that all pain arises from tissue damage) in our clinical community.1 2 This applies particularly in the area of acute non-traumatic pain (such as back and joint pain). To help bridge this gap, we outline eight principles to guide clinicians who manage musculoskeletal pain in sport (see infographic in figure 1). Figure 1 Infographic—principles to guide care of acute non-traumatic pain in sport. ### 1. In the absence of trauma, do not assume that pain indicates tissue damage

Introduction Reporting confidence intervals in scientific articles is important and relevant for evidence-based practice. Clinicians should understand confidence intervals in order to determine if they can realistically expect results similar to those presented in research studies when they implement the scientific evidence in clinical practice. The aims of this masterclass are: (1) to discuss confidence intervals around effect estimates; (2) to understand confidence intervals estimation (frequentist and Bayesian approaches); and (3) to interpret such uncertainty measures. Content Confidence intervals are measures of uncertainty around effect estimates. Interpretation of the frequentist 95% confidence interval: we can be 95% confident that the true (unknown) estimate would lie within the lower and upper limits of the interval, based on hypothesized repeats of the experiment. Many researchers and health professionals oversimplify the interpretation of the frequentist 95% confidence interval by dichotomizing it in statistically significant or non-statistically significant, hampering a proper discussion on the values, the width (precision) and the practical implications of such interval. Interpretation of the Bayesian 95% confidence interval (which is known as credible interval): there is a 95% probability that the true (unknown) estimate would lie within the interval, given the evidence provided by the observed data. Conclusions The use and reporting of confidence intervals should be encouraged in all scientific articles. Clinicians should consider using the interpretation, relevance and applicability of confidence intervals in real-world decision-making. Training and education may enhance knowledge and skills related to estimating, understanding and interpreting uncertainty measures, reducing the barriers for their use under either frequentist or Bayesian approaches.

Background: Behavioral and social science theories/models have been gaining attention in sports injury prevention.Objective: To investigate the potential of the Theory of Planned Behavior in explaining running-related injury preventive behavior.Methods: Six-month prospective cohort study based on data gathered from a randomized controlled trial. From a total of 1512 invited trail runners, 232 were included in this study. Preventive behaviors and their determinants were assessed at baseline and two and six months after baseline. Five-point Likert scales were used to assess the determinants of preventive behavior. A Bayesian path analysis was conducted applying mixed models and mediation analysis.Results: A 1-point increase in intention, attitude, subjective norm, and perceived behavioral control predicted an increase of 54% (95% Bayesian credible interval [BCI]: 38, 71) in the rate of performing running-related injury preventive behavior, explaining 49% (R-2 0.49; 95% BCI: 0.41, 0.56) of the variance around preventive behavior. Intention and perceived behavioral control predicted running-related injury preventive behavior directly, while 40% (95% BCI: 21, 61) and 44% (95% BCI: 20, 69) of the total effect of attitude was mediated by intention and perceived behavioral control, respectively. Attitude, subjective norm, and perceived behavioral control predicted intention.Conclusions: The Theory of Planned Behavior may have the potential to explain half of the variance around running-related injury preventive behavior and intention. Therefore, such theory may be considered a relevant and useful tool in developing, investigating, and/or implementing programs aimed at preventing running-related injuries. (C) 2021 Associacao Brasileira de Pesquisa e Pos-Graduacao em Fisioterapia. Published by Elsevier Espana, S.L.U. All rights reserved.

Background There is a lack of studies describing foot strike patterns in children and adolescents. This raises the question on what the natural foot strike pattern with less extrinsic influence should be and whether or not it is valid to make assumptions on adults based on the knowledge from children. Objectives To investigate the distribution of foot strike patterns in children and adolescents during running, and the association of participants’ characteristics with the foot strike patterns. Methods This is a cross-sectional study. Videos were acquired with a high-speed camera and running speed was measured with a stopwatch. Bayesian analyses were performed to allow foot strike pattern inferences from the sample to the population distribution and a supervised machine learning procedure was implemented to develop an algorithm based on logistic mixed models aimed at classifying the participants in rearfoot, midfoot, or forefoot strike patterns. Results We have included 415 children and adolescents. The distribution of foot strike patterns was predominantly rearfoot for shod and barefoot assessments. Running condition (barefoot versus shod), speed, and footwear (with versus without heel elevation) seemed to influence the foot strike pattern. Those running shod were more likely to present rearfoot pattern compared to barefoot. The classification accuracy of the final algorithm ranged from 80% to 88%. Conclusions The rearfoot pattern was predominant in our sample. Future well-designed prospective studies are needed to understand the influence of foot strike patterns on the incidence and prevalence of running-related injuries in children and adolescents during running, and in adult runners.

Background Running is one of the most popular and accessible physical activities in the world. However, running-related injuries are unfortunately very common. Scientific evidence is limited and scarce regarding (cost-)effectiveness and implementation process of interventions for running-related injuries prevention. Thus, the objective of this study will be to investigate the effectiveness, cost-effectiveness and implementation process of a running-related injury prevention program (RunIn3). Methods This is the protocol of a pragmatic hybrid type 1 randomized controlled trial. There will be 530 runners over 18 years old, without running-related injuries in the last 3 months from Sao Paulo, Brazil. This program will be delivered online with two broad actions: (1) to provide feedback on individual training characteristics and running-related injury risk; and (2) providing/enhancing knowledge, skills and self-efficacy on running-related injury preventive behaviors. The primary outcome will be the proportion of runners reporting running-related injuries. The secondary outcomes will be preventive behaviors, direct and indirect costs, and implementation outcomes. The main effectiveness analysis on the primary outcome will be performed using linear probability mixed models in order to allow outcome changes over time and to yield the absolute risk reduction between-groups. Discussion The main hypothesis of this study is that the RunIn3 program will be effective in reducing the running-related injury risk and in promoting preventive behavior, either by increasing the frequency of healthy behaviors or by reducing the frequency of risk behaviors. Moreover, if the RunIn3 program is effective in reducing the running-related injuries risk, we believe that this effect would go alongside with a reduction of societal costs. Trail registration Clinicaltrials.gov (NCT03892239) Registered 5 February 2019 - Prospectively registered, https://clinicaltrials.gov/ct2/show/NCT03892239 .

Confinement measures during the COVID-19 pandemic have caused substantial reductions in global physical activity (PA) levels. In view of the manifold health benefits of PA, the development of interventions counteracting this trend is paramount. Our survey with 15,261 participants (38 ± 15 years, 58.5% females) examined preferences towards digital home exercise programs in 14 countries affected by COVID-19. More than two-thirds of the sample (68.4%, n = 10,433) indicated being interested in home exercise, and most participants were willing to work out at least three times per week (89.3%, n = 9328). Binary logistic regression revealed that female sex, working part-time, younger age, and being registered in a gym were associated with willingness to exercise. Flexibility (71.1%, n = 7377), resistance (68.6%, n = 7116), and endurance training (62.4%, n = 6478) were the most preferred types of exercise. Our results may guide health providers in developing individually tailored PA interventions during the current and future pandemics.

BackgroundTrail running is popular worldwide, but there is no preventive intervention for running-related injury (RRI).AimTo evaluate the effectiveness of adding online tailored advice (TrailS6) to general advice on (1) the prevention of RRIs and (2) the determinants and actual preventive behaviour in Dutch trail runners.MethodsTwo-arm randomised controlled trial over 6 months. 232 trail runners were randomly assigned to an intervention or control group. All participants received online general advice on RRI prevention 1 week after baseline. Every 2 weeks, participants in the intervention group received specific advice tailored to their RRI status. The control group received no further intervention. Bayesian mixed models were used to analyse the data.ResultsTrail runners in the intervention group sustained 13% fewer RRIs compared with those in the control group after 6 months of follow-up (absolute risk difference −13.1%, 95% Bayesian highest posterior credible interval (95% BCI) −23.3 to −3.1). A preventive benefit was observed in one out of eight trail runners who had received the online tailored advice for 6 months (number needed to treat 8, 95% BCI 3 to 22). No significant between-group difference was observed on the determinants and actual preventive behaviours.ConclusionsOnline tailored advice prevented RRIs among Dutch trail runners. Therefore, online tailored advice may be used as a preventive component in multicomponent RRI prevention programmes. No effect was observed on determinants and actual preventive behaviours.Trial registration numberThe Netherlands National Trial Register (NTR5431).