Identifying and Minimizing Incentives for Competing Interests in Sports Medicine Publications.

Academics in sports medicine as well as other medical fields are generally expected to publish research and opinions in peer-reviewed journals. The peer-review process is intended to protect against the publication of flawed research and unsubstantiated claims. However, both financial and non-financial competing interests may result in sub-optimal results by affecting investigators, editors, peer reviewers, academic institutions, and publishers. In this article, we focus on the non-financial competing interests created in our current academic system. Because these competing interests are embedded in our current scholastic framework, the potential biases are difficult to quantify. To minimize the effect of these competing interests, we review and highlight some underlying incentives for each stakeholder and some potential solutions to mitigate their effects.

Identifiability of causal effects in test-negative design studies.

Causal directed acyclic graphs (DAGs) are often used to select variables in a regression model to identify causal effects. Outcome-based sampling studies, such as the 'test-negative design' used to assess vaccine effectiveness, present unique challenges that are not addressed by the common back-door criterion. Here we discuss intuitive, graphical approaches to explain why the common back-door criterion cannot be used for identification of population average causal effects with outcome-based sampling studies. We also describe graphical rules that can be used instead in outcome-based sampling studies when the objective is limited to determining if the causal odds ratio is identifiable, and illustrate recent changes to the free online software Dagitty which incorporate these principles.

Understanding Training Load as Exposure and Dose.

Various terms used in sport and exercise science, and medicine, are derived from other fields such as epidemiology, pharmacology and causal inference. Conceptual and nomological frameworks have described training load as a multidimensional construct manifested by two causally related subdimensions: external and internal training load. In this article, we explain how the concepts of training load and its subdimensions can be aligned to classifications used in occupational medicine and epidemiology, where exposure can also be differentiated into external and internal dose. The meanings of terms used in epidemiology such as exposure, external dose, internal dose and dose-response are therefore explored from a causal perspective and their underlying concepts are contextualised to the physical training process. We also explain how these concepts can assist in the validation process of training load measures. Specifically, to optimise training (i.e. within a causal context), a measure of exposure should be reflective of the mediating mechanisms of the primary outcome. Additionally, understanding the difference between intermediate and surrogate outcomes allows for the correct investigation of the effects of exposure measures and their interpretation in research and applied settings. Finally, whilst the dose-response relationship can provide evidence of the validity of a measure, conceptual and computational differentiation between causal (explanatory) and non-causal (descriptive and predictive) dose-response relationships is needed. Regardless of how sophisticated or "advanced" a training load measure (and metric) appears, in a causal context, if it cannot be connected to a plausible mediator of a relevant response (outcome), it is likely of little use in practice to support and optimise the training process.

Investigating the Effect of Return-to-Play Timing After Injury on Performance: Does the Analysis Answer the Research Objective?

Return-to-play decision making should be based on all the advantages and disadvantages of return to play for athletes, not just the risk of injury. For competitive athletes, this includes the effect of early versus delayed return to sport on performance. In this paper, we address the questions "How can I estimate the effect of injury on the individual's performance at return to play?" and "What is the effect of delaying return to sport on the individual's performance?". To address these questions, we describe (1) some foundational concepts, design and analytical challenges related to estimating the causal effect of return to play timing on performance in the athlete, (2) additional challenges if one is interested in the effects of delaying return to play and (3) differences when the questions relate to the team's performance. Although the analytical strategies described appear complicated, coaches and athletes make these judgements informally every day without explicitly stating their assumptions. Using a formal approach should help analysts provide the most valid answers to the questions asked by athletes and coaches. In brief, the choice of a comparison group depends on the research question and requires that one consider the hypothetical performance trajectory of the athlete had they never been injured. Thus, the optimal comparison group depends on the shape of the expected trajectory and the specific research question being asked.

Implementing Multiple Imputation for Missing Data in Longitudinal Studies When Models are Not Feasible: An Example Using the Random Hot Deck Approach.

Purpose: Researchers often use model-based multiple imputation to handle missing at random data to minimize bias. However, constraints within the data may sometimes result in implausible values, making model-based imputation infeasible. In these contexts, we illustrate how random hot deck imputation can allow for plausible multiple imputation in longitudinal studies. Patients and Methods: Our motivating example is the Childhood Health, Activity, and Motor Performance School Study Denmark (CHAMPS-DK), a prospective cohort study that measured weekly sports participation for 1700 Danish schoolchildren. Using observed data on 4 variables (pain, activity frequency, sport, sport counts), we created a gold-standard data set without missing data. We then created a synthetic data set by setting some variable values to missing based on a prediction model that mimicked real-data missingness patterns. To create 5 imputed data sets, we matched each record with missing data to several fully observed records, generated probabilities from matched records, and sampled from these records based on the probability of each occurring. We assessed variability and agreement (kappa) between the imputed data sets and the gold-standard data set. We compare results to common model-based imputation methods. Results: Variability across data sets appeared reasonable. The range of kappa for the random hot deck approach was moderate for activity frequency (0.65 to 0.71) and sport (0.59 to 0.85), and poor for common model-based approaches (range 0.00 to 0.11). The range of kappas for sport count was strong (0.87 to 0.97) for random hot deck imputation and weak to moderate (0.55 to 0.71) for common model-based imputation. Agreement was higher when more information was present, and when prevalence was higher for our binary variable sport. Conclusion: Random hot deck imputation should be considered as an alternative method when model-based approaches are infeasible, specifically where there are constraints within and between covariates.

No associations between C-reactive protein and spinal pain trajectories in children and adolescents (CHAMPS study-DK).

Preliminary evidence points to a link between C-reactive protein (CRP) and spinal pain in adults. However, there is a paucity of research in younger populations. Therefore, we aimed to determine associations between CRP and spinal pain in childhood and adolescence. We identified trajectories of spinal pain from childhood to adolescence and investigated the associations between CRP and trajectory subgroups. Six- to 11-year-old children from 13 primary schools, were followed from October 2008 and until 2014. High-sensitivity CRP collected at baseline (2008) was measured using serum samples. The outcome was the number of weeks with non-traumatic spinal pain between November 2008 and June 2014. We constructed a trajectory model to identify different spinal pain trajectory subgroups. The associations between CRP and spinal pain trajectory subgroups were modelled using mixed-effects multinominal logistic regression. Data from 1556 participants (52% female), with a mean age of 8.4 years at baseline, identified five spinal pain trajectory subgroups: "no pain" (55.3%), "rare" (23.7%), "rare, increasing" (13.6%), "moderate, increasing" (6.1%), and "early onset, decreasing" (1.3%). There were no differences in baseline high-sensitivity CRP levels between spinal pain trajectory subgroups. Thus, the heterogeneous courses of spinal pain experienced were not defined by differences in CRP at baseline.

Observed Injury Rates Did Not Follow Theoretically Predicted Injury Risk Patterns in Professional Human Circus Artists.

OBJECTIVE: Identifying which types of athletes have increased injury risk (ie, predictive risk factors) should help develop cost-effective selective injury prevention strategies. Our objective was to compare a theoretical injury risk classification system developed by coaches and rehabilitation therapists, with observed injury rates in human circus acts across dimensions of physical stressors, acrobatic complexity, qualifications, and residual risks. DESIGN: Descriptive epidemiological study. SETTING: professional circus company. PATIENTS OR OTHER PARTICIPANTS: Human circus artists performing in routine roles between 2007 and 2017. ASSESSMENT OF RISK FACTORS: Characteristics of circus acts categorized according to 4 different dimensions. MAIN OUTCOME MEASURES: Medical attention injury rates (injury requiring a visit to the therapist), time-loss injury rates (TL-1; injury resulting in at least one missed performance), and time-loss 15 injury rates (TL-15; injury resulting in at least 15 missed performances). RESULTS: Among 962 artists with 1 373 572 performances, 89.4% (860/962) incurred at least one medical attention injury, 74.2% (714/962) incurred at least one TL-1 injury, and 50.8% (489/962) incurred at least one TL-15 injury. There were important inconsistencies between theoretical and observed injury risk patterns in each of the 4 dimensions for all injury definitions (medical attention, TL-1, and TL-15). CONCLUSIONS: Although theoretical classifications are the only option when no data are available, observed risk patterns based on injury surveillance programs can help identify artists who have a high (or low) theoretical risk but are nonetheless actually at low (or high) risk of injury, given their current roles. This will help develop more cost-effective selective injury prevention programs.

Causal effects, workload and injury risk: The importance of specifying the research question.

OBJECTIVES: To illustrate why the research question determines whether and how sport medicine investigators should adjust for workload when interested in interventions or causal risk factors for injury. DESIGN: Theoretical conceptualization. METHODS: We use current concepts of causal inference to demonstrate the advantages and disadvantages of adjusting for workload through different analytic approaches when evaluating causal effects on injury risk. RESULTS: When a risk factor of interest changes workload, including workload in the regression will cause bias. When workload represents time-at-risk (e.g. games played, minutes run), including workload as an offset in Poisson regression provides a comparison of injury rates (injuries per unit time). This is equivalent to including log(workload) as an independent variable with the coefficient fixed to 1. If workload is included as an independent variable instead of an offset, using log(workload) rather than workload is more consistent with theory. This practice is similar to the principles of allometric scaling. When workload represents a combination of both time-at-risk and intensity, such as with session ratings of perceived exertion, the optimal analytical strategy may require modeling time-at-risk and intensity separately rather than as one factor. CONCLUSIONS: Whether to account for recent workload or not, and how to account for recent workload, depends on the research question and the causal assumptions, both of which should be explicitly stated.

Spinal pain in childhood: prevalence, trajectories, and diagnoses in children 6 to 17 years of age.

This study aimed to investigate the trajectories of spinal pain frequency from 6 to 17 years of age and describe the prevalence and frequency of spinal pain and related diagnoses in children following different pain trajectories. First through fifth-grade students from 13 primary schools were followed for 5.5 years. Occurrences of spinal pain were reported weekly via text messages. Children reporting spinal pain were physically evaluated and classified using International Classification of Disease criteria. Trajectories of spinal pain frequency were modeled from age 6 to 17 years with latent class growth analysis. We included data from 1556 children (52.4% female, mean (SD) baseline age = 9.1 (1.9) years) and identified 10,554 weeks of spinal pain in 329,756 weeks of observation. Sixty-three percent of children reported one or more occurrences of spinal pain. We identified five trajectories of spinal pain frequency. Half the children (49.8%) were classified as members of a "no pain" trajectory. The remaining children followed "rare" (27.9%), "rare, increasing" (14.5%), "moderate, increasing" (6.5%), or "early-onset, decreasing" (1.3%) spinal pain trajectories. The most common diagnoses in all trajectory groups were non-specific (e.g., "back pain"). Tissue-specific diagnoses (e.g., muscle strain) were less common and pathologies (e.g., fracture) were rare.  Conclusion: From childhood through adolescence, spinal pain was common and followed heterogeneous courses comprising stable, increasing, and early-onset trajectories. These findings accord with recommendations from adult back pain guidelines that most children with spinal pain can be reassured that they do not have a serious disease and encouraged to stay active. What is Known: • Spinal pain imposes a large burden on individuals and society. • Although many people first experience the condition in childhood, little is known about the developmental trajectories of spinal pain from childhood to adolescence. What is New: • Data from 1556 children and 329,756 participant weeks showed five unique spinal pain trajectories from 6 to 17 years: most children rarely reported spinal pain, while one in five followed increasing or early-onset trajectories. • Most pain occurrences were non-specific; pathological diagnoses were rare.

Barriers and Facilitators to Physical Activity for People With Scleroderma: A Scleroderma Patient-Centered Intervention Network Cohort Study.

OBJECTIVE: To support physical activity among people with systemic sclerosis (SSc [scleroderma]), we sought to determine the prevalence and importance of barriers and the likelihood of using possible facilitators. METHODS: We invited 1,707 participants from an international SSc cohort to rate the importance of 20 barriers (14 medical, 4 social or personal, 1 lifestyle, and 1 environmental) and the likelihood of using 91 corresponding barrier-specific and 12 general facilitators. RESULTS: Among 721 respondents, 13 barriers were experienced by ≥25% of participants, including 2 barriers (fatigue and Raynaud's phenomenon) rated "important" or "very important" by ≥50% of participants, 7 barriers (joint stiffness and contractures, shortness of breath, gastrointestinal problems, difficulty grasping, pain, muscle weakness and mobility limitations, and low motivation) by 26-50%, and 4 barriers by <26%. Overall, 23 of 103 facilitators (18 medical-related) were rated by ≥75% of participants as "likely" or "very likely" to use among those who experienced corresponding barriers. These facilitators focused on adapting exercise (e.g., using controlled, slow movement), taking care of one's body (e.g., stretching), keeping warm (e.g., wearing gloves), and protecting skin (e.g., covering ulcers). Among those participants who had previously tried the facilitator, all facilitators were rated by ≥50% as "likely" or "very likely" to use. Among those participants with the barrier who had not tried the facilitator, only 12 of 103 facilitators were rated by >50% of participants as "likely" or "very likely" to use. CONCLUSION: Medical-related physical activity barriers were common and considered important. Facilitators considered as most likely to be used involved adapting exercise, taking care of one's body, keeping warm, and protecting skin.

Causal simulation experiments: Lessons from bias amplification.

Recent theoretical work in causal inference has explored an important class of variables which, when conditioned on, may further amplify existing unmeasured confounding bias (bias amplification). Despite this theoretical work, existing simulations of bias amplification in clinical settings have suggested bias amplification may not be as important in many practical cases as suggested in the theoretical literature. We resolve this tension by using tools from the semi-parametric regression literature leading to a general characterization in terms of the geometry of OLS estimators which allows us to extend current results to a larger class of DAGs, functional forms, and distributional assumptions. We further use these results to understand the limitations of current simulation approaches and to propose a new framework for performing causal simulation experiments to compare estimators. We then evaluate the challenges and benefits of extending this simulation approach to the context of a real clinical data set with a binary treatment, laying the groundwork for a principled approach to sensitivity analysis for bias amplification in the presence of unmeasured confounding.

Predicting Injury Risk Over Changes in Physical Activity in Children Using the Acute:Chronic Workload Ratio.

Limited research exists on the relationship between changes in physical activity levels and injury in children. In this study, we investigated the prognostic relationship between changes in activity, measured by the acute:chronic workload ratio (ACWR), and injury in children. We used data from the Childhood Health, Activity, and Motor Performance School Study Denmark (2008-2014), a prospective cohort study of 1,660 children aged 6-17 years. We modeled the relationship between the uncoupled 5-week ACWR and injury, defined as patient-reported musculoskeletal pain, using generalized additive mixed models. These methods accounted for repeated measures, and they improved model fit and precision compared with previous studies that used logistic models. The prognostic model predicted an injury risk of approximately 3% between decreases in activity level of up to 60% and increases of up to 30%. Predicted risk was lower when activity decreased by more than 60% (minimum of 0.5% with no recreational activity). Predicted risk was higher when activity increased by more than 30% (4.5% with a 3-fold increase in activity). Girls were at significantly higher risk of injury than boys. We observed similar patterns but lower absolute risks when we restricted the outcome to clinician-diagnosed injury. Predicted increases in injury risk with increasing activity were much lower than those of previous studies carried out in adults.

Methodological options of the nominal group technique for survey item elicitation in health research: A scoping review.

OBJECTIVE: To conduct a scoping review that identifies different nominal group technique (NGT) methods used to elicit items for health surveys, and their advantages and disadvantages. STUDY DESIGN AND SETTING: We conducted a comprehensive search process from database inception to July 22, 2019 in Medline, EMBASE, PsychInfo, CINAHL, Cochrane Central and Scopus without language restriction. We screened titles and abstracts. Data from potentially relevant articles were extracted by one reviewer and verified by a second reviewer, with disagreements resolved by consensus or a third reviewer. RESULTS: We included 57 studies, which used between 1 and 41 nominal groups that included between 2 and 30 participants per group. We grouped the 30 identified decision points for the NGT process into two stages common to most qualitative group methods [Research objectives; Group characteristics] and three stages related to the nominal groups themselves [Eliciting survey items; Refining survey elicited items from stage 3; Evaluating and selecting final survey items]. We discuss the advantages and disadvantages of each option in relation to specific study contexts. CONCLUSION: Investigators should carefully consider their options for each of the identified decision points and document the reasons for their choices in their protocol to maximize validity and transparency.

Data-driven methods distort optimal cutoffs and accuracy estimates of depression screening tools: a simulation study using individual participant data.

OBJECTIVE: To evaluate, across multiple sample sizes, the degree that data-driven methods result in (1) optimal cutoffs different from population optimal cutoff and (2) bias in accuracy estimates. STUDY DESIGN AND SETTING: A total of 1,000 samples of sample size 100, 200, 500 and 1,000 each were randomly drawn to simulate studies of different sample sizes from a database (n = 13,255) synthesized to assess Edinburgh Postnatal Depression Scale (EPDS) screening accuracy. Optimal cutoffs were selected by maximizing Youden's J (sensitivity+specificity-1). Optimal cutoffs and accuracy estimates in simulated samples were compared to population values. RESULTS: Optimal cutoffs in simulated samples ranged from ≥ 5 to ≥ 17 for n = 100, ≥ 6 to ≥ 16 for n = 200, ≥ 6 to ≥ 14 for n = 500, and ≥ 8 to ≥ 13 for n = 1,000. Percentage of simulated samples identifying the population optimal cutoff (≥ 11) was 30% for n = 100, 35% for n = 200, 53% for n = 500, and 71% for n = 1,000. Mean overestimation of sensitivity and underestimation of specificity were 6.5 percentage point (pp) and -1.3 pp for n = 100, 4.2 pp and -1.1 pp for n = 200, 1.8 pp and -1.0 pp for n = 500, and 1.4 pp and -1.0 pp for n = 1,000. CONCLUSIONS: Small accuracy studies may identify inaccurate optimal cutoff and overstate accuracy estimates with data-driven methods.

The semiparametric accelerated trend-renewal process for recurrent event data.

Recurrent event data arise in many biomedical longitudinal studies when health-related events can occur repeatedly for each subject during the follow-up time. In this article, we examine the gap times between recurrent events. We propose a new semiparametric accelerated gap time model based on the trend-renewal process which contains trend and renewal components that allow for the intensity function to vary between successive events. We use the Buckley-James imputation approach to deal with censored transformed gap times. The proposed estimators are shown to be consistent and asymptotically normal. Model diagnostic plots of residuals and a method for predicting number of recurrent events given specified covariates and follow-up time are also presented. Simulation studies are conducted to assess finite sample performance of the proposed method. The proposed technique is demonstrated through an application to two real data sets.