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To provide certified athletic trainers, physicians, and other health care and fitness professionals with recommendations based on current evidence regarding the prevention of noncontact and indirect-contact anterior cruciate ligament (ACL) injuries in athletes and physically active individuals.   Preventing ACL injuries during sport and physical activity may dramatically decrease medical costs and long-term disability. Implementing ACL injury-prevention training programs may improve an individual's neuromuscular control and lower extremity biomechanics and thereby reduce the risk of injury. Recent evidence indicates that ACL injuries may be prevented through the use of multicomponent neuromuscular-training programs.   Multicomponent injury-prevention training programs are recommended for reducing noncontact and indirect-contact ACL injuries and strongly recommended for reducing noncontact and indirect-contact knee injuries during physical activity. These programs are advocated for improving balance, lower extremity biomechanics, muscle activation, functional performance, strength, and power, as well as decreasing landing impact forces. A multicomponent injury-prevention training program should, at minimum, provide feedback on movement technique in at least 3 of the following exercise categories: strength, plyometrics, agility, balance, and flexibility. Further guidance on training dosage, intensity, and implementation recommendations is offered in this statement.

Background Population-based studies in Canada and the United States estimate chronic physical health conditions affect between 20 to 30% of children aged 0 to 17. Challenges in measuring chronic conditions include the use of inconsistent definitions and algorithms that capture a limited number of conditions. Thus, we developed a chronic health condition (CHC) algorithm using administrative data to determine whether a child has a CHC based on (1) the diagnosis recorded for the visit, (2) the number of visits, and (3) within a specific reference period. Methods Data were from the cross-sectional 2014 Ontario Child Health Study, linked with Ontario Health Insurance Plan (OHIP) administrative health data. Unweighted prevalence estimates and agreement analyses (Cohen’s Kappa, sensitivity, specificity) were used to compare the survey parent-reported and algorithm-based presence of a CHC. Results 31.8% and 27.1% of children and youth had a CHC based on administrative and survey data, respectively. Agreement between administrative and survey data was poor ( k  = 0.17). Among a few specific conditions, agreement varied depending on the type of condition (e.g., diabetes k  = 0.77 vs health conditions k  = 0.21). Conclusion We found considerable discrepancies between administrative and survey-reported data. The results highlight the importance of using algorithms developed from multiple datasets to examine complex research questions, such as the measurement of chronicity.

Major depressive disorder (MDD) is the leading cause of disability worldwide, yet treatment selection still proceeds via “trial and error”. Given the varied presentation of MDD and heterogeneity of treatment response, the use of machine learning to understand complex, non-linear relationships in data may be key for treatment personalization. Well-organized, structured data from clinical trials with standardized outcome measures is useful for training machine learning models; however, combining data across trials poses numerous challenges. There is also persistent concern that machine learning models can propagate harmful biases. We have created a methodology for organizing and preprocessing depression clinical trial data such that transformed variables harmonized across disparate datasets can be used as input for feature selection. Using Bayesian optimization, we identified an optimal multi-layer dense neural network that used data from 21 clinical and sociodemographic features as input in order to perform differential treatment benefit prediction. With this combined dataset of 5032 individuals and 6 drugs, we created a differential treatment benefit prediction model. Our model generalized well to the held-out test set and produced similar accuracy metrics in the test and validation set with an AUC of 0.7 when predicting binary remission. To address the potential for bias propagation, we used a bias testing performance metric to evaluate the model for harmful biases related to ethnicity, age, or sex. We present a full pipeline from data preprocessing to model validation that was employed to create the first differential treatment benefit prediction model for MDD containing 6 treatment options.

Approximately two-thirds of patients with major depressive disorder do not achieve remission during their first treatment. There has been increasing interest in the use of digital, artificial intelligence-powered clinical decision support systems (CDSSs) to assist physicians in their treatment selection and management, improving the personalization and use of best practices such as measurement-based care. Previous literature shows that for digital mental health tools to be successful, the tool must be easy for patients and physicians to use and feasible within existing clinical workflows. This study aims to examine the feasibility of an artificial intelligence-powered CDSS, which combines the operationalized 2016 Canadian Network for Mood and Anxiety Treatments guidelines with a neural network-based individualized treatment remission prediction. Owing to the COVID-19 pandemic, the study was adapted to be completed entirely remotely. A total of 7 physicians recruited outpatients diagnosed with major depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Patients completed a minimum of one visit without the CDSS (baseline) and 2 subsequent visits where the CDSS was used by the physician (visits 1 and 2). The primary outcome of interest was change in appointment length after the introduction of the CDSS as a proxy for feasibility. Feasibility and acceptability data were collected through self-report questionnaires and semistructured interviews. Data were collected between January and November 2020. A total of 17 patients were enrolled in the study; of the 17 patients, 14 (82%) completed the study. There was no significant difference in appointment length between visits (introduction of the tool did not increase appointment length; F =0.805; mean squared error 58.08; P=.46). In total, 92% (12/13) of patients and 71% (5/7) of physicians felt that the tool was easy to use; 62% (8/13) of patients and 71% (5/7) of physicians rated that they trusted the CDSS. Of the 13 patients, 6 (46%) felt that the patient-clinician relationship significantly or somewhat improved, whereas 7 (54%) felt that it did not change. Our findings confirm that the integration of the tool does not significantly increase appointment length and suggest that the CDSS is easy to use and may have positive effects on the patient-physician relationship for some patients. The CDSS is feasible and ready for effectiveness studies. ClinicalTrials.gov NCT04061642; http://clinicaltrials.gov/ct2/show/NCT04061642.

[This corrects the article DOI: 10.2196/31862.].

Conclusions: ACL patients with better preoperative quadriceps activation and strength recovered quadriceps activation and strength better than those with lower preoperative quadriceps function. Because previous research has demonstrated a relationship between quadriceps activation and strength in healthy individuals, we had anticipated that preoperative quadriceps activation would affect postoperative quadriceps strength. Supported by NIH Grant K08 AR053152-01A2 Anterior Cruciate Ligament Injury Causes Biomechanical Alterations In Both The Injured And Non-Injured Leg: The JUMP ACL Study Goerger BM, Marshall SW, Beutler AI, Blackburn JT, Wilckens JH, Padua DA: Increased hip flexion is described during ACL injury mechanisms and decreased balance is associated with increased risk of future ACL injury in those with ACLR. [...]fatigue in ACLR females may partially explain the high risk of future ACL injury in these individuals.

Purpose: To examine the effect of attentional focus on agonist/antagonist muscle activity and force production in an open-chain, early-phase rehabilitation strengthening task applied to isolate the gluteus medius muscle (GMed). Methods: Forty-five active college-aged individuals (28 women, 17 men) were randomly assigned to an external focus of attention (EFA) group, an internal focus of attention (IFA) group, or a control group, and given specific movement cues. Co-contraction ratios and force production were determined as percent of maximal voluntary isometric contraction for GMed and adductor longus (AL). Results: There was a significant main effect of group for percent change of abductor force production of side-lying GMed hip abduction between the EFA and IFA groups (covariate significant at P < .001, main effect of group significant at P = .034 and EFA greater than IFA at P = .027). No main effect was seen in percent change of co-contraction ratio %GMed:%AL. Conclusions: Clinicians should consider employing EFA when assessing isolated muscle strength capabilities in patients and evaluate and strengthen the GMed in 10° of abduction, a position shown to optimize recruitment and force production during open-chain maximal voluntary isometric contraction. [Athletic Training & Sports Health Care. 2020;12(6):272–282.]

Cutting maneuvers have been implicated as a mechanism of noncontact anterior cruciate ligament (ACL) injuries in collegiate female basketball players. To investigate knee kinematics and kinetics during running when the width of a single step, relative to the path of travel, was manipulated, a lateral false-step maneuver. Crossover design. University biomechanics laboratory. Thirteen female collegiate basketball athletes (age = 19.7 +/- 1.1 years, height = 172.3 +/- 8.3 cm, mass = 71.8 +/- 8.7 kg). Three conditions: normal straight-ahead running, lateral false step of width 20% of body height, and lateral false step of width 35% of body height. Peak angles and internal moments for knee flexion, extension, abduction, adduction, internal rotation, and external rotation. Differences were noted among conditions in peak knee angles (flexion [P < .01], extension [P = .02], abduction [P < .01], and internal rotation [P < .01]) and peak internal knee moments (abduction [P < .01], adduction [P < .01], and internal rotation [P = .03]). The lateral false step of width 35% of body height was associated with larger peak flexion, abduction, and internal rotation angles and larger peak abduction, adduction, and internal rotation moments than normal running. Peak flexion and internal rotation angles were also larger for the lateral false step of width 20% of body height than for normal running, whereas peak extension angle was smaller. Peak internal rotation angle increased progressively with increasing step width. Performing a lateral false-step maneuver resulted in changes in knee kinematics and kinetics compared with normal running. The differences observed for lateral false steps were consistent with proposed mechanisms of ACL loading, suggesting that lateral false steps represent a hitherto neglected mechanism of noncontact ACL injury.

Athletes engage in activities that necessitate use of recovery strategies from exhaustive exercise. Although the benefits of cold-water immersion have been extensively studied, active recovery in water for submaximal-effort exercise has received limited consideration. The purpose of this study was to compare the influence of active recovery, passive recovery, and cold-water immersion on speed, power, and perceived soreness after exhaustive exercise. Twenty-three NCAA Division I athletes matched by sport, position, and sex were randomized into 3 groups: passive recovery, cold-water immersion, or active recovery. Dependent measures of perceived muscular soreness, maximum vertical-jump height, and 20-meter sprint time were recorded at baseline, postexercise, and 24 hours postintervention. Separate repeated measures analysis of variance was used to analyze the effect of group and time on the dependent measures. Cold-water immersion and active and passive recovery were not found to produce significant differences regarding the recovery of speed, power, or perceived soreness. [Athletic Training & Sports Health Care . 2013;5(4):169--176.]