Can a Psychologic Profile Predict Successful Return to Full Duty After a Musculoskeletal Injury?

BACKGROUND: Psychologic variables have been shown to have a strong relationship with recovery from injury and return to work or sports. The extent to which psychologic variables predict successful return to work in military settings is unknown. QUESTIONS/PURPOSES: In a population of active duty soldiers, (1) can a psychologic profile determine the risk of injury after return to full duty? (2) Do psychologic profiles differ between soldiers sustaining injuries in the spine (thoracic or lumbar) and those with injuries to the lower extremities? METHODS: Psychologic variables were assessed in soldiers returning to full, unrestricted duty after a recent musculoskeletal injury. Most of these were noncombat injuries from work-related physical activity. Between February 2016 and September 2017, 480 service members who were cleared to return to duty after musculoskeletal injuries (excluding those with high-velocity collisions, pregnancy, or amputation) were enrolled in a study that tracked subsequent injuries over the following year. Of those, we considered individuals with complete 12-month follow-up data as potentially eligible for analysis. Based on that, approximately 2% (8 of 480) were excluded because they did not complete baseline surveys, approximately 2% (11 of 480) were separated from the military during the follow-up period and had incomplete injury data, 1% (3 of 480) were excluded for not serving in the Army branch of the military, and approximately 2% (8 of 480) were excluded because they were not cleared to return to full duty. This resulted in 450 soldiers analyzed. Individuals were 86% (385 of 450) men; 74% (331 of 450) had lower extremity injuries and 26% (119 of 450) had spinal injuries, including soft tissue aches and pains (for example, strains and sprains), fractures, and disc herniations. Time-loss injury within 1 year was the primary outcome. While creating and validating a new prediction model using only psychological variables, 19 variables were assessed for nonlinearity, further factor selection was performed through elastic net, and models were internally validated through 2000 bootstrap iterations. Performance was deciphered through calibration, discrimination (area under the curve [AUC]), R 2 , and calibration in the large. Calibration assesses predicted versus actual risk by plotting the x and y intersection of these values; the more similar predicted risk values are to actual ones, the closer the slope of the line formed by the intersection points of all subjects is to equaling "1" (optimal calibration). Likewise, perfect discrimination (predicted injured versus actual injured) presents as an AUC of 1. Perfect calibration in the large would equal 0 because it represents the average predicted risk versus the actual outcome rate. Sensitivity analyses stratified groups by prior injury region (thoracic or lumbar spine and lower extremity) as well as the severity of injury by days of limited duty (moderate [7-27 days] and severe [28 + days]). RESULTS: A model comprising primarily psychologic variables including depression, anxiety, kinesiophobia, fear avoidance beliefs, and mood did not adequately determine the risk of subsequent injury. The derived logistic prediction model had 18 variables: R 2 = 0.03, calibration = 0.63 (95% confidence interval [CI] 0.30 to 0.97), AUC = 0.62 (95% CI 0.52 to 0.72), and calibration in the large = -0.17. Baseline psychologic profiles between body regions differed only for depression severity (mean difference 1 [95% CI 0 to 1]; p = 0.04), with greater mean scores for spine injuries than for lower extremity injuries. Performance was poor for those with prior spine injuries compared with those with lower extremity injuries (AUC 0.50 [95% CI 0.42 to 0.58] and 0.63 [95% CI 0.57 to 0.69], respectively) and moderate versus severe injury during the 1-year follow-up (AUC 0.61 [95% CI 0.51 to 0.71] versus 0.64 [95% CI 0.64 to 0.74], respectively). CONCLUSION: The psychologically based model poorly predicted subsequent injury. This study does not minimize the value of assessing the psychologic profiles of injured athletes, but rather suggests that models looking to identify injury risk should consider a multifactorial approach that also includes other nonpsychologic factors such as injury history. Future studies should refine the most important psychologic constructs that can add the most value and precision to multifactorial models aimed at identifying the risk of injury. LEVEL OF EVIDENCE: Level III, prognostic study.

Barriers and facilitators to implementation of musculoskeletal injury mitigation programmes for military service members around the world: a scoping review.

INTRODUCTION: Musculoskeletal injury (MSK-I) mitigation and prevention programmes (MSK-IMPPs) have been developed and implemented across militaries worldwide. Although programme efficacy is often reported, development and implementation details are often overlooked, limiting their scalability, sustainability and effectiveness. This scoping review aimed to identify the following in military populations: (1) barriers and facilitators to implementing and scaling MSK-IMPPs; (2) gaps in MSK-IMPP research and (3) future research priorities. METHODS: A scoping review assessed literature from inception to April 2022 that included studies on MSK-IMPP implementation and/or effectiveness in military populations. Barriers and facilitators to implementing these programmes were identified. RESULTS: From 132 articles, most were primary research studies (90; 68.2%); the remainder were review papers (42; 31.8%). Among primary studies, 3 (3.3%) investigated only women, 62 (69%) only men and 25 (27.8%) both. Barriers included limited resources, lack of stakeholder engagement, competing military priorities and equipment-related factors. Facilitators included strong stakeholder engagement, targeted programme design, involvement/proximity of MSK-I experts, providing MSK-I mitigation education, low burden on resources and emphasising end-user acceptability. Research gaps included variability in reported MSK-I outcomes and no consensus on relevant surveillance metrics and definitions. CONCLUSION: Despite a robust body of literature, there is a dearth of information about programme implementation; specifically, barriers or facilitators to success. Additionally, variability in outcomes and lack of consensus on MSK-I definitions may affect the development, implementation evaluation and comparison of MSK-IMPPs. There is a need for international consensus on definitions and optimal data reporting elements when conducting injury risk mitigation research in the military.

Move to health-a holistic approach to the management of chronic low back pain: an intervention and implementation protocol developed for a pragmatic clinical trial.

BACKGROUND: The prevalence of chronic pain conditions is growing. Low back pain was the primary cause of disability worldwide out of 156 conditions assessed between 1990 and 2016, according to the Global Burden of Disease Study. Conventional medical approaches have failed to identify effective and long-lasting approaches for the management of chronic pain, and often fail to consider the multiple domains that influence overall health and can contribute to the pain experience. Leading international organizations that focus on pain research have stated the importance of considering these other domains within holistic and multidisciplinary frameworks for treating pain. While the research behind the theoretical link between these domains and chronic pain outcomes has expanded greatly over the last decade, there have been few practical and feasible methods to implement this type of care in normal clinical practice. METHODS: The purpose of this manuscript is to describe an implementation protocol that is being used to deliver a complex holistic health intervention at multiple sites within a large government health system, as part of a larger multisite trial for patients with chronic low back pain. The Move to Health program developed by the US Army Medical Command was tailored for specific application to patients with low back pain and begins by providing an empirical link between eight different health domains (that include physical, emotional, social, and psychological constructs) and chronic low back pain. Through a six-step process, a health coach leverages motivational interviewing and information from a personal health inventory to guide the patient through a series of conversations about behavioral lifestyle choices. The patient chooses which domains they want to prioritize, and the health coach helps implement the plan with the use of SMART (Specific, Measurable, Attainable, Realistic, Time-bound) goals and a series of resources for every domain, triaged from self-management to specialist referral. DISCUSSION: Complex interventions described in clinical trials are often challenging to implement because they lack sufficient details. Implementation protocols can improve the ability to properly deliver trial interventions into regular clinical practice with increased fidelity. TRIAL REGISTRATION: Implementation of this intervention protocol was developed for a clinical trial that was registered a priori (clinicaltrials.gov #NCT04172038).

A Sequential Multiple-Assignment Randomized Trial (SMART) for Stepped Care Management of Low Back Pain in the Military Health System: A Trial Protocol.

BACKGROUND: The Defense Health Agency has prioritized system-level pain management initiatives within the Military Health System (MHS), with low back pain as one of the key focus areas. A stepped care model focused on nonpharmacologic treatment to promote self-management is recommended. Implementation of stepped care is complicated by lack of information on the most effective nonpharmacologic strategies and how to sequence and tailor the various available options. The Sequential Multiple-Assignment Randomization Trial for Low Back Pain (SMART LBP) is a multisite pragmatic trial using a SMART design to assess the effectiveness of nonpharmacologic treatments for chronic low back pain. DESIGN: This SMART trial has two treatment phases. Participants from three military treatment facilities are randomized to 6 weeks of phase I treatment, receiving either physical therapy (PT) or Army Medicine's holistic Move2Health (M2H) program in a package specific to low back pain. Nonresponders to treatment in phase I are again randomized to phase II treatment of combined M2H + PT or mindfulness-based treatment using the Mindfulness-Oriented Recovery Enhancement (MORE) program. The primary outcome is the Patient-Reported Outcomes Measurement Information System pain interference computer-adapted test score. SUMMARY: This trial is part of an initiative funded by the National Institutes of Health, Veterans Affairs, and the Department of Defense to establish a national infrastructure for effective system-level management of chronic pain with a focus on nonpharmacologic treatments. The results of this study will provide important information on nonpharmacologic care for chronic LBP in the MHS embedded within a stepped care framework.

Stakeholder Engagement in Pragmatic Clinical Trials: Emphasizing Relationships to Improve Pain Management Delivery and Outcomes.

BACKGROUND: The NIH-DOD-VA Pain Management Collaboratory (PMC) supports 11 pragmatic clinical trials (PCTs) on nonpharmacological approaches to management of pain and co-occurring conditions in U.S. military and veteran health organizations. The Stakeholder Engagement Work Group is supported by a separately funded Coordinating Center and was formed with the goal of developing respectful and productive partnerships that will maximize the ability to generate trustworthy, internally valid findings directly relevant to veterans and military service members with pain, front-line primary care clinicians and health care teams, and health system leaders. The Stakeholder Engagement Work Group provides a forum to promote success of the PCTs in which principal investigators and/or their designees discuss various stakeholder engagement strategies, address challenges, and share experiences. Herein, we communicate features of meaningful stakeholder engagement in the design and implementation of pain management pragmatic trials, across the PMC. DESIGN: Our collective experiences suggest that an optimal stakeholder-engaged research project involves understanding the following: i) Who are research stakeholders in PMC trials? ii) How do investigators ensure that stakeholders represent the interests of a study's target treatment population, including individuals from underrepresented groups?, and iii) How can sustained stakeholder relationships help overcome implementation challenges over the course of a PCT? SUMMARY: Our experiences outline the role of stakeholders in pain research and may inform future pragmatic trial researchers regarding methods to engage stakeholders effectively.

Imaging with ultrasound in physical therapy: What is the PT's scope of practice? A competency-based educational model and training recommendations.

Physical therapists employ ultrasound (US) imaging technology for a broad range of clinical and research purposes. Despite this, few physical therapy regulatory bodies guide the use of US imaging, and there are limited continuing education opportunities for physical therapists to become proficient in using US within their professional scope of practice. Here, we (i) outline the current status of US use by physical therapists; (ii) define and describe four broad categories of physical therapy US applications (ie, rehabilitation, diagnostic, intervention and research US); (iii) discuss how US use relates to the scope of high value physical therapy practice and (iv) propose a broad framework for a competency-based education model for training physical therapists in US. This paper only discusses US imaging-not 'therapeutic' US. Thus, 'imaging' is implicit anywhere the term 'ultrasound' is used.

Developing predictive models for return to work using the Military Power, Performance and Prevention (MP3) musculoskeletal injury risk algorithm: a study protocol for an injury risk assessment programme.

BACKGROUND: Musculoskeletal injuries are a primary source of disability in the US Military, and low back pain and lower extremity injuries account for over 44% of limited work days annually. History of prior musculoskeletal injury increases the risk for future injury. This study aims to determine the risk of injury after returning to work from a previous injury. The objective is to identify criteria that can help predict likelihood for future injury or re-injury. METHODS: There will be 480 active duty soldiers recruited from across four medical centres. These will be patients who have sustained a musculoskeletal injury in the lower extremity or lumbar/thoracic spine, and have now been cleared to return back to work without any limitations. Subjects will undergo a battery of physical performance tests and fill out sociodemographic surveys. They will be followed for a year to identify any musculoskeletal injuries that occur. Prediction algorithms will be derived using regression analysis from performance and sociodemographic variables found to be significantly different between injured and non-injured subjects. DISCUSSION: Due to the high rates of injuries, injury prevention and prediction initiatives are growing. This is the first study looking at predicting re-injury rates after an initial musculoskeletal injury. In addition, multivariate prediction models appear to have move value than models based on only one variable. This approach aims to validate a multivariate model used in healthy non-injured individuals to help improve variables that best predict the ability to return to work with lower risk of injury, after a recent musculoskeletal injury. TRIAL REGISTRATION NUMBER: NCT02776930.

What Risk Factors Are Associated With Musculoskeletal Injury in US Army Rangers? A Prospective Prognostic Study.

BACKGROUND: Musculoskeletal injury is the most common reason that soldiers are medically not ready to deploy. Understanding intrinsic risk factors that may place an elite soldier at risk of musculoskeletal injury may be beneficial in preventing musculoskeletal injury and maintaining operational military readiness. Findings from this population may also be useful as hypothesis-generating work for particular civilian settings such as law enforcement officers (SWAT teams), firefighters (smoke jumpers), or others in physically demanding professions. QUESTIONS/PURPOSES: The purposes of this study were (1) to examine whether using baseline measures of self-report and physical performance can identify musculoskeletal injury risk; and (2) to determine whether a combination of predictors would enhance the accuracy for determining future musculoskeletal injury risk in US Army Rangers. METHODS: Our study was a planned secondary analysis from a prospective cohort examining how baseline factors predict musculoskeletal injury. Baseline predictors associated with musculoskeletal injury were collected using surveys and physical performance measures. Survey data included demographic variables, injury history, and biopsychosocial questions. Physical performance measures included ankle dorsiflexion, Functional Movement Screen, lower and upper quarter Y-balance test, hop testing, pain provocation, and the Army Physical Fitness Test (consisting of a 2-mile run and 2 minutes of sit-ups and push-ups). A total of 320 Rangers were invited to enroll and 211 participated (66%). Occurrence of musculoskeletal injury was tracked for 1 year using monthly injury surveillance surveys, medical record reviews, and a query of the Department of Defense healthcare utilization database. Injury surveillance data were available on 100% of the subjects. Receiver operator characteristic curves and accuracy statistics were calculated to identify predictors of interest. A logistic regression equation was then calculated to find the most pertinent set of predictors. Of the 188 Rangers (age, 23.3 ± 3.7 years; body mass index, 26.0 ± 2.4 kg/m(2)) remaining in the cohort, 85 (45.2%) sustained a musculoskeletal injury of interest. RESULTS: Smoking, prior surgery, recurrent prior musculoskeletal injury, limited-duty days in the prior year for musculoskeletal injury, asymmetrical ankle dorsiflexion, pain with Functional Movement Screen clearing tests, and decreased performance on the 2-mile run and 2-minute sit-up test were associated with increased injury risk. Presenting with one or fewer predictors resulted in a sensitivity of 0.90 (95% confidence interval [CI], 0.83-0.95), and having three or more predictors resulted in a specificity of 0.98 (95% CI, 0.93-0.99). The combined factors that contribute to the final multivariable logistic regression equation yielded an odds ratio of 4.3 (95% CI, 2.0-9.2), relative risk of 1.9 (95% CI, 1.4-2.6), and an area under the curve of 0.64. CONCLUSIONS: Multiple factors (musculoskeletal injury history, smoking, pain provocation, movement tests, and lower scores on physical performance measures) were associated with individuals at risk for musculoskeletal injury. The summation of the number of risk factors produced a highly sensitive (one or less factor) and specific (three or more factors) model that could potentially be used to effectively identify and intervene in those persons with elevated risk for musculoskeletal injury. Future research should establish if screening and intervening can improve musculoskeletal health and if our findings among US Army Rangers translate to other occupations or athletes. LEVEL OF EVIDENCE: Level II, prognostic study.

Leveraging technology: creating and sustaining changes for health.

OBJECTIVE: The rapid growth and evolution of health-related technology capabilities are driving an established presence in the marketplace and are opening up tremendous potential to minimize and/or mitigate barriers associated with achieving optimal health, performance, and readiness. This article summarizes technology-based strategies that promote healthy habits related to physical activity, nutrition, and sleep. MATERIALS AND METHODS: The Telemedicine and Advanced Technology Research Center convened a workshop titled "Leveraging Technology: Creating & Sustaining Changes for Health" (May 29-30, 2013, Fort Detrick, MD). Participants included experts from academia (n=3), government (n=33), and industry (n=16). A modified Delphi method was used to establish expert consensus in six topic areas: (1) physical activity, (2) nutrition, (3) sleep, (4) incentives for behavior change, (5) usability/interoperability, and (6) mobile health/open platform. RESULTS: Overall, 162 technology features, constructs, and best practices were reviewed and prioritized for physical activity monitors (n=29), nutrition monitors (n=35), sleep monitors (n=24), incentives for change (n=36), usability and interoperability (n=25), and open data (n=13). CONCLUSIONS: Leading practices, gaps, and research needs for technology-based strategies were identified and prioritized. This information can be used to provide a research and development road map for (1) leveraging technology to minimize barriers to enhancing health and (2) facilitating evidence-based techniques to create and sustain healthy behaviors.

Clinical measures associated with dynamic balance and functional movement.

Decreased balance and impaired functional movement have been linked with increased injury risk. The purpose of our study was to determine the association between specific measures of power, strength, flexibility, balance, and endurance compared with more global measures of dynamic balance, using the Y-Balance Test (YBT), and functional movement, using the functional movement screen (FMS), in healthy soldiers. Our participants (n = 64; 53 men, 11 women) were healthy active duty service members (25.2 ± 3.8 years, 25.1 ± 3.1 kg·m(-2)). Seventeen tests with 38 associated measures of strength, power, flexibility, endurance, balance, and functional measures were assessed. A significant Pearson product moment correlation (r > 0.2 and p < 0.01) was used to narrow the number of variables of interest. Two hierarchical stepwise regression analyses were performed to determine the most parsimonious set of variables associated with the YBT and FMS performance scores. Our results included a 4 variable model (F = 13.4, p < 0.001) that was associated with YBT scores (R = 0.72, R2 = 0.51). Superior performance on the YBT was associated with better performance on the FMS lunge and upper trunk mobility tests, decreased number of hops during a 6-m hop test, and greater gastrocnemius flexibility. A second 4 variable model (F = 11.813, p < 0.001) was associated with FMS scores (R = 0.70, R2 = 0.50). Superior performance on the FMS was associated with greater anterior reach on the YBT, greater distance on the crossover hop test, increased hamstring flexibility, and higher levels of self-reported function through the lower-extremity functional scale. Physical fitness leaders and clinicians could use these models to inform decision making when developing and assessing the outcomes of a personalized intervention program for those with low FMS and YBT scores.

Joint mobilization forces and therapist reliability in subjects with knee osteoarthritis.

OBJECTIVES: This study determined biomechanical force parameters and reliability among clinicians performing knee joint mobilizations. METHODS: Sixteen subjects with knee osteoarthritis and six therapists participated in the study. Forces were recorded using a capacitive-based pressure mat for three techniques at two grades of mobilization, each with two trials of 15 seconds. Dosage (force-time integral), amplitude, and frequency were also calculated. Analysis of variance was used to analyze grade differences, intraclass correlation coefficients determined reliability, and correlations assessed force associations with subject and rater variables. RESULTS: Grade IV mobilizations produced higher mean forces (P<0.001) and higher dosage (P<0.001), while grade III produced higher maximum forces (P = 0.001). Grade III forces (Newtons) by technique (mean, maximum) were: extension 48, 81; flexion 41, 68; and medial glide 21, 34. Grade IV forces (Newtons) by technique (mean, maximum) were: extension 58, 78; flexion 44, 60; and medial glide 22, 30. Frequency (Hertz) ranged between 0.9-1.1 (grade III) and 1.4-1.6 (grade IV). Intra-clinician reliability was excellent (>0.90). Inter-clinician reliability was moderate for force and dosage, and poor for amplitude and frequency. DISCUSSION: Force measurements were consistent with previously reported ranges and clinical constructs. Grade III and grade IV mobilizations can be distinguished from each other with differences for force and frequency being small, and dosage and amplitude being large. Intra-clinician reliability was excellent for all biomechanical parameters and inter-clinician reliability for dosage, the main variable of clinical interest, was moderate. This study quantified the applied forces among multiple clinicians, which may help determine optimal dosage and standardize care.

Predicting Subsequent Injury after Being Cleared to Return to Work from Initial Lumbar or Lower Extremity Injury.

PURPOSE: The purpose of this study is to develop a model to predict re-injury after being cleared to return to full duty from an initial injury. METHODS: This was a prediction model derivation cohort study. Military service members cleared for unrestricted full duty after sustaining a musculoskeletal injury were enrolled from three large military hospitals. Medical history, demographics, psychological profile, physical performance (Y-Balance Test™, Functional Movement Screen™, Selective Functional Movement Assessment, triple hop, closed chain ankle dorsiflexion, 2-mile run, 75% bodyweight carry time), and past injury history were assessed. Monthly text messages, medical records and limited duty databases were used to identify injuries resulting in time lost from work in the following year. RESULTS: Four hundred fifty participants (65 females), ages 18 to 45 yr were analyzed. Fifteen variables were included in the final model. The area under the curve was 0.74 (95% confidence interval, 0.69-0.80), indicating good performance. The calibration score of the model was 1.05 (95% confidence interval, 0.80-1.30) indicating very good performance. With an injury incidence in our cohort of 38.0%, the treat all net benefit was 0.000, and the net benefit of our predictive model was 0.251. This means 25 additional soldiers out of every 100 were correctly identified as high risk for injury compared with not using a prediction model at all. CONCLUSIONS: This multivariable model accurately predicted injury risk after returning for full duty and was better than not using a prediction model at all (an additional 25 of every 100 tactical athletes were correctly identified). This model provides guidance for proper decision making about when these individuals are not ready to return to full duty, with higher risk of a subsequent injury.

Physiology of Health and Performance: Enabling Success of Women in Combat Arms Roles.

INTRODUCTION: The modern female soldier has yet to be fully characterized as she steps up to fill new combat roles that have only recently been opened to women. Both U.S. and U.K. military operational research efforts are supporting a science-based evolution of physical training and standards for female warfighters. The increasing representation of women in all military occupations makes it possible to discover and document the limits of female physiological performance. METHOD: An informal Delphi process was used to synthesize an integrated concept of current military female physiological research priorities and emerging findings using a panel of subject matter experts who presented their research and perspectives during the second Women in Combat Summit hosted by the TriService Nursing Research Program in February 2021. RESULTS: The physical characteristics of the modern soldier are changing as women train for nontraditional military roles, and they are emerging as stronger and leaner. Capabilities and physique will likely continue to evolve in response to new Army standards and training programs designed around science-based sex-neutral requirements. Strong bones may be a feature of the female pioneers who successfully complete training and secure roles traditionally reserved for men. Injury risk can be reduced by smarter, targeted training and with attention directed to female-specific hormonal status, biomechanics, and musculoskeletal architecture. An "estrogen advantage" appears to metabolically support enhanced mental endurance in physically demanding high-stress field conditions; a healthy estrogen environment is also essential for musculoskeletal health. The performance of female soldiers can be further enhanced by attention to equipment that serves their needs with seemingly simple solutions such as a suitable sports bra and personal protective equipment that accommodates the female anatomy. CONCLUSIONS: Female physiological limits and performance have yet to be adequately defined as women move into new roles that were previously developed and reserved for men. Emerging evidence indicates much greater physical capacity and physiological resilience than previously postulated.

Cross-Cutting Lessons Learned During the COVID-19 Pandemic-the Walter Reed Army Institute of Research Experience.

INTRODUCTION: At the start of the coronavirus disease 2019 (COVID-19) pandemic, Walter Reed Army Institute of Research (WRAIR) mobilized to rapidly conduct medical research to detect, prevent, and treat the disease in order to minimize the impact of the pandemic on the health and readiness of U.S. Forces. WRAIR's major efforts included the development of the Department of Defense (DoD) COVID-19 vaccine candidate, researching novel drug therapies and monoclonal antibodies, refining and scaling-up diagnostic capabilities, evaluating the impact of viral diversity, assessing the behavioral health of Soldiers, supporting U.S. DoD operational forces overseas, and providing myriad assistance to allied nations. WRAIR personnel have also filled key roles within the whole of government response to the pandemic. WRAIR had to overcome major pandemic-related operational challenges in order to quickly execute a multimillion-dollar portfolio of COVID-19 research. Consequently, the organization learned lessons that could benefit other leaders of medical research organizations preparing for the next pandemic. MATERIALS AND METHODS: We identified lessons learned using a qualitative thematic analysis of 76 observation/recommendation pairs from across the organization. These lessons learned were organized under the Army's four pillars of readiness (staffing, training, equipping, and leadership development). To this framework, we added organizing and leading to best capture our experiences within the context of pandemic response. RESULTS: The major lessons learned for organizing were: (1) the pandemic created a need to rapidly pivot to new scientific priorities; (2) necessary health and safety precautions disrupted the flow of normal science and put programs at risk of missing milestones; (3) relationships with partners and allies facilitated medical diplomacy and advancement of U.S. national military and economic goals; and (4) a successful response required interoperability within and across multiple organizations. For equipping: (1) existing infrastructure lacked sufficient capacity and technical capability to allow immediate countermeasure development; (2) critical supply chains were strained; and (3) critical information system function and capacity were suddenly insufficient under maximum remote work. For staffing and training: (1) successful telework required rapid shifts in management, engagement, and accountability methods; and (2) organizational policies and processes had to adapt quickly to support remote staffing. For leading and leadership development (1) engaged, hopeful, and empathetic leadership made a difference; and (2) the workforce benefitted from concerted leadership communication that created a shared understanding of shifting priorities as well as new processes and procedures. CONCLUSIONS: An effective pandemic response requires comprehensive institutional preparedness that facilitates flexibility and surge capacity. The single most important action leaders of medical research organizations can take to prepare for the next pandemic is to develop a quick-reaction force that would activate under prespecified criteria to manage reprioritization of all science and support activities to address pandemic response priorities at the velocity of relevance.

Abdominal and lumbar multifidus muscle size and symmetry at rest and during contracted States. Normative reference ranges.

OBJECTIVES: The purpose of this study was to establish reference values for abdominal and lumbar multifidus muscles at rest and while contracted in a sample of active healthy adults. METHODS: Three hundred forty participants (mean age ± SD, 21.8 ± 3.9 years; 96 females and 244 males) completed the study. Ultrasound imaging was used to assess the thickness of the transversus abdominis, internal and external oblique, rectus abdominis, and lumbar multifidus muscles. Additionally, the cross-sectional area of the rectus abdominis was assessed. RESULTS: Although males had significantly thicker muscles than females (P < .05), the relative change in thickness during specified tasks was equivalent. Overall, relative muscle thickness and symmetry were similar to previous studies using smaller sample sizes. CONCLUSIONS: These findings provide a robust data set of muscle thickness values measured by ultrasound imaging and can be used for comparison to those with pain, abnormal function, and pathologic conditions.

Automation to improve efficiency of field expedient injury prediction screening.

Musculoskeletal injuries are a primary source of disability in the U.S. Military. Physical training and sports-related activities account for up to 90% of all injuries, and 80% of these injuries are considered overuse in nature. As a result, there is a need to develop an evidence-based musculoskeletal screen that can assist with injury prevention. The purpose of this study was to assess the capability of an automated system to improve the efficiency of field expedient tests that may help predict injury risk and provide corrective strategies for deficits identified. The field expedient tests include survey questions and measures of movement quality, balance, trunk stability, power, mobility, and foot structure and mobility. Data entry for these tests was automated using handheld computers, barcode scanning, and netbook computers. An automated algorithm for injury risk stratification and mitigation techniques was run on a server computer. Without automation support, subjects were assessed in 84.5 ± 9.1 minutes per subject compared with 66.8 ± 6.1 minutes per subject with automation and 47.1 ± 5.2 minutes per subject with automation and process improvement measures (p < 0.001). The average time to manually enter the data was 22.2 ± 7.4 minutes per subject. An additional 11.5 ± 2.5 minutes per subject was required to manually assign an intervention strategy. Automation of this injury prevention screening protocol using handheld devices and netbook computers allowed for real-time data entry and enhanced the efficiency of injury screening, risk stratification, and prescription of a risk mitigation strategy.

Challenges With Engaging Military Stakeholders for Clinical Research at the Point of Care in the U.S. Military Health System.

The DoD has a specific mission that creates unique challenges for the conduct of clinical research. These unique challenges include (1) the fact that medical readiness is the number one priority, (2) understanding the role of military culture, and (3) understanding the highly transient flow of operations. Appropriate engagement with key stakeholders at the point of care, where research activities are executed, can mean the difference between success and failure. These key stakeholders include the beneficiaries of the study intervention (patients), clinicians delivering the care, and the military and clinic leadership of both. Challenges to recruitment into research studies include military training, temporary duty, and deployments that can disrupt availability for participation. Seeking medical care is still stigmatized in some military settings. Uniformed personnel, including clinicians, patients, and leaders, are constantly changing, often relocating every 2-4 years, limiting their ability to support clinical trials in this setting which often take 5-7 years to plan and execute. When relevant stakeholders are constantly changing, keeping them engaged becomes an enduring priority. Military leaders are driven by the ability to meet the demands of the assigned mission (readiness). Command endorsement and support are critical for service members to participate in stakeholder engagement panels or clinical trials offering novel treatments. To translate science into relevant practice within the Military Health System, early engagement with key stakeholders at the point of care and addressing mission-relevant factors is critical for success.

Predictive models for musculoskeletal injury risk: why statistical approach makes all the difference.

Objective: Compare performance between an injury prediction model categorising predictors and one that did not and compare a selection of predictors based on univariate significance versus assessing non-linear relationships. Methods: Validation and replication of a previously developed injury prediction model in a cohort of 1466 service members followed for 1 year after physical performance, medical history and sociodemographic variables were collected. The original model dichotomised 11 predictors. The second model (M2) kept predictors continuous but assumed linearity and the third model (M3) conducted non-linear transformations. The fourth model (M4) chose predictors the proper way (clinical reasoning and supporting evidence). Model performance was assessed with R2, calibration in the large, calibration slope and discrimination. Decision curve analyses were performed with risk thresholds from 0.25 to 0.50. Results: 478 personnel sustained an injury. The original model demonstrated poorer R2 (original:0.07; M2:0.63; M3:0.64; M4:0.08), calibration in the large (original:-0.11 (95% CI -0.22 to 0.00); M2: -0.02 (95% CI -0.17 to 0.13); M3:0.03 (95% CI -0.13 to 0.19); M4: -0.13 (95% CI -0.25 to -0.01)), calibration slope (original:0.84 (95% CI 0.61 to 1.07); M2:0.97 (95% CI 0.86 to 1.08); M3:0.90 (95% CI 0.75 to 1.05); M4: 081 (95% CI 0.59 to 1.03) and discrimination (original:0.63 (95% CI 0.60 to 0.66); M2:0.90 (95% CI 0.88 to 0.92); M3:0.90 (95% CI 0.88 to 0.92); M4: 0.63 (95% CI 0.60 to 0.66)). At 0.25 injury risk, M2 and M3 demonstrated a 0.43 net benefit improvement. At 0.50 injury risk, M2 and M3 demonstrated a 0.33 net benefit improvement compared with the original model. Conclusion: Model performance was substantially worse in the models with dichotomised variables. This highlights the need to follow established recommendations when developing prediction models.

Recovery, Rehabilitation, and Return to Full Duty in a Military Population After a Recent Injury: Differences Between Lower-Extremity and Spine Injuries.

PURPOSE: To compare readiness to return to duty in soldiers following recent lower-extremity versus spine injury. The secondary purposes were to provide normative data for the Selective Functional Movement Assessment Top Tier movements (SFMA-TTM) and assess the association between SFMA-TTM scores and future injury occurrence, comparing injuries of the lower extremity and thoracic/lumbar spine. METHODS: SFMA was rated by trained assessors on 480 U.S. Army soldiers within 2 weeks of being cleared to return to duty after recent lower-extremity or lumbar/thoracic injury. Participants were followed for 1 year to determine incidence of subsequent time-loss injury. RESULTS: Only 74.4% of soldiers felt 100% mission capable when returning to full duty (73.6% lower-extremity; 76.5% spine). After 1 year, 37.9% had sustained a time-loss injury, and pain with movement at baseline was associated with higher odds for having an injury (odd ratio 1.53 95% confidence interval 1.04-2.24; P = .032). Almost all (99.8%) had at least 1 dysfunctional pattern, and 44.1% had pain with at least 1 movement (40.3% with previous lower-extremity injury; 54.6% with previous spine injury) after being cleared to return to duty. CONCLUSIONS: One in four patients did not feel 100% mission capable upon being cleared for full duty. Pain with movement was also associated with future injury. Regardless of recent injury type, 99.8% of soldiers returned to full unrestricted duty with at least 1dysfunctional movement pattern and 44.1% had pain with at least 1 of the SFMA-TTM movements. LEVEL OF EVIDENCE: Level III, retrospective comparative cohort study.