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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., (Copyright © 2023 Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)

Ethnic-racial under-represented students (URM) exhibit greater attrition rates from physical therapy (PT) doctoral programs. Most predictive analytics in PT education are based on predictors of success in passing the licensure examination. However, data predicting the reasons why these groups of URM students withdraw from PT school are scarce. Admissions variables and academic perform¬ance of seven entry-level Doctor of Physical Therapy (DPT) cohorts (n = 191) from a US university were analyzed from their application and admission through graduation or withdrawal from the program. Through a binary logistic regression, it was found that the main predictors of with¬drawal from the DPT program were URM status (X2 = 8.77; p = 0.004; OR = 21.4) and failing the first practical exam (X2 = 12.30; p < 0.001; OR = 14.2). Those from URM back¬grounds were more than 20 times more likely to withdraw from PT school, while failing the first clinical practical exam increased 14 times the odds of withdrawing from PT school. Admission criteria and targeted retention strategies need to be addressed to ensure the success of URM students to ensure a more diverse PT workforce.

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.

Background: Musculoskeletal injuries are a primary source of disability. Understanding how risk factors predict injury is necessary to individualize and enhance injury reduction programs., Hypothesis: Because of the multifactorial nature of musculoskeletal injuries, multiple risk factors will provide a useful method of categorizing warrior athletes based on injury risk., Study Design: Prospective observational cohort study., Level of Evidence: Level 2., Methods: Baseline data were collected on 922 US Army soldiers/warrior athletes (mean age, 24.7 ± 5.2 years; mean body mass index, 26.8 ± 3.4 kg/m 2 ) using surveys and physical measures. Injury occurrence and health care utilization were collected for 1 year. Variables were compared in healthy versus injured participants using independent t tests or chi-square analysis. Significantly different factors between each group were entered into a logistic regression equation. Receiver operating characteristic curve and accuracy statistics were calculated for regression variables., Results: Of the 922 warrior athletes, 38.8% suffered a time-loss injury (TLI). Overall, 35 variables had a significant relationship with TLIs. The logistic regression equation, consisting of 11 variables of interest, was significant (adjusted R 2 = 0.21; odds ratio, 5.7 [95% CI, 4.1-7.9]; relative risk, 2.5 [95% CI, 2.1-2.9]; area under the curve, 0.73). Individuals with 2 variables had a sensitivity of 0.89, those with 7 or more variables had a specificity of 0.94., Conclusion: The sum of individual risk factors (prior injury, prior work restrictions, lower perceived recovery from injury, asymmetrical ankle dorsiflexion, decreased or asymmetrical performance on the Lower and Upper Quarter Y-Balance test, pain with movement, slower 2-mile run times, age, and sex) produced a highly sensitive and specific multivariate model for TLI in military servicemembers., Clinical Relevance: A better understanding of characteristics associated with future injury risk can provide a foundation for prevention programs designed to reduce medical costs and time lost.

Background: To consistently prepare physical therapist students for their first full-time clinical experience, the entry-level curriculum must provide and assess competency in the essential knowledge, skills, attitudes, and professional behaviors., Objective: The purpose of this Delphi study was to develop consensus on a core set of elements that should be demonstrated by physical therapist students prior to entry into their first full-time clinical experience. A second aim was to obtain the recommended competency levels and assessment methods., Design: The study was conducted using the Delphi method., Methods: Purposive selection and snowball sampling techniques were used to recruit clinical instructors, recent graduates, directors or academic coordinators of clinical education, and academic faculty. Four web-based survey rounds were used to achieve consensus, defined as agreement among ≥80% of respondents. The first round gathered demographic information on respondents and identified elements that were deemed essential; the second collected information about clarity and redundancy in the elements provided; the third asked participants to rank their agreement with elements and themes; and the fourth gathered the level of competency that physical therapist students should demonstrate prior to beginning a first full-time clinical experience., Results: Consensus revealed 95 elements, categorized under 14 themes, which were deemed essential for readiness for the first clinical experience. Levels of competency for each element were identified., Limitations: Participants might not have represented all academic programs, practice settings, and geographic locations., Conclusion: This study identified the specific knowledge, skills, attitudes, and professional behaviors in which all physical therapist students in the United States need to demonstrate competency before their first clinical experience, regardless of school or setting, which would allow learning experiences to be tailored appropriately.

Background: Musculoskeletal injuries during military service are a primary source of disability, resulting in 2.4 million annual health care visits and 25 million limited-duty days. While the injury incidence during basic training is well documented, there is little understanding of injury distribution by organization type in the US Army following initial training., Objective: To compare injury incidence, distribution, and impact across various military units., Methods: In this prospective observational cohort study, comprehensive injury data from subject questionnaires and medical chart reviews were collected over 12 months for 1430 initially healthy Army personnel, representing combat, combat support, combat service support, and ranger units. Health care utilization and time loss due to injury were also collected., Results: Of 1430 soldiers, 481 (33.6%) had time-loss injury, 222 (15.5%) were injured without limited work, 60 (4.2%) reported an injury but did not seek medical care, and 667 (46.6%) were uninjured. Across the whole sample, injuries were responsible for 5.9 ±14.4 medical visits per soldier, 21 902 days of limited work, and $1 337 000 ($1901 ± $6535 per soldier) in medical costs. Considering only those reporting injury, each person averaged 36.3 ± 59.7 limited-work days. The injury incidence was highest in combat service support units (65.6%), with a risk ratio 1.60 times that of the reference group (combat, 41.1%)., Conclusion: Combat support and combat service support personnel were more likely to have 1 or more injuries compared to rangers and combat personnel. The higher relative risk of injury in support units should be explored further. J Orthop Sports Phys Ther 2018;48(10):749-757. Epub 22 May 2018. doi:10.2519/jospt.2018.7979.

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., Competing Interests: Competing interests: None declared., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Context:  Although inactivity, being overweight, smoking, and a history of injury are identified as risk factors for poor health and injury, few authors have examined their association on physical performance. Young adults may be more likely to adopt healthier lifestyles if they understand the effect of health behaviors on performance., Objective:  To determine the association of being overweight, smoking, inactivity, and a history of injury with physical performance., Design:  Cross-sectional study., Setting:  Military population., Patients or Other Participants:  Active-duty service members (N = 1466; 1380 men, 86 women; age = 24.7 ± 5.0 years; body mass index = 26.7 ± 3.4 kg/m 2 )., Main Outcome Measure(s):  Participants performed 8 measures (the triple-crossover hop for distance, the 6-m timed-hop test, the Functional Movement Screen, the Lower Quarter Y-Balance Test, the Upper Quarter Y-Balance Test, and the 3-event Army Physical Fitness Test) for evaluation of endurance, strength, muscular endurance, power, agility, balance, and motor control. Participants were categorized based on the number of health risk factors present. Using an analysis of covariance, we assessed the relationship between risk factors and physical performance with age and sex as covariates., Results:  Compared with those who had no risk factors (27.9% of men, 34.9% of women), physical performance was worse in those who had 1, 2, or 3 to 4 risk factors present by 4.3%, 6.7%, and 10.3%, respectively. Decrements in performance for those with 3 to 4 risk factors ranged from 3.3% to 14.4%., Conclusions:  An unhealthy lifestyle habit or a history of injury was negatively associated with physical performance. Physical performance decrements were associated with the number of risk factors present. Understanding how risk factors contribute to decreased physical performance may enable clinicians to improve compliance with injury-prevention programs in occupational settings in which a young and relatively healthy workforce may be more concerned about performance than health.

Performance on movement tests helps to predict injury risk in a variety of physically active populations. Understanding baseline measures for normal is an important first step., Objectives: Determine differences in physical performance assessments and describe normative values for these tests based on military unit type., Methods: Assessment of power, balance, mobility, motor control, and performance on the Army Physical Fitness Test were assessed in a cohort of 1,466 soldiers. Analysis of variance was performed to compare the results based on military unit type (Rangers, Combat, Combat Service, and Combat Service Support) and analysis of covariance was performed to determine the influence of age and gender., Results: Rangers performed the best on all performance and fitness measures (p < 0.05). Combat soldiers performed better than Combat Service and Service Support soldiers on several physical performance tests and the Army Physical Fitness Test (p < 0.05). Performance in Combat Service and Service Support soldiers was equivalent on most measures (p < 0.05)., Conclusions: Functional performance and level of fitness varied significantly by military unit type. Understanding these differences will provide a foundation for future injury prediction and prevention strategies., (Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.)

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.

Objectives: Determine the influence of age and sex and describe normative data on field expedient tests associated with power, balance, trunk stability, mobility, and functional movement in a military population., Methods: Participants (n = 247) completed a series of clinical and functional tests, including closed-chain ankle dorsiflexion (DF), Functional Movement Screen (FMS), Y-Balance Test Lower Quarter (YBT-LQ), Y-Balance Test Upper Quarter (YBT-UQ), single leg vertical jump (SLVJ), 6-m timed hop (6-m timed), and triple hop. Descriptive statistics were calculated. Analysis of variance tests were performed to compare the results based on sex and age (<30 years, >30 years)., Results: Service members demonstrated DF of 34.2 ± 6.1°, FMS composite score of 16.2 ± 2.2, YBT-LQ normalized composite score of 96.9 ± 8.6%, YBT-UQ normalized composite score of 87.6 ± 9.6%, SLVJ of 26.9 ± 8.6 cm, 6-m hop of 2.4 ± 0.5 seconds, and a triple hop of 390.9 ± 110.8 cm. Men performed greater than women (p < 0.05) on the YBT-LQ, YBT-UQ, SLVJ, 6-m timed, and triple hop. Those <30 years of age performed better than older participants (p < 0.05) on the DF, FMS, YBT-LQ, SLVJ, 6-m hop, and triple hop., Conclusions: Findings provide normative data on military members. Men performed better on power, balance, and trunk stability tests, whereas younger individuals performed better on power, balance, mobility, and functional movement., (Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.)

Background: Lower extremity overuse injuries are detrimental to military readiness. Extremes of arch height and heavy loads carried by military personnel are associated with increased risk for overuse injury. Little is known regarding the impact of load carriage on plantar pressure distributions during gait., Objective: The objective of this study was to determine how load carriage affects plantar pressure distributions during gait in individuals with varying arch types., Design: A cross-sectional, repeated-measures design was used for the study., Methods: The study was performed at a research laboratory at Fort Sam Houston, Texas. Service members who were healthy and weighing ≥70 kg were enrolled in the study. The participants (97 men, 18 women; mean age=31.3 years, SD=5.6; mean weight=86.0 kg, SD=11.0) were categorized as having high-, normal-, or low-arched feet on the basis of published cutoff values for the arch height index. Plantar pressure measurements were obtained with the use of an in-shoe pressure measurement system while participants wore combat boots and walked on a treadmill under 3 loaded conditions (uniform, 20-kg load, and 40-kg load). Maximal force (MaxF) and force-time integral (FTI) were assessed with the use of a 9-sector mask to represent regions of the foot. A 3 × 3 repeated-measures analysis of variance was used for analysis across the levels of load and arch type., Results: A significant interaction existed between arch type and load for MaxF and FTI in the medial midfoot, with greater force in low-arched feet. In the medial forefoot, MaxF and FTI were greatest in high-arched feet across all load conditions. In the great toe region, low-arched and normally arched feet had greater MaxF and FTI. The relative distribution of FTI increased proportionately in all regions of the foot regardless of arch type for all load conditions., Limitations: The influence of fatigue, greater loads, and different walking speeds was not assessed., Conclusions: Regardless of arch type, increases in load did not alter the relative distribution of force over the plantar foot during gait. Participants with high-arched feet had greater force in the medial forefoot region, whereas those with normally arched or low-arched feet had greater force in the great toe region, regardless of load. These differences in force distribution may demonstrate different strategies to generate a rigid lever during toe-off.

U.S. military physical therapists have a proud history of providing medical care during operational deployments ranging from war to complex humanitarian emergencies. Regardless of austerity of environment or intensity of hostility, U.S. military physical therapists serve as autonomous providers, evaluating and treating service members with and without physician referral. This perspective article suggests that the versatility of U.S. military physical therapist practice enables them not only to diagnose musculoskeletal injuries but also to provide a wide range of definitive care and rehabilitation, reducing the need for costly evacuation. War is not sport, but the delivery of skilled musculoskeletal physical therapy services as close to the point of injury as possible parallels the sports medicine model for on- or near-field practice. This model that mixes direct access with near-immediate access enhances outcomes, reduces costs, and allows other health care team members to work at the highest levels of their licensure.

The patient was a 17-year-old adolescent male who was referred to a physical therapist for a chief complaint of anterior right hip pain. The physical therapist reviewed the patient's radiographs, which had been completed and interpreted as normal prior to referral, and determined that there were radiographic signs present that may be concerning for an avulsion fracture. Further evaluation through magnetic resonance imaging confirmed the presence of an avulsion fracture at the right anterior superior iliac spine.

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.

Few established measures allow effective quantification of physical performance in severely injured service members. We sought to establish preliminary normative data in 180 healthy, active-duty service members for physical performance measures that can be readily implemented in a clinical setting. Interrater and test-retest reliability and minimal detectable change (MDC) values were also determined. Physical performance testing included self-selected walking velocity on level and uneven terrain, timed stair ascent, the sit-to-stand five times test, the four-square step test, and the 6-minute walk test. Data analysis included descriptive statistics, intraclass correlation coefficients, and MDC. Interrater and test-retest reliability were excellent for all measures (intraclass correlation coefficients >0.75). MDC values for timed measures were <0.3 seconds for interrater comparisons and <1.5 seconds for between-day comparisons. Physical performance measures had a narrow range of normal performance and were reliable and stable between days.

Study Design: Controlled laboratory study., Objective: To explore potential associations between foot posture index (FPI-6) composite scores and dynamic plantar pressure measurements, and to describe each of the 6 subscales and the FPI-6 composite scores across our sample., Background: The FPI-6 is a static foot posture assessment comprised of 6 observations. Extreme scores have been associated with increased injury risk. However, knowledge describing the relationship between FPI-6 scores and plantar pressure distributions during gait is limited., Methods: Participants (n = 1000; 566 males, 434 females) were predominantly active adults (mean ± SD age, 30.6 ± 8.0 years; body mass index, 26.2 ± 3.7 kg/m²), who ran 3.1 ± 1.4 d/wk. Static and dynamic foot characteristics were compared using the FPI-6 and a capacitance-based pressure platform. Correlation and hierarchical stepwise regression analyses were performed to determine the most parsimonious set of dynamic pressure data associated with FPI-6 scores., Results: The mean ± SD FPI-6 score was 3.4 ± 2.9 (range, -6.0 to 11.0). Only 31 participants received a score of -2 (supinated foot) on any FPI-6 subscale. Classification of a pronated foot was 2.4 times more likely than a supinated foot. A 5-variable model (R = 0.57, R2 = 0.32) was developed to describe the association between dynamic plantar pressures and FPI-6 scores., Conclusion: The multivariate model associated with FPI-6 scores comprised clinically plausible variables which inform the association between static and dynamic foot postures. Different cutoff values may be required when using the FPI-6 to screen for individuals with supinated feet, given the limited number of high-arched participants identified by FPI-6 classifications.

Background: Although extreme values of arch height have been associated with increased risk for overuse injury, knowledge is limited regarding the association between arch height and plantar pressure distributions during gait. The primary purpose of this study was to explore which plantar pressure measurements during gait were associated with static arch height and arch height index., Methods: Static arch height, arch height index, and dynamic plantar pressure distributions were collected for 1000 subjects (566 males, 434 females, 30.6 [SD 8.0] years, 171.1 [SD 9.3]cm, 76.9 [SD 14.7]kg). A hierarchical regression analysis was performed to determine the most parsimonious set of plantar pressure parameters associated with arch height. The predicted values were used to calculate dynamic arch height index. Correlation and residual analysis were performed to assess the association between statically and dynamically determined arch height indices., Findings: A 5-variable model (F = 296.6; P < 0.001) was able to describe the relationship between static arch height and the dynamic foot during gait (R =0 .77 [95% CI = 0.75-0.80]). The correlation between the static and dynamically determined arch height indices was r = 0.60 (95% CI = 0.53, 0.63), with a mean residual of 0.000 (SD 0.015)., Interpretation: A multivariate model generated by plantar parameters during gait was able to predict 60% of the variability in static arch height. This model consisted of variables that appear to be clinically plausible and inform the association between static arch height and dynamic foot posture. Future researchers should address the association between statically and dynamically determined AHI values with lower extremity overuse injuries.

Objective: To determine whether changes in the transversus abdominis (TrA) and internal oblique (IO) muscles, as seen on ultrasound imaging, during the active straight leg raise (ASLR) test differ between subjects with and without unilateral lumbopelvic pain., Design: Cross-sectional, case-control study., Setting: Clinical laboratory., Participants: Subjects (n=15) with unilateral symptoms in the lumbopelvic region and age-matched and sex-matched control subjects (n=15)., Interventions: Bilateral measurements of the deep abdominal muscles (TrA and IO) were obtained simultaneously using ultrasound imaging to compare the percent change in muscle thickness from rest with (1) immediately on raising, (2) after a 10-second hold, and (3) within 5 seconds after returning the lower extremity to the plinth., Main Outcome Measure: Percent change in muscle thickness of both muscles from rest to the other 3 time intervals during the ASLR test., Results: The 3-way group x side measured x time and 2-way side measured x time interactions were not significant for either the TrA (P> or =.34) or the IO (P> or =.14) muscles. The 2-way interaction group x time was significant for both the TrA (P=.003) and the IO (P=.02) muscles. On lifting the lower extremity, the control group demonstrated a 23.7% and 11.2% increase in TrA and IO muscle thickness, respectively, while those with lumbopelvic pain demonstrated a 6.4% and 5.7% increase in TrA and IO muscle thickness, respectively., Conclusions: Although subjects with unilateral lumbopelvic pain demonstrated a smaller increase in muscle thickness, during the ASLR test there appears to be a symmetrical response in both of the deep abdominal muscles regardless of which lower extremity is lifted during the ASLR test or the unilateral nature of the symptoms. This study attests to the potential construct validity of using the ASLR test to assess different motor control strategies of the TrA and IO muscles in subjects with unilateral lumbopelvic pain.