An Exploration of Low Back Beliefs of Male Pre-Professional and Professional Dancers.

BACKGROUND: Globally, male dancers are affected by low back pain (LBP) up to 2.5 times more than female dancers. While female dancers' beliefs around LBP and dance-specific low back movements exist, no research has explored male dancers' beliefs. This study aimed to (1) examine the low back beliefs of Australian male professional and pre-professional dancers, and (2) determine if beliefs toward common low back movements and lifting differed when current LBP or history of disabling LBP (DLBP) were considered. METHODS: 40 male dancers (mean age [SD] 26.9 years [7.9]) from a range of dance backgrounds (all participating in ballet) were recruited to complete a cross-sectional survey comprising a beliefs questionnaire considering dance-specific movement and lifting tasks, the Back Pain Attitudes Questionnaire (Back-PAQ) and the Athletic Fear Avoidance Questionnaire (AFAQ). Primary analysis included initial descriptives, a repeated measures ANOVA for movement-specific beliefs and visual thematic analysis for written responses within the belief's questionnaire. Secondary subgroup analysis included independent T-tests for those with/without current LBP and those with/without a history of DLBP. RESULTS: Fourteen dancers reported current LBP and 30 reported a history of DLBP. Dancers held generally negative beliefs toward the low back (Back-PAQ mean 123.1 ± 9.7) with neither subgroup demonstrating significant between-group difference (P < .05). Dance-specific flexion movements were seen as safer than extension movements (P < .05), and more extended-spine lifting was seen as safer than more flexed-spine lifting (P < .05). Dancers experiencing current LBP held less positive beliefs surrounding some dance-specific movements. CONCLUSIONS: Dancers hold negative general beliefs toward the low back irrespective of current or historical DLBP, however their beliefs surrounding dance-specific movements were relatively positive. Dancers' beliefs surrounding some movements were affected by the presence of current LBP, in particular an arabesque and a fish dive.

Parental practices and perspectives on health and digital technology use information seeking for children aged 0-36 months.

BACKGROUND: Parents commonly seek information to support the health and well-being of their children. The increasing availability of health information online and social changes related to the COVID-19 pandemic may have changed what information is sought, from whom, where, and why. This qualitative study explored parents' practices and perspectives on seeking health and digital technology use information for their young children. METHODS: Twenty parents, living in Australia (7 rural, 3 remote, and 10 metropolitan), with children aged 0-36 months completed a semi-structured interview. RESULTS: Parents commonly turned to friends and family and online sources to access health information for their young children. For all types of health information, including digital technology use, themes were identified surrounding aspects of information sources participants valued and accessibility of health services. Perceived credibility and trustworthiness, relatability with other parents, ease of accessibility and convenience, and actionable, bite-sized information were valued. Reduced accessibility to health services due to COVID-19 and geographical location, and need for agency in managing their child's health influenced parents' choice of source of information. Few participants actively sought information about digital technology use for their young child, with the main focus on screen time. CONCLUSION: Interactions with family and friends and online sources are important to parents when accessing health information for their child. Parents valued information sources which they considered trustworthy, credible, and relatable, as well as easily accessible and convenient. SO WHAT?: Dissemination of health information reflecting these values may empower parents during this early stage of parenthood.

Objective Measurement of Posture and Movement in Young Children Using Wearable Sensors and Customised Mathematical Approaches: A Systematic Review.

Given the importance of young children's postures and movements to health and development, robust objective measures are required to provide high-quality evidence. This study aimed to systematically review the available evidence for objective measurement of young (0-5 years) children's posture and movement using machine learning and other algorithm methods on accelerometer data. From 1663 papers, a total of 20 papers reporting on 18 studies met the inclusion criteria. Papers were quality-assessed and data extracted and synthesised on sample, postures and movements identified, sensors used, model development, and accuracy. A common limitation of studies was a poor description of their sample data, yet over half scored adequate/good on their overall study design quality assessment. There was great diversity in all aspects examined, with evidence of increasing sophistication in approaches used over time. Model accuracy varied greatly, but for a range of postures and movements, models developed on a reasonable-sized (n > 25) sample were able to achieve an accuracy of >80%. Issues related to model development are discussed and implications for future research outlined. The current evidence suggests the rapidly developing field of machine learning has clear potential to enable the collection of high-quality evidence on the postures and movements of young children.

Movement quantity and quality: How do they relate to pain and disability in dancers?

OBJECTIVE: This field-based study aimed to determine the association between pre-professional student dancers' movement quantity and quality with (i) pain severity and (ii) pain related disability. METHODS: Pre-professional female ballet and contemporary dance students (n = 52) participated in 4 time points of data collection over a 12-week university semester. At each time point dancers provided self-reported pain outcomes (Numerical Rating Scale as a measure of pain severity and Patient Specific Functional Scale as a measure of pain related disability) and wore a wearable sensor system. This system combined wearable sensors with previously developed machine learning models capable of capturing movement quantity and quality outcomes. A series of linear mixed models were applied to determine if there was an association between dancers' movement quantity and quality over the 4 time points with pain severity and pain related disability. RESULTS: Almost all dancers (n = 50) experienced pain, and half of the dancers experienced disabling pain (n = 26). Significant associations were evident for pain related disability and movement quantity and quality variables. Specifically, greater pain related disability was associated with more light activity, fewer leg lifts to the front, a shorter average duration of leg lifts to the front and fewer total leg lifts. Greater pain related disability was also associated with higher thigh elevation angles to the side. There was no evidence for associations between movement quantity and quality variables and pain severity. DISCUSSION: Despite a high prevalence of musculoskeletal pain, dancers' levels of pain severity and disability were generally low. Between-person level associations were identified between dancers' movement quantity and quality, and pain related disability. These findings may reflect dancers' adaptations to pain related disability, while they continue to dance. This proof-of-concept research provides a compelling model for future work exploring dancers' pain using field-based, serial data collection.

Development of a Machine Learning Model for the Estimation of Hip and Lumbar Angles in Ballet Dancers.

OBJECTIVE: Accurate field-based assessment of dance kinematics is important to understand the etiology, and thus prevention and management, of hip and back pain. The study objective was to develop a machine learning model to estimate thigh elevation and lumbar sagittal plane angles during ballet leg lifting tasks, using wearable sensor data. METHODS: Female dancers (n=30) performed ballet-specific leg lifting tasks to the front, side, and behind the body. Dancers wore six wearable sensors (100 Hz). Data were simultaneously collected using an 18-camera motion analysis system (250 Hz). Due to synchronization and hardware malfunction issues, only 23 dancers had usable data. Using leave-one-out cross-validation, machine learning models were compared with the optic motion capture system using root mean square error (RMSE) in degrees and correlation coefficients (r) over the complete movement profile of each leg lift and mean absolute error (MAE) and Bland Altman plots for peak angle accuracy. RESULTS: The average RMSE for model estimation was 6.8° for thigh elevation angle and 5.6° for lumbar spine sagittal plane angle, with respective MAE of 6.3°and 5.7°. There was a strong correlation between the machine learning model and optic motion capture for peak angle values (thigh r=0.86, lumbar r=0.96). CONCLUSION: The models developed demonstrated an acceptable degree of accuracy for the estimation of thigh elevation angle and lumbar spine sagittal plane angle during dance-specific leg lifting tasks. This provides potential for a near-real-time, field-based measurement system.

Dancers' Joint Strategies for Achieving Turnout in Low and High Friction Conditions.

BACKGROUND: Dancing with legs externally rotated (turnout) is a fundamental element of ballet technique. A reliance on floor friction to achieve turnout may contribute toward the high injury rate in dancers. Joint strategies used by dancers in high and low friction turnout conditions are not well understood. OBJECTIVES: To quantify the lower limb and lumbar spine joint strategies used by female pre-professional dancers to achieve turnout in low-friction (rotation discs) and high-friction (functional and forced) conditions. METHODS: Twenty-three pre-professional female dancers participated in the study. A 12-camera motion analysis system collected hip and knee external rotation (ER), ankle abduction, and lumbar extension angles in three turnout conditions and passive hip ER range of motion angles. Repeated measures ANOVA analysed the differences between joint angles, maximum turnout angle (foot relative to pelvis), and available hip ER. RESULTS: Dancers demonstrated lower knee ER (18.5±4.8°) and ankle abduction (6.0±7.7°) angles during low-friction turnout compared to higher friction conditions (p<0.05). Dancers utilised between 70-83% of available hip ER within all conditions. Low-friction turnout demonstrated greater hip ER contribution within maximum turnout (43%) compared to higher friction conditions. Dancers demonstrated greater lumbar extension angles in low-friction turnout compared to higher friction conditions (p<0.05). CONCLUSIONS: Further hip ER strength training is required to promote greater hip ER range within the position. Rotation discs may be a valuable training tool as dancers demonstrated greater hip ER utilisation with less knee ER and ankle abduction; however, this position did promote undesirable lumbar extension.

An Exploration of Machine-Learning Estimation of Ground Reaction Force from Wearable Sensor Data.

This study aimed to develop a wearable sensor system, using machine-learning models, capable of accurately estimating peak ground reaction force (GRF) during ballet jumps in the field. Female dancers (n = 30) performed a series of bilateral and unilateral ballet jumps. Dancers wore six ActiGraph Link wearable sensors (100 Hz). Data were collected simultaneously from two AMTI force platforms and synchronised with the ActiGraph data. Due to sensor hardware malfunctions and synchronisation issues, a multistage approach to model development, using a reduced data set, was taken. Using data from the 14 dancers with complete multi-sensor synchronised data, the best single sensor was determined. Subsequently, the best single sensor model was refined and validated using all available data for that sensor (23 dancers). Root mean square error (RMSE) in body weight (BW) and correlation coefficients (r) were used to assess the GRF profile, and Bland-Altman plots were used to assess model peak GRF accuracy. The model based on sacrum data was the most accurate single sensor model (unilateral landings: RMSE = 0.24 BW, r = 0.95; bilateral landings: RMSE = 0.21 BW, r = 0.98) with the refined model still showing good accuracy (unilateral: RMSE = 0.42 BW, r = 0.80; bilateral: RMSE = 0.39 BW, r = 0.92). Machine-learning models applied to wearable sensor data can provide a field-based system for GRF estimation during ballet jumps.

Development of a Human Activity Recognition System for Ballet Tasks.

BACKGROUND: Accurate and detailed measurement of a dancer's training volume is a key requirement to understanding the relationship between a dancer's pain and training volume. Currently, no system capable of quantifying a dancer's training volume, with respect to specific movement activities, exists. The application of machine learning models to wearable sensor data for human activity recognition in sport has previously been applied to cricket, tennis and rugby. Thus, the purpose of this study was to develop a human activity recognition system using wearable sensor data to accurately identify key ballet movements (jumping and lifting the leg). Our primary objective was to determine if machine learning can accurately identify key ballet movements during dance training. The secondary objective was to determine the influence of the location and number of sensors on accuracy. RESULTS: Convolutional neural networks were applied to develop two models for every combination of six sensors (6, 5, 4, 3, etc.) with and without the inclusion of transition movements. At the first level of classification, including data from all sensors, without transitions, the model performed with 97.8% accuracy. The degree of accuracy reduced at the second (83.0%) and third (75.1%) levels of classification. The degree of accuracy reduced with inclusion of transitions, reduction in the number of sensors and various sensor combinations. CONCLUSION: The models developed were robust enough to identify jumping and leg lifting tasks in real-world exposures in dancers. The system provides a novel method for measuring dancer training volume through quantification of specific movement tasks. Such a system can be used to further understand the relationship between dancers' pain and training volume and for athlete monitoring systems. Further, this provides a proof of concept which can be easily translated to other lower limb dominant sporting activities.

An Exploration of Pre-Professional Dancers' Beliefs of the Low Back and Dance-Specific Low Back Movements.

OBJECTIVE: Low back pain (LBP) is common in dancers. A biopsychosocial model should be considered in the aetiology of LBP, including a dancer's general beliefs of the low back and movements of the spine. This study aimed to determine pre-professional dancers' beliefs about their lower back in general and dance-specific movements of the spine and to explore whether these beliefs were influenced by a history of disabling LBP. METHODS: 52 pre-professional female dancers (mean age 18.3 [1.4] yrs) were recruited and reported whether they had a history of disabling LBP and completed the Back Pain Attitudes Questionnaire (Back-PAQ) and a dance movement beliefs questionnaire. A linear mixed model was applied to determine the effect of a history of disabling LBP on dancers' beliefs (p<0.05). RESULTS: 20 dancers reported a history of disabling LBP. Regardless of this LBP history, dancers held generally negative beliefs as measured by the Back-PAQ (p=0.130). A history of disabling LBP did not influence dancers' perceived movement safety of all tasks (p=0.867), and dancers held negative beliefs towards extension activities. These beliefs were linked to the conceptions of perceived risk of damage and the need to protect the lower back. CONCLUSIONS: Dancers hold negative general beliefs around the low back and low back movements, regardless of a history of disabling LBP. Dancers perceive extension activities as more dangerous than flexion activities. These beliefs may reflect a combination of pain experience and beliefs specific to dance.

The Difference in Lower Limb Landing Kinematics Between Adolescent Dancers and Non-Dancers.

The high prevalence of lower limb overuse injuries among adolescent ballet dancers may be due in part to repetitive land- ings. This cross-sectional study compared how adolescent ballet dancers perform a drop-landing task in comparison to non-dancers in order to help understand injury mechanics. Fifteen adolescent female ballet dancers aged 11.9 ± 1.1 years and 17 non-dancers aged 10.9 ± 0.9 years each performed three single limb drop-landings from a 30 cm box. An 18-camera motion capture system (Vicon MX; Oxford Metrics, Oxford, UK; 250 Hz) and a force platform (Advanced Mechanical Technology Inc., Watertown, Massachusetts, USA; 2,000 Hz) were used to collect lower limb joint angles in all three planes of motion and peak vertical ground reaction forces during the landing phase. These variables were compared for the two sets of participants using independent samples t-tests (p < 0.01). While the dancers landed with greater sagittal plane range of motion, this appeared to provide no mechanical advantage with no reduction in ground reaction force. Rather, the increased sagittal range of motion was coupled with increased coronal and frontal plane motion. This may place dancers at increased risk of injury.

Differences in lower limb biomechanics between ballet dancers and non-dancers during functional landing tasks.

OBJECTIVES: To determine the differences in the lower limb landing biomechanics of adolescent ballet dancers compared to non-dancers when performing a hop and a stop jump task. DESIGN: Cross-sectional. SETTING: Laboratory. PARTICIPANTS: Thirteen adolescent female ballet dancers (11.8 ±â€¯1.1 years) and 17 non-dancers (10.9 ±â€¯0.8 years) performed hop and stop jump tasks. MAIN OUTCOME MEASURES: Vertical ground reaction force, and three-dimensional ankle, knee and hip joint angles and moments during the landing phase. RESULTS: Dancers displayed greater sagittal plane joint excursions during the hop and stop jump at the ankle (mean difference = 22.0°, P < 0.001, 14.8°, P < 0.001 respectively), knee (mean difference = 18.1°, P = 0.001, 9.8°, P = 0.002 respectively) and hip (stop jump task; mean difference = 8.3°, P = 0.008). Dancers displayed a larger hip extensor moment compared to non-dancers (P < 0.001) during the stop jump task only. Dancers also took longer to reach peak vGRF and jumped three times higher than non-dancers (P < 0.001) during the stop jump task. No difference in peak vGRF between groups was displayed for either task. CONCLUSIONS: Adolescent dancers demonstrate a transfer of landing technique to non-ballet specific tasks, reflective of the greater jump height and sagittal plane joint excursions. This landing strategy may be associated with the low rate of non-contact ACL injuries in female dancers.