We developed an evidence-based practice guideline to support occupational safety and health (OSH) professionals in assessing the risk due to lifting and in selecting effective preventive measures for low back pain (LBP) in the Netherlands. The guideline was developed at the request of the Dutch government by a project team of experts and OSH professionals in lifting and work-related LBP. The recommendations for risk assessment were based on the quality of instruments to assess the risk on LBP due to lifting. Recommendations for interventions were based on a systematic review of the effects of worker- and work directed interventions to reduce back load due to lifting. The quality of the evidence was rated as strong (A), moderate (B), limited (C) or based on consensus (D). Finally, eight experts and twenty-four OSH professionals commented on and evaluated the content and the feasibility of the preliminary guideline. For risk assessment we recommend loads heavier than 25 kg always to be considered a risk for LBP while loads less than 3 kg do not pose a risk. For loads between 3-25 kg, risk assessment shall be performed using the Manual handling Assessment Charts (MAC)-Tool or National Institute for Occupational Safety and Health (NIOSH) lifting equation. Effective work oriented interventions are patient lifting devices (Level A) and lifting devices for goods (Level C), optimizing working height (Level A) and reducing load mass (Level C). Ineffective work oriented preventive measures are regulations to ban lifting without proper alternatives (Level D). We do not recommend worker-oriented interventions but consider personal lift assist devices as promising (Level C). Ineffective worker-oriented preventive measures are training in lifting technique (Level A), use of back-belts (Level A) and pre-employment medical examinations (Level A). This multidisciplinary evidence-based practice guideline gives clear criteria whether an employee is at risk for LBP while lifting and provides an easy-reference for (in)effective risk reduction measures based on scientific evidence, experience, and consensus among OSH experts and practitioners.
MULTIFILE
Athlete development depends on many factors that need to be balanced by the coach. The amount of data collected grows with the development of sensor technology. To make data-informed decisions for training prescription of their athletes, coaches could be supported by feedback through a coach dashboard. The aim of this paper is to describe the design of a coach dashboard based on scientific knowledge, user requirements, and (sensor) data to support decision making of coaches for athlete development in cyclic sports. The design process involved collaboration with coaches, embedded scientists, researchers, and IT professionals. A classic design thinking process was used to structure the research activities in five phases: empathise, define, ideate, prototype, and test phases. To understand the user requirements of coaches, a survey (n = 38), interviews (n = 8) and focus-group sessions (n = 4) were held. Design principles were adopted into mock-ups, prototypes, and the final coach dashboard. Designing a coach dashboard using the co-operative research design helped to gain deep insights into the specific user requirements of coaches in their daily training practice. Integrating these requirements, scientific knowledge, and functionalities in the final coach dashboard allows the coach to make data-informed decisions on training prescription and optimise athlete development.
Training-induced adaptations in muscle morphology, including their magnitude and individual variation, remain relatively unknown in elite athletes. We reported changes in rowing performance and muscle morphology during the general and competitive preparation phases in elite rowers. Nineteen female rowers completed 8 weeks of general preparation, including concurrent endurance and high-load resistance training (HLRT). Seven rowers were monitored during a subsequent 16 weeks of competitive preparation, including concurrent endurance and resistance training with additional plyometric loading (APL). Vastus lateralis muscle volume, physiological cross-sectional area (PCSA), fascicle length, and pennation angle were measured using 3D ultrasonography. Rowing ergometer power output was measured as mean power in the final 4 minutes of an incremental test. Rowing ergometer power output improved during general preparation [+2 ± 2%, effect size (ES) = 0.22, P = 0.004], while fascicle length decreased (−5 ± 8%, ES = −0.47, P = 0.020). Rowing power output further improved during competitive preparation (+5 ± 3%, ES = 0.52, P = 0.010). Here, morphological adaptations were not significant, but demonstrated large ESs for fascicle length (+13 ± 19%, ES = 0.93), medium for pennation angle (−9 ± 15%, ES = −0.71), and small for muscle volume (+8 ± 13%, ES = 0.32). Importantly, rowers showed large individual differences in their training-induced muscle adaptations. In conclusion, vastus lateralis muscles of elite female athletes are highly adaptive to specific training stimuli, and adaptations largely differ between individual athletes. Therefore, coaches are encouraged to closely monitor their athletes' individual (muscle) adaptations to better evaluate the effectiveness of their training programs and finetune them to the athlete's individual needs.
