Early Stages Of Training Research Articles

Тактична підготовка в командних ігрових видах спорту на ранніх етапах багаторічного удосконалення спортсменів: постановка проблеми

The purpose of the study was to identify the importance and features of tactical training of athletes in team games in the early stages of long-term sports development. Materials and methods. The most common team game sports are singled out, in which the main game tools are the ball, namely: volleyball, handball, basketball and football. Curricula for children's and youth sports school and others are analyzed in each sport in order to identify the place and features of tactical training of athletes in the early stages of long-term sports improvement. Also, Ukrainian and foreign basic works in the field of sports and specialized literature for each of the above sports were developed. Results and discussion. Tactical training of the athlete is one of the determining factors in the effectiveness of his/her performances during competitive activities in team sports (football, volleyball, basketball, handball, etc.). At the same time, in sports theory to this day, it is considered that tactical training is a priority in the preparation of later stages of long-term improvement. In contrast, some domestic and foreign experts in the field of sports argue that athletes who are at the stage of preliminary basic training are already fully capable of effective implementation of tactical tasks during training and competitive activities in the chosen sport. In Ukraine, most children who specialize in team sports are involved in state sports organizations. When building a long-term process of training athletes, these organizations are guided by approved training programs in sports. Most of these programs are outdated and cannot provide effective training for Ukrainian athletes. One of the main conditions for the active development of team sports abroad is a change in approaches to building the educational process of young athletes. In fact, the content of these approaches is to increase the overall share of tactical training within the training process of young athletes, through the active use of games and competitive exercises. This is actively followed in the training of young players in leading European and world private clubs. The use of modern approaches to the training of young athletes in team sports in Ukraine will improve their level of training (including tactical). Conclusion. The study found that tactical training is an integral part of the training process of young athletes in team sports. However, the role of tactical training in the early stages of long-term training is insignificant. The need to update curricula to improve the training of young Ukrainian athletes in the early stages of long-term sports development has been identified. Also, differences between the theoretical and practical support of the process of tactical training of young athletes in Ukraine are identified

Quality assessment of anatomical MRI images from generative adversarial networks: Human assessment and image quality metrics

BackgroundGenerative Adversarial Networks (GANs) can synthesize brain images from image or noise input. So far, the gold standard for assessing the quality of the generated images has been human expert ratings. However, due to limitations of human assessment in terms of cost, scalability, and the limited sensitivity of the human eye to more subtle statistical relationships, a more automated approach towards evaluating GANs is required. New methodWe investigated to what extent visual quality can be assessed using image quality metrics and we used group analysis and spatial independent components analysis to verify that the GAN reproduces multivariate statistical relationships found in real data. Reference human data was obtained by recruiting neuroimaging experts to assess real Magnetic Resonance (MR) images and images generated by a GAN. Image quality was manipulated by exporting images at different stages of GAN training. ResultsExperts were sensitive to changes in image quality as evidenced by ratings and reaction times, and the generated images reproduced group effects (age, gender) and spatial correlations moderately well. We also surveyed a number of image quality metrics. Overall, Fréchet Inception Distance (FID), Maximum Mean Discrepancy (MMD) and Naturalness Image Quality Evaluator (NIQE) showed sensitivity to image quality and good correspondence with the human data, especially for lower-quality images (i.e., images from early stages of GAN training). However, only a Deep Quality Assessment (QA) model trained on human ratings was able to reproduce the subtle differences between higher-quality images. ConclusionsWe recommend a combination of group analyses, spatial correlation analyses, and both distortion metrics (FID, MMD, NIQE) and perceptual models (Deep QA) for a comprehensive evaluation and comparison of brain images produced by GANs.

The Auxiliary Function of Intelligent Mobile Robot in the Standard Training of Children’s Sports Movement

Mobile robots belong to mechanical devices. Mobile robots are commanded by humans and restricted by the principles established by artificial intelligence technology, mainly to assist humans in dangerous tasks. Intelligent mobile robot is a system that integrates perception, analysis, and decision-making, and it integrates a number of high-end technologies. It is currently the most active field of technological development. Infant sport is essentially a process of cultivating and caring for the physical fitness of children. This article aims to explore the auxiliary role of intelligent mobile robots in the standard training of children’s sports movements. The physique of the early childhood stage is closely related to the entire life stage. Once there is a deviation in the early childhood training stage, there will be very serious consequences. Therefore, the mobile intelligent robot is combined with children’s physical training, and it is expected that it will give correct guidance to improve children’s physical fitness. This article briefly designs the mobile robot, uses two independent wheels and a robotic arm with degrees of freedom, and analyzes the forward and inverse kinematics of the chassis and the robotic arm, which provides a theoretical basis for the design of the control algorithm. This article will focus on the training of children’s sports, explore the current deficiencies in children’s sports, and analyze the reasons and the role that intelligent mobile robots can provide in sports training. The experimental results in this paper show that the balance ability of children standing on one foot with eyes open is mainly distributed in the second, third, and fourth levels. Among them, the second level has the largest number of people, accounting for 52%, the third level accounts for 27%, the fourth level accounts for 22%, and the other levels are less distributed. When the intelligent mobile robot assists children’s movement, the child’s balance ability is generally distributed in the fourth and fifth levels. Among them, the fourth level has the largest number of people, accounting for 52%, followed by the fifth level, accounting for 26%, and the third level accounting for 14%. This shows that the intelligent mobile robot is effective in guiding the movement of young children.

Re-creating reality: validation of fresh frozen full cadaver airway training with videolaryngoscopy and bougie FIRST strategy

BackgroundTracheal intubation is the gold standard in emergency airway management. One way of measuring intubation quality is first pass success rate (FPSR). Mastery of tracheal intubation and maintenance of the skill is challenging for non-anesthesiologists. A combination of individual measures can increase FPSR. Videolaryngoscopy is an important tool augmenting laryngeal visualization. Bougie-first strategy can further improve FPSR in difficult airways. Standardized positioning maneuvers and manipulation of the soft tissues can enhance laryngeal visualization. Fresh frozen cadavers (FFC) are superior models compared to commercially manufactured manikins. By purposefully manipulating FFCs, it is possible to mimic the pre-hospital intubation conditions of helicopter emergency medical service (HEMS).MethodsTwenty-four trauma surgeons (12 per Group, NOVICES: no pre-hospital experience, HEMS: HEMS physicians) completed an airway training course using FFCs. The FFCs were modified to match airway characteristics of 60 prospectively documented intubations by HEMS physicians prior to the study (BASELINE). In four scenarios the local HEMS airway standard (1: unaided direct laryngoscopy (DL), OLD) was compared to two scenarios with modifications of the intubation technique (2: augmented DL (bougie and patient positioning), 3: augmented videolaryngoscopy (aVL)) and a control scenario (4: VL and bougie, positioning by participant, CONTROL). FPSR, POGO score, Cormack and Lehane grade and duration of intubation were recorded. No participant had anesthesiological qualifications or experience in VL.ResultsThe comparison between CONTROL and BASELINE revealed a significant increase of FPSR and achieved C&L grade for HEMS group (FPSR 100%, absolute difference 23%, p ≤ .001). The use of videolaryngoscopy, bougie, and the application of positioning techniques required significantly more time in the CONTROL scenario (HEMS group: mean 34.0 s (IQR 28.3–47.5), absolute difference to BASELINE: 13.0 s, p = .045). The groups differed significantly in the median number of real-life intubations performed in any setting (NOVICES n = 5 (IQR 0–18.75), HEMS n = 68 (IQR 37.25–99.75)). In the control scenario no significant differences were found between both groups. The airway characteristics of the FFC showed no significant differences compared to BASELINE.ConclusionAirway characteristics of a pre-hospital patient reference group cared for by HEMS were successfully reproduced in a fresh frozen cadaver model. In this setting, a combination of evidence based airway management techniques results in high FPSR and POGO rates of non-anesthesiological trained users. Comparable results (FPSR, POGO, duration of intubation) were achieved regardless of previous provider experience. The BOAH concept can therefore be used in the early stages of airway training and for skill maintenance.

Adopting attention-mechanisms for Neural Logic Rule Layers

Abstract In previous works we discovered that rule-based systems severely suffer in performance when increasing the number of rules. In order to increase the amount of possible boolean relations while keeping the number of rules fixed, we employ ideas from well known Spatial Transformer Systems and Self-Attention Networks: here, our learned rules are not static but are dynamically adjusted to fit the input data by training a separate rule-prediction system, which is predicting parameter matrices used in Neural Logic Rule Layers. We show, that these networks, termed Adaptive Neural Logic Rule Layers, outperform their static counterpart both in terms of final performance, as well as training stability and excitability during early stages of training.

User-Level Label Leakage from Gradients in Federated Learning

Abstract Federated learning enables multiple users to build a joint model by sharing their model updates (gradients), while their raw data remains local on their devices. In contrast to the common belief that this provides privacy benefits, we here add to the very recent results on privacy risks when sharing gradients. Specifically, we investigate Label Leakage from Gradients (LLG), a novel attack to extract the labels of the users’ training data from their shared gradients. The attack exploits the direction and magnitude of gradients to determine the presence or absence of any label. LLG is simple yet effective, capable of leaking potential sensitive information represented by labels, and scales well to arbitrary batch sizes and multiple classes. We mathematically and empirically demonstrate the validity of the attack under different settings. Moreover, empirical results show that LLG successfully extracts labels with high accuracy at the early stages of model training. We also discuss different defense mechanisms against such leakage. Our findings suggest that gradient compression is a practical technique to mitigate the attack.

Changes in Body Composition, Energy Metabolites and Electrolytes During Winter Survival Training in Male Soldiers

The aim of this study was to examine changes in body composition, energy metabolites and electrolytes during a 10-day winter survival training period. Two groups of male soldiers were examined: the REC group (n = 26; age 19.7 ± 1.2 years; BMI 23.9 ± 2.7) had recovery period between days 6 and 8 in the survival training, whereas the EXC group (n = 42; age 19.6 ± 0.8 years; BMI 23.1 ± 2.8) did not. The following data were collected: body composition (bioimpedance), energy balance (food diaries, heart rate variability measurements), and biomarkers (blood samples). In survival training, estimated energy balance was highly negative: −4,323 ± 1,515 kcal/d (EXC) and −4,635 ± 1,742 kcal/d (REC). Between days 1 and 10, body mass decreased by 3.9% (EXC) and 3.0% (REC). On day 6, free fatty acid and urea levels increased, whereas leptin, glucose and potassium decreased in all. Recovery period temporarily reversed some of the changes (body mass, leptin, free fatty acids, and urea) toward baseline levels. Survival training caused a severe energy deficit and reductions in body mass. The early stage of military survival training seems to alter energy, hormonal and fluid metabolism, but these effects disappear after an active recovery period.

PrimeNet: Adaptive Multi-Layer Deep Neural Structure for Enhanced Feature Selection in Early Convolution Stage

The colossal depths of the deep neural network sometimes suffer from ineffective backpropagation of the gradients through all its depths, whereas the strong performance of shallower multilayer neural structures proves their ability to increase the gradient signals in the early stages of training, which easily gets backpropagated for global loss corrections. Shallow neural structures are always a good starting point for encouraging the sturdy feature characteristics of the input. In this research, a shallow, deep neural structure called PrimeNet is proposed. PrimeNet is aimed to dynamically identify and encourage the quality visual indicators from the input to be used by the subsequent deep network layers and increase the gradient signals in the lower stages of the training pipeline. In addition to this, the layer-wise training is performed with the help of locally generated errors, which means the gradient is not backpropagated to previous layers, and the hidden layer weights are updated during the forward pass, making this structure a backpropagation free variant. PrimeNet has obtained state-of-the-art results on various image datasets, attaining the dual objective of: (1) a compact dynamic deep neural structure, which (2) eliminates the problem of backward-locking. The PrimeNet unit is proposed as an alternative to traditional convolution and dense blocks for faster and memory-efficient training, outperforming previously reported results aimed at adaptive methods for parallel and multilayer deep neural systems.

Deterministic policy optimization with clipped value expansion and long-horizon planning

Model-based reinforcement learning (MBRL) approaches have demonstrated great potential in handling complex tasks with high sample efficiency. However, MBRL struggles with asymptotic performance compared to model-free reinforcement learning (MFRL). In this paper, we present a long-horizon policy optimization method, namely model-based deterministic policy gradient (MBDPG), for efficient exploitation of the learned dynamics model through multi-step gradient information. First, we approximate the dynamics of the environment with a parameterized linear combination of an ensemble of Gaussian distributions. Moreover, the dynamics model is equipped with a memory module and trained on a multi-step prediction task to reduce cumulative error. Second, successful experience is used to guide the policy at the early stage of training to avoid ineffective exploration. Third, a clipped double value network is expanded in the learned dynamics to reduce overestimation bias. Finally, we present a deterministic policy gradient approach in the model that backpropagates multi-step gradient along the imagined trajectories. Our method shows higher sampling efficiency than the state-of-the-art MFRL methods while maintaining better convergence performance and time efficiency compared to the SOAT MBRL.

Indicators of speed and strength abilities of young fencers 12-13 years old

Background and Study Aim. The health of a young athlete in the early stages of training is a mandatory element of the training process. This is a guarantee of the integrity of the process of training athletes for the next stage of preliminary basic training. The purpose of the study is to determine the indicators of speed and strength qualities of young fencers 12-13 years old at the stage of initial training. Material and methods. Fencers (n=13, age – 12-13 years, sports experience – 3 years) took part in the study. The children's parents agreed to participate in the study. The following tests were used: speed of overcoming the distance of 14 meters by fencing steps forward in the on-quard position, seconds; speed of overcoming distance of 14 meters by fencing steps back in the on-quard position, seconds; hits on the target in 10 seconds, the number of times; “Standing Long Jump Test”, cm; "Vertical Jump Test", sm. The computer program Excel was used: the indicators of arithmetic mean and standard deviation were determined. Correlation analysis was performed to identify relationships between the results of athletes' control standards. Statistical reliability was determined by Student's t test. Results. A sufficient level of development of speed and strength abilities for fencers of this age and qualification has been established. The relationship between the speed and strength of the muscles of the upper and lower extremities in young fencers was observed. Conclusions. The selected content and load of athletes fully meet the objectives of training. This is emphasized by the steady development of speed and strength abilities of athletes during fencing.

Task-Coupling Elastic Learning for Physical Sign-Based Medical Image Classification.

Physical signs of patients indicate crucial evidence for diagnosing both location and nature of the disease, where there is a sequential relationship between the two tasks. Thus their joint learning can utilize intrinsic association by transferring related knowledge across relevant tasks. Choosing the right time to transfer is a critical problem for joint learning. However, how to dynamically adjust when tasks interact to capture the right time for transferring related knowledge is still an open issue. To this end, we propose a Task-Coupling Elastic Learning (TCEL) framework to model the task relatedness for classifying disease-location and disease-nature based on physical sign images. The main idea is to dynamically transfer relevant knowledge by progressively shifting task-coupling from loose to tight during the multi-stage training. In the early stage of training, we relax the constraints of modeling relations to focus more in learning the generic task-common features. In the later stage, the semantic guidance will be strengthened to learn the task-specific features. Specifically, a dynamic sequential module (DSM) is proposed to explicitly model the sequential relationship and enable multi-stage training. Moreover, to address the side effect of DSM, a new loss regularization is proposed. The extensive experiments on these two clinical datasets show the superiority of the proposed method over the baselines, and demonstrate the effectiveness of the proposed task-coupling elastic mechanism.

Communication skills training in psychiatry

SUMMARYGood communication skills are the basis of all effective doctor–patient relationships, and psychiatrists in particular have to manage many types of complex interaction. Research shows the benefits of communication skills training. This article describes strategies for teaching relevant clinical communication skills to trainee psychiatrists on MRCPsych courses and in local centres. The authors set out a sustainable training framework using higher trainees as tutors. There is a need for more widespread teaching of clinical communication skills in psychiatry and at an early stage of specialist training.

Методика оценки показателей физической подготовленности юных стрелков с нарушением слуха на начальном этапе подготовки

The relevance of this study is due to the need of monitoring the physical fitness of young shooters with hearing impairment in the process of sports training and the lack of a set of diagnostic tests to assess these indicators at the early stage of training. The subject of the study was defined as a diagnostic toolkit for assessing the physical fitness of young shooters with hearing impairment, including control test exercises to assess the full range of physical qualities. The aim of the study was to develop methods for the evaluation of physical fitness of young shooters with hearing impairment at the early stage of training. To achieve the goal the following research methods were used: analysis of scientific and methodical literature on the problem of research, analysis of normative documentation regulating the training process in bullet shooting for athletes with hearing impairment, pedagogical observation, concretization, systematization, testing of physical qualities, methods of mathematical statistics, generalization. Results of the study: the transfer standards used in bullet shooting of hearing-impaired athletes when transferring athletes from one training stage to another are analyzed; methods of evaluating physical fitness of young shooters with hearing impairment at the early stage of training are developed, including a set of control exercises assessing manifestations of all physical qualities necessary for young shooters with hearing impairment, substantiated the expediency of those methods. The results of the study can be recommended for practical application to hearing impaired athletes specializing in bullet shooting and their coaches in order to improve both the physical training process and the implementation of its qualitative and complete control.

Probability Differential-Based Class Label Noise Purification for Object Detection in Aerial Images

Modern object detection for aerial images requires numerous annotated data. However, the data annotation process inevitably introduces noise due to the bird’s eye view perspective of aerial images and the professional requirements of annotations. While recent noise-robust object detection methods achieved great success, the noise side-effect during the early training stage was still a problem. As demonstrated in this letter, noise during the early training stage will cumulatively affect the final performance. Based on the above observations, we propose a training strategy called correction maximization training to purify the noisy annotations and then train models. Specifically, we design a novel noise filter called the probability differential (PD) to identify and revise wrong labels. After purification, we train the detector with the revised dataset. Compared to existing works, the proposed method could be adapted in most modern object detectors (e.g., Faster RCNN and RetinaNet) and requires little hyperparameter tuning across different datasets and models. Extensive experiments on DOTA show that the proposed method achieves state-of-the-art results with both symmetric and asymmetric noise.

Family medicine residents' knowledge and attitudes towards biostatistics, Taif, Kingdom of Saudi Arabia.

It is essential for practicing clinicians to have core knowledge of biostatistics. However, surveys indicated that clinicians' attitudes towards biostatistics are negative. Despite its importance, little is known about the knowledge of and attitudes towards statistics among trainees in family medicine, particularly in Saudi Arabia. The current investigation attempts to evaluate knowledge and attitudes held by family medicine trainees in Taif and explore their correlates. This was a descriptive, questionnaire-based, cross-sectional study of residents in family medicine training programme in Taif, Saudi Arabia. We used Poisson regression modelling to evaluate the effect of background factors on knowledge and attitudes towards biostatistics. The study included 113 family medicine trainees at different levels of training. Only 36 (31.9%) of the participating trainees expressed positive attitudes towards biostatistics. On the other hand, 30 (26.5%) participating trainees were found to have good biostatistics knowledge, compared to 83 (73.5%) trainees whose knowledge level was found to be poor. Upon adjusting for all background factors simultaneously, only younger age, level R4 training, publishing one or three papers were found to be associated with poorer attitudes towards biostatistics. Older age was associated with worsening of attitudes (adjusted odds = 0.9900, P = 0.00924), and so also was being a senior R4 trainee (adjusted odds = 0.9045, P = 0.01301). Publishing one paper (compared to publishing over three papers) was associated with poorer attitudes towards biostatistics (adjusted odds = 0.8857, P = 0.03525). Also, having published three papers (compared to publishing over three papers) was still associated with worse attitudes towards biostatistics (adjusted odds = 0.8528, P = 0.01318). The main finding of our current study is the poor level of knowledge and overtly negative attitudes held by family medicine trainees in Taif towards biostatics. Knowledge was particularly poor about advanced statistical concepts such as survival analysis and linear regression modelling. However, poor levels of knowledge about biostatistics could be a function of poor research productivity among family medicine trainees. Age, seniority in training and involvement in research also impacted positively on attitudes towards biostatistics. Therefore, it is recommended that the training curriculum for family medicine trainees should first cover essential biostatistics in a creative and accessible way and secondly encourage engagement research and publication from an early stage of training.

COMPARATIVE ANALYSIS OF SPORT SELECTION SYSTEMS IN DIFFERENT COUNTRIES

The aim of the research is to explore the sport selection systems in different countries and do a comparative analysis. Commitment to selection in professional sport is a required procedure from the early stages of training and it enables coaches to identify talented and gifted children. Actually the requirements for athletes are becoming increasingly rigorous and few athletes involved in sport may have good performance. Hence, there is a need for sport selection. This is by far very relevant topic in Armenia, too, for we have “limited” number of good and promising athletes. A more massive survey is planned to be carried out among coaches and professionals within sport-related fields to find out what skills and talents they consider important for different sports. In addition to ongoing research, as a final result, theoretical and practical councils are foreseen to be established to help form a unified system of sport selection and increase the efficiency of talented athletes’ selection.

A Controllable Multi-Lingual Multi-Speaker Multi-Style Text-to-Speech Synthesis With Multivariate Information Minimization

In this letter, we propose a multivariate information minimization method that disentangles three or more latent representations. We show that control factors can be disentangled by minimizing interactive dependency, which can be expressed as a sum of mutual information upper bound terms. Since the upper bound estimate converges from the early training stage, there is little performance degradation due to auxiliary loss. The proposed technique is applied to train a text-to-speech synthesizer with multi-lingual, multi-speaker, and multi-style corpora. Subjective listening tests validate that the proposed method can improve the synthesizer in terms of quality as well as controllability.

ME‐MADDPG: An efficient learning‐based motion planning method for multiple agents in complex environments

Developing efficient motion policies for multiagents is a challenge in a decentralized dynamic situation, where each agent plans its own paths without knowing the policies of the other agents involved. This paper presents an efficient learning-based motion planning method for multiagent systems. It adopts the framework of multiagent deep deterministic policy gradient (MADDPG) to directly map partially observed information to motion commands for multiple agents. To improve the efficiency of MADDPG in sample utilization, so as to train more brilliant agents that can adapt to more complex environments, a strategy named mixed experience (ME) is introduced to MADDPG, and this has led to our proposed ME-MADDPG algorithm. The novel ME strategy can be embodied into three specific mechanisms: (1) an artificial potential field-based sample generator to produce high-quality samples in the early training stage; (2) a dynamic mixed sampling strategy to mix the training data from different sources with a variable proportion; (3) a delayed learning skill to stabilize the training of the multiple agents. A series of experiments have been conducted to verify the performance of the proposed ME-MADDPG algorithm, and it has been demonstrated that, compared with MADDPG, the proposed algorithm can significantly improve the convergence speed and convergence effect in the training process, and it has also shown better efficiency and better adaptability in complex dynamic environments while it is used for multiagent motion planning applications.

The Differentiate Effects of Resistance Training With or Without External Load on Young Soccer Players' Performance and Body Composition.

Purpose: The purpose of this study was to examine the effects of 15 weeks (2/week) of two different resistance training (RT) programs [the self-load group (SG) vs. the overload group (OG)] on selected measures of physical performance in young male soccer players.Methods: The countermovement jump (CMJ), aerobic endurance (VO2 max), and body composition [body mass (BM), height (H), body fat percentage (% BF), and lean mass (LM)] were measured before and after the 15-week RT interventions. Subjects were randomized to treatments: 1. SG [age = 15.34 ± 1.34 years]; 2. OG [age = 16.28 ± 1.21 years].Results: The level of significance set for the study (p ≤ 0.05). Within-group analysis did report significant differences in all variables for the SG (p = 0.008 to 0.001; ES = −0.33 to 1.41, small to large) as in the OG (p = 0.001; ES = 0.82 to 1.30, large). Between-groups analysis reported differences in CMJ (F = 4.32; p = 0.004) for the OG.Conclusion: The main findings of this study indicated that RT with and without external load was effective in improving the measures of physical performance in young soccer players, with special attention to jumping ability, where the OG group was more effective. Furthermore, there is no interference to aerobic endurance. It is recommended that soccer coaches implement RT without external load in the early stages of training or in players with late maturation development and in those soccer clubs with limited material resources.

TP8.2.2 Surgical Escape Rooms: A Novel Approach to identifying and addressing Resilience and Academic Buoyancy

Abstract Introduction Traditional Simulation is useful practice for real life scenarios whilst Surgical Escape Rooms (ER) assess other elements. Resilience contributes to physical and emotional wellbeing as well as the development of coping strategies. Consistent short-term Academic Buoyancy levels can have an impact on long-term levels of Resilience. Method Two groups of 4th year medical students were given the validated Brief Resilience Scale (BRS) and the Academic Buoyancy Scale (ABS) before and after. The first group completed the Surgical ER whilst the second group completed a Surgical Simulation. During the ER session, participants were assessed by multiple, independent assessors on 4 parameters - participation, objective display of frustration/stress, interaction with the team and definitive decisions taken. These were then correlated with their initial self-assessments scores. Result The ER group ABS Scores improved (3.45 to 3.8; Range 0-4) whilst BRS scores decreased (4.5 to 3.9; Range 0-5). The Simulation group ABS scores decreased (3.4 to 2.9) whilst BRS scores improved (2.9 to 3.2). Scores became more polarised across all groups. Participants who scored low on the BRS/ABS displayed lower levels of participation, team interaction and fewer definitive actions taken but also displayed fewer indicators of overt stress in comparison to their higher scoring counterparts. Conclusion Escape Rooms are useful in challenging individuals to improve problem solving skills and encourage lateral thinking. It would be useful to incorporate ER’s in the early stages of training to build confidence and reduce the immediate negative impact of Simulation at later stages.