Training Aid Research Articles

PROMOÇÃO DA SAÚDE E BEM-ESTAR EM IDOSOS ATRAVÉS DE PROGRAMAS DE EXERCICIOS FUNCIONAL: UMA REVISÃO INTEGRATIVA

This study presents an integrative review on the benefits of functional exercises for elderly health and well-being. With the global aging population and associated public health challenges, it is crucial to explore practices that enhance quality of life (SILVA; SANTOS, 2019). The research analyzed studies that highlight how functional training aids in maintaining physical fitness, autonomy, and disease prevention. Observed benefits include improvements in physical abilities, such as strength and balance, and cognitive function (ALMEIDA; CARDOSO, 2022), as well as a positive impact on social interaction and psychological well-being among the elderly (FREITAS; ALMEIDA, 2021). The study also discusses adapting exercise programs to meet individual needs, considering factors like health conditions and reduced mobility (RODRIGUES; LIMA, 2023)

Brain-computer interface applications in the aging population with Alzheimers and Parkinsons disease

Abstract. The rapidly aging population faces increasing prevalence of neurodegenerative conditions like Alzheimer's Disease (AD) and Parkinson's Disease (PD), which significantly impair cognitive and motor functions. There is an urgent need for increased research, awareness, and development of effective treatments to mitigate their impact on the affected individuals and their families. This paper delves into the history, mechanisms, and applications of brain-computer interfaces (BCIs) as innovative solutions to mitigate these impacts. BCIs enable direct brain-to-device communication, circumventing conventional neuromuscular routes. We highlight how neurofeedback and neuroplasticity facilitated by BCIs not only restore motor skills and cognitive functions but also enhance the overall quality of life for sufferers. Through applications in cognitive training, motor assistance, and advanced communication aids, BCIs present a significant promise despite the ethical and practical challenges they pose. The continual advancement of this technology promises to a future when its incorporation into treatment plans will be widely used and provide significant advantages for those with PD and AD.

The effect of special exercises using some auxiliary tools to develop some bio-kinetic abilities and the accuracy of the crushing and snatch forehand strikes among badminton players

The best means and ways to develop an athlete's physical and skill capabilities, and among these means is the use of training aids that help develop some bio-kinetic abilities, and prepared exercises have had an important role in improving athletic performance in badminton, where the player must possess physical fitness, explosive power, and strength. Characterized by speed as well as accuracy, awareness, and focus while playing on the court, the badminton player must be physically fit through a continuous movement of small and large muscles to achieve good performance, which requires special physical abilities and skills, and the most important of these bio-kinetic abilities are agility, coordination, and measuring the coordination between the eye and the arm. These abilities are needed by the badminton player while playing on the court. The study aimed to prepare special exercises using some auxiliary tools to develop some bio-kinetic abilities and the accuracy of the crushing and lightning forehand strikes among badminton players, in addition to identifying the effect of special exercises using some auxiliary tools on For badminton players, the researcher adopted the experimental method, and the sample number was (10) players from the badminton training center in the Armenian club, aged (17-19). They were distributed into two experimental and control groups, and they were chosen randomly because the research objectives require the use of athletes proficient in the game's technical performance. The researcher applied her main experiment using special exercises with some auxiliary tools, with (4) training units per week for (8) weeks. The results of the study showed that there was a positive effect on the results of bio-kinetic abilities between the two groups and in favor of the experimental group. It was shown in the kinetic response speed test for the first experimental group 7.423, agility 3.012, and compatibility 3.123, and for the second experimental group in the kinetic response speed test 3.208, agility 6.861, and compatibility 6.907. As for the skill tests for the first experimental group, The front smash hit was 7,234 and the diagonal front snap shot was 28.00. It was shown in the skill tests for the second experimental group that the front smash hit was 3,372 and the diagonal front snap shot was 3,400, which included exercises. The researcher recommends adopting the results of this study and disseminating them, and emphasizing equipping the stadiums with modern training methods, due to the results they achieve. Positive physical development serves one of the goals of sustainable development: good health and good education.

Immersive virtual reality in forestry work – implementation for chainsaw training

ABSTRACT Growing interest in virtual reality (VR) and its technical development has resulted in several applications for training and teaching purposes. This paper studied an immersive VR platform, hereafter referred to as IVR, developed for training in motor-manual tree delimbing as a learning tool, which is one of the first in forestry work training. The tested platform was the Husqvarna Limberjack, available for free download and publicly accessible. The platform uses an immersive VR to teach users how to delimb stems with a chainsaw. The study included four groups with different previous experience of using immersive VR as the first factor and a chainsaw as the second factor. The experiment included records of the time required to complete the tasks. That data was used in a procedural study in which the average and best times of the groups were utilized. Statistical analysis showed differences between the groups with and without experience in both factors. The learning curves showed a 12.4 to 26.7% improvement for all four groups. The IVR platform turned out to be a useful training aid, where skills can be gained before going to practice in field.

Communicating robots’ intent through visual cues enhances human anticipatory behavior in human–dual robot collaboration

The present study aims at exploring the effect of communicating robots’ intent through visual cues, to the human on a complex human-robot collaborative task. Specifically, it aims to investigate (i) whether the use of such “anticipatory cues” will have a positive effect on task efficiency, human safety and collaborating fluency, (ii) the degree of this effect with varying robots’ speed and (iii) whether a retention effect will be observed after the removal of the cues. For exploring these issues, a human - dual robot industrial assembly task was designed in a Virtual Reality simulation environment and testing was carried out by 64 volunteer participants. Results showed that communicating robots’ intent through visual cues enhanced human anticipatory behavior, resulting in a significant improvement in human safety, team efficiency and collaborative fluency, in conjunction with a favorable subjective tendency towards the robots. However, the positive effect of the anticipatory cues was not found to increase with higher robot speed. Finally, the findings suggest that prior exposure to the cues made participants more confident in coordinating with the robots, even when the cues were removed from them, thus retaining their prior efficiency but with a negative effect on safety. In summary, the study provides evidence that use of anticipatory visual cues accelerates the legibility of robot movement and fosters human confidence and familiarization. The use of anticipatory cues seems promising for high-pace, non-repetitive interactions with collaborative robots or as a training aid in more repetitive human-robot collaborative tasks.

Closing the referral loop on health-related social needs.

184 Background: Additional clinical challenges arise by way of health-related social needs (HRSNs) presenting barriers outside of clinic walls. Taking a person-centered approach by assessing and addressing HRSNs to overcome barriers can be practiced through resource referrals to community-based organizations offering specialized social services. Using closed-loop referral (CLR) technology, HRSNs can be addressed resulting in higher treatment completion rates and on-time visits contributing to positive health outcomes, quality of life, and improved business outcomes. HRSNs are categorized in major groups such as transit, food, housing, money, health (i.e. mental health, dental care, nutrition counseling, etc.), and care (i.e. daycare, end-of-life care, physical safety, etc.). In this study, we seek to substantiate CLR technology to address common HRSNs impacting cancer patients through real-time data sharing and resource facilitation showing reportable evidence that the HRSNs have been addressed. Methods: On June 5 th , 2023, The US Oncology Network (The Network) launched Findhelp’s CLR platform onboarding users in over 600 clinical service sites nationwide. Implementation and change management began with a pilot group and deployment to remaining clinical sites in a sequence of three waves. Methods used to measure engagement came through onboarding analytics and click rates tracked through the Findhelp CLR platform. For training and support job aides, new user workflows, promo materials and weekly office hours were held to catalyze engagement. Results: Within an eleven-month measurement period, 75% of practices in The Network showed navigation activities within the referral platform. The top five resource searches by need included health (21.7%), transit (20.8%), food (19.9%), housing (18.9%), and care (6.5%). Over 2,000 referrals were made with 1,306 being CLRs for nearly 500 patients receiving help to meet identified HRSNs through the CLR technology. Conclusions: In this study, over 50% of patients referred to social care services were captured as successfully receiving help meeting identified HRSNs. This study opens doors to further research on what HRSNs were not met, and to identify distressed demographics by location and geographical resource deserts with unmet HRSNs.

Supplements, Training And Recovery Aids Used By 2022 Masters Field Hockey World Cup Participants

Supplements, Training And Recovery Aids Used By 2022 Masters Field Hockey World Cup Participants

Evaluation of Volatile Organic Compounds from Spotted Lanternfly (Lycorma delicatula) Eggs Using Headspace Odor Sampling Methods.

The spotted lanternfly (SLF) is an invasive species native to China. It was first discovered in the United States in Pennsylvania in 2014. It is known to cause great economic damage by destroying various crops, specifically grape vines, and therefore, several efforts have been made to control and mitigate its spread from the Northeast. Canine detection is a useful detection tool; however, it is crucial to understand the volatile organic compounds emitting by this pest to better direct canine training paradigms to prevent false alerts and to understand potential volatile markers of importance indicative of this species. The purpose of this study is to address the gap in research regarding the volatile organic compound (VOC) profile of SLF to better inform pest control mitigation strategies. Instrumental analysis was performed utilizing SPME-GC/MS on cold-killed SLF eggs, dried crickets, and tree bark. Differences in detected VOCs within each sample set depicted distinctive odor profiles for each matrix tested. Storage of these samples also depicted VOC accumulation variation as a function of time, thereby providing implications for long-term storage and sample handling for these types of training aids in canine applications.

INTEGRATING DUAL FUNDUS IMAGE DEEP FEATURE POOLING BASED ON CUP AND DISC SEGMENTATION FOR EFFICIENT GLAUCOMA DETECTION FRAMEWORK INDULGING HEURISTIC CONCEPT

The permanent damage occurring to the optical nerve, which transmits the visualized images to the brain leading to permanent vision loss, is called glaucoma. The detection and diagnosis of glaucoma at the beginning stage are essential to prevent permanent damage caused to vision as there are no initial symptoms to detect the onset of the damage, and there is no cure while the damage progresses to its extreme stage. Many models utilizing deep learning technology have been executed to identify the presence of glaucoma using digital Fundus Images (FI). However, these methods need specialized hardware and are computationally complicated as there is not much-labeled data available, leading to generalization issues in these models. Therefore, the development of a deep learning-oriented model for Glaucoma Detection (GD) using the dual feature pooling of cup and disc segmentation features with the aid of the FI is the main motive behind this work. At first, the digital FI is congregated from standardized online data sources. Then the gathered images are considered for the image segmentation procedure. The disc is segmented from the input image with the aid of the Transformer based Adaptive ResUNet++ (TA-ResUNet++) framework. The segmented disc image is now provided to hybrid convolution networks (HCN) for extracting the disc-oriented features. At the same time, the cup is segmented from the gathered input image using the executed TA-ResUnet++. Following this, the cup features are extracted using the same HCN model. The obtained features regarding the disc and the cup are concatenated in order to generate a single pool of glaucoma features. Then these features are inputted into the implemented bidirectional long short-term memory with multi-head attention (Bi-LSTM-MHA) mechanism to detect the presence of glaucoma in people. The segmentation and detection outcomes are made better by optimizing the parameters in the TA-ResUNet++ and Bi-LSTM-MHA models with the aid of hybrid sewing training with the Chameleon swarm optimization algorithm (HST-CSA). The experimental analysis is done to analyze the effective performance of the developed GD model. Jaccard analysis performed for the developed HST-CSOA-TA-ResUNet++-based disc segmentation gained better performance as 18.29% than MobileNet, 14.11% efficient than ResNet, 12.79% superior to Bi-LSTM and 5.43% higher than Bi-LSTM-MHA while considering best as the statistical measure.

Quadriceps Activation After Anterior Cruciate Ligament Reconstruction: The Early Bird Gets the Worm!

Arthrogenic Muscle Inhibition (AMI) is a phenomenon observed in individuals with joint injury or pathology, characterized by a reflexive inhibition of surrounding musculature, altered neuromuscular control, and compromised functional performance. After anterior cruciate ligament reconstruction (ACLR) one of the most obvious consequences of AMI is the lack of quadriceps activation and strength. Understanding the underlying mechanisms of AMI is crucial for developing effective therapeutic interventions. The surgical procedure needed to reconstruct the ACL has biochemical et physiological consequences such as inflammation, pain, and altered proprioception. These alterations contribute to the development of AMI. Therapeutic interventions aimed at addressing AMI encompass a multidimensional approach targeting pain reduction, inflammation management, proprioceptive training, and quadriceps activation. Early management focusing on pain modulation through modalities like ice, compression, and pharmacological agents help mitigate the inflammatory response and alleviate pain, thereby reducing the reflexive inhibition of quadriceps. Quadriceps activation techniques such as neuromuscular electrical stimulation (NMES) and biofeedback training aid in overcoming muscle inhibition and restoring muscle strength. NMES elicits muscle contractions through electrical stimulation, bypassing the inhibitory mechanisms associated with AMI, thus facilitating muscle activation and strength gains. Comprehensive rehabilitation programs tailored to individual needs and stage of recovery are essential for optimizing outcomes in AMI. The objective of this clinical viewpoint is to delineate the significance of adopting a multimodal approach for the effective management of AMI, emphasizing the integration of pain modulation, proprioceptive training, muscle activation techniques, and manual therapy interventions. Highlighting the critical role of early intervention and targeted rehabilitation programs, this article aims to underscore their importance in restoring optimal function and mitigating long-term complications associated with AMI.

Patient autonomy and shared decision-making in the context of clinical trial participation.

This study aimed to explore how incorporating shared decision-making (SDM) can address recruitment challenges in clinical trials. Specifically, it examines how SDM can align the trial process with patient preferences, enhance patient autonomy and increase active patient participation. Additionally, it identifies potential conflicts between SDM and certain clinical trial aspects, such as randomization or blinding, and proposes solutions to mitigate these issues. We conducted a comprehensive review of existing literature on patient recruitment challenges in clinical trials and the role of SDM in addressing these challenges. We analysed case studies and trial reports to identify common obstacles and assess the effectiveness of SDM in improving patient accrual. Additionally, we evaluated three proposed solutions: adequate trial design, communication skill training and patient decision aids. Our review indicates that incorporating SDM can significantly enhance patient recruitment by promoting patient autonomy and engagement. SDM encourages physicians to adopt a more open and informative approach, which aligns the trial process with patient preferences and reduces psychological barriers such as fear and mental stress. However, implementing SDM can conflict with elements such as randomization and blinding, potentially complicating trial design and execution. The desire for patient autonomy and active engagement through SDM may clash with traditional clinical trial methodologies. To address these conflicts, we propose three solutions: redesigning trials to better accommodate SDM principles, providing communication skill training for physicians and developing patient decision aids. By focussing on patient wishes and emotions, these solutions can integrate SDM into clinical trials effectively. Shared decision-making provides a framework that can promote patient recruitment and trial participation by enhancing patient autonomy and engagement. With proper implementation of trial design modifications, communication skill training and patient decision aids, SDM can support rather than hinder clinical trial execution, ultimately contributing to the advancement of evidence-based medicine.

The effects of tactile aids in video games for children’s rhythmic coordination training: An fNIRS study

Neurological or neurodevelopmental disorders, such as Parkinson’s disease and dyslexia, can impair rhythm perception and production. Deficits in rhythm are associated with poor performance in language, attention, and working memory tasks. Research indicates that retraining rhythmic skills may enhance these related cognitive functions. In this context, using tactile aids for rhythm training emerges as a promising approach for children who do not fully benefit from conventional audiovisual rhythm games. This is because tactile aids can compensate for sensory deficiencies and facilitate more extensive brain activation. In our study, we employed functional near-infrared spectroscopy (fNIRS) to assess the impact of tactile aids on brain cortical activation during rhythmic training in children aged 6–12 years (N = 25). We also measured the participants’ spontaneous motor rhythms. The findings indicate that tactile stimulation significantly improves performance in synchronized rhythm tasks compared to audiovisual stimulation alone, particularly enhancing activation in brain regions associated with speech training such as the prefrontal cortex, motor cortex, and temporal areas. These results not only support the application of rhythm training in speech rehabilitation, but also highlight the potential of tactile aids as an effective multisensory learning strategy.

Development of a Paper-Based Sol–Gel Vapochromic Sensor for the Detection of Vapor Cross-Contamination within a Closed Container

Contamination of trace levels of volatile organic compounds (VOCs) in enclosed spaces is not usually a significant cause for concern; however, it can be relevant in the case of canine scent detection training as a canine’s superior sense of smell makes them highly likely to detect low levels of contamination, contributing to inefficient training. Thus, herein, we address the need for a simple, low-cost, robust, vapochromic sensor to determine the cross-contamination of VOCs within closed containers, such as canine training aid kits. This study focuses on the development of a vapor sensor, which produces a rapid colorimetric change when a target chemical vapor is present. A pH indicator is used as the colorimetric dye and its incorporation into a sol–gel matrix on a paper substrate is confirmed via SEM characterization. The sensor’s stability and performance is tested against exposure to various levels of sunlight and temperature. The design allows the sensor to present a clear and unambiguous visible response to the release of the volatile target within a closed container. It can be readily incorporated into existing training kits and functions as a straightforward reminder of when training aids need to be changed or a new containment system should be considered.

Examining the Impact of a Behavior Modification Program on Disease Prevention Behaviors among Individuals at Risk of Diabetes: A Quasi-Experimental Investigation.

This study aimed to develop and test a behavior modification intervention to prevent type 2 diabetes (T2DM) among at-risk individuals. The primary goal was to compare diabetes prevention behaviors and fasting blood sugar levels between the intervention and comparison groups. This study utilizes a quasi-experimental design to develop a behavior modification intervention for preventing diabetes. It involves two groups, each with pre- and post-intervention assessments, comprising 60 at-risk individuals equally divided into intervention and comparison groups. The 8-week intervention includes components like risk assessment, dietary skill enhancement, exercise, stress management, and social media platforms (data recording training, follow-up visits, reminders, and visual aids). Data collection includes self-administered questionnaires and blood sugar level measurements. Statistical analysis involved paired t-tests for within-group comparisons and independent t-tests for between-group differences. The findings showed that the intervention group achieved significantly higher average scores in nutrition, exercise, and stress management, and had significantly lower average blood sugar levels compared to the comparison group. These results suggest that healthcare providers and policymakers should develop community health programs and public health policies that incorporate integrative care, leverage social media platforms, and foster collaboration with other health professionals to improve outcomes for individuals at risk of T2DM.

Posture detection of athletes in sports based on posture solving algorithms

With the rapid development of science and technology, the field of sports is constantly exploring and applying new technical means to improve the training effect and competitive level of athletes. Among them, the athletes' posture detection technology based on the attitude solving algorithm has been widely concerned in recent years. However, the current attitude solving algorithm has the limitation of low precision and low efficiency. Aiming at this, a new attitude solving algorithm is proposed. Firstly, the coordinate system is determined according to the theory of inertial navigation, and the attitude Angle is obtained by calculating the acceleration and magnetic induction intensity. Then the current attitude matrix is calculated according to the obtained attitude Angle. The initializing quaternion based on the attitude matrix is studied. Then, according to the advantages and defects of the three sensors, a complementary filtering algorithm is proposed for data fusion, so as to reduce the error of the final attitude solution. In order to further improve the accuracy of attitude detection, the complementary filter algorithm and double-layer Kalman filter algorithm are combined to process the data, and finally the quaternion is updated. It can be seen that the detection error of the research constructed model is only 9.94%, and its three attitude angle errors are mainly concentrated between -0.5° and 0.5° The model constructed by the research can realize high-precision posture detection, which can provide more scientific and reliable training aids for gymnastics, which has very strict requirements for movements in sports. It has positive significance for the development of sports.

Exploring Trainees’ Behaviour in Hands-on Cybersecurity Exercises Through Data Mining

Despite the rising number of cybersecurity professionals, the demand for more experts in this field is still substantial. Cybersecurity professionals must also possess up-to-date knowledge and skills to counter cybersecurity threats’ dynamicity and rapidly evolving nature. Hands-on cybersecurity training is mandatory to practice various tools and improve one’s technical cybersecurity skills. Generally, an interactive learning environment is set, where trainees perform sophisticated tasks by accessing complete operating systems, applications, and networks. One of the main challenges that cybersecurity organizations are facing today is the generation of massive data through practice exercises. So, it becomes a problem to convert this data into knowledge to improve the overall quality of the learning system. The large amount of interaction data and its complexity also limit us to do automated analysis. Thus, these challenges for cybersecurity learners can be addressed through appropriate educational data analysis by having insights or testing hypotheses or models on a proper dataset. Revealing the patterns, rules, item sets and time taken by trainees while using any command line tool could help the trainer to assess the trainees and to provide feedback. Therefore, in this paper we are analyzing the frequency patterns and timing information captured from the trainees’ command line log to reveal their solving techniques, easy and struggling stages, slipups, and individual performance. Through our study, we aim to show how education and training providers can foresee learners who are less likely to succeed in a task or exhibit low performance, which can impede learning proficiency. With this knowledge, organizations and trainers can identify trainees who require additional attention or support. It may also be able to identify elements related to an organization like training aids, training methodology, etc. that need improvement. This study demonstrates the utility of data-mining techniques, specifically rule mining and sequential mining, to empower training designers to delve into datasets derived from cyber security training exercises.

Aspects of the dynamics of osteogenesis and bone tissue resorption markers concentrations in elite biathlonists due to the compression specificity of the cyclic training aids used at the stages of the early season

Aim: study the dynamics of osteogenesis and bone resorption markers in elite biathlonists owing to the “compression” specifics of cyclic training aids, mainly used at the stages of the early season of the annual training cycle.Materials and methods: 23 elite biathlonists undergoing centralized training as the members of the Russian national team took part in the study.Results: no changes in the P1NP amounts reaching a reliable level were recorded throughout the early season. The average group osteocalcin amount at the precompetition stage significantly (p < 0,05) increased compared with that measured at the special preliminary stage. Dynamics of β-CrossLaps concentration showed significant (p < 0,05) decrease during the transition from the general preliminary to the special preliminary stage.Conclusion: the degree of intense training activity influence on the activity of bone cells and in turn the response of bone tissue to training loads depend on a set of exercise parameters performed by the athlete, such as duration, intensity, specificity, recovery time and mechanical stress. Optimizing the ratio of cyclic aids with different levels of compression loads during specialized training promotes adaptive changes which protect bone tissue from resorption affected by intense physical exercises. When analyzing the levels of bone metabolism markers for diagnosis and monitoring disorders associated with skeletal overload which could occur high-intensity training loads, an individual approach as well as recognition of the load specifics and parameters performed by an athlete at a specific stage of the training macrocycle are required.

Effect of membrane properties on the odor emanating from training aids for explosive-detecting canines.

Canines are widely used for real-time detection of explosives and have proven to be on par with instrumental methods. Canines are thought to rely largely upon detection of volatile chemical constituents of the explosives, though not necessarily the explosive itself. Hence, it is crucial to understand the odor available to them as generated by training aids. Previous studies have established that the Training Aid Delivery Device (TADD) developed by SciK9 is a reliable training aid that reduces cross-contamination and doubles as a storage device. A TADD comprises a standardized container, a synthetic membrane, a membrane holder, and a lid. In the work presented, activated charcoal strips were placed above and below the TADD membrane to determine the relative amounts of volatiles emitted by dynamite (i.e., ethylene glycol dinitrate (EGDN) and trinitroglycerin (NG)). The strips were eluted and the extracts tested using gas chromatography-mass spectrometry in negative ion chemical ionization mode. A series of t-tests at 95% confidence level were performed to determine any differences in vapor composition above and below the membranes. Nine synthetic membranes and six glass fiber membranes were tested in this study. It was expected that the relative concentration of volatiles would remain the same on both sides of the membrane; however, selective removal of nitroglycerin by some membranes was observed. Synthetic membranes with larger pore sizes showed no alteration in the vapor composition. Both synthetic and glass fiber membranes did not show a significant change in relative concentration of the other volatile compound in dynamite, i.e., EGDN. Out of all the membranes tested, three synthetic membranes and four glass fiber membranes showed selective alteration in odor availability of nitroglycerin in dynamite. For training purposes, membranes that do not alter the vapor composition should be used in the training aid.

Interventions for School-Aged Children with Auditory Processing Disorder: A Scoping Review.

(1) Background: Auditory processing (AP) disorder is associated with learning difficulties and poses challenges to school-aged children in their daily activities. This scoping review identifies interventions and provides audiologists with protocol insights and outcome measures. (2) Methods: A systematic search of both peer-reviewed and grey literature (January 2006 to August 2023) covered ten databases. Studies included had the following characteristics: (i) published in French or English; (ii) participants were school-aged, and had a normal audiogram, AP difficulties or disorder, and no cognitive, developmental, congenital or neurological disorder (with the exception of learning, attention, and language disabilities); (iii) were intervention studies or systematic reviews. (3) Results: Forty-two studies were included, and they predominantly featured auditory training (AT), addressing spatial processing, dichotic listening, temporal processing and listening to speech in noise. Some interventions included cognitive or language training, assistive devices or hearing aids. Outcome measures listed included electrophysiological, AP, cognitive and language measures and questionnaires addressed to parents, teachers or the participants. (4) Conclusions: Most interventions focused on bottom-up approaches, particularly AT. A limited number of top-down approaches were observed. The compiled tools underscore the need for research on metric responsiveness and point to the inadequate consideration given to understanding how children perceive change.

Identifying and Reducing Insulin Errors in the Simulated Military Critical Care Air Transport Environment: A Human Factors Approach.

During high-fidelity simulations in the Critical Care Air Transport (CCAT) Advanced course, we identified a high frequency of insulin medication errors and sought strategies to reduce them using a human factors approach. Of 169 eligible CCAT simulations, 22 were randomly selected for retrospective audio-video review to establish a baseline frequency of insulin medication errors. Using the Human Factors Analysis Classification System, dosing errors, defined as a physician ordering an inappropriate dose, were categorized as decision-based; administration errors, defined as a clinician preparing and administering a dose different than ordered, were categorized as skill-based. Next, 3 a priori interventions were developed to decrease the frequency of insulin medication errors, and these were grouped into 2 study arms. Arm 1 included a didactic session reviewing a sliding-scale insulin (SSI) dosing protocol and a hands-on exercise requiring all CCAT teams to practice preparing 10 units of insulin including a 2-person check. Arm 2 contained arm 1 interventions and added an SSI cognitive aid available to students during simulation. Frequency and type of insulin medication errors were collected for both arms with 93 simulations for arm 1 (January-August 2021) and 139 for arm 2 (August 2021-July 2022). The frequency of decision-based and skill-based errors was compared across control and intervention arms. Baseline insulin medication error rates were as follows: decision-based error occurred in 6/22 (27.3%) simulations and skill-based error occurred in 6/22 (27.3%). Five of the 6 skill-based errors resulted in administration of a 10-fold higher dose than ordered. The post-intervention decision-based error rates were 9/93 (9.7%) and 23/139 (2.2%), respectively, for arms 1 and 2. Compared to baseline error rates, both arm 1 (P = .04) and arm 2 (P < .001) had a significantly lower rate of decision-based errors. Additionally, arm 2 had a significantly lower decision-based error rate compared to arm 1 (P = .015). For skill-based preparation errors, 1/93 (1.1%) occurred in arm 1 and 4/139 (2.9%) occurred in arm 2. Compared to baseline, this represents a significant decrease in skill-based error in both arm 1 (P < .001) and arm 2 (P < .001). There were no significant differences in skill-based error between arms 1 and 2. This study demonstrates the value of descriptive error analysis during high-fidelity simulation using audio-video review and effective risk mitigation using training and cognitive aids to reduce medication errors in CCAT. As demonstrated by post-intervention observations, a human factors approach successfully reduced decision-based error by using didactic training and cognitive aids and reduced skill-based error using hands-on training. We recommend the development of a Clinical Practice Guideline including an SSI protocol, guidelines for a 2-person check, and a cognitive aid for implementation with deployed CCAT teams. Furthermore, hands-on training for insulin preparation and administration should be incorporated into home station sustainment training to reduced medication errors in the operational environment.