Assessment Of Skills Research Articles

Spatial-temporal attention for video-based assessment of intraoperative surgical skill.

Accurate, unbiased, and reproducible assessment of skill is a vital resource for surgeons throughout their career. The objective in this research is to develop and validate algorithms for video-based assessment of intraoperative surgical skill. Algorithms to classify surgical video into expert or novice categories provide a summative assessment of skill, which is useful for evaluating surgeons at discrete time points in their training or certification of surgeons. Using a spatial-temporal neural network architecture, we tested the hypothesis that explicit supervision of spatial attention supervised by instrument tip locations improves the algorithm's generalizability to unseen dataset. The best performing model had an area under the receiver operating characteristic curve (AUC) of 0.88. Augmenting the network with supervision of spatial attention improved specificity of its predictions (with small changes in sensitivity and AUC) and led to improved measures of discrimination when tested with unseen dataset. Our findings show that explicit supervision of attention learned from images using instrument tip locations can improve performance of algorithms for objective video-based assessment of surgical skill.

Utilising H5P Simulations to Enhance Social Work Education

Higher education is tasked with the challenge of producing graduate-ready professionals. Thus, alternative learning and assessment activities are needed to provide students with real-life complex experiences, particularly in fields like social work. This quasi-experimental design study explored the effectiveness of H5P virtual simulation to teach assessment and direct practice skills to social work students (n = 80). Mixed-methods data based on the pre/post outcomes of skill development were analysed using descriptive and bi-variate analysis as well as thematic analysis for qualitative data. A Wilcoxon signed-rank test reveals significant outcomes in assessment and practice skills between pre- and post-measures. The qualitative findings include three key themes: (1) realism, (2) engagement, and (3) practice skills. This study provides evidence and highlights the importance of using virtual simulation to help students develop skills to manage complex real-world problems.

Automated assessment of non-technical skills by heart-rate data.

Observer-based scoring systems, or automatic methods, based on features or kinematic data analysis, are used to perform surgical skill assessments. These methods have several limitations, observer-based ones are subjective, and the automatic ones mainly focus on technical skills or use data strongly related to technical skills to assess non-technical skills. In this study, we are exploring the use of heart-rate data, a non-technical-related data, to predict values of an observer-based scoring system thanks to random forest regressors. Heart-rate data from 35 junior resident orthopedic surgeons were collected during the evaluation of a meniscectomy performed on a bench-top simulator. Each participant has been evaluated by two assessors using the Arthroscopic Surgical Skill Evaluation Tool (ASSET) score. A preprocessing stage on heart-rate data, composed of threshold filtering and a detrending method, was considered before extracting 41 features. Then a random forest regressor has been optimized thanks to a randomized search cross-validation strategy to predict each score component. The prediction of the partially non-technical-related components presents promising results, with the best result obtained for the safety component with a mean absolute error of 0.24, which represents a mean absolute percentage error of 5.76%. The analysis of feature important allowed us to determine which features are the more related to each ASSET component, and therefore determine the underlying impact of the sympathetic and parasympathetic nervous systems. In this preliminary work, a random forest regressor train on feature extract from heart-rate data could be used for automatic skill assessment and more especially for the partially non-technical-related components. Combined with more traditional data, such as kinematic data, it could help to perform accurate automatic skill assessment.

Deep learning for surgical instrument recognition and segmentation in robotic-assisted surgeries: a systematic review

Applying deep learning (DL) for annotating surgical instruments in robot-assisted minimally invasive surgeries (MIS) represents a significant advancement in surgical technology. This systematic review examines 48 studies that utilize advanced DL methods and architectures. These sophisticated DL models have shown notable improvements in the precision and efficiency of detecting and segmenting surgical tools. The enhanced capabilities of these models support various clinical applications, including real-time intraoperative guidance, comprehensive postoperative evaluations, and objective assessments of surgical skills. By accurately identifying and segmenting surgical instruments in video data, DL models provide detailed feedback to surgeons, thereby improving surgical outcomes and reducing complication risks. Furthermore, the application of DL in surgical education is transformative. The review underscores the significant impact of DL on improving the accuracy of skill assessments and the overall quality of surgical training programs. However, implementing DL in surgical tool detection and segmentation faces challenges, such as the need for large, accurately annotated datasets to train these models effectively. The manual annotation process is labor-intensive and time-consuming, posing a significant bottleneck. Future research should focus on automating the detection and segmentation process and enhancing the robustness of DL models against environmental variations. Expanding the application of DL models across various surgical specialties will be essential to fully realize this technology’s potential. Integrating DL with other emerging technologies, such as augmented reality (AR), also offers promising opportunities to further enhance the precision and efficacy of surgical procedures.

Assessment of Dental Students' Knowledge and Attitudes About the Epidemiologic and Clinical Characteristics of Oral Cancer: Implications for Other Middle-income Countries.

The stage of detection of head and neck cancer and the time between detection and treatment are critical to prognosis. The importance of the dentist in primary diagnosis and treatment planning has been emphasized. The purpose of this study was to evaluate the knowledge of dental students in the prevention and early diagnosis of oral cancer. A descriptive cross-sectional study was conducted on 199 students from different institutions. A self-administered questionnaire with 34 multiple-choice questions on clinical and epidemiologic knowledge and opinions about oral cancer was used. Descriptive analysis to show means and frequencies and the binomial logistic regression test were used to perform the statistical analysis. The confidence level used was 95%. The results showed that all students in the study had heard of the existence of oral cancer, but only 24.6% knew someone with the disease. The majority reported a lack of information in the population about prevention and self-examination, as well as a lack of information campaigns in institutions. Although the majority perform clinical examinations of the oral mucosa (73.4%) and refer patients with suspicious lesions to specialists, there is low confidence in performing biopsies (73.4%) and gaps in training during graduation (84.4%). The majority have never attended continuing education courses on oral cancer but show interest (97.5%). The study identifies deficiencies in the knowledge and practices of dental students and highlights the need for improved teaching and training to promote oral cancer prevention and early detection. Further research in this area and ongoing assessment of students' skills are suggested.

Further validating the robotic microsurgery platform through preclinical studies on rat femoral artery and vein.

Introduction This research aims to validate the proficiency and accuracy of the robotic microsurgery platform using rat femoral vessel model. Materials and Methods Total of 256 rat femoral vessels were performed, half using robotic and the other by manual microanastomosis by 8 microsurgeons with less than 5 years of experience given 8 trials (rats) each. Vessel demographics, proficiency (duration of suture and Structured Assessment of Robotic Microsurgical Skills (SARMS)) and accuracy (patency and Scanning Electron Microscopic (SEM)) was analyzed between the two groups. Results Using the robot, an average of 4 trials was needed to reach a plateau in total anastomosis time and patency. Significant more time was required for each vessel anastomosis (34.33 versus 21.63 minutes on the 8th trial, p<0.001) one factor being higher number of sutures compared to the hand-sewn group (artery: 7.86±0.51 versus 5.86±0.67, p=0.035, vein: 12.63±0.49 versus 9.57±0.99, p=0.055). The SARMS scores became nonsignificant between the two group on the 4th trial. The SEM showed higher tendency of unevenly spaced sutures, infolding, tears in the vessel wall for the hand-sewn group. Conclusion Using the robot, similar patency, accuracy, and proficiency can be reached through fast but steep learning process within 4 trials (anastomosis of 8 vessels) as the hand-sewn group. The robotic anastomosis may take longer time, but this is due to the increased number of sutures reflecting higher precision and accuracy. Further insight of precision and accuracy was found through the SEM demonstrating the possibility of the robot to prevent unexpected and unwanted complications.

Assessment of first-touch skills in robotic surgical training using hi-Sim and the hinotori surgical robot system among surgeons and novices

PurposeSurgeons’ adaptability to robotic manipulation remains underexplored. This study evaluated the participants’ first-touch robotic training skills using the hinotori surgical robot system and its simulator (hi-Sim) to assess adaptability.MethodsWe enrolled 11 robotic surgeons (RS), 13 laparoscopic surgeons (LS), and 15 novices (N). After tutorial and training, participants performed pegboard tasks, camera and clutch operations, energizing operations, and suture sponge tasks on hi-Sim. They also completed a suture ligation task using the hinotori surgical robot system on a suture simulator. Median scores and task completion times were compared.ResultsPegboard task scores were 95.0%, 92.0%, and 91.5% for the RS, LS, and N groups, respectively, with differences between the RS group and LS and N groups. Camera and clutch operation scores were 93.1%, 49.7%, and 89.1%, respectively, showing differences between the RS group and LS and N groups. Energizing operation scores were 90.9%, 85.2%, and 95.0%, respectively, with a significant difference between the LS and N groups. Suture sponge task scores were 90.6%, 43.1%, and 46.2%, respectively, with differences between the RS group and LS and N groups. For the suture ligation task, completion times were 368 s, 666 s, and 1095 s, respectively, indicating differences among groups. Suture scores were 12, 10, and 7 points, respectively, with differences between the RS and N groups.ConclusionFirst-touch simulator-based robotic skills were partially influenced by prior robotic surgical experience, while suturing skills were affected by overall surgical experience. Thus, robotic training programs should be tailored to individual adaptability.

Meningkatkan Hasil Belajar Menyundul dalam Permainan Sepakbola Melalui Model Pembelajaran Kooperatif Tipe Team Games Tournament (TTG) Pada Siswa Kelas X SMA Negeri 7 Ambon

Heading the ball is one of the learning materials for the game of football. Students are required to have competence through understanding and the ability to practice basic head-to-head techniques. The purpose of this study is to determine the improvement of football heading learning outcomes through the TGT learning model in grade X students of SMA Negeri 7 Ambon. This type of research is classroom action research. The implementation of the action takes place in two cycles. The subjects of the study were 26 students in class X. Learning outcomes are determined based on the rubric of assessment of attitudes, knowledge and skills. The results of the study showed that the learning results of heading the ball in cycle I, there were 16 students who had completed or 68.56% with a total score of 1391.25. Meanwhile, 10 students did not complete or 25.80% with a total score of 662.46. In the second cycle, 26 students have met the KKM or (91.01%) with a total score of 2295.72. The results of this study can be concluded that the TGT learning model can improve the learning outcomes of basic dribbling techniques in football games in grade X students of SMA Negeri 7 Ambon.

Functional outcome of mirror therapy versus task oriented training on hand function in children with unilateral cerebral palsy

Background. Unilateral cerebral palsy (UCP) is a kind of spastic cerebral palsy which is characterized by atypical posture of upper limb, poor eye-hand coordination, and reduced hand skills. These symptoms can restrict a child’s ability to engage in life activities. Purpose. To compare the effectiveness of mirror therapy as well as task-oriented training on hand functions improvement among UCP children. Methods. Sixty children suffering from UCP were randomly allocated into three equal groups. A schemed physical therapy protocol was utilized to the control, mirror therapy (MT), and task-oriented training (TOT) groups. The protocols of mirror therapy and task-oriented training were administered to MT and TOT groups respectively. Assessments of upper extremity skills, hand dexterity, wrist extension range of motion, along with overall grip strength were conducted at baseline and after intervention using the Quality of Upper Extremity Skills Test (QUEST), Box and Block Test (BBT), universal goniometer, as well as pneumatic squeeze handheld dynamometer respectively. Throughout a total of twelve consecutive weeks, the intervention session was held three days a week. Results. The change amount in all measured hand outcomes were significantly improved following the intervention in all three groups, with the TOT group showing a larger significant effect. Conclusion. Task-oriented training had superior impact than mirror therapy in enhancing hand functions among children having UCP.

Assessment of basic locomotor movement skills of elementary school students using TGMD-2

Introduction. Basic movement is the foundation of human behavior and helps young children to learn new skills in other areas. A child can actively move and exercise if they have basic movement skills. Therefore, it is necessary to identify the real condition of children’s movement skills, especially lower grade elementary school children. This can be used as a reference to prevent undesirable outcomes, such as the onset of obesity in children. Method. This study is a Pre-experimental design conducted to assess basic movement abilities in learning activities of eight locomotor movements, namely walking, running, hopping, jumping, galloping, sliding, skipping, and leaping by means of observation through motion observation instruments using the Gross Motor Development 2 (TGMD-2) Test approach.The subjects of this study were 42 students from Pilahan public elementary school, including 14 students from grade 1, 14 from grade 2, and 14 from grade 3. Results. The research found that among the 42 lower grade students of Pilahan State Elementary School, 12 students scored below average, 14 students scored moderately, and 16 students scored above average. Conclusion. Thus, it is expected that this data can be used as a basis for evaluating students who have not scored above average. This data is also expected to serve as a reference for further research on the issue of lower grade elementary school students with below-average basic movement skills.

Affective disorders: eliminate WArning signs And REstore functioning: AWARE. Results from a randomized controlled multimodular intervention study targeting functioning in patients with affective disorders.

There is a compelling need for innovative intervention strategies for patients with affective disorders, given their increasing global prevalence and significant associated disability and impaired functioning. This study aimed to investigate whether a comprehensive multimodule individualized intervention (AWARE), targeting known mediators of functioning, improves functioning in affective disorders. AWARE was a randomized, controlled, rater-blind clinical trial conducted at two centers in the Capital Region of Denmark (Clinicaltrials.gov, NCT04701827). Participants were adults with bipolar disorder or major depressive disorder and impaired functioning. Participants were randomized to the six-month AWARE intervention or treatment as usual (TAU). The AWARE intervention is based on the International Classification of Functioning, Disability and Health (ICF) Brief Core Set for Bipolar and Unipolar Disorder.The primary outcome was observation-based functioning using the Assessment of Motor and Process Skills (AMPS). Secondary outcomes were functioning, QoL, stress, and cognition. Between February 2021 and January 2023, 103 patients were enrolled; 50 allocated to AWARE treatment and 53 to TAU (96 included in the full analysis set). There was no statistically significant differential change over time between groups in the primary outcome (AMPS), however, both groups showed a statistically significant improvement at endpoint. The AWARE intervention had a statistically significant effect compared with TAU on secondary outcomes of patient-reported functioning, stress and cognition. Compared with TAU, the AWARE intervention was ineffective at improving overall functioning on the primary outcome, presumably due to the short duration of the intervention. Further development of effective treatments targeting functioning is needed.

Machine learning perioperative applications in visceral surgery: a narrative review

Artificial intelligence in surgery has seen an expansive rise in research and clinical implementation in recent years, with many of the models being driven by machine learning. In the preoperative setting, machine learning models have been utilized to guide indications for surgery, appropriate timing of operations, calculation of risks and prognostication, along with improving estimations of time and resources required for surgeries. Intraoperative applications that have been demonstrated are visual annotations of the surgical field, automated classification of surgical phases and prediction of intraoperative patient decompensation. Postoperative applications have been studied the most, with most efforts put towards prediction of postoperative complications, recurrence patterns of malignancy, enhanced surgical education and assessment of surgical skill. Challenges to implementation of these models in clinical practice include the need for more quantity and quality of standardized data to improve model performance, sufficient resources and infrastructure to train and use machine learning, along with addressing ethical and patient acceptance considerations.

Speaking Skill Assessment Instrument Validity: An Investigation into Instructors’ Perceptions

To EFL learners, speaking the target language with satisfactory fluency is a highly significant aspect of learning the language. Assessment of learners’ progress and achievement in speaking skills is equally significant to identify the course of further action, whether it is for feedback, placement, or grading. At the English Language Institute (ELI), King Abdulaziz University in Saudi Arabia, learners’ proficiency in spoken English is assessed for end-of-the-term grading using Interview and Speaking Project as test instruments. The Interview questions are random, while the Speaking Project involves collection of materials on a chosen topic and report writing, followed by presentation and question-answer session. An empirical research study was conducted to examine ELI teachers’ perceptions on the reliability and validity of the two assessment instruments to accurately measure learners’ proficiency in speaking skill and meeting the requirements to reflect the learning outcomes designed for the speaking English course. The data were collected through a survey questionnaire and a structured interview. The surveyed instructors were also encouraged to express their opinions on the role of formative assessment in determining learners’ final grades in English speaking skill.

Assessment of Managerial Skills Among Healthcare Provider Managers

The primary objective of this research is to assess the managerial skills of managers working in healthcare and hospital centers (primary healthcare) within Isfahan province. This cross-sectional study was carried out in 2023, encompassing a sample size of 1,420 healthcare providers operating in these healthcare and hospital centers. The research utilized the Cameron and Whetten questionnaire, which employs a Likert scale for measurement. Data analysis was conducted using Pearson correlation coefficient and linear regression tests. The findings revealed that 53.4% of managers demonstrated effective skills in writing, oral communication, and listening. Additionally, 62.8% of managers exhibited proficiency in time management. However, only 39.12% were adept at avoiding troublesome decisions, 30.2% were skilled in persuading higher-level individuals, and 30.8% showed competence in planning. A significant relationship was identified between the ability to persuade higher-level individuals to perform tasks and teamwork among managers with more work experience. The results also highlighted a higher incidence of troublesome decision-making among women and individuals with extensive managerial experience. In conclusion, the study suggests that managers of healthcare providers in healthcare and hospital centers (primary healthcare) in Isfahan province require more focused attention and training in certain key managerial skills to enhance their effectiveness. This includes improving their abilities in decision-making, persuasion, and planning, which are crucial for their roles. Therefore, targeted training programs and interventions are recommended to address these gaps and improve the overall managerial capabilities within these healthcare settings.

Enhancing Analytical Reading and Writing Skills in Vocational Education: The Role of Collaborative and Task-Based Learning

Purpose: This study aims to evaluate the effectiveness of combining Collaborative Learning (CL) and Task-Based Learning Teaching (TBLT) in enhancing vocational students&amp;#39; analytical reading ability and writing skills. Method: Conducted at a vocational college in southern China, the study involved 192 students divided into an experiment group (n=25) receiving the blended approach and a control group (n=27) following traditional methods. The intervention lasted four weeks, with pre-tests and post-tests administered using the Analytical Reading Ability Test (ARAT) and Writing Skill Assessment Scale (WSAS). Data were analyzed using ANOVA and t-tests. Results: The findings indicated that the blended approach significantly improved the students&amp;rsquo; skills. The experiment group showed substantial improvements, with post-test scores in analytical reading ability (35.28&amp;plusmn;1.54) and writing skills (25.20&amp;plusmn;1.56) significantly higher than pre-test scores (29.48&amp;plusmn;2.37; 20.24&amp;plusmn;2.13). Moreover, the experiment group outperformed the control group at the 0.05 significance level in both areas. Conclusions: Integrating Collaborative Learning with Task-Based Learning Teaching significantly enhances vocational students&amp;rsquo; analytical reading and writing skills. This approach offers a valuable instructional strategy for vocational education, preparing students for the demands of a globalized job market.

Crowd-Sourced Assessment of Laparoscopic Surgical Skills for Ob/Gyn Residents

Importance Feedback is an essential part of graduate medical education. With increasing demands on time and fewer opportunities for formal feedback in residency, there is an increasing need for objective and actionable feedback. Objective To understand how the Crowd-Sourced Assessment of Technical Skills (CSATS) assessment of residents’ laparoscopic skills compares with the current faculty assessment in an obstetrics/gynecology residency program. Design, Setting, and Participants This was a prospective educational intervention study involving residents from a single academic obstetrics/gynecology residency program at a large tertiary teaching hospital. Individual performance videos of hysterectomies, myomectomies, and endometriosis resections were recorded and uploaded to the CSATS database where they were analyzed. Formal written feedback reports from the CSATS system were sent to the residents. Residents then completed a survey addressing satisfaction, timeliness, and utility of the CSATS feedback method overall and in comparison with the residency’s in-person feedback and with the standard written, electronic feedback evaluation. Results A total of 16 residents submitted 65 videos of operations. Overall comparison of CSATS vs faculty evaluation was equivalent. Residents found that CSATS response time was slower than receiving in-person feedback from faculty. When comparing CSATS with the standard feedback form, residents felt strongly that CSATS was superior for both surgical skill feedback and procedure evaluation, with both categories having a mean top score. When comparing low-volume CSATS utilization vs high-volume CSATS utilization, there were no statistical differences. Overall, residents reported high satisfaction with CSATS evaluation. Conclusions Residents were generally satisfied with CSATS as an overall feedback tool. CSATS could be a possible addition to help improve resident education.

Seasonal forecasts have sufficient skill to inform some agricultural decisions.

Abstract Seasonal forecasts, which look several months into the future, are currently underutilized in active decision-making, particularly for agricultural and natural resource management. This underutilization can be attributed to the absence of forecasts for decision-relevant variables at the required spatiotemporal resolution and at the time when the decisions are made and a perception of poor skill by decision-makers. Addressing these constraints, we quantified the skill of seasonal forecasts in informing two agricultural decisions with differing decision timeframes and influencer variables: (a) whether to apply fertilizer in fall or wait until spring based on expected winter temperatures, and (b) drought response, such as whether to lease water based on expectations of drought. We also looked into how early the forecast can be provided without significant degradation in skill. Currently, drought response decisions are typically formulated in April, utilizing drought forecasts issued in the same month, while fall fertilization decisions are generally made between August and September. There is growing interest among stakeholders in the availability of earlier forecasts to inform these critical choices. We utilized the North American Multi-Model Ensemble (NMME) hindcasts for the time period 1982 - 2020 over the Pacific Northwest US to obtain meteorological variables. Runoff was estimated via simulations of the coupled crop-hydrology VIC-CropSyst model. The skill assessment with the Heidke Skill Score (HSS) yielded promising outcomes in both decisions for the entire Pacific Northwest region. Notably, NMME’s positive skill (median HSS of 30%) in predicting warmer winters identifies years when fertilizer application should be avoided to prevent fertilizer loss through mineralization (and associated costs). Similarly, there is skill in forecasting drought conditions in most irrigated watersheds for up to two months in advance of April, the current decision time. In conclusion, our findings affirm that contrary to the perception of low skill and resulting underutilization, current seasonal forecasts hold the potential to inform at least some key agricultural decisions.

Water deprivation induces a systemic pro-catabolic state that differentially affects oxidative and glycolytic skeletal muscles in male mice.

Dehydration, characterized by the loss of total body water and/or electrolytes due to diseases or inadequate fluid intake, is prevalent globally but often underestimated. Its contribution to long-term chronic diseases and sarcopenia is recognized, yet the mechanisms involved in systemic and muscle protein metabolism during dehydration remain unclear. This study investigated metabolic adaptations in a 36-hour water deprivation (WD) model of mice. Male C57BL/6 mice underwent 36-h WD or pair-feeding at rest, with assessments of motor skills along with biochemical, and metabolic parameters. Dehydration was confirmed by hypernatremia, body mass loss, hyporexia, and increased activity of vasopressinergic and oxytocinergic neurons compared to controls. These results were associated with liver mass loss, decreased glycaemia, and increased cholesterolemia. Additionally, increased VO2 and a decreased respiratory exchange ratio indicated reduced carbohydrate consumption and potentially increased protein use during dehydration. Thus, skeletal muscle protein metabolism was evaluated due to its high protein content. In the oxidative muscles of the WD group, total and proteasomal proteolysis increased, which was associated with decreased Akt-mediated intracellular signaling. Interestingly, there was an increase in fiber cross-sectional area, likely due to higher muscle water content caused by increased intracellular osmolality induced by protein catabolism products. Conversely, no changes were observed in protein turnover or water content in glycolytic muscles. These findings suggest that short-term WD imposes a pro-catabolic state, depleting protein content in skeletal muscle. However, skeletal muscle may respond differently to dehydration based on its phenotype and might adapt for a limited time.

Empowering Social Growth Through Virtual Reality–Based Intervention for Children With Attention-Deficit/Hyperactivity Disorder: 3-Arm Randomized Controlled Trial

Background Attention-deficit/hyperactivity disorder (ADHD) usually begins in childhood and is often accompanied by impairments in social functioning. Virtual reality (VR) has emerged as an adjunctive tool to embed in social skills training to enhance the social skills of children with ADHD, but its effectiveness requires further investigation. Objective This study aims to enhance the social skills of children with ADHD by examining the feasibility and effectiveness of VR-based training in comparison to traditional social skills training. Methods A 3-arm randomized controlled trial was conducted with 90 children with ADHD aged 6-12 years. Participants were randomly assigned to 3 weeks of 12-session VR-based social skills training, traditional social skills training, or a waitlist control group of equivalent duration. Outcome measures included assessments by a clinical psychologist who was blinded to group assignments, the Social Skills Improvement System Rating Scale, the Behavior Rating Inventory of Executive Function, and the Simulator Sickness Questionnaire, conducted at baseline and after the intervention. Results The preliminary results support the feasibility and acceptability of VR training for children with ADHD aged 6-12 years. Analysis showed that the VR and traditional social skills training groups experienced a statistically significant improvement in the clinical psychologist assessment of social skills and parent-rated self-control, initiative, and emotional control after the intervention compared with baseline. The VR group performed significantly better than the traditional social skills group on social skills assessed by clinical psychologists (F2,85=76.77; P&lt;.001) and on parent-rated self-control (F2,85=18.77; P&lt;.001), initiative (F2,85=11.93; P&lt;.001), and emotional control (F2,85=17.27; P&lt;.001). No significant between-group differences were found for parent-rated cooperation and inhibition (all P&gt;.05). Conclusions The findings provide preliminary evidence supporting the feasibility and superior effectiveness of VR-based social skills training compared to traditional approaches for enhancing social skills and related executive functions in children with ADHD. These results suggest that VR may be a valuable tool to embed within social skills interventions for this population. Further research is warranted to explore the long-term impacts and generalizability of these benefits. Trial Registration ClinicalTrials.gov NCT05778526; https://clinicaltrials.gov/study/NCT05778526 International Registered Report Identifier (IRRID) RR2-10.2196/48208

NEXT-GENERATION EDGE CLOUD-TO-THING CONTINUUM MODEL FOR EVALUATING CHILDREN’s MOTOR SKILLS USING DEEP LEARNING ALGORITHM

Young children can enhance their movements and develop motor abilities through play and education with guidance and practice. Understanding young children’s physical development and identifying potential growth areas require an analysis of their motor skills. In this study, we assess young children’s motor skills using a unique deep residual technique on the cloud-to-thing continuum. Seven kids were used to identify autistic movements. The dataset was gathered from the Tamimi Centre for Autism in Saudi Arabia. The data preprocessing to standardize the data’s scale using min–max normalization and removing noise-relevant features is extracted using principal component analysis (PCA). This step is crucial for ensuring the quality and reliability of the data used for subsequent analysis. The bumble bees mating optimization with deep residual algorithm (BBMO-DRN) is designed to handle the complexities of motor skill assessment. Finally, we explore the potential of cloud–fog–edge computing in data storing and processing young children’s motor skill development. The results showed that the proposed method performs better compared to the existing methods. This will make it possible to evaluate how well the suggested solution works in terms of accuracy, precision, recall, [Formula: see text]1-score, and scalability. As a result, this proposed approach in evaluating young children’s motor skills is to improve data storage in the cloud to the thing continuum.