Duration Of Training Research Articles

#2857 Home hemodialysis training time: associated factors and impact on technique survival

Abstract Background and Aims The optimal training time for Home Hemodialysis (HHD), its related factors and its impact in the technique survival are not well established. Our objective was to analyze the risk factors associated with longer duration of HD training and to assess the impact of training time on the survival of the technique. Method Single-center observational study in which all patients seen in our HHD program from January 2013 to November 2023 were included. Training time was defined as the total number of dialysis treatments undertaken for instructional purposes, regardless of prior experience. Patients were divided into two groups, according to standard (≤31 days) or prolonged (>31 days) training duration. Sociodemographic and clinical variables were compared between the two groups, and the factors associated with prolonged training were analyzed using binary logistic regression. HDD failure was the composite of technique failure (defined as transfer to in-center HD for ≥ 30 consecutive days) and death. Results We analyzed 50 patients (women: 18, 36%) with a mean age of 55.1 ± 12.6 years and a median length of time on dialysis of 33 (IQR 3-369) months. The median training time was 31 (IQR 24-45) days. 14 (28%) patients were single, 22 (44%) were actively working and the percentage of primary, middle and university education was 20%, 56% and 24%, respectively. In the univariate analysis, a younger age, and the presence of a care partner were associated with a shorter HHD training time, whereas the type of vascular access, the educational level, the marital status, the gender, and the need for a care partner were similar in both standard and prolonged training duration groups. After a multivariate logistic regression analysis, the only factor independently associated to a longer training time was the age (OR: 1.08, 95% CI: 1.02-1.14; p = 0.01). After a median follow-up of 27 (IQR: 15-50) months, HDD failure was observed in 12 (27%) of patients. Although in the crude analysis the technique survival tended to be lower in the prolonged training duration group (Fig. 1), this finding was not confirmed after adjusting for age. Conclusion In our experience, the older age was the only factor independently associated with longer HDD training time, whereas a longer training time did not impact in the HDD survival. These data suggest that HHD training should be especially careful in elderly patients, whose learning may require greater use of time and resources.

Research application of session-RPE in monitoring the training load of elite endurance athletes

PurposeTRIMP and sRPE are both representative indicators of training load(TL), and the correlation between two has been widely demonstrated across various sports. The aim of this study was to investigate the reliability of sRPE-TRIMP correlation across different intensities/duration of training in cross-country skiing, and whether sRPE can serve as an validity supplement to TRIMP data in cases of lost heart rate data.Method10 athletes were used as the experimental objects. The intensity, duration and RPE of 273 different types of training sessions were collected, and statistical methods were used for data analysis.Results1. There was a significant correlation between sRPE and TRIMP (r = 0.68, p < 0.05), but the correlation differs among the LIT, MIT and HIT groups (r = 0.70, 0.46, r = 0.31, p < 0.05) 2. sRPE-TRIMP correlation among three different time duration in the LIT group (0-60 min, 60-120 min and 120-180 min), are all highly significant (r = 0.70, 0.67, 0.69, p < 0.05) and the LRsRPE-TRIMP of 3 duration have no significant differences (chow test, p > 0.05). 3. The difference in actual training duration between samples was the main reason for the difference in the application effect of sRPE, because the actual training duration ratio of LIT was 89.7 ± 16.4%; MIT, 98.5 ± 6.2%; and HIT, 94.4 ± 13.5%.Conclusion1. The linear relationship between sRPE and TRIMP (LRsRPE-TRIMP) is more significant in LIT compared to that in MIT and HIT. 2. Variations in the duration of LIT sessions do not affect the consistency of the relationship between sRPE and TRIMP. 3. Discrepancies between actual and planned training durations directly impact the significance of the LRsRPE-TRIMP.

Cross-sectional study on exercise-related skin complaints among sports students at two German universities

Sports activities can lead to exercise-related skin complaints. These include different symptoms (e.g. infections, mechanical injuries, contact dermatitis). Previous studies mostly focused only on skin infections and injuries in competitive athletes. The purpose of this study was to determine the frequency and characteristics of exercise-related skin complaints among sports students and to what extent these complaints influence physical fitness. We performed a self-administered online survey among 259 actively exercising sports students from two German universities. Descriptive analyses were conducted. The most common complaints were blistering (57.3%), dryness (56.7%), redness (44.7%), and chafing (34.0%). Hands and feet (78.0% each) were most frequently affected. Participants whose skin was particularly stressed (47.5%) had higher training duration (7.6 h/week, 95%-CI 6.8–8.3 h) than those without complaints (5.1 h/week, 95%-CI 5.5–6.7 h, p = 0.003). The students reported reduced intensity (34.7%) and frequency (22.7%) of training due to their skin complaints. A reduction in performance was reported by 32.0% of the students. Actively exercising sports students considered an intact skin as essential for their physical fitness. Reported impairments of the skin led to a reduced intensity and frequency of training. To enhance the awareness of exercise-related skin complaints, further research is necessary.

Is it time to reduce the length of postgraduate training for physician-scientists in internal medicine?

Physician-scientists play a crucial role in advancing medical knowledge and patient care, yet the long periods of time required to complete training may impede expansion of this workforce. We examined the relationship between postgraduate training and time to receipt of NIH or Veterans Affairs career development awards (CDAs) for physician-scientists in internal medicine. Data from NIH RePORTER were analyzed for internal medicine residency graduates who received specific CDAs (K08, K23, K99, or IK2) in 2022. Additionally, information on degrees and training duration was collected. Internal medicine residency graduates constituted 19% of K awardees and 28% of IK2 awardees. Of MD-PhD internal medicine-trained graduates who received a K award, 92% received a K08 award; of MD-only graduates who received a K award, a majority received a K23 award. The median time from medical school graduation to CDA was 9.6 years for K awardees and 10.2 years for IK2 awardees. The time from medical school graduation to K or IK2 award was shorter for US MD-PhD graduates than US MD-only graduates. We propose that the time from medical school graduation to receipt of CDAs must be shortened to accelerate training and retention of physician-scientists.

Advances in undergraduate and postgraduate education- bedside, simulation and E-learning

Clinical bedside teaching the cornerstone of medical education in the 19th century has been shaped and developed by changes in healthcare delivery and work practices. Developing skilled clinicians to work and thrive in these complex environments requires innovative and adaptive strategies. In this rapidly changing environment compounded by a shorter duration of training, there is an increasing focus on the student learner, team-based working and the development of professionalism. The continuum of medical education from undergraduate through postgraduate to continued professional development has been greatly enhanced by the adoption of new strategies and technologies. Simulation is long established in medical education and its benefits well recognised. Technological developments including Artificial Intelligence have supported and enhanced the quality of simulation in medical education. There is a broad range of simulation available with varying degrees of fidelity, as required, culminating in immersive virtual reality. The challenges for medical educators of the Covid-19 pandemic, with closure or restricted access to clinical patients, wards and classrooms, resulted in rapid restructuring of teaching programs and for many to move “on-line”. This resulted in widespread rapid adoption of technologically driven medical education, with E-learning, blended learning and innovative strategies to increase student engagement. The seismic changes in medical education necessitated by the Covid-19 pandemic coupled with the upskilling of medical educators and technological advances, should result in an exciting period of continued innovation in medical education, a second “Golden Era” and enhance medical education for many years to come.

Pediatric Residents Knowledge of Penicillin Allergy.

Penicillin allergy knowledge has not been evaluated specifically in the pediatric resident population. An anonymous electronic survey was distributed to all the pediatric residents in a single residency program to ascertain knowledge of penicillin allergies and allergy history taking skills. Responses among each resident class were compared using the Fisher exact test, 2-tailed. A total of 46 (52%) of 88 pediatric residents completed the survey. Only 63% reported to have had prior penicillin allergy education. All residents incorrectly identified low-risk symptoms as high-risk symptoms. The knowledge of penicillin allergy was poor across all training levels with no improvement over the duration of training. There is large support in the literature for de-labeling penicillin allergy in patients. Pediatric residents evaluate patients in childhood when most of the allergy labeling occurs. We need to consider strategies for incorporating penicillin allergy education in pediatric residency training.

Measuring and Comparing Service Delivery Time in Government and Outsourced Health Posts Affiliated with Tehran University of Medical Sciences

Background: The duration of healthcare services has a significant impact on the quality of care and patient's satisfaction. Having information on service delivery time in both government and outsourced Health Posts (HPs) can contribute to evidence-based policymaking and better resource management. Therefore, this study aims to estimate and compare service delivery time in government and outsourced HPs. Methods: This descriptive-analytical cross-sectional study was conducted in six affiliated HPs under Tehran University of Medical Sciences in 2019–2020. Data were collected through a census using a stopwatch and a time recording form during one working week. The average duration of each service (in minutes) was obtained. The results were reported using descriptive statistics and were analyzed using SPSS24 software and multivariate analysis of variance (ANOVA). Results: The total mean of duration of services provided in government HPs (777.6 minutes) was greater than that in outsourced HPs (788.5 minutes). Among the 10 services provided, the average duration of services for adolescents (20.4±4.5 minutes), young adults (20.5±5.6 minutes), middle-aged adults (26.1±10.4 minutes), and elderly individuals (24.3±13.6 minutes) in government HPs was significantly longer than in outsourced HPs (p<0.05). Additionally, the average duration of health education services (23.1±10.5 minutes) and health ambassador training (36.1±13.7 minutes) in private HPs was significantly longer than in government HPs (p<0.05). Conclusion: In outsourced HPs, it is important to focus on creating a balance between the number of visits and the staff available for services which target adolescents, young adults, middle-aged adults, and elderly individuals. In government HPs, emphasis should be placed on increasing the time allocated for educational and promotional health services. By considering the importance of service delivery time and the observed differences in findings of this study, it is crucial to prioritize the duration of service delivery as an important performance measure when comparing government and outsourced HPs.

The effect of the interaction between shooting training from different positions of the ball and eye coordination on the soccer shooting accuracy

Background and purpose This study aims to determine the effect of interaction between shooting training in terms of ball position and foot eye coordination on football shooting accuracy. Material and methods The determination of the research method can be influenced by the object of research. In this study, the method chosen was the experimental method. Data preparation in this study was carried out using a 2x2 factorial research design framework. This research aims to compare two different treatments of research subjects by applying factorial design techniques. The choice of the experimental method is considered an appropriate approach because this method involves a series of trials that include an initial test, a practice session, and ends with a final test to evaluate the results. Data collection required for this research was carried out at the UPTD SPNF SKB Salatiga football field located at Jl. Soekarno Hatta, Cebongan, Argomulyo District, Salatiga City, Central Java Province. This research was conducted over a 6 week period in February - March 2024, on Tuesdays, Wednesdays and Fridays. The training duration for each meeting is 90 minutes, with a schedule of 15.30-17.00 on Tuesdays and Wednesdays, and 14.30-16.00 on Fridays. The total number of meetings reached 16 times, excluding the initial and final tests. Results Players who have high ankle coordination who get a stationary ball training method, have an average shooting accuracy of 15.10. While players who have high ankle coordination and get a moving training method have an average shooting accuracy of 11.20. Players who have low foot-eye coordination who get the moving ball training method have an average shooting accuracy in soccer games of 9.20. Players who have low foot-eye coordination and get a stationary ball training method have an average shooting accuracy result of 8.80. Conclusions There is an interaction between training methods and ankle coordination on the results of shooting accuracy in soccer games. In players who have high ankle coordination and get a stationary ball training method gives the effect of better results than players with low ankle coordination. Players of the moving ball training method with low ankle coordination give the effect of better results than the stationary ball training method.

Adjunctive hiking bouts during 8weeks regular sailing training improves cardiorespiratory and muscular responses during hiking emulation in highly trained sailors.

To investigate the effects of 8-week hiking bench training on cardiorespiratory and muscular responses of highly trained sailors during hiking emulation. Twenty-four sailors were assigned into two groups: the hiking bench training group (HTG, n=12) and the control group (CG, n=12). Both groups maintained their regular training with the HTG performed two additional hiking bench training sessions per week for 8weeks, while the CG performed an equivalent duration of on-water sailing training. Physiological responses were assessed by performing four successive 3-min hiking bouts on a sailing emulation ergometer before and after the 8-week training period. Comparing the pretest, both groups exhibited a significant decrease (p<0.05) in the percentage of maximal oxygen uptake (%VO2max) and maximal heart rate (%HRmax); the HTG experienced a greater decrease in %VO2max in bouts 2 and 3. The root mean square (RMS) of rectus femoris (RF), vastus lateralis (VL), rectus abdominis (RA), and external oblique decreased significantly (p<0.05), whereas the mean power frequency (MPF) of RF, VL, and RA exhibited an increasing trend. The RMS of RF and RA in HTG were lower than those in CG in the initial three bouts; VL and EA in HTG were lower than those in CG in bouts 1 and 2 (p<0.05). The MPF of RA in HTG was significantly increased in bouts 2, 3, and 4 (p<0.05). Eight-week hiking bench training could improve hiking economy and the activation of lower limb and trunk muscles delaying the onset of fatigue in sailors.

AutoAugHAR: Automated Data Augmentation for Sensor-based Human Activity Recognition

Sensor-based HAR models face challenges in cross-subject generalization due to the complexities of data collection and annotation, impacting the size and representativeness of datasets. While data augmentation has been successfully employed in domains like natural language and image processing, its application in HAR remains underexplored. This study presents AutoAugHAR, an innovative two-stage gradient-based data augmentation optimization framework. AutoAugHAR is designed to take into account the unique attributes of candidate augmentation operations and the unique nature and challenges of HAR tasks. Notably, it optimizes the augmentation pipeline during HAR model training without substantially extending the training duration. In evaluations on eight inertial-measurement-units-based benchmark datasets using five HAR models, AutoAugHAR has demonstrated superior robustness and effectiveness compared to other leading data augmentation frameworks. A salient feature of AutoAugHAR is its model-agnostic design, allowing for its seamless integration with any HAR model without the need for structural modifications. Furthermore, we also demonstrate the generalizability and flexible extensibility of AutoAugHAR on four datasets from other adjacent domains. We strongly recommend its integration as a standard protocol in HAR model training and will release it as an open-source tool1.

Experimental and simulated evaluation of inverse model for shallow underground thermal storage

This study employs an inverse grey-box (IGB) modeling approach, which combines measured data and the physics of systems to predict the performance of shallow underground thermal energy storage (UTES) with top and side insulation. A simplified IGB model of the shallow UTES was developed using thermal network analysis. Experimental studies were conducted for shallow vertical and horizontal UTES configurations. Detailed models representing the field experiments were developed using the TRNSYS simulation tool and calibrated with the measured data from the experimental setup. The 4 Resistance 2 Capacitance (4R2C) IGB model was trained and tested in MATLAB using field experimental data and the data from the calibrated TRNSYS model. In comparing experimental data with the TRNSYS model for UTES, the prediction of outlet water temperature showed good agreement, with root mean square error (RMSE) and coefficient of variation of RMSE (CVRMSE) values of 0.94 °C and 3.16 % for vertical, and 0.99 °C and 2.97 % for horizontal configurations. The IGB model also aligned well with the experimental data, showing CVRMSE of 7.91 % and 3.17 % for vertical and horizontal systems, respectively. Sensitivity analysis revealed that model performance improves with longer training durations and closer testing times to training periods. However, a convergence point of 20 weeks of training data was achieved for making long-term performance predictions.

Sign Language Detection Using CNN and LSTM Based Model

In the context of our current work, we have taken a major step in examining and contrasting the effectiveness of several machine learning models for sign language recognition. Convolutional Neural Network (CNN) model building was the focus of our minor project, which resulted in the successful publication of a research paper [6]. Our method was validated by this model, which showed significant accuracy in recognizing sign language. We wanted to build a Long Short-Term Memory (LSTM) model for the same reason as we moved on to our larger project. The aim was not only to construct an additional efficient model but also to conduct a comparative analysis between the LSTM and the CNN model that was previously constructed. This comparison included a thorough assessment of both models based on a number of variables, including accuracy, loss, speed, and others. We can now confidently state that we have created an LSTM model for sign language recognition that is fully operational. In addition, we have compared our CNN model with our LSTM model, assessing both models according to training accuracy, training loss, validation accuracy, validation loss, and training duration. This development opens the door for more research in this area and represents an important turning point in our study. Our research will be strengthened by the solid foundation our findings provide. Keywords: Convolutional Neural Network, Long Short-Term Memory, Sign Language Detection, Training, Validation

Evaluation of augmented reality training for a navigation device used for CT-guided needle placement.

Numerous navigation devices for percutaneous, CT-guided interventions exist and are, due to their advantages, increasingly integrated into the clinical workflow. However, effective training methods to ensure safe usage are still lacking. This study compares the potential of an augmented reality (AR) training application with conventional instructions for the Cube Navigation System (CNS), hypothesizing enhanced training with AR, leading to safer clinical usage. An AR-tablet app was developed to train users puncturing with CNS. In a study, 34 medical students were divided into two groups: One trained with the AR-app, while the other used conventional instructions. After training, each participant executed 6 punctures on a phantom (204 in total) following a standardized protocol to identify and measure two potential CNS procedural user errors: (1) missing the coordinates specified and (2) altering the needle trajectory during puncture. Training performance based on train time and occurrence of procedural errors, as well as scores of User Experience Questionnaire (UEQ) for both groups, was compared. Training duration was similar between the groups. However, the AR-trained participants showed a 55.1% reduced frequency of the first procedural error (p > 0.05) and a 35.1% reduced extent of the second procedural error (p < 0.01) compared to the conventionally trained participants. UEQ scores favored the AR-training in five of six categories (p < 0.05). The AR-app enhanced training performance and user experience over traditional methods. This suggests the potential of AR-training for navigation devices like the CNS, potentially increasing their safety, ultimately improving outcomes in percutaneous needle placements.

Educational Needs Analysis on Actual Conditions &amp; Educational Contents for Develop the Image Making Education Program

Image making is a very important factor for people whose jobs involve providing services face-to-face with customers. In particular, the image of a beauty worker has a positive impact not only on communication with customers but also on work performance. Therefore, this study aims to analyze the education status and education content needed when developing education for beauty majors through a needs survey and prepare the basis for educational materials. A questionnaire was distributed to a total of 460 beauty majors and collected and analyzed. Statistical analysis was performed using SPSS for Windows 25.0, and frequency analysis, cross-tabulation, and descriptive statistical analysis were performed. First, out of 460 respondents, only 66 (14.3%) had participated in an image-making education program. Most of the respondents said that they participated in the training program through school classes and received once in school. Second, the appropriate frequency of training was found to be once a week for 1-2 hours per session, and the highest frequency was for lecture+practice blending classes. Third, the contents ranked 1 to 3 among the educational contents are as follows. the first rank was 'manners and etiquette', the second was 'facial expression management', the third was 'service response skills'. Teaching method is preferred a combination of lecture and practice. As duration of training, once a week and 1-2 hours per session were the most preferred. In this study, the purpose of this study is to provide basic data for future program development by analyzing the educational status and educational content.

Fast and practical intrusion detection system based on federated learning for VANET

VANET facilitates communication between vehicles and roadside units, thereby enhancing traffic safety and efficiency. However, it also introduces several attack vectors, compromising security and privacy. To enhance the practicality and precision of existing VANET intrusion detection systems, we propose a novel hybrid algorithm named VAN-IDS. This algorithm combines packet analysis and physical feature analysis. Temporal properties of packets are analyzed using Bi-LSTM, while physical attributes of vehicles are evaluated using LightGBM. Predictive outputs from both models are merged using the Dempster–Shafer theory. Data is collected from the F2MD simulation environment, and experiments are conducted to evaluate the efficacy of VAN-IDS. Results show that VAN-IDS achieves an accuracy exceeding 98.5% in detecting DoS and Sybil attacks, surpassing existing VANET IDSs and meeting real-time detection requirements. Federated learning is introduced, with VAN-FED-IDS designed to accelerate model training and updates, while protecting the privacy of the model and dataset. Roadside units (RSUs) serve as edge computing nodes for local model training, while cloud services aggregate models for collaborative training of detection algorithms. In these experiments, the open-source federated learning frameworks Flower and FedTree are used to assess communication overhead and training duration in both single-machine simulation and multi-machine deployment scenarios. This demonstrates the viability of federated learning, which can protect local data privacy, expedite model training and updates within the IDS, and maintain the original model’s detection accuracy.

Does working memory training improve emotion regulation and reduce internalizing symptoms? A pair of three-level meta-analyses

BackgroundEmotional dysfunction is a core feature of many mental disorders. Working memory training (WM-T) is promising to improve emotion regulation and reduce internalizing symptoms (anxiety and depressive symptoms), but the results are mixed. Therefore, we conducted meta-analyses to clarify these mixed results. MethodsWe searched Web of Science, PubMed, ScienceDirect, and EBSCO to identify relevant studies and screened the references. The effect size was calculated using Hedges’ g. Three-level, random-effects models were run using metafor in R. ResultsThe current study included 44 articles, of which 29 were involved with emotion regulation, and 30 were involved with internalizing symptoms. The results showed that WM-T could yield emotional benefits, but the benefits were confined to enhancing explicit emotional regulation capacity and reducing anxiety symptoms. For the meta-analysis regarding the effect of WM-T on emotion regulation, there was no significant moderator. For the meta-analysis regarding the effect of WM-T on internalizing symptoms, the emotional valence of the material and control group were statistically significant moderators. ConclusionWM-T could yield certain emotional effects, but only to improve explicit emotion regulation capacity and reduce anxiety symptoms. In addition, some measures could enhance the effect, such as targeting specific populations, increasing the number of training sessions (≥15) or duration (>450 minutes), using negative material, and using n-back training tasks.

Enhanced Classification of Imbalanced Medical Datasets using Hybrid Data-Level, Cost-Sensitive and Ensemble Methods

Addressing the class imbalance in classification problems is particularly challenging, especially in the context of medical datasets where misclassifying minority class samples can have significant repercussions. This study is dedicated to mitigating class imbalance in medical datasets by employing a hybrid approach that combines data-level, cost-sensitive, and ensemble methods. Through an assessment of the performance, measured by AUC-ROC values, Sensitivity, F1-Score, and G-Mean of 20 data-level and four cost-sensitive models on seventeen medical datasets - 12 small and five large, a hybridized model, SMOTE-RF-CS-LR has been devised. This model integrates the Synthetic Minority Oversampling Technique (SMOTE), the ensemble classifier Random Forest (RF), and the Cost-Sensitive Logistic Regression (CS-LR). Upon testing the hybridized model on diverse imbalanced ratios, it demonstrated remarkable performance, achieving outstanding performance values on the majority of the datasets. Further examination of the model's training duration and time complexity revealed its efficiency, taking less than a second to train on each small dataset. Consequently, the proposed hybridized model not only proves to be time-efficient but also exhibits robust capabilities in handling class imbalance, yielding outstanding classification results in the context of medical datasets.

Transparency in Cognitive Training Meta-analyses: A Meta-review.

Meta-analyses often present flexibility regarding their inclusion criteria, outcomes of interest, statistical analyses, and assessments of the primary studies. For this reason, it is necessary to transparently report all the information that could impact the results. In this meta-review, we aimed to assess the transparency of meta-analyses that examined the benefits of cognitive training, given the ongoing controversy that exists in this field. Ninety-seven meta-analytic reviews were included, which examined a wide range of populations with different clinical conditions and ages. Regarding the reporting, information about the search of the studies, screening procedure, or data collection was detailed by most reviews. However, authors usually failed to report other aspects such as the specific meta-analytic parameters, the formula used to compute the effect sizes, or the data from primary studies that were used to compute the effect sizes. Although some of these practices have improved over the years, others remained the same. Moreover, examining the eligibility criteria of the reviews revealed a great heterogeneity in aspects such as the training duration, age cut-offs, or study designs that were considered. Preregistered meta-analyses often specified poorly how they would deal with the multiplicity of data or assess publication bias in their protocols, and some contained non-disclosed deviations in their eligibility criteria or outcomes of interests. The findings shown here, although they do not question the benefits of cognitive training, illustrate important aspects that future reviews must consider.

The alterations of functional brain networks and its relationship with sport decision-making and training duration in soccer players across different skill levels

Studies have indicated that skilled soccer players possess superior decision-making abilities compared to their less-skilled counterparts. However, the underlying neural mechanism for this phenomenon remains incompletely understood. In our investigation, we explored distinctions in the topology of functional brain networks between skilled and less-skilled soccer players. Employing mediating analysis, we scrutinized the relationships among functional brain network parameters, training duration, and decision-making accuracy. Our findings revealed that skilled soccer players demonstrated significantly higher decision-making accuracy compared to their less-skilled counterparts. Skilled players also exhibited increased values in the cluster coefficient, characteristic path length and local efficiency but lower global efficiency. Moreover, we observed enhanced functional brain connectivity within the occipital and cingulo-opercular networks, as well as between the fronto-parietal and cingulo-opercular networks in skilled soccer players. Cluster coefficient and functional connectivity between fronto-parietal and cingulo-opercular networks had positive mediating effects on the association between training duration and sport decision-making accuracy. In conclusion, our study provides initial evidence for distinctions in functional brain network parameters between soccer players with varying skill levels and their relationship with sport decision-making accuracy.

Cochlear Implants after Meningitis and Otosclerosis: A Comparison between Cochlear Ossification and Speech Perception Tests.

(1) Background: Performance after Cochlear Implantation (CI) can vary depending on numerous factors. This study aims to investigate how meningitis or otosclerosis can influence CI performance. (2) Methods: Retrospective analysis of CI performance in patients with etiological diagnosis of meningitis or otosclerosis, comparing the etiologies and analyzing the image findings, along with electrode array insertion status and technique. (3) Results: Speech recognition in CI patients with otosclerosis improves faster than in patients with meningitis. Other features such as radiological findings, degree of cochlear ossification, surgical technique used and total or partial insertion of electrodes do not seem to be directly related to speech recognition test performance. (4) Conclusions: Patients should be warned that their postoperative results have a strong correlation with the disease that caused their hearing loss and that, in cases of meningitis, a longer duration of speech-language training may be necessary to reach satisfactory results.