Low Performers Research Articles

The Validity of a Portable Strain-Gauge Apparatus Versus a Commercial Isokinetic Dynamometer for Evaluating Knee Extension Kinetics.

Isokinetic dynamometers are widely used when assessing neuromuscular function including knee extension kinetics. However, these dynamometers are often prohibitively expensive and are not portable. Thus strain-gauge technology has grown in popularity. The purpose of this study was to compare kinetic data captured via an isokinetic dynamometer against an affordable and portable strain-gauge with a treatment plinth during maximal isometric knee extensions. Cross-sectional study. Healthy participants (8 males and 6 females; age 30.2±7.1 years) volunteered and performed knee extensions at a 90° knee angle on a dynamometer and a treatment plinth with a portable strain-gauge. Peak force (PF), peak rate of force development (PRFD), rate of force development (RFD2080) and impulse (IMP2080) from 20-80% of onset to peak force were assessed using both strain-gauge and isokinetic dynamometer. Between-device differences were evaluated by the Wilcoxon signed-rank test, Cohen's d effect sizes (ES), Pearson's correlation coefficients (r), and Bland-Altman plots. No significant or meaningful differences were identified between isokinetic and strain-gauge devices (all p≥0.268, ES≤0.35). However, slightly greater (2.5-9.5%) outputs were observed with the isokinetic dynamometer. Very large significant between-device correlations were found for PF (r=0.77, p=0.001) and PRFD (r=0.73, p=0.003), while small and moderate non-significant between-device correlations were found for RFD2080 (r=0.48, p=0.079) and IMP2080 (r=0.59, p=0.060). Bland-Altman plots did not reveal apparent biases from high to low performers. These results indicate that the strain-gauge device can produce valid maximal and rapid force expression measurements. Similar results, such as those quantified via an isokinetic device, can be obtained without extreme rigour and constraint. The study's findings support using the practically relevant treatment plinth and strain-gauge combination as a suitable alternative to the isokinetic dynamometry for measuring PF and PRFD. Therefore, more rehabilitation and sports performance practitioners can confidently assess knee extension kinetics. 3.

Analysis of personality traits using Myers-Briggs type indicator in correlation to the academic performance of BS ECE undergraduates

academic performance among Bachelor of Science in Electronics Engineering (BS ECE) students. A sample of 70 students completed the Myers-Briggs Type Indicator (MBTI) assessment and provided academic performance data. Statistical analyses using Microsoft Excel examined associations between MBTI types and achievement. Overall, sensing and introverted types like ISTJ and ISFJ were most prevalent while intuitive, extroverted types were uncommon. The highest academic scorers frequently exhibited introverted, sensing, feeling traits such as ISFJ. Lower performers sometimes showed opposite extraverted, thinking types like ESTJ. Results indicate certain personality profiles may be drawn to engineering fields where they can thrive. However, variations emerged even among poorer scorers. Differences in thinking versus feeling dimensions also distinguished top and bottom achievers. While insightful, the small sample size limits generalizability. Assessing more undergraduate year levels could provide additional perspectives. Findings imply tailoring instructional methods to traits like introversion or thinking may optimize student engagement and learning. Monitoring personality development throughout engineering curricula may also support retention. Further research on personality's interaction with program demands over time is needed. Exploring larger samples across multiple cohorts and degrees could reveal more patterns. This initial investigation fills a knowledge gap, but expanded studies using bigger samples will deepen understanding of links between personality and performance in engineering education.

Utility of a Benchmarking Report for Balancing Infection Prevention and Antimicrobial Stewardship in Children with Complicated Appendicitis.

To develop a severity-adjusted, hospital-level benchmarking comparative performance report for postoperative organ space infection and antibiotic utilization in children with complicated appendicitis. No benchmarking data exist to aid hospitals in identifying and prioritizing opportunities for infection prevention or antimicrobial stewardship in children with complicated appendicitis. This was a multicenter cohort study using NSQIP-Pediatric data from 16 hospitals participating in a regional research consortium, augmented with antibiotic utilization data obtained through supplemental chart review. Children with complicated appendicitis who underwent appendectomy from 07/01/2015 to 06/30/2020 were included. Thirty-day postoperative OSI rates and cumulative antibiotic utilization were compared between hospitals using observed-to-expected (O/E) ratios after adjusting for disease severity using mixed effects models. Hospitals were considered outliers if the 95% confidence interval for O/E ratios did not include 1.0. 1790 patients were included. Overall, the OSI rate was 15.6% (hospital range: 2.6-39.4%) and median cumulative antibiotic utilization was 9.0 days (range: 3.0-13.0). Across hospitals, adjusted O/E ratios ranged 5.7-fold for OSI (0.49-2.80, P=0.03) and 2.4-fold for antibiotic utilization (0.59-1.45, P<0.01). Three (19%) hospitals were outliers for OSI (1 high and 2 low performers), and eight (50%) were outliers for antibiotic utilization (5 high and 3 low utilizers). Ten (63%) hospitals were identified as outliers in one or both measures. A comparative performance benchmarking report may help hospitals identify and prioritize quality improvement opportunities for infection prevention and antimicrobial stewardship, as well as identify exemplar performers for dissemination of best practices.

Reinforcement learning tutor better supported lower performers in a math task

Resource limitations make it challenging to provide all students with one of the most effective educational interventions: personalized instruction. Reinforcement learning could be a pivotal tool to decrease the development costs and enhance the effectiveness of intelligent tutoring software, that aims to provide the right support, at the right time, to a student. Here we illustrate that deep reinforcement learning can be used to provide adaptive pedagogical support to students learning about the concept of volume in a narrative storyline software. Using explainable artificial intelligence tools, we extracted interpretable insights about the pedagogical policy learned and demonstrated that the resulting policy had similar performance in a different student population. Most importantly, in both studies, the reinforcement-learning narrative system had the largest benefit for those students with the lowest initial pretest scores, suggesting the opportunity for AI to adapt and provide support for those most in need.

Pupillary correlates of individual differences in n-back task performance.

We used pupillometry during a 2-back task to examine individual differences in the intensity and consistency of attention and their relative role in a working memory task. We used sensitivity, or the ability to distinguish targets (2-back matches) and nontargets, as the measure of task performance; task-evoked pupillary responses (TEPRs) as the measure of attentional intensity; and intraindividual pretrial pupil variability as the measure of attentional consistency. TEPRs were greater on target trials compared with nontarget trials, although there was no difference in TEPR magnitude when participants answered correctly or incorrectly to targets. Importantly, this effect interacted with performance: high performers showed a greater separation in their TEPRs between targets and nontargets, whereas there was little difference for low performers. Further, in regression analysis, larger TEPRs on target trials predicted better performance, whereas larger TEPRs on nontarget trials predicted worse performance. Sensitivity positively correlated with average pretrial pupil diameter and negatively correlated with intraindividual variability in pretrial pupil diameter. Overall, we found evidence that both attentional intensity (TEPRs) and consistency (pretrial pupil variation) predict performance on an n-back working memory task.

대학 핵심역량기반 학습역량 측정도구 개발 및 효과 탐색

Objectives This study aims to develop a scale to measure a set of learning competence elements based on the core college competencies by extracting them and investigating their effects by applying an extracurricular pro-gram to reinforce the competence of low performers in learning.&#x0D; Methods For these purposes, the investigator tested the scale for its content validity with two Delphi surveys based on previous studies, selecting 176 items after the first survey and six components and 51 preliminary items after the second one. The main study carried out a confirmatory factor analysis to test the items by the component in fitness, reliability, and validity with students who participated in the extracurricular program and tested the model for fitness based on discriminant and convergent validity with AMOS 21.0.&#x0D; Results Based on the results, the study developed a scale to measure learning competence with six components and 35 items. To investigate its effects, the extracurricular program to reinforce learning competence was applied to ten low performers in learning in two semesters with changes to their learning competence measurements analyzed. The analysis results show that there were significant outcomes for learning motives, self-directed, cre-ative convergence, learning strategies, and community spirit under the six components and no significant out-comes for learning affection.&#x0D; Conclusions Based on these findings, the study offers some objective ground data helpful for each college and university to develop a custom scale to measure learning competence based on the core competencies, measure the degree of competence cultivation based on the characteristics of learners, and assess outcomes with custom extracurricular program supports, thus holding its research implications. Furthermore, we aim to lay the founda-tion for practicing and strengthening core competency education.

A Bebras Computational Thinking (ABC-Thinking) program for primary school: Evaluation using the competent computational thinking test

Bebras tasks are considered to develop Computational Thinking (CT) and are currently used for this purpose in many studies. However, the relationship between Bebras tasks and CT is recent and, given the scarcity of validated instruments for assessing CT that are not associated with a specific learning environment, the expected development of CT through Bebras tasks has not been sufficiently evaluated, especially in Primary School. For this reason, we designed the ABC-Thinking program for the development of CT in which a set of Bebras tasks were selected and categorised according to the CT skills they were related to, specific lesson plans were designed to integrate these tasks in a 12-week curriculum, and teachers were trained to apply the program. Using the competent Computational Thinking test (cCTt) in a pre-post-test experimental design, we looked to determine whether Primary School students developed specific CT skills after the program, and, therefore, whether Bebras could be considered suitable for the development of this competence. The results show a significant development in specific CT skills, interesting findings in the gender differences in this development, and between high and low performers. Finally, qualitative data indicate the suitability of the ABC-Thinking program with respect to teachers’ practice.

PISA Maths-Reading index and its relationship with gender and levels of performance

The Spanish PISA 2018 students sample (>35,900 fifteen-year-old students) has been analysed by calculating the Mathematics minus Reading scores of all individuals in the sample, relating this Maths-Reading index to the personal and educational characteristics of the respondents. Results of the first step of the analysis show that the positive Maths-Reading Index values (higher scores in maths than in reading) are mainly related to gender, and negative values (higher scores in reading) are mainly related to the joy of reading and to a series of factors linked to interest and respect for other cultures, among others. Subsequently, the individual level of global performance is taken into account with a cluster analysis generating groups of high, medium and low performers. Changes in factors affecting the Maths-Reading index when this level-based grouping is considered are analysed, showing the importance of grade repetition for low performers and the influence of socio-economic factors for medium performers, while high performers are affected especially by non-cognitive aspects such as self-concept or expected occupational status. Finally, combined effects of gender and level of performance are taken into account, showing that the factors affect male and female students differently for the disparate performance-based groups. This study contributes to a more precise knowledge of the main factors associated with students’ tendency to have better scores in mathematical items than in reading items or vice versa, and to distinguish the differential role of personal and environmental factors not only globally, but also when gender and performance levels are taken into account. Studying this personal tendency is significant as it is related to students’ study choice, especially Science-Technology-Engineering-Mathematics (STEM) degrees.

A neuroimaging measure to capture heterogeneous patterns of atrophy in Parkinson’s disease and dementia with Lewy bodies

IntroductionParkinson’s disease (PD) and Dementia with Lewy bodies (DLB) show heterogeneous brain atrophy patterns which group-average analyses fail to capture. Neuroanatomical normative modelling overcomes this by comparing individuals to a large reference cohort. Patient-specific atrophy patterns are measured objectively and summarised to index overall neurodegeneration (the ‘total outlier count’). We aimed to quantify patterns of neurodegenerative dissimilarity in participants with PD and DLB and evaluate the potential clinical relevance of total outlier count by testing its association with key clinical measures in PD and DLB. Materials and methodsWe included 108 participants with PD and 61 with DLB. PD participants were subclassified into high and low visual performers as this has previously been shown to stratify those at increased dementia risk. We generated z-scores from T1w-MRI scans for each participant relative to normative regional cortical thickness and subcortical volumes, modelled in a reference cohort (n = 58,836). Outliers (z < −1.96) were aggregated across 169 brain regions per participant. To measure dissimilarity, individuals’ Hamming distance scores were calculated. We also examined total outlier counts between high versus low visual performance in PD; and PD versus DLB; and tested associations between these and cognition. ResultsThere was significantly greater inter-individual dissimilarity in brain-outlier patterns in PD poor compared to high visual performers (W = 522.5; p < 0.01) and in DLB compared to PD (W = 5649; p < 0.01). PD poor visual performers had significantly greater total outlier counts compared to high (β = -4.73 (SE = 1.30); t = -3.64; p < 0.01) whereas a conventional group-level GLM failed to identify differences. Higher total outlier counts were associated with poorer MoCA (β = -0.55 (SE = 0.27), t = -2.04, p = 0.05) and composite cognitive scores (β = -2.01 (SE = 0.79); t = -2.54; p = 0.02) in DLB, and visuoperception (β = -0.67 (SE = 0.19); t = -3.59; p < 0.01), in PD. ConclusionsNeuroanatomical normative modelling shows promise as a clinically informative technique in PD and DLB, where patterns of atrophy are variable.

A Visuo-Haptic System for Nodule Detection Training: Insights from EEG and behavioral analysis.

Medical palpation is a key skill for clinicians. It is typically trained using animal and synthetic models, which however raise ethical concerns and produce high volumes of consumables. An alternative could be visuo-haptic simulations, despite their training efficacy has not been proved yet. The assessment of palpatory skills requires objective methods, that can be achieved by combining performance metrics with electroencephalography (EEG). The goals of this study were to: (i) develop a visuo-haptic system to train nodule detection, combining a Geomagic Touch haptic device with a visuo-haptic simulation of a skin patch and a nodule, implemented using SOFA framework; (ii) assess whether this system could be used for training and evaluation. To do so, we collected performance and EEG data of 19 subjects performing multiple repetitions of a nodule detection task. Results revealed that participants could be divided in low and high performers; the former applied a greater pressure when looking for the nodule and showed a higher EEG alpha (8.5 - 13 Hz) peak at rest; The latter explored the skin remaining on its surface and were characterized by low alpha power. Furthermore, alpha power positively correlated with error and negatively with palpation depth. Altogether, these results suggest that alpha power might be an indicator of performance, denoting an increase in vigilance, attention, information processing, cognitive processes, and engagement, ultimately affecting strategy and performance. Also, the combination of EEG with performance data can provide an objective measure of the user's palpation ability.

A Comparative Study on Learning styles and Strategies of High and Low Preforming Students on Mathematics

The students in a class are diverged from many perspectives, among such perspectives their learning styles and strategies is one of the major. Basically, we as a teacher rather used to notice the learning styles and strategies of our students, we just motivated to categorize our students as high performer or low performer. In this context, this is a case study research on the topic 'A comparative study on learning styles and strategies of high and low performing students on mathematics' with the objectives to compare the learning strategies used by high and low performing students in mathematics. For which, four (two from each categories) students were selected purposively on the basis of their performance in mathematics as the key research participants from a higher secondary level. The identification of their learning strategies are based on four subheadings as readiness for learning, pre-knowledge of the content, process for learning and solving a problem. With the prolong engagement with participants, the study concluded with the various differences as well as similarities in each category and on the basis of such differences and similarities, the study further emphasized to be aware about their learning styles and strategies is more beneficial to create the meaningful teaching learning environment in the classroom.

Improving Statewide Post-Operative Sepsis Performance Measurement Using Hospital Risk Adjustment Within a Surgical Collaborative.

Background: The Georgia Quality Improvement Program (GQIP) surgical collaborative participating hospitals have shown consistently poor performance in the post-operative sepsis category of National Surgical Quality Improvement Program data as compared with national benchmarks. We aimed to compare crude versus risk-adjusted post-operative sepsis rankings to determine high and low performers amongst GQIP hospitals. Patients and Methods: The cohort included intra-abdominal general surgery patients across 10 collaborative hospitals from 2015 to 2020. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) sepsis definition was used among all hospitals for case abstraction and NSQIP data were utilized to train and validate a multivariable risk-adjustment model with post-operative sepsis as the outcome. This model was used to rank GQIP hospitals by risk-adjusted post-operative sepsis rates. Rankings between crude and risk-adjusted post-operative sepsis rankings were compared ordinally and for changes in tertile. Results: The study included 20,314 patients with 595 cases of post-operative sepsis. Crude 30-day post-operative sepsis risk among hospitals ranged from 0.81 to 5.11. When applying the risk-adjustment model which included: age, American Society of Anesthesiology class, case complexity, pre-operative pneumonia/urinary tract infection/surgical site infection, admission status, and wound class, nine of 10 hospitals were re-ranked and four hospitals changed performance tertiles. Conclusions: Inter-collaborative risk-adjusted post-operative sepsis rankings are important to present. These metrics benchmark collaborating hospitals, which facilitates best practice exchange from high to low performers.

Evaluation of different feedback designs for target guidance in human controlled robotic cranes: A comparison between high and low performance groups

Labour shortages and costly operator training are driving the need for digital on-board robotic crane operator support in forestry and construction. This simulator study investigated the effects of sonification (auditory, pitch/loudness) and continuous visual (brightness/size) feedback on aiming movements with a robotic crane for low and high performers. The feedback was designed non-linear and linear. Thirty-six participants controlled a robotic crane bimanually using joysticks across 320 movements. Performance and skill indicators (movement time, accuracy, trajectory, smoothness) as well as satisfaction, and usefulness were assessed. Low-performing participants showed higher movement accuracy, particularly with non-linear pitch feedback compared to visual feedback. High performers exhibited no significant performance improvement in movement time, accuracy, or smoothness. There was no effect of linear or non-linear mapping of the feedback. Additionally, perceived satisfaction was lower with auditory than visual feedback. These results suggest that real-time auditory feedback can enhance operator accuracy whereas acceptance remains challenging.

Understanding asymmetric effects of attribute performance on tourist satisfaction with island tourism using user-generated data

PurposePast research often relies on linear relationship assumptions from the perspective of managers when studying the relationship between attribute performance and satisfaction. However, this study extracts tourists’ online reviews to explore asymmetric relationships and identifies island tourism satisfiers, hybrids and dissatisfiers.Design/methodology/approachThe research uses 3,523 reviews from Tripadvisor to examine Langkawi Island’s tourist satisfaction. Latent Dirichlet allocation (LDA) machine-learning approach, penalty–reward contrast analysis and asymmetric impact-performance analysis (AIPA) were employed to extract and analyse the data.FindingsLangkawi’s dissatisfiers included “hotel and restaurant”, “beach leisure”, “water sport”, “snorkelling”, “commanding view”, “waterfall”, “sky bridge walk”, “animal show”, “animal feeding”, “history culture”, “village activity” and “duty-free mall”. Amongst these, five were low performers. Hybrids encompassed “ticket purchasing”, “amenity” “traditional food market” and “gift and souvenir”, all of which were low performers. Only one attribute was categorised as a satisfier: “nature view” which performed exceptionally well.Practical implicationsThis study provides recommendations to enhance tourist satisfaction and address tourist dissatisfaction. The elements requiring immediate attention for enhancement are the five low-performance dissatisfiers, as they represent tourists’ fundamental expectations. Conversely, the satisfier or excitement factor (i.e. nature views – mangroves and wildlife) could be prominently featured in promotional materials.Originality/valueThis research constitutes an early endeavour to categorise attributes of island tourism into groups of satisfaction, hybrid or dissatisfaction based on user-generated data. It is underpinned by two-factor and three-factor theories.

Vertical Jump Neuromuscular Performance Characteristics Determining On-Court Contribution in Male and Female NCAA Division 1 Basketball Players.

While various quantifiable physical attributes have been found to contribute to athletes' performance, there is a lack of scientific literature focused on examining how they relate to success during competition performance. The aim of this study was to investigate different countermovement jump (CMJ)-derived force-time characteristics and their utility in distinguishing high from low performers within a measure of on-court contribution (i.e., minutes per game played). Twenty-nine collegiate athletes (n = 15 males and n = 14 females) volunteered to participate in this investigation and performed CMJs on dual force plates sampling at 1000 Hz, weekly over the course of their basketball season. The athletes' average of their three best test-days across the season was used for further analysis. To identify their on-court contribution, athletes were divided into groups with high and low minutes per game, based on a median-split analysis. The findings suggest that at the overall group level (i.e., both genders), the modified reactive strength index (mRSI) and braking rate of force development (RFD) revealed the greatest between-group magnitudes of difference, with athletes playing more minutes per game showing greater performance. At the team-specific level, the braking RFD, average braking velocity, and mRSI were shown to be the greatest differentiators between groups for the men's team. The women's high-minutes group displayed greater magnitudes of mRSI and jump height. By identifying the neuromuscular qualities seen in top performers within their respective populations, the attributed physical performance underpinning these qualities may be identified, providing practitioners with insights into physical performance qualities and training methodologies that have the potential to influence basketball performance.

Identifying Individualized Neurophysiological Causal Features for Working Memory Performance: Implications for Non‐Invasive Brain Stimulation

AbstractBackgroundNon‐invasive brain stimulation (NIBS) has been extensively used to target specific neural oscillations with the aim of improving working memory performance. However, current NIBS paradigms have two main limitations: first, lack of personalization and second, a need for a randomized controlled trial (RCT) to infer causality between targets of NIBS and subsequent performance. RCT is a powerful measure to infer causality, but its implementation is expensive, time consuming, and sometimes simply not possible. Therefore, our aim was to use computational models and observational data to discover causal relations between neural oscillations and working memory performance to identify potential targets and stimulation parameters for personalized NIBS paradigms.MethodWe used electroencephalography (EEG) data of 66 young healthy participants collected while performing a 3‐back working memory task. Using graphical causal modeling, we extracted individualized causal brain oscillations of 3‐back performance and compared the causal features between two groups: high and low performers.ResultTotal number of causal features in high performers was higher than low performers. Among the causal features, right temporal gamma oscillation was ∼5 times (z‐score = 3.87, p = 0.003) more frequently a causal feature among high performers than low performers. However, the power of causal temporal gamma oscillation was not different between the two groups.ConclusionOur findings suggest that a potential approach to improve working memory performance using NIBS is to induce more causal gamma oscillations by, for example, generating more local gamma entrainment over the right temporal cortex and not necessarily by increasing gamma power.

Evaluating cognitive phenotypes and associations with neuroimaging biomarkers of dementia in a sample of aging individuals using unsupervised machine learning

AbstractBackgroundOtherwise cognitively normal individuals can experience age‐related cognitive dysfunction and may present with heterogenous patterns of cognitive impairment. There is limited knowledge regarding the presence and stability of cognitive subtypes observed in individuals with mild cognitive impairment and dementia (e.g., dysexecutive, non‐amnestic). Further, the extent to which cognitive subtypes related to age‐ and dementia‐related neuroimaging biomarkers is uncertain.MethodThis study sought to evaluate the presence and composition of cognitive subtypes in a large diverse community sample of aging individuals without dementia (NC; Baseline N = 337; Table 1). Participants enrolled in the Wake Forest ADRC and completed an annual battery of cognitive assessments (Uniform Data Set; NACC), the Mini‐Mental State Exam (MMSE), and Clinical Diagnostic Rating Scale (CDR). Unsupervised machine learning (e.g., clustering: hierarchical, k‐means, and k‐medoids algorithms; 1000 bootstrap iterations; majority voting rule) was applied to the battery of cognitive assessments. Demographic characteristics and neuroimaging measures of amyloid deposition (global PiB PET SUVr; Aβ‐PET), total brain volume (BVOL), diffusion‐weighted fractional anisotropy (FA), and NODDI freewater (FW) were compared across prospective clusters using general linear models. Highly correlated cognitive metrics (r&gt;.85) were removed prior to analysis.ResultCluster analyses using baseline cognitive scores suggested NC participants could be partitioned into two to eight clusters; two primary clusters representing one large homogenous group of relatively unimpaired individuals and another heterogenous cluster composed of 4‐7 possible cognitive subgroups (Figure 1). The two‐cluster solution partitioned NC participants into higher and lower cognitive performers. Across cluster solutions, lower performing individuals were older, had higher Aβ‐PET, and lower total brain volume on average (p&lt;.05; Figure 2).ConclusionWe did not observe well‐defined clusters representing distinct cognitive subtypes reported in previous studies (e.g., dysexecutive, amnestic, visuospatial). However, a heterogenous subset of NC participants exhibited substantial variability across assessments. Three‐ and four‐cluster solutions identified individuals with greater impairment in executive functioning, and verbal learning and memory respectively. Findings highlight the need to model complex patterns of cognitive abilities in otherwise healthy older adults. Future longitudinal work will assess how health information and neuroimaging biomarkers of dementia contribute to the composition and stability of cognitively defined subgroups.

Vocal pitch matching in early childhood as a relative cognitive strength among low academic performers

In this study, using some novel measures, we examined vocal pitch matching in 4- and 5-year-old children in transitional kindergarten classrooms and, at two time points, tested relationships between children’s singing pitch accuracy and their classroom grades as well as performance on standardized measures of developing cognitive and academic skills. Consistent with previous studies, children’s grades were strongly correlated with their performance on standardized measures and differed significantly by gender, maternal education, household income and household language. In contrast, vocal pitch matching and tonal pitch processing showed no consistent relationship to grades, standardized tests or sociodemographic variables, and children with lower academic performance showed statistically equivalent pitch singing on average compared to their peers with higher grades. These findings suggest pitch processing and production abilities may be a relative cognitive strength among children doing less well in school, which may be explored for developing programmes to lift their academic performance.

Biomarker Profiling for Alzheimer‐like Dementia in Aged Non‐human Primates

AbstractBackgroundAlzheimer’s disease (AD) places increasingly burdens on global healthcare. Non‐human primates (NHPs) have been used in preclinical pharmacology for AD drug discovery and they were mainly based on induction by amyloid plaque. However, previous strategies focused on clearance and prevention of amyloid plaques and neurofibrillary inclusions have mostly yielded discouraging results in clinical trials for AD. More fitting NHP models reflective of natural ageing of brain with an AD‐related clinical profile would be most desirable for translational pharmacology. To address this, the pilot study herein profiled a group of aged NHPs for biomarkers characteristic of AD‐like dementia, including cognitive behavior, diagnostic neuroimaging, EEG, and amyloid beta 42 (Aβ42) in cerebrospinal fluid (CSF).MethodTwo groups of male Macaca fascicularis (adult: 9‐11 years, n = 4; aged: 20‐25 years, n = 10) were trained to perform a delayed response task (DRT) to assess their short term memory. Meanwhile, their CSF levels of Aβ42 were determined. EEG signals at rest were captured with Neuroscan EEG System and data processed with customized Matlab code. The volume of hippocampus in eight selected animals were analyzed through a 3‐D reconstruction with MRI imaging.ResultSix (6) out of 10 aged animals showed lower DRT performance (successful rate &lt; 80%) than the remaining 4 and those in the adult group. The overall DRT performance was positively correlated with the CSF levels of Aβ42 in all animals. Moreover, we observed the slowing of EEG activity (increased δ &amp; θ activity and decreased β activity) in the frontal lobe and smaller average volume of hippocampus in the low DRT performers vis‐à‐vis the rest of the animals.ConclusionWe identified a group of aged NHPs with spontaneous dementia, with cognitive, electrophysiological and brain structural characteristic of mild cognitive impairment in the humans. Their CSF levels of Aβ42 inversely correlated with the memory function. Most notably, EEG and neuroimaging showed promising potential as non‐invasive approaches for the evaluation of aging‐related dementia of NHP in the longitudinal studies. The translational value of such animals could provide important insight to the disease progress and the therapeutic efficacy of AD treatment in the preclinical stages.

Formative assessments during COVID-19 pandemic: an observational study on performance and experiences of medical students

Background Because of COVID-19, the 2020 written medical examinations were replaced by mandatory formative online assessments. This study aimed to determine students’ performance, self-assessment of performance, and perception about the switch from a summative to a formative approach. Methods Medical students from year 2 to 5 (n=648) were included. They could repeat each test once or twice. They rated their performance after each attempt and were then given their score. Detailed feedback was given at the end of the session. An online survey determined medical students’ perception about the reorganization of education. Two items concerned the switch from summative to formative assessments Results Formative assessments involved 2385 examinees totaling 3197 attempts. Among examinees, 30.8% made at least 2 attempts. Scores increased significantly at the second attempt (median 9.4, IQR 10.8), and duration decreased (median -31.0, IQR 48.0). More than half of examinees (54.6%) underestimated their score, female students more often than male. Low performers overestimated, while high performers underestimated their scores. Students approved of the switch to formative assessments. Stress was lessened but motivation for learning decreased. Conclusions Medical students’ better scores at a second attempt support a benefit of detailed feedback, learning time and re-test opportunity on performance. Decreased learning motivation and a minority of students repeating the formative assessments point to the positive influence of summative assessment on learning.