Objective Measures Of Performance Research Articles

Comparing the effectiveness of AR training and slide-based training: The case study of metro construction safety

Metro construction poses significant risks and is prone to severe safety accidents. Safety training is critical to mitigate risks and reduce the number of accidents, as it allows workers to enhance their skills in risk identification, risk assessment, and risk response and ultimately reduce accidents. However, traditional training methods used today, such as slide presentations, videos, or text-based materials, provide a passive learning environment, which can limit their effectiveness in knowledge transfer. Augmented Reality (AR) has emerged as a promising tool for training, allowing trainees to have an active learning environment. Nevertheless, research on assessing the effectiveness of AR safety training while comparing it with traditional methods is still limited. This study aims to compare the short-term and long-term effects on objective performance measures and subjective evaluations of both traditional and AR training. This is done by developing a new AR safety training for metro construction and comparing it with an equivalent slide-based safety training with 72 participants divided into two training groups. The selected safety case study covers the entire safety risk management process, including risk identification, risk assessment, and risk response. Results indicate that AR training is more effective than traditional training in terms of short-term knowledge acquisition of risk identification and long-term knowledge retention of risk identification, risk assessment, and risk response. These findings can have implications for the design of future safety training guidelines and recommendations.

Heart rate variability as an indicator of fatigue: A structural equation model approach

Driver fatigue significantly impairs performance and is a major risk factor for road crashes. However, fatigue is difficult to objectively measure and quantify. This study aimed to elucidate associations between heart rate variability (HRV) metrics and multidimensional fatigue construct encompassing objective and subjective measures in young drivers with self-reported short sleep. Eighty-four young adults underwent assessments during simulated driving. HRV indices RMSSD and LF/HF ratio were derived from an electrocardiogram, while relative Theta power, oculography drowsiness, lane position variability, and Karolinska Sleepiness Score measured fatigue. RMSSD negatively correlated with Theta power, and LF/HF ratio positively correlated with position variability. Exploratory factor analysis extracted three factors, with RMSSD and LF/HF loading onto one. Structural equation modelling tested the prediction of a latent fatigue construct from HRV. Two models demonstrated an acceptable fit. RMSSD negatively predicted fatigue, explaining 6.4 % of the variance, while the LF/HF ratio positively predicted fatigue, accounting for 3.7 % of the variance. In summary, HRV, particularly RMSSD, showed significant relationships with multidimensional fatigue. Lower RMSSD and higher LF/HF ratio are associated with greater fatigue levels. This study demonstrates that HRV indices exhibit significant relationships within a multidimensional model of fatigue incorporating objective performance, ocular, and subjective measures. The findings provide initial evidence towards using HRV for monitoring complex manifestations of fatigue, rather than single dimensions. Further applied research should investigate translating these findings to naturalistic settings and validating HRV thresholds predictive of on-road impairment.

Performance information and issue prioritization by political and managerial decision-makers: A discrete choice experiment

Abstract Issue prioritization is the first stage of attention-based theories of decision-making, but remains theoretically and empirically uncharted territory in public administration research. We propose and test how issue prioritization is informed by the characteristics of the performance information on which decision-makers rely, in particular its source (internal or external information), nature (objective or subjective information), aspiration level (historical, social, or coercive aspirations), and required cognitive effort (attention costs). Furthermore, we theorize how these characteristics of performance information determine issue prioritization decisions of political and managerial decision-makers in different ways. We empirically examine issue prioritization decisions in road maintenance and primary school education using a discrete choice experiment among 2,313 local government officials. The experiment reveals that decision-makers are more likely to prioritize issues that are signaled through objective performance measures and that are articulated relative to coercive aspirations, but that the effects of the information’s source and attention costs differ between policy domains. Comparison of observational variation regarding decision-makers’ roles indicates that public managers more strongly prioritize road maintenance issues that are articulated in objective performance information, but not in primary school education. The study advances public administration research and theory with a “horizontal” behavioral perspective on decision-makers’ information processing to prioritize between simultaneous performance issues.

R.I.M.E. and reason: multi-station OSCE enhancement to neutralize grade inflation

ABSTRACT To offset grade inflation, many clerkships combine faculty evaluations with objective assessments including the Medical Examiners Subject Examination (NBME-SE) or Objective Structured Clinical Examination (OSCE), however, standardized methods are not established. Following a curriculum transition removing faculty clinical evaluations from summative grading, final clerkship designations of fail (F), pass (P), and pass-with-distinction (PD) were determined by combined NBME-SE and OSCE performance, with overall PD for the clerkship requiring meeting this threshold in both. At the time, 90% of students achieved PD on the Internal Medicine (IM) OSCE resulting in overall clerkship grades primarily determined by the NBME-SE. The clerkship sought to enhance the OSCE to provide a more thorough objective clinical skills assessment, offset grade inflation, and reduce the NBME-SE primary determination of the final clerkship grade. The single-station 43-point OSCE was enhanced to a three-station 75-point OSCE using the Reporter-Interpreter-Manager-Educator (RIME) framework to align patient encounters with targeted assessments of progressive skills and competencies related to the clerkship rotation. Student performances were evaluated pre- and post-OSCE enhancement. Student surveys provided feedback about the clinical realism of the OSCE and the difficulty. Pre-intervention OSCE scores were more tightly clustered (SD = 5.65%) around a high average performance with scores being highly negatively skewed. Post-intervention OSCE scores were more dispersed (SD = 6.88%) around a lower average with scores being far less skewed resulting in an approximately normal distribution. This lowered the total number of students achieving PD on the OSCE and PD in the clerkship, thus reducing the relative weight of the NMBE-SE in the overall clerkship grade. Student response was positive, indicating the examination was fair and reflective of their clinical experiences. Through structured development, OSCE assessment can provide a realistic and objective measurement of clinical performance as part of the summative evaluation of students.

Sensor-Based Quantitative Assessment of Children's Fine Motor Competence: An Instrumented Version of the Placing Bricks Test.

The assessment of fine motor competence plays a pivotal role in neuropsychological examinations for the identification of developmental deficits. Several tests have been proposed for the characterization of fine motor competence, with evaluation metrics primarily based on qualitative observation, limiting quantitative assessment to measures such as test durations. The Placing Bricks (PB) test evaluates fine motor competence across the lifespan, relying on the measurement of time to completion. The present study aims at instrumenting the PB test using wearable inertial sensors to complement PB standard assessment with reliable and objective process-oriented measures of performance. Fifty-four primary school children (27 6-year-olds and 27 7-year-olds) performed the PB according to standard protocol with their dominant and non-dominant hands, while wearing two tri-axial inertial sensors, one per wrist. An ad hoc algorithm based on the analysis of forearm angular velocity data was developed to automatically identify task events, and to quantify phases and their variability. The algorithm performance was tested against video recordings in data from five children. Cycle and Placing durations showed a strong agreement between IMU- and Video-derived measurements, with a mean difference <0.1 s, 95% confidence intervals <50% median phase duration, and very high positive correlation (ρ > 0.9). Analyzing the whole population, significant differences were found for age, as follows: six-year-olds exhibited longer cycle durations and higher variability, indicating a stage of development and potential differences in hand dominance; seven-year-olds demonstrated quicker and less variable performance, aligning with the expected maturation and the refined motor control associated with dominant hand training during the first year of school. The proposed sensor-based approach allowed the quantitative assessment of fine motor competence in children, providing a portable and rapid tool for monitoring developmental progress.

Dynamic joint decision of matching parameters and relocation strategies in ride-sourcing systems interacting with traffic congestion

As the ride-sourcing market expands, ride-sourcing fleets have increased urban traffic congestion, and in turn, road congestion is affecting ride-sourcing operations. It is crucial to incorporate this interaction mechanism into the operational decision of ride-sourcing systems. This mechanism can be described in detail by simulation models. Applying simulation-based optimization methods to the real-time operation of ride-sourcing systems is challenging due to the limitations of simulation efficiency. To tackle this issue, this study first proposes a modular simulation model combining time-driven and event-driven mechanisms. The simulation model comprises two layers: the traffic flow module at the bottom, defined by trip-based and multi-region macroscopic fundamental diagrams and cell transmission models, and the ride-sourcing operation module at the top, which considers the interaction between the traffic congestion and ride-sourcing operation and models the random behavior of passengers and drivers. We verify the efficiency and accuracy of the simulation model. The simulation model is utilized as an evaluator of the objective functions and performance measures. Then, we integrate the Bayesian optimization, parallel sampling, and rolling horizon approaches to develop an efficient and effective simulation-based optimization framework for the dynamic joint decision-making of matching radius, matching intervals, and threshold relocation strategies. Six groups of experiments for the traffic scenario in Berlin reveal some interesting findings. (1) The matching rate first increases and then decreases with the matching radius (a concave function), while the closest study does not think so. (2) As the fleet size grows, passenger waiting time reaches its minimum and then rises because of the increased endogenous congestion generated by ride-sourcing fleets. (3) The optimal operation strategy considering endogenous congestion not only leads to an increase in the system revenue and efficiency but also leads to congestion relief, even though the latter was not our initial objective. This benefit is the most pronounced when the fleet size and background traffic are moderate.

Strategic alignment in multispecialty hospitals: Implementing a balanced scorecard approach for optimal performance

The study investigates the relationship between strategic alignment, balanced scorecard (BSC) implementation, and optimal performance (OP) in multispecialty hospitals. Data from 530 healthcare professionals in Lucknow, Varanasi, Kanpur, and Prayagraj were collected using a cross-sectional design. Descriptive statistics, correlation analysis, and regression analysis were employed for data analysis. The results demonstrate significant positive relationships between strategic alignment, balanced scorecard, and optimal performance. Both strategic alignment and balanced scorecards were identified as significant predictors of optimal performance, indicating that higher scores in these constructs are associated with higher levels of performance. The findings underscore the critical role of strategic alignment and performance measurement frameworks in enhancing organizational performance in healthcare settings. However, the study faces limitations, including reliance on self-reported data and limited generalizability to other healthcare settings and regions. Future research should explore longitudinal or experimental designs and incorporate objective performance measures to enhance the validity and generalizability of the findings. Overall, the study contributes to understanding strategic management practices in healthcare organizations and highlights avenues for further research in this area.

Performance of General Bureau Civil Servants in The Regional Secretariat of North Sulawesi Province

The aim of this research is to describe, interpret and analyze the performance of Civil Servants (PNS) in the Administration Sub-Section for Leadership and Expert Staff of the General Bureau of the Regional Secretariat of North Sulawesi Province seen from the aspects of Employee Performance Targets (SKP), Discipline and the application of Civil Service principles State (ASN) "BerAKHLAK" (Service Oriented, Responsible, Competent, Harmonious, Loyal, Adaptive and Collaborative). The research method applied is a descriptive qualitative approach using observation, interview, and document analysis techniques. The research results revealed a performance gap among civil servants, where some succeeded in achieving satisfactory results while others did not meet expectations. Factors such as effective training, motivation, conducive work environment, and reward and punishment systems were identified as important determinants in achieving optimal performance. The obstacles faced involve the quality and quantity of Human Resources (HR), with uncertainty that all civil servant members can contribute collectively. Therefore, a more thorough and objective performance measurement approach is needed. This research suggests an increase in the implementation of intensive training, improvements in the motivation system through structured rewards, evaluation of work environment conditions, as well as collaborative efforts with external parties to enrich technological understanding and skills.

Analysis of statistical estimators and neural network approaches for speech enhancement

Speech communicated is adversely affected by environmental noise. It is important to process the speech and reduce noise for better understanding. Speech enhancement or noise reduction is useful to provide comfort for human or machine listening. Traditional algorithms provide better noise reduction and better-quality speech. Due to the non-stationary nature of noise and the quasi-stationary nature of speech, the traditional methods are proven inadequate in achieving high-quality speech. Later statistical estimators based on Gaussian, and super-Gaussian Probability Density Function (PDF) assumption further improved the enhancement performance. But still, non-stationary noise nature introduces artifacts in processed signal and results in decreased performance. It is observed that neural network approaches and the factorization approach provide better performance even under non-stationary noises by proper training and large database. Different features result in variations in output performance under unseen noise and speaker conditions. It is important to understand the importance and advantages of traditional methods, statistical estimators, and neural network approaches performances. To select the suitable method for a required application, it is essential to consider the trade-off between quality and distortion. In this work, the importance of speech enhancement methods is discussed. Performance measures used for understanding the speech enhancement like Signal to Noise Ratio (SNR), Segmental SNR, Log-Likelihood Ratio (LLR), Weighted Spectral Slope (WSS), Perceptual Evaluation of Speech Quality (PESQ), Short-Time Objective Intelligibility (STOI), Signal to Distortion Ratio (SDR) and Mean Opinion Score (MOS), are given. Highlights of important results are discussed for analyzing better speech enhancement methods for the required application. In this work, performance is compared using objective and subjective performance measures. Simulation results show superior performance when neural network is employed in statistical estimators.

Preconditioning Frailty Phenotype Influences Survival and Relapse for Older Allogeneic Transplantation Recipients

Hematologic malignancies disproportionately affect older adults. Hematopoietic cell transplantation (HCT) is potentially curative, but poor overall survival (OS) has limited its use in older adults. Fried's frailty phenotype (FFP) is a geriatric assessment tool that combines objective and subjective performance measures: gait speed, grip strength, activity level, exhaustion, and weight loss. People meeting ≥3 criteria are classified as frail; 1 or 2 criteria, as pre-frail; and 0 criteria, as fit. To evaluate the association of pre-HCT FFP with post-HCT outcomes, we assessed FFP prior to conditioning for 280 HCT recipients age ≥60 years with acute leukemia or a myeloid neoplasm at 3 institutions. When analyzing survival by age group, patients age ≥70 years had inferior OS compared to patients age 60 to 69 years (P = .002), with corresponding OS estimates of 38.9% (95% confidence interval [CI], 27.8% to 49.9%) and 59.3% (95% CI, 51.9% to 65.9%). Nonrelapse mortality (NRM) also was significantly higher in the older patients (P = .0005); the 2-year cumulative incidences of NRM were 38.5% (95% CI, 27.5% to 49.2%) and 17.2% (95% CI, 12.3% to 22.8%), for older and younger recipients, respectively. The cumulative incidences of relapse did not differ by age group (P = .3435). Roughly one-third (35.5%) of the patients were fit, 57.5% were pre-frail, and 7.5% were frail, with corresponding 2-year OS estimates of 68.4% (95% CI, 57.9% to 76.8%), 45.5% (95% CI, 37.4% to 53.2%), and 45.8% (95% CI, 23.4% to 65.8%) (P = .013). FFP was not significantly associated with NRM, but being frail or pre-frail was associated with a higher rate of disease-related deaths (33.3% and 27.3%, respectively, compared with 17.4% for fit patients; P = .043). In univariate modeling of restricted mean survival time with a 3-year horizon (RMST_3y), the factors that were significantly associated were FFP, age, Karnofsky Performance Status (KPS), Disease Risk Index (DRI), and HCT-specific Comorbidity Index (HCT-CI). Of those factors, only FFP (P = .006), age (P = .006), KPS (P = .004), and DRI (P = .005) were significantly associated in multivariate modeling of RMST_3y. Estimates of RMST_3y were computed and 5 risk-groups were created with survival ranging from 31.4 months for those who were age 60 to 69 years, fit, had KPS 90 to 100, and low/intermediate-risk DRI compared to 10.5 months for those who had high-risk features for all the evaluated factors. In univariate and multivariate analyses for restricted mean time to relapse with a 3-year horizon (RMRT_3y), FFP (pre-frail versus fit, P = .007; frail versus fit, P = .061) and DRI (P = .001) were the only significant factors. Predicted RMRT_3y was longest (30.6 months) for those who were fit and had low/intermediate-risk DRI scores and shortest (19.1 months) for those who were frail and had high-risk or very high-risk DRI scores. Both age and FFP impact survival after HCT. Incorporation of FFP into pre-HCT evaluations may improve decision-making and counseling regarding HCT risk for older adults. Our findings support future trials designed to reverse frailty, such as pre-HCT supervised exercise programs, and correlative analyses to unravel the connection of frailty and relapse to generate future targets for intervention. Finally, exploration of novel HCT platforms to reduce relapse in pre-frail and frail patients, as well as reduce NRM in adults age >70 years, are warranted.

Online physiology teaching for nursing students during the COVID-19 pandemic – strengths, challenges and reinforcement measures

Objectives: The forced shift to online education during the COVID-19 pandemic posed several challenges to Indian nursing education, especially with a complex subject like physiology. The objective of the study was to assess the apprehensions, expectations, and challenges perceived by nursing students and physiology faculty about the online mode of learning physiology, to evaluate the utility of reinforcement measures during the constraints of the pandemic, and to compare the online, offline, and blended modes. Materials and Methods: First-year nursing students (n = 100) underwent online and blended modes of physiology learning, with added reinforcement measures, during the pandemic. Beginning, mid, and end of course feedback was taken from students on the expectations and perceptions of the online mode. Feedback was obtained from students and faculty to understand the strengths and challenges of both modes. Quantitative data of student feedback were analysed using the Cochran-Mantel-Haenszel test. Thematic content analysis was used for qualitative data. Objective measures of student performance were compared using unpaired t-tests. Results: Online learning was perceived to be more difficult than anticipated by students. ‘Comfort’ in learning and ‘time management’ were the major strengths, while ‘reduced internet connectivity,’ ‘lack of interactions’ and ‘health issues’ were the biggest challenges expressed by students and faculty. The planned reinforcement measures were ‘sometimes’ helpful in revising and improving students’ confidence. The final summative assessment scores of students showed a better performance compared to the preceding academic batch. Conclusion: Students and faculty expressed some advantages and several disadvantages of online learning. They preferred offline or well-designed blended learning. The reinforcement measures seemed to aid student learning. The objective measures of assessment showed that students adapted well to the online mode. A model for blended learning for 1st-year nursing education, that utilises the advantages of both modes of learning, has been proposed, which requires further validation.

Implementation of Artificial Intelligence-Based Computer Vision Model for Sleeve Gastrectomy: Experience in One Tertiary Center.

Sleeve gastrectomy (SG) is the most common metabolic and bariatric procedure performed. Leveraging artificial intelligence (AI) for automated real-time data structuring and annotations of surgical videos has immense potential of clinical applications. This study presents initial real-world implementation of AI-based computer vision model in sleeve gastrectomy (SG) and external validation of accuracy of safety milestone annotations. A retrospective single-center study of 49 consecutive SG videos was captured and analyzed by the AI platform (December 2020-August 2023). A bariatric surgeon viewed all videos and assessed safety milestones adherence, compared to the AI annotations. Patients' data were retrieved from the bariatric unit registry. SG total duration was 47.5min (interquartile range 36-64). Main steps included preparation (12.2%), dissection of the greater curvature (30.8%), gastric transection (28.5%), specimen extraction (7.2%), and final inspection (14.4%). Out of body time comprised 6.9% of the total video. Safety milestones components and AI-surgeon agreements included the following: bougie insertion (100%), distance from pylorus ≥ 2cm (100%), parallel to lesser curvature (98%), fundus mobilization (100%), and distance from esophagus ≥ 1cm (true-100%, false-13.6%; kappa coefficient 0.2, p = 0.006). Intraoperative complications included notable hemorrhage (n = 4) and parenchymal injury (n = 1). The AI model provides a fully automated SG video analysis. Outcomes suggest its accuracy in four of five safety milestone annotations. This data is valuable, as it reflects objective performance measures which can help us improve the surgical quality and efficiency of SG. Larger cohorts will enable SG standardization and clinical correlations with outcomes, aiming to improve patients' safety.

Human Factors at Play: Understanding the Impact of Conditioning on Presence and Reaction Time in Mixed Reality.

A prerequisite to improving the presence of a user in mixed reality (MR) is the ability to measure and quantify presence. Traditionally, subjective questionnaires have been used to assess the level of presence. However, recent studies have shown that presence is correlated with objective and systemic human performance measures such as reaction time. These studies analyze the correlation between presence and reaction time when technical factors such as object realism and plausibility of the object's behavior change. However, additional psychological and physiological human factors can also impact presence. It is unclear if presence can be mapped to and correlated with reaction time when human factors such as conditioning are involved. To answer this question, we conducted an exploratory study ($N=60$) where the relationship between presence and reaction time was assessed under three different conditioning scenarios: control, positive, and negative. We demonstrated that human factors impact presence. We found that presence scores and reaction times are significantly correlated (correlation coefficient of -0.64), suggesting that the impact of human factors on reaction time correlates with its effect on presence. In demonstrating that, our study takes another important step toward using objective and systemic measures like reaction time as a presence measure.

Open-label placebo treatment does not enhance cognitive abilities in healthy volunteers

The use of so-called ‘smart drugs’ such as modafinil to improve cognitive performance has recently attracted considerable attention. However, their side effects have limited user enthusiasm. Open-label placebo (OLP) treatment, i.e., inert treatments that are openly disclosed to individuals as having no active pharmacological ingredient, has been shown to improve various medical symptoms and conditions, including those related to cognitive performance. OLP treatment could therefore be an exciting alternative to pharmacological cognitive enhancers. Here, we used a randomized-controlled design to investigate the effect of a 21-day OLP treatment on several sub-domains of cognitive performance in N = 78 healthy volunteers. Subjective and objective measures of cognitive performance as well as different measures of well-being were obtained before and after the treatment period. Using a combination of classic Frequentist and Bayesian analysis approaches showed no additional benefit from OLP treatment in any of the subjective or objective measures of cognitive performance. Our study thus highlights possible limitations of OLP treatment in boosting cognitive performance in healthy volunteers. These findings are discussed in the light of expectancy-value considerations that may determine OLP efficacy.

Understanding Gaps Between Objective and Subjective Performance Measures: Accreditation of Public Service Organizations and Citizen Satisfaction

Governments use various performance measures to ensure that public services delivered by private-sector providers are safe and meet citizens’ particular needs. These measures can include awarding accreditation and assessing citizen satisfaction. However, few studies have investigated how objective performance measures relate to citizens’ subjective evaluations of providers from the perspective of service users. To fill this gap in the literature, this study closely explores a particular case of the Korean childcare market in which governments administer a large number of private-sector providers that play a dominant role in delivering public services. Our findings indicate the positive accreditation–satisfaction link is weakened when parents may not be aware of a provider's accreditation status or when their selected service provider is nonprofit, as opposed to for-profit. Overall, this study suggests that it is important to understand why there is some degree of incongruence between objective and subjective measures and how these two different performance indicators converge in the data. Special attention should be given to bridging the gap by closely reviewing institutional pressure on service providers and a symbolic impression of accreditation.

Objective and Subjective Methods for Evaluating the Usability of Schematic Maps: The Case Against Informal Expert Assessments

ABSTRACT Schematization is an established method to improve transit map usability, especially for rail-based modes. However, official designs differ considerably in the application of such methods, leading to the question of whether some designs might be better optimized than others. Objective measurements of performance comparing the use of different versions currently offers the soundest method of determining usability, especially compared with soliciting subjective evaluations from the general public – which are typically uncorrelated with objective measures. A short-cut to design evaluation might be to consult experts in the domains of cartography or graphic design. However, the research discussed here indicates that informal expert-evaluations are almost indistinguishable from those offered by the general public. In order to be given credence, expert-evaluations of usability must be derived from generalized empirical evidence, or else grounded in clearly stated, falsifiable theories of usability, or at least based upon logically transparent arguments.

Simulator-based driving test prescreening as a complement to driver testing – Toward safer and more risk-aware drivers

Young people represent a high-risk group of drivers and the prevalence of road traffic crashes among young drivers is high. Thus, to increase traffic safety, it is essential to ensure that new drivers are both sufficiently educated in and assessed for risk awareness.The aim of this study was to examine the possibility and potential benefit of using a driving simulator screening test as a complement to the existing on-road driving test. The main idea is to detect drivers who are not ready to proceed to the driving test.A comparative study was performed with participants who passed and failed a simulator test and an on-road driving test, respectively. A comparison between subjective and objective measures of performance and risk was also included. A driving simulator was placed at a traffic school and customers were recruited as participants. In total, 70 participants took part in the study and the simulated drive consisted of rural roads, urban traffic, and motorways with 16 different scenarios, constructed from the second level of the GDE matrix, to examine driving behavior, attention, and risk perception.The results show that with a screening test in a driving simulator, it is possible to detect drivers who consider themselves ready to take a driving test, but who have not yet reached the level of risk awareness required to be a safe driver. Test scenarios should be suited to detect deficiencies in risk awareness, test different levels of the GDE matrix and, to complement the driving test, be difficult to assess in an on-road driving test. Deficiencies in self-evaluation that are well-known among young drivers are again confirmed. To practice self-evaluation, the driving simulator is suggested as a pedagogical tool, linked to the GDE matrix.

Subjective and objective measures of visual awareness converge.

Within consciousness research, the most appropriate assessment of visual awareness is matter of a controversial debate: Subjective measures rely on introspections of the observer related to perceptual experiences, whereas objective measures are based on performance of the observer to accurately detect or discriminate the stimulus in question across a series of trials. In the present study, we compared subjective and objective awareness measurements across different stimulus feature and contrast levels using a temporal two-alternative forced choice task. This task has the advantage to provide an objective psychophysical performance measurement, while minimizing biases from unconscious processing. Thresholds based on subjective ratings with the Perceptual Awareness Scale (PAS) and on performance accuracy were determined for detection (stimulus presence) and discrimination (letter case) tasks at high and low stimulus contrast. We found a comparable pattern of thresholds across tasks and contrasts for objective and subjective measurements of awareness. These findings suggest that objective performance measures based on accuracy and subjective ratings of the visual experience can provide similar information on the feature-content of a percept. The observed similarity of thresholds validates psychophysical and subjective approaches to awareness as providing converging and thus most likely veridical measures of awareness.

Altered neural processes underlying executive function in occupational burnout-Basis for a novel EEG biomarker.

As burnout has become a global pandemic, there is a call for improved understanding and detection of alterations in brain functions related to it. We have previously reported challenges in executive functions (EFs) in daily life, especially in metacognition, in subjects with occupational burnout, along with alterations in cardiac physiology. In the current study, we focused on the impact of burnout on brain physiology during a task requiring EF. Fifty-four volunteers filled in inventories of burnout, depression, and EF in daily life (BBI-15, BDI, and BRIEF-A). Based on the BBI-15 score, subjects were divided into burnout and non-burnout groups. Subjects performed a Go/NoGo test (Executive RT test) engaging several EFs, while their EEG was recorded. The inventory scores, cognitive performance scores, and event-related potential (N2, P3) amplitudes, latencies, and interpeak latencies (IPLs) were compared between the groups. There were significant differences in the BDI and BRIEF-A scores between the groups, with more symptoms of depression and challenges in daily life in the burnout group. There were no differences in objective performance measures in the EF task between the groups. However, centroparietal P3 amplitude was larger, and while there were no differences in N2 or P3 latencies, N2-P3 IPL was longer in the Go condition in the burnout than in non-burnout group. Both ERP measures correlated significantly with burnout symptoms. A regression model from centroparietal P3 amplitude and N2-P3 IPL predicted significantly both the BBI-15 score and the BRIEF-A metacognition index. We conclude that burnout is linked with challenges in EF in daily life and alterations in the underlying neural processes. While cognitive performance in the task was equal, electrophysiological measures differed between the groups. Prolonged N2-P3 IPL points toward slowed transition from one cognitive process to another. Increased P3 amplitude, on the other hand, reflects increased allocation of neural processing resources. This may be a compensatory mechanism, allowing for equal performance with controls. These electrophysiological measures, obtained during the EF task, show promise as brain physiology-based biomarkers of burnout, contributing to its improved and objective detection. In addition, these results indicate occupational burnout is linked with objective alterations in brain physiology.

Gauging the Power of Perseverance and Extent of Unrealized Potential in One Intellectual Domain

Abstract Human potential and its limits are of broad interest. One issue is whether high-level intellectual performance depends mainly on persistence and extensive practice, or whether genes set widely varying maximum performance levels. Another issue is whether, if genes do limit performance level, how much genetic potential still goes undeveloped in a given domain's participants who progress some way and then stop. International chess is a good test domain because it has objective performance measures, little gatekeeper influence, and abundant longitudinal, population-level data. Performance of 27,362 players entering the international chess domain between 1985 and 1999 was investigated in 6 studies. By June 2022, only about 3% had met the high achievement criterion of grandmaster status, taking a median 9.26 years and 472 internationally rated games to gain the title, far more games than the median all-participant career total of 130. About 67% of those playing over 1,500 games became grandmasters, and almost all grandmasters had achieved the title by 1,500 games. Then, for non-grandmaster participants playing at least 100 but less than 1,500 games, a mathematical model, which predicts future grandmaster performance reasonably well, estimated their unrealized potential. The model projected their learning curves out to over 1,500 games and predicted their peak rating if they actually had played over 1,500 games. By model predictions, perhaps only 10–15% might have achieved the title by persisting. These results show that persistence is important but not all-important because genes may limit maximum performance level. Players also may gauge accurately their ultimate performance prospects.