Task Performance Research Articles

Effects of noise exposure on stress hormone changes during task performance in young Korean men: quasi-experimental study

ABSTRACT Numerous studies have suggested that noise exposure might be associated with changes in stress hormone levels. However, quantitative evidence for these effects in humans is rare and remains controversial. This study aimed to investigate the acute effects of exposure to noise and its different levels on stress hormone changes in task performance. Quasi-experimental noise exposure environment was established for 90 male university student volunteers in their twenties, and each was exposed to different noise levels during task performance. The stress hormones tested included cortisol, adrenocorticotropic hormone (ACTH), adrenaline, and noradrenaline. A one-way ANOVA was performed to investigate differences in hormone levels measured in the three groups according to the noise exposure levels (35, 45, or 75 dB). Analysis of covariance (ANCOVA) was used to adjust for confounding factors that might affect hormone levels. After adjusting for confounders, significant exposure-dependent differences were found in hormone levels in salivary cortisol, serum cortisol, serum ACTH, and serum adrenaline. The amount of hormonal increase in 75 dB exposure group compared to 35 or 45 dB groups was detected. Similar results were also seen in the rate of change analysis. Our findings indicate that short-term noise exposure during task performance elevates stress hormone levels. Further, the extent of stress hormone alterations varies with noise exposure levels. Changes in hormone levels are an objective measure that may be used to identify health effects and stress responses in various noise environments.

An Intervention into Imagery and Self-Efficacy: Enhancing Athletic Achievements of Alpine Skiers

Psychological preparation has taken on a crucial role in today’s sports practice. Effective resolutions to the challenges inherent in athletes’ psychological preparation require a comprehensive understanding of the key components that constitute the psychological preparation process. This quasi-experimental study aims to first, assess the interrelationships among imagery abilities, physical self-efficacy, and sport performance among a sample of alpine skiers. Secondly, this study sought to assess the effect of a psychological intervention on imagery and self-efficacy, and its impact on their task performance. The proposed hypothesis suggests that integrating imagery and self-efficacy interventions into the training process of alpine skiers will enhance athletes’ achievements on the slalom ski track. Seven leading Latvian youth alpine skiers with an average age of M = 17.14 (SD = 1.77) participated in a three-month psychological skill intervention targeting imagery and self-efficacy enhancement, alongside control training sessions on a slalom ski track to evaluate its effectiveness on sport performance. Pre- and post-intervention assessments were conducted using questionnaires, revealing significant improvements in imagery abilities and self-efficacy (p < 0.05). Notably, positive interrelationships between imagery abilities, self-efficacy, and sport performance were observed. These findings underscore the efficacy of integrating psychological interventions into the athlete training process and highlight the importance of psychological readiness in optimizing athletic achievements, particularly in dynamic sports like alpine skiing. The study results provide novel theoretical and practical psychological insights into the training process of athletes in sports.

Semi-supervised PolSAR Image Change Detection using Similarity Matching

Abstract. The lack of precisely labeled data limits the development of supervised polarimetric synthetic aperture radar (PolSAR) image change detection. Therefore, semi-supervised deep learning methods have recently demonstrated their significant capability for PolSAR image change detection. Similarity Matching (SimMatch) improves the performance of semi-supervised learning tasks across different benchmark datasets and different settings. Introducing SimMatch into the field of PolSAR image change detection can improve the performance of semi-supervised PolSAR image change detection under limited labeled data conditions. Usually, semi-supervision solves the problem of insufficient labeled data by generating pseudo-labels. However, when the pseudo-label method is simply applied, the model will fit on the confident but wrong pseudo-labels, resulting in poor performance. SimMatch offers a solution by requiring the strongly augmented view to share the same semantic similarity (i.e. label prediction) and instance characteristics (i.e. similarity between instances) with a weak augmented view for more intrinsic feature matching. Besides, by using a labeled memory buffer, the two similarities can be isomorphically transformed with each other by introducing the aggregating and unfolding techniques. Therefore, the semantic and instance pseudo-labels can be mutually propagated, and then, the detection performance of the PolSAR image change detection is improved. Experimental results on real PolSAR datasets demonstrated that SimMatch is an effective semi-supervised PolSAR change detection method and its performance surpasses some well-known change detection methods. Compared to the fully-supervised algorithm CWNN, the semi-supervised SimMatch algorithm can improve accuracy by up to 14.4%.

Parental and Child Sleep: Children with Vision Impairment, Autistic Children, and Children with Comorbid Vision Impairment and Autism.

Parents report associations between children's sleep disturbances and behaviors. Children with neurodevelopmental conditions (e.g., Williams Syndrome and autism) are consistently reported to experience increased sleeping problems. Sleep in children with vision impairment and children with a dual diagnosis of vision impairment and autism remains understudied. Our exploratory study compared sleep profiles in 52 children (aged 4-12 years) and their parents (n = 37), across four groups: children with vision impairment (VI; n = 9), autism (n = 10), comorbid vision impairment + autism (n = 6), and typically developing children (n = 27). Childhood sleep was measured using the parental report Childhood Sleep Habits Questionnaire and sleep diaries. Children's cognitive functioning was measured using digit span, semantic, and phonemic verbal fluency measures. Parental sleep was measured via the Pittsburgh Sleep Quality Index and Epworth Sleepiness Scale. Clinically disordered sleep was reported in all child groups (p ≤ 0.001), particularly children with VI + autism. Age, not sleep quality/quantity, predicted cognitive task performance in TD and autistic groups, but not in VI and VI + autism groups. The child's diagnosis affected parental sleep, particularly in children with a dual diagnosis of VI + autism. All participants experienced problematic sleep to varying degrees. Those most affected were children and parents in the VI + autism group, suggesting that autism may be the main driver of sleep problems in our sample.

Body and Brain Quality-Diversity in Robot Swarms

In biological societies, complex interactions between the behavior and morphology of evolving organisms and their environment have given rise to a wide range of complex and diverse social structures. Similarly, in artificial counterparts such as swarm-robotics systems, collective behaviors emerge via the interconnected dynamics of robot morphology (sensory-motor configuration), behavior (controller), and environment (task). Various studies have demonstrated morphological and behavioral diversity enables biological groups to exhibit adaptive, robust, and resilient collective behavior across changing environments. However, in artificial (swarm robotic) systems there is little research on the impact of changing environments on morphological and behavioral (body-brain) diversity in emergent collective behavior, and the benefits of such diversity. This study uses evolutionary collective robotics as an experimental platform to investigate the impact of increasing task environment complexity (collective behavior task difficulty) on the evolution and benefits of morphological and behavioral diversity in robotic swarms. Results indicate that body-brain evolution using coupled behavior and morphology diversity maintenance yields higher behavioral and morphological diversity, which is beneficial for collective behavior task performance across task environments. Results also indicate that such behavioral and morphological diversity maintenance coupled with body-brain evolution produces neuro-morpho complexity that does not increase concomitantly with task complexity.

Testing the Model of Judicial Stress using a COVID-era survey of U.S. federal court personnel

Non-judicial court personnel, critical to a well-functioning justice system, experience overloaded dockets and the responsibility of making significant decisions, contributing to cognitive stress. Understanding and mitigating their stress is essential for maintaining judicial efficiency. We adapted Miller and Richardson’s Model of Judicial Stress to assess stress in a broad sample of non-judicial court personnel (n = 122), including judges, lawyers, and administrative staff. Participants responded to surveys about their stress levels, job performance, and health; they also completed cognitive performance tasks. The findings indicated that stress negatively affected employee outcomes including cognitive performance, job performance, job satisfaction, and health outcomes. Notably, perceived job performance had declined compared to the previous year, suggesting that the pandemic was an additional significant stressor. Based on the data, the Model of Judicial Stress is also applicable to other types of courtroom personnel, underlining its relevance across various judicial roles.

Educational Attainment Moderates Task-state Control Network Connectivity Relations to Response Conflict Among Healthy Older Adults.

Older adult executive function varies widely due to brain and cognitive aging. Variance in older adult executive function is linked to increased response conflict from cognitive and brain aging. Cognitive Reserve (CR) is a theoretical protective mechanism that lessens brain aging's impact on cognition and is associated with greater educational attainment. Recent work in rest-state fMRI suggests CR proxies moderate the relationship between functional connectivity (FC) and cognitive performance. Brain network FC in "control networks", including the salience (SN), dorsal attention (DAN) and frontoparietal (FPN) networks, are associated with cognitive processes in older adults. CR is hypothesized to maintain cognitive processing in part through changes in how brain networks respond to cognitive demands. However, it is unclear how CR proxies like educational attainment are related to control network FC during performance when cognitive demands are increased relative to rest. Because CR is expressed more in those with higher education, we hypothesized stronger control network FC would relate to better performance, where this relationship would be strongest among the most educated. We collected flanker task data during fMRI to assess the impact of a CR-proxy (i.e., educational attainment) on response conflict among older adult subjects (n=42, age=65-80). Linear mixed effects models showed more educated older adults with greater SN-FC had a smaller flanker effect (i.e., less influence of distractors; p<.001) during task performance. For the first time, we show that educational attainment moderates the relationship between task-state SN-FC and executive function among older adults.

Association of obesity to reaction time and visual memory in schizophrenia

BackgroundBoth overweight and cognitive deficits are common among people with schizophrenia (SZ) and schizoaffective disorder. The results in earlier studies have been inconsistent on whether overweight is associated with cognitive deficits in psychotic disorders. AimsOur aim in this study was to detect possible associations between obesity and cognitive deficits among study participants with SZ and schizoaffective disorder. MethodsThe study sample included 5382 participants with a clinical diagnosis of SZ or schizoaffective disorder selected from the Finnish SUPER study. Obesity was measured both with body-mass index and waist circumference. The cognitive performance was evaluated with two tests from the Cambridge automated neuropsychological test battery: Reaction time was evaluated with the 5-choice serial reaction time task. Visual memory was evaluated with the paired associative learning test. The final analysis included a total sample of 4498 participants applicable for the analysis of the reaction time and 3967 participants for the analysis of the visual memory. ResultsObesity measured with body-mass index was associated with better performance in reaction time task among both female and male participants. Among male participants, overweight was associated with better performance in the visual memory test. The waist circumference was not associated with cognitive measures. ConclusionsThe results suggest that obesity in people with SZ or schizoaffective disorder might not be associated with cognitive deficits but instead with better cognitive performance. The results were opposite from earlier literature on the general population. More research is required to better understand whether the results might be partly caused by the differences in the etiology of obesity between the general population and people with SZ.

Conditional independence as a statistical assessment of evidence integration processes.

Intuitively, combining multiple sources of evidence should lead to more accurate decisions than considering single sources of evidence individually. In practice, however, the proper computation may be difficult, or may require additional data that are inaccessible. Here, based on the concept of conditional independence, we consider expressions that can serve either as recipes for integrating evidence based on limited data, or as statistical benchmarks for characterizing evidence integration processes. Consider three events, A, B, and C. We find that, if A and B are conditionally independent with respect to C, then the probability that C occurs given that both A and B are known, P(C|A, B), can be easily calculated without the need to measure the full three-way dependency between A, B, and C. This simplified approach can be used in two general ways: to generate predictions by combining multiple (conditionally independent) sources of evidence, or to test whether separate sources of evidence are functionally independent of each other. These applications are demonstrated with four computer-simulated examples, which include detecting a disease based on repeated diagnostic testing, inferring biological age based on multiple biomarkers of aging, discriminating two spatial locations based on multiple cue stimuli (multisensory integration), and examining how behavioral performance in a visual search task depends on selection histories. Besides providing a sound prescription for predicting outcomes, this methodology may be useful for analyzing experimental data of many types.

Detecting causal relationships between work motivation and job performance: a meta-analytic review of cross-lagged studies

Given that competing hypotheses about the causal relationship between work motivation and job performance exist, the current research utilized meta-analytic structural equation modeling (MASEM) methodology to detect the causal relationships between work motivation and job performance. In particular, completing hypotheses were checked by applying longitudinal data that include 84 correlations (n = 4389) from 11 independent studies measuring both work motivation and job performance over two waves. We find that the effect of motivation (T1) on performance (T2), with performance (T1) controlled, was positive and significant (β = 0.143). However, the effect of performance (T1) on motivation (T2), with motivation (T1) controlled, was not significant. These findings remain stable and robust across different measures of job performance (task performance versus organizational citizenship behavior), different measures of work motivation (engagement versus other motivations), and different time lags (1–6 months versus 7–12 months), suggesting that work motivation is more likely to cause job performance than vice versa. Practical and theoretical contributions are discussed.

Neural Signatures of Evidence Accumulation Encode Subjective Perceptual Confidence Independent of Performance

Confidence is an adaptive computation when environmental feedback is absent, yet there is little consensus regarding how perceptual confidence is computed in the brain. Difficulty arises because confidence correlates with other factors, such as accuracy, response time (RT), or evidence quality. We investigated whether neural signatures of evidence accumulation during a perceptual choice predict subjective confidence independently of these factors. Using motion stimuli, a central-parietal positive-going electroencephalogram component (CPP) behaves as an accumulating decision variable that predicts evidence quality, RT, accuracy, and confidence (Experiment 1, N = 25 adults). When we psychophysically varied confidence while holding accuracy constant (Experiment 2, N = 25 adults), the CPP still predicted confidence. Statistically controlling for RT, accuracy, and evidence quality (Experiment 3, N = 24 adults), the CPP still explained unique variance in confidence. The results indicate that a predecision neural signature of evidence accumulation, the CPP, encodes subjective perceptual confidence in decision-making independent of task performance.

When EU Agencies Set Up Advisory Committees: All About Autonomy?

AbstractEuropean Union (EU) agencies' relations with interest groups have received scarce research attention despite their relevance to bureaucratic autonomy and functioning. Such relations may be organised via advisory committees, which are durable organisational structures for regularised contact between an agency and those societal actors given membership by the agency. Advisory committees may be imposed by the legislator to control an agency or harnessed by the latter to build autonomy. The EU legislator leaves significant discretion to EU agencies regarding advisory committees. However, EU agencies' late emergence in already densely populated regulatory fields begs the question of whether the use of agency discretion is fully autonomous. A case in point is the Agency for the Cooperation of Energy Regulators (ACER), whose establishment and design of three European Stakeholder Committees are examined here. Advisory committees were needed by, but also imposed on, ACER, reflecting agency preferences to improve task performance as much as prior institutionalisation within the organisational field. Hence, factors beyond legal requirements can constrain agency discretion on how to organise the organisation of agency–interest group relations.

Prevalence of high impulsivity and its relation to sleep indices in opioid use disorder patients receiving methadone maintenance treatment

BackgroundThe relation between impulsivity and sleep indices is not well determined in patients receiving methadone maintenance treatment (MMT). Aimsto evaluate high impulsivity prevalence, its risk factors and relation with sleep indices.Methods: a random MMT sample (n = 61) plus MMT current cocaine users (n = 20) were assessed for impulsivity (Barratt impulsivity scale [BIS-11] and Balloon Analogue Risk task [BART]), sleep quality (Pittsburg Sleep Quality Index [PSQI]), sleepiness (The Epworth sleepiness scale [ESS]), and substance in urine. Results81 patients, aged 56.6 ± 10, 54.3% tested positive to any substance, 53.1% with poor sleep (PSQI>5) and 43.2% with daytime sleepiness (ESS >7) were studied. Impulsivity (BIS-11 ≥ 72) prevalence was 27.9% (of the representative sample), and 30.9% of all participants. These patients characterized with any substance and shorter duration in MMT with no sleep indices or other differences including BART balloon task performance (that was higher only in any substance than non-substance user group). However, impulsive score linearly correlated with daytime sleepiness (R = 0.2, p = 0.05). Impulsivity proportion was lowest among those with no cocaine followed by cocaine use and the highest in those who used cocaine and opiates (20.8%, 33.3% and 60% respectively, p = 0.02), as daily sleep (38.3%, 42.1% and 60%, p = 0.3) although not statistically significant. ConclusionDaytime sleepiness correlated with impulsivity, but cocaine usage is the robust factor. Further follow-up is warranted to determine whether substance discontinuing will lead to a reduction in impulsivity, and improved vigilance. Sleep quality did not relate to daytime sleepiness and impulsivity and need further research.

Cigarette smoking and cognitive task performance: Experimental effects of very-low nicotine-content cigarettes.

Reductions in the nicotine content of cigarettes decrease smoking rate and dependence severity, but effects on cognition are less well established. The potential impacts of very-low nicotine-content (VLNC) cigarettes on cognitive task performance must be evaluated, especially in vulnerable populations. The aim of the present study is to experimentally examine the effects of VLNC cigarettes on cognitive performance. Adults who smoked daily (n = 775) from three vulnerable populations (socioeconomically disadvantaged reproductive-age women, individuals with opioid use disorder, affective disorders) were examined. Participants were randomly assigned to normal nicotine content (NNC; 15.8 mg nicotine/g tobacco) or VLNC (2.4 mg/g or 0.4 mg/g) cigarettes for 12 weeks. Response inhibition (stop-signal task), working memory (n-back task; n of 2-n of 0), and cognitive interference (nicotine Stroop task) were assessed at baseline, 2, 6, and 12 weeks. Results were analyzed using mixed-model repeated-measures analyses of variance. Extended exposure to VLNC cigarettes produced no significant changes in any measure of cognitive performance compared to NNC cigarettes. Over weeks, response times on the n-back task decreased across doses. No significant effects were observed on the stop-signal or nicotine Stroop tasks. All three vulnerable populations performed comparably on all three cognitive tasks. Extended exposure to VLNC cigarettes produced no impairments in cognitive performance on any of the assessed tasks compared to NNC cigarettes. These findings are consistent with the larger literature detailing other consequences following exposure to VLNC cigarettes and are encouraging for the adoption of a nicotine-reduction policy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Task-order control in dual-tasks: Only marginal interactions between conflict at lower levels and higher processes of task organization.

When simultaneously performing two tasks that share response properties, interference can occur. Besides general performance decrements, performance in the first task is worse when the second task requires a spatially incompatible response, known as the backward crosstalk effect (BCE). The size of this BCE, similar to congruency effects in conflict tasks, is subject to a sequential modulation, with a smaller BCE after incompatible compared to compatible trials. In the present study, we focus on a potential bidirectional interaction between crosstalk (and its resolution) at a lower level of task performance and higher-order processes of task organization. Two questions were of particular interest: First, do participants switch task order more frequently after a conflict-prone incompatible trial than after a compatible trial? Second, does changing task order influence the efficiency of conflict resolution, as indexed by the size of the sequential modulation of the BCE. Across four experiments, we only found marginal evidence for an influence of lower-level conflict on higher-order processes of task organization, with only one experiment revealing a tendency to repeat task order following conflict. Our results thus suggest practical independence between conflict and task-order control. When separating processes of task selection and task performance, the sequential modulation was generally diminished, suggesting that conflict resolution in dual-tasks can be disrupted by a deliberate decision about task order, or, alternatively, by a longer inter-trial interval. Finally, the study found a strong bias towards repeating the same task order across trials, suggesting that task-order sets not only impact task performance but also guide task selection.

HAMMF: Hierarchical attention-based multi-task and multi-modal fusion model for computer-aided diagnosis of Alzheimer’s disease

Alzheimer’s disease (AD) is a progressive neurodegenerative condition, and early intervention can help slow its progression. However, integrating multi-dimensional information and deep convolutional networks increases the model parameters, affecting diagnosis accuracy and efficiency and hindering clinical diagnostic model deployment. Multi-modal neuroimaging can offer more precise diagnostic results, while multi-task modeling of classification and regression tasks can enhance the performance and stability of AD diagnosis. This study proposes a Hierarchical Attention-based Multi-task Multi-modal Fusion model (HAMMF) that leverages multi-modal neuroimaging data to concurrently learn AD classification tasks, cognitive score regression, and age regression tasks using attention-based techniques. Firstly, we preprocess MRI and PET image data to obtain two modal data, each containing distinct information. Next, we incorporate a novel Contextual Hierarchical Attention Module (CHAM) to aggregate multi-modal features. This module employs channel and spatial attention to extract fine-grained pathological features from unimodal image data across various dimensions. Using these attention mechanisms, the Transformer can effectively capture correlated features of multi-modal inputs. Lastly, we adopt multi-task learning in our model to investigate the influence of different variables on diagnosis, with a primary classification task and a secondary regression task for optimal multi-task prediction performance. Our experiments utilized MRI and PET images from 720 subjects in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. The results show that our proposed model achieves an overall accuracy of 93.15% for AD/NC recognition, and the visualization results demonstrate its strong pathological feature recognition performance.

Electroencephalogram Functional Connectivity Analysis and Classification of Mental Arithmetic Working Memory Task

Analyzing brain activity during mental arithmetic tasks provides insight into psychological disorders such as ADHD, dyscalculia, and autism. While most research is conducted on the static functional connectivity of the brain while performing a cognitive task, the dynamic changes of the brain, which provide meaningful information for diagnosing individual differences in cognitive tasks, are often ignored. This paper aims to classify electroencephalogram (EEG) signals for rest vs. mental arithmetic task performance, using Bayesian functional connectivity features in the sensor space as inputs into a graph convolutional network. The subject-specific (intrasubject) classification performed on 36 subjects for rest vs. mental arithmetic task performance achieved the highest subject-specific classification accuracy of 98% and an average accuracy of 91% in the beta frequency band, outperforming state-of-the-art methods. In addition, statistical analysis confirms the consistency of Bayesian functional connectivity features compared to traditional functional connectivity features. Furthermore, the graph-theoretical analysis of functional connectivity networks reveals that good-performance subjects had higher global efficiency, betweenness centrality, and closeness centrality than bad-performance subjects. The ablation study on the classification of three cognitive states (subtraction, music, and memory) achieved a classification accuracy of 97%, and visual working memory (n-back task) achieved a classification accuracy of 94%, confirming the consistency and reliability of the proposed methodology.

JOB BULLYING AND ITS RELATIONSHIP TO JOB FRUSTRATION

The current study sought to test the level of contribution of both occupational bullying with its dimensions represented by (physical or material bullying, verbal bullying, physical bullying) and its relationship to occupational frustration with its dimensions represented by (self-frustration, relationship frustration, frustration with merit), as it adopted within its theoretical framework occupational bullying As an independent variable, job frustration came as a dependent variable. The researcher reached a set of conclusions, the most important of which is that job bullying has a bad impact on the employees of the organization studied as a result of the neglect of its officials regarding the employees and their care and providing them with means of success at work and providing the best services to them despite their commitment to the laws, rules and codes that the organization has established to perform the tasks assigned to it. The most important recommendations were that the organization must strive to encourage the elimination of bullying at work and continue to establish regulations, laws and rules that help overcome this phenomenon among employees and provide the best services in order to reach a high level of task performance.

Early Eye Disengagement Is Regulated by Task Complexity and Task Repetition in Visual Tracking Task.

Understanding human actions often requires in-depth detection and interpretation of bio-signals. Early eye disengagement from the target (EEDT) represents a significant eye behavior that involves the proactive disengagement of the gazes from the target to gather information on the anticipated pathway, thereby enabling rapid reactions to the environment. It remains unknown how task difficulty and task repetition affect EEDT. We aim to provide direct evidence of how these factors influence EEDT. We developed a visual tracking task in which participants viewed arrow movement videos while their eye movements were tracked. The task complexity was increased by increasing movement steps. Every movement pattern was performed twice to assess the effect of repetition on eye movement. Participants were required to recall the movement patterns for recall accuracy evaluation and complete cognitive load assessment. EEDT was quantified by the fixation duration and frequency within the areas of eye before arrow. When task difficulty increased, we found the recall accuracy score decreased, the cognitive load increased, and EEDT decreased significantly. The EEDT was higher in the second trial, but significance only existed in tasks with lower complexity. EEDT was positively correlated with recall accuracy and negatively correlated with cognitive load. Performing EEDT was reduced by task complexity and increased by task repetition. EEDT may be a promising sensory measure for assessing task performance and cognitive load and can be used for the future development of eye-tracking-based sensors.

Assessing self-regulated processes: what do primary school students do, say and think in the process of understanding a text?

AbstractSelf-regulation has a positive impact on learning and academic achievement, but due to its nature, it is difficult to assess it in a valid and reliable manner. This study aims to explore the validity of three self-regulation assessment methods in text comprehension tasks (questionnaire, think-aloud and traces) as well as to identify the variables associated with reading performance. For this purpose, individual sessions were conducted with 96 sixth-grade primary education students, who were asked to read a text and complete two reading comprehension tasks working in a virtual environment. Task traces were recorded, think-aloud was recorded and coded, and participants answered a self-report questionnaire about the strategies used. A limited relationship was found between self-regulation measured by means of the questionnaire, think-aloud and traces, and the relationship between think-aloud and traces was moderate. Regarding the factors related to text comprehension task performance, think-aloud and task time measurements were found to be better predictors of performance than the questionnaire.