Relevant Physiological Indicators for Assessing Workload in Conditionally Automated Driving, Through Three-Class Classification and Regression

In future conditionally automated driving, drivers may be asked to take over control of the car while it is driving autonomously. Performing a non-driving-related task could degrade their takeover performance, which could be detected by continuous assessment of drivers' mental load. In this regard, three physiological signals from 80 subjects were collected during 1 h of conditionally automated driving in a simulator. Participants were asked to perform a non-driving cognitive task (N-back) for 90 s, 15 times during driving. The modality and difficulty of the task were experimentally manipulated. The experiment yielded a dataset of drivers' physiological indicators during the task sequences, which was used to predict drivers' workload. This was done by classifying task difficulty (three classes) and regressing participants' reported level of subjective workload after each task (on a 0–20 scale). Classification of task modality was also studied. For each task, the effect of sensor fusion and task performance were studied. The implemented pipeline consisted of a repeated cross validation approach with grid search applied to three machine learning algorithms. The results showed that three different levels of mental load could be classified with a f1-score of 0.713 using the skin conductance and respiration signals as inputs of a random forest classifier. The best regression model predicted the subjective level of workload with a mean absolute error of 3.195 using the three signals. The accuracy of the model increased with participants' task performance. However, classification of task modality (visual or auditory) was not successful. Some physiological indicators such as estimates of respiratory sinus arrhythmia, respiratory amplitude, and temporal indices of heart rate variability were found to be relevant measures of mental workload. Their use should be preferred for ongoing assessment of driver workload in automated driving.

Sub- and Supra-Second Timing in Auditory Perception: Evidence for Cross-Domain Relationships

Previous studies indicate that there are at least two levels of temporal processing: the sub- and supra-second domains. The relationship between these domains remains unclear. The aim of this study was to test whether performance on the sub-second level is related to that on the supra-second one, or whether these two domains operate independently. Participants were 118 healthy adults (mean age = 23 years). The sub-second level was studied with a temporal-order judgment task and indexed by the Temporal Order Threshold (TOT), on which lower values corresponded to better performance. On the basis of TOT results, the initial sample was classified into two groups characterized by either higher temporal efficiency (HTE) or lower temporal efficiency (LTE). Next, the efficiency of performance on the supra-second level was studied in these two groups using the subjective accentuation task, in which participants listened to monotonous sequences of beats and were asked to mentally accentuate every n-th beat to create individual rhythmic patterns. The extent of temporal integration was assessed on the basis of the number of beats being united and better performance corresponded to longer units. The novel results are differences between groups in this temporal integration. The HTE group integrated beats in significantly longer units than did the LTE group. Moreover, for tasks with higher mental load, the HTE group relied more on a constant time strategy, whereas the LTE group relied more on mental counting, probably because of less efficient temporal integration. These findings provide insight into associations between sub- and supra-second levels of processing and point to a common time keeping system, which is active independently of temporal domain.

Mental workLoad Accumulation Effect of Mobile Phone Distraction in L2 Autopilot Mode

As self-driving vehicles become more common, there is a need for precise measurement and definition of when and in what ways a driver can use a mobile phone in autonomous driving mode, for how long it can be used, the complexity of the call content, and the accumulated psychological load. This study uses a 2 (driving mode) * 2 (call content complexity) * 6 (driving phase) three-factor mixed experimental design to investigate the effect of these factors on the driver's psychological load by measuring the driver's performance on peripheral visual detection tasks, pupil diameter, and EEG components in various brain regions in the alpha band. The results showed that drivers' mental load levels converge between manual and automatic driving modes as the duration of driving increases, regardless of the level of complexity of the mobile phone conversation. This suggests that mobile phone conversations can also disrupt the driver's cognitive resource balance in automatic driving mode, as it increases mental load while also impairing the normal functioning of brain functions such as cognitive control, problem solving, and judgment, thereby compromising driving safety.

Analysing the Relationship Between Mental Load or Mental Effort and Metacomprehension Under Different Conditions of Multimedia Design

Cognitive load theory assumes effort may only lead to comprehension if the material-induced load leaves enough resources for learning processes. Therefore, multimedia materials should induce as little non-relevant load as possible. Metacognition research assumes that learners tap into their memory processes to generate a mental representation of their comprehension to regulate learning. However, when judging their comprehension, learners need to make inferences about actual understanding using cues such as their experienced mental load and effort during learning. Theoretical assumptions would assume both to affect understanding and its metacognitive representation (metacomprehension). However, the question remains how perceived effort and load are related to metacomprehension judgments while learning with multimedia learning material. Additionally, it remains unclear if this varies under different conditions of multimedia design. To better understand the relationship between perceived mental load and effort and comprehension and metacomprehension under different design conditions of multimedia material, we conducted a randomised between-subjects study (N = 156) varying the design of the learning material (text-picture integrated, split attention, active integration). Mediation analyses testing for both direct and indirect effects of mental load and effort on metacomprehension judgments showed various effects. Beyond indirect effects via comprehension, both mental load and effort were directly related to metacomprehension, however, this seems to vary under different conditions of multimedia design, at least for mental effort. As the direction of effect can only be theoretically assumed, but was not empirically tested, follow-up research needs to identify ways to manipulate effort and load perceptions without tinkering with metacognitive processes directly. Despite the limitations due to the correlative design, this research has implications for our understanding of cognitive and metacognitive processes during learning with multimedia.

Busy and confused? High risk of missed alerts in the cockpit: an electrophysiological study

Of evolutionary importance, the ability to react to unexpected auditory stimuli remains critical today, especially in settings such as aircraft cockpits or air traffic control towers, characterized by high mental and auditory loads. Evidences show that both factors can negatively impact auditory attention and prevent appropriate reactions in hazardous situations. In the present study, sixty participants performed a simulated aviation task, varying in terms of mental load (no, low, high mental load), that was embedded with a concurrent tone detection paradigm, in which auditory load was manipulated by the number of different tones (1, 2 or 3). We measured both detection performance (miss, false alarm) and brain activity (event-related potentials) related to the target tone. Our results showed that both mental and auditory loads affected tone detection performance. Importantly, their combined effects had a massive impact on the percentage of missed target tones. While, in the no mental load condition, miss rate was very low with 1 (0.53%) and 2 tones (1.11%), it increased drastically with 3 tones (24.44%), and this effect was accentuated as mental load increased, yielding to the higher miss rate in the 3-tone paradigm under high mental load conditions (68.64%). Increased mental load, auditory load, and miss rate, were all associated with disrupted brain response to the target tone as showed by reductions of the P3b amplitude. In sum, our results highlight the importance of balancing mental and auditory loads to maintain or improve efficient reactions to alarms in complex environment.

Workload Status and Its Relationship with Job Stress in Nurses during the COVID-19 Pandemic

Background and Purpose: Currently, the high prevalence of COVID-19 and increased workload in hospitals has posed a threat to the physical, mental, and emotional health of nurses. The present study was an attempt to investigate the workload and its relationship with job stress of nurses in COVID-19 reference hospitals in southern Iran. Materials and Methods: This descriptive-analytical and cross-sectional study was conducted in 2021 on 431 nurses from COVID-19 reference hospitals in southern Iran. Data collection tools included the NASA workload and OSIPOW job stress standard questionnaires. Data were analyzed using t-test, ANOVA, and Pearson correlation coefficient in SPSS23 Software and at a significance level of 0.05 Results: The mean age and work experience of the nurses participating in the study were 31.03±5.23 and 6.42±4.61, respectively. The mean scores of the workload and job stresses were 83.64 ± 17.24 (of 100) and 236.68 ± 16.54 (of 300), respectively. Mental load dimension (85.81 ±19.31, of 100) among workload dimensions and role workload dimension (43.62 ± 19.14, of 50) among job stress dimensions had the highest mean score. Thus, there was found a statistically significant relationship between workload and job stress of nurses (P= 0.04, r= 0.19). Conclusion: Workload and job stress of the studied nurses were estimated at a high level. There was a significant positive correlation between these two variables, and increasing workload resulted in an increase in job stress.

Considerations of the Mental Workload in Socio-Technical Systems in the Manufacturing Industry

As cognitive tasks have displaced physical tasks in today's manufacturing industry, this sector can demand high levels of mental workload from workers. In certain situations, there is a high cognitive load, which affects operators reducing their attention to the task and causing them mental fatigue and distractions, resulting in errors that generate economic costs or even injuries to workers. This literature review aims to provide a comprehensive understanding the use of mental workload in the manufacturing sector. The methodology consisted of conducting a search in four databases. In the search, a combination of keywords was used, classifying each journal according to the mental workload evaluation means, the type of evaluation, and the area of application. Articles not focusing on the manufacturing area were discarded. Of the total of 3839 articles found, 12 have been selected. Regarding the methods used for mental load assessment, the analytic techniques were found to be the most frequently used.

‘When will this end? Will it end?’ The impact of the March–June 2020 UK COVID-19 lockdown response on mental health: a longitudinal survey of mothers in the Born in Bradford study

ObjectivesTo explore clinically important increases in depression/anxiety from before to during the first UK COVID-19 lockdown and factors related to this change, with a particular focus on ethnic differences.DesignPre-COVID-19 and lockdown surveys nested within two longitudinal Born in Bradford cohort studies.Participants1860 mothers with a child aged 0–5 or 9–13, 48% Pakistani heritage.Main outcome measuresORs for a clinically important increase (5 points or more) in depression (eight item Patient Health Questionnaire (PHQ-8)) and anxiety (Generalised Anxiety Disorder Assessment (GAD-7)) in unadjusted regression analyses, repeated with exposures of interest separated by ethnicity to look for differences in magnitude of associations, and lived experience of mothers captured in open text questions.ResultsThe number of women reporting clinically important depression/anxiety increased from 11% to 20% (95% CI 10%–13%; 18%–22%) and from 10% to 16% (95% CI 8%–11%; 15%–18%), respectively. Increases in depression/anxiety were associated with loneliness (OR=8.37, 95% CI 5.70 to 12.27; 8.50, 95% CI 5.71 to 12.65, respectively); financial (6.23, 95% CI 3.96 to 9.80; 6.03, 95% CI 3.82 to 9.51), food (3.33, 95% CI 2.09 to 5.28; 3.46, 95% CI 2.15 to 5.58) and housing insecurity (3.29, 95% CI 2.36 to 4.58; 3.0, 95% CI 2.11 to 4.25); a lack of physical activity (3.13, 95% CI 2.15 to 4.56; 2.55, 95% CI 1.72 to 3.78); and a poor partner relationship (3.6, 95% CI 2.44 to 5.43; 5.1, 95% CI 3.37 to 7.62). The magnitude of associations between key exposures and worsening mental health varied between ethnic groups.Responses to open text questions illustrated a complex interplay of challenges contributing to mental ill health including: acute health anxieties; the mental load of managing multiple responsibilities; loss of social support and coping strategies; pressures of financial and employment insecurity; and being unable to switch off from the pandemic.ConclusionsMental ill health has worsened for many during the COVID-19 lockdown, particularly in those who are lonely and economically insecure. The magnitude of associations between key exposures and worsening mental health varied between ethnic groups. Mental health problems may have longer term consequences for public health and interventions that address the potential causes are needed.

Mental Load and Fatigue Assessment Instruments: A Systematic Review

Mental load and fatigue are important causes of performance decreases and accidents in different activities. However, a robust systematic review, detailing the instruments used to quantify them, is currently lacking. The purpose of this study was to summarize and classify by derivations the validated instruments used to quantify mental load and fatigue. The most representative electronic databases in the scope of this review, PubMed, WOS, Scopus, SPORTDiscus, and PsycINFO (until September 2020) were searched for studies that included instruments to analyze mental load and fatigue. The quality of the selected studies was scored using a quality assessment checklist. A total of 40 papers were included. Most of the papers used subjective scales (75%) to quantify mental load and fatigue, with a small presence of behavioral (n = 5) and objective techniques (n = 5). Less is known about the analysis of mental load and fatigue using a combination of derivations. Despite the high cost and complexity of objective techniques, research that applies these measures is important for further analysis of brain processes in mental load and fatigue. The design of a battery of tests that include the three types of derivations also seems necessary.