The development of a new sport-specific classification of coping and a meta-analysis of the relationship between different coping strategies and moderators on sporting outcomes

There is an ever growing coping and sports performance literature, with researchers using many different methods to assess performance and different classifications of coping. As such, it makes it difficult to compare studies and therefore identify how coping is related to performance. Furthermore, there are no quantitative syntheses of the results from these studies. A quantitative synthesis would facilitate a more comprehensive understanding of how coping is associated with athletic performance. In order to accurately compare studies, our first aim was to develop a new coping classification that would make this possible. Firstly, we reviewed the strengths and limitations of the different coping classifications and then identified the commonalities and differences between such classifications. We opted for a three-factor classification of coping, because the evidence suggests that a three-factor classification provides a superior model fit to two-factor approaches. Our new classification of coping was based on an existing model from the developmental literature, which received an excellent model fit. We made some adaptations, however, as our classification was intended for an athletic population. As such, we classified coping as mastery (i.e., controlling the situation and eliminating the stressor), internal regulation (i.e., managing internal stress responses), or goal withdrawal (i.e., ceasing efforts towards goal attainment). Undertaking a meta-analysis, our second aim was to identify which coping strategies correlated with sports performance and whether this relationship varied according to moderator variables. Articles were sourced from online electronic databases and manual journal searches. PRISMA guidelines were used to search, select, and synthesize relevant studies. Random effects meta-analyses were performed to identify associations between coping classification and sport performance. Q, I2, and R2 values assessed heterogeneity. Eighteen published investigations, including 3900 participants and incorporating fifty-nine correlations, indicated an overall positive effect for mastery coping, a negligible negative effect for internal regulation coping, and a negative effect for goal withdrawal strategies. The findings of this meta-analysis could be used by sports practitioners to help them deliver effective coping interventions. In order to maximize performance, practitioners could encourage the use of mastery coping, but advise their athletes not to use goal withdrawal strategies

Psychological rumination and recovery from work in Intensive Care Professionals : associations with stress, burnout, depression, and health

Background The work demands of critical care can be a major cause of stress in intensive care unit (ICU) professionals and lead to poor health outcomes. In the process of recovery from work, psychological rumination is considered to be an important mediating variable in the relationship between work demands and health outcomes. This study aimed to extend our knowledge of the process by which ICU stressors and differing rumination styles are associated with burnout, depression and risk of psychiatric morbidity among ICU professionals. Methods Ninety-six healthcare professionals (58 doctors and 38 nurses) who work in ICUs in the UK completed a questionnaire on ICU-related stressors, burnout, work-related rumination, depression and risk of psychiatric morbidity. Results Significant associations between ICU stressors, affective rumination, burnout, depression and risk of psychiatric morbidity were found. Longer working hours were also related to increased ICU stressors. Affective rumination (but not problem-solving pondering or distraction detachment) mediated the relationship between ICU stressors, burnout, depression and risk of psychiatric morbidity, such that increased ICU stressors, and greater affective rumination, were associated with greater burnout, depression and risk of psychiatric morbidity. No moderating effects were observed. Conclusions Longer working hours were associated with increased ICU stressors, and increased ICU stressors conferred greater burnout, depression and risk of psychiatric morbidity via increased affective rumination. The importance of screening healthcare practitioners within intensive care for depression, burnout and psychiatric morbidity has been highlighted. Future research should evaluate psychological interventions which target rumination style and could be made available to those at highest risk. The efficacy and cost effectiveness of delivering these interventions should also be considered

Assessing Needs and Outcomes of Children and Youth Receiving Intensive Services

This study investigated whether children/youth in Ontario triaged to residential services showed a higher intensity of need than those referred to outpatient services, and whether residential treatment gains were sufficient for transition to community services. Participants included 2053 children/youth assessed at 23 diverse mental health agencies across Ontario using the interRAI™ Child and Youth Mental Health (ChYMH) instrument. Various presenting problems were examined utilizing scales including: Disruptive/Aggressive Behavior, Hyperactive/Distraction, Social Disengagement, Anxiety, and Sleep Difficulties. Analyses were conducted separately for boys and girls. Notable differences were found in the initial assessment, with residential boys scoring higher on all scales than outpatient boys, and residential girls scoring higher on the externalizing scales (Disruptive/Aggressive Behavior, Hyperactive/Distraction) than outpatient girls. Treatment gains at residential discharge included improvements in Anxiety, Social Disengagement, Hyperactive/Distraction and Sleep Difficulties for boys and girls to levels at or below the initial scores of outpatient peers. Disruptive/Aggressive Behavior is still a high need following residential services. The results highlight differences in severity of mental health presentation between children/youth receiving residential and outpatient services, and how multiple agencies in Ontario are providing services that successfully reduce the severity of mental health needs

Improving Drivers’ Behaviour When Partial Driving Automation Fails

With the advent of automated vehicle systems, the role of drivers has changed to a more supervisory role. However, it is known that all vehicles with Level 2 (L2) systems have a very specific operational design domain (ODD) and can only function on limited conditions. Hence, it is important for drivers to perceive the situations properly and regain the control from the L2 system when needed. As suggested by past research, designing an informative interface could help drivers in their new supervision and intervention role while driving with L2 vehicles by providing feedback to drivers when hazards or event that may cause system failure are detected. On the other hand there are many situations where these vehicles cannot detect hazards and provide any feedback prior to the event. In these cases, training programs which provide drivers with an experience of these system limitations and allow them to practice dealing with such limitations can prove to be effective countermeasures. The objective of the current study is to employ different methods (designing HMI and training drivers) to increase drivers’ situational awareness regarding operational design domain (ODD) and improve drivers performance in transfer of control situations while driving with level 2 (L2) automation features. This study includes two experiments- in first experiment, an informative dashboard interface was designed and tested through three phases (observation, prototyping, testing). Results from the testing phase showed that drivers who received the newly designed dashboards took back control more effectively and had more situational awareness compared to the control group. In the second experiment, a PC-based training program was designed and tested to improve drivers takeover response and situational awareness when L2 systems reach their ODD limits. Results showed drivers in the PC-based training group took back control more effectively when L2 systems reached their ODD limits and had more situational awareness compared to the drivers who received user manual or placebo training

Enhancing environmental engagement with natural language interfaces for in-vehicle navigation systems

Four on-road studies were conducted in the Clifton area of Nottingham, UK, aiming to explore the relationships between driver workload and environmental engagement associated with ‘active’ and ‘passive’ navigation systems. In a between-subjects design, a total of 61 experienced drivers completed two experimental drives comprising the same three routes (with overlapping sections), staged one week apart. Drivers were provided with the navigational support of a commercially-available navigation device (‘satnav’), an informed passenger (a stranger with expert route knowledge), a collaborative passenger (an individual with whom they had a close, personal relationship) or a novel interface employing conversational natural language NAV-NLI). The NAV-NLI was created by curating linguistic intercourse extracted from the earlier conditions, and delivering this using a Wizard-of-Oz technique. The different navigational methods were notable for their varying interactivity and the preponderance of environmental landmark information within route directions. Participants experienced the same guidance on each of the two drives to explore changes in reported and observed behaviour. Results show that participants who were more active in the navigation task (collaborative passenger or NAV-NLI) demonstrated enhanced environmental engagement (landmark recognition, route-learning and survey knowledge) allowing them to reconstruct the route more accurately post-drive, compared to drivers using more passive forms of navigational support (SatNav or informed passenger). Workload measures (TDT, NASA-TLX) indicated no differences between conditions, although satnav users and collaborative passenger drivers reported lower workload during their second drive. The research demonstrates clear benefits and potential for a navigation system employing two-way conversational language to deliver instructions. This could help support a long-term perspective in the development of spatial knowledge, enabling drivers to become less reliant on the technology and begin to re-establish associations between viewing an environmental feature and the related navigational manoeuvre

How to keep drivers engaged while supervising driving automation? A literature survey and categorization of six solution areas

This work aimed to organise recommendations for keeping people engaged during human supervision of driving automation, encouraging a safe and acceptable introduction of automated driving systems. First, heuristic knowledge of human factors, ergonomics, and psychological theory was used to propose solution areas to human supervisory control problems of sustained attention. Driving and non-driving research examples were drawn to substantiate the solution areas. Automotive manufacturers might (1) avoid this supervisory role altogether, (2) reduce it in objective ways or (3) alter its subjective experiences, (4) utilize conditioning learning principles such as with gamification and/or selection/training techniques, (5) support internal driver cognitive processes and mental models and/or (6) leverage externally situated information regarding relations between the driver, the driving task, and the driving environment. Second, a cross-domain literature survey of influential human-automation interaction research was conducted for how to keep engagement/attention in supervisory control. The solution areas (via numeric theme codes) were found to be reliably applied from independent rater categorisations of research recommendations. Areas (5) and (6) were addressed by around 70% or more of the studies, areas (2) and (4) in around 50% of the studies, and areas (3) and (1) in less than around 20% and 5%, respectively. The present contribution offers a guiding organisational framework towards improving human attention while supervising driving automation.submittedVersio

Unconstrained design: improving multitasking with in-vehicle information systems through enhanced situation awareness

In the age of information, in-vehicle multitasking is inevitable. The popularity of the automobile in combination with the demands of everyday life presents a demand to do more than simply focus on the road. Situation Awareness (SA) is a theory that allows designers to understand how operators interact in dynamic, complex environments. Unconstrained Design is proposed as a way of enhancing multitasking performance in-vehicle. This paper presents an experimental investigation into human-machine interface concepts that aim to support drivers to multitask in-vehicle when frequent task switching is required. Two SA-based approaches were investigated, one which focussed on supporting preparation for a Non-Driving Related Activity (NDRA), and one which focussed on supporting the Driving Related Activity (DRA) when an NDRA is active. While multitasking, Contextual Cueing, using a Head-up Display, produced significant reductions in NDRA response time while an auditory lane keeping aid increased the amount of time a driver spent in the central region of a lane. This provides evidence to suggest that using SA and Unconstrained Design as a philosophy for the design of IVIS that supports drivers’ ability to multitask in-vehicle, could lead to task performance improvements.Jaguar Land Rove

Modeling driver distraction mechanism and its safety impact in automated vehicle environment.

Automated Vehicle (AV) technology expects to enhance driving safety by eliminating human errors. However, driver distraction still exists under automated driving. The Society of Automotive Engineers (SAE) has defined six levels of driving automation from Level 0~5. Until achieving Level 5, human drivers are still needed. Therefore, the Human-Vehicle Interaction (HVI) necessarily diverts a driver’s attention away from driving. Existing research mainly focused on quantifying distraction in human-operated vehicles rather than in the AV environment. It causes a lack of knowledge on how AV distraction can be detected, quantified, and understood. Moreover, existing research in exploring AV distraction has mainly pre-defined distraction as a binary outcome and investigated the patterns that contribute to distraction from multiple perspectives. However, the magnitude of AV distraction is not accurately quantified. Moreover, past studies in quantifying distraction have mainly used wearable sensors’ data. In reality, it is not realistic for drivers to wear these sensors whenever they drive. Hence, a research motivation is to develop a surrogate model that can replace the wearable device-based data to predict AV distraction. From the safety perspective, there lacks a comprehensive understanding of how AV distraction impacts safety. Furthermore, a solution is needed for safely offsetting the impact of distracted driving. In this context, this research aims to (1) improve the existing methods in quantifying Human-Vehicle Interaction-induced (HVI-induced) driver distraction under automated driving; (2) develop a surrogate driver distraction prediction model without using wearable sensor data; (3) quantitatively reveal the dynamic nature of safety benefits and collision hazards of HVI-induced visual and cognitive distractions under automated driving by mathematically formulating the interrelationships among contributing factors; and (4) propose a conceptual prototype of an AI-driven, Ultra-advanced Collision Avoidance System (AUCAS-L3) targeting HVI-induced driver distraction under automated driving without eye-tracking and video-recording. Fixation and pupil dilation data from the eye tracking device are used to model driver distraction, focusing on visual and cognitive distraction, respectively. In order to validate the proposed methods for measuring and modeling driver distraction, a data collection was conducted by inviting drivers to try out automated driving under Level 3 automation on a simulator. Each driver went through a jaywalker scenario twice, receiving a takeover request under two types of HVI, namely “visual only” and “visual and audible”. Each driver was required to wear an eye-tracker so that the fixation and pupil dilation data could be collected when driving, along with driving performance data being recorded by the simulator. In addition, drivers’ demographical information was collected by a pre-experiment survey. As a result, the magnitude of visual and cognitive distraction was quantified, exploring the dynamic changes over time. Drivers are more concentrated and maintain a higher level of takeover readiness under the “visual and audible” warning, compared to “visual only” warning. The change of visual distraction was mathematically formulated as a function of time. In addition, the change of visual distraction magnitude over time is explained from the driving psychology perspective. Moreover, the visual distraction was also measured by direction in this research, and hotspots of visual distraction were identified with regard to driving safety. When discussing the cognitive distraction magnitude, the driver’s age was identified as a contributing factor. HVI warning type contributes to the significant difference in cognitive distraction acceleration rate. After drivers reach the maximum visual distraction, cognitive distraction tends to increase continuously. Also, this research contributes to quantitatively revealing how visual and cognitive distraction impacts the collision hazards, respectively. Moreover, this research contributes to the literature by developing deep learning-based models in predicting a driver’s visual and cognitive distraction intensity, focusing on demographics, HVI warning types, and driving performance. As a solution to safety issues caused by driver distraction, the AUCAS-L3 has been proposed. The AUCAS-L3 is validated with high accuracies in predicting (a) whether a driver is distracted and does not perform takeover actions and (b) whether crashes happen or not if taken over. After predicting the presence of driver distraction or a crash, AUCAS-L3 automatically applies the brake pedal for drivers as effective and efficient protection to driver distraction under automated driving. And finally, a conceptual prototype in predicting AV distraction and traffic conflict was proposed, which can predict the collision hazards in advance of 0.82 seconds on average

Physical practice and wellness courses reduce distress and improve wellbeing in police officers

Background: The aim of this work was to evaluate a course to reduce distress in an Italian police force. Based on the findings from the first investigations on this population, courses to improve the ability to manage distress were tailored by management. Several free courses were proposed, including physical efficiency (e.g., total body conditioning) and wellness (e.g., autogenic training) classes. The goal of this research was to evaluate the courses and their impact on the perceived distress and general health of the participants, as well as the effectiveness in increasing the use of adaptive coping strategies. Methods: A descriptive investigation was conducted involving a sample of 105 police officers before (time 1) and after (time 2) they had participated in the courses. Results: Findings confirmed both physical and wellness courses affected, in participants, the perceived distress, thereby increasing the perception of wellbeing. The participants expressed having mental health benefits, the use of adaptive coping strategies increased, while the maladaptive coping strategies decreased. Conclusion: This study confirms that these courses could effectively reduce the risk of chronic disease, a consequence of persistent exposure to distress