Background: Teamwork is essential in healthcare, but team performance tends to deteriorate in stressful situations. Further development of training and education for healthcare teams requires a more complete understanding of team performance in stressful situations. We wanted to learn from others, by looking beyond the field of medicine, aiming to learn about a) sources of stress, b) effects of stress on team performance and c) concepts on dealing with stress. Methods: A scoping literature review was undertaken. The three largest interdisciplinary databases outside of healthcare, Scopus, Web of Science and PsycINFO, were searched for articles published in English between 2008 and 2020. Eligible articles focused on team performance in stressful situations with outcome measures at a team level. Studies were selected, and data were extracted and analysed by at least two researchers. Results: In total, 15 articles were included in the review (4 non-comparative, 6 multi- or mixed methods, 5 experimental studies). Three sources of stress were identified: performance pressure, role pressure and time pressure. Potential effects of stress on the team were: a narrow focus on task execution, unclear responsibilities within the team and diminished understanding of the situation. Communication, shared knowledge and situational awareness were identified as potentially helpful team processes. Cross training was suggested as a promising intervention to develop a shared mental model within a team. Conclusion: Stress can have a significant impact on team performance. Developing strategies to prevent and manage stress and its impact has the potential to significantly increase performance of teams in stressful situations. Further research into the development and use of team cognition in stress in healthcare teams is needed, in order to be able to integrate this ‘team brain’ in training and education with the specific goal of preparing professionals for team performance in stressful situations.
MULTIFILE
As a consequence of climate change and urbanization, many cities will have to deal with more flooding and extreme heat stress. This paper presents a framework to maximize the effectiveness of Nature-Based Solutions (NBS) for flood risk reduction and thermal comfort enhancement. The framework involves an assessment of hazards with the use of models and field measurements. It also detects suitable implementation sites for NBS and quantifies their effectiveness for thermal comfort enhancement and flood risk reduction. The framework was applied in a densely urbanized study area, for which different small-scale urban NBS and their potential locations for implementation were assessed. The overall results show that the most effective performance in terms of flood mitigation and thermal comfort enhancement is likely achieved by applying a range of different measures at different locations. Therefore, the work presented here shows the potential of the framework to achieve an effective combination of measures and their locations, which was demonstrated on the case of the Sukhumvit area in Bangkok (Thailand). This can be particularly suitable for assessing and planning flood mitigation measures in combination with heat stress reduction.
The demanding environment that contemporary dance students are exposed to could result in high stress levels, which can influence injury susceptibility. Therefore, this study aims to investigate the association between stress and injuries. In the period between September 2016 and March 2020, four cohorts of first-year dance students (N = 186; mean age 19.21 ± 1.35 years) were followed for one academic year. Each month, general stress was assessed on a 0-100 visual analogous scale. The Oslo Sports Trauma Research Center Questionnaire on Health Problems was used on a monthly basis to monitor injuries. Injuries were defined as "all injuries" (i.e., any physical complaint irrespective of the need for medical attention or time-loss from dance) and "substantial injuries" (i.e., leading to moderate/severe/complete reductions in training volume or performance). Mann-Whitney tests were performed to measure differences in general stress levels between injured and injury-free students, while repeated-measures ANOVA were performed to investigate whether general stress scores increased before and during injury occurrence. The overall average monthly general stress score over all cohorts for all students was 39.81. The monthly general stress scores ranged from 31.75 to 49.16. Overall, injured and substantially injured students reported higher stress scores than injury-free students, with significant differences in 3 out of the 9 months for all injuries (September, October, March, p < 0.05), and in 5 months for substantial injuries (September, October, November, December, April, p < 0.05). Within the 3-month period before and during injury occurrence, a (marginally) significant linear effect of general stress across the time periods was found for all injuries [F(1.87,216.49) = 3.10, p = 0.051] and substantial injuries [F(2,138) = 4.16, p = 0.018]. The results indicate an association between general stress and injuries. Future research should focus on effects of varying stress levels on injury risk using higher sampling frequency, for instance by measuring weekly since stress levels are likely to fluctuate daily. Practically, strategies aiming at stress reduction might have the potential to reduce the burden of dance injuries and may have positive outcomes for dancers, teachers, schools, and companies.
Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.
The Netherlands is one of the most densely populated countries in Europe. Despite the excellent road network, The Netherlands is confronted with this density on a daily basis: the negative impact of traffic jams and incidents on travel times is growing by 38% the next 5 years. VIA NOVA will lay the necessary foundation for the next step of technological developments to overcome these negative impacts of congestion in future. This next step in technological developments is called Talking Traffic. Vehicles will communicate directly with the infrastructure and other road users and vice versa. The potential with respect to congestion reduction is big, because traffic can be managed more directly. To reach this potential, Talking Traffic relies to a large extent on (big)data already available in modern cars: data of sensors, navigation, etc. However, the problem is data usage in terms of quality and variety among car-brands. The partners stressed the fact that besides technical requirements: data deployment quality, code of practice and a guideline, research should also address business requirements. Without a clear view on quality variations and demands with respect to quality, the data cannot be used effectively. VIA NOVA researches the following issues, o quality and quantity of data from cars o needed quality and quantity of data from cars in Talking Traffic use cases o big data analysis tools to interpret large quantities of data o business models, privacy and security of data from cars The outcome enables users to judge whether data from cars can be useful to solve specific traffic related problems, which data is than to be used, which quality of data is needed and finally the quantity of the needed data. With this measure Talking Traffic can be deployed more effectively resulting in more reduction of congestion.
