How nature nurtures: Amygdala activity decreases as the result of a one-hour walk in nature

Since living in cities is associated with an increased risk for mental disorders such as anxiety disorders, depression and schizophrenia, it is essential to understand how exposure to urban and natural environments affects mental health and the brain. It has been shown that the amygdala is more activated during a stress task in urban compared to rural dwellers. However, no study so far has examined the causal effects of natural and urban environments on stress-related brain mechanisms. To address this question, we conducted an intervention study to investigate changes in stress-related brain regions as an effect of a one-hour walk in an urban (busy street) vs. natural environment (forest). Brain activation was measured in 63 healthy participants, before and after the walk, using a fearful faces task. Our findings reveal that amygdala activation decreases after the walk in nature, whereas it remains stable after the walk in an urban environment. These results suggest that going for a nature walk can have salutogenic effects for stress-related brain regions, and consequently, it may act as a preventive measure against mental strain and potentially disease. Given the rapidly increasing urbanization, the present results aim to influence urban planning to create more accessible green areas and to adapt urban environments in a way that will be beneficial for citizens’ mental health.

Mental Workload Analysis Using NASA-TLX Method at Bank XYZ - Medan Balaikota Consumer Loan Unit

All human activities, whether light, medium, or heavy, must have or contain a workload. Basically, every human being has a varied workload capacity, thus it's not inconceivable that the workload experienced by one worker differs from that of another, because there are a variety of elements that influence the difference in workload capacity. Sales and processing teams are under a lot of pressure to meet credit disbursement targets, which puts them under a lot of mental strain. A worker will experience work stress if he is given an excessive workload. When it comes to work, the influence of stress will result in a decline in performance, efficiency, and productivity of the work in question. To address this issue, a study based on the National Aeronautics and Space Administration Task Load Index (NASA-TLX) approach will be conducted to measure the mental strain of personnel in the Medan Balaikota consumer loan unit. NASA-TLX is a way for analyzing the mental workload of workers who must do a variety of tasks at work. Mental demand, physical demand, temporal demand, performance, effort, and frustration dimensions are among the six variables to be measured. Thirty workers of PT Bank XYZ Consumer Loan Unit Medan Balaikota Branch were surveyed. The NASA-TLX survey method is a quantitative descriptive methodology that was utilized to test in this study. According to the findings of the study, the NASA-TLX average score of PT Bank XYZ Consumer Loan Unit Medan Balaikota Branch employees obtained through research had a modest value. The result is a score of 77. Keywords: Mental Workload, NASA-TLX.

Is Mindfulness and Compassion Training Advisable in Alleviating Professional Burnout Among Physicians? Dilemmas and Possibilities in Healthcare System

The profession of a physician is a profession of social responsibility, in which medical competence should go hand in hand with non-medical competences. Mental strain, physical fatigue and entanglement in the administrative system can result in chronic stress and contribute to professional burnout, affecting both the well-being of medical staff and the quality of medical care provided. The Author’s intention is to promote mindfulness and compassion training that are considered to be protective and promoting the well-being of physicians resources in conditions of exposure to occupational stress. The analysis was based on 197 documents retrieved from the PubMed/Medline, Science Direct/Scopus databases in years 2008–2017, referring to the impact of mindfulness and compassion training on professional burnout among physicians. Only 21 papers retrieved from the scientific bases met inclusion criteria, referring to the impact of mindfulness and compassion training on professional burnout among physicians. Increasing concentration, improving memory, reducing the level of stress, anxiety and depression and strengthening kindness attitude are the basis for mindfulness and compassion training, which also supports the ability of unreactive responses to difficult situations, develops communication between the physician and the patient.

The impact of Covid-19 on Belgian mental health care: A Delphi study among psychosocial health professionals, patients, and informal caretakers

The Covid-19 pandemic is primarily viewed as a threat to physical health, and therefore, biomedical sciences have become an integral part of the public discourse guiding policy decisions. Nonetheless, the pandemic and the measures implemented have an impact on the population’s psychosocial health. The impact of Covid-19 on the psychosocial care system should be thoroughly investigated to mitigate this effect. In this context, the present study was conducted to establish a consensus about the impact of Covid-19 on psychosocial health and the care system in Belgium. Using the Belgian Superior Health Council’s expert database, a three-round Delphi consensus development process was organized with psychosocial experts (i.e., professionals, patients, and informal caregiver representatives). Overall, 113 of the 148 experts who participated in round 1 fully completed round 2 (76% response rate). Consensus (defined as >70% agreement and an interquartile interval (IQR) of no more than 2) was reached in round 2 for all but three statements. Fifty experts responded to round 3 by providing some final nuances, but none of them reaffirmed their positions or added new points to the discussion (44.25% response rate). The most robust agreement (>80%) was found for three statements: the pandemic has increased social inequalities in society, which increase the risk of long-term psychosocial problems; the fear of contamination creates a constant mental strain on the population, wearing people out; and there is a lack of strategic vision about psychosocial care and an underestimation of the importance of psychosocial health in society. Our findings show that experts believe the psychosocial impact of Covid-19 is underappreciated, which has a negative impact on psychosocial care in Belgium. Several unmet needs were identified, but so were helpful resources and barriers. The Delphi study’s overarching conclusion is that the pandemic does not affect society as a whole in the same way or with the same intensity. The experts, thereby, warn that the psychosocial inequalities in society are on the rise.

410. The Importance of Personal Protective Equipment Education Opportunities and Messages of Encouragement at the Workplace to Reduce Burnout: Cross-sectional Survey After the First Wave of the COVID-19 Pandemic in Japan

Background The rapid spread of the COVID-19 pandemic has taken a considerable mental strain on frontline healthcare workers (HCWs). Although a number of studies have reported on burnout during the peak of the pandemic, few studies have analyzed it after the pandemic temporally subsided. This study aimed to identify which intervention or support was helpful to reduce the physical and mental burden during the pandemic. Methods An online cross-sectional survey of HCWs from June 15 to July 6, 2020, was conducted at a tertiary hospital in Tokyo, Japan. Demographic characteristics, results of the Japanese version of the Maslach Burnout Inventory-General Survey, types of anxiety and stress, changes in life and work after the peak of the pandemic, and types of support aimed at reducing the physical or mental burden, were determined. Results Out of 672 HCWs, 149 (22.6%) met the overall burnout criteria. Figure 1 showed the comparison of what helped reduce their physical and mental burden between the burnout group and the non-burnout group. After adjusted by the potential covariates, burnout was more prevalent in women (OR, 3.11; 95% CI, 1.45–6.67; p = .003), and had heightened anxiety due to unfamiliarity with PPE (OR, 1.98; 95% CI, 1.20–3.27; p=.007). Conversely, participants who reported that PPE education opportunities (OR, .484; 95% CI, .236–.993; p = .048) and messages of encouragement at the workplace (OR, .584; 95% CI, .352–.969; p = .037) helped reduce their physical and mental burden had less burnout. Figure 1. What factors helped reduce the physical or mental burden Conclusion The educational interventions for PPE and messages of encouragement at the workplace may be needed to reduce the mental burden for HCWs. Disclosures All Authors: No reported disclosures

Employing Multimodal Machine Learning for Stress Detection

In the current information age, the human lifestyle has become more knowledge-oriented, leading to sedentary employment. This has given rise to a number of health and mental disorders. Mental wellness is one of the most neglected, however crucial, aspects of today’s fast-paced world. Mental health issues can, both directly and indirectly, affect other sections of human physiology and impede an individual’s day-to-day activities and performance. However, identifying the stress and finding the stress trend for an individual that may lead to serious mental ailments is challenging and involves multiple factors. Such identification can be achieved accurately by fusing these multiple modalities (due to various factors) arising from a person’s behavioral patterns. Specific techniques are identified in the literature for this purpose; however, very few machine learning-based methods are proposed for such multimodal fusion tasks. In this work, a multimodal AI-based framework is proposed to monitor a person’s working behavior and stress levels. We propose a methodology for efficiently detecting stress due to workload by concatenating heterogeneous raw sensor data streams (e.g., face expressions, posture, heart rate, and computer interaction). This data can be securely stored and analyzed to understand and discover personalized unique behavioral patterns leading to mental strain and fatigue. The contribution of this work is twofold: firstly, proposing a multimodal AI-based strategy for fusion to detect stress and its level and, secondly, identifying a stress pattern over a period of time. We were able to achieve 96.09% accuracy on the test set in stress detection and classification. Further, we were able to reduce the stress scale prediction model loss to 0.036 using these modalities. This work can prove important for the community at large, specifically those working sedentary jobs, to monitor and identify stress levels, especially in current times of COVID-19.

DIFFICULTIES ENCOUNTERED BY NURSE STUDENTS WHEN WORKING WITH ELDERLY PEOPLE

During the training process, nurse students acquire knowledge, skills and competencies to work with different groups of patients. Working with elderly people has its difficulties and specificities. The acquisition of practical skills by students for planning and documenting individual health care for the elderly people is a process in which teachers and mentors have a leading role. Objectives: To identify the factors which make it difficult for nurse students to work with elderly people. Methods: The study involved 52 3rd year nurse students – from the Faculty of Medicine of Trakia University in Bulgaria. A questionnaire was used, including open-ended and closed-ended questions, allowing more than one answer. The data was processed mathematically and graphically. Results: The main difficulties for students in working with the elderly people are as follows: the process of communication (92.16%), difficult perception of new information (80.64%) and memory impairment in the elderly patient (61.44%); The main difficulties related to the organization of activity - insufficient experience in working with geriatric patients (92.16%); insufficient time for communication with patients (94.08%); lack of comfort in the patient's home (57.60%); a "Diary for tracking and self-monitoring of the condition" of an elderly person - it is very useful for 90.24% of students so that they can monitor the condition of the elderly person; It was found that 65.28% of students do not want to work with elderly people, as 46.09% of them indicate the motive for this as mental strain. Conclusion: The teacher and the mentor are leading figures in preparing students to work with elderly people. The practical preparation for planning and documenting individual health care for elderly people is very important in the training process of nurse students.

Identifying Chinese Medicine Patterns of Tension-Type Headache and Understanding Its Subgroups

Tension-type headache (TTH) is common among adults. Individualized management strategies are limited due to lack of understanding of subtypes of TTH. Chinese medicine (CM) uses the pattern differentiation approach to subtype all health conditions. There is, however, a lack of evidence-based information on CM patterns of TTH. This study aimed to identity common CM patterns of TTH. TTH sufferers were invited for a survey, consisting of a validated Chinese Medicine Headache Questionnaire (CMHQ), Migraine Disability Assessment Test, and Perceived Stress Scale. The CMHQ consisted of information about headache, aggravating and relieving factors, and accompanying symptoms. Principal component analysis was used for factor extraction and TwoStep cluster analyses for identifying clusters. ANOVA was used to compare cluster groups with disability and stress. In total, 170 eligible participants took part in the survey. The commonest headache features were continuous pain (64%); fixed location (74%); aggravated by overwork (74%), stress (74%), or mental strain (70%); and relieved by sleeping (78%). The commonest nonpain symptoms were fatigue (71%) and neck stiffness (70%). Four clusters, differing in their key signs and symptoms, could be assigned to three different CM patterns including ascendant hyperactivity of liver yang (cluster 1), dual qi and blood deficiency (cluster 2), liver depression forming fire (cluster 3), and an unlabelled group (cluster 4). Additionally, over 75% participants in clusters 1 and 2 have episodic TTH, over one-third participants in cluster 3 have chronic TTH, and a majority of participants in cluster 4 have infrequent TTH. The three patterns identified also differed in levels of disability and some elements of coping as measured with PSS. The three CM patterns identified are common clinical presentations of TTH. The new information will contribute to further understanding of the subtypes of TTH and guide the development of targeted intervention combinations for clinical practice and research.

New Measures of Heart Rate Variability Based on Subband Tachogram Complexity and Spectral Characteristics for Improved Stress and Anxiety Monitoring in Highly Ecological Settings

Prediction of mental states, such as stress and anxiety, can be important in situations where reduced job performance due to increased mental strain can lead to critical situations (e.g., front-line healthcare workers and first responders). While recent advances in biomedical wearable sensor technologies have allowed for collection of multiple physiological signals in everyday environments, numerous challenges emerge from such uncontrolled settings, including increased noise levels and artifacts, confounding effects from other psychological states (e.g., mental fatigue), as well as physical variables (e.g., physical activity). These factors can be particularly detrimental for heart rate variability (HRV) measures which, in controlled settings, have been shown to accurately track stress and anxiety states. In this paper, we propose two new ways of computing HRV proxies which we show are more robust to such artifacts and confounding factors. The proposed features measure spectral and complexity properties of different aspects of the autonomic nervous system, as well as their interaction. Across two separate “in-the-wild” datasets, the proposed features showed to not only outperform benchmark HRV metrics, but to also provide complementary information, thus leading to significantly greater accuracy levels when fused together. Feature ranking analysis further showed the proposed features appearing in 45–64% of the top features, thus further emphasizing their importance. In particular, features derived from the high frequency band showed to be most important in the presence of fatigue and physical activity confounding factors, thus corroborating their importance for mental state assessment in highly ecological settings.

Impact of COVID-19 Restrictions on the Social-Emotional Wellbeing of Preschool Children and Their Families

In the spring of 2020, as a result of the lockdown caused by the COVID-19 pandemic, many children dropped out of daycare and early education in Finland, and parents had to balance work and childcare for months. The wellbeing of families during the lockdown has been studied to some extent, but few studies have focused on children under school age. In May 2020, we sent a survey to the 82 families originally recruited in our study on supporting social-emotional development in early childhood education units, which had been interrupted by the pandemic. Twenty families responded to questionnaires about the impacts of the lockdown on the wellbeing of the children and their parents. Parents reported a decline in children’s prosocial behavior compared to the time before the pandemic and assessed that the children who stayed at home were lonelier than children who remained in daycare. Otherwise, being at home or in care was not associated with children’s physical or mental wellbeing. Parents had experienced increased mental strain and increased problems in marital relationships and the disruption of children’s participation in daycare was associated with deterioration in the parent–child relationship. Due to the small sample size, these results should be interpreted with caution.