Neurophysiological determinants of occupational stress and burnout

IntroductionResearch results show that one of the greatest health challenges of the 21st century, especially in developed countries, is becoming the fight against the effects of living too fast, including the fight against occupational stress and burnout. Aim of the study The purpose of this article is to elucidate the neurophysiological determinants of occupational stress and burnout, including ocupational, including through the path of research review and the development of computational models based on artificial intelligence. Materials and methods A literature search was conducted in six bibliographic databases: PubMed, EBSCO, PEDro, Web of Science, Scopus and Google Scholar. Articles were searched in English using the following keywords: occupational stress, burnout, marker, electroencephalography, EEG, magnetic resonance imaging, MRI, fMRI, computed tomography, CT, positron emission tomography, PET, computational model, machine learning, artificial intelligence, virtual patient, digital twin and similar. Neurophysiological determinants of occupational stress and burnout as far as computational models of occupational stress and burnout were analysed and discussed. Results The best currently observed neurophysiological markers of occupational stress and burnout may currently be a combination of EEG analysis (alpha power (IAF, PAF), P300, ERP (VPP and EPN)), diagnostic PET imaging (ACC, insular cortex and hippocampus) and monitoring changes in cortisol, prolactin, adrenocorticotropic hormone (ACTH), corticotropin-releasing hormone (CRH) and thyroid hormones, as well as plasma BDNF levels. In addition, ERPs (LPPs) are a marker significantly differentiating burnout from depression. Conclusions The combination of traditional clinimetric tests, the aforementioned neurophysiological tests and AI-based big data analysis will provide new classifiers, highly accurate results and new diagnostic methods. &nbsp

Selected determinants of occupational stress and burnout in physiotherapists and IT professionals

IntroductionOccupational stress and burnout have a statistically significant negative impact on learning and work in the professional groups studied, but the exact manner and strength of the impact and the neurophysiological mechanisms underlying the aforementioned phenomena are not yet well understood. The main reason for this is the paucity of research, both on the neurobiological basis and on the incidence and impact on the lives of different professional groups. Aim of the study The main objective of the study is to determine the clinical and neurophysiological determinants of occupational stress and burnout, and in particular to investigate whether: - occupational stress and burnout are related to occupational group, - the start of professional work already during studies is a significant differentiating factor, - the nature of work, gender and seniority affect work-related musculoskeletal problems. Materials and methods Two groups were recruited for the study: study group (physiotherapists, n = 50), reference group (IT professionals, n = 50). Five clinimetric scales were used in the study: PSS10, MBI, SWLS, MSQ-SF, NMQ. Results Clinical and neurophysiological determinants of occupational stress and burnout relate to statistically significant effects: occupation, age, length of work, mode of employment, combination of study and work, and multi-work/multi-job. Conclusions Stress and burnout are related to the occupational group, with physiotherapists' occupational group experiencing them with greater severity than the IT occupational group. Starting a career already during studies is an important differentiating factor: it increases the risk of stress and professional burnout. The mode of employment, gender and seniority influence work-related musculoskeletal problems: they are experienced more often by the self-employed, men, older people and those with longer work experience

Electrophysiological Neuroimaging using sLORETA Comparing 22 Age Matched Male and Female Schizophrenia Patients

BACKGROUND: Standardized low resolution brain electric tomography (sLORETA) is a validated neuroimaging method for localizing the electric activity in the brain based on multichannel surface electroencephalogram (EEG) recordings, having the benefit of improved time resolution of EEG measurements, better than that of functional magnetic resonance imaging (fMRI), and with a spatial resolution similar to that of fMRI.OBJECTIVE: The purpose of this electrophysiological neuroimaging study was to provide a deeper mechanistic understanding of both olanzapine and risperidone pharmacodynamics relative to gender. In doing so, we age-matched 22 men and women and initially evaluated their resting-state EEG recordings and later used sLORETA to visualize the differences in brain activity amongst the two patient groups.METHODS: In this investigation, EEG data were analyzed from male and female schizophrenia patients treated with either olanzapine or risperidone, both atypical antipsychotics, during their in-patient stay at the Department of Psychiatry. Twenty two males and females were age-matched and EEG recordings were analyzed from 19 silver/silver chloride electrodes. Thirty-seconds of resting EEG were spectrally transformed into sLORETA. Three-dimensional statistical non-paramentric maps for the sLORETA global field power within each band were finally computed.RESULTS: The results indicated that, relative to males patients, females schizophrenia patients had increased neuronal synchronization in delta frequency, slow-wave, EEG band located in the dorsolateral prefrontal cortex, within the middle frontal gyrus (t= -2.881, p <0.03580). These findings suggest that females experience greater dopamine receptor and serotonin receptor neuronal blockade relative to age-matched males. Further, our findings provided insight to the pharmacodynamics of secondgeneration antipsychotics olanzapine and risperidone.CONCLUSION: When compared to male patients, female patients suffering from schizophrenia have dopamine and serotonin receptors that are blocked more readily than age-matched male schizophrenia patients. Clinically, this may translate into a quicker time to treatment-response in females as compared to male patients

Predicting lithium treatment response in bipolar patients using gender-specific gene expression biomarkers and machine learning [version 3; referees: 1 approved, 2 approved with reservations]

Background: We sought to test the hypothesis that transcriptome-level gene signatures are differentially expressed between male and female bipolar patients, prior to lithium treatment, in a patient cohort who later were clinically classified as lithium treatment responders. Methods: Gene expression study data was obtained from the Lithium Treatment-Moderate dose Use Study data accessed from the National Center for Biotechnology Information’s Gene Expression Omnibus via accession number GSE4548. Differential gene expression analysis was conducted using the Linear Models for Microarray and RNA-Seq (limma) package and the Decision Tree and Random Forest machine learning algorithms in R. Results: Using quantitative gene expression values reported from patient blood samples, the RBPMS2 and LILRA5 genes classify male lithium responders with an area under the receiver operator characteristic curve (AUROC) of 0.92 and the ABRACL, FHL3, and NBPF14  genes classify female lithium responders AUROC of 1. A Decision Tree rule for establishing male versus female samples, using gene expression values were found to be: if RPS4Y1 ≥ 9.643, patient is a male and if RPS4Y1 < 9.643, patient is female with a probability=100%. Conclusions: We developed a pre-treatment gender- and gene-expression-based predictive model selective for classifying male lithium responders with a sensitivity of 96% using 2-genes and female lithium responders with sensitivity=92% using 3-genes

Wielokryterialna analiza wyników badania wypalenia zawodowego

The aim of this study on multi-criteria analysis of job burnout is to fill an existing research gap, bringing an element of novelty and enabling a near comparison with other analytical methods used to assess job burnout. The concept of using the MCA in the analysis of occupational burnout outcomes appears useful and effective. The MCA acts as a useful computational tool in this case. It can be effectively applied in the area of job burnout and work-related stress, where single-criteria methodologies produce uncertain results, are debatable or may be considered ineffective, because the factors (organisational, social, environmental and other) relevant for proper assessment and decisionmaking cannot be expressed in terms of objective values or are expressed linguistically. Further research using fuzzy logic may bring the next step in the development of the proposed method towards a holistic approach.Celem niniejszego badania poświęconego wielokryterialnej analizie wypalenia zawodowego jest wypełnienie istniejącej luki badawczej, wnosząc element nowości i umożliwiając przysżłosciowe oorównanie z innymi metodami analitycznymi stosowanym do oceny wypalenia zawodowego. Koncepcja wykorzystania MCA w analizie wyników wypalenia zawodowego wydaje się przydatna i efektywna. MCA działa w tym przypadku jako użyteczne narzędzie obliczeniowe. Może być skutecznie stosowane w obszarze wypalenia zawodowego i stresu zwiazanego z pracą, gdzie metodologie oparte na pojedynczych kryteriach dają niepewne wyniki, są dyskusyjne lub mogą być uznane za nieskuteczne, gdyż istotne dla własciwej oceny i podjęcie decyzji czynniki (organizacyjne, społeczne, środowiskowe i inne) nie mogą być wyrażone w kategoriach wartości obiektywnych lub są wyrażane lingwistycznie. Dalsze badania z wykorzystaniem logiki rozmytej mogą przynieść kolejny etap rozwoju proponowanej metody w kierunku podejścia całościowego

Objawy wypalenia zawodowego jako podstawa modelu obliczeniowego

The current challenge is to explore and optimise computational measures of burnout to objectively determine the best way to calculate job satisfaction, job burnout and predictors of intention to quit across occupational groups. The aim of the research presented in this article was to review studies in the field of computational determination of the relationship between the experience of stress at work and the occurrence of symptoms of professional burnout.Obecnym wyzwaniem jest zbadanie i optymalizacja obliczeniowych miar wypalenia zawodowego w celu obiektywnego określenia najlepszego sposobu obliczania satysfakcji z pracy, wypalenia zawodowego i predyktorów zamiaru odejścia z pracy w różnych grupach zawodowych.Celem badań prezentowanych w artykule był przegląd badań w zakresie obliczeniowego określanie zależności między doświadczaniem stresu w pracy a występowaniem objawów wypalenia zawodowego

Most Popular Signal Processing Methods in Motor-Imagery BCI: A Review and Meta-Analysis

Brain-Computer Interfaces (BCI) constitute an alternative channel of communication between humans and environment. There are a number of different technologies which enable the recording of brain activity. One of these is electroencephalography (EEG). The most common EEG methods include interfaces whose operation is based on changes in the activity of Sensorimotor Rhythms (SMR) during imagery movement, so-called Motor Imagery BCI (MIBCI).The present article is a review of 131 articles published from 1997 to 2017 discussing various procedures of data processing in MIBCI. The experiments described in these publications have been compared in terms of the methods used for data registration and analysis. Some of the studies (76 reports) were subjected to meta-analysis which showed corrected average classification accuracy achieved in these studies at the level of 51.96%, a high degree of heterogeneity of results (Q = 1806577.61; df = 486; p &lt; 0.001; I2 = 99.97%), as well as significant effects of number of channels, number of mental images, and method of spatial filtering. On the other hand the meta-regression failed to provide evidence that there was an increase in the effectiveness of the solutions proposed in the articles published in recent years. The authors have proposed a newly developed standard for presenting results acquired during MIBCI experiments, which is designed to facilitate communication and comparison of essential information regarding the effects observed. Also, based on the findings of descriptive analysis and meta-analysis, the authors formulated recommendations regarding practices applied in research on signal processing in MIBCIs

Związane z pracą niekorzystne zmiany zdrowotne w grupie zawodowej informatyków – narracyjny przegląd literatury

Occupational medicine is increasingly using modern technology and becoming more interdisciplinary. This may be a response to both the development of medical and other sciences that support contemporary clinical practice as well as new therapeutic approaches that are oriented towards collaboration within an interdisciplinary team, are patient-centred and meet the requirements of Evidence-Based Medicine. This article attempts to assess the extent to which opportunities in this area are being exploited and to identify factors that offer opportunities for breakthrough.Medycyna pracy coraz częściej korzysta z nowoczesnych technologii i staje się coraz bardziej interdyscyplinarna. Może to być reakcją zarówno na rozwój nauk medycznych i innych nauk wspierających współczesną praktykę kliniczną, jak również nowe sposoby terapii ukierunkowane na współpracę w ramach zespołu interdyscyplinarnego, zorientowaną na pacjenta i spełniająca wymagania Medycyny Opartej na Faktach. Artykuł stanowi próbę oceny, w jakim stopniu wykorzystuje się możliwości w tym obszarze i wskazania czynników dających szanse na przełom

Mapping the Human Brain in Frequency Band Analysis of Brain Cortex Electroencephalographic Activity for Selected Psychiatric Disorders

There are still no good quantitative methods to be applied in psychiatric diagnosis. The interview is still the main and most important tool in the psychiatrist work. This paper presents the results of electroencephalographic research with the subjects of a group of 30 patients with psychiatric disorders compared to the control group of healthy volunteers. All subjects were solving working memory task. The digit-span working memory task test was chosen as one of the most popular tasks given to subjects with cognitive dysfunctions, especially for the patients with panic disorders, depression (including the depressive phase of bipolar disorder), phobias, and schizophrenia. Having such cohort of patients some results for the subjects with insomnia and Asperger syndrome are also presented. The cortical activity of their brains was registered by the dense array EEG amplifier. Source localization using the photogrammetry station and the sLORETA algorithm was then performed in five EEG frequency bands. The most active Brodmann Areas are indicated. Methodology for mapping the brain and research protocol are presented. The first results indicate that the presented technique can be useful in finding psychiatric disorder neurophysiological biomarkers. The first attempts were made to associate hyperactivity of selected Brodmann Areas with particular disorders