Background/Objectives: For the rapid, objective characterization of the physiological stress response, there is currently no generally recognized standard. The stress measurement methods used in practice (e.g., for psychological measures of stress) are often subjective, or in the case of biological markers (e.g., cortisol, amylase), they usually require a blood test. For this reason, the use of heart rate variability (HRV) to characterize stress has recently come to the fore. HRV is the variability in the length of heartbeat intervals, which indicates the ability of the heart to respond to various physiological and environmental stimuli. However, the conventional HRV metrics are not corrected for heart rate dependence; hence, they fail to fully account for the complex physiology of stress and relaxation. In order to remedy this problem, here we introduce a novel HRV parameter, the normalized variability derived from an RMSSD “Master Curve”, and we compare it with the conventional metrics. Methods: In Study 1, the relaxation state was induced either by heart rate variability biofeedback training (N = 21) or by habitual relaxation (N = 21), while in Study 2 (N = 9), the Socially Evaluated Cold Pressor Test and the Socially Evaluated Stroop Test were used to induce stress in the subject. For a statistical evaluation of the data, the Kolmogorov–Smirnov test was used to compare the distributions of mean HR, log(RMSSD), log(SDNN), and normalized variability before, during, and after relaxation and stress. Results: The results of this study indicate that while log(RMSSD) and log(SDNN) did not change significantly, the normalized variability did undergo a significant change both in relaxation states and in stress states induced by the Socially Evaluated Cold Pressor Test. Conclusions: Overall, we suggest this novel type of normalized variability ought to be used as a sensitive stress indicator, and in general, for the characterization of the complex processes of the vegetative nervous system.

(1) Background and Goal: Several studies have investigated the association of sleep, diurnal patterns, and circadian rhythms with the presence and with the risk states of mental illnesses such as schizophrenia and bipolar disorder. The goal of our study was to examine actigraphic measures to identify features that can be extracted from them so that a machine learning model can detect premorbid latent liabilities for schizotypy and bipolarity. (2) Methods: Our team developed a small wrist-worn measurement device that collects and identifies actigraphic data based on an accelerometer. The sensors were used by carefully selected healthy participants who were divided into three groups: Control Group (C), Cyclothymia Factor Group (CFG), and Positive Schizotypy Factor Group (PSF). From the data they collected, our team performed data cleaning operations and then used the extracted metrics to generate the feature combinations deemed most effective, along with three machine learning algorithms for categorization. (3) Results: By conducting the training, we were able to identify a set of mildly correlated traits and their order of importance based on the Shapley value that had the greatest impact on the detection of bipolarity and schizotypy according to the logistic regression, Light Gradient Boost, and Random Forest algorithms. (4) Conclusions: These results were successfully compared to the results of other researchers; we had a similar differentiation in features used by others, and successfully developed new ones that might be a good complement for further research. In the future, identifying these traits may help us identify people at risk from mental disorders early in a cost-effective, automated way.

Antenatal and postpartum depression has been associated with maternal, child and family-unit complications. Our aim was to assess the impact of a depression screening and intervention program on perinatal complications. This study included 2042 women. They were screened on the Edinburgh Postnatal Depression Scale (EPDS), three times during pregnancy and once after childbirth. If their EPDS score was above the cut-off score, psychological intervention was offered. Significant relationships were found between depression scores and perinatal complications, such as protracted cervical dilation, protracted descent, preeclampsia, intrauterine growth restriction, low birthweight and cesarean section. Depression scores were higher in the intervention group, compared to the non-intervention group, but decreased after the consultations. The cesarean section rate was significantly lower in the consultation group. A rapid screening process can provide an adequate tool to identify women who are more likely to have such complications due to depression.

Biofeedback (BF) therapy methods have evolved considerably in recent years. The best known is biofeedback training based on heart rate variability (HRV), which is used to treat asthma, depression, stress, and anxiety, among other conditions, by synchronizing the rhythm of breathing and heartbeat. The aim of our research was to develop a methodology and test its applicability using photoplethysmographs and smartphones to conduct biofeedback sessions for frontline healthcare workers under their everyday stressful conditions. Our hypothesis is that such a methodology is not only comparable to traditional training itself, but can make regular sessions increasingly effective in reducing real-life stress by providing appropriate feedback to the subject. The sample consisted 28 participants. Our proprietary method based on HRV biofeedback is able to determine the resonance frequency of the subjects, i.e., the number at which the pulse and respiration are in sync. Our research app then uses visual feedback to help the subject reach this frequency, which, if maintained, can significantly reduce stress. By comparing BF with Free relaxation, we conclude that BF does not lose effectiveness over time and repetitions, but increases it. This paper is our pilot study in which we discuss the method used to select participants, the development and operation of the protocol and algorithm, and present and analyze the results obtained. The showcased results demonstrate our hypothesis that purely IT-based relaxation techniques can effectively compete with spontaneous relaxation through biofeedback. This provides a basis for further investigation and development of the methodology and its widespread use to effectively reduce workplace stress.

Introduction: The screening of perinatal depression was introduced in Szeged in April 2011. Aim: Our aim was to assess the extent of perinatal mood changing and to explore the risk factors of it. Method: Perinatal nurses gave the Edinburgh Postnatal Depression Scale to the 3849 participants four times. Results: In the first trimester were the highest average scores (3.74) and pathological rate (10.8%) compared to the other measurement occasions. There was a positive correlation between the scores of the measurement occasions. The higher average scores related to the epidural anesthesia almost significantly, but significantly to the low birth weight, unplanned pregnancies, younger and older age, single marital status and multiparity of the participant. Conclusions: Even the first trimester is sensitive to pathological mood changes, which besides with other factors could be risk factors to postpartum depression. To avoid this it is important to continue the screening and provide adequate help. Orv. Hetil., 2017, 158(4), 139–146.

Absztrakt: Bevezetés: A kiégés egyre nagyobb problémát jelent a munkahelyeken, egyre több kutatás foglalkozik a vizsgálatával. Az orvosi pályán fokozottan jelen van a kiégés veszélye, a sürgősségi osztályon való munka pedig ehhez képest is nagyobb kockázatot jelent, mégis kevesen foglalkoznak az itt dolgozókat érintő kiégés vizsgálatával. Célkitűzés: A szegedi Sürgősségi Betegellátó Önálló Osztály dolgozói között a kiégés vizsgálata, különböző változókkal való összefüggéseinek elemzése. Módszer: A demográfiai adatokra, testi panaszokra, társas támogatottságra és a pszichológiai immunrendszer felmérésére irányuló adatgyűjtés anonim kérdőíves módszerrel történt, a kiégést pedig a Maslach Kiégés Kérdőívvel vizsgáltuk. Eredmények: A statisztikai elemzés szerint negatív irányú az összefüggés a kiégés és az életkor, a gyermekszám, az egészségügyben eltöltött évek száma, a testi tünetek száma, a társas támogatottság, valamint a pszichológiai immunrendszer között. Az ‘egyedülálló’ családi állapot kockázati tényező. Következtetések: A kiégéssel kapcsolatban az eredmények alapján megfigyelhetők rizikó- és protektív tényezők, mely adatok segíthetnek a prevenció és az intervenció kidolgozásában. Orv Hetil. 2018; 159(3): 113–118. Introduction: Burnout has been described as a growing problem amongst healthcare workers. Emergency department staffs experience the burden of stress day by day, yet only a few studies have examined their burnout. Aim: In this study we wanted to investigate the burnout and its relations to other variables amongst the employees of the Department of Emergency Medicine in Szeged. Method: Cross-sectional design utilizing a self-administered questionnaire was used to collect data from the staff of the Department. Burnout was measured using the Maslach Burnout Inventory. Results: Burnout is considerably prevalent among the workers of the Emergency Department, especially nurses and physicians. The study found negative relation between burnout and age, number of children, number of years in the healthcare system, number of physical symptoms, social support and psychological immune system. Being single was a risk factor. Conclusions: The risks and protective factors found to be associated with burnout in this study might help to set up institutional prevention and intervention strategies. Orv Hetil. 2018; 159(3): 113–118.