Changes in global and relationship-specific attachment working models

Attachment theorists suggest that people construct a number of distinct working models throughout life. People develop global working models, which reflect their expectations and beliefs concerning relationships in general, as well as relationship-specific working models of close others—their mothers, fathers, romantic partners, and friends. The present research investigated the interplay of these different working models over time. We analyzed longitudinal data collected from 4,904 adults (mean age = 35.24 years; SD = 11.63) who completed between 3 and 24 online survey assessments (median test–retest interval = 35 days). Using latent growth curve modeling, we examined the associations among both long-term changes and short-term fluctuations in participants’ working models. Our findings suggest that different working models not only change together over the long run, but also exhibit co-occurring, short-term fluctuations. This was true concerning the associations between global and relationship-specific models as well as among different relationship-specific models.

ПЕРФУЗІЙНА ДИСФУНКЦІЯ ПРИ ГОСТРОМУ ПАНКРЕАТИТІ: ПЕРСПЕКТИВНІ НАПРЯМКИ УДОСКОНАЛЕННЯ ДІАГНОСТИКИ ТА СТРАТИФІКАЦІЇ ЗАХВОРЮВАННЯ

Introduction. Acute pancreatitis (AP) is one of the most common diseases of the digestive system that require hospitalization. To date, the problem of stratification and differential diagnosis of AP in the early stages remains unresolved, which encourages the search for new methods of diagnosis and prediction of the severity of AP. Aim. To evaluate the possibility of creating a clinically oriented system of stratification and prognosis of AP on the basis of dynamic changes in microcirculation depending on the duration of the disease and severity of AP. Materials and methods. Assessment of the state of microcirculation (MC) of patients by laser Doppler flowmetry (LDF) was performed with the “LAKK-02” device. Kruskal-Wallis non-parametric analysis of variance and the median test were used to test statistical hypotheses when comparing independent samples. Pairwise comparison of independent samples was performed using the Mann-Whitney U test. Results. The study determined the indicators of MC in patients with different AP severity degrees on the first day of the disease. The microcirculation parameter (MP) in patients with mild, moderate, and severe AP was 3.9; 3.8 and 6.8 perfusion units (p.u.), respectively. The blood flow modulation rate (ơ) was 0.52; 0.54 and 0.69 p.u. in mild, moderate, and severe AP. In our study, the coefficient of variation (Kv) averaged 17.3%; 20.0% and 11.7% in patients with mild, moderate, and severe AP, respectively. Conclusions. LDF in AP is an informative method of diagnosing the state of MC, which is a universal link in all pathophysiological reactions of the organism. Changes of MC in AP depend on the severity of AP and the period of the disease. The pathophysiological microcirculatory phenomena, revealed on the first day of the disease, provide us with the perspectives of early clinical distinguishing the moderate and severe forms of AP from the so-called group of “destructive forms”.

Smart Devices and Family Roles: A Study of Smart Device Use Among Children Aged 2-5 in Thailand’s Health Region 3

This research investigated smart device use among young Thai children. The study likewise explored the relationship between smart device screen time, family roles in smart device use, and effects of smart device use. In 2020, primary data were collected through questionnaires from 1,100 primary parents of 2-5-year-old children in five provinces in Health Region 3. A Mann-Whitney U Test and Median Test were used in data analyses of the associations. The results revealed that 2-5-year-old children had an average screen time per day of 1 hour and 33 minutes, with 54.3% spending more than 1 hour on smart devices daily. In addition, 21.5% reported owning a smartphone, of which 55.2% accessed YouTube to watch cartoons and movies. In terms of screen time, 21.7% of the children reported unrestricted use. In terms of effects from smart device use, children being easily irritated and moody was noted by most parents (61.5%). In addition, variables under family roles and effects of smart device use showed a statistically significant correlation with smart device screen time. However, median screen time varied by each variable under family roles and effects of smart device use. The findings are essential for future policy planning, which will enable families with young children to become aware of appropriate smartphone or tablet usage by their children.

Temporal and Spatial Autocorrelation as Determinants of Regional AOD-PM2.5 Model Performance in the Middle East

Exposure to fine particulate matter (PM2.5) air pollution has been shown in numerous studies to be associated with detrimental health effects. However, the ability to conduct epidemiological assessments can be limited due to challenges in generating reliable PM2.5 estimates, particularly in parts of the world such as the Middle East where measurements are scarce and extreme meteorological events such as sandstorms are frequent. In order to supplement exposure modeling efforts under such conditions, satellite-retrieved aerosol optical depth (AOD) has proven to be useful due to its global coverage. By using AODs from the Multiangle Implementation of Atmospheric Correction (MAIAC) of the MODerate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging Spectroradiometer (MISR) combined with meteorological and assimilated aerosol information from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), we constructed machine learning models to predict PM2.5 in the area surrounding the Persian Gulf, including Kuwait, Bahrain, and the United Arab Emirates (U.A.E). Our models showed regional differences in predictive performance, with better results in the U.A.E. (median test R2 = 0.66) than Kuwait (median test R2 = 0.51). Variable importance also differed by region, where satellite-retrieved AOD variables were more important for predicting PM2.5 in Kuwait than in the U.A.E. Divergent trends in the temporal and spatial autocorrelations of PM2.5 and AOD in the two regions offered possible explanations for differences in predictive performance and variable importance. In a test of model transferability, we found that models trained in one region and applied to another did not predict PM2.5 well, even if the transferred model had better performance. Overall the results of our study suggest that models developed over large geographic areas could generate PM2.5 estimates with greater uncertainty than could be obtained by taking a regional modeling approach. Furthermore, development of methods to better incorporate spatial and temporal autocorrelations in machine learning models warrants further examination.

National Health Systems and COVID-19 Death Toll Doubling Time

Coronavirus disease 2019 (COVID-19) has placed stress on all National Health Systems (NHSs) worldwide. Recent studies on the disease have evaluated different variables, namely, quarantine models, mitigation efforts, damage to mental health, mortality of the population with chronic diseases, diagnosis, use of masks and social distancing, and mortality based on age. This study focused on the four NHSs recognized by the WHO. These systems are as follows: (1) The Beveridge model, (2) the Bismarck model, (3) the National Health Insurance (NHI) model, and (4) the “Out-of-Pocket” model. The study analyzes the response of the health systems to the pandemic by comparing the time in days required to double the number of disease-related deaths. The statistical analysis was limited to 56 countries representing 70% of the global population. Each country was grouped into the health system defined by the WHO. The study compared the median death toll DT, between health systems using Mood's median test method. The results show high variability of the temporal trends in each group; none of the health systems for the three analyzed periods maintain stable interquartile ranges (IQRs). Nevertheless, the results obtained show similar medians between the study groups. The COVID-19 pandemic saturates health systems regardless of their management structures, and the result measured with the time for doubling death rate variable is similar among the four NHSs.

Demographic And Statistical Modelling Of Grandfatherhood In Russia

In recent years, negative demographic trends have been developing in Russia. The most important is a decline in the birth rate. Researchers are actively looking for new determinants of this process, on the basis of which measures of population policy can be developed. One of these determinants may be active grandparenting, which means the active participation of grandparents in the processes of caring for grandchildren. The aim of this study is to create a demographic and statistical model of a typical Russian grandfather, actively involved in childcare. We used the following methods: parametric and nonparametric independent samples tests (t-test, Mann-Whitney U test, median test), regression analysis, indirect method of calculations. As a result, two models were presented – statistical demographic model of the age when Russian men enter grandparenthood and demographic model of a typical Russian grandfather actively involved in childcare. Our study is a preliminary stage for a large-scale survey of grandparenting practices in Russia. The number of older people is growing fast, which makes this socio-economic group increasingly important for addressing the problems of demographic decline in Russia. Therefore, large-scale research of grandparenthood is crucial for more efficient policy-making in this sphere.

A [68Ga]Ga-DOTANOC PET/CT Radiomic Model for Non-Invasive Prediction of Tumour Grade in Pancreatic Neuroendocrine Tumours

Predicting grade 1 (G1) and 2 (G2) primary pancreatic neuroendocrine tumour (panNET) is crucial to foresee panNET clinical behaviour. Fifty-one patients with G1-G2 primary panNET demonstrated by pre-surgical [68Ga]Ga-DOTANOC PET/CT and diagnostic conventional imaging were grouped according to the tumour grade assessment method: histology on the whole excised primary lesion (HS) or biopsy (BS). First-order and second-order radiomic features (RFs) were computed from SUV maps for the whole tumour volume on HS. The RFs showing the lowest p-values and the highest area under the curve (AUC) were selected. Three radiomic models were assessed: A (trained on HS, validated on BS), B (trained on BS, validated on HS), and C (using the cross-validation on the whole dataset). The second-order normalized homogeneity and entropy was the most effective RFs couple predicting G2 and G1. The best performance was achieved by model A (test AUC = 0.90, sensitivity = 0.88, specificity = 0.89), followed by model C (median test AUC = 0.87, sensitivity = 0.83, specificity = 0.82). Model B performed worse. Using HS to train a radiomic model leads to the best prediction, although a “hybrid” (HS+BS) population performs better than biopsy-only. The non-invasive prediction of panNET grading may be especially useful in lesions not amenable to biopsy while [68Ga]Ga-DOTANOC heterogeneity might recommend FDG PET/CT.

Shoulder strap fixation of LUCAS-2 to facilitate continuous CPR during non-supine (stair) stretcher transport of OHCAs patients

Early recognition and rapid initiation of high-quality cardiopulmonary resuscitation (CPR) are key to maximising chances of achieving successful return of spontaneous circulation in patients with out-of-hospital cardiac arrests (OHCAs), as well as improving patient outcomes both inside and outside hospital. Mechanical chest compression devices such as the LUCAS-2 have been developed to assist rescuers in providing consistent, high-quality compressions, even during transportation. However, providing uninterrupted and effective compressions with LUCAS-2 during transportation down stairwells and in tight spaces in a non-supine position is relatively impossible. In this study, we proposed adaptations to the LUCAS-2 to allow its use during transportation down stairwells and examined its effectiveness in providing high-quality CPR to simulated OHCA patients. 20 volunteer emergency medical technicians were randomised into 10 pairs, each undergoing 2 simulation runs per experimental arm (LUCAS-2 versus control) with a loaded Resusci Anne First Aid full body manikin weighing 60 kg. Quality of CPR compressions performed was measured using the CPRmeter placed on the sternum of the manikin. The respective times taken for each phase of the simulation protocol were recorded. Fisher’s exact tests were used to analyse categorical variables and median test to analyse continuous variables. The LUCAS-2 group required a longer time (~ 35 s) to prepare the patient prior to transport (p < 0.0001) and arrive at the ambulance (p < 0.0001) compared to the control group. The CPR quality in terms of depth and rate for the overall resuscitation period did not differ significantly between the LUCAS-2 group and control group, though there was a reduction in both parameters when evaluating the device’s automated compressions during transport. Nevertheless, the application of the LUCAS-2 device yielded a significantly higher chest compression fraction of 0.76 (p < 0.0001). Our novel adaptations to the LUCAS-2 device allow for uninterrupted compressions in patients being transported down stairwells, thus yielding better chest compression fractions for the overall resuscitation period. Whether potentially improved post-OHCA survival rates may be achieved requires confirmation in a real-world scenario study.

Scalp high-frequency oscillation rates are higher in younger children

High-frequency oscillations in scalp EEG are promising non-invasive biomarkers of epileptogenicity. However, it is unclear how high-frequency oscillations are impacted by age in the paediatric population. We prospectively recorded whole-night scalp EEG in 30 children and adolescents with focal or generalized epilepsy. We used an automated and clinically validated high-frequency oscillation detector to determine ripple rates (80–250 Hz) in bipolar channels. Children &lt; 7 years had higher high-frequency oscillation rates (P = 0.021) when compared with older children. The median test−retest reliability of high-frequency oscillation rates reached 100% (iqr 50) for a data interval duration of 10 min. Scalp high-frequency oscillation frequency decreased with age (r = −0.558, P = 0.002), whereas scalp high-frequency oscillation duration and amplitude were unaffected. The signal-to-noise ratio improved with age (r = 0.37, P = 0.048), and the background ripple band activity decreased with age (r = −0.463, P = 0.011). We characterize the relationship of scalp high-frequency oscillation features and age in paediatric patients. EEG intervals of ≥10 min duration are required for reliable measurements of high-frequency oscillation rates. This study is a further step towards establishing scalp high-frequency oscillations as a valid epileptogenicity biomarker in this vulnerable age group.

Effects of Speciation, Cooking and Changes in Bioaccessibility on Methylmercury Exposure Assessment for Contrasting Diets of Fish and Marine Mammals

Uptake of the neurotoxicant monomethylmercury (MeHg) from fish and marine mammals continues to present a public health concern in Canada and elsewhere. However, fish and marine mammals are key diet items contributing to food security for some Indigenous populations in Canada. Mercury (Hg) exposure is estimated assuming that 100% of Hg is methylated, that 100% will be absorbed by the consumer and that cooking does not affect MeHg concentrations. Some of these assumptions do not correspond to our current state of knowledge. The aim of this study was to assess the impact of additional variables on Hg exposure equation using probabilistic risk analysis. New variables tested were (1) the proportion of methylated Hg compared to total Hg (pMeHg, %), (2) the relative absorption factor (RAF, %) expressed as bioaccessibility and (3) the mass loss factor (MLF, unitless) that represents the loss of moisture during cooking, known to increase MeHg concentration in fish and mammals. For the new variables, data from literature were used in order to set point estimate values that were further used in the probabilistic risk analysis. Modelling results for both fish and marine mammals indicate that adding these new variables significantly influenced estimates of MeHg exposure (Mood’s median test, p < 0.05). This study highlights that the evaluation of exposure to MeHg is sensitive to pMeHg, RAF and MLF, and the inclusion of these variables in risk assessment should be considered with care. Further research is needed to provide better food-dependent, population-specific estimates of RAF and MLF before formal inclusion in exposure estimates.