Low Resilience Research Articles

정신건강 전문가의 감정노동이 소진에 미치는 영향

In South Korea, recent incidents, such as the murder of a mentally ill person and a rampage involving a weapon, have highlighted the national responsibility for mental health service. The purpose of this study is to examine the relationship between levels of emotional labor caused by exposure to emotional labor by mental health professionals in the process of performing their work, and to verify the moderating effect of resilience in this relationship. The main findings were as follows. First, It was confirmed that higher levels of emotional labor, longer work experience, higher academic backgrounds among mental health professionals, and lower salaries are associated with increased burnout. Second, resilience moderates on the level of emotional labor and exhaustion. In groups with high resilience, there is little difference in burnout levels depending on the level of emotional labor. However, among individuals with low resilience, burnout tends to increase as the level of emotional labor increases. Based on the results of these studies, practical measures were presented to prevent emotional labor and burnout in mental health professionals.

A STUDY ON PERFORMANCE OF POLYPROPYLENE CARPETS PRODUCED WITH DIFFERENT FILAMENT FINENESS AND SLIP ADDITIVE RATIOS UNDER STATIC LOADING

Polypropylene, which is one of the most used polymers in machine carpet production as pile yarn, has some disadvantages need to be developed, such as lower resilience, flattening, matting etc. For this reason, there are so many studies in order to improve the inferior properties of polypropylene in carpet industry. In this study, eight carpet samples were produced by polypropylene BCF yarns with two filament fineness (3.7 and 9.5 dpf) and four ratios of slip additive (0 wt%, 0.5 wt%, 1 wt%, 2 wt%). In order to determine the effects of different filament fineness and additive percentage on thickness loss and resilience, carpet samples were exposed to short-term static loading test. According to the results, samples with 9.5 dpf filament fineness had lower thickness loss values compared to those of samples with 3.7 dpf filament fineness. Besides, the resilience behaviours of samples with 9.5 dpf filament fineness were also obtained to be better than samples with 3.7 dpf filament fineness. In consideration with slip additive percentages, although a trend was not observed between the increased additive ratio and mechanical responses of carpets, a difference was obtained between pure and 2 wt% additive blended samples. The blended samples with 2 wt% additive had shown lower thickness loss and higher resilience compared to neat samples.

Self-Rated Effectiveness of Ayahuasca and Breathwork on Well-Being, Psychological Resilience, Self-Compassion, and Personality: An Observational Comparison Study

Background: In recent years, there has been a growing interest in the therapeutic potential of classical psychedelics like ayahuasca for mental health improvement. Naturalistic studies at ayahuasca retreats have shown (short-term) improvements in mental well-being but understanding the psychological mechanisms is crucial. We are interested in psychological processes such as resilience, self-compassion, and personality traits. Additionally, it is unclear whether changes are solely due to ayahuasca or influenced by the social setting. To address this, a control group participating in a breathwork session, similar to ayahuasca retreats, was included. Methods: In this observational study, individuals who attended an ayahuasca retreat (n = 69) and individuals who participated in a breathwork session (n = 30) completed an online survey one week before (baseline) and one, six, and twelve weeks after they entered the retreat/session. The survey included a series of questionnaires, i.e., the World Health Organisation-Five Well-Being Index, 14-item Resilience Scale, Self-Compassion Scale–Short Form, and Big Five Inventory-10. A linear mixed model (LMM) was used to analyze the outcome data. Results: It was shown that well-being, resilience, and self-compassion increased and remained stable over 12 weeks compared to baseline, regardless of group (ayahuasca or breathwork). Older participants generally reported higher resilience and self-compassion. Self-compassion was also higher in the ayahuasca group overall. Neuroticism decreased in both groups, with lower scores in the ayahuasca group. Agreeableness increased over time, also not influenced by group membership, while there were no changes in extraversion, conscientiousness, or openness. Discussion: Both interventions improved well-being, aligning with prior research. Importantly, this study unveils a novel finding: both interventions enhance resilience and self-compassion for up to three months, offering promise for conditions marked by low well-being, resilience, and self-compassion like depression and anxiety-related disorders. While acknowledging its limitations (e.g., self-selected sample, no specific information of the ayahuasca brew or the breathwork technique), it emphasizes the need for controlled studies with control groups, attention to social contexts in research on these interventions, and to assess other variables like depth of altered states of consciousness that might explain improvement in psychological processes and wellbeing.

MENTAL HEALTH AND RESILIENCE AMONG PAKISTANI WOMEN SUFFERING FROM POLYCYSTIC OVARY SYNDROME

Background: Polycystic Ovary Syndrome (PCOS) is associated with multiple mental health issues, however resilience can work as a buffer against mental illnesses. The objective of the present study was to investigate the relationship between mental health and resilience and to compare mental health and resilience between working and non-working women suffering from PCOS. Method: This cross-sectional comparative study was conducted in the gynaecological wards of government and private hospitals and clinics from January to June 2023. Two hundred women suffering from PCOS were selected through non-probability sampling. The data was collected through two reliable measures: the Mental Health Inventory 38-Urdu (MHI-38) and the Connor Davidson Resilience Scale-Urdu. Data was analyzed on SPSS-26 by means of Cronbach alpha reliability, Pearson correlation, Mean±SD, and t-tests. Results: Psychometric properties showed high reliability of the study scale for MHI 38-U (?=0.87) and for CDRS-U (?=0.82, p<0.001). There was a significantly positive correlation between mental health and resilience (r=0.85, p<0.001). Non-working women experience lower mental health (Mean±SD 85.37±9.91) than working women (Mean±SD 136.50±12.94), (p<0.001). Working women experience higher resilience (Mean±SD 65.06±8.71) than non-working women with PCOS (Mean±SD 47.55±12.17), (p<0.001). Conclusion: There was a significant positive relationship between mental health and resilience. Non-working women reported compromised mental health and low resilience compared to working women suffering from PCOS. Pak J Pysiol 2024;20(1):45-47

Spatial and Temporal Changes in Ecological Resilience in the Shanxi–Shaanxi–Inner Mongolia Energy Zone with Multi-Scenario Simulation

The energy-driven expansion of artificial surfaces has resulted in severe ecological problems. Scientific evaluation of regional ecological resilience under different scenarios is crucial for promoting ecological restoration. This study chose the Shanxi–Shaanxi–Inner Mongolia Energy Zone (SEZ) and modeled an ecological resilience evaluation based on resistance, adaptability, and recovery. Land-use change and ecological resilience from 1980 to 2020 were then analyzed. Moreover, the SEZ land-use patterns and ecological resilience in 2030 were simulated under business as usual (BAU), energy and mineral development (EMD), and ecological conservation and restoration (ECR) scenarios. The results showed that (1) the SEZ was dominated by cultivated land, grassland, and unused land. (2) Ecological resilience showed a changing trend of decreasing and then increasing, with high ecological resilience areas mainly located in the Yellow River Basin, whereas low ecological resilience areas spread outward from the central urban areas. (3) The ecological resilience level was the lowest under the EMD scenario and the highest under the ECR scenario. This study not only expands the analysis framework of ecological resilience research but also provides scientific support for ecological conservation in ecologically fragile areas with intensive human activity worldwide.

Resilience-aware MLOps for AI-based medical diagnostic system.

The healthcare sector demands a higher degree of responsibility, trustworthiness, and accountability when implementing Artificial Intelligence (AI) systems. Machine learning operations (MLOps) for AI-based medical diagnostic systems are primarily focused on aspects such as data quality and confidentiality, bias reduction, model deployment, performance monitoring, and continuous improvement. However, so far, MLOps techniques do not take into account the need to provide resilience to disturbances such as adversarial attacks, including fault injections, and drift, including out-of-distribution. This article is concerned with the MLOps methodology that incorporates the steps necessary to increase the resilience of an AI-based medical diagnostic system against various kinds of disruptive influences. Post-hoc resilience optimization, post-hoc predictive uncertainty calibration, uncertainty monitoring, and graceful degradation are incorporated as additional stages in MLOps. To optimize the resilience of the AI based medical diagnostic system, additional components in the form of adapters and meta-adapters are utilized. These components are fine-tuned during meta-training based on the results of adaptation to synthetic disturbances. Furthermore, an additional model is introduced for post-hoc calibration of predictive uncertainty. This model is trained using both in-distribution and out-of-distribution data to refine predictive confidence during the inference mode. The structure of resilience-aware MLOps for medical diagnostic systems has been proposed. Experimentally confirmed increase of robustness and speed of adaptation for medical image recognition system during several intervals of the system's life cycle due to the use of resilience optimization and uncertainty calibration stages. The experiments were performed on the DermaMNIST dataset, BloodMNIST and PathMNIST. ResNet-18 as a representative of convolutional networks and MedViT-T as a representative of visual transformers are considered. It is worth noting that transformers exhibited lower resilience than convolutional networks, although this observation may be attributed to potential imperfections in the architecture of adapters and meta-adapters. The main novelty of the suggested resilience-aware MLOps methodology and structure lie in the separating possibilities and activities on creating a basic model for normal operating conditions and ensuring its resilience and trustworthiness. This is significant for the medical applications as the developer of the basic model should devote more time to comprehending medical field and the diagnostic task at hand, rather than specializing in system resilience. Resilience optimization increases robustness to disturbances and speed of adaptation. Calibrated confidences ensure the recognition of a portion of unabsorbed disturbances to mitigate their impact, thereby enhancing trustworthiness.

Resilience Level and Associated Factors Among Medical Undergraduates in a Selected University in Sri Lanka

Medical undergraduates experience many challenges in their academic, social as well as financial aspects in present day circumstances. All these challenges make them vulnerable if they can’t withstand it. Resilience is the ability to withstand adversities an individual faces. If they lack resilience, they are likely to face many negative consequences. Objective of the study was to assess the resilience level and associated factors among medical undergraduates in a selected university in Sri Lanka. A descriptive cross-sectional study was conducted among all the medical undergraduates (n= 578) studying in the medical faculty during April to September 2023 in Wayamba medical faculty. Study instruments consist of the 14-Item Resilience Scale, to assess the level of resilience and a self-administered questionnaire to inquire the associated factors. The levels of resilience were expressed as percentages with 95% CI. Bivariate and multivariate logistic regression is used to assess the associated factors of low resilience. Probability < 0.05 was selected as the significance level. The results were expressed as odds ratios (OR) and 95% CI. The response rate was 85.3% (n= 492). Mean age was 22 years (SD =1.2) and majority were females (69.3%). Low, moderate, and high levels of resilience of medical undergraduates were 51% (n = 251), 30% (n = 148) and 18.9% (n =93) respectively. In each academic year, half of the undergraduates had low level of resilience. Male sex (AOR = 2.4; 95% CI =1.2 – 4.8), getting angry frequently (AOR = 3.0; 95% CI = 1.5 -6.0) and not engage in extracurricular activities (AOR = 2.2; 95% CI = 1.2 - 4.2) were significantly associated with low resilience level among medical undergraduates. Except the sex, other two are modifiable factors and need to take necessary interventions to rectify it. Recommend resilience enhancing interventions among medical undergraduates. Needs to explore the research area with qualitative studies to get highest yield.

Monitoring vegetation patterns and their drivers to infer resilience: Automated detection of vegetation and megaherbivores from drone imagery using deep learning

Ecological pattern theory has highlighted spatial vegetation patterns that can be used as indicators of ecosystem resilience. Combining this spatial pattern theory with aerial imagery from drones and automated image processing with deep learning methods, we show how monitoring of natural ecosystems can be enhanced through quantifying vegetation spatial patterns. We demonstrate this approach in a tropical seagrass ecosystem with a high abundance of turtles that generate vegetation patches when grazing. Past field observations suggest that patch size and density reflect the seagrass meadow resilience, but understanding the natural variation in vegetation patchiness is crucial. Employing the deep learning methods of semantic segmentation and object detection, we quantify vegetation patchiness metrics and turtle distribution across 12 ha of seagrass meadow in the years 2012 and 2022. The resulting output facilitates spatial and temporal comparisons, revealing areas of low resilience. In 2012, turtle grazing across the entire site yielded vegetation patch sizes averaging 2 ± 0.2 m2 (95% confidence interval). Reduced patch sizes of 0.24 ± 0.05 m2 and 0.67 ± 0.6 m2 at the reef edge and beach slope respectively, in conjunction with a reduced patch density, indicated lower resilience at the seagrass meadow edges. Analysis of the 2022 dataset indicates a general decrease in patch size over time, suggesting declining resilience. A retraining experiment of the semantic segmentation model was conducted where the initial model was retrained on the 2022 dataset and demonstrated the adaptability of the deep learning methods. Despite using different equipment, the model achieved high accuracy with only 5–10 additional training images. By providing the tools to conduct these analyses, we aim to stimulate the uptake of deep learning for enhancing the data obtained from aerial imagery to improve the monitoring and conservation of natural ecosystems.

Exploring the prevalence and predictors of low resilience and likely PTSD in residents of two provinces in Canada during the 2023 wildfires.

The recent wildfires in Canada serve as a stark example of the substantial and enduring harm they cause to the health of individuals and communities. Assessing the prevalence and correlates of Post-traumatic stress disorder (PTSD) and low resilience is valuable for policymakers in public health. The study aimed to assess the prevalence and predictors of low resilience and likely PTSD among subscribers of Text4Hope, an e-mental health program that delivered daily supportive messages to residents of Nova Scotia (NS) and Alberta(AB) during the recent wildfires. Data collection was through a self-administered online survey completed by residents of the affected regions of NS and AB from May 14 to June 23, 2023. Data were analyzed using Statistical Package for the Social Sciences. Out of 298 respondents, the prevalence of low resilience and likely PTSD in our sample were 52.0 and 39.3%, respectively. Unemployed respondents were about 3 times more likely to experience both low resilience and PTSD symptoms compared to those employed. Respondents with a history of mental health diagnosis were about 4 times more likely to experience likely PTSD compared to those with no history of mental health diagnosis. This study established that unemployment and a history of mental health diagnosis predicted likely PTSD, while unemployment was associated with low resilience during the wildfire. These findings offer insights for clinical interventions and the creation of psychosocial support programs for vulnerable populations.

Assessing topographic effects on forest responses to drought with multiple seasonal metrics from Sentinel-2

Topography determines run-off direction, redistributes groundwater, and affects land surface solar radiation loads and the associated evaporative forcing, consequently, topography can modulate the impact of drought and heat waves on ecosystems. This topographic modulation effect, which typically occurs at the local scale, is often overlooked when assessing ecosystem drought responses using moderate-to-coarse spatial resolution satellite observations, such as the Moderate-resolution Imaging Spectroradiometer (MODIS) imagery. Sentinel-2 and Landsat imagery with finer resolution are suitable for monitoring changes at the local scale, however, studies relying on single vegetation metrics may fail to get a holistic picture of vegetation drought responses, particularly for forests that have complex physiological mechanisms. Here, we performed a comprehensive assessment of the topographic effects on coniferous forest responses to the severe 2018 drought in Scandinavia, using 6 vegetation seasonal metrics during 2017–2021 from the Sentienl-2 High-Resolution Vegetation Phenology and Productivity (HR-VPP) products. We found significant differences (p < 0.05) between sunny and shady aspects, between higher and lower elevations, and between steep and gentle slopes, regarding the maximum impact time, forest drought resistance, and resilience. Specifically, the sunny aspects and steep slopes were related to higher risks of delayed impacts and low resistance and resilience, and elevation and slope were more powerful in regulating the phenology shift and greening rate loss. We also identified different sensitivity in greenness and productivity to topographic effect and greater sensitivity of spring phenology to topographic differences as compared to autumn phenology. The study demonstrates vegetation drought responses represented by multiple seasonal metrics, reveals the prevalent topographic effects at the local scale, and quantifies the magnitudes of the effects with regional statistics.

Genetic and Distribution Data of the Bramble Shark Echinorhinus brucus (Bonnaterre, 1788) and the Prickly Shark Echinorhinus cookei Pietschmann, 1928 to Better Reconstruct Their Conservation Status.

Elasmobranch species show low resilience in relation to anthropogenic stressors such as fishing efforts, loss of habitats, and climate change. In this sense, the elasmobranch populations appear to be at risk of extinction in many cases. Despite conservation researchers making efforts to implement knowledge, the information on the biology, reproduction, distribution, or genetic structure of some species is still scattered, often caused by the occurrence of species in inaccessible habitats. Echinorhinus brucus is a deep benthic shark evaluated as "Endangered" on which little information is available, particularly about its geographical range and genetic structure, while E. cookei is listed as "Data Deficient". Echinorhinus brucus belongs to the Echinorhinidae family, and its unique congeneric species is E. cookei. The main morphological diagnostic characteristic of both species is the presence of denticles with different shapes and patterns on the derma. In the present paper, mitochondrial COI and NADH2 sequences were retrieved from both E. brucus and E. cookei species, and analyses were conducted by applying different models of phylogenetic inference. Sequences of E. brucus captured in the Indian Ocean (IOS) did not cluster with the Atlantic E. brucus counterparts (AOS) but instead with E. cookei sequences; the different models showed an overlapping tree topology. Concurrently, a review of the historical and recent captures of the two species was carried out. The worldwide distribution of E. brucus excludes the Pacific Ocean area, where E. cookei occurs, and is characterised by presumably current local extinctions in the North Sea and the western Mediterranean Sea. The dataset describes two definite areas of significantly high abundance of E. brucus located in the Atlantic Ocean (Brazil) and the Indian Ocean (India). These areas suggest zones for conservation plans, especially considering the two lineages identified through molecular approaches.

Being the Mother of a Special Child: Resilience and Marital Adjustment in Mothers of Children with Autism Spectrum Disorder.

This study aims to examine the levels and the relationship between resilience and marital adjustment in mothers of a child diagnosed with autism spectrum disorder. Seventy mothers with a child diagnosed with autism spectrum disorder who have been followed up in the Child and Adolescent Psychiatry Outpatient Clinic of Bakırköy Training and Research Hospital for Psychiatry Neurology and Neurosurgery and 74 mothers with a typically developing child to form the control group were included in the study. The Childhood Autism Rating Scale was applied to assess the severity of autism symptoms in children. Sociodemographic form, Beck Depression Scale and Beck Anxiety Scale were applied. The Psychological Resilience Scale for Adults was used to assess resilience. The Marital Adjustment Scale was applied to evaluate the participants' marital adjustment. The level of resilience (P < .001) and marital adjustment (P = .002) in mothers of children with autism spectrum disorder were found to be lower when compared to mothers with a typically developing child. There is a negative correlation between the level of resilience and the severity of autism (P = .002) (r = -0.361). A positive correlation was found between marital adjustment and resilience (P < .001) (r = 0.465). High levels of depressive symptoms (P = .003), low marital adjustment (P = .003), and low educational level were found to be predictive of low resilience (P = .044). Taking advantage of the fact that resilience is a dynamic process, there is a need to develop strategies to increase resilience in mothers of children with autism spectrum disorder, which will also give rise to individual and marital well-being.

Resilience Improves Patient-Reported Outcomes After Orthopaedic Trauma.

To analyze the relationship between patient resilience and patient-reported outcomes after orthopaedic trauma. Retrospective analysis of prospectively collected data. Single Level 1 Trauma Center. Patients were selected based on completion of the Patient-Reported Outcomes Measurement Information System (PROMIS) and Brief Resilience Scale (BRS) surveys 6 months after undergoing operative fracture fixation following orthopaedic trauma. Patients were excluded if they did not complete all PROMIS and BRS surveys. Resilience, measured by the BRS, was analyzed for its effect on patient-reported outcomes, measured by PROMIS Global Physical Health, Physical Function, Pain Interference, Global Mental Health, Depression, and Anxiety. Variables collected were demographics (age, gender, race, body mass index), injury severity score, and postoperative complications (nonunion, infection). All variables were analyzed with univariate for effect on all PROMIS scores. Variables with significance were included in multivariate analysis. Patients were then separated into high resilience (BRS >4.3) and low resilience (BRS <3.0) groups for additional analysis. A total of 99 patients were included in the analysis. Most patients were male (53%) with an average age of 47 years. Postoperative BRS scores significantly correlated with PROMIS Global Physical Health, Pain Interference, Physical Function, Global Mental Health, Depression, and Anxiety ( P ≤ 0.001 for all scores) at 6 months after injury on both univariate and multivariate analyses. The high resilience group had significantly higher PROMIS Global Physical Health, Physical Function, and Global Mental Health scores and significantly lower PROMIS Pain Interference, Depression, and Anxiety scores ( P ≤ 0.001 for all scores). Resilience in orthopaedic trauma has a positive association with patient outcomes at 6 months postoperatively. Patients with higher resilience report higher scores in all PROMIS categories regardless of injury severity. Future studies directed at increasing resilience may improve outcomes in patients who experience orthopaedic trauma. Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Low Psychological Resilience Predict the Risk for Alcohol Use Disorder in General Population: National Mental Health Survey of Korea 2021

Low Psychological Resilience Predict the Risk for Alcohol Use Disorder in General Population: National Mental Health Survey of Korea 2021

TurboBlom: A light and resilient key predistribution scheme with application to Internet of Things.

In the Internet of Things (IoT), there are often devices that are computationally too constrained to establish a security key using traditional key distribution mechanisms such as those based on the Diffie-Hellman key exchange. To address this, current solution commonly rely on key predistribution schemes (KPSs). Among KPSs, the Blom scheme provably provides the highest resilience against node capture attacks. This, however, comes at high computational overhead, because the Blom scheme requires many multiplications over a large finite field. To overcome this computational overhead, we present TurboBlom, a novel amendment of the Blom scheme. TurboBlom circumvents the need for field multiplications by utilizing specialized generator matrices, such as random zero-one matrices. We demonstrate that, through this approach, TurboBlom can significantly reduce the computational overhead of the Blom scheme by orders of magnitude. In our next key finding, we demonstrate that TurboBlom offers a level of resilience against node capture that is virtually on par with the Blom scheme. Notably, we prove that the gap between the resilience of the two schemes is exponentially small. These features of TurboBlom (i.e., low computational overhead and high resilience) make it suitable for computationally constrained devices. Such devices exist in abundance in IoT, for example, as part of Low Power and Lossy Networks (LLNs). To demonstrate a sample application of TurboBlom, we show how to use it to enable sender authentication in the Routing Protocol for LLNs (RPL), a standard routing protocol for IoT.

A Novel Thermal Interface Material Composed of Vertically Aligned Boron Nitride and Graphite Films for Ultrahigh Through-Plane Thermal Conductivity.

The relentless drive toward miniaturization in microelectronic devices has sparked an urgent need for materials that offer both high thermal conductivity (TC) and excellent electrical insulation. Thermal interface materials (TIMs) possessing these dual attributes are highly sought after for modern electronics, but achieving such a combination has proven to be a formidable challenge. In this study, a cutting-edge solution is presented by developing boron nitride (BN) and graphite films layered silicone rubber composites with exceptional TC and electrical insulation properties. Through a carefully devised stacking-cutting method, the high orientation degree of both BN and graphite films is successfully preserved, resulting in an unprecedented through-plane TC of 23.7Wm-1K-1 and a remarkably low compressive modulus of 4.85MPa. Furthermore, the exceptional properties of composites, including low thermal resistance and high resilience rate, make them a reliable and durable option for various applications. Practical tests demonstrate their outstanding heat dissipation performance, significantly reducing CPU temperatures in a computer cooling system. This research work unveils the possible upper limit of TC in BN-based TIMs and paves the way for their large-scale practical implementation, particularly in the thermal management of next-generation electronic devices.

Hope and psychological resilience in primary caregivers of patients with a chronic mental illness followed in a community mental health center

PurposeThe aim of this study is to examine hope and psychological resilience in primary caregivers of patients with a chronic mental illness. Design and methodsThe descriptive study was conducted on 297 caregivers in community mental health centers in Turkey. Data were collected using the Introductory Information Form, Dispositional Hope Scale and the Resilience Scale for Adults. FindingsHope and psychological resilience of primary caregivers of patients with a chronic mental illness were moderate. To sociodemographic and caregiver characteristics; caregivers who are over 40 years old, lost his/her spouse, low education level, housewife or retired, unemployed, who evaluated their incomes low, mother, living in the same house with the patient, caring for ten years or more, caring for another patient and not getting help in care had lower hope and resilience levels. Compared to patients with a diagnosis of bipolar disorder, caregivers of patients with schizophrenia had lower hope and psychological resilience levels. ConclusionsPrimary caregivers of patients with a chronic mental illness should be supported in terms of hope and psychological resilience.

The Effect of Environmental Awareness on Work Engagement and Employment Resilience

A crucial aspect that employees must have is resilience as well as high work engagement. Employees who are actively involved and resilient in difficult situations at work will make higher contributions than employees with low resilience and engagement, who tend to be passive. Unfortunately, work engagement and resilience can also be influenced by environmental awareness. This study aims to see the influence of environmental awareness on work engagement and work resilience in employees, especially mining employees. The type of research used is quantitative research with a saturated sampling method. The population in this study amounted to 302 people. The subjects selected were mine employees—data analysis techniques using simple linear regression tests. The results showed that, individually and jointly, environmental awareness affected work engagement and work resilience in mining employees. The results of this study answer the assumption that workers experience a dilemma. Otherwise, environmental awareness still makes employees have high work engagement and resilience even though they work in mining companies.

A first characterization of the microbiota-resilience link in swine

BackgroundThe gut microbiome plays a crucial role in understanding complex biological mechanisms, including host resilience to stressors. Investigating the microbiota-resilience link in animals and plants holds relevance in addressing challenges like adaptation of agricultural species to a warming environment. This study aims to characterize the microbiota-resilience connection in swine. As resilience is not directly observable, we estimated it using four distinct indicators based on daily feed consumption variability, assuming animals with greater intake variation may face challenges in maintaining stable physiological status. These indicators were analyzed both as linear and categorical variables. In our first set of analyses, we explored the microbiota-resilience link using PERMANOVA, α-diversity analysis, and discriminant analysis. Additionally, we quantified the ratio of estimated microbiota variance to total phenotypic variance (microbiability). Finally, we conducted a Partial Least Squares-Discriminant Analysis (PLS-DA) to assess the classification performance of the microbiota with indicators expressed in classes.ResultsThis study offers four key insights. Firstly, among all indicators, two effectively captured resilience. Secondly, our analyses revealed robust relationship between microbial composition and resilience in terms of both composition and richness. We found decreased α-diversity in less-resilient animals, while specific amplicon sequence variants (ASVs) and KEGG pathways associated with inflammatory responses were negatively linked to resilience. Thirdly, considering resilience indicators in classes, we observed significant differences in microbial composition primarily in animals with lower resilience. Lastly, our study indicates that gut microbial composition can serve as a reliable biomarker for distinguishing individuals with lower resilience.ConclusionOur comprehensive analyses have highlighted the host-microbiota and resilience connection, contributing valuable insights to the existing scientific knowledge. The practical implications of PLS-DA and microbiability results are noteworthy. PLS-DA suggests that host-microbiota interactions could be utilized as biomarkers for monitoring resilience. Furthermore, the microbiability findings show that leveraging host-microbiota insights may improve the identification of resilient animals, supporting their adaptive capacity in response to changing environmental conditions. These practical implications offer promising avenues for enhancing animal well-being and adaptation strategies in the context of environmental challenges faced by livestock populations.7uyXcYriZkKxPgmfB9NKtxVideo

To what extent is the effect of sensory processing sensitivity on distress mediated by resilience? Putting the diathesis-stress model to the test in a sample of gifted adults

The purpose of this prospective study was to examine (a) whether Sensory Processing Sensitivity (SPS) measured at baseline (T0) predicts distress at one year follow-up (T1), and (b) whether and in what way resilience mediates the effect of SPS on distress. The study sample consisted of gifted adults. A total of 738 respondents participated in the study at T0 and T1 (mean age of 44.86; 63.4% female). Structural Equation Modeling and logistic regression analysis were conducted. A high level of SPS at T0 predicted psychological (anxiety and depression) and somatic (physical symptoms and fatigue) distress at T1. As far as indirect effects are concerned, results depended upon whether we looked at the negative or positive higher-order dimension of SPS. A higher score on negative SPS was associated with lower resilience which in turn led to more distress, indicating that low resilience increased the negative impact of negative SPS on distress. In contrast, a higher score on positive SPS was related to more resilience, resulting in less distress, suggesting that in this case resilience had a buffering effect. As resilience is a buffer between SPS and distress, follow-up research could focus on psychological interventions aimed at increasing resilience.