Largest Total Effect Research Articles

Nursing Work Engagement, Professional Quality of Life, and Intent to Leave: A Structural Equation Modeling Pathway Analysis.

Work engagement, professional quality of life (ProQOL), and intent to leave (ITL) significantly impact organizational behaviors and outcomes. Understanding the complex interrelationships among nurse work engagement, ProQOL, and ITL is essential for improving nurse retention, job satisfaction, and patient outcomes. In previous investigations, work engagement, ProQOL, and ITL relationships have primarily been analyzed individually. A more integrated approach is needed to gain a comprehensive understanding of these factors in the nursing profession. This study was designed to evaluate the interrelationships among work engagement, ProQOL (compassion satisfaction [CS], burnout, and secondary traumatic stress [STS]), and ITL in nurses using structural equation modeling path analysis. This was a quantitative descriptive study. Data were collected from registered nurses in the United States (n = 900) using the Utrecht Work Engagement Scale, the ProQOL-5 (CS, burnout, and STS), and a demographics datasheet (including a one-item ITL question). The proposed theoretical model, incorporating major constructs, was tested using structural equation modeling. Level of work engagement in nurses impacts ITL through ProQOL. Among the mediating variables, burnout (0.31) had the largest total effect on ITL, followed by STS (0.12) and CS (-0.12). Burnout and STS were found to correlate with ITL directly, whereas CS was found to correlate with ITL indirectly. Promoting work engagement, addressing burnout and STS, and fostering CS can positively influence nurse retention and job satisfaction, ultimately improving patient care quality. Healthcare leaders and policymakers should implement strategies to enhance nurse engagement, reduce burnout, and cultivate compassion satisfaction to increase nurse retention and improve organizational outcomes.

Contributions of soil organic carbon-induced root- and soil properties complexity to water flow in eastern China

Water flow within the soils affects the efficiency of materials transfer mediated by water. Soil organic carbon (SOC) as an important role in active water flow events can drive the complexity of root-soil synthesis by improving root and soil properties. However, contributions of SOC-induced root- and soil properties complexity to water flow are not well understood. In this study, dye tracing experiments at the three forest stands (oak, pine, and bamboo forests) were conducted to explore water flow patterns, i.e., preferential flow paths (PFP), stream buffer zones (SBZ), and water flow zones (WFZ). X-ray microtomography (CT) scanning was performed to reconstruct the root architecture. The partial least squares path model was applied to quantitatively explore the effects of root- and soil properties on water flow. The results showed that the index of water flow connectivity (IWFC) in the PFP and WFZ patterns decreased with increasing soil depth, while IWFC in the SBZ pattern increased at first and then decreased. In the PFP pattern, soil physical properties had the larger total effects (TE = 0.624) on IWFC change compared with root properties (TE = 0.257). In the SBZ pattern, the total effects of root properties controlling IWFC change (TE = 0.510) were greater than soil physical properties (TE = −0.386). Both of them can equally affect the IWFC in the WFZ pattern. In conclusion, the influences of SOC by driving the changes of soil properties on gravity-driven convective flow process were dramatically stronger than root properties, while SOC could primarily drive the changes of root properties and thereby affect capillary-driven convective flow process. The present results can provide a scientific basis for sustainable forestry management and also a better understanding of the forestry hydrology.

Characterizing the regional distribution, interaction with microorganisms, and sources of dissolved organic matter for summer rainfall: Insights from spectroscopy, community structure, and back-trajectory analyses

Dissolved organic matter (DOM) in rainfall participates in many biogeochemical cycles in aquatic environments and affects biological activities in water bodies. Revealing the characteristics of rainfall DOM could broaden our understanding of the carbon cycle. Therefore, the distribution characteristics and response mechanisms of DOM to microorganisms were investigated in different regions of Hebei. The results indicated that the water quality of the northern region was worse than that of the middle and southern regions. The two protein like components (C1, C2) and one humic like component (C3) were obtained; at high molecular weight (MW), the fluorescence intensity is high in the northern region (0.03 ± 0.02 R.U.), while at low MW, the fluorescence intensity is highest in the southern region (0.50 ± 0.18 R.U.). Furthermore, C2 is significantly positively correlated with C1 (P < 0.01), while C2 is significantly negatively correlated with C3 (P < 0.05) was observed. The spectral index results indicated that rainfall DOM exhibited low humification and highly autochthonous characteristics. The southern region obtained higher richness and diversity of microbial species than northern region (P < 0.05). The community exhibits significant spatiotemporal differences, and the Acinetobacter, Enterobacter, and Massilia, were dominant genus. Redundancy and network analyses showed that the effects of C1, C2, and nitrate on microorganisms increased with decreasing MW, while low MW exhibited a more complex network between DOM and microorganisms than high MW. Meanwhile, C1, C2 had a large total effect on β-diversity and function through structural equation modeling. The backward trajectory model indicates that the sources of air masses are from the northwest, local area, and sea in the northern, middle, and southern regions, respectively. This study broadened the understanding of the composition of summer rainfall DOM and its interactions with microorganisms during rainfall.

Effect and Mechanism of Root Characteristics of Different Rice Varieties on Methane Emissions

Methane (CH4), which is an important component of the greenhouse gases from paddy ecosystems, is a major contributor to climate change. CH4 emissions from paddy ecosystems are closely related to the rice root system; however, how the rice root system affects CH4 emissions remains unclear. We conducted a field experiment in 2023 at the Heping Irrigation District Rice Irrigation Experiment Station in Qing’an County, Heilongjiang Province. The field experiment used five local rice varieties with similar fertility periods to observe rice root morphology and physiology indexes, CH4 emission fluxes, and cumulative CH4 emissions. A structural equation model (SEM) was established to investigate the effects of root characteristics on the CH4 emissions from rice and understand the potential mechanisms of these effects. The results showed that the seasonal patterns of CH4 emission fluxes were similar in different rice varieties, and that, during the tillering to heading–flowering stages, the cumulative CH4 emissions accounted for 89.8–92.6% of the total cumulative CH4 emissions of rice. Significant negative correlations were observed between CH4 emission fluxes and root volume, root dry weight, root oxidation activity (ROA), and root radial oxygen loss (ROL) (r = −0.839, −0.885, −0.401 and −0.934, p &lt; 0.05), while there were significant positive correlations between root diameter; malic acid, citric acid, and succinic acid contents; and CH4 emission fluxes (r = 0.407, 0.753, 0.797, and 0.685, p &lt; 0.05). The SEM showed that CH4 emission fluxes were directly influenced by ROL and organic acid contents, while the other root indicators had indirect effects by modulating ROL and organic acid contents. ROL and root volume had the largest total effect, indicating that ROL and root volume were the most significant root physiological and morphological indicators affecting CH4 emission fluxes. This study provides theoretical support and reference data for achieving sustainable agricultural development in the black soil region of Northeast China.

Leadership effectiveness through coaching: Authentic and change-oriented leadership.

There has been an increasing shift towards individually owned leader development programs within organizations. Whilst leadership coaching is one of these and is gaining in popularity, the mechanisms of its effect remain poorly understood. We develop and investigate a model in which leadership coaching enhances leader effectiveness through coaching's positive effect on authentic and change-oriented leadership behaviours as well as self-efficacy. To assess the model, multi-source data were collected for organizational leaders (N = 70) pre- and post-coaching. To investigate mechanisms of coaching's effect, relations between latent change scores were assessed in structural equation modelling using partial least squares indicating that after accounting for base-line scores, coaching-related increases in authentic leadership behaviour has the largest total effect on leadership effectiveness.

Research on process safety of offshore wind turbines installation: A theoretical model and empirical evidence

As the world energy problem becomes more and more prominent, offshore wind farms have made remarkable progress in the last few years. With the advent of the rush to install offshore wind turbines around the world, offshore wind turbine (OWT) installation accidents have gradually increased. The process safety associated with offshore wind turbine installations has been a growing concern in offshore wind industry. To address this issue, this study aims to identify the factors affecting offshore wind turbine installation process safety, and to evaluate the correlations among these factors. The study involved an investigation into the causes and procedures of accidents that occurred during offshore wind turbine installation, leading to the development of customized safety factors. A questionnaire survey was developed and administered by a team of offshore wind industry professionals, including scholars, managers, and workers, and the data collected was analyzed using a theoretical model based on structural equation modeling. The results show that environment and weather condition, organization and management, and OWT installation technology have a significant impact on OWT installation technology. Furthermore, OWT installation technology has the largest total effect on the process safety of OWT installation.

Soil Microbial Community in Relation to Soil Organic Carbon and Labile Soil Organic Carbon Fractions under Detritus Treatments in a Subtropical Karst Region during the Rainy and Dry Seasons

Climate and detritus influence soil organic carbon (SOC) and labile SOC fractions by affecting soil microbial communities. However, it is not clear how, or to what extent, different detritus treatments affect soil microbial communities and SOC content in karst landscapes during different seasons. Plots in a karst landscape were treated with different detritus input regimes (control, no litter, no roots, no litter or roots, and double litter), and samples were collected during the dry and rainy seasons. We used Illumina sequencing of 16S rRNA to examine shifts in the diversity and composition of the associated soil microbial communities. Additionally, labile SOC fractions, including dissolved organic carbon (DOC) and microbial biomass carbon (MBC), along with soil physicochemical properties and C-degrading enzyme activities, were analyzed. The results revealed that the responses of soil properties and labile SOC fractions to detritus treatments were more pronounced during the rainy season than during the dry season, which mainly reflected that the levels of available potassium (AK), DOC, and MBC were significantly increased during the rainy season. Moreover, SOC and total nitrogen (TN) demonstrated significant changes with the double litter (DL) treatment during the rainy season. The responses of soil microbial communities to detritus treatments varied with the season, as reflected primarily in changes in the relative abundance of Ascomycota, unclassified_K_fungi, Proteobacteria, and Actinobacteriota. Climate, detritus treatments, and their interactions had significant effects on the species richness of soil bacterial communities, but did not influence fungal community diversity. Furthermore, structural equation modeling (SEM) revealed that the soil bacterial composition had the largest total effects on SOC, DOC, and MBC. In addition to directly influencing SOC, DOC, and MBC, soil properties (TN, AK, and pH) indirectly affected SOC, DOC, and MBC by altering C-degrading enzyme activity and the microbial community. We conclude that detritus treatments affect the soil microbial community and labile carbon fractions during both the rainy and dry seasons. Relationships among SOC, labile SOC fractions, enzyme activities, microbial communities, and function differed between seasons and among treatment types. This research advances our knowledge of how variation in detritus treatments affects biogeochemical cycling in karst soils during the rainy and dry seasons.

Characteristics and factors influencing soil organic carbon composition by vegetation type in spoil heaps.

The variation of organic carbon content in spoil heaps is closely related to improving soil structure, maintaining soil fertility, and regulating soil carbon cycling balance. Analyzing the soil organic carbon content and related driving factors during the natural vegetation restoration process of spoil heaps is of great significance for promoting the accumulation of soil organic carbon in the spoil heaps. we selected spoil heaps with the same number of years of restoration to research the variations in soil organic carbon components under different vegetation types (grassland: GL, shrubland: SL, secondary forest: SF) and compared the results with those on bare land (BL). Our results showed that vegetation type and soil depth significantly affect the content of soil organic carbon components. There was no difference in soil organic carbon components between SF and SL, but both were considerably superior to GL and BL (p<0.05), and the particulate organic carbon (POC) and light fraction organic carbon (LFOC) contents of SL were the highest. A significant positive linear correlation existed between SOC and active organic carbon components. Pearson's correlation and redundancy analysis showed that the available potassium (AK) and total nitrogen (TN) contents and gravel content (GC) in the BL soil significantly impacted soil organic carbon. When vegetation is present, TN, total phosphorus (TP), and Fine root biomass (FRB) significantly affect soil organic carbon. Structural equation modelling (SEM) shows that AK and soil moisture content (SMC) directly affect the organic carbon composition content of BL, When there is vegetation cover, fine root biomass (FRB) had the largest total effect in the SEM. Soil bulk density (BD) has a negative impact on soil organic carbon, especially in the presence of vegetation. These findings suggest that vegetation restoration can significantly increase soil organic carbon content, FRB, AK, and TN play important roles in enhancing soil organic carbon. Supplementation with nitrogen and potassium should be considered in the bare land stage, and shrubs nitrogen-fixing functions and well-developed roots are more beneficial for the accumulation of soil organic carbon.

Predictors of post-stroke depression: the perspective from the social convoy model.

Post-stroke depression (PSD) as one of the most common neuropsychiatric disorders after a stroke and is caused by many factors. However, the relationships among different factors and their potential contributions to PSD remain unclear. Two hundred and seventy-six patients were recruited into this study. The general information questionnaire, the Patient Health Questionnaire-9, the Perceived Social Support Scale, the Family Assessment Device, the General Well-Being Scale, the Barthel Index, and the modified Rankin Scale were used to assess the condition of patients. Subsequently, we identify the main causes associated with the PSD and then performed a path analysis to clarify the direct, indirect and total effects among the variables. We found that age, stroke with coronary heart disease, neurological function, family function, social support, and general well-being had a significant impact on PSD (P < 0.05). Of these, neurological function had the largest total effect on PSD (β = 0.451), social support contributed the most as a direct effect (β = -0.306), and family function showed the largest indirect effect (β = -0.264). Individual, disease, and social-psychological factors all contributed to the development of PSD. We should pay more attention to comprehensive assessment, especially for those with poor neurological function, and lacking family or social support. In addition, it would be preferable to provide them with necessary support and care strategies to reduce the incidence of PSD.

Micronutrient Powders Feeding Behaviors of Baby Caregivers in Remote Rural Areas of Sichuan Province: A Study Based on the Theory of Reasoned Action

To explore the status quo and influencing factors of feeding behaviors of micronutrient powders (MNP), or yingyangbao in Pinyin, the Chinese Romanization system, of baby caregivers in remote rural areas of Sichuan Province. In 2019, caregivers of babies aged 6 to 24 months from 6 counties of Sichuan Province were selected as the respondents of the survey through a multistage cluster random sampling method. Data concerning the baby caregivers' attitude of behavior, subjective norms, behavioral intention, and feeding behaviors about MNP feeding were collected with a questionnaire through a structured interview. Based on the theory of reasoned action, a structural equation model was constructed to explore the influencing factors of feeding behaviors. A total of 1002 valid samples were included in the study. The effective feeding rate of MNP among the baby caregivers was 55.49%. The results of model analysis suggested that attitude of behavior ( β direct=0.212, 95% CI: 0.105-0.327), subjective norm ( β direct=0.123, 95% CI: 0.016-0.228), and behavioral intention ( β direct=0.162, 95% CI: 0.093-0.224) could have a significant direct impact on MNP feeding behaviors. Behavior attitude ( β indirect=0.044, 95% CI: 0.023-0.073) and subjective norms ( β indirect=0.018, 95% CI: 0.001-0.040) could have a significant indirect impact on MNP feeding behaviors through the intermediary of behavioral intention. Among the three theoretical elements, attitude of behavior had the largest total effect on the feeding behavior ( β total=0.256, 95% CI: 0.148-0.366). The effective feeding rate of MNP among baby caregivers in remote rural areas of Sichuan Province is low. The attitude of behavior and subjective norms of caregivers may have a direct impact on their feeding behavior, and both attitude of behavior and subjective norms can have an indirect impact on the feeding behavior through the intermediary of behavioral intention. The influence of attitude of behavior attitude on feeding behavior is greater than that of subjective norms. Future intervention plans for promoting effective MNP feeding should incorporate health education for baby caregivers and their important social relations. Thus, baby caregivers' attitude and willingness for MNP feeding will be strengthened and the effective feeding rate of MNP will be improved accordingly.

Path Analysis of the Main Control Factors of Transpiration in Greenhouse, Drip-Irrigated Grapes in Cold Areas of Northeast China

To investigate the characteristics of grape transpiration water consumption and its environmental coupling mechanism in a greenhouse growing environment in cold areas of Northeast China, the dynamic monitoring of greenhouse grape sap flow and microenvironmental factors in a greenhouse was carried out for two years. Correlation analysis and path analysis were used to study the characteristics of grape transpiration environmental factors at different temporal scales (instantaneous, daily, and growth period) and the influence mechanisms on greenhouse grape transpiration. The results of correlation analysis by growth period showed that, on the instantaneous scale, the correlation between each meteorological factor and grape transpiration reached a significant level (coefficient of determination R2 ranged from 0.25 to 0.84). On the daily scale, the correlation of solar radiation (Rs) was the best except for the new growth period (R2 ranged from 0.49 to 0.89). The results of the split-fertility path analysis showed that the total effects of Rs on instantaneous transpiration were the largest at all stages of fertility, with decision coefficients (R) ranging from 0.69 to 0.90. On the daily scale, the total and direct effects of Rs on daily transpiration were the largest (R ranged from 0.70 to 0.94), except for the new growth period. The results of the whole growth period path analysis showed that Rs had the greatest effect on instantaneous transpiration, with R of 0.86. On the daily scale, Rs was also the most influential factor in grape transpiration, with R of 0.81. On the growth period scale, only air temperature (Ta) and leaf area index (LAI) were significantly correlated with transpiration (p &lt; 0.05), and Rs had the largest total effect on transpiration with R of 0.68. To sum up, on each time scale, Rs was always the most important factor influencing grape transpiration. However, as the time scale increased, the effects of LAI and soil water content (SW) on transpiration increased while the effects of Rs, Ta, RH, and VPD on transpiration gradually decreased.

Water use efficiency control for a maize field under mulched drip irrigation

Agricultural ecosystem water use efficiency (WUE) is an important indicator reflecting carbon-water coupling, but its control mechanisms in managed fields remain unclear. In order to reveal the influencing factors of WUE in the agricultural field under mulched drip irrigation (DM), we carried out the 8-year continuous observations in a maize field from Northwestern China. The structural equation model, relative importance analysis and principal component analysis were used to quantify the regulation effects of environmental and biological factors on WUE at different time scales, in different growth stages and under different hydrothermal conditions. The results showed that annual WUE varied between 2.18 g C Kg−1 H2O and 3.60 g C Kg−1 H2O, with a multi-year mean of 2.91 g C Kg−1 H2O. The total effects of air temperature on the daily WUE in the whole growth period, the vegetative growth stage, the warm and dry years, the cold and wet years, and the warm and wet years were the largest, with values of 0.61, 0.80, 0.70, 0.70 and 0.91 respectively. However, vapor pressure deficit and net radiation had the largest total effect in the cold and dry years (−0.63) and the reproductive growth stage (−0.49), respectively. Leaf biomass played a leading role in regulating the daily and interannual WUE, and the relative importance of leaf biomass to WUE in the vegetative growth stage was up to 75 %. In the warm and wet years, the relative importance of root biomass to WUE was 33 %, slightly higher than that of leaf biomass (31 %). At the same time, we found that Ta has the potential to increase WUE under future climate warming. Our results improve the understanding of carbon-water coupling mechanisms and provide important enlightenment on how crop ecosystems should adapt to future climate change.

Construction and validation of a revised satisfaction index model for the Chinese urban and rural resident-based basic medical insurance scheme

BackgroundQuality is the most important factor in satisfaction. However, the existing satisfaction index model of urban and rural resident-based basic medical insurance scheme (SIM_URRBMI) lacks the segmentation of perceived quality elements, it couldn’t provide a reference for quality improvement and satisfaction promotion. This study aims to construct a revised SIM_URRBMI that can accurately and detailly measure perceived quality and provide feasible and scientific suggestions for improving the satisfaction of urban and rural residents' basic medical insurance scheme (URRBMI) in China.MethodsBased on the theoretical framework of the American Customer Satisfaction Index, the elements of perceived quality were refined through literature review and expert consultation, and a pool of alternative measurement variables was formed. A three-stage randomized stratified cluster sampling was adopted. The main decision makers of URRBMI in the families of primary school students in 8 primary schools in Changsha were selected. Both the classic test theory and the item response theory were used for measurement variables selection. The reliability and validity of the model were tested by partial least squares (PLS)-related methods.ResultsA total of 1909 respondents who had URRBMI for their children were investigated. The SIM_URRBMI1.0 consists of 11 latent variables and 28 measurement variables with good reliability and validity. Among the three explanatory variables of public satisfaction, perceived quality had the largest total effect (path coefficient) (0.737). The variable with the greatest effect among the five first-order latent variables on perceived quality was the quality of the medical insurance policy (0.472).ConclusionsThe SIM_URRBMI1.0 consists of 28 measurement variables and 11 latent variables. It is a reliable, valid, and standard satisfaction measurement tool for URRBMI with good prediction ability for public satisfaction. In addition, the model provides an accurate evaluation of the perceived quality, which will greatly help with performance improvement diagnosis. The most critical aspects of satisfaction improvement are optimizing the scope and proportion of reimbursement as well as setting appropriate level of deductible and capitation of URRBMI.

Depression in healthcare workers: Results from the nationwide AMADEUS survey

BackgroundThere is now a wealth of evidence showing that work is a major determinant of physical and mental health. Recent studies have suggested increased rates of depression in healthcare workers (HCWs) in the context of the Covid-19 pandemic, with direct impact on care quality and productivity. AimTo determine the rate of clinical depression in a national sample of HCWs in France during the post-Covid-19 area and to identify related factors (professional, individual and health-related risk behaviors) using a structural equation modeling analysis. MethodA survey comprising a number of standardized scales was sent to public and private national healthcare facilities through the mail or disseminated through emails from professional associations and social networks. Results10,325 participants were recruited; 3122 (30.2%, 95% confidence interval [29.4–31.1]) met likely diagnostic criteria for clinical depression. Professional factors had the largest total effect (β = 0.57) (burn-out: β = 0.74, sustained bullying at the workplace β = 0.48 and decision-making latitude β = −0.47), followed by individual factors (β = 0.30) (the main individual factor was recurrent major depression, path coefficient = 0.67).Professional factors had both a direct (path coefficient = 0.38) and indirect (through health risk behaviors, path coefficient = 0.19) effect on depression. Individual factors had a direct (path coefficient 0.21) and indirect (through health risk behaviors (path coefficient = 0.09) effect on depression. Health risk behaviors had a direct effect on depression (path coefficient = 0.31). InterpretationThese results provide potential explanations for the likely causes of poor psychological health among HCWs. We propose several potential interventions related to professional factors and health risk behaviors. Our results suggest that improving organizational issues, reducing exposure to potentially morally injurious events, promoting brief naps at work and provision of evidence-based prevention approaches have been reported to be helpful in supporting the mental health of hospital staff (not only relaxation or stress management but training in leadership aspects, increasing the knowledge and practice of giving efficient performance feedback, reducing conflicting demands and peer support programs such as Trauma Risk Management. Our data suggest that developing caregivers reported experience and outcome measures (CREMs/CROMs) would be helpful to monitor work environment and its effect on depression in healthcare workers.

Exploring structural relations among computer self-efficacy, perceived immersion, and intention to use virtual reality training systems.

The use of virtual reality (VR) training systems for education has grown in popularity in recent years. Scholars have reported that self-efficacy and interactivity are important predictors of learning outcomes in virtual learning environments, but little empirical research has been conducted to explain how computer self-efficacy (as a subcategory of self-efficacy) and perceived immersion (as a correlate of interactivity) are connected to the intention to use VR training systems. The present study aims to determine which factors significantly influence behavioral intention when students are exposed to VR training systems via an updated technology acceptance frame by incorporating the constructs of computer self-efficacy and perceived immersion simultaneously. We developed a VR training system regarding circuit connection and a reliable and validated instrument including 9 subscales. The sample data were collected from 124 junior middle school students and 210 senior high school students in two schools located in western China. The samples were further processed into a structural equation model with path analysis and cohort analysis. The results showed that the intention to use VR training systems was indirectly influenced by computer self-efficacy but directly influenced by perceived immersion (β = 0.451). However, perceived immersion seemed to be influenced mostly by learner interaction (β = 0.332). Among external variables, learner interaction (β = 0.149) had the largest total effect on use intention, followed by facilitating conditions (β = 0.138), computer self-efficacy (β = 0.104), experimental fidelity (β = 0.083), and subjective norms (β = 0.077). The moderating roles of gender differences, grade level, and previous experience in structural relations were also identified. The findings of the present study highlight the ways in which factors and associations are considered in the practical development of VR training systems.

Cost drivers associated with diffuse large B-cell lymphoma (DLBCL) in Japan: A structural equation model (SEM) analysis.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive non-Hodgkin’s lymphoma of increasing prevalence in Japan. However, patients with relapsed or refractory disease to first line treatment (rrDLBCL) have been found to shoulder greater economic burden and have poor survival with subsequent lines of therapy. The relative impact of individual patient attributes on total medical cost among patients with rrDLBCL receiving second or third line (2L/3L) therapy was assessed. Structural equation modelling was used to identify potential cost drivers of total medical costs incurred by treatment and procedures in a Japanese retrospective claims database. From the database, rrDLBCL patients on 2L or 3L of treatment were grouped into respective cohorts. The mean [median] (SD) total medical cost of care for the 2L cohort was 73,296.40 [58,223.11] (58,409.79) US dollars (USD) and 75,238.35 [60,477.31] (59,583.66) USD for the 3L cohort. The largest total effect on medical cost in both cohorts was length of hospital stay (LOS) (β: 0.750 [95%CI: 0.728, 0.772] vs β: 0.762 [95%CI: 0.729, 0.794]). Length of hospital stay and potential heart disease complications due to line of treatment were the primary drivers of total cost for patients who had received at least 2L or 3L therapy for rrDLBCL.

Research on Continuous Static Coverage of Multiple Heterogeneous Warning Vehicles Considering No-fly Areas

Through the analysis of the types of tasks and flight routes faced by the warning vehicle, this paper proposes the problem of continuous static coverage of the multi-heterogeneous warning vehicle (referred to as WV) considering No-fly areas to be solved. By analysing things like detection area, no-fly area, WV patrol strategy form, patrol strategy planning mechanism and detection capability of WV, based on the philosophy of model stratification and time segmentation, a multi-layer multi-stage patrol strategy planning method (referred to as MLMPSPM) for determining the patrol strategies of multiple heterogeneous warning vehicles (WVs) during multi-patrol cycles considering no-fly areas is proposed, including the process of determining the planning stage index. In detail, MLMPSPM mainly introduces the patrol strategy planning method of EF and ER . Whether EF or ER includes input section, planning section, stage warning effect of planning stage, and patrol strategy objective planning, etc. EU planning processes is the extension of EF and ER . In the experimental results section, the relevant experimental parameters are designed in detail, the experimental results show that MLMPSPM can not only determine the patrol strategies of all WVs throughout the alert process considering time-varying no-fly areas, but also achieve a large total warning effect.

Modeling the relationship between classroom emotions, motivation, and learner willingness to communicate in EFL: applying a holistic approach of positive psychology in SLA research

ABSTRACT This study utilises a holistic approach of positive psychology (PP) in the second language acquisition (SLA) domain to test a model of willingness to communicate in English language (L2WTC) among 328 Saudi learners. The model examines how potential connections among learners’ negative emotions (anxiety and boredom), positive emotions (enjoyment and grit), and motivation have a positive effect on learner L2WTC. Questionnaire data were analyzed using a partial least squares structural equation modelling (PLS-SEM) analysis to identify and verify direct, indirect, and total effects in the model. The final model adequately fit the data. All learner emotions except boredom significantly directly predicted L2WTC. The strongest direct predictors of L2WTC were motivation, followed by anxiety. Grit directly affected motivation, and enjoyment mediated the relationship between motivation and L2WTC. Significant negative direct paths were detected from anxiety to motivation, enjoyment, and grit, and indirect paths from anxiety to L2WTC were shown through the mediation of these variables. Anxiety had the largest total effect on L2WTC, followed by motivation. These findings support the feasibility of a holistic perspective of PP in the SLA by which positive and negative emotional/affective variables can inherently interact to account for L2WTC via classroom pedagogical interventions for emotion regulation.

The Relationships Amongst Pediatric Nurses' Work Environments, Work Attitudes, and Experiences of Burnout.

Background: Pediatric nurses care for some of the most vulnerable patients in our healthcare system. Research on health care provider organizational behavior shows that the quality of care nurses provide is directly related to their well-being, influenced by Burnout and job stress, in the workplace. However, most of the research conducted on nursing populations neglects to separately study nurses who care for children. In a resource limited system where health care provider well-being is recognized as a priority, it is important for administrators to understand the environmental and attitudinal work factors most influential to pediatric nurse work outcomes in order to target optimization strategies. The aim of the study was to identify which modifiable work environment factors, e.g., [Incivility, Perceived Organizational Support, Quality of Work-life] make the greatest contribution to the work outcome of Burnout (i.e., Personal Accomplishment, Emotional Exhaustion, Depersonalization) in pediatric nurses.Methods: A cross-sectional survey design was used at a large quaternary care pediatric hospital in Toronto, Canada. We administered a survey to a convenience sample of all registered nurses with >3 months experience in the Pediatric, Cardiac, and Neonatal Intensive Care Units from January 2021–March 2021. Path analysis was used to test our proposed model which was specified a priori based on a review of the literature.Results: 143 nurses completed the survey. Path analysis of the tested model resulted in good fit. Quality of Work-life had the largest direct effect on Work Engagement (β = 0.582, S.E. = 0.111, p < 0.001). Work Engagement had the largest direct effect on Personal Accomplishment (β = 0.68, S.E. = 0.53, p < 0.001). Quality of Work-life had the largest indirect effect on Personal Accomplishment (β = 0.4, S.E. = 0.65, p < 0.001), Emotional Exhaustion (β = −0.33, S.E. = 0.87, p < 0.001), and Depersonalization (β =−0.17, S.E. = 0.41, p = 0.006), respectively. Work Engagement had the largest total effect on Personal Accomplishment (β = 0.68, S.E. = 0.64, p < 0.001) and the third largest total effect on Emotional Exhaustion (β = −0.57, S.E. = 0.83, p < 0.001). Quality of Work-life had the second largest total effect on Work Engagement (β = 0.58, S.E. = 0.11, p < 0.001) indicating that Quality of Work-life is mediated through Work Engagement for its effect on Burnout.Conclusions: Our results indicate work environment and work attitude factors that can provide organizational leadership with a targeted focus to reduce pediatric critical care nurse Burnout, and thus improve provider well-being, in a resource limited system.

Factors influencing green ship recycling: A conceptual framework and modeling

It is an environmentally friendly and economical way to send end-of-life ships for dismantling and recycling by the shipowners. More and more countries expressed concerns on the pollutants caused during ship dismantling and proposed green ship recycling concept. This study aims to propose the factors influencing green ship recycling and evaluate their interrelationships and effects on green ship recycling. By investigating the procedures and pollutants during ship dismantling, customized factors influencing green ship recycling were proposed. Questionnaire survey was designed and conducted by scholars, managers and workers in ship recycling field. The data were analyzed based on structure equation modeling with a proposed theoretical model. Overall, organization and management factor has the largest total effect on green ship recycling, followed by environmental protection facilities and plans factor and ship recycling technology and equipment factor. The environmental protection facilities and plans factor and ecological index factor are the direct contributors of green ship recycling. The theoretical implication of this study is discussed, as well as the managerial implication which could be beneficial to ship recycling companies and policy makers.