According to recent empirical research (Transparency International, 2013), nearly 15% of people worldwide admitted to having paid a bribe in an educational setting. Given the nature of corruption,...

The world is getting increasingly interconnected. For this reason, schools should apply strategies to develop students’ civic skills and global civic engagement. The purpose of this paper is to examine the influence of multicultural exposure, multicultural interaction, social media usage, and study abroad experience on global civic engagement. The correlational survey model was applied for the study. The participants were selected through cluster random sampling during the 2018-2019 academic year. This study was implemented with 425 high school students who attend (...) private schools. The authors used Global Citizenship Scale (Morais & Ogden, 2011) and Multicultural Experience Assessment (Aytug, Kern, & Dilchert, 2018). The findings showed that multicultural exposure, multicultural interaction, and social media usage were positively correlated to global civic engagement. In addition, multicultural exposure, multicultural interaction, social media usage, and study abroad experience significantly predicted global civic engagement. (shrink)

Opaque value chains as well as environmental, ethical and health issues and food scandals are decreasing consumer trust in conventional agriculture and the dominant food system. As a result, critical consumers are increasingly turning to community-supported agriculture (CSA) to reconnect with producers and food. CSA is often perceived as a more sustainable, localized mode of food production, providing transparent production or social interaction between consumers and producers. This enables consumers to observe where their food is coming from, which means CSA (...) is considered suitable for building trust in food (production). However, it remains unclear how exactly members’ trust in ‘their’ farmers is built. To determine the factors that predict members’ trust in CSA and its farmers, and the importance of these factors when compared to each other, we conducted a quantitative study among CSA members in Germany and applied a multiple regression model (n = 790). The analysis revealed that trust in CSA and its farmers is influenced by “reputation”, “supply of information”, “direct social interaction” and the “duration of CSA membership”. Other factors such as the “certification status of the CSA farm” and “attitudes toward organic certification” did not significantly predict trust. We conclude that producers’ willingness to be transparent already signals trustworthiness to CSA members and is more important to members than formal signals. Other actors within the food system could learn from CSA principles and foster a transition toward a more regionalized value-based food system to help restore agriculture’s integrity. (shrink)

Problematic smartphone use is an expanded public health heed that requires more study to clarify the influence elements of different populations. The aim of this study was to investigate the relationship between smartphone use, and sleep quality, self-perceived health, and exercise participation in university students. A total of 1,575 Taiwanese undergraduate students from 7 universities participated in the study. Three questionnaires were completed by the study individuals. The results show the overall PSU rate was 11.8%. Average smartphone users were more (...) likely to feel in good health, better sleep quality and less unsatisfactory exercise participation than those who were problematic smartphone users. Multiple logistic regression analysis indicated that PSU, low weekly exercise frequency, and poor sleep quality were significant indicators of poor self-perceived health. We concluded that both low physical activity and PSU did have negative impacts on self-perceived health and sleep quality for undergraduate students. (shrink)

Multiple goals balancing is an important but not yet fully validated dimension of complex problem solving (CPS). The present study used process data to explore how solvers clarify goals, set priorities, and balance conflicting goals. We extracted behavioral indicators of goal pursuit from the log data of 3,201 students on the third subtask of the “Ticket” task in the PISA 2012 CPS test. Cluster analysis was used to identify 10 groups that varied in goal pursuit behavior. Logistics and (...) least-squares regression analysis were used to explore how goal pursuit affected task scores and CPS proficiency. The results showed that competent solvers clarified goals and weighed priorities more effectively. They also made trade-offs between conflicting goals. The importance of theoretically-driven log data analysis and coping strategies in the face of multiple goals conflict scenarios was discussed. (shrink)

How to make use of the leaders’ psychological capital to improve the innovation behavior of employees is an important issue for the talent management of enterprises today, and it is also the goal that enterprises must pursue if they want to stand out in the fierce competition. Therefore, in this study, 154 enterprises in high-tech area were selected for questionnaire survey. The correlation between lead-member exchange (LMX) relationship (emotion, loyalty, contribution, professional respect), leaders' psychological capital (confidence, hope, optimism, tenacity), and (...) employees' innovation behaviors were analyzed by multivariate regression. Hierarchical regression method was used to examine the mediating effect of the LEX. It was found that confidence, toughness, and contribution were significantly positively correlated with employee innovation behavior (P<0.000). The positive correlation between hope, optimism, emotion, and loyalty with employees' innovation behavior was significant (P<0.05). Emotion, loyalty, and contribution had mediating effects on the leaders’ psychological capital and the innovation behavior of employees. In conclusion, the leaders’ psychological capital can have a significant positive effect on the innovation behavior of employees directly, and it can also have an indirect positive effect on the innovation behavior of employees by maintaining high quality LMX. (shrink)

This study aimed to investigate the serial-multiple mediation effect of professional identity, psychological capital, work-related stress, and work-related wellbeing among intensive care unit nurses in China. The cross-sectional survey was conducted from January 2017 to May 2017 in two Grade III A general hospitals in Jining, Shandong Province, China. Cluster sampling was used to recruit participants from the two hospitals. A total of 330 ICU nurses participated in the study. The nurses’ work stress scale, Chinese nurse’s professional identity scale, (...) the PsyCap questionnaire, and Chinese work-related wellbeing scale were used to collect the data. Descriptive analysis, independent-samples t-test, one-way analysis of variance, Pearson correlation analysis, linear regression analysis, and structural equation modeling were used to analyze the data. The average score for the work-related wellbeing of ICU nurses was 85.91 ± 13.94. Work-related stress, professional identity, and PsyCap correlated significantly with work-related wellbeing. The major predictors of work-related wellbeing were PsyCap, work-related stress, professional identity, and monthly salary. The serial-multiple mediation effects of professional identity and PsyCap in the relationship between work-related stress and work-related wellbeing were statistically significant. Positive professional identity and PsyCap were sequentially associated with decreased work-related stress, which in turn was related to increased work-related wellbeing among ICU nurses. Therefore, this study aims to explore the impact of ICU nurses’ work-related stress on work-related wellbeing, as well as the mediating effect of professional identity and PsyCap. It is hoped that hospital care managers will pay attention to the mental health of ICU nurses, increase their professional identity, and reduce work-related stress to improve the quality of the ICU nursing service and stabilize nursing work. (shrink)

With the widespread application of information technology and the continuous deepening of my country’s education informatization construction, the educational field has increasingly higher requirements for teachers’ informatization quality. The advancement of the process of education informatization depends to a large extent on the level of teachers’ own level of informatization and has gradually become an important indicator to measure the informatization of education. The main body of education and the decisive factor are teachers. The scientific and reasonable evaluation of informatization (...) education is an important content of today’s education informatization. This paper uses regression analysis to evaluate the teacher education information system and uses mathematical statistics to establish a linear regression model for the city and analyze and calculate it. Through the quantitative analysis of the evaluation index system of the education informatization level, the multiple linear regression analysis method was used to establish the linear regression mathematical model of the school education informatization level on each secondary index, and the influence of various indicators on the school education informatization level was analyzed to establish a scientific evaluation system to evaluate the literacy of teachers’ informatization education and to give suggestions for improving the level of school education informatization. The design of the evaluation system is more scientific and reasonable, the regression error is small, the results obtained are more accurate, and the impact of nonlinear errors is basically eliminated. (shrink)

AimThe aim of our study was to analyze physical activity levels, sitting time, physical fitness, and their relationship with depressive symptoms after home confinement in previously active older adults.MethodsThis cross-sectional study sample comprised 68 older adults from a community-based exercise program conducted in Porto, Portugal. After home confinement, participants were assessed in person for lower-body strength, cardiorespiratory fitness, agility/dynamic balance, handgrip strength, and anthropometry. Telephone interviews were performed to evaluate depressive symptoms with the Geriatric Depression Scale – 15 items and (...) physical activity levels through the International Physical Activity Questionnaire. Individuals were also asked to self-report changes in their physical activity levels and time spent sitting.ResultsNinety percent of older adults self-reported a decrease in overall physical activity levels, and nearly 65% increased daily sitting time during the home confinement. However, previously active older adults still presented high levels of physical fitness after 11 weeks of home confinement. Overall, 52.9% of participants scored 5 or more points on GDS-15, which is suggestive of depression. Higher levels of moderate-to-vigorous physical activity and cardiorespiratory fitness were found in the non-depressed group compared with the depressed group. Finally, results from multiple regression analysis revealed that MVPA was negatively associated with depression. This model explained 16.4% of the variability seen in depression score, controlled for age, gender, and education.ConclusionEven reporting a decline in physical activity, older adults who previously participated in a formal exercise program, still presented high levels of physical fitness after 11 weeks of home confinement. However, MVPA, but not physical fitness, seems to be an associated depression score in previously active older adults. These results reinforce the importance of older adults to remain physically active, since higher levels of MVPA may have a protective effect on depressive symptoms and, therefore, mitigate the negative impact of home confinement on mental health. Future longitudinal research studies are needed to ascertain these results. (shrink)

This study investigated the impact of supervisors’ servant leadership on supervisees’ moral identity and subsequent in-role performance. Data from 226 supervisor–supervisee dyads were collected from several domestic and multinational companies operating in the Kingdom of Saudi Arabia. Confirmatory factor analysis was conducted to confirm the factorial validity of the measures that were employed in this study. The hypothesized moderated mediation model was tested using hierarchical multiple regression analysis. Based on social learning theory, the results showed that (...) supervisees’ moral identity served as the psychological mediating mechanism through which supervisors’ servant leadership led to supervisees’ increased in-role performance. Furthermore, the results also supported supervisees’ avoidance orientation as the dispositional boundary condition of this mediating effect. This study contributes to both the servant leadership and moral identity literatures by addressing questions with useful theoretical and managerial implications. (shrink)

Multimedia learning research addresses the question of how to design instructional material effectively. Signaling and adding graphics are typical instructional means that might support constructing a mental model, particularly when learning abstract content from multiple representations. Although signals can help to select relevant aspects of the learning content, additional graphics could help to visualize mentally the subject matter. Learners’ prior knowledge is an important factor for the effectiveness of both types of support: signals and added graphics. Therefore, we conducted (...) an experimental study situated in a university course of computer science with N = 124 participants. In our 2 × 2 factorial design, we investigated the effects of signals and illustrating graphics on learning outcomes and their potential interplay. Based on our regression analysis, we revealed prior knowledge as a significant moderator. Although learners with low levels of prior knowledge can profit from all types of help but still gain rather weak learning outcomes, learners with medium levels of prior knowledge profit from the synergy of both helps. With higher levels of prior knowledge, signals were particularly hampering. To improve the understanding of these supportive or hampering effects, a more fine-grained analysis of these processes and motivational effects is necessary. (shrink)

ObjectiveIn the context of Healthy China, the effect of external motivation on sports anomie behavior from the perspective of gender among Chinese college students was investigated.ParticipantsIn total, 2,340 college students were involved in this study.MethodsThe self-made scales were used, which were about anomie behavior and external motivation in sports. The independent sample T-test was used to compare the sports anomie behavior between male and female students. Then, multiple linear regression analysis was adopted to examine the effects of (...) external motivation on sports anomie behavior.ResultsGirls’ sports anomie behavior was lower than boys. There were significant gender differences in honor motivation, obedience motivation, and economic motivation; girls’ motivations were lower than boys. The academic motivation was negatively correlated with the sports anomie behavior of college students of both genders. The economic motivation was positively correlated with their sports anomie behavior. The honor motivation was negatively correlated with the sports anomie behavior of female college students.ConclusionFemale college students’ sports anomie behavior and external motivation are lower than that of male college students. External motivation had a significant influence on college students’ sports anomie behavior. (shrink)

A statistical method for inference of formal causes was introduced. The procedure, referred to as the method of corresponding regressions, was explained and illustrated using a variety of simulated causal models. The method reflects IV/DV relations among variables traditionally limited to correlational or structural equation analysis. The method was applied to additive, subtractive, multiplicative, recursive and reflected models, as well as models of unrelated and correlated dependent variables. Initial applications to data from physical science, biology, economics, marketing and psychology (...) were developed, with generally supportive results. (shrink)

Based on the review and research on the teleworking modality and the variables that impact it at the organizational level, such as quality of life, communication, organizational culture or productivity, a case study is proposed under the innovation and teleworking model of a company. Japanese automotive industry for the application of Multivariate Analysis techniques such as Principal Component Analysis and Linear Regression, in order to condense the information provided by multiple variables into principal components and validate (...) the relationships and impact that exist between them, thus determining the interdependence and correlation of the same with the telework variable, allowing to simplify the complexity of sample spaces with many dimensions. It was possible to identify the main components with the variables' own labels and the dependent and predictive variables of the case were statistically validated, through the use of the IBM SPSS. (shrink)

The current paper highlights a new, interactive Shiny App that can be used to aid in understanding and teaching the important task of conducting a prior sensitivity analysis when implementing Bayesian estimation methods. In this paper, we discuss the importance of examining prior distributions through a sensitivity analysis. We argue that conducting a prior sensitivity analysis is equally important when so-called diffuse priors are implemented as it is with subjective priors. As a proof of concept, we conducted (...) a small simulation study, which illustrates the impact of priors on final model estimates. The findings from the simulation study highlight the importance of conducting a sensitivity analysis of priors. This concept is further extended through an interactive Shiny App that we developed. The Shiny App allows users to explore the impact of various forms of priors using empirical data. We introduce this Shiny App and thoroughly detail an example using a simple multiple regression model that users at all levels can understand. In this paper, we highlight how to determine the different settings for a prior sensitivity analysis, how to visually and statistically compare results obtained in the sensitivity analysis, and how to display findings and write up disparate results obtained across the sensitivity analysis. The goal is that novice users can follow the process outlined here and work within the interactive Shiny App to gain a deeper understanding of the role of prior distributions and the importance of a sensitivity analysis when implementing Bayesian methods. The intended audience is broad and can include those with limited exposure to Bayesian methods or the specific model presented here. (shrink)

A judgement analysis of people's social inferences of attitudes and ability was conducted. University students were asked to infer the liberalness ( N = 60; Study 1) or intelligence ( N = 40; Study 2) of targets seen in pictures. Multiple regression analyses revealed that attractiveness was the most important cue for predicting inferences of liberalness, while an ethnic cue (i.e., being Asian) was the most important cue for judgements about intelligence. Results also showed that a single-cue (...) model was less susceptible to overfitting, but significantly less accurate than a multiple-cue model in predicting participant's intelligence judgements. Although the multiple regression models suffered a degree of overfitting, cross validation showed that they continued to have significant predictive value when applied to new data. Furthermore, a “random partner” method (comparing each participant's own regression equation with that of another, randomly selected, participant) provided evidence of significant idiosyncratic variation in the way intelligence judgements were made. (shrink)

By definition, metacognitive processes may monitor or regulate various stages of first-order processing. By combining causal analysis with hypotheses expressed by other authors we derive the theoretical and methodological consequences of this special relation between metacognition and the underlying processes. In particular, we prove that because multiple processing stages may be monitored or regulated and because metacognition may form latent feedback loops, 1) without strong additional causal assumptions, typical measures of metacognitive monitoring or regulation are confounded; 2) without (...) strong additional causal assumptions, typical methods of controlling for first-order task performance (i.e., calibration, staircase, including first-order task performance in a regression analysis, or analyzing correct and incorrect trials separately) not only do not deconfound measures of metacognition but may even introduce bias; 3) that the first two problems cannot be solved by using simple models of decision-making derived from Signal Detection Theory. We conclude the paper by advocating robust methods of discovering properties of latent mechanisms. (shrink)

Color harmony is the focus of many researchers in the field of art and design, and its research results have been widely used in artistic creation and design activities. With the development of signal processing and artificial intelligence technology, new ideas and methods are provided for color harmony theory and color harmony calculation. In this article, psychological experimental methods and information technology are combined to design and quantify the 16-dimensional physical features of multiple colors, including multi-color statistical features and (...) multi-color contrast features. Eighty-four subjects are invited to give a 5-level score on the degree of color harmony for 164 multi-color materials selected from the screenshots of film and television scenes. Based on the multi-color physical features and the subjective evaluation experiment, the correlation analysis is firstly carried out, which shows that the overall lightness, difference of the color tones, number of multiple colors, lightness contrast, color tone contrast, and cool/warm contrast are significantly correlated with color harmony. On the other hand, the regression prediction model and classification prediction model of color harmony are constructed based on machine learning algorithms. In terms of regression prediction model, the prediction accuracy of linear models is higher than that of nonlinear models, with 63.9% as the highest, indicating that the multi-color physical features can explain color harmony well. In terms of classification prediction model, the Random Forest has the best prediction performance, with an accuracy of 80.2%. (shrink)

This paper presents the concept and algorithm of data mining and focuses on the linear regression algorithm. Based on the multiple linear regression algorithm, many factors affecting CET4 are analyzed. Ideas based on data mining, collecting history data and appropriate to transform, using statistical analysis techniques to the many factors influencing the CET-4 test were analyzed, and we have obtained the CET-4 test result and its influencing factors. It was found that the linear regression relationship (...) between the degrees of fit was relatively high. We further improve the algorithm and establish a partition-weighted K-nearest neighbor algorithm. The K-weighted K nearest neighbor algorithm and the partition algorithm are used in the CET-4 test score classification prediction, and the statistical method is used to study the relevant factors that affect the CET-4 test score, and screen classification is performed to predict when the comparison verification will pass. The weight K of the input feature and the adjacent feature are weighted, although the allocation algorithm of the adjacent classification effect has not been significantly improved, but the stability classification is better than K-nearest neighbor algorithm, its classification efficiency is greatly improved, classification time is greatly reduced, and classification efficiency is increased by 119%. In order to detect potential risk graduating students earlier, this paper proposes an appropriate and timely early warning and preschool K-nearest neighbor algorithm classification model. Taking test scores or make-up exams and re-learning as input features, the classification model can effectively predict ordinary students who have not graduated. (shrink)

Front-line employees (FELs) facing double challenges of handling demanding supervisors and irresponsible customers in organizational settings. Performance of service organizations exceedingly reliant on knowledge sharing within organizational employees. FLEs develop the destructive emotions of revenge attitude from abusive supervision and customers’ mistreatment and diminish knowledge sharing. This work aims to determine the effect of abusive supervision (ABS) and customer mistreatment (CMT) on the development of revenge attitude (RVA) and felt obligation (FTO) reduces the knowledge hiding behaviors. Moreover, the FLEs categorical (...) factors of work experience and gender vary the effect of knowledge hiding. Survey data from 201 FLEs police officers. Structural equation modeling partial least square regression (PLS-SEM) SmartPLS 3.1 was utilized to test the model. Study results confirm that ABS and CMT significantly impact the RVA, and FTO reduces the RVA. Moreover, RVA influences the evasive, playing dumb, and rationalized knowledge hiding behaviors, and FTO significantly streamlined the knowledge hiding behaviors. FLEs personal attributes of experience and gender moderates the knowledge hiding behaviour and analysed with PLS multiple group analysis (MGA). The study contributes to the knowledge hiding in service work settings FLEs facing internal and external pressures. Service firms need to train the FLEs to manage the customer with the established working standards and work with the supervisor exceeding expectations. Study limitations and future research opportunities were reported at the end. (shrink)

A growing body of research has focused on the relationship between board diversity and firm performance. A series of empirical literatures have also examined a significant positive correlation between the two. But these results only demonstrate the relationship between the input of ‘diversity’ and the output of ‘firm performance’. Such research is more of a black box because board diversity must act on certain strategies or decisions to affect firm performance. Some scholars try theoretical analysis with the purpose of (...) opening the black box. In order to verify the relevant theoretical analysis results, this study uses the mediating effect analysis model in the field of psychology, through multiple regression, impulse analysis, variance decomposition and other methods, to thus empirically test the mediating effect of technological innovation in the process of board diversification promoting corporate performance. We found that board diversity can improve firm performance by enhancing the level of technological innovation. Among them, technological innovation has played a complete mediating role in the diversity of board members’ functional and occupational background, and played a partial mediating role in the diversification of directors’ part-time jobs. Technological innovation is a key indicator bridging board diversity and firm performance. This study can explore and explain the inner workings of the significant relationship between board diversity and firm performance, and link research findings on similar phenomena. The research results may make the existing board governance theories more systematic, expand the extension of theoretical research, and provide some empirical research references for academics and practitioners. (shrink)

In order to analyze the characteristics of airport flight delayed time series, based on the construction of flight delay time series, firstly, the K-means algorithm is used to cluster the time series of delayed departures. Secondly, combining with R/s analysis method of Fractal theory, Hurst index of the series is calculated, and Fractal characteristics of the series are analyzed. Then, the VAR (Vector Auto Regression) model is constructed, and Impulse Response Function (IRF) and Variance Decomposition are conducted to (...) explore the impact of the fluctuation of flight delay time series on the future delay. The results show that K-means algorithm divides the time series into five categories, and each category has significant characteristics. Hurst index values of different time series are in the interval of (0.5, 1), indicating that the time series have good fractal characteristics. Through the IRF and Variance Decomposition of VAR model, results show that the time series are significantly affected by random pulses, and the prediction changes of the series come from multiple time series fluctuations. The prediction results show that the flight delay time series is predictable. (shrink)

Background: Cognitive impairment is one of the core symptoms of schizophrenia, which is considered to be significantly correlated to prognosis. In recent years, many studies have suggested that metabolic disorders could be related to a higher risk of cognitive defects in a general setting. However, there has been limited evidence on the association between metabolism and cognitive function in patients with early-stage schizophrenia.Methods: In this study, we recruited 172 patients with early-stage schizophrenia. Relevant metabolic parameters were examined and cognitive function (...) was evaluated by using the MATRICS Consensus Cognitive Battery (MCCB) to investigate the relationship between metabolic disorder and cognitive impairment.Results: Generally, the prevalence of cognitive impairment among patients in our study was 84.7% (144/170), which was much higher than that in the general population. Compared with the general Chinese setting, the study population presented a higher proportion of metabolic disturbance. Patients who had metabolic disturbance showed no significant differences on cognitive function compared with the other patients. Correlation analysis showed that metabolic status was significantly correlated with cognitive function as assessed by the cognitive domain scores (p < 0.05), while such association was not found in further multiple regression analysis.Conclusions: Therefore, there may be no association between metabolic disorder and cognitive impairment in patients with early-stage schizophrenia.Trial Registration: Clinicaltrials.gov, NCT02880462. Registered August 26, 2016. (shrink)

This paper presents conceptual clustering algorithms using regression analysis. The basic idea is that given data can be classified to the class “existing” and so conceptual clustering is transformed to classification. The algorithms consist of transforming given data to the data with a class, obtaining a function by regression analysis, approximating the function by a Boolean function, and generating a concept hierarchy from the Boolean function. Regression analysis includes linear regression analysis and (...) nonlinear regression analysis by neural networks. The algorithms can perform the multiple classification and generate simple clusters. The algorithms using linear regression analysis and neural networks have been applied to real data. Results show that the algorithm using neural networks works well. (shrink)

Advances in science and technology has led to the rise of different issues in relation to human life and security as well as the environment. These issues also paved the way for the field of Bioethics with its principles aiming to uphold moral standards on these issues. This study aimed to test and modify the theoretical models of the factors influencing the conviction schemas of BS Biology Bioethics students of a state university toward bioethical issues. One hundred ten (110) undergraduate (...) students were pre-tested and post-tested for comprehension of Bioethics principles, moral disengagement, and convictions toward bioethical issues. Identified personal factors were also retrieved for testing. Results showed that the Bioethics course has increased the participants’ comprehension of Bioethics principles, moral disengagement, and convictions. Stepwise multiple regression results revealed that anxiety, extraversion, exposure to media, and moral disengagement can predict pre-convictions. On the other hand, only moral disengagement was found to predict post-convictions. Furthermore, moral disengagement can be predicted by convictions before the course while anxiety, openness to change, and convictions were the predictors after the course. The proposed theoretical model was for tested goodness of fit using Structural Equation Modeling (SEM) and acceptance was based on the model fit criteria. Since the proposed model was not found to fit the data, this was revised based on the results of multiple regression and correlation among exogenous variables. Three models were constructed and found to fit the data adequately. These models show the direct and indirect effects of personal factors and moral disengagement on convictions. The mediating effects of moral disengagement and convictions to each other were also shown. Findings further imply that the ability to understand the principles does not influence convictions, but rather moral disengagement has a greater influence on the said factor. Improving moral education by integrating Bioethics to the curriculum is recommended to further strengthen the moral judgement and reasoning of students. (shrink)

Child trauma plays an important role in the etiology of Bordeline Personality Disorder. Of all traumas, sexual trauma is the most common, severe and most associated with receiving a BPD diagnosis when adult. Etiologic models posit sexual abuse as a prognostic factor in BPD. Here we apply machine learning using Multiple Kernel Regression to the Magnetic Resonance Structural Images of 20 BPD and 13 healthy control to see whether their brain predicts five sources of traumas: sex abuse, emotion (...) neglect, emotional abuse, physical neglect, physical abuse. We also applied the same analysis to predict symptom severity in five domains: affective, cognitive, impulsivity, interpersonal for BPD patients only. Results indicate that CTQ sexual trauma is predicted by a set of areas including the amygdala, the Heschl area, the Caudate, the Putamen, and portions of the Cerebellum in BPD patients only. Importantly, interpersonal problems only in BPD patients were predicted by a set of areas including temporal lobe and cerebellar regions. Notably, sexual trauma and interpersonal problems were not predicted by structural features in matched healthy controls. This finding may help elucidate the brain circuit affected by traumatic experiences and connected with interpersonal problems BPD suffer from. (shrink)

The paper deals with the regressive analytical method understood as "the way backward". In the first section the paper gives a historical survey concentrating on three paradigmatic examples: Pappus's definition of analysis and synthesis, the definition of method to be found in the so_called "Logic of Port Royal", and David Hilbert's definition of the axiomatic method as a procedure for setting up axiomatic systems. In the second section the scepticism of traditional philosophy of science concerning the regressive method is (...) reflected. (shrink)

Source: Author: Ahamed Lebbe Mohamed Aslam, S.M. Ahamed Lebbe There is a relationship between the fiscal deficit and inflation, which was confirmed empirically in several studies conducted in many countries. Sri Lanka has been encountering the problem of inflation for the recent years. But in Sri Lanka, this proposition has not yet been studied scientifically. Therefore, this study was going to fill this gap. The objective of this study was to test the impact of fiscal deficit on inflation in Sri (...) Lanka. For this study, the annual time series data were used during the period of 1959 to 2013. The fiscal deficit, exchange rate, government expenditures and import outflow were used as independent variables while the Colombo consumer price index was considered as dependent variable. In addition, the multiple regressions model was used to test the impact of fiscal deficit on inflation. Based on the regression results, the fiscal deficit preserved the positive relationship with inflation in Sri Lanka at one percent significant level. Therefore, this study confirmed that the fiscal deficit accelerates the inflation in Sri Lanka. ]]>. (shrink)

The purpose of the study was to analyse the level and the trends of Potential Years of Life Lost due to the main causes of death in Poland in the years 2002-2011. The material for the study was the information from the Central Statistical Office on the number of deaths due to the main causes of death in Poland in the years 2002-2011. The premature mortality analysis was conducted with the use of the PYLL indicator. PYLL rate was calculated (...) following the method proposed by J. Romeder, according to which premature mortality was defined as death before the age of 70. Time trends of PYLL rate and the average annual percent change were assessed using jointpoint models and the Joinpoint Regression Program. In the years 2002-2011, PYLL rate for all-cause deaths decreased by 7.0% among men and 8.1% among women. In 2011, the main reasons for PYLL among men were: external causes, cardiovascular diseases and cancers. Among women the leading causes were: cancers, cardiovascular diseases and external causes. PYLL rate increased among men for colorectal cancer, and among women for colorectal and lung cancer. The presented epidemiological situation for premature mortality in Poland shows that in the majority of cases it is caused by preventable deaths, which highlights a need to intensify measures in primary and secondary prevention. (shrink)

This study was part of a larger cross-national research project at the Norway’s University of Bergen, which involved participants from over 30 countries. This undertaking delves into developmental assets, creativity, and thriving, and the part they play in determining mental health. Thus, this study examined the developmental assets, creativity, thriving, and their importance to mental health in a sample of Malaysian emerging adults. This study was based on a sample of 394 undergraduate students, comprising 264 females and 130 males, ranging (...) between the ages of 18 and 26 years. Two subscales of the Reisman diagnostic creativity assessment were used to measure creativity. Meanwhile, thriving indicators of Search Institute were used to measure thriving while the short form of the mental health continuum for adolescents was used to measure mental health. An online Google form was used to collect data from university students enrolled in both public and private universities. The correlation analysis results revealed that all the variables were positively correlated to each other and that the relationship between development assets, creativity, thriving, and mental health ranged from weak to moderate. Multiple regression analysis produced four models that indicated that positive identity, support, creativity, and thriving have a significant influence on mental health among emerging adults. Further, analyses using the PROCESS procedure demonstrated significant indirect effects of positive identity and support on mental health through its effects on creativity and thriving. As such, it is our recommendation that mental health practitioners tailor their treatment approach to include positive identity, support, creativity, and thriving in their sessions with Malaysian emerging adults. (shrink)

Based on the nationally representative sample data from the Chinese General Social Survey, this study examines the relationship of education levels and health status with an individual's probability of being employed in China. The findings obtained from the binary logistic regression estimator suggest that people with a higher level of education were more likely to be employed than those who have less or no education. The individual with university or above education was found to be 85% more likely to (...) be employed than college or equal diploma holders. Further, the healthier individual was found to be 11% more likely to be employed than relatively less healthy. Moreover, the resulting coefficients obtained from the moderation effect suggest that all of the two-way interaction effects among health status and education levels with gender are not statistically significant even at the 10% level. The results suggest that there was no multiplicative effect of gender with health status and level of education on an individual's probability of being employed. Further, the study also suggests important policy implications in the light of China's active labor force market and the gender gap in employment. (shrink)

Averroes is well-known for his controversial thesis that there is only one separate intellect for all humankind. This article provides a detailed analysis of Averroes’s Unity Argument from his Long Commentary on De Anima, which argues from unified intelligible concepts to a single transcendent intellect. I set out the Unity Argument in its textual and philosophical context, explain exactly how the argument works on a new interpretation of its infinite regress, and offer some brief suggestions as to how it (...) might be further evaluated in light of alternative ancient and medieval theories. Ultimately, I demonstrate that the Unity Argument is Averroes’s most important philosophical argument for his distinctive view of intellect. (shrink)

Job motivation remains an area of concern among researchers due to the rising issues of poor or lack of motivation among workers. This refers to one’s personal will or drives to perform a task at work. Meanwhile, job satisfaction refers to an employee’s sense of fulfillment with his or her work experience. Therefore, the current study utilized the descriptive- correlational research design to investigate the impact of job motivation on the job satisfaction of accountants. To gather essential data and achieve (...) the objectives of the study, Multidimensional Work Motivational Scale (MWMS) and Minnesota Satisfaction Questionnaire (MSQ) were administered to the target respondents. The collected data were then analyzed using a Multiple Regression Analysis; findings revealed that job motivation has a significant impact on the job satisfaction of accountants. Additionally, the results of this study were carefully evaluated and discussed, and recommendations were made to benefit the stakeholders of the study and contribute to the existing body of knowledge. (shrink)

The COVID-19 pandemic has already had an enormous impact on numerous aspects of human society such as health, education, economy, business, or work and created favorable conditions for the expansion of teleworking. The aim of the paper is to identify and analyze five teleworking impact factors that affect thewellbeing and productivity of employees. The data were gathered by a quantitative research method through a questionnaire applied to 327 Romanian employees who hold a Bachelor or Master degree. Firstly, they were analyzed (...) and interpreted through a factorial analysis focusing on the five teleworking impact factors. Secondly, the authors carried on cluster analysis, followed by multiple linear regression, using R statistical software. This study shows that there is a plethora of factors that influence the wellbeing and productivity of employees: individual and societal factors, organizational and work-related factors, technological factors, social factors at home, and social factors at work. Also, the cluster analysis brings to light significant differences between various Romanian employees such as: their gender, income, age, education, and city size. (shrink)

With the further acceleration of urbanization in China, the proportions of both urban residents’ energy consumption and energy-consuming terminal electricity are showing an increasing trend at the same time. In view of the dynamic and time-varying complex system characteristics of power system, it is of great significance to study the impact mechanism of urbanization residents’ electricity consumption on the realization of demand-side management and environmental protection. Based on the one-year follow-up survey data obtained from household meter reading, this paper studies (...) the impact mechanism of urban residents’ electricity consumption in different seasons and terminals by descriptive analysis and multiple linear regression model. The results show that, on the whole, electricity is a necessity for urban households and does not change significantly with changes in income. At the turn of summer and autumn and the turn of winter and spring, high-income families tend to use higher levels of energy in pursuit of comfort, while low- and middle-income families do not have luxury consumption. In different seasons, the influence mechanism of household electricity consumption at different terminals is different. (shrink)

This study was designed to examine the determinants of and differences between the ethical beliefs of two groups of Japanese students in religious and secular universities. Multiple regression analysis revealed that students of the Japanese religious university perceived that young, male, relativistic, and opportunistic students tended to behave less ethically than did older, female, and idealistic students. Students of the Japanese secular university perceived that male, achievement-oriented, and opportunistic students tended to behave less ethically than did female (...) and experience-oriented students. Opportunism was found to be one of the most important determinants in explaining misconduct. Multivariate analysis of variance (MANOVA) and multiple discriminant analysis (MDA) revealed that students of the Japanese secular university tended to score higher on achievement and humanism, and lower on theism and positivism than did students of the Japanese religious university. In addition, students of the Japanese secular university were somewhat more sensitive to academic dishonesty practices than were students of the Japanese religious university. (shrink)

Academic productivity is realized through resources obtained from professional networks in which scientists are embedded. Using a national survey of academic faculty in Science, Technology, Engineering, and Mathematics fields across multiple institution types, we examine how the structure of professional networks affects scholarly productivity and how those effects may differ by race, ethnicity, and gender. We find that network size masks important differences in composition. Using negative binomial regression, we find that both the size and composition of professional (...) networks affect scientific productivity, but bigger is not always better. We find that instrumental networks increase scholarly productivity, while advice networks reduce it. There are important interactive effects that are masked by modeling only direct effects. We find that white men are especially advantaged by instrumental networks, and women are especially advantaged by advice networks. (shrink)

BackgroundAlthough, moral distress presents a serious problem among critical care nurses in many countries, limited research has been conducted on it. A validated scale has been developed to evaluate moral distress and has enabled cross-cultural comparison for seeking its root causes.Research aimsThis study aimed to (1) clarify the current status of moral distress among nurses who worked in critical care areas in Japan, (2) compare the moral distress levels among nurses in Japan with previously reported results from the United States (...) (US), and (3) explore the factors associated with moral distress.Research designA nationwide cross-sectional study was conducted.Participants and research contextWe conducted a self-administered questionnaire survey using the Measure of Moral Distress–Healthcare Professionals (MMD-HP) among critical care nurses who were randomly selected from hospitals across Japan. The mean differences between the two countries were compared using a Student's t-test with summary statistics. The factors associated with higher levels of moral distress were examined using a multiple regression analysis.Ethical considerationsThe study was approved by the Ethics Committee of the Tokyo Medical and Dental University (approval nos. M2018-214 and M2019-045).ResultsWe obtained 955 valid responses from 94 facilities. In Japan, the items with the highest moral distress scores were those related to aggressive/inappropriate treatment. The total MMD-HP score was significantly higher in Japanese nurses compared to US nurses (122.8 ± 70.8 vs 112.3 ± 73.2). Some factors, such as leadership experience, were associated with higher moral distress.DiscussionThe top root causes of moral distress were similar to potentially inappropriate treatments in both countries.ConclusionThis study revealed the factors associated with higher moral distress and its characteristics in each country. These results can be used for reducing moral distress in the future. (shrink)

Corruption Perceptions Index (CPI) scores for 47 countries reported by Transparency International were used to ascertain determinants of bribe taking in international business. Two sets of independent variables – economic and cultural – were used in a multiple regression analysis. Results indicate that bribe taking was more likely to be prevalent in countries with low per capita income and lower disparities in income distribution. Cultural factors such as high power distance and high masculinity in a country were (...) also likely to be associated with high level of bribe taking. Both economic and cultural factors were important explanatory factors of bribery. Implications of the findings for combating bribery are discussed. (shrink)

This study examines the effects of demographic characteristics on ethical perceptions. While earlier research has produced conflicting results regarding the predictive power of these variables, significant and definite insights were obtained with proper controls. The following predictors of ethical attitudes are examined: age, gender, marital status, education, dependent children status, region of the country and years in business, while controlling for job status. A nation-wide random sample of employees was used in obtaining a response rate of fifty-three percent (total n (...) of 423). Indices of aspects of business ethical attitudes were constructed using factor analysis. Linear multiple regression analysis indicated the significant predictive variables. Age was found to be a most-significant predictor. Older workers had stricter interpretations of ethical standards. Gender and region predicted attitudes about job-discrimination practices only, with women and persons from the Midwest most strongly opposed to the practice. All the other variables proved to be unreliable ethics predictors. (shrink)

Introduction: Motor evoked potentials (MEPs) to transcranial magnetic stimulation are known to be susceptible to several sources of variability. However, conflicting evidences on individual characteristics in relatively small sample sizes have been reported. We investigated the effect of age, height, and sex on MEPs of the motor cortex and spinal roots in a large cohort. Methods: A total of 587 subjects clinically and neuroradiologically intact were included. MEPs were recorded during mild tonic contraction through a circular coil applied over the (...) “hot spot” of the first dorsal interosseous and tibialis anterior muscles, bilaterally. Central motor conduction time (CMCT) was estimated as the difference between MEP cortical latency and the peripheral motor conduction time by cervical or lumbar magnetic stimulation. Peak-to-peak MEP amplitude to cortical stimulation and right-to-left difference of each parameter were also measured. Results: After Bonferroni correction, general linear (multiple) regression analysis showed that both MEP cortical latency and peripheral motor conduction time at four limbs positively correlated with age and height. At lower limbs, an independent effect of sex on the same measures was also observed (with females showing smaller values than males). CMCT correlated with both age (negatively) and height (positively) when analyzed by a single regression; however, with a multiple regression analysis this significance disappeared, due to the correction for the multicollinearity within the dataset. Conclusions: Physical individual features need to be considered for a more accurate and meaningful MEPs interpretation. Both in clinical practice and in research setting, patients and controls should be matched for age, height, and sex. (shrink)

OBJECTIVE: (a) To measure the effect of a guideline-based training on the performance of ontology developers compared with the performance after unspecific training by a competency question based evaluation; and (b) to provide empirical evidence for the applicability of competency questions in formal ontology evaluation in general. BACKGROUND: A close connection between ontology development and ontology evaluation as quality management procedure can been attained with the use of competency questions. Competency questions are often used as a semi-formal specification of requirements (...) for an ontology under development. Hence they can also be used as evaluation instruments, in order to check how far an ontology fulfills these requirements. METHODS: A randomized controlled trial was conducted with two groups of 12 students each. The intervention consisted in a differential guideline-based training on ontology development vs. unspecific training. After a group-specific training focusing on three topics per group, performance of students was assessed with 12 exercises (2 exercises per topic), in which the students had to apply their skills. Different types of competency questions were elaborated for the analysis of the students' ontologies. We used the proportion of correct answers as a measure of ontology quality. RESULTS: On single topic level, the performance of ontology developers increased after guideline-based training for two out of the six topics: it increased from a proportion of 0.46 to 0.63 for the topic Process \& Participation and from 0.44 to 0.53 for the topic Collective Material Entity. In regression analysis, a positive correlation was shown between the performance of students on untrained topics and the performance after specific guideline-based training. Moreover, in multiple regression analysis an overall effect of specific training of 0.09 was calculated (p < 0.1). CONCLUSION: The results show an effect of a specific guideline-based training on the performance of ontology developers compared to the performance after unspecific training by an increase of about 10 \% on the rate of correct competency questions. In addition, this study has shown the general applicability of competency questions in a formal ontology evaluation scenario. However, the study also shows that the training of ontology developers and their performance evaluation is a tedious task. The resulting performance of ontology developers is more dependent on the a priori individual competencies than on the specific acquired skills after training. (shrink)

The youngest population in society is recognized as that at the healthiest stage of life but is burdened by the occurrence of premature death that should be avoidable. There is a need to use adequate statistical methods in assessing the health status of the population of developmental age. The aim of the study was to analyze trends of mortality in children and adolescents by age and gender in the Podlaskie Voivodeship in the years 2003-2012 by joinpoint regression and to (...) identify the causes of mortality. The mortality rate was analysed according to gender and the age groups: 0, 1-4, 5-9, 10-14 and 15-19 years in the Podlaskie Voivodeship. The data were obtained from the Central Statistical Office for the period 2003-2012. Differences in mortality levels between age and gender subgroups were obtained by the Wilcoxon signed-rank test. Join- point regression was used to analyze the trends in mortality. The nomenclature of ICD-10 was used to assess the causes of mortality of children and adolescents. In the Podlaskie Voivodeship in the years 2003-2012 in the 0-19-year-old age group, the highest proportion of deaths (42.4%) occurred during the first year of life. There were differences in mortality rates between boys (8.0/104) and girls (3.1/104) in the 15-19-year-old age group (p < 0.01), and also between the 1-14-year-old and 15-19-year-old age groups (p < 0.01), both among boys (2.1/104 vs. 8.0/104) and girls (1.5/104 vs. 3.1/104). Monotonous trends were shown regarding total mortality rates in infants. There was a drop in the mortality rate of infant girls (AAPC = 5.3%, p < 0.05) and boys (AAPC = 4.7%, p < 0.05). Changes in the direction of the total mortality rate trend were visible in the population of boys aged 1-14 years, in which, between 2003 and 2010, a significant reduction in mortality (AAPC = 9.5%) was observed, while in the years 2010-2012 the trend was not significant. No statistical evidence was found that mortality changed among girls in the 1-14-year-old and 15-19-year-old age groups. Deaths in infancy were due to perinatal conditions and congenital mal- formations. The main causes of mortality in the 1-19-year-old age group were external causes, mainly traffic accidents and intentional self-harm. Joinpoint regression indicated a uniform decrease of mortality in the years 2003-2012 except for boys from 1-14 years old, for whom the decreasing trend was for the years 2003-2010 with subsequent stabilization. The main problems are still infant deaths due to perinatal conditions, traffic accidents and intentional self-harm in boys in the 15-19-year-old age group. (shrink)