Kruja is a middle-range city located in the center of Albania. The city of Kruja dates back to its existence from the V-VI century and extends to the city around the VI and IX centuries. It becomes the first capital of Albania in the XI-th century, specifically in 1190. This paper is going to deal with only two groups of buildings that are an integral part of the historical city of Kruja, the historical dwellings (XVIII century) and the socialist ones (...) (1960-1985). This paper aims to analyze through linear regressions the relation between two parameters: moisture content and temperature of the indoor walls and floors of the historic and socialist buildings in the city of Kruja. Three types of historic dwelling and three types of socialist apartments have been analyzed, relatively uniformly oriented. The measurements with specific instruments are done on the same day, for three hours. The degree of reactivity is different for both groups of buildings. The historical buildings are more sensitive to temperature rise. They respond invers to it (as the temperature rise, the level of the moisture content decreases), with a higher coefficient than socialist ones, and appear to be more efficient in reducing the level of the moisture, despite the average moisture content being higher. This paper takes into consideration also the analysis of the materials of the construction for both categories. If the level of moisture is reduced, the buildings will be improved and the quality of life indicators of the inhabitance will be improved too. (shrink)

The use of linear regression is ubiquitous across the social and behavioral sciences, and yet researchers rarely hold that the variables in their target systems are in fact linearly related. This raises the question of how to interpret linear regression coefficients when there is ‘functional misspecification’ and the target system exhibits nonlinearity. Here, recent methodological discussions among practitioners have mirrored philosophical debates over scientific realism. In this paper, I frame the prevailing views in terms of their stance on (...) the scientific realism debate. I then present a novel realist interpretation of linear regression—the ‘secant interpretation’—based on a property I derive about the manner in which linear regression coefficients represent properties of non-linear systems of interest. (shrink)

The regression model is generally utilized in several fields of study because of its applications. Regression is an extremely incredible approach; it builds up a connection between dependent and independent variables. We have addressed a powerful computational model by utilizing dengue information joined with fuzzy multiple linear regression. Information is accumulated on dengue fever through the survey. This paper is centered on the comparison of the crisp method with fuzzy multiple linear regression, and then, the utilization (...) of a fuzzy multiple regression method is explained after the comparison. We have used multiple regression and then converted the said technique into three fuzzy cases. The effectiveness of the fuzzy multiple regression model is measured by numerical computation and comparison of both techniques. 2020 Mathematics Subject Classification. Primary 30C45; 30C50; 30C80; Secondary 11B65, 47B38. (shrink)

Economic burden of private supplementary tutoring is increasing around the world. Demand for private supplementary tutoring, contributing factors, and their effects are investigated in the study. For this purpose, data were collected through questionnaire, and multistage non-probability technique was used. Hurder model was used to find the factors affecting demand for private supplementary tutoring at the higher secondary level. Linear regression model was used to find the economic burden of family and factors affecting the demand for private tutoring. The (...) findings showed that several factors have a significant effect on the demand for private supplementary tutoring, and some of them significantly impact on the economic burden. The study recommends regulating the market of shadow education because of differentiated tuition fee in different tuition centers to cut down the burden of private tutoring for households. (shrink)

Linear regression and its variants have been widely used for classification problems. However, they usually predefine a strict binary label matrix which has no freedom to fit the samples. In addition, they cannot deal with complex real-world applications such as the case of face recognition where samples may not be linearly separable owing to varying poses, expressions, and illumination conditions. Therefore, in this paper, we propose the kernel negative ε dragging linear regression method for robust classification on noised (...) and nonlinear data. First, a technique called negative ε dragging is introduced for relaxing class labels and is integrated into the LR model for classification to properly treat the class margin of conventional linear regressions for obtaining robust result. Then, the data is implicitly mapped into a high dimensional kernel space by using the nonlinear mapping determined by a kernel function to make the data more linearly separable. Finally, our obtained KNDLR method is able to partially alleviate the problem of overfitting and can perform classification well for noised and deformable data. Experimental results show that the KNDLR classification algorithm obtains greater generalization performance and leads to better robust classification decision. (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)

This analysis demonstrates the application of a data duplication technique in linear regression with censored observations of the waiting time to third pregnancy ending in two outcome types, using data from Malaysia. The linear model not only confirmed the results obtained by the Cox proportional hazards model, but also identified two additional significant factors. The method provides a useful alternative when Cox proportionality assumption of the hazards is violated.

The main aim of this paper is to analyze the electronic banking services in Kosovo’s banking net profit during the period 2013 - 2017. The paper discusses the role that these services have played in the development of the banking industry, modernization of e-commerce, and economic growth. These services provide higher security, faster and easier access by reducing transaction costs, access to more distant markets, and access to many products and services. The main paper results have shown that E-banking services (...) have the highest positive impact in banking net profit, while automated teller machine services have shown a slight positive impact. The highest positive correlation results have been seen in point-of-sale services, whereas automated teller machine services showed a negative correlation in banking net profit in Kosovo during the research period. The constant increase of demand for these services has enabled banks to increase their profits in the banking market of Kosovo. Therefore, the paper finds that commercial banks in Kosovo should increase their focus on the advancement and development of electronic banking services (particularly, E-Banking services which are very practical and can be easily used anywhere and anytime). (shrink)

Wheat is the most imperative crop for man feeding and is planted in numerous countries under rainfed conditions in semiarid zones. It is necessary for decision-makers and governments to predict the yield of rainfed wheat before harvest and to determine the effect of the major factors on it. Different methods have been suggested for forecasting yield with various levels of accuracy. One of these approaches is the statistical regression model, which is simple and applicable for regions with scarce data (...) available. Since the weather is the most important factor affecting the production of wheat, particularly in rainfed cultivation, regression models using weather parameters are very common. However, the coefficients of these models are location based and should be determined locally. Therefore, in this research, backward multiple linear regression technique based on relative importance metrics was used to determine the most important effective weather parameters on rainfed wheat productions in Fars Province, south of Iran, during 2006–2013. The influence of each parameter in the final model was analyzed using the values of LMG relative importance metric. The result indicated that sunshine hours had the biggest LMG and, therefore, was the most effective parameter. Also, among the other considered parameters, rainy days, minimum relative humidity, and average relative humidity with LMG values of 21.97%, 21.69%, and 21.62%, respectively, had the most effects on rainfed wheat yield in the studied area. All parameters except for the sunshine hours positively affected rainfed wheat yield. The most important reason for the significance of these parameters can be the prevailing dry and semidry climate in the southern areas of Iran. The proposed model for determination of weather parameters effects on rainfed wheat could be a great guidance and aid for different stakeholders such as farmers, decision-makers, and governments. (shrink)

Researchers in the social and behavioral sciences often have clear expectations about the order/direction of the parameters in their statistical model. For example, a researcher might expect that regression coefficient β 1 is larger than β 2 and β 3. The corresponding hypothesis is H : β 1 > {β 2, β 3 } and this is known as an (order) constrained hypothesis. A major advantage of testing such a hypothesis is that power can be gained and inherently a (...) smaller sample size is needed. This article discusses this gain in sample size reduction, when an increasing number of constraints is included into the hypothesis. The main goal is to present sample-size tables for constrained hypotheses. A sample-size table contains the necessary sample-size at a pre-specified power (say, 0.80) for an increasing number of constraints. To obtain sample-size tables, two Monte Carlo simulations were performed, one for ANOVA and one for multiple regression. Three results are salient. First, in an ANOVA the needed sample-size decreases with 30–50% when complete ordering of the parameters is taken into account. Second, small deviations from the imposed order have only a minor impact on the power. Third, at the maximum number of constraints, the linear regression results are comparable with the ANOVA results. However, in the case of fewer constraints, ordering the parameters (e.g., β 1 > β 2 ) results in a higher power than assigning a positive or a negative sign to the parameters (e.g., β 1 > 0). (shrink)

The liver is the human body’s mandatory organ, but detecting liver disease at an early stage is very difficult due to the hiddenness of symptoms. Liver diseases may cause loss of energy or weakness when some irregularities in the working of the liver get visible. Cancer is one of the most common diseases of the liver and also the most fatal of all. Uncontrolled growth of harmful cells is developed inside the liver. If diagnosed late, it may cause death. Treatment (...) of liver diseases at an early stage is, therefore, an important issue as is designing a model to diagnose early disease. Firstly, an appropriate feature should be identified which plays a more significant part in the detection of liver cancer at an early stage. Therefore, it is essential to extract some essential features from thousands of unwanted features. So, these features will be mined using data mining and soft computing techniques. These techniques give optimized results that will be helpful in disease diagnosis at an early stage. In these techniques, we use feature selection methods to reduce the dataset’s feature, which include Filter, Wrapper, and Embedded methods. Different Regression algorithms are then applied to these methods individually to evaluate the result. Regression algorithms include Linear Regression, Ridge Regression, LASSO Regression, Support Vector Regression, Decision Tree Regression, Multilayer Perceptron Regression, and Random Forest Regression. Based on the accuracy and error rates generated by these Regression algorithms, we have evaluated our results. The result shows that Random Forest Regression with the Wrapper Method from all the deployed Regression techniques is the best and gives the highest R2-Score of 0.8923 and lowest MSE of 0.0618. (shrink)

Log-linear analysis is a practical tool for examining relationships, successfully applied in many fields of science. This paper discusses the topic of estimation of the chance of getting pregnant in couples that underwent ART insemination. The authors focus on finding significant interactions between variables, on the basis of which statistical models are built. With the use of results of log-linear analysis, a model predicting the chances of achieving a clinical pregnancy that contained interactions was successfully built. Moreover, it was more (...) complete than the model obtained with the use of logistic regression alone. (shrink)

As one of the low-carbon products, remanufactured products are being paid more attention in more and more countries. But the low willingness of Chinese consumers to pay for them makes it difficult for remanufactured products companies to move forward in the Chinese market. This study explores the factors that affect consumers’ willingness to pay for remanufactured goods, through the hierarchical linear regression method, based on questionnaires. The results show that demographic variables (age, education, occupation, and income), individual subjective variables (...) (environmental awareness, secondhand preferences, and Chinese quality trust) and product perception variables (MP4 quality perceived risk, face risk, and product impact on the environment) have a significant impact on the willingness to pay for remanufactured goods. (shrink)

Proper linear models are those in which predictor variables are given weights such that the resulting linear composite optimally predicts some criterion of interest; examples of proper linear models are standard regression analysis, discriminant function analysis, and ridge regression analysis. Research summarized in P. Meehl's book on clinical vs statistical prediction and research stimulated in part by that book indicate that when a numerical criterion variable is to be predicted from numerical predictor variables, proper linear models outperform clinical (...) intuition. Improper linear models are those in which the weights of the predictor variables are obtained by some nonoptimal method. The present article presents evidence that even such improper linear models are superior to clinical intuition when predicting a numerical criterion from numerical predictors. In fact, unit weighting is quite robust for making such predictions. The application of unit weights to decide what bullet the Denver Police Department should use is described; some technical, psychological, and ethical resistances to using linear models in making social decisions are considered; and arguments that could weaken these resistances are presented. (shrink)

The present study explored heterogeneity in the association between engaged living and problematic Internet use. This study included 641 adolescents from four junior-senior high schools of Guangzhou, China. Besides the standard linear regression analysis, mixture regression analysis was conducted to detect certain subgroups of adolescents, based on their divergent association between engaged living and PIU. Sex, age, and psychological need were further compared among the latent subgroups. The results showed that a mixture regression model could account for (...) more variance of PIU than a traditional linear regression model, and identified three subgroups based on their class-specific regression of PIU to engaged living. For the High-PIU class, lower social integration and higher absorption were associated with increased PIU; for the Medium-PIU class, only high social integration was linked with the increase of PIU. For the Low-PIU class, no relation between engaged living and PIU were found. Additionally, being male or having a lower level of satisfied psychological needs increased the link between engaged living and PIU. The results indicated a heterogeneous relationship between engaged living and PIU among adolescents, and prevention or intervention programs should be tailored specifically to subgroups with moderate or high levels of PIU and to those with lower levels of psychological needs’ satisfaction, as identified by the mixture regression model. (shrink)

We study Compositional Models based on Dirichlet Regression where, given a (vector) covariate x, one considers the response variable, y, to be a positive vector with a conditional Dirichlet distribution, y | X We introduce a new method for estimating the parameters of the Dirichlet Covariate Model given a linear model on X, and also propose a Bayesian model selection approach. We present some numerical results which suggest that our proposals are more stable and robust than traditional approaches.

A result from a standard linear model course is that the variance of the ordinary least squares (OLS) coefficient of a variable will never decrease when including additional covariates into the regression. The variance inflation factor (VIF) measures the increase of the variance. Another result from a standard linear model or experimental design course is that including additional covariates in a linear model of the outcome on the treatment indicator will never increase the variance of the OLS coefficient of (...) the treatment at least asymptotically. This technique is called the analysis of covariance (ANCOVA), which is often used to improve the efficiency of treatment effect estimation. So we have two paradoxical results: adding covariates never decreases the variance in the first result but never increases the variance in the second result. In fact, these two results are derived under different assumptions. More precisely, the VIF result conditions on the treatment indicators but the ANCOVA result averages over them. Comparing the estimators with and without adjusting for additional covariates in a completely randomized experiment, I show that the former has smaller variance averaging over the treatment indicators, and the latter has smaller variance at the cost of a larger bias conditioning on the treatment indicators. Therefore, there is no real paradox. (shrink)

The costs of agricultural inputs added to those of labor represent almost a third of the total cost of Brazilian sugarcane production. This study analyzes the behavior of the price per ton of sugarcane in Brazil, relating it to the main production costs of this cultivation. Twelve price indicators from January 2015 to December 2020 were evaluated. First, the data were adjusted to a multiple linear regression model to identify the significant variables on variation in the price per ton (...) of sugarcane. Then, the Monte Carlo simulation was used to measure the level of certainty of occurrence of these variables, and forecasts were obtained from the adjustment of ARIMA models. The results showed the influence of the costs of diesel oil, two agricultural pesticides, and daily laborers on the price of sugarcane, besides an increasing trend of its, providing relevant short-term projections for decision-making about investments in the agribusiness sector. (shrink)

The aim of this study was to examine whether the relationship between the ratio of job-related positive to negative emotions and job burnout is best described as linear or curvilinear. Participants were 89 police officers and 86 firefighters. The positivity ratio was evaluated using the Job-related Affective Wellbeing Scale. Exhaustion and disengagement, two components of job burnout, were measured using the Oldenburg Burnout Inventory. The results of regression analysis revealed that curvilinear relationships between the positivity ratio and two components (...) of job burnout appeared to better fit the data than linear relationships. The relationship between the positivity ratio and exhaustion was curvilinear with a curve point at around 2.1. A similar curvilinear relationship, but with a lower curve point, i.e., around 1.8, was observed for disengagement. It seems that beyond certain values there may be hidden costs of maintaining positive emotions at work. Also, the unequal curve points for subscales suggest that different dimensions of work-related functioning are variously prone to such costs. (shrink)

We describe a unification of old and recent ideas for formulating graphical models to explain time series data, including Granger causality, semi-automated search procedures for graphical causal models, modeling of contemporaneous influences in times series, and heuristic generalized additive model corrections to linear models. We illustrate the procedures by finding a structure of exogenous variables and mediating variables among time series of remote geospatial indices of ocean surface temperatures and pressures. The analysis agrees with known exogenous drivers of the indices, (...) not assumed in the analysis. Automated search applied to the residuals after regressing each series on its lags and the lags of its Granger causes yields a graphical model of “comtemporaneous” causal relations identical with the qualitative graphical relations from the time series. A similar analysis produces reasonable results when applied to candidate climate indices obtained by a clustering method from sea surface temperature and sea level pressure data. (shrink)

We describe a unification of old and recent ideas for formulating graphical models to explain time series data, including Granger causality, semi-automated search procedures for graphical causal models, modeling of contemporaneous influences in times series, and heuristic generalized additive model corrections to linear models. We illustrate the procedures by finding a structure of exogenous variables and mediating variables among time series of remote geospatial indices of ocean surface temperatures and pressures. The analysis agrees with known exogenous drivers of the indices, (...) not assumed in the analysis. Automated search applied to the residuals after regressing each series on its lags and the lags of its Granger causes yields a graphical model of “comtemporaneous” causal relations identical with the qualitative graphical relations from the time series. A similar analysis produces reasonable results when applied to candidate climate indices obtained by a clustering method from sea surface temperature and sea level pressure data. (shrink)

Water quality control helps in the estimation of water bodies and detects the span of pollutants and their effect on the neighboring environment. This is why the water quality of the northern part of Lake Manzala has been studied here from January to March, 2016. This study aims to model and create a program for linear and nonlinear regression of the water elements in Lake Manzala to assess and predict the water quality. Water samples have been extracted from various (...) depths, and physio-chemical properties and heavy metal concentrations have been evaluated. This study has proposed a new algorithm for predicting water quality called “Algorithm of Estimation Regression Model”. On the contrary, in renewable energy applications, statistical modeling and forecasting the solar radiation remains a significant issue with detect to reinforce power management. A new proposed method for forecasting the average Monthly Global Solar Energy in Queensland, Australia, is called, Converting Data Set into Markov Model. It was used to obtain Markov transition probability matrices for three and six states of the solar energy. The proposed forecasting method yielded accurate results with minimal error. (shrink)

The authenticity of the company’s accounting information is an important guarantee for the effective operation of the capital market. Accounting fraud is the tampering and distortion of the company’s public disclosure information. The continuous outbreak of fraud cases has dealt a heavy blow to the confidence of investors, shaken the credit foundation of the capital market, and hindered the healthy and stable development of the capital market. Therefore, it is of great theoretical and practical significance to carry out the research (...) on the identification and governance of accounting fraud. Traditionally, accounting fraud identification is mostly based on linear thinking to build the fraud identification model. However, more and more studies show that fraud has typical nonlinear characteristics, and the multiobjective of fraud means also determines the limitations of using the linear model for identification. Considering that the traditional identification methods may have the defects of model setting error and insufficient information extraction, this paper constructs the support vector machine and logistic regression model to identify accounting fraud. The support vector machine is used to improve the learning ability and generalization ability of unknown phenomena, and the explanatory power of each variable to the whole model is identified by the logistic regression model. This paper breaks through the linear constraint hypothesis and explores the model setting form which is more suitable for the law of corporate fraud behaviour to extract the fraud identification information more fully and provide more powerful support for investors to effectively identify fraud. (shrink)

This paper argues that while Chambers' method of corresponding regressions offers an intriguing way of analyzing empirical data much remains to be done to make the mathematical, and thus, the statistical meaning of the procedure clear and intuitive. Chambers' theoretical justification of the method of the claim that it can in some sense validate formal cause explanations as alternatives to efficient cause, mechanistic ones is rejected. Chambers has misattributed the mechanistic cast of most contemporary psychological explanations to linear temporality rather (...) than to necessity, and has preserved such necessity in the quality of asymmetry. The paper seeks to distinguish and clarify temporality, causality, and necessity in order to be more clear about the central theoretical problem Chambers identifies. It is further argued that the current theoretical issues facing the discipline likely cannot be resolved by methodological advances. (shrink)

The purpose of the study is to determine the impact of entrepreneurial initiative on the development of innovation activity of country enterprises. The theory of entrepreneurship by clarifying the essence of entrepreneurial initiative got further elaboration in the article. The methodical approach to the analysis and evaluation of the entrepreneurial initiative and its impact on the innovation activity of the enterprises, the results of which are the basis for further development of proposals to stimulate entrepreneurial initiative and development of their (...) innovation activity is suggested. The estimation of innovation activity of 1758 enterprises of Ukraine by calculating the integral indicator of innovation activity revealed its low level for innovation active enterprises. The method of one-dimensional linear regression has determined that an increase in the number of business structures per 10 thousand people of the country's population at a rate of 1.0 causes an increase in the indicator of innovation activity by 0.172. It is proved in the article that development of infrastructure of enterprenerial environment and creation of centers for entrepreneurship development act as an important mechanism of increasing innovation activity of enterprises of the country. (shrink)

In families, mothers and fathers may hold the same or different levels of theories of intelligence. This congruence and discrepancy may influence parental involvement in children’s education. The current study examined how both parents’ theories of intelligence and the direction and degree of the discrepancy of parents’ intelligence theories influence maternal and paternal involvement separately. We measured 1,694 matched pairs of parents’ theories of intelligence and educational involvement, and examined the relationships using linear regressions and polynomial regressions with response surface (...) analysis. The results showed that 1) the mother’s intelligence theory positively related to both paternal involvement and maternal involvement, but the father’s intelligence theory only positively related to paternal involvement; 2) when the parents’ theories of intelligence reached congruence, the parents’ theories of intelligence are positively related to both maternal and paternal involvement; 3) when the parents’ theories of intelligence have discrepancy, the maternal involvement is higher while the mother’s intelligence theory’s level is more incremental than father’s; and 4) when the parents’ theories of intelligence have discrepancy, more discrepancy of parents’ theories of intelligence is related to more paternal involvement. This study revealed the significance of mother’s role in education, highlighted the importance of parents’ congruence and discrepancies in beliefs, examined how parents’ beliefs impact their own behavior and their couple’s behavior. (shrink)

The aim of the present study was to investigate the association between work-related moral stress, moral climate and moral sensitivity in mental health nursing. By means of the three scales Hospital Ethical Climate Survey, Moral Sensitivity Questionnaire and Work-Related Moral Stress, 49 participants’ experiences were assessed. The results of linear regression analysis indicated that moral stress was determined to a degree by the work place’s moral climate as well as by two aspects of the mental health staff’s moral sensitivity. (...) The nurses’ experience of ‘moral burden’ or ‘moral support’ increased or decreased their experience of moral stress. Their work-related moral stress was determined by the job-associated moral climate and two aspects of moral sensitivity. Our findings showed an association between three concepts: moral sensitivity, moral climate and moral stress. Despite being a small study, the findings seem relevant for future research leading to theory development and conceptual clarity. We suggest that more attention be given to methodological issues and developing designs that allow for comparative research in other disciplines, as well as in-depth knowledge of moral agency. Copyright © 2011 by SAGE Publications. (shrink)

Aims: The experience of a compromised sense of ‘self’, termed ego-dissolution, is a key feature of the psychedelic experience and acute psychosis. This study aimed to validate the Ego-Dissolution Inventory (EDI), a new 8-item self-report scale designed to measure ego-dissolution. Additionally, we aimed to investigate the specificity of the relationship between psychedelics and ego-dissolution. Method: Sixteen items relating to altered ego-consciousness were included in an internet questionnaire; 8 relating to the experience of ego-dissolution (comprising the EDI), and 8 relating to (...) the antithetical experience of increased self-assuredness. Items were rated using a visual analogue scale. Participants answered the questionnaire for experiences with classical psychedelic drugs, cocaine or alcohol. They also answered the 7 questions from the Mystical Experiences Questionnaire (MEQ) relating to the experience of unity with one’s surroundings. Results: 691 participants completed the questionnaire, providing data for 1828 drug experiences (1043 psychedelics. 377 cocaine. 408 alcohol). Exploratory factor analysis demonstrated that the 8 EDI items loaded exclusively onto a single common factor, which was orthogonal to a second factor comprised of the items relating to increased self-assuredness (rho= -.110), demonstrating discriminant validity. The EDI correlated strongly with our measure of unitive experience (rho =.735), demonstrating convergent validity. EDI internal consistency was excellent (Cronbach’s alpha 0.93). Three analyses confirmed the specificity of ego-dissolution for experiences occasioned by psychedelic drugs. Firstly, EDI score correlated with drug-dose for psychedelic drugs (rho=.371), but not for cocaine (rho=.115) or alcohol (rho=-0.055). Secondly, the linear regression line relating the subjective intensity of the experience to EDI was significantly steeper for psychedelics (unstandardized B coefficient= 0.701) compared with cocaine (0.135) or alcohol (0.144). Finally, a binary support vector machine classifier identified experiences occasioned by psychedelic drugs vs. cocaine or alcohol with over 85% accuracy using ratings of ego-dissolution and ego-inflation alone. Conclusions: Our results demonstrate the psychometric structure, internal consistency and construct validity of the EDI. Moreover, we demonstrate the close relationship between ego-dissolution and the psychedelic experience. The EDI will facilitate the study of the neuronal correlates of ego-dissolution, which is relevant for psychedelic-assisted psychotherapy and our understanding of psychosis. (shrink)

The annual volume of ethics consultations (ECs) has been a topic of interest in the bioethics literature, in part because of its presumed relationship to quality. To better understand factors associated with EC volume, we used multiple linear regression to model the number of case consultations performed in the last year based on a national survey. We found that hospital bed size, academic affiliation, and urban/rural location were all associated with EC volume, but were not the primary drivers. Instead, (...) these variables affected EC volume through three other variables, all of which relate to ethics staffing: the percentage of case consultations performed by a single individual; whether the survey respondent’s main role at the hospital contained the word “ethics”; and especially, the number of full-time ethics program staff. We conclude that EC is an example of supply-sensitive care, and further research is needed to determine the optimal level of EC activity. (shrink)

Purpose: The cost of capital is a critical factor influencing investment decisions and company financing. Sustainability reporting also enhances the strategic and organizational legitimacy of companies. Therefore, it is expected that sustainability reporting can influence company legitimacy with enhancing trust of companies, their capital costs is reduced. Based on this premise, the objective of this research is to investigate the impact of sustainability reporting on the cost of capital of companies listed on the Iraq Stock Exchange. Method: for testing of (...) hypothesis Data from 33 listed companies on the Iraq Stock Exchange during the company's period of 2012-2022 was collected and analyzed using a multiple linear regression approach with a combination of panel data analysis. Result: Our findings indicate that Iraqi firms experience higher costs of capital due to their weak implementation of sustainability reporting. Conclusion: reporting on corporate sustainability activities can enhance reputation of companies and, by gaining legitimacy for the companies, their cost of capital is reduced. Implication: These findings can inform policymakers about the need to strengthen requirements for sustainability reporting. Also help investor to form an optimal portfolio based on the policy of companies in compliance with the sustainability reporting. (shrink)

In this study, we examined the perception of actual and ideal ethical climate type among 95 nurses working in the internal medicine wards of one central hospital in the state of Israel. We also examined whether nurses’ demographic characteristics influence that perception and if a relationship between perceptions of an actual and an ideal ethical climate type influences nurses’ job satisfaction. A questionnaire composed of three subquestionnaires was administered and the responses analyzed using multiple linear regressions, analysis of variance and (...) Pearson’s correlation coefficient. The results demonstrated that demographic characteristics (such as: gender, job tenure and level of education) partially influence the perception of an ideal ethical climate. Incongruence in perceptions of ‘caring’ and ‘independence’ climate types indicated a decline in nurses’ job satisfaction, while perception of actual ‘caring’ and ‘service’ climates positively influenced all aspects of job satisfaction. We recommend constructing training programs emphasizing the ethics of nursing practice and also to help lead nurses to clarify an ethical framework and guide nursing staff in dealing with ethical dilemmas. (shrink)

This paper examines whether a firm’s financial performance is associated with superior environmental, social and governance scores in emerging markets of multinationals in Latin America. The study addresses the current research gap on this issue; it develops hypotheses and tests them by applying linear regressions with a data panel drawn from the Thomson Reuters Eikon™ database to analyse data on 104 multinationals from Brazil, Chile, Colombia, Mexico and Peru between 2011 and 2015. The results suggest that the relationship between the (...) ESG score and FP is significantly statistically negative. Furthermore, in examining environmental, social and governance separately to accurately determine each variable’s relationship to multilatinas’ FP, the results reveal a negative relationship. Finally, the empirical analysis provides evidence for a moderating effect of financial slack and geographic international diversification on the relationship between ESG dimensions and firms’ FP. This study furthers understanding of the relationship between ESG dimensions and FP for the Latin American business context. (shrink)

The magnitude of public concerns about agricultural innovations has often been underestimated, as past examples, such as pesticides, nanotechnology, and cloning, demonstrate. Indeed, studies have proven that the agricultural sector presents an area of tension and often attracts skepticism concerning new technologies. Digital technologies have become increasingly popular in agriculture. Yet there are almost no investigations on the public acceptance of digitalization in agriculture so far. Our online survey provides initial insights to reduce this knowledge gap. The sample represents the (...) German population in terms of gender, age, education and size of place of residence. Results showed that if the potential of digital farming technologies regarding animal welfare and environmental protection was described, respondents reacted positively. Thus, the general attitudes of respondents toward the benefits of DFT were mostly positive. The approval to increasing adoption rates of particular DFT by providing subsidies was also high. Linear regression models showed that the dominant positive influences on respondents’ attitudes toward the benefits of DFT were a generally positive attitude toward farming and a strong trust in farmers in Germany. Confronting respondents with pictures showing DFT resulted in many spontaneous negative associations and general criticism of agricultural production. The latter holds true for DFT in animal husbandry in particular. However, as agriculture as a whole is criticized by many groups in Germany, it is unlikely that benefits from digitalization will significantly increase the public acceptance of agriculture as a whole. (shrink)

Background: Moral distress is considered to be the negative feelings that arise when one knows the morally correct response to a situation but cannot act because of institutional or hierarchal constraints. Objectives: To analyze moral distress and its relation with sociodemographic and academic variables in undergraduate students from different universities in Brazil. Method: Quantitative study with a cross-sectional design. Data were collected through the Moral Distress Scale for Nursing Students, with 499 nursing students from three universities in the extreme south (...) of Brazil answering the scale. The data were analyzed in the statistical software SPSS version 22.0, through descriptive statistical analysis, association tests (t-test and analysis of variance), and linear regression models. Ethical considerations: Approval for the study was obtained from the Research Ethics Committee at Universidade Federal do Rio Grande. Findings: The mean intensity of moral distress in the constructs ranged from 1.60 to 2.55. As to the occurrence of situations leading to moral distress in the constructs, the frequencies ranged from 1.21 to 2.43. The intensity level of moral distress showed higher averages in the more advanced grades of the undergraduate nursing course, when compared to the early grades of this course (between 5 and 10 grade, average = 2.60–3.14, p = 0.000). Conclusion: The demographic and academic characteristics of the undergraduate nursing students who referred higher levels of moral distress were being enrolled in the final course semesters, were at a federal university, and had no prior degree as an auxiliary nurse/nursing technician. (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)

In clinical practice, evidence suggests that teaching ethics using normative ethical theory has little influence on the ethical actions of providers in practice. Thus, new training methods are needed that improve clinician response to ethical problems. A sensemaking approach to ethics training has demonstrated promise as an evidence-based pedagogical method to improve ethical reasoning and response. Project ECHO is theoretically linked to improved sensemaking. This study examines the effectiveness of ECHO and training in use of sensemaking approaches to ethical response (...) by clinicians. A quasi-experimental design study using univariate linear regression was used to examine the effect of the three types of ethics training on ethical response self-efficacy scores, while controlling for participant characteristics of years in practice, discipline and sex. We found evidence that training in sensemaking through participation in ECHO promotes improved ethical response self-efficacy of clinicians. However, results also suggest that a traditional ECHO format that does not explicitly introduce sensemaking strategies into the training does not result in the same learning outcomes as measured through an ethical response self-efficacy survey. This study found important preliminary results to support use of sensemaking approaches in clinical ethics training. (shrink)

The main purpose of this paper is to investigate the role of social and emotional learning skills and resilience in explaining mental health in male and female adolescents, during the COVID-19 pandemic. Three self-report questionnaires were administered to 778 participants aged between 11 and 16 years and recruited from 18 schools in Northern Italy. The SSIS-SELb-S and the CD-RISC 10 assessed SEL and resilience skills respectively, while the Strengths and Difficulties Questionnaire was used to measure mental health in terms of (...) internalizing problems, externalizing problems, and prosocial behavior. We found that SEL and resilience skills were positively and significantly associated with each other, negatively associated with internalizing and externalizing problems, and positively related to prosocial behavior. Three linear regression analyses showed the significant role of resilience, age, and gender in explaining the variance of internalizing problems; the significant role of SEL skills, resilience, age, and gender in explaining the variance of externalizing problems; and the role of SEL skills, age, and gender in explaining prosocial behavior. Importantly, we found that resilience fully mediated the relationship between SEL skills and internalizing problems, partially mediated the relationship between SEL skills and externalizing problems and didn't mediate the relationship between SEL skills and prosocial behavior. The paper concludes with a discussion of the limitations of the study as well as its practical implications. (shrink)

Resilience factors have been suggested as key mechanisms in the relation between symptoms and disability among individuals with chronic pain. However, there is a need to better operationalize resilience and to empirically evaluate its role and function. The present study examined psychological flexibility as a resilience factor in relation to symptoms and functioning among 252 adults with chronic pain applying for participation in a digital ACT-based self-help treatment. Participants completed measures of symptoms (pain intensity, anxiety), functioning (pain interference, depression), as (...) well as the hypothesized resilience factor psychological flexibility (measured as avoidance, value obstruction, and value progress). As expected, symptoms, functioning and resilience factors were significantly associated. Hierarchical linear regression analyses showed that psychological flexibility significantly contributed to the prediction of pain interference and depression when adjusting for age, pain and anxiety. Also, participants with low levels of psychological flexibility were more likely to be on sick leave. Furthermore, a series of multiple mediation analyses showed that psychological flexibility (avoidance, value obstruction, value progress) had a significant indirect effect on the relationship between symptoms and functioning. Avoidance was consistently shown to contribute to the indirect effect. Results support previous findings and suggest the importance of psychological flexibility as a resilience factor among individuals with chronic pain and anxiety. (shrink)

In this paper I present both a critical appraisal of Humphreys' probabilistic theory of causality and a sketch of an alternative view of the relationship between the notions of probability and of cause. Though I do not doubt that determinism is false, I claim that the examples used to motivate Humphreys' theory typically refer to subjective rather than objective chance. Additionally, I argue on a number of grounds that Humphreys' suggestion that linear regression models be used as a canonical (...) form for the description of causal relations is untenable. I conclude by exploring the variety of ways in which probabilistic elements can be embedded into the structure of causal mechanisms. This investigation suggests both that deterministic mechanisms can produce stochastic behavior and stochastic mechanisms can produce deterministic behavior. Note: Link is to the article in a subscription database available to users affiliated with Butler University. Appropriate login information will be required for access. Users not affiliated with Butler University should contact their local librarian for assistance in locating a copy of this article. (shrink)

Background The Covid-19 pandemic has impacted compassion fatigue and the mental health of health care providers, particularly midwives and nurses. Although there are studies involving health workers such as nurses and physicians affected by the pandemic’s compassion fatigue, few studies include midwives. Research objective The present study seeks to investigate the effects of compassion fatigue experienced by midwives working under intense stress during the third wave of the COVID-19 pandemic on the level of moral sensitivity. Research design This is a (...) descriptive-correlation study. Participants The statistical population consisted of all the midwives in Türkiye hospitals in 2021. This cross-sectional study was collected through a questionnaire using convenience sampling. Three hundred and ten midwives working in different units of the country participated in the study. Ethical considerations Approval from the researcher’s university Institutional Review Board for ethical review was obtained with the code of IRB 20/510. Findings The average age of the midwives is 34.29 ± 8.39. It has been noticed that 43.5% of the midwives work in public hospitals and 38.1% in family health and community health centers. Midwives’ mean MR-CS score is 67.11 ± 25.13, secondary trauma sub-dimension average 15.77 ± 6.23, and occupational burnout sub-dimension 40.69 ± 16.35. The mean moral sensitivity questionnaire score is determined as 93.86 ± 19.51. It has been observed that the working style and working time are effective on compassion fatigue. In the linear regression model, 98% of compassion fatigue was explained. Age, secondary trauma, and occupational burnout sub-dimensions affect the model. Discussion Working year, working style, second trauma, age, and occupational burnout parameters may help explain some of the links between midwives’ symptoms of compassion fatigue. Conclusion The pandemic affects the compassion fatigue of midwives. It is crucial to provide social support to midwives and health workers to prevent compassion fatigue and examine and control groups at risk in mental health. (shrink)

Literature on ethical behavior has paid little attention to the mechanism between macro-environmental variables and environmental performance. This study aims at constructing a model to examine the relationships which link cultural values, population growth, economic development, and environmental performance by incorporating the mediating role of education. The multiple linear regression model was employed to test the hypotheses on a 3-year-pooled sample of 51 countries. Empirical results conclude that national culture, economic development, and population growth would significantly influence environmental performance (...) directly. In addition, through the mediating effect of education, population growth and national culture would significantly affect environmental performance indirectly. These findings provide theoretical and managerial implications for constructing the mechanism of cultural values and ethical behavior in general and environmental management in particular. (shrink)

This research paper explores the implications of emotional intelligence and the Big Five personality model on virtual team effectiveness. It illustrates how emotional intelligence and Big Five personality traits help team members better understand interpersonal relationships and develop constructive virtual teams. The widespread use of virtual team meetings for collaborative work over in-person interaction with diverse personalities creates discord and trust among team members, limiting overall productivity. A quantitative analysis approach is used, with hypotheses tested and a series of multiple (...) linear regression analyses performed on data collected from relevant industries using convenient sampling. The findings show that the Big Five personality affects the virtual team's trust and collaboration parameters. However, the relationship between personality traits and team effectiveness is mediated by emotional intelligence. Also, it is explored that having control over emotional intelligence or developing emotional intelligence would improve team performance while managing and working with a diverse group of people. (shrink)

The ongoing COVID-19 pandemic has taken a significant toll on mental health; people around the world are experiencing high levels of stress and deteriorated wellbeing. The past research shows that positive emotions can help people cultivate a resilient mindset; however, the reality created by the global crisis itself limits the opportunities for experiencing positive emotions. Thus, it is unclear to what extent their effect is strong enough to counter the psychological impact of the current pandemic. Here, the author reports the (...) findings of a survey conducted across two large representative samples in the United Kingdom and the United States during the first wave of the COVID-19 pandemic. A linear regression model revealed that the presence of positive emotions is strongly linked with resilience, in particular for individuals experiencing more negative emotions. These results show that positive emotions are particularly important to mental health in the context of high stress, reflected by increased levels of negative emotional experiences. These results are also consistent with the existential positive psychology perspective, which posits that even negative emotions can contribute to wellbeing once they are transformed. The author discusses the potential of positive emotions to transform suffering and thereby ameliorate the negative impact of the present collective crisis. (shrink)

The development of neuropsychological assessment methods using virtual reality (VR) is a valid and promising option for the detection of cognitive impairment in the older people, focusing on activities composed of tasks of multiple demands. This study verified the association of age, schooling, and general cognitive status on the performance of neurologically healthy older adults in ECO-VR, a virtual reality task of multiple demands for neuropsychological assessment. A total of 111 older adults answered a sociodemographic questionnaire, the Mini Mental State (...) Examination, the Vocabulary subtest of the Wechsler Intelligence Scale for Adults (third edition), and the ECO-VR. Correlation analyses, multiple linear regression, and comparisons between groups (effects by age and schooling groups) were used to evaluate the results. The ECO-VR total score was significantly associated with age, years of education, MMSE, and Vocabulary subtest. The linear regression models identified that age was the main predictor for total score and rule breaking of ECO-VR. According to the univariate analysis, it was identified the main effect of age group and schooling group in the total ECO-VR score, but there was no interaction effect. The results are discussed in order to understand the role of sociodemographic characteristics in the performance of older adults in a virtual reality task of multiple demands. It was also verified the possibility use of virtual reality for neuropsychological assessment of older adults. (shrink)