Significant Factors Influencing Rural Residents’ Well-Being with Regard to Electricity Consumption: An Empirical Analysis in China

The article provides an empirical test of the hypothesis of the influence of the level of economic development of the country on the level of development of its social capital based on panel data analysis. In this study, the Indices of Social Development elaborated by the International Institute of Social Studies under World Bank support are used as an indicators of social capital development as they best meet the requirements for complexity (include six integrated indicators of Civic Activism, Clubs and Associations, Intergroup Cohesion, Interpersonal Safety and Trust, Gender Equality, Inclusion of Minorities), comprehensiveness of measurement, sustainability. In order to provide an empirical analysis, we built a panel that includes data for 20 countries divided into four groups according to the level of economic development. The first G7 countries (France, Germany, Italy, United Kingdom); the second group is the economically developed countries, EU members and Turkey, the third group is the new EU member states (Estonia, Latvia, Lithuania, Romania); to the fourth group – post-Soviet republics (Armenia, Georgia, Russian Federation, Ukraine). The analysis shows that the parameters of economic development of countries cannot be completely excluded from the determinants of social capital. Indicators show that the slowdown in economic growth leads to greater cohesion among people in communities, social control over the efficiency of distribution and use of funds, and enforcement of property rights. The level of tolerance to racial diversity and the likelihood of negative externalities will depend on the change in the rate of economic growth. Also, increasing the well-being of people will have a positive impact on the level of citizens’ personal safety, reducing the level of crime, increasing trust. Key words: social capital, economic growth, determinant, indice of social development.

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Factors Influencing the General Well Being of Adolescents with Health Problems

SSRN Electronic Journal ◽

10.2139/ssrn.3204904 ◽

2018 ◽

Author(s):

A. Nirmala ◽

V. Valarmathi ◽

P. Venkataraman ◽

C. Kanniammal ◽

Judie Arulappan

Keyword(s):

Well Being ◽

Health Problems ◽

Factors Influencing

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Trust in Artificial Intelligence: Meta-Analytic Findings

Human Factors The Journal of the Human Factors and Ergonomics Society ◽

10.1177/00187208211013988 ◽

2021 ◽

pp. 001872082110139

Author(s):

Alexandra D. Kaplan ◽

Theresa T. Kessler ◽

J. Christopher Brill ◽

P. A. Hancock

Keyword(s):

Artificial Intelligence ◽

Empirical Research ◽

Meta Analysis ◽

Automated Vehicles ◽

Factors Influencing ◽

Moderating Factors ◽

Shared Context ◽

Build Systems ◽

Significant Factors

Objective The present meta-analysis sought to determine significant factors that predict trust in artificial intelligence (AI). Such factors were divided into those relating to (a) the human trustor, (b) the AI trustee, and (c) the shared context of their interaction. Background There are many factors influencing trust in robots, automation, and technology in general, and there have been several meta-analytic attempts to understand the antecedents of trust in these areas. However, no targeted meta-analysis has been performed examining the antecedents of trust in AI. Method Data from 65 articles examined the three predicted categories, as well as the subcategories of human characteristics and abilities, AI performance and attributes, and contextual tasking. Lastly, four common uses for AI (i.e., chatbots, robots, automated vehicles, and nonembodied, plain algorithms) were examined as further potential moderating factors. Results Results showed that all of the examined categories were significant predictors of trust in AI as well as many individual antecedents such as AI reliability and anthropomorphism, among many others. Conclusion Overall, the results of this meta-analysis determined several factors that influence trust, including some that have no bearing on AI performance. Additionally, we highlight the areas where there is currently no empirical research. Application Findings from this analysis will allow designers to build systems that elicit higher or lower levels of trust, as they require.

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Demographic and psychological predictors of alcohol use and misuse in autistic adults

Autism ◽

10.1177/1362361321992668 ◽

2021 ◽

Vol 25 (5) ◽

pp. 1469-1480

Author(s):

Maya Bowri ◽

Laura Hull ◽

Carrie Allison ◽

Paula Smith ◽

Simon Baron-Cohen ◽

...

Keyword(s):

Social Anxiety ◽

Alcohol Use ◽

Online Survey ◽

Autistic Traits ◽

Well Being ◽

Psychological Predictors ◽

Autistic Adults ◽

Mental Well Being ◽

Shaped Pattern ◽

Significant Factors

This study explored demographic and psychological predictors of alcohol use and misuse in a high-functioning, community sample of 237 autistic adults aged 18–75 (mean = 41.92 and standard deviation = 13.3) recruited in the United Kingdom. An online survey measured demographic information, autistic traits, depression, generalised anxiety, social anxiety, mental well-being, social camouflaging and alcohol use with the Alcohol Use Disorders Identification Test. The sample was divided into three groups (non-drinkers, non-hazardous drinkers and hazardous drinkers) and multinomial logistic regression models were used to investigate associations between alcohol use and demographic factors, autistic traits, mental health variables and social camouflaging. Our results demonstrated a U-shaped pattern among autistic adults, with non-drinkers and hazardous drinkers scoring significantly higher than non-hazardous drinkers on levels of autistic traits, depression, generalised anxiety and social anxiety. In multivariate analysis, autistic non-drinkers were less likely to be male (odds ratio = 0.44; 95% confidence interval = 0.22–0.87) and had more autistic traits (odds ratio = 2.50; 95% confidence interval = 1.19–5.28). Gender and level of autistic traits may be the most significant factors in predicting alcohol use in the autistic community. Lay abstract Alcohol use and misuse are associated with a variety of negative physical, psychological and social consequences. The limited existing research on substance use including alcohol use in autistic adults has yielded mixed findings, with some studies concluding that autism reduces the likelihood of substance use and others suggesting that autism may increase an individual’s risk for substance misuse. This study investigated demographic and psychological predictors of alcohol use and misuse in a sample of 237 autistic adults. An online survey was used to obtain data on demographic information, autistic traits, depression, generalised anxiety, social anxiety, mental well-being, social camouflaging and alcohol use. The sample was divided into three groups (non-drinkers, non-hazardous drinkers and hazardous drinkers) in order to investigate associations between alcohol use and demographic factors, autistic traits, mental health variables and social camouflaging. Our results demonstrated a U-shaped pattern among autistic adults, with non-drinkers and hazardous drinkers scoring higher than non-hazardous drinkers on levels of autistic traits, depression, generalised anxiety and social anxiety. Autistic non-drinkers were less likely to be male and had more autistic traits. Gender and level of autistic traits may be the most significant factors in predicting alcohol use in the autistic community.

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Vulnerability context and well-being factors of Indigenous community development: a study of Peninsular Malaysia

AlterNative An International Journal of Indigenous Peoples ◽

10.1177/1177180121995166 ◽

2021 ◽

Vol 17 (1) ◽

pp. 94-105

Author(s):

Md. Khaled Saifullah ◽

Muhammad Mehedi Masud ◽

Fatimah Binti Kari

Keyword(s):

Basic Education ◽

Economic Status ◽

Well Being ◽

Peninsular Malaysia ◽

Indigenous Community ◽

Access To Education ◽

Environmental Aspects ◽

The Social ◽

To Receive ◽

Significant Factors

The Indigenous people of Malaysia are a heterogeneous community scattered over more than 852 villages in Peninsular Malaysia. This community has been identified to be among the poorest and marginalized in Peninsular Malaysia. This study evaluates the well-being factors as well as problems that hinder the development of an Indigenous community in Peninsular Malaysia. This article adopted a quantitative approach based on data collected through survey and 2,136 respondents were interviewed. The study reveals that the Indigenous community is likely to remain poor in terms of economic status significantly because of insufficient access to basic education and the inability of being employed. This is also due to the inability to receive support for housing, economic livelihood, and other social infrastructures. In addition, the study indicates that economic status and access to education are the most significant factors that may help improve the overall well-being of an Indigenous community. This finding also suggests that the social and environmental aspects in Peninsular Malaysia have not improved together with economic development.

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Factors influencing individual investors behavior - an empirical analysis from hyderabad city

Materials Today Proceedings ◽

10.1016/j.matpr.2021.01.231 ◽

2021 ◽

Author(s):

Sowmya Kethi Reddi ◽

Sai Nikhila Vangaveti

Keyword(s):

Empirical Analysis ◽

Individual Investors ◽

Factors Influencing

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Factors Affecting Secondary Traumatic Stress of Nurses Caring for COVID-19 Patients in South Korea

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18136843 ◽

2021 ◽

Vol 18 (13) ◽

pp. 6843

Author(s):

Mee Sun Lee ◽

Sujin Shin ◽

Eunmin Hong

Keyword(s):

Social Support ◽

Regression Analysis ◽

Traumatic Stress ◽

Secondary Traumatic Stress ◽

Direct Care ◽

Hierarchical Regression ◽

Factors Affecting ◽

Factors Influencing ◽

Affect Patient Care ◽

Significant Factors

The secondary traumatic stress (STS) of nurses caring for COVID-19 patients is expected to be high, and it can adversely affect patient care. The purpose of this study was to examine the degree of STS of nurses caring for COVID-19 patients, and we identified various factors that influence STS. This study followed a descriptive design. The data of 136 nurses who had provided direct care to COVID-19 patients from 5 September to 26 September 2020 were collected online. Hierarchical regression analysis was conducted to identify the factors influencing STS. Participants experienced moderate levels of STS. The regression model of Model 1 was statistically significant (F = 6.21, p < 0.001), and the significant factors influencing STS were the duration of care for patients with COVID-19 for more than 30 days (β = 0.28, p < 0.001) and working in an undesignated COVID-19 hospital (β = 0.21, p = 0.038). In Model 2, the factor influencing STS was the support of a friend in the category of social support (β = −0.21, p = 0.039). The nurses caring for COVID-19 patients are experiencing a persistent and moderate level of STS. This study can be used as basic data to treat and prevent STS.

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Individual Condensation Trails in Aircraft Trajectory Optimization

Sustainability ◽

10.3390/su11216082 ◽

2019 ◽

Vol 11 (21) ◽

pp. 6082 ◽

Cited By ~ 3

Author(s):

Judith Rosenow ◽

Hartmut Fricke

Keyword(s):

Global Warming ◽

Trajectory Optimization ◽

Wind Shear ◽

Impact Factors ◽

Factors Influencing ◽

Order Of Magnitude ◽

Aircraft Trajectory ◽

The Impact ◽

Arbitrary Trajectory ◽

Significant Factors

Contrails are one of the driving contributors to global warming, induced by aviation. The quantification of the impact of contrails on global warming is nontrivial and requires further in-depth investigation. In detail, condensation trails might even change the algebraic sign between a cooling and a warming effect in an order of magnitude, which is comparable to the impact of aviation-emitted carbon dioxides and nitrogen oxides. This implies the necessity to granularly consider the environmental impact of condensation trails in single-trajectory optimization tools. The intent of this study is the elaboration of all significant factors influencing on the net effect of single condensation trails. Possible simplifications will be proposed for a consideration in single-trajectory optimization tools. Finally, the effects of the most important impact factors, such as latitude, time of the year, and time of the day, wind shear, and atmospheric turbulence as well as their consideration in a multi-criteria trajectory optimization tool are exemplified. The results can be used for an arbitrary trajectory optimization tool with environmental optimization intents.

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