scholarly journals Does a University’s Enslavement History Play a Role in Black Student–White Faculty Interactions? A Structural Equation Model

2021 ◽  
Vol 11 (12) ◽  
pp. 809
Author(s):  
Juan C. Garibay ◽  
Christopher Mathis
Keyword(s):  
Structural Equation ◽  
Research Policy ◽  
Emotional Responses ◽  
Racial Microaggressions ◽  
Equation Model ◽  
Black College ◽  
Equation Modeling ◽  
Policy And Practice ◽  
White Faculty ◽  
History Play

Drawing upon Hartman’s (1997) notion of the afterlife of slavery and Critical Race Quantitative Inquiry, this study examines whether Black college students’ emotional responses to their institution’s history of slavery plays a role in contemporary interactions with white faculty. Using structural equation modeling techniques on a sample of 92 Black students from a southern U.S. institution historically involved in slavery, findings highlight the significance of background characteristics, students’ emotional responses to their institution’s slavery history, and experiences with racial microaggressions during college in predicting negative interactions with white faculty. Implications for research, policy, and practice are discussed.

Examining Psychosociocultural Influences as Predictors of Black College Students’ Academic Self-Concept and Achievement

2020 ◽  
pp. 009579842097979
Author(s):  
Samuel T. Beasley ◽  
Shannon McClain
Keyword(s):  
College Students ◽  
Academic Engagement ◽  
Structural Equation ◽  
Black College ◽  
Self Concept ◽  
Equation Modeling ◽  
Black College Students ◽  
Grade Point ◽  
Racial Centrality ◽  
Positive Direct

Using the psychosociocultural framework, this study concurrently examined the influence of psychological (academic self-concept and academic engagement attitudes), social (caring student-faculty relationships), and cultural variables (racial centrality and perceived university environment) on the academic achievement of Black college students. Participants were 247 Black collegians recruited from a large, Southwestern predominately White institution. Results of structural equation modeling largely supported hypothesized relationships between variables, accounting for 16% of the variance in grade point average (GPA), 75% of the variance in academic engagement, and 29% of the variance in academic self-concept. Results revealed two positive direct paths to GPA: (a) racial centrality and (b) academic self-concept; academic self-concept had a key role in facilitating indirect effects on academic engagement and GPA. Findings highlight multiple noncognitive predictors that can facilitate Black students’ academic functioning. Research and practice implications of these findings are outlined.

Researchers’ awareness about plagiarism and impact of plagiarism detection tools – does awareness effect the actions towards preventing plagiarism?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sk. Mamun Mostofa ◽  
Mashiat Tabassum ◽  
S.M. Zabed Ahmed
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Personal Characteristics ◽  
Equation Model ◽  
Equation Modeling ◽  
Plagiarism Detection ◽  
Chi Square ◽  
Content Type ◽  
Reported Study ◽  
Chi Square Test

Purpose This paper aims to analyse researchers’ awareness about plagiarism and impact of plagiarism detection tools on the actions that they take to prevent plagiarism. It also employs a structural model that examines whether awareness of plagiarism and anti-plagiarism tools have any significant effect on the actions taken by the researchers to avoid plagiarism. Design/methodology/approach A survey questionnaire was distributed to researchers at a large public university in Bangladesh. The survey accumulated 184 valid responses. Descriptive statistics were obtained to assess researchers’ awareness about plagiarism and impact of plagiarism detection tools and the actions taken by them. The reasons that may cause plagiarism were also identified. The awareness of the availability of the anti-plagiarism software that was being used by the university and its actual use by the researchers was gathered through the survey. Non-parametric Mann–Whitney and Kruskal–Wallis tests were conducted to investigate the differences in awareness levels and actions in terms of gender, age, discipline and current level of research. The chi-square test was carried out to examine the relationship between awareness about the availability of the anti-plagiarism software and its use by the researchers. Finally, the survey data were analysed using structural equation modeling to examine the effects of awareness of plagiarism and anti-plagiarism software on the actions taken by the researchers. Findings The study revealed that the level of awareness regarding plagiarism and impact of plagiarism detection software is generally high among the researchers. There are some significant differences between researchers’ demographic and personal characteristics and their awareness levels and actions with regard to plagiarism. The findings indicate that almost three-quarters of the researchers were aware about the anti-plagiarism tool that is being used, whereas more than half of the researchers indicated that they used the software to assess their works. The results of the structural equation model do not show a good fit, although there is strong statistical evidence that awareness about plagiarism and anti-plagiarism software has significantly impacted researchers’ actions towards preventing plagiarism. Originality/value There is no reported study on researchers’ awareness of plagiarism and its affiliated issues in Bangladesh. The findings of this study will not only provide useful insights regarding awareness about plagiarism but also assist university authorities to formulate relevant policy and take necessary actions against plagiarism in higher education institutions.

Stepfamily Closeness and Depression Among American Indian Emerging Adults: A Structural Equation Modeling Approach

2018 ◽  
Vol 40 (3) ◽  
pp. 267-292 ◽  
Author(s):  
Kaitlin P. Ward ◽  
Gordon E. Limb ◽  
Sarah Higbee ◽  
Helena Haueter
Keyword(s):  
American Indian ◽  
Emerging Adults ◽  
American Indians ◽  
Structural Equation ◽  
The United States ◽  
Equation Model ◽  
Equation Modeling ◽  
Racial Groups ◽  
Biological Parent ◽  
Parent Child

Stepfamilies are one of the fastest growing family structures among all racial groups in the United States. Stepfamily research among many racial groups, specifically American Indians, is virtually nonexistent. This is unfortunate, as American Indians are more likely to divorce and remarry compared with other populations. From a family systems perspective, this study examined whether retrospectively perceived closeness in three stepfamily relationships, namely child–residential biological parent, child–residential stepparent, and child–stepsibling, were negatively associated with depression scores in 226 American Indian emerging adults. A structural equation model showed that increased child–residential biological parent and child–stepsibling closeness predicted decreased depression scores, whereas child–residential stepparent closeness did not. We also found that depression scores significantly predicted retrospective perceptions of child–residential biological parent, child–residential stepparent, and child–stepsibling closeness. Findings encourage interventions that strengthen American Indian child–residential biological parent and child–stepsibling relationships, and underscore the need for further research that explores American Indian stepfamily relationships.

scholarly journals Cyberchondria severity and quality of life among Lebanese adults: the mediating role of fear of COVID-19, depression, anxiety, stress and obsessive–compulsive behavior—a structural equation model approach

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Clara Rahme ◽  
Marwan Akel ◽  
Sahar Obeid ◽  
Souheil Hallit
Keyword(s):  
Quality Of Life ◽  
Structural Equation ◽  
Equation Model ◽  
Mediating Effect ◽  
Equation Modeling ◽  
Obsessive Compulsive ◽  
Online Questionnaire ◽  
Cross Sectional ◽  
Compulsive Disorder

Abstract Background This study highlights the significant association between cyberchondria and quality of life among the Lebanese population in the time of COVID-19. The aim was to assess the association between cyberchondria and quality of life (QOL) of Lebanese community during the COVID-19 pandemic and assess the mediating effect of fear of COVID-19, depression, anxiety, stress and Yale-Brown Obsessive–Compulsive Scale in this association. Methods This cross-sectional study was carried out between December 2020 and January 2021, during the COVID-19 pandemic. A total of 449 persons participated in this study by filling the online questionnaire. Structural equation modeling (SEM) was performed to examine the structural relationship between cyberchondria severity, the mediator (anxiety, stress, depression, obsessive–compulsive disorder (OCD) and fear of COVID-19) and physical/mental QOL. Results Having a university level of education and older age were significantly associated with higher physical QOL scores, whereas higher obsession-compulsion disorder, higher stress and higher anxiety were significantly associated with lower physical QOL scores. Higher anxiety was significantly associated with lower mental QOL scores. The results of the SEM showed that stress, fear of COVID-19 and to a lesser limit OCD, mediated the association between cyberchondria severity and physical QOL, whereas anxiety, stress and fear of COVID-19 mediated the association between cyberchondria severity and mental QOL. Conclusion This research reported interesting results encouraging more exploration of cyberchondria and its association with quality of life during this unique period of the pandemic. However, this virus has altered the lives of individuals all across the world, and the consequences will last for a long time. Along with all of the steps done to stop the development of COVID-19 and improve physical outcomes, mental health requires immediate care. More research is needed to determine the coping techniques people are employing to deal with the pandemic.

scholarly journals THE IMPACT OF PERSONAL PRODUCTIVITY DUE TO THE ATTACKS OF CORONAVIRUS DISEASE 2019: USING PARTIAL LEAST STRUCTURAL EQUATION MODEL

2020 ◽  
pp. 1-4
Author(s):  
SHEKH ABDULLAH-AL-MUSA AHMED ◽  
NIK ZULKARNAEN BIN KHIDZIR ◽  
SHIRIN AFROZ
Keyword(s):  
Structural Equation ◽  
Influence Factor ◽  
Equation Model ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Dependent Variables ◽  
Independent Variable ◽  
Personal Productivity ◽  
The Impact

Global coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease was first identified in December 2019 in Wuhan, the capital of China’s Hubei Province, and has since spread globally, resulting in the ongoing 2019–2020 coronavirus pandemic that has an impact which would be disturbed the personal productivity in the community. The dependent variable which is threat of COVID-19 (Thr_Cov-19), vulnerability of COVID-19 (Vul_Cov-19), and the unexpected change in society factors and one independent variable that is personal disturbance factors is used in this paper. Moreover, using as an indicator which will determine disturbance of personal productivity (D_PP) in the society. Since multiple regression by partial least square-structural equation modeling is used to examined of data by following unstructured method. Moreover, the resulting point out three dependent variables significantly influences on the independent variable of personal productivity in the society. As a matter of fact, this study concludes the foremost influence factor on D_PP in society due to COVID-19 risk factors such as Thr_Cov-19, Vul_Cov-19, and unexpected changed in the society factors. This study contributes to introductory study but vibrant understanding in stimulating the prediction of personal productivity in the society due to the COVID-19 attacks.

scholarly journals Gender roles and dating violence: A mediator role of moral disengagement

2020 ◽  
Vol 10 (2) ◽  
pp. 169-183
Author(s):  
Ahmet Erdem ◽  
Fuad Bakioğlu
Keyword(s):  
Gender Roles ◽  
Dating Violence ◽  
Structural Equation ◽  
Moral Disengagement ◽  
Relevant Literature ◽  
Equation Model ◽  
Equation Modeling ◽  
Mediator Role ◽  
The Relationship

The aim of this study was to investigate the mediator role of moral disengagement in the relationship between gender roles and dating violence. Participants were 425 university students [310 (72.9%) female, 115 (27.1%) male, Mage = 20.68 years, SD = 2.21] who completed questionnaires package involving the Gender Roles Attitudes Scale, the Attitudes toward Dating Violence Scales, and the Moral Disengagement Scale. The data were analyzed using structural equation modeling. A bootstrapping analysis was conducted in order to determine any indirect effects. The results showed that gender roles predicted moral disengagement and dating violence negatively, and that moral disengagement predicted dating violence positively. It was further found that the structural equation model that proposed that gender roles had a direct and an indirect effect through moral disengagement on dating violence was confirmed. The results of the study were discussed in the light of relevant literature, and suggestions for future studies were made.

A structural equation model for big data adoption in the healthcare supply chain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dindayal Agrawal ◽  
Jitender Madaan
Keyword(s):  
Factor Analysis ◽  
Big Data ◽  
Supply Chain ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Model ◽  
Equation Modeling ◽  
Data Governance ◽  
Social Perspective ◽  
Content Type

PurposeThe purpose of this study is to examine the barriers to the implementation of big data (BD) in the healthcare supply chain (HSC).Design/methodology/approachFirst, the barriers concerning BD adoption in the HSC were found by conducting a detailed literature survey and with the expert's opinion. Then the exploratory factor analysis (EFA) was employed to categorize the barriers. The obtained results are verified using the confirmatory factor analysis (CFA). Structural equation modeling (SEM) analysis gives the path diagram representing the interrelationship between latent variables and observed variables.FindingsThe segregation of 13 barriers into three categories, namely “data governance perspective,” “technological and expertise perspective,” and “organizational and social perspective,” is performed using EFA. Three hypotheses are tested, and all are accepted. It can be concluded that the “data governance perspective” is positively related to “technological and expertise perspective” and “organizational and social perspective” factors. Also, the “technological and expertise perspective” is positively related to “organizational and social perspective.”Research limitations/implicationsIn literature, very few studies have been performed on finding the barriers to BD adoption in the HSC. The systematic methodology and statistical verification applied in this study empowers the healthcare organizations and policymakers in further decision-making.Originality/valueThis paper is first of its kind to adopt an approach to classify barriers to BD implementation in the HSC into three distinct perspectives.

The effects of employer SNS motioning on employee perceived privacy violation, procedural justice, and leave intention

2018 ◽  
Vol 118 (6) ◽  
pp. 1153-1169 ◽  
Author(s):  
Hung-Yue Suen
Keyword(s):  
Data Collection ◽  
Procedural Justice ◽  
Social Networking Sites ◽  
Structural Equation ◽  
Intent To Leave ◽  
Equation Model ◽  
Equation Modeling ◽  
Full Time ◽  
Initial Examination ◽  
Content Type

Purpose The purpose of this paper is to propose a model to understand how and when employees’ perceived privacy violations and procedural injustice interact to predict intent to leave in the context of the use of social networking sites (SNSs) monitoring. Design/methodology/approach This study was conducted in a field setting of Facebook to frame the hypotheses in a structural equation model with partial least squares-structural equation modeling. Variables were measured empirically by administering questionnaires to full-time employed Facebook users who had experienced SNS monitoring. Findings The results showed that when an employee believed that he/she had more ability to control his/her SNS information, he/she was less likely to perceive that his/her privacy had been invaded; and when an employee believed that the transparency of the SNS data collection process was higher, he or she was more likely to perceive procedural justice in SNS monitoring. Research limitations/implications This research draws attention to the importance of intent to leave in the absence of perceived procedural justice under SNS monitoring, and the partial mediation of the perception of justice or injustice by perceived privacy violations. Practical implications For employers, the author recommends that employers come to know how to conduct SNS monitoring and data collection with limited risk of employee loss. Social implications For employees, the author suggests that SNS users learn how to control their SNS information and make sure to check their privacy settings on the SNS that they use frequently. Originality/value This study provided an initial examination and bridged the gap between employer use of SNS monitoring and employee reactions by opening a mediating and moderating black box that has rarely been assessed.

scholarly journals Factors Influencing Farmer Willingness to Reduce Aggression between Pigs

Animals ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Rachel Peden ◽  
Faical Akaichi ◽  
Irene Camerlink ◽  
Laura Boyle ◽  
Simon Turner
Keyword(s):  
Animal Welfare ◽  
Structural Equation ◽  
Equation Model ◽  
Growing Pigs ◽  
Mitigation Strategies ◽  
Equation Modeling ◽  
Attitudes And Practices ◽  
Farmer Behavior ◽  
Relevant Stakeholder ◽  
Research Findings

Aggression between pigs remains an important animal welfare issue despite several solutions existing. Uptake of livestock welfare research relies on various stakeholders being willing to recommend or adopt changes to farm structure or management (e.g., veterinarians, researchers, farmers). This survey provides insight into the attitudes and practices of 122 UK and Irish pig farmers regarding aggression between growing pigs. Our aim was to understand why mitigation strategies are not adequately implemented. The majority of farmers mixed pigs at least once during production and had tried at least one mitigation strategy in the past. Farmers expressed limited willingness to implement strategies in the future, and a structural equation model revealed that this was directly influenced by their beliefs about the outcome of controlling aggression, and their perception of their ability to implement the necessary changes. Willingness was indirectly influenced by their perceptions of aggression as a problem and views of relevant stakeholder groups. Veterinarians had the greatest impact on farmer behavior. We recommend that researchers test research findings in practice, calculate cost-benefits of implementation, and transfer knowledge through various sources. This study showed that structural equation modeling is a valuable tool to understand farmer behavior regarding specific and entrenched animal welfare issues.

Analysis of Elderly Mobility by Structural Equation Modeling

2003 ◽  
Vol 1854 (1) ◽  
pp. 81-89 ◽  
Author(s):  
Sungyop Kim
Keyword(s):  
Structural Equation Model ◽  
Urban Form ◽  
Structural Equation ◽  
Elderly Population ◽  
Puget Sound ◽  
The Elderly ◽  
Equation Model ◽  
Education Level ◽  
Equation Modeling ◽  
Elderly Mobility

Mobility is a critical element of quality of life. This is as true for the elderly population as for the larger population. The elderly often have limited physical abilities and financial constraints that might reduce their mobility. Helping the growing elderly population to maintain decent mobility is a critical challenge for transportation planning and policy. For this, the factors that influence the mobility of the elderly population (elderly mobility) must be understood. Only a few systematic studies, however, have been published. Descriptive statistics of the potentially influential factors make it difficult to assess their effects on elderly mobility. The transportation mobility of retired people age 65 years or older in the Puget Sound region of Washington State was analyzed by using a structural equation model. The statistical significance and relative effects of various personal and household characteristics and urban form on elderly mobility were tested. The structural equation model finds statistically significant relationships between age, gender, transportation disability, possession of a driver's license, and education level and elderly mobility. Among these variables, age and education level show the strongest effects. Urban form, however, seems to be insignificant.

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