Structural Equation Modeling Model Research Articles

Impact of the customary law on the implementation of land use rights of Bana ethnic minority in Vinh Thanh district, Binh Dinh province

The study was conducted to test the impact of customary law on the exercise of land use rights of ethnic minorities. The research model of the paper is the linear structural equation model (SEM). The method of partial least squares (PLS) tests the SEM model with 124 survey samples of households and individuals of the Bana ethnic group in Vinh Thanh District, a mountainous district in West Northern Binh Dinh Province, Vietnam. The research results show many differences between customary law and law in implementing land use rights of the Bana ethnic minorities, leading to transactions on land use rights of the Bana ethnic group not being registered at the state agency. The research results confirm a robust relationship between customary law and the exercise of land use rights of ethnic minorities. This relationship is shown through the significance level of the research model achieved at 1%; the coefficient β for evaluating the relationship between customary law and the exercise of land use rights is 0.458. The estimated path coefficient close to +1 indicates a strong positive relationship. The research results provide some suggestions for further integrating customary law into the law in implementing and developing land law policies to improve the efficient implementation of land use rights for ethnic minorities.

RELATIONSHIP OF SOCIAL SUPPORT AND SOCIAL ENGAGEMENT WITH COGNITION IN AN ETHNICALLY DIVERSE OLDER POPULATION

Abstract One quarter of older adults in the U.S. are socially isolated; far more experience subjective loneliness. The potentially negative effects of limited social support and social engagement pose a concern for maintaining the well-being of older individuals, including the effect on cognitive function. To test the hypothesis that cognitive function is associated with social support and social engagement, we employed structural equation modeling (SEM) to analyze data from an ethnically diverse sample (118 African American, 147 Afro-Caribbean, 133 Hispanic, and 235 European American) of 623 community-dwelling older adults age ≥ 65 (173 male, 450 female). Using the model proposed by Cenè et al. (2022), we conceptualized level of social support and engagement as the exposure, emotional state (anxiety, depression, general emotional well-being), and physical function (functional activity, life space, general physical function, and self-rating of health) as mediators and cognitive function as the outcome of interest. Statistically significant direct and indirect effects were found between the three latent variables (emotional state, physical function, and social support and social engagement), indicating that the level of social support and engagement the older individual is related directly and indirectly to cognition (β=-.75, SE=.49, p<.028; β=-0.08, SE=0.795, p=0.017). The SEM models showed goodness of fit with χ2/df=3.001, CFI=0.931, AGFI=0.966, SRMR=0.045, and RMSA=0.058, and explained 35.3% of the variability. These values support the hypothetical model. Results suggest the importance of maintaining existing social support and engagement activities as well as development and testing of approaches to increase social support and engagement in later life.

The Influence of Halal Certification, Halal Awareness, and Brand Image on Interest in Buying Halal Food Products: An Empirical Study of Consumers in Indonesia

This study aims to determine the effect of variables on halal certification, halal awareness, brand image, and intention to buy halal food products. This research is a study of consumers of halal products. The data in this study were obtained by distributing online questionnaires to respondents who were consumers of halal products in Indonesia. The quantitative approach uses surveys as primary data and data analysis using structural equation modelling (SEM). Respondents in this study were consumers of halal products, with a total of 480 respondents who were consumers of halal food products. The method used in the sampling of respondents was purposive sampling with the criteria of having bought halal food. Collecting data by using research instruments, data analysis is quantitative. The data analysis method used in this study uses descriptive analysis to identify characteristics and the Structural Equation Modeling (SEM) analysis method with SmartPLS 3.2.6 software. The analysis in the SEM model can be divided into two stages, namely, the measurement model and the structural analysis model. The results showed that halal certification has a positive effect on purchase intention. Halal certification has a positive effect on brand image. Brand image has a positive effect on purchase intention. Halal awareness has a positive effect on purchase intention. Halal certification positively and significantly affects purchase intention through brand image.

Interactive synchrony and infants' vagal tone as an index of emotion regulation: associations within each mother- and father-infant dyad and across dyads.

Studies have shown that infants' emotion regulation capacities are closely linked to the quality of parent-infant interactions. However, these links have been mostly studied in mother-infant dyads and less is known about how the quality of father-infant interactions contributes to the development of emotion regulation during infancy. In this study, we aimed to investigate the links between interactive synchrony (i.e., an index of the quality of parent-infant coordination of interactive behaviors) and infants' vagal tone (i.e., a physiological index of emotion regulation). To understand the respective contributions of both parents, as well as the interrelations between the functioning of both dyads within a family, we observed mothers and fathers from 84 families interacting with their infants. Synchrony was assessed by using the CARE-Index; infants' vagal tone was derived from the analysis of infants' electrocardiograms recorded during the interactions. Moreover, to take the play's order into account, we counterbalanced the procedure, so that approximately half of the mothers played first. We specified a first structural equation modeling (SEM) model to investigate the associations between interactive synchrony and the infants' root mean square of successive differences (RMSSD), an index of vagal regulation, in the two successive parts of the play. We conducted a multigroup analysis in a second SEM model to investigate the associations of the first SEM model in two groups based on the order of interaction. The results of the SEM models showed that greater synchrony was related to greater infant RMSSD within mother-infant dyads and across one dyad to the other dyad in the full sample and in the group of fathers who interacted first with the infants. The associations between synchrony and infant vagal tone within father-infant dyads never appeared to be significant, nor did any associations within each dyad and across dyads when mothers interacted first. This study highlights that the links between interactions and infants' vagal tone are sensitive to family members' interdependencies and some conditions (the order of interaction).

SIMULATION STUDY FOR UNDERSTANDING THE PERFORMANCE OF PARTIAL LEAST SQUARES–MODIFIED FUZZY CLUSTERING (PLSMFC) IN FINDING GROUPS UNDER STRUCTURAL EQUATION MODEL

In structural equation modeling (SEM), it is usually assumed that all observations follow only one model. This becomes irrelevant if the observations contain natural groups, each of which has a different SEM model. Mukid et al (2002) have proposed the partial least squares-modified fuzzy clustering method (PLSMFC) as a way to find groups of observations and at the same time estimate the parameters of the SEM model. This research aims to understand the performance of the PLSMFC method in finding groups of observations characterized by different forms of structural equation models. The goal was achieved by conducting a simulation study involving factors such as SEM model specification and number of clusters. The procedure used is to force the generated data into a different number of segments. The segment validity measures used are the fuzziness performance index (FPI) and normalized classification entropy (NCE). The correct number of segments is indicated by the smallest FPI and NCE values. Based on simulation studies, it is known that the PLSMFC method can detect segments accurately, especially if the size of the segments used to reallocate observations is larger than the number of segments used to generate the data.

Validation of the Chinese version of academic goals orientation questionnaire in nursing student: a study based on SEM and IRT multidimensional models

ObjectiveTo translate the Academic Goals Orientation Questionnaire (AGOQ) into Chinese and to determine the validity and reliability of the (AGOQ) in Chinese nursing students based on SEM and IRT multidimensional models.MethodsThe participants were 654 nursing students with an age range of 17–26 years (mean age 21.61 ± 1.73 years). The psychometric properties of AGOQ were investigated based on a dual analytical perspective of structural equation modeling (SEM) and item response theory (IRT).ResultsThe Cronbach’s α value of the questionnaire is 0.895. A four-factor model was obtained by exploratory factor analysis, which explained the variance of 71.892%. With confirmatory factor analysis, a new four-factors model was built and showed an acceptable goodness-of-fit, chi-square/degree of freedom (CMIN/DF) = 4.008, goodness of fit index (GFI) = 0.932, adjusted goodness of fit index (AGFI) = 0.905, comparative fit index (CFI) = 0.952, incremental fit index (IFI) = 0.952, Tucker Lewis index (TLI) = 0.941. In the analysis part of IRT, according to the comparison between Akek’s information criterion (AIC) and Bayesian information criterion (BIC), we choose the Graded Response Model (GRM) for analysis. The results show that the difficulty value is monotonically increasing, and the discrimination of all items is greater than 0.19, which shows that 16 items can be retained.ConclusionsThis study tested the psychometric characteristics of AGOQ of nursing students in China. The results confirmed that the Chinese version of AGOQ has good psychometric characteristics and can be used to measure the academic goal orientation of nursing students in China.

Health literacy, worry about unmet needs for medical care, and psychological well-being among older Chinese adults.

This study aims to examine the relationship between older adults' health literacy and their psychological well-being and the role of worry about future unmet needs for medical care in mediating this relationship. We adopted a sample of 965 older Chinese people aged 60+ (49.74% female) from the 2021 Chinese General Social Survey. A series of structural equation models (SEMs) were performed. Health literacy was measured by three items regarding older people's ability to understand medical professionals, ask them questions, and read medical instructions. A single-item question was adopted to measure participants' worry about unmet needs for future medical care. Psychological well-being was measured by three items regarding emotional problems and depressed or anxious mood in the past 4 weeks. Worry about future unmet needs for medical care mediates the relationship between lack of health literacy and Chinese older people's psychological well-being. The indirect effect accounts for 22.3% of the total effect. The SEM model has a satisfactory model fit (goodness of fit index = 1.000, comparative fit index = 0.999, Tucker-Lewis index = 0.997, root mean square error of approximation = 0.009, standardized root mean square residual = 0.023, chi-square test = 50.96, P = 0.321). The findings of this study underscore the importance of improving communication quality between healthcare providers and older adults. Clinical interventions that promote health literacy and address worries about unmet needs for medical services may benefit older adults. Geriatr Gerontol Int 2024; 24: 202-207.

The Influence of Capital Market Openness on the Sentiment of Chinese Investors

In recent years, China has been gradually and progressively promoting the opening of its capital markets to the outside world. In this study, a questionnaire survey and SEM (Structural Equation Modeling) model analysis were used to investigate the mechanisms and outcomes of capital market openness on Chinese investor sentiment based on the Land-Hong Kong Link Policy.The study reveals that following the opening of the capital markets, individual investor sentiment tends to become more rational due to factors such as changes in investor structure and shifts in value investment concepts. In the future, it is recommended that China's capital markets promote basic investment education and enhance the development of financial regulations to progress towards a deeper level of openness.

Considering Statistically Equivalent Models when using Structural Equation Modeling: an Example from Physics Identity

Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. Using a SEM model involves a crucial step of considering statistically equivalent models and contemplating why the proposed model should not be rejected in favor of equivalent ones. However, many studies using SEM did not explicitly discuss this step. In this study, we use physics identity model as an example to demonstrate how multiple statistically equivalent models have distinct instructional implications. Previous research has indicated that physics identity comprises three dimensions: perceived recognition, self-efficacy, and interest. However, the relationships between these dimensions have not been thoroughly understood. Here, we discuss how our proposed model with perceived recognition predicting self-efficacy and interest is supported by prior studies involving individual student interviews and how intervention studies can further determine a more accurate causal model. Our study highlights the importance of considering statistically equivalent models when using SEM as an analysis tool.

Work Environment, Human Resource Practices, and Organizational Culture: A Causal Model on Service Quality of Employees in Government Agency in Davao Region

Purpose: This quantitative, non-experimental study aimed to establish the best-fit structural model for the service quality of employees in a national government agency, with a specific focus on the Department of Environment and Natural Resources (DENR) in the Davao Region. Its significance lies in contributing to the existing body of knowledge in the field of public administration, leading to a more efficient and effective delivery of public services. Examining the relationship between factors such as the work environment, human resource practices, and organizational culture concerning service quality, this study builds upon the conclusions drawn from international research, which has investigated these factors in other countries but has yet to address the specific context of the Philippines, particularly in the Davao Region. Therefore, this study would address the gap by examining these relationships in the local context, contributing valuable insights to the literature on service quality in the Philippines.
 Methodology: A standardized instrument, administered through the Google platform, was used to survey 400 rank-and-file employees selected via stratified sampling in the Davao Region. The data collected were analyzed using statistical methods, including mean and standard deviation calculations, Pearson correlation analysis, multiple regression, and structural equation modeling (SEM).
 Findings: The study revealed that the service quality (dependent variable) was very high, while the work environment, human resource practices, and organizational culture (independent variables) were all at high levels. A Pearson correlation analysis unveiled a statistically significant and positively correlated relationship between the independent and dependent variables. Multiple regression analysis indicated that work environment, human resource practices, and organizational culture influence service quality. Moreover, organizational culture was found to be the best influencer of service quality of employees. Significantly, Model 5 emerges as the most fitting structural model for assessing service quality. The model demonstrated the direct influence of the work environment on service quality. Additionally, the SEM model identified specific variables that can predict service quality: training and development and evaluation and supervision (for human resource practices), physical and social work environment (for work environment), and adaptability, consistency, and involvement (for organizational culture).
 Recommendations: Therefore, the discoveries from this study offer valuable insights with direct relevance to policymakers and managers seeking to improve service quality in national government agencies.

Pathway analysis of the impact of health literacy, social support and self-efficacy on self-management behaviors in pregnant women with gestational diabetes mellitus.

The purpose of this study was to investigate the pathways by which health literacy (HL), social support, and self-efficacy influence self-management behaviors of pregnant women with Gestational diabetes mellitus (GDM) and the interrelationships between the variables. A total of 565 pregnant women with GDM was recruited. The Demographic Characteristics Form, Health Literacy Scale, Perceived Social Support Scale, General Self-efficacy Scale and GDM Self-management Behavior Scale were used for data collection. Descriptive statistics, zero-ordered correlation analysis, and multiple linear regression analysis were performed on the variables; Structural Equation Model (SEM) were constructed for pathway analysis. A positive correlation was found between health literacy, social support, self-efficacy, and self-management behaviors among pregnant women with GDM after adjusting for age, education level, income level, work status, parity, and family history of diabetes (r ranging from 0.203 to 0.533). A further multiple linear regression analysis showed that functional HL, communicative HL, critical HL, social support, and self-efficacy were all independent influences on self-management behaviors and accounted for 36.3% of the variance. Communicative HL and critical HL explained the strongest self-management behaviors (β = 0.316 and 0.255, respectively, p < 0.001). The SEM model was suitable for χ2/DF = 2.860, RMSEA = 0.060, IFI = 0.953, TLI = 0.943, and CFI = 0.952. The results showed direct positive effects of health literacy on self-management behaviors and self-efficacy, direct positive effects of social support on health literacy and self-efficacy. Social support and self-efficacy have had no significant direct impact on self-management behaviors, but social support may indirectly influence self-management behaviors through the health literacy mediation role. Healthcare providers should pay attention to the positive impacts of health literacy and social support on self-management behaviors of pregnant women with GDM. Improving the health literacy level of pregnant women with GDM should be the key point of intervention in practice, and the social support system should be fully mobilized to enhance emotional support and life support to promote the improvement of self-management behaviors.

Causal factors influencing the use of social commerce platforms

As the world of commerce evolves rapidly with the digital transformation, understanding the dynamics of social commerce (s-commerce) becomes increasingly critical. This study delves into the causal factors influencing the adoption of online s-commerce platforms, employing a Structural Equation Model (SEM) to illuminate consumer behavior. The SEM model integrates five variables: social factors, motivational factors, technological factors, platform characteristics, and economic factors. Data sourced from 400 s-commerce platform users validates the model's measurement reliability, confirming convergent and discriminant validity. The findings substantiate hypotheses indicating that social, technological, platform characteristics, and economic factors directly influence both s-commerce platform usage and user motivation. Additionally, motivation directly impacts platform usage, with historical influences also considered, revealing the enduring role of motivation in platform adoption, mediating other factors. This research has wide-reaching implications for businesses, academia, policymakers, and consumers. It underscores the imperative to adapt to the evolving s-commerce landscape, especially in emerging economies like Thailand, where it can drive economic growth and reshape commerce. Stakeholders, including businesses, researchers, policymakers, and consumers, should grasp these implications to harness the opportunities presented by the s-commerce revolution.

The Role of Government Policy on the Influence of Digital Marketing Through Social Media on the Performance of Micro, Small and Medium Enterprises (MSMEs) in Indonesia

The research objective ware to examine the role of government policy on the influence of digital marketing through social media on MSMEs in Indonesia. This type of research is quantitative, with an explanatory approach. The research ware conducted on 500 MSME actors or owners in Indonesia who used digital marketing through social media channels (Instagram, Facebook and Twitter) as their marketing tools. Data collection through a questionnaire in the form of a google form which is distributed online. The questionnaire was processed and transformed into an interval scale using the Method of Successive (MSI), then analyzed using the SEM (Structural Equation Modeling) model through the AMOS software. The results showed that perceived ease of use had a positive effect on attitudes towards using social media. Perceived usefulness of using social media has a positive effect on attitudes towards using social media. The attitude of using social media has a positive effect on the use of social media. The use of social media has a positive effect on the performance of MSMEs. That is, the higher the use of social media, the higher the performance of MSMEs. Government policies have a positive effect on the performance of MSMEs. That is, the higher the government policy, the higher the performance of MSMEs. Government policies moderate the influence of social media use and MSME performance. That is, government policies strengthen the influence of social media use and the performance of MSMEs.

Development and validation of a modified LibQUAL scale in health sciences libraries: application of Structural Equation Modeling.

The application of structural equation modeling (SEM), a statistical modeling tool for scale construction and development, is becoming increasingly popular in the health sciences librarianship and information science research. This study explores the application of SEM to health science libraries by describing the development and validation of a modified LibQUAL scale within an Iranian health sciences library setting. A literature search was performed across several information sources to identify candidate items to be included in the primary questionnaire. After translation, linguistic validation, and a pilot study, two cross-sectional studies were performed. SEM modeling framework was used for the assessment of the reliability and validity of the modified LibQUAL scale. The internal consistency of the scale was evaluated by measuring Cronbach's alpha coefficient and composite reliability. Exploratory and confirmatory factor analyses were used for the evaluation of the construct validity of the scale. Smart-PLS software was used for statistical modeling. Composite reliability and Cronbach's alpha coefficient for each scale ranged between 0.90 and 0.95, indicating adequate internal consistency with the LibQUAL scale. Confirmatory factor analysis confirmed the three-factor model of the LibQUAL scale. The convergent validity of the scale was supported, as the average variances extracted for all proposed factors were above 0.50. The discriminant validity was also confirmed using Fornel and Larcker and Heterotrait-Monotrait Ratio (HTMT) methods. Evaluation of psychometric properties of the translated and locally modified LibQUAL in the Persian language indicated adequate reliability, factorial validity, and stability of this instrument for Iranian health sciences libraries.

NG-SEM: an effective non-Gaussian structural equation modeling framework for gene regulatory network inference from single-cell RNA-seq data.

Inference of gene regulatory network (GRN) from gene expression profiles has been a central problem in systems biology and bioinformatics in the past decades. The tremendous emergency of single-cell RNA sequencing (scRNA-seq) data brings new opportunities and challenges for GRN inference: the extensive dropouts and complicated noise structure may also degrade the performance of contemporary gene regulatory models. Thus, there is an urgent need to develop more accurate methods for gene regulatory network inference in single-cell data while considering the noise structure at the same time. In this paper, we extend the traditional structural equation modeling (SEM) framework by considering a flexible noise modeling strategy, namely we use the Gaussian mixtures to approximate the complex stochastic nature of a biological system, since the Gaussian mixture framework can be arguably served as a universal approximation for any continuous distributions. The proposed non-Gaussian SEM framework is called NG-SEM, which can be optimized by iteratively performing Expectation-Maximization algorithm and weighted least-squares method. Moreover, the Akaike Information Criteria is adopted to select the number of components of the Gaussian mixture. To probe the accuracy and stability of our proposed method, we design a comprehensive variate of control experiments to systematically investigate the performance of NG-SEM under various conditions, including simulations and real biological data sets. Results on synthetic data demonstrate that this strategy can improve the performance of traditional Gaussian SEM model and results on real biological data sets verify that NG-SEM outperforms other five state-of-the-art methods.

Risks for Companies during the COVID-19 Crisis: Dataset Modelling and Management through Digitalisation

The goal is to create a systemic risk profile of companies during the COVID-19 crisis, which reflects their cause-and-effect relationships and risk management. The research objects are the following types of risks for companies listed in “Global-500” (Fortune) and the top 55 most competitive digital economies of the world (IMD) in 2017–2022: (1) risk of reduction in competitiveness (rank), (2) risk of reduction in revenue, and (3) risk of reduction in profit. The research methodology is based on the method of structural equation modelling (SEM), which allowed for exploring the cause-and-effect relationships between risk changes and digital risk management for companies during the COVID-19 crisis. As a result, based on the SEM model, it was proven that risks for companies during the COVID-19 crisis only slightly increased compared with that at the pre-crisis level. It was determined that companies faced large risks during the COVID-19 crisis in developed countries. It was discovered that, due to successful adaptation, risk management of companies assuaged the manifestations of the COVID-19 crisis in the economy. The key conclusion is that, under the conditions of a crisis of a non-economic nature (e.g., the COVID-19 crisis), companies independently and successfully manage their risks with the help of measures of digitalisation: corporate risk management with the limitation of state intervention is preferable. The contribution to the literature consists of the development of the concept of risks for companies by clarifying the specifics of risks and risk management of companies during the COVID-19 crisis. The theoretical significance lies in the fact that the authors’ conclusions rethought the risks for companies under the conditions of a crisis given the special context of a crisis of a non-economic nature (via the example of the COVID-19 crisis). The practical significance is that the developed novel approach to risk management of companies through digitalisation, which is based on the experience of the COVID-19 crisis, will be useful for risk management of companies under the conditions of future crises of non-economic nature caused by epidemics/pandemics and/or environmental disasters.

Psychometric properties of the Coach-Athlete Relationship Questionnaire (CART-Q) in a sample of Brazilian youth and adult athletes

This study examined the psychometric properties of the Coach–Athlete Relationship Questionnaire (CART-Q) in a sample of 1344 Brazilian youth and adult athletes. Participants completed the CART-Q and the Basic Needs Satisfaction in Sport Scale (BNSSS). Data analysis was conducted through Confirmatory Factor Analysis (CFA), Structural Equation Modeling (SEM), Cronbach's alpha, composite reliability, multigroup analysis, and Pearson's correlation ( p &lt; .05). CFA confirmed a multidimensional structure containing the three dimensions of Closeness, Commitment, and Complementarity: χ² (37) = 264.10; χ²/df = 5.13; CFI = .96; TLI = .94; and RMSEA = .068. Internal consistency was satisfactory (&gt;.70). SEM model showed an acceptable fit ( χ² (56) = 593.28; χ²/df = 2.71; CFI = .90; TLI = .90; RMSEA = .057), indicating that the three dimensions of the CART-Q predicted positively all basic needs satisfaction subscales (β range = .11 to .38). CART-Q was revealed to be invariant across gender, sport type, and age group. It was concluded that the CART-Q can satisfactorily be used in research studies involving Brazilian athletes regardless of their age group, gender, and sport.

Board of directors and financial performance: the role of risk management in Palestinian-listed companies

PurposeThis study aims to investigate the effect of the board of directors on financial performance, either directly or indirectly through the existence of risk management after the issuance of the Palestinian Code on Corporate Governance (PCCG) in Palestine.Design/methodology/approachThis study presents an empirical investigation of 31 nonfinancial Palestinian-listed companies from 2010 to 2016. This study utilizes the structural equation modeling (SEM) model.FindingsThe results of the SEM model find that there is a significant positive effect of the existence of risk management and the tenure-Chief Executive Officer (CEO) on financial performance. However, CEO duality has a significant negative effect on financial performance. The results also find that the effect of CEO duality and board size are significantly positive on financial performance through the existence of risk management.Research limitations/implicationsThis study adds to the existing literature by investigating the effect of the board of directors on financial performance, either directly or indirectly through the existence of risk management in Palestine as one of the youngest stock exchanges in the region that assists in testing the validity of agency theory in a young and small emerging Islamic market context.Practical implicationsThe results of this paper are significant to shareholders and managers of companies to make proper choices in order to secure the interests of stakeholders and increase the flow of capital and foreign investment.Originality/valueTo the best of the authors’ knowledge, it is one of the first papers to investigate the effect of the board of directors and financial performance, either directly or indirectly through the existence of risk management in Palestine.

Structural Relationship of Psychiatric Disorders, Quality of Life, Coping Styles and Their Associated Factors Among Brain Pathology Patients and Hematological Cancer Patients

Introduction: The study aimed to examine the structural relationship of major depressive disorder (MDD), anxiety disorder, various mental diseases, quality of life, coping methods, and other variables in patient with brain pathology and hematological cancer patients. Methods: A total of (n=215) samples were included in the structural equation modeling (SEM) analyses. The analyses were done with brain pathology patients (110) and haematological cancer patients (105). Results: In the current study, the multivariate normality kurtosis was 9.112 with c.r = 3.950 obtained in this SEM model. In the SEM model, the global health status towards MDD can explain about 30% of the variance. The global health status score was found to have a significant positive association with self-distraction coping styles, gender, and emotional functioning. Gender has a significant positive association with global health status, indicating that male patients have improved overall health. In terms of severity of MDD the positive correlation was found with panic disorder life time. Emotional functioning, self distraction and global health status were shown to have a significant and inverse relationship with the severity of MDD (p&lt;0.05). Conclusion: The severity of MDD was found to have a strong and detrimental association with cancer types indicating the brain pathology patients tends to have more severity of depression compared to haematological cancer patients.

Analysis of service quality factors affecting passenger satisfaction with bus service based on a structural equation modeling: A case study of Ho Chi Minh City

This study aims to examine service quality factors and the extent of their influence on passenger satisfaction with public bus transport service. The study will describe the steps of creating a SEM (Structural Equation Modeling) model to demonstrate the service quality - satisfaction relations. Survey data conducted by the Ho Chi Minh Public Transport Management Centre in collaboration with the World Bank consultants from December 2019 to January 2020 includes 3,913 questionnaires on 25 subsidized bus routes. The analysis results from the SEM model indicate that the factors with the strongest impact on satisfaction are availability possibility, service information, fare, service attitude and friendliness with the environment. This result suggests that public transport should focus on improving these service quality factors to ensure a high level of passengers’ satisfaction.