Explanation of Children’s Health through Parents’ Mental Health and Job Satisfaction by Structural Equation Modeling

BACKGROUND: Worldwide, much evidence exists on the influence of parents’ socioeconomic conditions, including employment, on children’s health. However, the mechanisms for this affect are still being investigated. Few studies have been conducted in Iran to investigate this issue. This study investigated working conditions, job satisfaction, and mental health of employed people and the association between these variables and their children’s health.MATERIALS & METHODS: In this correlational work, 200 male and female staff of the official part of Educational Organization and the schools of Mashhad with children aged 5-18 years was randomly selected. The data were gathered using a demographic questionnaire, the 20-item Minnesota Job Satisfaction Questionnaire, the 28-item General Health Questionnaire, and the 28-item Child Health Questionnaire. The data were then analyzed using SPSS. The associations under study were investigated by structural equation modeling in AMOS.RESULTS: Approximately 17% of the variation in the parents’ job satisfaction could be explained by the parents’ insurance, income, and work hours; 6% of the variation in their mental health was explained by job satisfaction, and 26% of the variation in children’s health was directly explained by the parents’ job satisfaction and mental health. However, approximately 32.2% of the variation in children’s health could be explained in the light of the direct effect of the parents’ mental health and direct and indirect effects of the parents’ job satisfaction. The goodness of fit index was 0.94.CONCLUSION: Parents’ job satisfaction was associated with and considerably explained children’s health. Although this finding may be partially related to the job satisfaction effect on mental health, the reasons for the affect of job satisfaction on children’s health and the potential mechanisms of this association require further studies.

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Organizational Commitment As Influenced by Leadership Behavior of Administrators, Job Satisfaction and Burnout of Teachers: A Structural Equation Modeling

UIC Research Journal ◽

10.17158/228 ◽

2012 ◽

Vol 18 (1) ◽

Cited By ~ 1

Author(s):

Felix C. Chavez, Jr.

Keyword(s):

Job Satisfaction ◽

Structural Equation Modeling ◽

Organizational Commitment ◽

Structural Equation ◽

Quantitative Research ◽

Goodness Of Fit ◽

Leadership Behavior ◽

Stepwise Multiple Regression ◽

Equation Modeling ◽

Best Fit

This study was conducted to determine the best fit model of organizational commitment. Specifically, it established the interrelationship among leadership behavior, job satisfaction, burnout, and organizational commitment. Quantitative research design was utilized in this study. The data were gathered from the teachers among the randomly selected academic institutions in Region XI, Philippines. Moreover, sets of survey questionnaires were used as instruments to obtain information from the participants. Pearson product moment correlation was used to find the significance of the relationship between the independent and dependent variables. Stepwise multiple regression analysis was used to identify the variables that best predict organizational commitment and likewise Structural Equation Modeling was used to identify the model that best fits organizational commitment. The findings revealed that the over-all leadership behavior of administrators and organizational commitment of teachers were high. On the other hand, the job satisfaction of teachers was moderate and their degree of burnout was low. Furthermore, the leadership behavior, job satisfaction, and burnout were highly correlated with organizational commitment, and found to be significant predictors of organizational commitment. Finally, the best fit model of organizational commitment was the Hypothesized Model 5, which passed all the goodness of fit indices criteria.

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Perceived Employability Moderates Burnout and Depression Among Bank Employees

Social Behavior and Personality An International Journal ◽

10.2224/sbp.2016.44.7.1123 ◽

2016 ◽

Vol 44 (7) ◽

pp. 1123-1132 ◽

Cited By ~ 1

Author(s):

Haishu Qiao ◽

Yue Xia ◽

Ying Li

Keyword(s):

Mental Health ◽

Structural Equation Modeling ◽

Structural Equation ◽

Moderating Effect ◽

Equation Modeling ◽

Hierarchical Regression ◽

Negatively Associated ◽

Perceived Employability ◽

Bank Employees ◽

The Relationship

Because bank employees have been found to be especially susceptible to burnout and depression, we explored the relationship between these variables, and examined the moderating effect of perceived employability on the burnout–depression relationship in a sample of Chinese bank employees. As we expected, burnout and perceived employability were, respectively, positively and negatively associated with depression. The results of hierarchical regression and structural equation modeling indicated that perceived employability moderated the relationship between burnout and depression; higher perceived employability was associated with a weaker relationship between burnout and depression. Interventions aimed at developing the perceived employability of Chinese bank employees may help to improve mental health in this group.

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Doctors’ Job Satisfaction and Its Relationships With Doctor-Patient Relationship and Work-Family Conflict in China: A Structural Equation Modeling

INQUIRY The Journal of Health Care Organization Provision and Financing ◽

10.1177/0046958018790831 ◽

2018 ◽

Vol 55 ◽

pp. 004695801879083 ◽

Cited By ~ 3

Author(s):

Shumin Deng ◽

Ningxi Yang ◽

Shiyue Li ◽

Wei Wang ◽

Hong Yan ◽

...

Keyword(s):

Job Satisfaction ◽

Structural Equation Modeling ◽

Family Conflict ◽

Structural Equation ◽

Hubei Province ◽

Equation Modeling ◽

Patient Relationship ◽

Work Family Conflict ◽

Doctor Patient Relationship ◽

Work Family

The objective of this study was to evaluate the relationship of doctors’ job satisfaction with doctor-patient relationship and work-family conflict in China. The data came from a cross-sectional survey in Hubei province, which was part of China’s Fifth National Health Services Survey conducted in 2013. The survey in Hubei covered 54 secondary and tertiary general hospitals distributed in 20 counties. Of the 1080 questionnaires, 908 were included into our analysis. After surviving from reliability and validity tests, structural equation modeling was applied for further analysis with SPSS 20.0 and Mplus 7.0. The results showed that the average score of job satisfaction is 19.61 out of 30 points, indicating a relatively low level of doctors’ job satisfaction in Hubei province. Work-family conflict was found to have negative impact on doctors’ job satisfaction, and good doctor-patient relationship was found to have positive impact on their job satisfaction. Therefore, hospital administrators and policy makers should make effort to design and implement strategies that focus on meliorating doctor-patient relationship and balancing doctors’ work and family life to further improve their job satisfaction.

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MODEL PENGUKURAN TINGKAT KEPERCAYAAN PELANGGAN (ONLINE TRUST) TERHADAP SITUS E-COMMERCE (Studi Kasus pada Pelanggan E-Commerce di Provinsi Bali)

International Journal of Natural Science and Engineering ◽

10.23887/ijnse.v1i3.12939 ◽

2018 ◽

Vol 1 (3) ◽

pp. 100

Author(s):

I Made Endra Wiartika Putra ◽

Gede Rasben Dantes ◽

I Made Candiasa

Keyword(s):

Structural Equation Modeling ◽

Structural Equation ◽

Goodness Of Fit ◽

Equation Modeling ◽

Snowball Sampling ◽

Cronbach’S Alpha ◽

Purposive Sampling ◽

Online Trust ◽

Cronbach's Alpha ◽

Fit Index

Penelitian ini bertujuan untuk mengetahui model pengukuran tingkat kepercayaan pelanggan terhadap situs e-commerce. Langkah awal yang dilakukan yaitu identifikasi faktor-faktor yang mempengaruhi kepercayaan pelanggan melalui studi literatur dan studi empirik untuk menentukan model analisis terhadap kepuasan pelanggan. Faktor yang mempengaruhi kepercayaan pelanggan untuk bertransaksi secara online yaitu pengetahuan konsumen terhadap e-commerce, reputasi penjual, resiko dalam transaksi, kemudahan penggunaan e-commerce, jaminan sistem, sikap/perilaku terhadap sistem dan sistem keamanan. Populasi dalam penelitian ini adalah masyarakat Provinsi Bali menggunakan metode purposive sampling dan snowball sampling dengan kriteria responden pernah berkunjung dan melakukan transaksi di e-commerce yang ada di Indonesia lebih dari 3 kali. Instrumen penelitian berupa kuesioner dengan data interval berskala 5 Likert. Instrumen terlebih dahulu diuji validitas isi dengan metode Robert Gregory, validitas empiris menggunakan rumus product moment, reliabilitas instrument menggunakan Cronbach’s Alpha, dan menghasilkan 59 pernyataan yang dapat digunakan untuk pengambilan data. Jumlah responden yang digunakan dalam penelitian ini adalah sebanyak 126 responden. Teknik analisis data, pengujian hipotesis dan pengujian model menggunakan metode Structural Equation Modeling dengan bantuan aplikasi SPSS AMOS 21. Hasil penelitian ini melalui pengujian hipotesis menunjukkan bahwa pengetahuan tentang situs e-commerce dan perlindungan keamanan berpengaruh negatif dan tidak signifikan terhadap kepercayaan pelanggan. Resiko, kemudahan e-commerce, jaminan sistem dan sistem keamanan bukan menjadi sesuatu yang penting untuk dipertimbangkan dalam meningkatkan kepercayaan pelanggan karena pengaruhnya tidak signifikan. Reputasi yang dirasakan dan sikap merupakan hal yang perlu diperhatikan dan paling berpengaruh terhadap kepercayaan pelanggan pelanggan. Hasil penelitian ini kemudian diuji menggunakan goodness of fit index dan menghasilkan bahwa model penelitian tersebut dapat diterima dan dapat digunakan untuk meningkatkan keinginan pelanggan untuk bertransaksi online

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A Corrected Goodness-of-Fit Index (CGFI) for Model Evaluation in Structural Equation Modeling

Structural Equation Modeling A Multidisciplinary Journal ◽

10.1080/10705511.2019.1695213 ◽

2019 ◽

Vol 27 (5) ◽

pp. 735-749 ◽

Cited By ~ 1

Author(s):

Kai Wang ◽

Ying Xu ◽

Chaolong Wang ◽

Ming Tan ◽

Pingyan Chen

Keyword(s):

Structural Equation Modeling ◽

Model Evaluation ◽

Structural Equation ◽

Goodness Of Fit ◽

Equation Modeling ◽

Fit Index

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Confirmatory Factor Analysis (CFA), Exploratory Structural Equation Modeling (ESEM), and Set-ESEM: Optimal Balance Between Goodness of Fit and Parsimony

Multivariate Behavioral Research ◽

10.1080/00273171.2019.1602503 ◽

2019 ◽

Vol 55 (1) ◽

pp. 102-119 ◽

Cited By ~ 13

Author(s):

Herbert W. Marsh ◽

Jiesi Guo ◽

Theresa Dicke ◽

Philip D. Parker ◽

Rhonda G. Craven

Keyword(s):

Factor Analysis ◽

Structural Equation Modeling ◽

Confirmatory Factor Analysis ◽

Structural Equation ◽

Goodness Of Fit ◽

Equation Modeling ◽

Exploratory Structural Equation Modeling ◽

Optimal Balance ◽

Confirmatory Factor

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Technological Justice and Job Satisfaction: Structural Equation Modeling

Global Encyclopedia of Public Administration, Public Policy, and Governance ◽

10.1007/978-3-319-31816-5_4183-1 ◽

2020 ◽

pp. 1-4

Author(s):

Samir M. Hammami ◽

Osama Hazzi

Keyword(s):

Job Satisfaction ◽

Structural Equation Modeling ◽

Structural Equation ◽

Equation Modeling

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Cutoff criteria for overall model fit indexes in generalized structured component analysis

Journal of Marketing Analytics ◽

10.1057/s41270-020-00089-1 ◽

2020 ◽

Vol 8 (4) ◽

pp. 189-202

Author(s):

Gyeongcheol Cho ◽

Heungsun Hwang ◽

Marko Sarstedt ◽

Christian M. Ringle

Keyword(s):

Structural Equation Modeling ◽

Structural Equation ◽

Goodness Of Fit ◽

Component Analysis ◽

Model Fit ◽

Equation Modeling ◽

Generalized Structured Component Analysis ◽

Root Mean Square Residual ◽

Fit Indexes ◽

Cutoff Criteria

AbstractGeneralized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model evaluation, including the goodness-of-fit index (GFI) and the standardized root mean square residual (SRMR). While these indexes have a solid standing in factor-based structural equation modeling, nothing is known about their performance in GSCA. Addressing this limitation, we present a simulation study’s results, which confirm that both GFI and SRMR indexes distinguish effectively between correct and misspecified models. Based on our findings, we propose rules-of-thumb cutoff criteria for each index in different sample sizes, which researchers could use to assess model fit in practice.

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