Social support and motivation to transfer as predictors of training transfer: testing full and partial mediation using meta-analytic structural equation modelling

2018 ◽  
Vol 22 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Sarah Reinhold ◽  
Andreas Gegenfurtner ◽  
Doris Lewalter
Keyword(s):  
Social Support ◽  
Structural Equation Modelling ◽  
Structural Equation ◽  
Training Transfer ◽  
Equation Modelling ◽  
Motivation To Transfer ◽  
Transfer Testing

scholarly journals The impact of general health and social support on health promoting lifestyle in the first year postpartum: the structural equation modelling

10.19082/6231 ◽  
2018 ◽  
Vol 10 (1) ◽  
pp. 6231-6239 ◽  
Author(s):  
Khadijeh Hajimiri ◽  
Elham Shakibazadeh ◽  
Ali Asghar Haeri Mehrizi ◽  
Sakineh Shabbidar ◽  
Roya Sadeghi
Keyword(s):  
Social Support ◽  
Structural Equation Modelling ◽  
General Health ◽  
Structural Equation ◽  
First Year ◽  
Equation Modelling ◽  
Health Promoting ◽  
Health Promoting Lifestyle ◽  
The Impact

An Application of Structural Equation Modelling to Search Antecedents Latent Variables in Organisational Health, Occupational Role Stress and Social Support for Organisational Commitment

2015 ◽  
Vol 4 (2and3) ◽  
Author(s):  
Swati Mishra ◽  
S. M. Khan ◽  
P. C. Mishra
Keyword(s):  
Social Support ◽  
Organizational Commitment ◽  
Structural Equation Modelling ◽  
Latent Variables ◽  
Structural Equation ◽  
Organizational Health ◽  
Role Stress ◽  
Equation Modelling ◽  
Occupational Role ◽  
Endogenous Variables

In this article, a search for antecedents latent variables of organizational commitment from organizational health, occupational role stress, and social support for Indian Nationalized Bank Managers was made. Structural Equation Modelling (SEM) was used to assess the fit of the model that identified autonomy, cohesiveness, goal focus, role overload, and responsibility for the person as statistically significant antecedents of organizational commitment. Our models provided a good fit. Direct and indirect effects of exogenous variables on endogenous variables estimated and resultant percent of variance accounted into organizational commitment reported.

The transition to hospital consultant and the influence of preparedness, social support, and perception: A structural equation modelling approach

2013 ◽  
Vol 35 (4) ◽  
pp. 320-327 ◽  
Author(s):  
Michiel Westerman ◽  
Pim W. Teunissen ◽  
Joanne P.I. Fokkema ◽  
Cees P.M. van der Vleuten ◽  
Albert J.J.A. Scherpbier ◽  
...  
Keyword(s):  
Social Support ◽  
Structural Equation Modelling ◽  
Structural Equation ◽  
Equation Modelling ◽  
Hospital Consultant ◽  
Modelling Approach

scholarly journals Exploring Social and Financial Hardship, Mental Health Problems and the Role of Social Support in Asylum Seekers Using Structural Equation Modelling

2020 ◽  
Vol 17 (19) ◽  
pp. 6948
Author(s):  
Mathilde Sengoelge ◽  
Øivind Solberg ◽  
Alexander Nissen ◽  
Fredrik Saboonchi
Keyword(s):  
Mental Health ◽  
Social Support ◽  
Structural Equation Modelling ◽  
Asylum Seekers ◽  
Structural Equation ◽  
Mental Health Problems ◽  
Health Problems ◽  
Financial Hardship ◽  
Equation Modelling

Asylum seekers are exposed to a range of social and financial difficulties suggested to adversely impact mental health. Uprooted social networks and living conditions during the asylum seeking process potentially predispose this population to low access to social support. The aim of this study was to examine the relationship between social and financial hardship and mental health problems, and assess the potential mediating role of social support among asylum seekers. Cross sectional survey data from a cohort of asylum seekers in Sweden (N = 455) were subjected to structural equation modelling for examining hypothesized pathways between social and financial hardship, common mental health problems (CMHPs) and social support. Fit indices showed adequate to excellent fit of the examined models with CMHPs as the outcome (all CFI ≥ 0.951, RMSEA < 0.05, SRMR < 0.056). CMHPs were positively regressed on social and financial hardship (B = 0.786, S = 0.102, p < 0.001) and negatively regressed on social support (B = −0.103, SE = 0.032, p = 0.001). Social support mediated the association between social and financial hardship and CMHPs (effect estimate = 0.075, 95% CI = 0.032–0.136). The results point to the importance of social and living conditions of asylum seekers and indicate that social support is both socially patterned and may act as a mitigating resource to inform interventions and policies.

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