A Model into Relations Between Spousal Support, Financial Satisfaction, and Marital Satisfaction

We developed a novel model combining the partial least squares structural equation modeling (PLS-SEM) and Artificial Neural Network (ANN) to examine the relationships between demographic variables, spousal support, financial satisfaction, and marital satisfaction. The sample comprised 948 Turkish pa...

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Bibliographic Details
Published in:Journal of family and economic issues 2024-09, Vol.45 (3), p.723-740
Main Authors: Günaydın, H. Deniz, Kayral, Ihsan Erdem
Format: Article
Language:English
Subjects:
Age
Age groups
Education
Family
Family support
Food
Gender
Labor unions
Marital satisfaction
Marriage
Neural networks
Original Paper
Personality and Social Psychology
Social networks
Social Policy
Social Sciences
Sociology
Starvation
Structural equation modeling
Variables
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Summary:We developed a novel model combining the partial least squares structural equation modeling (PLS-SEM) and Artificial Neural Network (ANN) to examine the relationships between demographic variables, spousal support, financial satisfaction, and marital satisfaction. The sample comprised 948 Turkish participants who completed the Spousal Support Scale, Financial Satisfaction Scale, and Kansas Marital Satisfaction Index. In the dimension of PLS-SEM, spousal support positively influenced financial satisfaction. In the below- and above-starvation-line groups, marital satisfaction was positively influenced by financial satisfaction and spousal support. The PLS-SEM and the ANN models were integrated, and the present PLS-SEM model was validated. SS and FS were two crucial aspects of a marriage that significantly determine overall marital satisfaction in the below- and above-starvation-line groups. The MLP analysis demonstrated the validity of the relationship model between marital satisfaction and demographics. Age in the group above the starvation line and the number of children in the group below the starvation line were significant variables for MS.
ISSN:1058-0476
1573-3475
DOI:10.1007/s10834-023-09908-w