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Predictors of Mental Health During High-Risk Pregnancy

Authors :
Nayere Azam Hajikhani
Giti Ozgoli
Taghi Pourebrahim
Yadollah Mehrabi
Source :
Crescent Journal of Medical and Biological Sciences, Vol 7, Iss 1, Pp 54-58 (2020)
Publication Year :
2020
Publisher :
Aras Part Medical International Press, 2020.

Abstract

Objectives: Given the increased morbidity and mortality rates in high-risk pregnancies, which are associated with stress, this study aimed to investigate the predictors of the mental health of mothers during high-risk pregnancy. Materials and Methods: To this end, 750 eligible couples referring to hospitals and public health centers of Gorgan (2016-2017) were selected using stratified-cluster random sampling method. Then, pregnancy worries and social support questionnaires were completed by mothers and mental health questionnaire was completed by the couples. Next, the correlation level was measured by Pearson correlation coefficient. Finally, the contribution of each variable as the predictor of maternal mental health was discussed by utilizing stepwise regression analysis. Results: The mean score of worry was 34.57 among the mothers, which was lower than the mean value while the support score was 14.45 which was higher than the mean value. The strongest predictors of the mental health of mothers with high-risk pregnancy were mother’s worry, the mental health of fathers, and the social support with standard coefficients of 0.447, 0.153, and -0.88, respectively. Conclusions: In general, counseling and care programs are recommended for high-risk pregnant mothers in order to reduce their worries while increasing the mental health of the spouses and encouraging important relatives to attract further social support and improve the maternal mental health.

Details

Language :
English
ISSN :
21489696
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Crescent Journal of Medical and Biological Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.7fa6420e3f77432bb989d5d1e4c5b5c1
Document Type :
article