Volume 26, Issue 103 (10-2017)                   JGUMS 2017, 26(103): 53-62 | Back to browse issues page

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Izadirad H, Niknami S, Zareban I, Hidarnia A. Predictors of Self-Care in Pregnancy Based on Integration of Health Belief Model and Social Support . JGUMS 2017; 26 (103) :53-62
URL: http://journal.gums.ac.ir/article-1-1520-en.html
Abstract:   (4123 Views)
Introduction: Due to weakness of self-care during pregnancy, adverse pregnancy outcomes including abortion, stillbirth, premature birth, etc may occur. Individual and social factors affect self-care of pregnancy
Objective: Use of path analysis method to determine predictors of pregnancy self-care based on combination of health belief model and social support.
Materials and Methods: This was a descriptive analytical study conducted on 215 pregnant women living in Baluchistan region , Iran. Two-stage cluster sampling was performed. Data collection tool was questionnaire of integrated model ( HBM and social support constructs). To analyze the data, SPSS version 18 statistical indicators and descriptive statistics, bivariate correlations, and linear regression.
Results: Self-efficacy, perceived severity and sensitivity were found to be directly effective on self-care. Also, social support had indirect effects on self-care through an effect on self-efficacy, perceived susceptibility and severity. Social support was identified as the strongest predictor of self-care of pregnancy (46/6%). A significant correlation was found between  susceptibility and self-care (0.598), severity and self-care (0.726), benefits and self-care (0.348), self-efficacy and self-care (0.824) and social support(0.745) with self-care(p<0.05). An inverse association was observed between perceived barriers and  self-care(p <0.05, r=-0.685).
Conclusion: Integrated Model (HBM and social support structures) with an emphasis on social support and self efficacy can be used as a framework for designing educational interventions to promote self-care.
Conflict of interest: none declared
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Review Paper: Research | Subject: Special
Received: 2017/10/29 | Accepted: 2017/10/29 | Published: 2017/10/29

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