Iranian Journal of Nursing and Midwifery Research (Jan 2019)

Predicting exclusive breastfeeding among iranian mothers: Application of the theory of planned behavior using structural equation modeling

  • Razyeh Bajoulvand,
  • Emilio González-Jiménez,
  • Mohammad-Hasan Imani-Nasab,
  • Farzad Ebrahimzadeh

DOI
https://doi.org/10.4103/ijnmr.IJNMR_164_18
Journal volume & issue
Vol. 24, no. 5
pp. 323 – 329

Abstract

Read online

Background: Identifying the factors that lead to the beginning, continuing, or stopping the Exclusive Breastfeeding (EBF) by mothers can be of great assistance in the design of interventions to strengthen this behavior. The aim of this study was to predict EBF among mothers with Infants Less than Six Months of Age (ILSMA) according to the Theory of Planned Behavior (TPB). Materials and Methods: The study was a cross-sectional one that conducted among 304 mothers with ILSMA in Khorramabad-Iran in 2017 using Structural Equation Modeling (SEM). The sampling method was a combination of census, stratified random, and systematic random sampling. The data collection tool was a contextualized, valid, and reliable questionnaire according to the TPB. Data were collected by a trained interviewer. Data were analyzed using SPSS-16 and AMOS-20 software programs and SEM. Results: Perceived Behavioral Control (PBC) could explain 65% of mothers' EBF intention. Intention and PBC were able to predict 79% of the variance in EBF together. The fitness indices of EBF model in the current study were acceptable (RMSEA = 0.07, CMIN/DF = 2.58, NFI = 0.81, CFI = 0.87, and GFI = 0.83). Conclusions: TPB is an appropriate model for predicting the intention and behavior of EBF. Policy makers and health system managers are recommended for taking some measures to add a standardized questionnaire in the electronic health record to predict EBF according to TPB of pregnant women and mothers with ILSMA. In this way, they can empower primary healthcare providers to design and implement a theory-based interventional plan.

Keywords