Date of Award
10-5-2017
Publication Type
Master Thesis
Degree Name
M.Sc.N.
Department
Nursing
Keywords
breastfeeding, breast-feeding, predictors, prenatal, self efficacy, self-efficacy
Supervisor
Kane, Debbie
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
The purpose of this study was to identify predictors of breastfeeding self-efficacy in the prenatal period among both primiparous and multiparous women. A sample of 401 Canadian women in their third trimester of pregnancy completed an online survey. Stepwise multiple linear regression was used to identify predictors of breastfeeding self-efficacy, as measured by the breastfeeding self-efficacy scale – short form (BSES-SF). The following eight variables were found to explain 41.2% of the variance in BSES-SF scores: feeling prepared for labour and birth, number of living children, breastfeeding knowledge, trait anxiety, length of plan to exclusively breastfeed, income, plan to exclusively breastfeed and type of healthcare provider. After exploring predictors of breastfeeding self-efficacy among the primiparous women in the sample, the following six variables explained 31.6% of the variance in BSES-SF scores: feeling prepared for labour and birth, income, trait anxiety, length of plan to exclusively breastfeed, education and marital status. Among the multiparous women in the sample the following four variables explained 33.6% of the variance in BSES-SF scores: trait anxiety, length of prior exclusive breastfeeding experience, breastfeeding knowledge and plan to exclusively breastfeed. Through the identification of predictors of breastfeeding self-efficacy in the prenatal period, healthcare providers can strategically target women at risk of low breastfeeding self-efficacy and intervene early to promote breastfeeding.
Recommended Citation
Corby, Kathryn, "Investigating Predictors of Prenatal Breastfeeding Self-Efficacy" (2017). Electronic Theses and Dissertations. 7244.
https://scholar.uwindsor.ca/etd/7244