Pesquisa em Medicina de Família e Ciências Médicas

Pesquisa em Medicina de Família e Ciências Médicas
Acesso livre

ISSN: 2327-4972

Abstrato

Perceptions of Home Delivery Risk and Associated Factors among Pregnant Mothers in North Achefer District, Amhara Region of Ethiopia: The Health Belief Model Perspective

Resom Berhe, Adane Nigusie

Background: Women continue to experience various problems utilizing skilled attendants help at delivery. The clinical causes of maternal deaths, the characteristics of women who die and the causes inherent to the health care system are well known in Ethiopia and elsewhere. Less is known about the perception of risk that may contribute to
women’s deaths during pregnancy and childbirth.
Methods: A community based cross-sectional study was undertaken on 610 pregnant women who were in their third trimester in January 2015. Systematic random sampling technique was applied. Data were collected using a modified version of the Champion’s Health Belief Model Constructs Instrument to assess the perception of risk of home
delivery among pregnant women.
Result: Among women with a last live birth delivered anytime within two years prior to the survey, 55.6% (95% CI: 1.07-1.47) had been assisted by Non-skilled birth attendants. It was shown that home delivery was significantly associated with perceived susceptibility (AOR=4.93, 95% CI: 2.94-8.20), perceived barrier (AOR=5.00 95% CI: 3.05-8.20) and perceived severity (AOR=1.62, 95% CI: 1.04-2.54). The largest variance of intention to give birth at home was explained by Perceived Seriousness (46.2%) and followed by Perceive Susceptibility (32.2%) and perceived barrier (26.4%) among pregnant mothers.
Conclusion: Given the perceived susceptibility, perceived severity and perceived barriers roles in home delivery prediction, it is recommended to consider these structures in designing educational interventions in order to promote institutional delivery in the research area.

Isenção de responsabilidade: Este resumo foi traduzido com recurso a ferramentas de inteligência artificial e ainda não foi revisto ou verificado.
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