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What do Women Want? Experiences of Low-Income Women with Postpartum Contraception and Contraceptive Counseling

Lynn M Yee, Katherine C Farner, Erin King and Melissa A Simon

Background: Contraceptive counseling can increase postpartum contraception use, yet the optimal method and timing for counseling are unknown. The objective was to investigate preferences of underserved pregnant and postpartum women regarding contraception use and counseling.

Method: Surveys regarding contraception experiences and perceptions of contraceptive counseling were conducted with 57 women age 18 and older who were postpartum or antepartum with a previous delivery within 5 years and receiving Medicaid-funded care at an academic medical center. Health literacy was assessed using REALM-7. Responses were analyzed using descriptive statistics.

Results: A majority of women reported unplanned pregnancies (78%). Women using contraception at the time of conception reported “not sure” (30%) and “taken wrong” (30%) as primary reasons for failure. Most subjects had at least a high school level of health literacy (88%), desired to use a postpartum contraceptive method (92%) and had a high self-reported understanding of that method (94%). Most women reported receiving counseling (91%) and stated that the best time for counseling was both before and after childbirth (84%). However, only 60% of subjects intended to use the method they were prescribed at discharge; reasons for changing included side effects (37%), desire for different contraception (23%) and too complicated of a method prescribed (17%).

Conclusion: Women perceived the best timing of contraceptive education to be both antepartum and postpartum. Despite a high frequency of prior contraceptive failure, self-reported understanding of the chosen postpartum contraceptive method was high. Contraception counseling should be tailored to a woman’s perceived needs, with such education occurring frequently and within the context of her health literacy.

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado.