Women's perceptions about female reproductive system: a survey from an academic obstetrics and gynecology practice

Arch Gynecol Obstet. 2014 Jun;289(6):1219-23. doi: 10.1007/s00404-013-3116-1. Epub 2013 Dec 7.

Abstract

Objective: To assess women's knowledge about female reproductive system and the demographic factors that may influence their perceptions.

Study design: In this cross-sectional study, all qualifying adult women at our academic practice were asked to complete a self-administered anonymous questionnaire about the effects of female reproductive system between June and August 2009. We assessed the accuracy of their knowledge and analyzed the effect of demographic factors.

Results: The majority of the 500 participants were in 18- to 59-year age range (93 %), Caucasian (81 %), married (56 %), college graduates (74 %) and had private insurance (82 %). Mean correct score was 63 ± 20 %. In univariate analysis, those respondents who were older, Caucasian, and had private insurance scored significantly higher (p < 0.05) When all the variables were entered in a fractional logit model, only age, race and reason for the visit remained as independent predictors for a better overall score in this survey. Twenty-nine percent of the participants thought hysterectomy included removal of ovaries and tubes. About a quarter of the respondents thought menstrual function would continue after hysterectomy. The question for whether removal of the uterus resulted in climacteric changes was correctly answered only by 34 %. While 59 % of women did not agree that removing the entire uterus eliminated the cervical cancer risk, 66 % concluded that they would continue to need Pap smears after total hysterectomy.

Conclusion: Women's knowledge about female reproductive system is limited, especially for those who are younger and from a minority.

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Cross-Sectional Studies
  • Female
  • Genitalia, Female / anatomy & histology*
  • Health Knowledge, Attitudes, Practice*
  • Humans
  • Insurance, Health / statistics & numerical data
  • Logistic Models
  • Middle Aged
  • Pregnancy
  • Racial Groups / statistics & numerical data
  • Reproductive Physiological Phenomena*
  • Surveys and Questionnaires
  • Young Adult