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Psychometric Evaluation of an Instrument to Measure Prospective Pregnancy Preferences

Authors
  • Rocca, Corinne H.1
  • Ralph, Lauren J.1
  • Wilson, Mark2
  • Gould, Heather1
  • Foster, Diana G.1
  • 1 Department of Obstetrics, Gynecology and Reproductive Sciences, Bixby Center for Global Reproductive Health, Advancing New Standards in Reproductive Health (ANSIRH), University of California, San Francisco, School of Medicine, San Francisco
  • 2 University of California, Graduate School of Education, Berkeley, CA
Type
Published Article
Journal
Medical Care
Publisher
Lippincott Williams & Wilkins
Publication Date
Jan 15, 2019
Volume
57
Issue
2
Pages
152–158
Identifiers
DOI: 10.1097/MLR.0000000000001048
PMID: 30550399
PMCID: PMC6331264
Source
PubMed Central
Keywords
License
Green

Abstract

Background: Existing approaches to measuring women’s pregnancy intentions suffer important limitations, including retrospective assessment, overly simple categories, and a presumption that all women plan pregnancies. No psychometrically valid scales exist to prospectively measure the ranges of women’s pregnancy preferences. Materials and Methods: Using a rigorous construct modeling approach, we developed a scale to measure desire to avoid pregnancy. We developed 60 draft items from existing research, assessed comprehension through 25 cognitive interviews, and administered items in surveys with 594 nonpregnant women in 7 primary and reproductive health care facilities in Arizona, New Jersey, New Mexico, South Carolina, and Texas in 2016–2017. We used item response theory to reduce the item set and assess the scale’s reliability, internal structure validity, and external validity. Items were included based on fit to a random effects multinomial logistic regression model (partial credit item response model), correspondence of item difficulty with participants’ pregnancy preference levels, and consistency of each item’s response options with overall scale scores. Results: The 14 final items covered 3 conceptual domains: cognitive preferences, affective feelings, and practical consequences. Items fit the unidimensional model, with a separation reliability of 0.90 (Cronbach α: 0.95). The scale met established criteria for internal validity, including correspondence between each item’s response categories and overall scale scores. We found no important differential item functioning by participant characteristics. Conclusions: A robust measure is available to prospectively measure desire to avoid pregnancy. The measure can aid in identifying women who could benefit from contraceptive care and research on less desired pregnancy.

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