Literature DB >> 33041369

Childbearing Worldviews and Contraceptive Behavior Among Young Women.

Hana Shepherd1, Emily A Marshall2.   

Abstract

OBJECTIVE: To classify young women into groups based on their childbearing worldviews-patterns of attitudes about domains related to childbearing-and to test whether these groups predict contraceptive behavior.
BACKGROUND: Contraceptive behavior-defined here as contraceptive use or abstinence-among young women in the United States illustrates the often puzzling relationship between attitudes and behavior. This study argues that considering sets of attitudes relevant to childbearing in relation to each other can explain apparent contradictions between attitudes and contraceptive behavior.
METHOD: Using data from the Relationship Dynamics and Social Life study of young women (N=832), this study analyzes the relationships among attitudes about childbearing by using latent class analysis to partition survey respondents into meaningful groups, and then multinomial logistic regression analysis to examine the relationship between group membership and contraceptive behavior. Latent class analysis (LCA) identifies classes that share similar relationships between responses across a series of variables to measure childbearing worldviews.
RESULTS: Latent class analysis identifies six classes of young women that share childbearing worldviews, four of which were predicted by existing literature. Membership in those classes is then shown to predict contraceptive behavior, an important behavioral outcome.
CONCLUSION: The concept of worldviews and the method for identifying them will allow family researchers to identify meaningful groups in a population, as well as to generate theories about childbearing and contraceptive behavior.

Entities:  

Keywords:  contraception; culture; emerging adulthood; fertility; quantitative methodology

Year:  2019        PMID: 33041369      PMCID: PMC7546315          DOI: 10.1111/jomf.12581

Source DB:  PubMed          Journal:  J Marriage Fam        ISSN: 0022-2445


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