Testing the disclosure decision-making model: disclosing birth control status among college women

ABSTRACT

Reproductive health communication can greatly benefit college women by providing informational and emotional support for their reproductive sexual health. However, communication about birth control with friends and sexual partners can be difficult especially if there is stigma around the topic. Applying the Disclosure Decision-Making Model, this study employs a survey of 104 college women regarding their disclosure of birth control status to a peer (Model 1) and a sexual partner (Model 2) to understand the mechanisms of decision-making (i.e., stigma, relational quality, anticipated response, disclosure efficacy) on the depth of disclosing reproductive health information. Results suggest that for both models, relational quality and anticipated response were the predictors of disclosure depth. Although all the significant paths were equivalent in the two models, relational quality predicted anticipated response more strongly in partner model. Theoretical and practical implications of the findings are discussed.

KEYWORDS:

• DD-MM
• disclosure
• birth control
• stigma
• reproductive health communication

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Notes on contributors

Seulgi Park

Seulgi Park is a Ph.D. student in the Department of Communication at University at Albany, SUNY. Her research interests include health literacy and health communication for immigrants, especially with Limited English Proficiency.

Fan Yang

Fan Yang (Ph.D., the Pennsylvania State University) is an assistant professor in the Department of Communication at University at Albany, SUNY. Her research focuses on new media and strategic communications. She is interested in examining psychological effects of new communication technologies on decision making using methods such as experiment, big-data analysis, and meta-data analysis.

Molly Hayden

Molly Hayden is an MPH graduate in the School of Public Health at University at Albany, SUNY. Her primary area of interest is in social behavior and community health, as well as health communication.

Amanda Morel

Amanda Morel is an MA graduate from the Department of Communication at University at Albany, SUNY. Her research focuses on interpersonal and intercultural communication. She is interested in examining women’s health in low income communities and how experiences impact one’s health.