Assessing health diagnosis disclosure decisions in relationships: testing the disclosure decision-making model

Illness affects millions of Americans each year, and the disclosure of health conditions can facilitate access to social support, in addition to other physical and physiological benefits. This article tests the Disclosure Decision-Making Model (DD-MM; Greene, 2009 ) to predict factors that influence the likelihood of disclosing (and past disclosure of) nonvisible physical or mental health-related information. One hundred eighty-seven (n = 187) people were recruited for a study to report on both disclosing and not disclosing a nonvisible health condition. Measured variables included information assessment, relational quality, anticipated reactions (support, relational consequences), confidence in response, disclosure efficacy, and disclosure (likelihood of disclosure and depth of disclosure). Structural equation modeling results supported many of the proposed hypotheses, with a great deal of similarity across models. Specifically, assessing information predicted efficacy, and to some extent relational outcomes. Closeness was related to response overall and to efficacy in one model. Response predicted outcome overall and likelihood of disclosure in one model. Finally, efficacy predicted likelihood of disclosure and depth of disclosure. The article discusses the implications of the findings for understanding information, relationship assessments, and efficacy in disclosing health diagnoses.