Sexual Orientation Self-Concept Ambiguity: Scale Adaptation and Validation

Amelia E Talley, Jordan E Stevens, Amelia E Talley, Jordan E Stevens

Abstract

The current article describes the adaptation of a measure of sexual orientation self-concept ambiguity (SSA) from an existing measure of general self-concept clarity. Latent "trait" scores of SSA reflect the extent to which a person's beliefs about their own sexual orientation are perceived as inconsistent, unreliable, or incongruent. Sexual minority and heterosexual women ( n = 348), ages 18 to 30, completed a cross-sectional survey. Categorical confirmatory factor analysis guided the selection of items to form a 10-item, self-report measure of SSA. In the current report, we also examine (a) reliability of the 10-item scale score, (b) measurement invariance based on respondents' sexual identity status and age group, and (c) correlations with preexisting surveys that purport to measure similar constructs and theoretical correlates. Evidence for internal reliability, measurement invariance (based on respondent sex), and convergent validity was also investigated in an independent, validation sample. The lowest SSA scores were reported by women who self-ascribed an exclusively heterosexual or exclusively lesbian/gay sexual identity, whereas those who reported a bisexual, mostly lesbian/gay, or mostly heterosexual identity, reported relatively higher SSA scores.

Keywords: scale adaptation; self-concept clarity; sexual minority; sexual self-concept.

Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1
Figure 1
Ten-item categorical confirmatory factor model for the calibration and validation samples. Note. SSA = sexual orientation self-concept ambiguity. Values before the slash are culled from the calibration sample model, whereas values following the slash are culled from the validation sample model. Values inside the circles are residual variances for each item.

Source: PubMed

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