The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed on March 19, 2010). Thesis advisor: Dr. Anna Bardone-Cone. Includes bibliographical references.

Thesis (M.A.)--Denver Seminary, 2007. / Abstract and vita. Includes bibliographical references (leaves 71-78).

Thesis (Ph. D.)--University of Tennessee, Knoxville, 2003. / Title from title page screen (viewed Sept. 24, 2003). Thesis advisor: Dr. Schuyler Huck. Document formatted into pages (vii, 133 p.). Vita. Includes bibliographical references (p. 112-123).

Thesis (Ph. D.)--University of Oregon, 2002. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 139-152). Also available for download via the World Wide Web; free to University of Oregon users.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 225-240). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 196-208). Available also in a digital version from Dissertation Abstracts.

Anxiety and depression are debilitating disorders that often co-occur. Their differentiation has important ramifications for theory and treatment. Beck's (1976) Cognitive Content Specificity (CCS) hypothesis proposes that depression and anxiety are characterized by unique cognitive profiles that should be reflected, among other variables, in their cognitions. Further, the Balanced States of Mind model (BSOM; Schwartz, 1997) asserts that the cognitive ratio of positive to the sum of positive and negative cognitions is implicated in distinguishing various levels of pathology from optimal functioning. The present study used a cross-sectional design to compare the differentiating abilities of the CCS hypothesis and the joint CCS/BSOM model by examining depression and test anxiety-relevant positive and negative cognitions separately versus the BSOM cognitive ratios. Additionally, the specific interval predictions of the BSOM model were tested for test anxiety and depressive content. Four groups of college women were selected from a larger sample of college women from a large public university: Depressed (n = 51), Test Anxious (n = 51), "Mixed" Depressed and Test Anxious (n = 51), and Control (n = 51). Findings indicated that the Depressed Group differed from Test Anxious Group on test anxious and depressive negative cognitions and BSOM ratios. Consistent with previous literature, positive anxious content yielded less specificity, as it failed to discriminate between test anxious and depressed groups. While the "Mixed" group was most dysfunctional, Controls showed a least dysfunctional cognitive profile on both cognitions and cognitive ratios. Thus, the quantitative parameters of the BSOM model with varying content were partially validated, with depressive content not fitting the predictions as well as test anxious content. Results support the integration of the CCS and BSOM models and the use of a specific anxiety disorder (i.e., test anxiety) as ways to improve depression-anxiety differentiation in nonclinical populations. Theoretical and treatment implications are highlighted, and limitations are discussed.

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