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The Attribution Theory of Hopelessness Depression: Conscious Causal Analysis or Unconscious Linguistic Bias?

Attribution theory holds that the affective reaction and mood that people develop in response to a situation is to a great degree dependent on what they perceive has caused the situation. Self-blame is a specific result of certain attributions and often leads to depression. The main purpose of this study is to determine if a relationship exists between a specific, character-related linguistic bias and an increased risk for, and an elevated level of, depression. This is accomplished by comparing subjects' test results in a measure of linguistic bias with the Beck Depression Inventory score and with a measurement of attributional style. Further, by drawing on the philosophical basis of cognitive therapeutic practices, it is argued that self-blame is only related to depression if it is characterological in nature and that such characterological self-blame is implicit in the linguistic style of the individual. Elevated usage of the verb "to be" in evaluating a negative life event was found to correlate with an above-average level of the somatic symptoms of depression. Subjects who preferred "to be" sentences also made more attributions of stability in regard to the hypothetical negative scenarios. Very little correlation was obtained between depression levels and depressogenic attributions. It is argued that while the usage of specific words and the application of depressogenic attributions are confounded, the use of two separate questionnaires both related to a common vignette permits some separation. While linguistic bias does not explain the development of depression, it is at least as good a correlate as attributional style. Depressogenic biases in word usage may be the conscious expression of attributional style. / Thesis / Master of Science (MS)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/24309
Date09 1900
CreatorsBell, Martin
ContributorsCarment, D. W., Psychology
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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