Language and the role of gender for predicting schizophrenia in high-risk individuals
dc.contributor.advisor
Bak, Thomas
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dc.contributor.author
Crowther, Jamie
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dc.contributor.author
Malicki, Isabella
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dc.date.accessioned
2016-08-17T13:43:39Z
dc.date.available
2016-08-17T13:43:39Z
dc.date.issued
2014-05-23
dc.description.abstract
There are numerous language abnormalities in schizophrenia which have been consistently observed and reported. There are also well-covered gender differences in how the illness is expressed. However, comparatively little is known about what kinds of symptoms are present in the earlier stages of the disease, before a formal diagnosis is made. The Edinburgh High Risk Study of schizophrenia was a longitudinal study of individuals at a high genetic risk for schizophrenia, some of whom went on to develop the illness. By analysing interview transcripts from this study, Watson et al. (2012) found that people at high risk who developed schizophrenia used significantly more of the second person pronoun 'you' than those at high risk who did not develop the illness. The purpose of the present study was to replicate and expand this finding to all second person pronouns, and to see if other abnormalities present in schizophrenic speech were observable. We also looked at how these might differ between men and women. We found no significant difference between those who went on to develop schizophrenia and those who did not on any measures (including second person pronouns), and gender had no significant effect. However there were methodological and technical issues (mostly relating to insufficient statistical power) that may account for this finding. We therefore provided methodological recommendations and guidelines for future studies, and highlighted some potentially promising avenues of research.
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dc.identifier.uri
http://hdl.handle.net/1842/16068
dc.language.iso
en
dc.publisher
The University of Edinburgh
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dc.subject
Schizophrenia
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dc.subject
Language
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dc.subject
Gender
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dc.title
Language and the role of gender for predicting schizophrenia in high-risk individuals
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Undergraduate
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dc.type.qualificationname
MA Master of Arts
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dcterms.accessRights
Restricted Access
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