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Causal beliefs about depression as predictors of essentialist thinking and in network models
Descriptive
TitleInfo
Title
Causal beliefs about depression as predictors of essentialist thinking and in network models
Name
(type = personal)
NamePart
(type = family)
Mann
NamePart
(type = given)
Sarah Louise
NamePart
(type = date)
1979-
DisplayForm
Sarah Louise Mann
Role
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(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Contrada
NamePart
(type = given)
Richard J
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Richard J Contrada
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Leventhal
NamePart
(type = given)
Howard
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Howard Leventhal
Affiliation
Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Gara
NamePart
(type = given)
Michael
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Michael Gara
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Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Clemow
NamePart
(type = given)
Lynn
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Lynn Clemow
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
outside member
Name
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NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
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NamePart
School of Graduate Studies
Role
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school
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Text
Genre
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theses
OriginInfo
DateCreated
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2018
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(type = degree)
2018-01
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2018
Place
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xx
Language
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(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
This project includes two studies of causal beliefs about depression conducted in a U.S. adult sample (N = 319) via Amazon’s Mechanical Turk platform. Study 1 tested hypotheses based on essentialist theory, guided by the theoretical framework of Leventhal’s Commonsense Model (CSM) of illness cognition. Essentialist theory suggests that in the general population, biological causal beliefs about mental illnesses, including depression, frequently are associated with negative prognostic beliefs and stigmatizing attitudes. Consistent with this, findings indicated that biological causal beliefs were associated with viewing depression as more consequential and longer-lasting; contrary to hypotheses, biological attributions also predicted viewing depression as more treatable. Also counter to predictions, biological causal beliefs were inversely related to depression stigma; these relationships were partially mediated by beliefs about consequences and duration. Relationships between biological causal beliefs and stigma also were moderated by familiarity with depression, such that weaker biological attributions predicted higher levels of stigma specifically among participants who reported a history of depression. Study 2 used network analysis to model perceived interrelationships among putative causes of depression. Network models of causal beliefs were generated for the full sample and for subgroups reporting high versus low confidence in their understanding of depression (illness coherence). These models varied considerably in complexity and illuminated within-sample differences in construals of stress versus depression, beliefs about mutually maintaining factors (bidirectional relationships), and the role of biological causes in the context of other factors. Together, these studies suggest refinements to essentialist theory, avenues for future research into relationships between mental illness beliefs and stigma, and guidance for psychoeducation in depression treatment and public health messaging.
Subject
(authority = RUETD)
Topic
Psychology
Subject
(authority = ETD-LCSH)
Topic
Depression, Mental
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
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ETD_8573
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (x, 151 p. : ill.)
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Sarah Louise Mann
RelatedItem
(type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier
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rucore10001600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3M61PGP
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Mann
GivenName
Sarah
MiddleName
Louise
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(point = start)
2017-12-18 22:31:20
AssociatedEntity
Name
Sarah Mann
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Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
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ETD
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windows xp
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1.7
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2017-12-18T22:25:35
DateCreated
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2017-12-18T22:25:35
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Statistical Profile