#Sad: Twitter Content Predicts Changes in Cognitive Vulnerability and Depressive Symptoms.
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| Title: | #Sad: Twitter Content Predicts Changes in Cognitive Vulnerability and Depressive Symptoms. |
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| Authors: | Sasso, Maria P. (AUTHOR), Giovanetti, Annaleis K. (AUTHOR), Schied, Anastasia L. (AUTHOR), Burke, Hugh H. (AUTHOR), Haeffel, Gerald J. (AUTHOR) |
| Source: | Cognitive Therapy & Research. Aug2019, Vol. 43 Issue 4, p657-665. 9p. 1 Diagram, 2 Charts. |
| Subjects: | Social anxiety, Social media, Mental health, Social networks, Disease risk factors |
| Abstract: | Research shows that social media networks can affect both the physical and mental health of its users. We hypothesized that social media would also be associated with cognitive vulnerability to depression. To test this hypothesis, we used a 3-month pre-post prospective longitudinal design with a sample of undergraduates (n = 105). Results showed that participants who had tweets with a "past focus" (as determined by LIWC software) were more likely to exhibit increases in cognitive vulnerability and depressive symptoms than participants who did not have tweets with a past focus. Increases in cognitive vulnerability were associated with increases in depressive symptoms. However, the effect of Twitter content on future depressive symptoms was not accounted for by increases in cognitive vulnerability. Rather, one's past focus Twitter content had an effect on future depressive symptoms that was independent of its effect on future cognitive vulnerability levels. These results provide further support for the plasticity of cognitive vulnerability in early adulthood as well as corroborate emerging evidence for the association between social media and mental health risk factors. [ABSTRACT FROM AUTHOR] |
| Copyright of Cognitive Therapy & Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 137076452 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: #Sad: Twitter Content Predicts Changes in Cognitive Vulnerability and Depressive Symptoms. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sasso%2C+Maria+P%2E%22">Sasso, Maria P.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Giovanetti%2C+Annaleis+K%2E%22">Giovanetti, Annaleis K.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schied%2C+Anastasia+L%2E%22">Schied, Anastasia L.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Burke%2C+Hugh+H%2E%22">Burke, Hugh H.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Haeffel%2C+Gerald+J%2E%22">Haeffel, Gerald J.</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Cognitive+Therapy+%26+Research%22">Cognitive Therapy & Research</searchLink>. Aug2019, Vol. 43 Issue 4, p657-665. 9p. 1 Diagram, 2 Charts. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Social+anxiety%22">Social anxiety</searchLink><br /><searchLink fieldCode="DE" term="%22Social+media%22">Social media</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+health%22">Mental health</searchLink><br /><searchLink fieldCode="DE" term="%22Social+networks%22">Social networks</searchLink><br /><searchLink fieldCode="DE" term="%22Disease+risk+factors%22">Disease risk factors</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Research shows that social media networks can affect both the physical and mental health of its users. We hypothesized that social media would also be associated with cognitive vulnerability to depression. To test this hypothesis, we used a 3-month pre-post prospective longitudinal design with a sample of undergraduates (n = 105). Results showed that participants who had tweets with a "past focus" (as determined by LIWC software) were more likely to exhibit increases in cognitive vulnerability and depressive symptoms than participants who did not have tweets with a past focus. Increases in cognitive vulnerability were associated with increases in depressive symptoms. However, the effect of Twitter content on future depressive symptoms was not accounted for by increases in cognitive vulnerability. Rather, one's past focus Twitter content had an effect on future depressive symptoms that was independent of its effect on future cognitive vulnerability levels. These results provide further support for the plasticity of cognitive vulnerability in early adulthood as well as corroborate emerging evidence for the association between social media and mental health risk factors. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Cognitive Therapy & Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=137076452 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10608-019-10001-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 657 Subjects: – SubjectFull: Social anxiety Type: general – SubjectFull: Social media Type: general – SubjectFull: Mental health Type: general – SubjectFull: Social networks Type: general – SubjectFull: Disease risk factors Type: general Titles: – TitleFull: #Sad: Twitter Content Predicts Changes in Cognitive Vulnerability and Depressive Symptoms. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sasso, Maria P. – PersonEntity: Name: NameFull: Giovanetti, Annaleis K. – PersonEntity: Name: NameFull: Schied, Anastasia L. – PersonEntity: Name: NameFull: Burke, Hugh H. – PersonEntity: Name: NameFull: Haeffel, Gerald J. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 01475916 Numbering: – Type: volume Value: 43 – Type: issue Value: 4 Titles: – TitleFull: Cognitive Therapy & Research Type: main |
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