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dc.contributor.authorUlbricht, Christine M.
dc.contributor.authorDumenci, Levent
dc.contributor.authorRothschild, Anthony J.
dc.contributor.authorLapane, Kate L.
dc.date2022-08-11T08:08:34.000
dc.date.accessioned2022-08-23T15:59:16Z
dc.date.available2022-08-23T15:59:16Z
dc.date.issued2015-10-05
dc.date.submitted2016-03-07
dc.identifier.citationAm J Mens Health. 2015 Oct 5. pii: 1557988315607297. <a href="http://dx.doi.org/10.1177/1557988315607297">Link to article on publisher's site</a>
dc.identifier.issn1557-9883 (Linking)
dc.identifier.doi10.1177/1557988315607297
dc.identifier.pmid26438468
dc.identifier.urihttp://hdl.handle.net/20.500.14038/30626
dc.description.abstractThe burden of depression in men is high. Current diagnostic criteria may not fully capture men's experience with depression. Descriptions of the heterogeneity in depression among men are lacking. The purpose of the study was to characterize latent subtypes of major depression and changes in these subtypes among men receiving citalopram in Level 1 of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. Latent transition analysis was applied to data from 387 men who completed baseline and Week 12 study visits in Level 1 of STAR*D. Items from the self-report version of the Quick Inventory of Depressive Symptomatology were used as indicators of latent depression subtypes. Four statuses were identified at baseline and Week 12. Baseline statuses were Mild (10% of men), Moderate (53%), Severe with Psychomotor Slowing (20%), and Severe with Psychomotor Agitation (17%). At Week 12, the statuses were Symptom Resolution (41%), Mild (36%), Moderate (18%), and Severe with Psychomotor Slowing (5%). Men in the Mild status were most likely to transition to Symptom Resolution (probability = 69%). Men in the Severe with Agitation status were least likely to transition to Symptom Resolution (probability = 0%). This work highlights the need to not focus solely on summary rating scores but to also consider patterns of symptoms when treating depression.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=26438468&dopt=Abstract">Link to Article in PubMed</a>
dc.relation.urlhttp://dx.doi.org/10.1177/1557988315607297
dc.subjectSTAR*D
dc.subjectdepression subtypes
dc.subjectlatent transition analysis
dc.subjectmajor depressive disorder
dc.subjectMental Disorders
dc.subjectPsychiatry
dc.titleChanges in Depression Subtypes Among Men in STAR*D: A Latent Transition Analysis
dc.typeJournal Article
dc.source.journaltitleAmerican journal of men's health
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/faculty_pubs/902
dc.identifier.contextkey8277644
html.description.abstract<p>The burden of depression in men is high. Current diagnostic criteria may not fully capture men's experience with depression. Descriptions of the heterogeneity in depression among men are lacking. The purpose of the study was to characterize latent subtypes of major depression and changes in these subtypes among men receiving citalopram in Level 1 of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. Latent transition analysis was applied to data from 387 men who completed baseline and Week 12 study visits in Level 1 of STAR*D. Items from the self-report version of the Quick Inventory of Depressive Symptomatology were used as indicators of latent depression subtypes. Four statuses were identified at baseline and Week 12. Baseline statuses were Mild (10% of men), Moderate (53%), Severe with Psychomotor Slowing (20%), and Severe with Psychomotor Agitation (17%). At Week 12, the statuses were Symptom Resolution (41%), Mild (36%), Moderate (18%), and Severe with Psychomotor Slowing (5%). Men in the Mild status were most likely to transition to Symptom Resolution (probability = 69%). Men in the Severe with Agitation status were least likely to transition to Symptom Resolution (probability = 0%). This work highlights the need to not focus solely on summary rating scores but to also consider patterns of symptoms when treating depression.</p>
dc.identifier.submissionpathfaculty_pubs/902
dc.contributor.departmentDepartment of Quantitative Health Sciences
dc.contributor.departmentDepartment of Psychiatry


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