Early PTSD Symptom Trajectories: Persistence, Recovery, and Response to Treatment: Results from the Jerusalem Trauma Outreach and Prevention Study (J-TOPS)
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{"title"=>"Early PTSD Symptom Trajectories: Persistence, Recovery, and Response to Treatment: Results from the Jerusalem Trauma Outreach and Prevention Study (J-TOPS)", "type"=>"journal", "authors"=>[{"first_name"=>"Isaac R.", "last_name"=>"Galatzer-Levy", "scopus_author_id"=>"16303648200"}, {"first_name"=>"Yael", "last_name"=>"Ankri", "scopus_author_id"=>"36135239600"}, {"first_name"=>"Sara", "last_name"=>"Freedman", "scopus_author_id"=>"7202419311"}, {"first_name"=>"Yossi", "last_name"=>"Israeli-Shalev", "scopus_author_id"=>"42261614100"}, {"first_name"=>"Pablo", "last_name"=>"Roitman", "scopus_author_id"=>"55832538700"}, {"first_name"=>"Moran", "last_name"=>"Gilad", "scopus_author_id"=>"55831656500"}, {"first_name"=>"Arieh Y.", "last_name"=>"Shalev", "scopus_author_id"=>"7101874657"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84882802043", "pui"=>"369632872", "doi"=>"10.1371/journal.pone.0070084", "isbn"=>"1932-6203", "sgr"=>"84882802043", "pmid"=>"23990895"}, "id"=>"3f1bf3c0-c95f-3f49-859c-007f06a23412", "abstract"=>"CONTEXT: Uncovering heterogeneities in the progression of early PTSD symptoms can improve our understanding of the disorder's pathogenesis and prophylaxis. OBJECTIVES: To describe discrete symptom trajectories and examine their relevance for preventive interventions. DESIGN: Latent Growth Mixture Modeling (LGMM) of data from a randomized controlled study of early treatment. LGMM identifies latent longitudinal trajectories by exploring discrete mixture distributions underlying observable data. SETTING: Hadassah Hospital unselectively receives trauma survivors from Jerusalem and vicinity. PARTICIPANTS: Adult survivors of potentially traumatic events consecutively admitted to the hospital's emergency department (ED) were assessed ten days and one-, five-, nine- and fifteen months after ED admission. Participants with data at ten days and at least two additional assessments (n = 957) were included; 125 received cognitive behavioral therapy (CBT) between one and nine months. APPROACH: We used LGMM to identify latent parameters of symptom progression and tested the effect of CBT on these parameters. CBT consisted of 12 weekly sessions of either cognitive therapy (n = 41) or prolonged exposure (PE, n = 49), starting 29.8+/-5.7 days after ED admission, or delayed PE (n = 35) starting at 151.8+/-42.4 days. CBT effectively reduced PTSD symptoms in the entire sample. MAIN OUTCOME MEASURE: Latent trajectories of PTSD symptoms; effects of CBT on these trajectories. RESULTS: THREE TRAJECTORIES WERE IDENTIFIED: Rapid Remitting (rapid decrease in symptoms from 1- to 5-months; 56% of the sample), Slow Remitting (progressive decrease in symptoms over 15 months; 27%) and Non-Remitting (persistently elevated symptoms; 17%). CBT accelerated the recovery of the Slow Remitting class but did not affect the other classes. CONCLUSIONS: The early course of PTSD symptoms is characterized by distinct and diverging response patterns that are centrally relevant to understanding the disorder and preventing its occurrence. Studies of the pathogenesis of PTSD may benefit from using clustered symptom trajectories as their dependent variables.", "link"=>"http://www.mendeley.com/research/early-ptsd-symptom-trajectories-persistence-recovery-response-treatment-results-jerusalem-trauma-out", "reader_count"=>69, "reader_count_by_academic_status"=>{"Student > Doctoral Student"=>6, "Researcher"=>10, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>2, "Other"=>7, "Student > Master"=>11, "Student > Bachelor"=>8, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Student > Doctoral Student"=>6, "Researcher"=>10, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>2, "Other"=>7, "Student > Master"=>11, "Student > Bachelor"=>8, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>6, "Biochemistry, Genetics and Molecular Biology"=>2, "Medicine and Dentistry"=>16, "Agricultural and Biological Sciences"=>3, "Neuroscience"=>4, "Psychology"=>32, "Social Sciences"=>4, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>16}, "Neuroscience"=>{"Neuroscience"=>4}, "Social Sciences"=>{"Social Sciences"=>4}, "Psychology"=>{"Psychology"=>32}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Unspecified"=>{"Unspecified"=>6}}, "reader_count_by_country"=>{"United Kingdom"=>1, "Ethiopia"=>1, "Spain"=>1}, "group_count"=>5}

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  • {"files"=>["https://ndownloader.figshare.com/files/1179788"], "description"=>"<p><i>Note</i>. <i>Est = Estimate; SE = Standard Error.</i></p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Clinical research design", "Clinical epidemiology", "Mental health", "psychiatry", "Anxiety disorders", "psychology", "Psychological stress", "parameter", "estimates", "3-classes"], "article_id"=>780374, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Isaac R. Galatzer-Levy", "Yael Ankri", "Sara Freedman", "Yossi Israeli-Shalev", "Pablo Roitman", "Moran Gilad", "Arieh Y. Shalev"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0070084.t003", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Growth_Factor_Parameter_Estimates_for_Treatment_on_the_Slope_of_the_3_Classes_n_8202_8202_957_/780374", "title"=>"Growth Factor Parameter Estimates for Treatment on the Slope of the 3-Classes (n = 957).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-08-22 02:21:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1179789"], "description"=>"<p><i>Note.</i> AIC = Akaike information criterion; BIC = Bayesian information criterion; SSBIC = sample size adjusted Bayesian information criterion; LRT = Lo-Mendell-Rubin test; BLRT = bootstrap likelihood ratio test.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Clinical research design", "Clinical epidemiology", "Mental health", "psychiatry", "Anxiety disorders", "psychology", "Psychological stress", "indices", "one-", "four-class", "ptsd", "severity"], "article_id"=>780375, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Isaac R. Galatzer-Levy", "Yael Ankri", "Sara Freedman", "Yossi Israeli-Shalev", "Pablo Roitman", "Moran Gilad", "Arieh Y. Shalev"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0070084.t002", "stats"=>{"downloads"=>5, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Fit_Indices_for_One_to_Four_Class_Growth_Mixture_Models_of_PTSD_Symptom_Severity_n_8202_8202_957_/780375", "title"=>"Fit Indices for One- to Four-Class Growth Mixture Models of PTSD Symptom Severity (n = 957).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-08-22 02:21:01"}

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Relative Metric

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