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Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach

BACKGROUND: Postpartum depression can take many forms. Different symptom patterns could have divergent implications for how we screen, diagnose, and treat postpartum depression. We sought to utilise a recently developed robust estimation algorithm to automatically identify differential patterns in d...

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Autores principales: Nieser, Kenneth J., Stowe, Zachary N., Newport, D. Jeffrey, Coker, Jessica L., Cochran, Amy L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925853/
https://www.ncbi.nlm.nih.gov/pubmed/36798754
http://dx.doi.org/10.1016/j.eclinm.2023.101830
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author Nieser, Kenneth J.
Stowe, Zachary N.
Newport, D. Jeffrey
Coker, Jessica L.
Cochran, Amy L.
author_facet Nieser, Kenneth J.
Stowe, Zachary N.
Newport, D. Jeffrey
Coker, Jessica L.
Cochran, Amy L.
author_sort Nieser, Kenneth J.
collection PubMed
description BACKGROUND: Postpartum depression can take many forms. Different symptom patterns could have divergent implications for how we screen, diagnose, and treat postpartum depression. We sought to utilise a recently developed robust estimation algorithm to automatically identify differential patterns in depressive symptoms and subsequently characterise the individuals who exhibit different patterns. METHODS: Depressive symptom data (N = 548) were collected from women with neuropsychiatric illnesses at two U.S. urban sites participating in a longitudinal observational study of stress across the perinatal period. Data were collected from Emory University between 1994 and 2012 and from the University of Arkansas for Medical Sciences between 2012 and 2017. We conducted an exploratory factor analysis of Beck Depression Inventory (BDI) items using a robust expectation-maximization algorithm, rather than a conventional expectation-maximization algorithm. This recently developed method enabled automatic detection of differential symptom patterns. We described differences in symptom patterns and conducted unadjusted and adjusted analyses of associations of symptom patterns with demographics and psychiatric histories. FINDINGS: 53 (9.7%) participants were identified by the algorithm as having a different pattern of reported symptoms compared to other participants. This group had more severe symptoms across all items—especially items related to thoughts of self-harm and self-judgement—and differed in how their symptoms related to underlying psychological constructs. History of social anxiety disorder (OR: 4.0; 95% CI [1.9, 8.1]) and history of childhood trauma (for each 5-point increase, OR: 1.2; 95% CI [1.1, 1.3]) were significantly associated with this differential pattern after adjustment for other covariates. INTERPRETATION: Social anxiety disorder and childhood trauma are associated with differential patterns of severe postpartum depressive symptoms, which might warrant tailored strategies for screening, diagnosis, and treatment to address these comorbid conditions. FUNDING: There are no funding sources to declare.
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spelling pubmed-99258532023-02-15 Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach Nieser, Kenneth J. Stowe, Zachary N. Newport, D. Jeffrey Coker, Jessica L. Cochran, Amy L. eClinicalMedicine Articles BACKGROUND: Postpartum depression can take many forms. Different symptom patterns could have divergent implications for how we screen, diagnose, and treat postpartum depression. We sought to utilise a recently developed robust estimation algorithm to automatically identify differential patterns in depressive symptoms and subsequently characterise the individuals who exhibit different patterns. METHODS: Depressive symptom data (N = 548) were collected from women with neuropsychiatric illnesses at two U.S. urban sites participating in a longitudinal observational study of stress across the perinatal period. Data were collected from Emory University between 1994 and 2012 and from the University of Arkansas for Medical Sciences between 2012 and 2017. We conducted an exploratory factor analysis of Beck Depression Inventory (BDI) items using a robust expectation-maximization algorithm, rather than a conventional expectation-maximization algorithm. This recently developed method enabled automatic detection of differential symptom patterns. We described differences in symptom patterns and conducted unadjusted and adjusted analyses of associations of symptom patterns with demographics and psychiatric histories. FINDINGS: 53 (9.7%) participants were identified by the algorithm as having a different pattern of reported symptoms compared to other participants. This group had more severe symptoms across all items—especially items related to thoughts of self-harm and self-judgement—and differed in how their symptoms related to underlying psychological constructs. History of social anxiety disorder (OR: 4.0; 95% CI [1.9, 8.1]) and history of childhood trauma (for each 5-point increase, OR: 1.2; 95% CI [1.1, 1.3]) were significantly associated with this differential pattern after adjustment for other covariates. INTERPRETATION: Social anxiety disorder and childhood trauma are associated with differential patterns of severe postpartum depressive symptoms, which might warrant tailored strategies for screening, diagnosis, and treatment to address these comorbid conditions. FUNDING: There are no funding sources to declare. Elsevier 2023-02-01 /pmc/articles/PMC9925853/ /pubmed/36798754 http://dx.doi.org/10.1016/j.eclinm.2023.101830 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Articles
Nieser, Kenneth J.
Stowe, Zachary N.
Newport, D. Jeffrey
Coker, Jessica L.
Cochran, Amy L.
Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach
title Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach
title_full Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach
title_fullStr Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach
title_full_unstemmed Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach
title_short Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach
title_sort detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925853/
https://www.ncbi.nlm.nih.gov/pubmed/36798754
http://dx.doi.org/10.1016/j.eclinm.2023.101830
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