Multifactorial prediction of depression diagnosis and symptom dimensions. (April 2021)
- Record Type:
- Journal Article
- Title:
- Multifactorial prediction of depression diagnosis and symptom dimensions. (April 2021)
- Main Title:
- Multifactorial prediction of depression diagnosis and symptom dimensions
- Authors:
- McNamara, Mary E.
Shumake, Jason
Stewart, Rochelle A.
Labrada, Jocelyn
Alario, Alexandra
Allen, John J.B.
Palmer, Rohan
Schnyer, David M.
McGeary, John E.
Beevers, Christopher G. - Abstract:
- Highlights: Psychiatric control groups can help isolate factors specific to the diagnosis of interest. Low positive self-referential processing is a strong differentiator of depression. Additionally, anhedonia and impairment are also important predictors. Abstract: While depression is a leading cause of disability, prior investigations of depression have been limited by studying correlates in isolation. A data-driven approach was applied to identify out-of-sample predictors of current depression from adults ( N = 217) sampled on a continuum of no depression to clinical levels. The current study used elastic net regularized regression and predictors from sociodemographic, self-report, polygenic scores, resting electroencephalography, pupillometry, actigraphy, and cognitive tasks to classify individuals into currently depressed (MDE), psychiatric control (PC), and no current psychopathology (NP) groups, as well as predicting symptom severity and lifetime MDE. Cross-validated models explained 20.6% of the out-of-fold deviance for the classification of MDEs versus PC, 33.2% of the deviance for MDE versus NP, but -0.6% of the deviance between PC and NP. Additionally, predictors accounted for 25.7% of the out-of-fold variance in anhedonia severity, 65.7% of the variance in depression severity, and 12.9% of the deviance in lifetime depression (yes/no). Self-referent processing, anhedonia, and psychosocial functioning emerged as important differentiators of MDE and PC groups.Highlights: Psychiatric control groups can help isolate factors specific to the diagnosis of interest. Low positive self-referential processing is a strong differentiator of depression. Additionally, anhedonia and impairment are also important predictors. Abstract: While depression is a leading cause of disability, prior investigations of depression have been limited by studying correlates in isolation. A data-driven approach was applied to identify out-of-sample predictors of current depression from adults ( N = 217) sampled on a continuum of no depression to clinical levels. The current study used elastic net regularized regression and predictors from sociodemographic, self-report, polygenic scores, resting electroencephalography, pupillometry, actigraphy, and cognitive tasks to classify individuals into currently depressed (MDE), psychiatric control (PC), and no current psychopathology (NP) groups, as well as predicting symptom severity and lifetime MDE. Cross-validated models explained 20.6% of the out-of-fold deviance for the classification of MDEs versus PC, 33.2% of the deviance for MDE versus NP, but -0.6% of the deviance between PC and NP. Additionally, predictors accounted for 25.7% of the out-of-fold variance in anhedonia severity, 65.7% of the variance in depression severity, and 12.9% of the deviance in lifetime depression (yes/no). Self-referent processing, anhedonia, and psychosocial functioning emerged as important differentiators of MDE and PC groups. Findings highlight the advantages of using psychiatric control groups to isolate factors specific to depression. … (more)
- Is Part Of:
- Psychiatry research. Volume 298(2021)
- Journal:
- Psychiatry research
- Issue:
- Volume 298(2021)
- Issue Display:
- Volume 298, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 298
- Issue:
- 2021
- Issue Sort Value:
- 2021-0298-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04
- Subjects:
- Statistical learning -- Psychiatric control -- Classification
Psychiatry -- Periodicals
Psychiatry -- periodicals
Psychiatrie -- Périodiques
616.89 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01651781 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.psychres.2021.113805 ↗
- Languages:
- English
- ISSNs:
- 0165-1781
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6946.263700
British Library DSC - BLDSS-3PM
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- 22872.xml