The University of Southampton
University of Southampton Institutional Repository

Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta‐analysis.

Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta‐analysis.
Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta‐analysis.
Objectives
A previous individual participant data meta-analysis (IPDMA) identified differences in major depression classification rates between different diagnostic interviews, controlling for depressive symptoms on the basis of the Patient Health Questionnaire-9. We aimed to determine whether similar results would be seen in a different population, using studies that administered the Edinburgh Postnatal Depression Scale (EPDS) in pregnancy or postpartum.

Methods
Data accrued for an EPDS diagnostic accuracy IPDMA were analysed. Binomial generalised linear mixed models were fit to compare depression classification odds for the Mini International Neuropsychiatric Interview (MINI), Composite International Diagnostic Interview (CIDI), and Structured Clinical Interview for DSM (SCID), controlling for EPDS scores and participant characteristics.

Results
Among fully structured interviews, the MINI (15 studies, 2,532 participants, 342 major depression cases) classified depression more often than the CIDI (3 studies, 2,948 participants, 194 major depression cases; adjusted odds ratio [aOR] = 3.72, 95% confidence interval [CI] [1.21, 11.43]). Compared with the semistructured SCID (28 studies, 7,403 participants, 1,027 major depression cases), odds with the CIDI (interaction aOR = 0.88, 95% CI [0.85, 0.92]) and MINI (interaction aOR = 0.95, 95% CI [0.92, 0.99]) increased less as EPDS scores increased.

Conclusion
Different interviews may not classify major depression equivalently.
1049-8931
Levis, Brooke
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McMillan, Dean
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Levis, Brooke, McMillan, Dean, Sun, Ying, He, Chen, Rice, Danielle B., Krishnan, Ankur, Wu, Yin, Azar, Marleine, Sanchez, Tatiana A., Chiovitti, Matthew J., Bhandari, Parash Mani, Neupane, Dipika, Saadat, Nazanin, Riehm, Kira E., Imran, Mahrukh, Boruff, Jill T., Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P. A., Kloda, Lorie A., Patten, Scott B, Shrier, Ian, Ziegelstein, Roy C., Comeau, Liane, Mitchell, Nicholas D., Tonelli, Marcello, Vigod, Simone N., Aceti, Franca, Alvarado, Rubén, Alvarado-Esquivel, Cosme, Bakare, Muideen O., Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, Boyce, Philip M., Bunevicius, Adomas, Castro e Couto, Tiago, Chaudron, Linda H., Correa, Humberto, de Figueiredo, Felipe Pinheiro, Eapen, Valsamma, Fernandes, Michelle, Figueiredo, Barbara, Fisher, Jane R.W., Garcia-Esteve, Lluïsa, Giardinelli, Lisa, Helle, Nadine, Howard, Louise M., Khalifa, Dina Sami, Kohlhoff, Jane, Kusminskas, Laima, Kozinszky, Zoltan, Lelli, Lorenzo, Leonardou, Angeliki A., Lewis, Beth A., Maes, Michael, Meuti, Valentina, Nakic Rados, Sandra, Navarro Garcia, Purificacion, Nishi, Daisuke, Luwa E-Andjafono, Daniel Okitundu, Robertson-Blackmore, Emma, Rochat, Tamsen J., Rowe, Heather J., Siu, Bonnie W. M., Skalkidou, Alkistis, Stein, Alan, Stewart, Robert C., Su, Kuan-pin, Sundstrom-Poromaa, Inger, Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Thiagayson, Pavaani, Toreki, Annamaria, Torres-Gimenez, Anna, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega-Dienstmaier, Johann M., Wynter, Karen and Yonkers, Kimberly A. (2019) Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta‐analysis. International Journal of Methods in Psychiatric Research, 28 (4), [e1803]. (doi:10.1002/mpr.1803).

Record type: Article

Abstract

Objectives
A previous individual participant data meta-analysis (IPDMA) identified differences in major depression classification rates between different diagnostic interviews, controlling for depressive symptoms on the basis of the Patient Health Questionnaire-9. We aimed to determine whether similar results would be seen in a different population, using studies that administered the Edinburgh Postnatal Depression Scale (EPDS) in pregnancy or postpartum.

Methods
Data accrued for an EPDS diagnostic accuracy IPDMA were analysed. Binomial generalised linear mixed models were fit to compare depression classification odds for the Mini International Neuropsychiatric Interview (MINI), Composite International Diagnostic Interview (CIDI), and Structured Clinical Interview for DSM (SCID), controlling for EPDS scores and participant characteristics.

Results
Among fully structured interviews, the MINI (15 studies, 2,532 participants, 342 major depression cases) classified depression more often than the CIDI (3 studies, 2,948 participants, 194 major depression cases; adjusted odds ratio [aOR] = 3.72, 95% confidence interval [CI] [1.21, 11.43]). Compared with the semistructured SCID (28 studies, 7,403 participants, 1,027 major depression cases), odds with the CIDI (interaction aOR = 0.88, 95% CI [0.85, 0.92]) and MINI (interaction aOR = 0.95, 95% CI [0.92, 0.99]) increased less as EPDS scores increased.

Conclusion
Different interviews may not classify major depression equivalently.

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More information

Accepted/In Press date: 16 August 2019
e-pub ahead of print date: 30 September 2019
Published date: 1 December 2019
Additional Information: © 2019 The Authors. International Journal of Methods in Psychiatric Research published by John Wiley & Sons Ltd

Identifiers

Local EPrints ID: 468376
URI: http://eprints.soton.ac.uk/id/eprint/468376
ISSN: 1049-8931
PURE UUID: 5c99d295-8a5c-4e4c-8f7c-76a8b11c50f7
ORCID for Michelle Fernandes: ORCID iD orcid.org/0000-0002-0051-3389

Catalogue record

Date deposited: 11 Aug 2022 16:57
Last modified: 17 Mar 2024 04:10

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Contributors

Author: Brooke Levis
Author: Dean McMillan
Author: Ying Sun
Author: Chen He
Author: Danielle B. Rice
Author: Ankur Krishnan
Author: Yin Wu
Author: Marleine Azar
Author: Tatiana A. Sanchez
Author: Matthew J. Chiovitti
Author: Parash Mani Bhandari
Author: Dipika Neupane
Author: Nazanin Saadat
Author: Kira E. Riehm
Author: Mahrukh Imran
Author: Jill T. Boruff
Author: Pim Cuijpers
Author: Simon Gilbody
Author: John P. A. Ioannidis
Author: Lorie A. Kloda
Author: Scott B Patten
Author: Ian Shrier
Author: Roy C. Ziegelstein
Author: Liane Comeau
Author: Nicholas D. Mitchell
Author: Marcello Tonelli
Author: Simone N. Vigod
Author: Franca Aceti
Author: Rubén Alvarado
Author: Cosme Alvarado-Esquivel
Author: Muideen O. Bakare
Author: Jacqueline Barnes
Author: Cheryl Tatano Beck
Author: Carola Bindt
Author: Philip M. Boyce
Author: Adomas Bunevicius
Author: Tiago Castro e Couto
Author: Linda H. Chaudron
Author: Humberto Correa
Author: Felipe Pinheiro de Figueiredo
Author: Valsamma Eapen
Author: Michelle Fernandes ORCID iD
Author: Barbara Figueiredo
Author: Jane R.W. Fisher
Author: Lluïsa Garcia-Esteve
Author: Lisa Giardinelli
Author: Nadine Helle
Author: Louise M. Howard
Author: Dina Sami Khalifa
Author: Jane Kohlhoff
Author: Laima Kusminskas
Author: Zoltan Kozinszky
Author: Lorenzo Lelli
Author: Angeliki A. Leonardou
Author: Beth A. Lewis
Author: Michael Maes
Author: Valentina Meuti
Author: Sandra Nakic Rados
Author: Purificacion Navarro Garcia
Author: Daisuke Nishi
Author: Daniel Okitundu Luwa E-Andjafono
Author: Emma Robertson-Blackmore
Author: Tamsen J. Rochat
Author: Heather J. Rowe
Author: Bonnie W. M. Siu
Author: Alkistis Skalkidou
Author: Alan Stein
Author: Robert C. Stewart
Author: Kuan-pin Su
Author: Inger Sundstrom-Poromaa
Author: Meri Tadinac
Author: S. Darius Tandon
Author: Iva Tendais
Author: Pavaani Thiagayson
Author: Annamaria Toreki
Author: Anna Torres-Gimenez
Author: Thach D. Tran
Author: Kylee Trevillion
Author: Katherine Turner
Author: Johann M. Vega-Dienstmaier
Author: Karen Wynter
Author: Kimberly A. Yonkers

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