Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: a synthesis of three individual participant data meta-analyses

Y. Wu; B. Levis; J. P. A. Ioannidis; A. Benedetti; B. D. Thombs; DEPRESsion Screening Data (DEPRESSD) Collaboration

doi:10.1159/000509283

Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: a synthesis of three individual participant data meta-analyses

Y. Wu, B. Levis, J. P. A. Ioannidis, A. Benedetti^*, B. D. Thombs^*, DEPRESsion Screening Data (DEPRESSD) Collaboration

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

26 Citations (Scopus)

67 Downloads (Pure)

Abstract

Introduction: Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results. Objective: To compare the odds of the major depression classification based on the SCID, CIDI, and MINI. Methods: We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis. Results: In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies; 25,749 participants) classified major depression more often than the SCID (108 studies; 21,953 participants; aOR 1.46; 95% confidence interval [CI] 1.11-1.92]). Classification odds for the CIDI (30 studies; 21,703 participants) and the SCID did not differ overall (aOR 1.19; 95% CI 0.79-1.75); however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64; 95% CI 0.52-0.80). Conclusions: Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics.

Original language	English
Pages (from-to)	28-40
Number of pages	13
Journal	Psychotherapy and Psychosomatics
Volume	90
Issue number	1
DOIs	https://doi.org/10.1159/000509283
Publication status	Published - 2021

Keywords

depressive disorders
diagnostic interviews
individual participant data meta-analysis
major depression
classification

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10.1159/000509283

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Wu, Y., Levis, B., Ioannidis, J. P. A., Benedetti, A., Thombs, B. D., & DEPRESsion Screening Data (DEPRESSD) Collaboration (2021). Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: a synthesis of three individual participant data meta-analyses. Psychotherapy and Psychosomatics, 90(1), 28-40. https://doi.org/10.1159/000509283

@article{8be342cbda004e3280de54b5a776765d,

title = "Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: a synthesis of three individual participant data meta-analyses",

abstract = "Introduction: Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results. Objective: To compare the odds of the major depression classification based on the SCID, CIDI, and MINI. Methods: We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis. Results: In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies; 25,749 participants) classified major depression more often than the SCID (108 studies; 21,953 participants; aOR 1.46; 95% confidence interval [CI] 1.11-1.92]). Classification odds for the CIDI (30 studies; 21,703 participants) and the SCID did not differ overall (aOR 1.19; 95% CI 0.79-1.75); however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64; 95% CI 0.52-0.80). Conclusions: Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics. ",

keywords = "depressive disorders, diagnostic interviews, individual participant data meta-analysis, major depression, classification",

author = "Y. Wu and B. Levis and Ioannidis, {J. P. A.} and A. Benedetti and Thombs, {B. D.} and {DEPRESsion Screening Data (DEPRESSD) Collaboration} and Ying Sun and Chen He and Ankur Krishnan and Bhandari, {Parash Mani} and Dipika Neupane and Zelalem Negeri and Mahrukh Imran and Rice, {Danielle B.} and Riehm, {Kira E.} and Nazanin Saadat and Marleine Azar and Levis, {Alexander W.} and Sanchez, {Tatiana A.} and Chiovitti, {Matthew J.} and Yan, {Xin Wei} and Jill Boruff and Kloda, {Lorie A.} and Pim Cuijpers and Simon Gilbody and Dean McMillan and Patten, {Scott B.} and Ian Shrier and Ziegelstein, {Roy C.} and Liane Comeau and Mitchell, {Nicholas D.} and Marcello Tonelli and Vigod, {Simone N.} and Melissa Henry and Zahinoor Ismail and Loiselle, {Carmen G.} and Akena, {Dickens H.} and Samir Al-Adawi and Alamri, {Sultan H.} and Rub{\'e}n Alvarado and Cosme Alvarado-Esquivel and Dagmar Amtmann and Bruce Arroll and Liat Ayalon and Bakare, {Muideen O.} and Baradaran, {Hamid R.} and Jacqueline Barnes and Bavle, {Amar D.} and Beck, {Cheryl Tatano} and Anna Beraldi and Bernstein, {Charles N.} and Arvin Bhana and Carola Bindt and Bombardier, {Charles H.} and Boyce, {Philip M.} and Natalie B{\"u}el-Drabe and Buji, {Ryna Imma} and Adomas Bunevicius and Jurate Butnoriene and Robertas Bunevicius and Peter Butterworth and Gregory Carter and Chagas, {Marcos H.} and Chan, {Juliana C.N.} and Chan, {Lai Fong} and Chaudron, {Linda H.} and Chen, {Chih Ken} and Rushina Cholera and Kerrie Clover and Conroy, {Ron{\'a}n M.} and Aaron Conway and Yeates Conwell and Humberto Correa and {Castro E Couto}, Tiago and Daniel Cukor and Eli Dabscheck and Daray, {Federico M.} and {De Figueiredo}, {Felipe Pinheiro} and {De Man-Van Ginkel}, {Janneke M.} and Crisanto Diez-Quevedo and Elles Douven and Downing, {Marina G.} and Valsamma Eapen and Fann, {Jesse R.} and Anthony Feinstein and Ferentinos, {Panagiotis P.} and Michelle Fernandes and Sally Field and Barbara Figueiredo and Fischer, {Felix H.} and Fisher, {Jane R. W.} and Flint, {Alastair J.} and Maiko Fujimori and Fung, {Daniel S. S.} and Pamela Gallagher and Milena Gandy and Llu{\"i}sa Garcia-Esteve and Garman, {Emily C.} and Bizu Gelaye and Leila Gholizadeh and Lisa Giardinelli and Gibson, {Lorna J.} and Felicity Goodyear-Smith and Luigi Grassi and Green, {Eric P.} and Greeno, {Catherine G.} and Hall, {Brian J.} and Liisa Hantsoo and Haroz, {Emily E.} and Martin Harter and Ulrich Hegerl and Nadine Helle and Leanne Hides and Hobfoll, {Stevan E.} and Simone Honikman and Howard, {Louise M.} and Marie Hudson and Thomas Hyphantis and Masatoshi Inagaki and Josef Jenewein and Jeon, {Hong Jin} and Nathalie Jette and Monika Keller and Khalifa, {Dina Sami} and Khamseh, {Mohammad E.} and Kiely, {Kim M.} and Sung-Wan Kim and Marie Kjargaard and Sebastian Kohler and Jane Kohlhoff and Kohrt, {Brandon A.} and Zoltan Kozinszky and Laima Kusminskas and Yunxin Kwan and Femke Lamers and Lara, {Maria Asuncion} and Lorenzo Lelli and Leonardou, {Angeliki A.} and Levin-Aspenson, {Holly F.} and Manote Lotrakul and Loureiro, {Sonia R.} and Bernd Lowe and Luitel, {Nagendra P.} and Crick Lund and Michael Maes and Marrie, {Ruth Ann} and Laura Marsh and Rocio Martin-Santos and Marx, {Brian P.} and Loreto Massardo and Yutaka Matsuoka and Anja Mehner and Valentina Meuti and Ioannis Michopoulos and Laurent Misery and Sidik, {Sherina Mohd} and Munhoz, {Tiago N.} and Kumiko Muramatsu and Rado{\v s}, {Sandra Naki{\'c}} and Nakku, {Juliet E.M.} and Laura Navarrete and Garcia, {Purificacion Navarro} and Ricard Navines and Daisuke Nishi and O'Donnell, {Meaghan L.} and {Luwa E-Andjafono}, {Daniel Okitundu} and Os{\'o}rio, {Fl{\'a}via L.} and Ahmet {\"O}zt{\"u}rk and Jurate Peceliuniene and Pence, {Brian W.} and Philippe Persoons and Angelo Picardi and Luis Pintor and Ponsford, {Jennie L.} and Pugh, {Stephanie L.} and Quinn, {Terence J.} and Elmars Rancans and Rathod, {Sujit D.} and Reme, {Silje E.} and Katrin Reuter and Emma Robertson-Blackmore and Rochat, {Tamsen J.} and Rooney, {Alasdair G.} and Rowe, {Heather J.} and Roberto S{\'a}nchez-Gonz{\'a}lez and Santos, {In{\'a} S.} and Schram, {Miranda T.} and Schwarzbold, {Marcelo L.} and Cankorur, {Vesile Senturk} and Juwita Shaaban and Louise Sharpe and Shinn, {Eileen H.} and Abbey Sidebottom and S{\'e}bastien Simard and Adam Simning and Susanne Singer and Siu, {Bonnie W.M.} and Alkistis Skalkidou and Lena Spangenberg and Lesley Stafford and Alan Stein and Stewart, {Robert C.} and Jon Stone and Kuan-Pin Su and Serge Sultan and Inger Sundstr{\"o}m-Poromaa and Sung, {Sharon C.} and Keiko Suzuki and Meri Tadinac and Tan, {Pei Lin Lynnette} and Tandon, {S. Darius} and Martin Taylor-Rowan and Teixeira, {Antonio L.} and Iva Tendais and Pavaani Thiagayson and Istvan Tiringer and Annam{\'a}ria T{\"o}reki and Anna Torres-Gim{\'e}nez and Tran, {Thach D.} and Kylee Trevillion and Tung, {Ka Yee} and Alyna Turner and Katherine Turner and {Van Der Feltz-Cornelis}, {Christina M.} and {Van Heyningen}, Thandi and {Van Weert}, {Henk C.} and Vega-Dienstmaier, {Johann M.} and V{\"o}hringer, {Paul A.} and Wagner, {Lynne I.} and Mark Walterfang and Wang, {Jian Li} and Wenzheng Wang and Wang, {Liang Jen} and Jennifer White and Wong, {Dana K.} and Karen Wynter and Mitsuhiko Yamada and Yonkers, {Kimberly A.} and Zeng, {Qing Zhi} and Yuying Zhang",

year = "2021",

doi = "10.1159/000509283",

language = "English",

volume = "90",

pages = "28--40",

journal = "Psychotherapy and Psychosomatics",

issn = "0033-3190",

publisher = "S. Karger AG",

number = "1",

}

Wu, Y, Levis, B, Ioannidis, JPA, Benedetti, A, Thombs, BD & DEPRESsion Screening Data (DEPRESSD) Collaboration 2021, 'Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: a synthesis of three individual participant data meta-analyses', Psychotherapy and Psychosomatics, vol. 90, no. 1, pp. 28-40. https://doi.org/10.1159/000509283

TY - JOUR

T1 - Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews

T2 - a synthesis of three individual participant data meta-analyses

AU - Wu, Y.

AU - Levis, B.

AU - Ioannidis, J. P. A.

AU - Benedetti, A.

AU - Thombs, B. D.

AU - DEPRESsion Screening Data (DEPRESSD) Collaboration

AU - Sun, Ying

AU - He, Chen

AU - Krishnan, Ankur

AU - Bhandari, Parash Mani

AU - Neupane, Dipika

AU - Negeri, Zelalem

AU - Imran, Mahrukh

AU - Rice, Danielle B.

AU - Riehm, Kira E.

AU - Saadat, Nazanin

AU - Azar, Marleine

AU - Levis, Alexander W.

AU - Sanchez, Tatiana A.

AU - Chiovitti, Matthew J.

AU - Yan, Xin Wei

AU - Boruff, Jill

AU - Kloda, Lorie A.

AU - Cuijpers, Pim

AU - Gilbody, Simon

AU - McMillan, Dean

AU - Patten, Scott B.

AU - Shrier, Ian

AU - Ziegelstein, Roy C.

AU - Comeau, Liane

AU - Mitchell, Nicholas D.

AU - Tonelli, Marcello

AU - Vigod, Simone N.

AU - Henry, Melissa

AU - Ismail, Zahinoor

AU - Loiselle, Carmen G.

AU - Akena, Dickens H.

AU - Al-Adawi, Samir

AU - Alamri, Sultan H.

AU - Alvarado, Rubén

AU - Alvarado-Esquivel, Cosme

AU - Amtmann, Dagmar

AU - Arroll, Bruce

AU - Ayalon, Liat

AU - Bakare, Muideen O.

AU - Baradaran, Hamid R.

AU - Barnes, Jacqueline

AU - Bavle, Amar D.

AU - Beck, Cheryl Tatano

AU - Beraldi, Anna

AU - Bernstein, Charles N.

AU - Bhana, Arvin

AU - Bindt, Carola

AU - Bombardier, Charles H.

AU - Boyce, Philip M.

AU - Büel-Drabe, Natalie

AU - Buji, Ryna Imma

AU - Bunevicius, Adomas

AU - Butnoriene, Jurate

AU - Bunevicius, Robertas

AU - Butterworth, Peter

AU - Carter, Gregory

AU - Chagas, Marcos H.

AU - Chan, Juliana C.N.

AU - Chan, Lai Fong

AU - Chaudron, Linda H.

AU - Chen, Chih Ken

AU - Cholera, Rushina

AU - Clover, Kerrie

AU - Conroy, Ronán M.

AU - Conway, Aaron

AU - Conwell, Yeates

AU - Correa, Humberto

AU - Castro E Couto, Tiago

AU - Cukor, Daniel

AU - Dabscheck, Eli

AU - Daray, Federico M.

AU - De Figueiredo, Felipe Pinheiro

AU - De Man-Van Ginkel, Janneke M.

AU - Diez-Quevedo, Crisanto

AU - Douven, Elles

AU - Downing, Marina G.

AU - Eapen, Valsamma

AU - Fann, Jesse R.

AU - Feinstein, Anthony

AU - Ferentinos, Panagiotis P.

AU - Fernandes, Michelle

AU - Field, Sally

AU - Figueiredo, Barbara

AU - Fischer, Felix H.

AU - Fisher, Jane R. W.

AU - Flint, Alastair J.

AU - Fujimori, Maiko

AU - Fung, Daniel S. S.

AU - Gallagher, Pamela

AU - Gandy, Milena

AU - Garcia-Esteve, Lluïsa

AU - Garman, Emily C.

AU - Gelaye, Bizu

AU - Gholizadeh, Leila

AU - Giardinelli, Lisa

AU - Gibson, Lorna J.

AU - Goodyear-Smith, Felicity

AU - Grassi, Luigi

AU - Green, Eric P.

AU - Greeno, Catherine G.

AU - Hall, Brian J.

AU - Hantsoo, Liisa

AU - Haroz, Emily E.

AU - Harter, Martin

AU - Hegerl, Ulrich

AU - Helle, Nadine

AU - Hides, Leanne

AU - Hobfoll, Stevan E.

AU - Honikman, Simone

AU - Howard, Louise M.

AU - Hudson, Marie

AU - Hyphantis, Thomas

AU - Inagaki, Masatoshi

AU - Jenewein, Josef

AU - Jeon, Hong Jin

AU - Jette, Nathalie

AU - Keller, Monika

AU - Khalifa, Dina Sami

AU - Khamseh, Mohammad E.

AU - Kiely, Kim M.

AU - Kim, Sung-Wan

AU - Kjargaard, Marie

AU - Kohler, Sebastian

AU - Kohlhoff, Jane

AU - Kohrt, Brandon A.

AU - Kozinszky, Zoltan

AU - Kusminskas, Laima

AU - Kwan, Yunxin

AU - Lamers, Femke

AU - Lara, Maria Asuncion

AU - Lelli, Lorenzo

AU - Leonardou, Angeliki A.

AU - Levin-Aspenson, Holly F.

AU - Lotrakul, Manote

AU - Loureiro, Sonia R.

AU - Lowe, Bernd

AU - Luitel, Nagendra P.

AU - Lund, Crick

AU - Maes, Michael

AU - Marrie, Ruth Ann

AU - Marsh, Laura

AU - Martin-Santos, Rocio

AU - Marx, Brian P.

AU - Massardo, Loreto

AU - Matsuoka, Yutaka

AU - Mehner, Anja

AU - Meuti, Valentina

AU - Michopoulos, Ioannis

AU - Misery, Laurent

AU - Sidik, Sherina Mohd

AU - Munhoz, Tiago N.

AU - Muramatsu, Kumiko

AU - Radoš, Sandra Nakić

AU - Nakku, Juliet E.M.

AU - Navarrete, Laura

AU - Garcia, Purificacion Navarro

AU - Navines, Ricard

AU - Nishi, Daisuke

AU - O'Donnell, Meaghan L.

AU - Luwa E-Andjafono, Daniel Okitundu

AU - Osório, Flávia L.

AU - Öztürk, Ahmet

AU - Peceliuniene, Jurate

AU - Pence, Brian W.

AU - Persoons, Philippe

AU - Picardi, Angelo

AU - Pintor, Luis

AU - Ponsford, Jennie L.

AU - Pugh, Stephanie L.

AU - Quinn, Terence J.

AU - Rancans, Elmars

AU - Rathod, Sujit D.

AU - Reme, Silje E.

AU - Reuter, Katrin

AU - Robertson-Blackmore, Emma

AU - Rochat, Tamsen J.

AU - Rooney, Alasdair G.

AU - Rowe, Heather J.

AU - Sánchez-González, Roberto

AU - Santos, Iná S.

AU - Schram, Miranda T.

AU - Schwarzbold, Marcelo L.

AU - Cankorur, Vesile Senturk

AU - Shaaban, Juwita

AU - Sharpe, Louise

AU - Shinn, Eileen H.

AU - Sidebottom, Abbey

AU - Simard, Sébastien

AU - Simning, Adam

AU - Singer, Susanne

AU - Siu, Bonnie W.M.

AU - Skalkidou, Alkistis

AU - Spangenberg, Lena

AU - Stafford, Lesley

AU - Stein, Alan

AU - Stewart, Robert C.

AU - Stone, Jon

AU - Su, Kuan-Pin

AU - Sultan, Serge

AU - Sundström-Poromaa, Inger

AU - Sung, Sharon C.

AU - Suzuki, Keiko

AU - Tadinac, Meri

AU - Tan, Pei Lin Lynnette

AU - Tandon, S. Darius

AU - Taylor-Rowan, Martin

AU - Teixeira, Antonio L.

AU - Tendais, Iva

AU - Thiagayson, Pavaani

AU - Tiringer, Istvan

AU - Töreki, Annamária

AU - Torres-Giménez, Anna

AU - Tran, Thach D.

AU - Trevillion, Kylee

AU - Tung, Ka Yee

AU - Turner, Alyna

AU - Turner, Katherine

AU - Van Der Feltz-Cornelis, Christina M.

AU - Van Heyningen, Thandi

AU - Van Weert, Henk C.

AU - Vega-Dienstmaier, Johann M.

AU - Vöhringer, Paul A.

AU - Wagner, Lynne I.

AU - Walterfang, Mark

AU - Wang, Jian Li

AU - Wang, Wenzheng

AU - Wang, Liang Jen

AU - White, Jennifer

AU - Wong, Dana K.

AU - Wynter, Karen

AU - Yamada, Mitsuhiko

AU - Yonkers, Kimberly A.

AU - Zeng, Qing Zhi

AU - Zhang, Yuying

PY - 2021

Y1 - 2021

N2 - Introduction: Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results. Objective: To compare the odds of the major depression classification based on the SCID, CIDI, and MINI. Methods: We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis. Results: In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies; 25,749 participants) classified major depression more often than the SCID (108 studies; 21,953 participants; aOR 1.46; 95% confidence interval [CI] 1.11-1.92]). Classification odds for the CIDI (30 studies; 21,703 participants) and the SCID did not differ overall (aOR 1.19; 95% CI 0.79-1.75); however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64; 95% CI 0.52-0.80). Conclusions: Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics.

AB - Introduction: Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results. Objective: To compare the odds of the major depression classification based on the SCID, CIDI, and MINI. Methods: We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis. Results: In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies; 25,749 participants) classified major depression more often than the SCID (108 studies; 21,953 participants; aOR 1.46; 95% confidence interval [CI] 1.11-1.92]). Classification odds for the CIDI (30 studies; 21,703 participants) and the SCID did not differ overall (aOR 1.19; 95% CI 0.79-1.75); however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64; 95% CI 0.52-0.80). Conclusions: Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics.

KW - depressive disorders

KW - diagnostic interviews

KW - individual participant data meta-analysis

KW - major depression

KW - classification

UR - http://www.scopus.com/inward/record.url?scp=85095432734&partnerID=8YFLogxK

U2 - 10.1159/000509283

DO - 10.1159/000509283

M3 - Article

C2 - 32814337

AN - SCOPUS:85095432734

SN - 0033-3190

VL - 90

SP - 28

EP - 40

JO - Psychotherapy and Psychosomatics

JF - Psychotherapy and Psychosomatics

IS - 1

ER -

Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: a synthesis of three individual participant data meta-analyses

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