DEPRESsion Screening Data (DEPRESSD) Project 

In 2012, Dr. Thombs and Dr. Andrea Benedetti, Associate Professor at McGill, partnered with local and international experts to set up the DEPRESsion Screening Data (DEPRESSD) Project to gather and synthesize large datasets and evaluate the accuracy of depression screening tools using individual participant data meta-analyses (IPDMAs). To date, the project has obtained CIHR funding to conduct analyses on the most commonly used depression screening tools in primary care (PHQ-9), perinatal care (EPDS), hospital care (HADS) and geriatric care (GDS). This project will allow us to provide practitioners and policy-makers with accurate, unbiased estimates of diagnostic accuracy for the screening tools, in order to better inform decisions on screening policy. Funded by 6 CIHR grants, the DEPRESSD collaboration now includes over 300 investigators from over 58 countries with numbers growing as more data are accrued. Large datasets for conducting IPDMAs and as a unique data sharing platform for the PHQ-9 (58 studies; 17,357 participants), HADS (83 studies; 19,839 participants), and EPDS (51 studies; 20,349 participants) with updates in process, as well as a new dataset on the GDS in progress.

To learn more about the DEPRESSD project, please visit the DEPRESSD website: https://www.depressd.ca/.

 

Living Systematic Review of Mental Health in COVID-19 :
On April 13, 2020, the DEPRESSD team initiated a new project - Living Systematic Review of Mental Health in COVID-19. Mental health during the current COVID-19 outbreak may be negatively affected by uncertainties associated with long-term personal, social, and societal implications of the crisis and from isolation due to social distancing and movement restrictions. Given the limitations in the quantity and quality of evidence available from previous infectious disease outbreaks and the different characteristics of the COVID-19 outbreak, synthesis of new mental health evidence that is being generated during COVID-19 is urgently needed.

The objectives of the living systematic review are to evaluate (1) changes in mental health symptoms from prior to COVID-19 to during the pandemic and across different time points in the pandemic; and (2) the effect of interventions on mental health symptoms during COVID-19.

Results of the living systematic review are updated and posted on the website: https://www.depressd.ca/covid-19-mental-health

Co-Principal  Investigator :

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Andrea Benedetti

Team Members:

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Brooke Levis

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Chen He

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Tiffany Dal Santo

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Kexin Li

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Danielle Rice

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Dipika  Neupane

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Eliana Brehaut

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Xia Qiu

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Sheryl Sun

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Olivia Bonardi

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Amina Tasleem

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Elsa-Lynn   Nassar

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Yin Wu

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Yutong Wang

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Anneke Yao

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Jizhou Tian

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Zelalem Negeri

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Ian Thombs-Vite

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Diana Jiang

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Yi Liu

Latest Publications: 

(Names of members of research team staff and students in bold)

Journal publications: 

Levis B, Negeri Z, Sun Y, Benedetti A, Thombs BD, for the DEPRESsion Screening Data (DEPRESSD) EPDS Collaboration. Accuracy of the Edinburgh Postnatal Depression Scale (EPDS) for screening to detect major depression: systematic review and meta-analysis of individual participant data. BMJ. In Press.

Wu Y, Levis B, Ioannidis J, Benedetti A, Thombs BD, on behalf of the DEPRESsion Screening Data (DEPRESSD) Collaboration. Probability of major depression based on the SCID, CIDI, and MINI diagnostic interviews: a synthesis of three individual participant data meta-analyses. Psychother Psychosom. Online ahead of print.

Levis B, Sun Y, He C, Wu Y, Krishnan A, Bhandari PM, Neupane D, Imran M, Brehaut E, Negeri Z, Fischer FH, Benedetti A, Thombs BD, for the DEPRESsion Screening Data (DEPRESSD) PHQ Collaboration. Accuracy of the PHQ-2 alone and in combination with the PHQ-9 for screening to detect major depression: an individual participant data meta-analysis. JAMA. 2020;323(22):2290-3000. Link: https://pubmed.ncbi.nlm.nih.gov/32515813/

Wu Y, Levis B, Riehm KE, Saadat N, Levis AW, Azar M, Rice DB, Boruff J, Cuijpers P, Gilbody S, Ioannidis JPA, Kloda LA, McMillan D, Patten SB, Shrier I, Ziegelstein RC, Akena DH, Arroll B, Ayalon L, Baradaran HR, Baron M, Bombardier CH, Butterworth P, Carter G, Chagas MH, Chan JCN, Cholera R, Conwell Y, de Man-van Ginkel JM, Fann JR, Fischer FH, Fung D, Gelaye B, Goodyear-Smith F, Greeno CG, Hall BJ, Harrison PA, Härter M, Hegerl U, Hides L, Hobfoll SE, Hudson M, Hyphantis T, Inagaki M, Jetté N, Khamseh ME, Kiely KM, Kwan Y, Lamers F, Liu S-I, Lotrakul M, Loureiro SR, Löwe B, McGuire A, Mohd-Sidik S, Munhoz TN, Muramatsu K, Osório FL, Patel V, Pence BW, Persoons P, Picardi A, Reuter K, Rooney AG, Santos IS, Shaaban J, Sidebottom A, Simning A, Stafford L, Sung S, Tan PLL, Turner A, van Weert HC, White J, Whooley MA, Winkley K, Yamada M, Benedetti A, Thombs BD. Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis. Psychol Med. 2019 Jul 12:1-13. doi: 10.1017/S0033291719001314. Link: https://pubmed.ncbi.nlm.nih.gov/31298180/

Levis B, Benedetti A, Thombs BD, and the DEPRESsion Screening Data (DEPRESSD) Collaboration (Riehm KE, Saadat N, Levis AW, Azar M, Rice DB, Chiovitti MJ, Sanchez TA, Boruff J, Cuijpers P, Gilbody S, Ioannidis JPA, Kloda LA, McMillan D, Patten SB, Shrier I, Ziegelstein RC, Akena DH, Arroll B, Ayalon L, Baradaran HR, Baron M, Bombardier CH, Butterworth P, Carter G, Chagas MH, Chan JCN, Clover K, Conwell Y, de Man-van Ginkel JM, Delgadillo J, Fann JR, Fischer FH, Fung D, Gelaye B, Goodyear-Smith F, Greeno CG, Hall BJ, Hambridge J, Harrison PA, Härter M, Hegerl U, Hides L, Hobfoll SE, Hudson M, Inagaki M, Ismail K, Jetté N, Khamseh ME, Kiely KM, Kwan Y, Liu SI, Lotrakul M, Loureiro SR, Löwe B, Marsh L, McGuire A, Mohd Sidik S, Munhoz TN, Muramatsu K, Osório FL, Patel V, Pence BW, Persoons P, Picardi A, Reuter K, Rooney AG, Santos IS, Shaaban J, Sidebottom A, Simning A, Stafford L, Sung SC, Tan PLL, Turner A, van der Feltz-Cornelis CM, van Weert HC, Vöhringer PA, White J, Whooley MA, Winkley K, Yamada M, and Zhang Y). Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis. BMJ. 2019;365:I1476. Link: https://pubmed.ncbi.nlm.nih.gov/30967483/

Study protocols:

Brehaut E, Neupane D, Levis B, Wu Y, Ioannidis JPA, Benedetti A, Thombs BD, and the and the DEPRESsion Screening Data (DEPRESSD) Collaboration. Optimal cutoff selection in depression screening studies using the PHQ-9, EPDS, and HADS. Open Science Framework. September 15, 2020. https://osf.io/fxhyw/

Neupane D, Bhandari PM, Levis B, Shrier I, Ioannidis JPA, Markham S, Thombs BD, Benedetti A, and the DEPRESsion Screening Data (DEPRESSD) Collaboration. Evaluation of direct and indirect methods for comparing the screening accuracy of the PHQ-9 and HADS-D: protocol for an individual participant data meta-analysis. Open Science Framework. June 8, 2020. https://osf.io/75v6u/

Bhandari PM, Levis B, Negeri Z, Wu Y, Ioannidis JPA, Shrier I, Cuijpers P, Thombs BD, Benedetti A, and the DEPRESsion Screening Data (DEPRESSD) EPDS Collaboration. Estimating confidence intervals for the Youden’s J optimal cutoff and correcting for optimism in associated accuracy estimates: Protocol for an analysis using individual participant data of the Edinburgh Postnatal Depression Scale. Open Science Framework. May 2, 2020. https://osf.io/5gqth/

Bhandari PM, Levis B, Negeri Z, Wu Y, Ioannidis JPA, Shrier I, Cuijpers P, Thombs BD, Benedetti A, and the DEPRESsion Screening Data (DEPRESSD) Collaboration. Estimating confidence intervals for the Youden’s J optimal cutoff and correcting for optimism in associated accuracy estimates: Protocol for an analysis using individual participant data of the Patient Health Questionnaire-9. Open Science Framework. February 12, 2020. https://osf.io/5gqth/

Brehaut E, Neupane D, Levis B, Wu Y, Benedetti A, Thombs BD, and the DEPRESsion Screening Data (DEPRESSD) HADS Collaboration. Depression prevalence based on the HADS depression subscale compared to Structured Clinical Interview for DSM classification: individual participant data meta-analysis. Open Science Framework. January 24, 2020. https://osf.io/n5a3e/