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148 results on '"Neupane, Dipika"'

1. Comparison of Patient Health Questionnaire-9, Edinburgh Postnatal Depression Scale and Hospital Anxiety and Depression – Depression subscale scores by administration mode: An individual participant data differential item functioning meta-analysis

Author

Azar, Marleine, Bhandari, Parash Mani, Chiovitti, Matthew J., He, Chen, Imran, Mahrukh, Krishnan, Ankur, Negeri, Zelalem, Neupane, Dipika, Riehm, Kira E., Yan, Xin Wei, Kloda, Lorie A., Henry, Melissa, Ismail, Zahinoor, Loiselle, Carmen G., Mitchell, Nicholas D., Al-Adawi, Samir, Alvarado, Rubén, Amtmann, Dagmar, Arroll, Bruce, Ayalon, Liat, Baradaran, Hamid R., Barnes, Jacqueline, Beck, Kevin R., Beck, Cheryl Tatano, Bernstein, Charles N., Bindt, Carola, Bombardier, Charles H., Boye, Birgitte, Büel-Drabe, Natalie, Buji, Ryna Imma, Bunevicius, Adomas, Butterworth, Peter, Can, Ceyhun, Carter, Gregory, Chagas, Marcos H., Chan, Juliana C.N., Chan, Lai Fong, Chen, Chih-Ken, Chibanda, Dixon, Chorwe-Sungani, Genesis, Clover, Kerrie, Conroy, Ronán M., Conway, Aaron, Conwell, Yeates, Correa, Humberto, Couto, Thiago Castro e, Cukor, Daniel, Daray, Federico M., de Man-van Ginkel, Janneke M., De Souza, Jennifer, Downing, Marina G., Eapen, Valsamma, Fann, Jesse R., Favez, Nicolas, Felice, Ethel, Fellmeth, Gracia, Ferentinos, Panagiotis P., Fernandes, Michelle, Field, Sally, Figueiredo, Barbara, Fischer, Felix H., Fisher, Jane R.W., Flint, Alastair J., Fujimori, Maiko, Fung, Daniel S.S., Gallagher, Pamela, Gandy, Milena, Gelaye, Bizu, Gholizadeh, Leila, Gibson, Lorna J., Goodyear-Smith, Felicity, Grassi, Luigi, Green, Eric P., Greeno, Catherine G., Hall, Brian J., Hantsoo, Liisa, Haroz, Emily E., Härter, Martin, Hegerl, Ulrich, Helle, Nadine, Hernando, Asuncion, Hides, Leanne, Hobfoll, Stevan E., Honikman, Simone, Howard, Louise M., Hyphantis, Thomas, Iglesias-González, Maria, Inagaki, Masatoshi, Jenewein, Josef, Jeon, Hong Jin, Jetté, Nathalie, Julião, Miguel, Kettunen, Pirjo A., Khamseh, Mohammad E., Kiely, Kim M., Kim, Sung-Wan, Kjærgaard, Marie, Kohlhoff, Jane, Kohrt, Brandon A., König, Hans-Helmut, Kozinszky, Zoltán, Kwan, Yunxin, Lamers, Femke, Lara, María Asunción, Leonardou, Angeliki A., Levin-Aspenson, Holly F., Liu, Shen-Ing, Löbner, Margrit, Loosman, Wim L., Lotrakul, Manote, Loureiro, Sonia R., Love, Anthony W., Löwe, Bernd, Luitel, Nagendra P., Lund, Crick, Maes, Michael, Malt, Ulrik F., Marrie, Ruth Ann, Marsh, Laura, Martínez, Pablo, Marx, Brian P., Matsuoka, Yutaka, McGuire, Anthony, Mehnert, Anja, Michopoulos, Ioannis, Sidik, Sherina Mohd, Müller-Nordhorn, Jacqueline, Muramatsu, Kumiko, Radoš, Sandra Nakić, Navarrete, Laura, Nelson, Christian J., Ng, Chong Guan, Nishi, Daisuke, O'Donnell, Meaghan L., O'Rourke, Suzanne J., Osório, Flávia L., Pabst, Alexander, Pasco, Julie A., Pawlby, Susan J., Peceliuniene, Jurate, Pence, Brian W., Persoons, Philippe, Petersen, Inge, Picardi, Angelo, Ponsford, Jennie L., Pugh, Stephanie L., Pulido, Federico, Quinn, Terence J., Quispel, Chantal, Rathod, Sujit D., Reme, Silje E., Reuter, Katrin, Riedel-Heller, Steffi G., Rooney, Alasdair G., Santos, Iná S., Saracino, Rebecca M., Schellekens, Melanie P.J., Schwarzbold, Marcelo L., Cankorur, Vesile Senturk, Shaaban, Juwita, Sharp, Deborah J., Sharpe, Louise, Shinn, Eileen H., Sidebottom, Abbey, Simard, Sébastien, Singer, Susanne, Skalkidou, Alkistis, Smith-Nielsen, Johanne, Spangenberg, Lena, Stafford, Lesley, Stein, Alan, Stewart, Robert C., Strobel, Natalie A., Su, Kuan-Pin, Sultan, Serge, Sundström-Poromaa, Inger, Sung, Sharon C., Suzuki, Keiko, Tadinac, Meri, Tan, Pei Lin Lynnette, Tandon, S. Darius, Taylor-Rowan, Martin, Teixeira, Antonio L., Tendais, Iva, Tiringer, Istvan, Töreki, Annamária, Tran, Thach D., Trevillion, Kylee, Tschorn, Mira, Turner, Alyna, Væver, Mette S., van der Feltz-Cornelis, Christina M., van Heyningen, Thandi, Vega-Dienstmaier, Johann M., Wagner, Michael, Wagner, Lynne I., Wang, Liang-Jen, Wang, Jian Li, Watson, David, Weyerer, Siegfried B., White, Jennifer, Whooley, Mary A., Wiese, Birgitt, Williams, Lana J., Winkley, Kirsty, Wynter, Karen, Yamada, Mitsuhiko, Yonkers, Kimberly A., Zeng, Qing Zhi, Zhang, Yuying, Harel, Daphna, Wu, Yin, Levis, Brooke, Fan, Suiqiong, Sun, Ying, Xu, Mingyao, Rice, Danielle B., Boruff, Jill, Markham, Sarah, Ioannidis, John P.A., Takwoingi, Yemisi, Patten, Scott B., Ziegelstein, Roy C., Cuijpers, Pim, Gilbody, Simon, Vigod, Simone, Akena, Dickens, Benedetti, Andrea, and Thombs, Brett D.

Published
2024
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2. Individual patient data meta-analysis estimates the minimal detectable change of the Geriatric Depression Scale-15

Author

Krishnan, Ankur, He, Chen, Santo, Tiffany Dal, Neupane, Dipika, Brehaut, Eliana, Bhandari, Parash M., Qiu, Xia, Li, Letong, Imran, Mahrukh, Nassar, Elsa-Lynn, Adams, Kathryn Betts, Allgaier, Antje-Kathrin, Baillon, Sarah F., Caramelli, Paulo, Castro-Costa, Erico, Chagas, Marcos H.N., Cullum, Sarah, Dias, Filipi L.C., Isik, Ahmet Turan, Jetté, Nathalie, Katz, Patricia, Kim, Wonhyoung, König, Hans-Helmut, Lima-Costa, Maria Fernanda, Löbner, Margrit, Malakouti, Seyed Kazem, Marsh, Laura, Moon, Heehyul E., Mougias, Antonis A., Nelson, Christian J., Pabst, Alexander, Quinn, Terence J., Riedel-Heller, Steffi G., Saracino, Rebecca, Scherer, Martin, Volz, Matthias, Wagner, Michael, Weyerer, Siegfried B., González-Domínguez, Nadia P., Wu, Yin, Fan, Suiqiong, Levis, Brooke, Sun, Ying, Gilbody, Simon, Ioannidis, John P.A., Harel, Daphna, Vigod, Simone N., Markham, Sarah, Ziegelstein, Roy C., Cuijpers, Pim, Patten, Scott B., Boruff, Jill T., Thombs, Brett D., and Benedetti, Andrea

Published
2024
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4. External validation of a shortened screening tool using individual participant data meta-analysis: A case study of the Patient Health Questionnaire-Dep-4

Author

He, Chen, Wu, Yin, Krishnan, Ankur, Mani Bhandari, Parash, Neupane, Dipika, Negeri, Zelalem, Imran, Mahrukh, Rice, Danielle B., Riehm, Kira E., Azar, Marleine, Levis, Alexander W., Boruff, Jill, Gilbody, Simon, Kloda, Lorie A., Amtmann, Dagmar, Ayalon, Liat, Baradaran, Hamid R., Beraldi, Anna, Bernstein, Charles N., Bhana, Arvin, Imma Buji, Ryna, Chagas, Marcos H., C. N. Chan, Juliana, Fong Chan, Lai, Chibanda, Dixon, Conway, Aaron, Daray, Federico M., de Man-van Ginkel, Janneke M., Diez-Quevedo, Crisanto, Field, Sally, R. W. Fisher, Jane, Fung, Daniel, Garman, Emily C., Flisher, Alan J, Gelaye, Bizu, Gholizadeh, Leila, Gibson, Lorna J., Green, Eric P., Hall, Brian J., Hantsoo, Liisa, Haroz, Emily E., Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E., Honikman, Simone, Hudson, Marie, Hyphantis, Thomas, Inagaki, Masatoshi, Jin Jeon, Hong, Jetté, Nathalie, Khamseh, Mohammad E., Köhler, Sebastian, Kohrt, Brandon A., Kwan, Yunxin, Lamers, Femke, Asunción Lara, Maria, Levin-Aspenson, Holly F., Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R., Löwe, Bernd, Luitel, Nagendra P., Lund, Crick, Ann Marrie, Ruth, Marx, Brian P., Mohd Sidik, Sherina, Munhoz, Tiago N., Muramatsu, Kumiko, E. M. Nakku, Juliet, Navarrete, Laura, Osório, Flávia L., Persoons, Philippe, Picardi, Angelo, Pugh, Stephanie L., Quinn, Terence J., Rancans, Elmars, Rathod, Sujit D., Reuter, Katrin, Rowe, Heather J., Santos, Iná S., Schram, Miranda T., Shaaban, Juwita, Shinn, Eileen H., Spangenberg, Lena, Stafford, Lesley, Sung, Sharon C., Suzuki, Keiko, Lin Lynnette Tan, Pei, Taylor-Rowan, Martin, Tran, Thach D., van der Feltz-Cornelis, Christina M., van Heyningen, Thandi, van Weert, Henk C., Wagner, Lynne I., Li Wang, Jian, Watson, David, Wynter, Karen, Yamada, Mitsuhiko, Zhi Zeng, Qing, Zhang, Yuying, Harel, Daphna, Levis, Brooke, Sun, Ying, Fischer, Felix, Ioannidis, John P.A., Cuijpers, Pim, Patten, Scott B., Ziegelstein, Roy C., Markham, Sarah, Benedetti, Andrea, and Thombs, Brett D.

Published
2022
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5. Systematic review of mental health symptom changes by sex or gender in early-COVID-19 compared to pre-pandemic

Author

Dal Santo, Tiffany, Sun, Ying, Wu, Yin, He, Chen, Wang, Yutong, Jiang, Xiaowen, Li, Kexin, Bonardi, Olivia, Krishnan, Ankur, Boruff, Jill T., Rice, Danielle B., Markham, Sarah, Levis, Brooke, Azar, Marleine, Neupane, Dipika, Tasleem, Amina, Yao, Anneke, Thombs-Vite, Ian, Agic, Branka, Fahim, Christine, Martin, Michael S., Sockalingam, Sanjeev, Turecki, Gustavo, Benedetti, Andrea, and Thombs, Brett D.

Published
2022
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6. Data-driven methods distort optimal cutoffs and accuracy estimates of depression screening tools: a simulation study using individual participant data

Author

Sun, Ying, He, Chen, Rice, Danielle B., Krishnan, Ankur, Wu, Yin, Azar, Marleine, Sanchez, Tatiana A., Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., Imran, Mahrukh, Negeri, Zelalem, Boruff, Jill T., Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P.A., Kloda, Lorie A., 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, Bavle, Amar D., 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, Favez, Nicolas, Felice, Ethel, Fernandes, Michelle, Figueiredo, Barbara, Fisher, Jane R.W., Garcia-Esteve, Lluïsa, Giardinelli, Lisa, Helle, Nadine, Howard, Louise M., Khalifa, Dina Sami, Kohlhoff, Jane, Kozinszky, Zoltán, Kusminskas, Laima, Lelli, Lorenzo, Leonardou, Angeliki A., Maes, Michael, Meuti, Valentina, Radoš, Sandra Nakić, García, Purificación Navarro, Nishi, Daisuke, Luwa E-Andjafono, Daniel Okitundu, Pawlby, Susan J., Quispel, Chantal, Robertson-Blackmore, Emma, Rochat, Tamsen J., Rowe, Heather J., Sharp, Deborah J., Siu, Bonnie W.M., Skalkidou, Alkistis, Stein, Alan, Stewart, Robert C., Su, Kuan-Pin, Sundström-Poromaa, Inger, Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Thiagayson, Pavaani, Töreki, Annamária, Torres-Giménez, Anna, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega-Dienstmaier, Johann M., Wynter, Karen, Yonkers, Kimberly A., Bhandari, Parash Mani, Levis, Brooke, Neupane, Dipika, Patten, Scott B., Shrier, Ian, Thombs, Brett D., and Benedetti, Andrea

Published
2021
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7. Validation of the COVID-19 Fears Questionnaires for Chronic Medical Conditions: A Scleroderma Patient-centered Intervention Network COVID-19 Cohort study

Author

Culos-Reed, Nicole, El-Baalbaki, Ghassan, Hebblethwaite, Shannon, Patten, Scott, Varga, John, Bustamante, Laura, Duchek, Delaney, Ellis, Kelsey, Rice, Danielle, Dyas, Laura, Fortuné, Catherine, Gietzen, Amy, Guillot, Geneviève, Lewis, Nancy, Nielsen, Karen, Richard, Michelle, Sauvé, Maureen, Welling, Joep, Wu, Yin, Kwakkenbos, Linda, Henry, Richard S., Tao, Lydia, Harb, Sami, Bourgeault, Angelica, Carrier, Marie-Eve, Levis, Brooke, Sun, Ying, Bhandari, Parash Mani, Carboni-Jiménez, Andrea, Gagarine, Maria, He, Chen, Krishnan, Ankur, Negeri, Zelalem F., Neupane, Dipika, Mouthon, Luc, Bartlett, Susan J., Benedetti, Andrea, and Thombs, Brett D.

Published
2020
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8. Depression prevalence using the HADS-D compared to SCID major depression classification: An individual participant data meta-analysis

Author

Brehaut, Eliana, Neupane, Dipika, Levis, Brooke, Wu, Yin, Sun, Ying, Krishnan, Ankur, He, Chen, Bhandari, Parash Mani, Negeri, Zelalem, Riehm, Kira E., Rice, Danielle B., Azar, Marleine, Yan, Xin Wei, Imran, Mahrukh, Chiovitti, Matthew J., Saadat, Nazanin, Cuijpers, Pim, Ioannidis, John P.A., Markham, Sarah, Patten, Scott B., Ziegelstein, Roy C., Henry, Melissa, Ismail, Zahinoor, Loiselle, Carmen G., Mitchell, Nicholas D., Tonelli, Marcello, Boruff, Jill T., Kloda, Lorie A., Beraldi, Anna, Braeken, Anna P.B.M., Carter, Gregory, Clover, Kerrie, Conroy, Ronán M., Cukor, Daniel, da Rocha e Silva, Carlos E., De Souza, Jennifer, Downing, Marina G., Feinstein, Anthony, Ferentinos, Panagiotis P., Fischer, Felix H., Flint, Alastair J., Fujimori, Maiko, Gallagher, Pamela, Goebel, Simone, Jetté, Nathalie, Julião, Miguel, Keller, Monika, Kjærgaard, Marie, Love, Anthony W., Löwe, Bernd, Martin-Santos, Rocio, Michopoulos, Ioannis, Navines, Ricard, O’Rourke, Suzanne J., Öztürk, Ahmet, Pintor, Luis, Ponsford, Jennie L., Rooney, Alasdair G., Sánchez-González, Roberto, Schwarzbold, Marcelo L., Sharpe, Michael, Simard, Sébastien, Singer, Susanne, Stone, Jon, Tung, Ka-Yee, Turner, Alyna, Walker, Jane, Walterfang, Mark, White, Jennifer, Benedetti, Andrea, and Thombs, Brett D.

Published
2020
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9. Protocol for a partially nested randomised controlled trial to evaluate the effectiveness of the scleroderma patient-centered intervention network COVID-19 home-isolation activities together (SPIN-CHAT) program to reduce anxiety among at-risk scleroderma patients

Author

Fortuné, Catherine, Gietzen, Amy, Guillot, Geneviève, Lewis, Nancy, Nielsen, Karen, Richard, Michelle, Sauvé, Maureen, Welling, Joep, Baron, Murray, Furst, Daniel E., Gottesman, Karen, Malcarne, Vanessa, Mayes, Maureen D., Mouthon, Luc, Nielson, Warren R., Riggs, Robert, Wigley, Fredrick, Assassi, Shervin, Boutron, Isabelle, Ells, Carolyn, van den Ende, Cornelia, Fligelstone, Kim, Frech, Tracy, Godard, Dominique, Harel, Daphna, Hinchcliff, Monique, Hudson, Marie, Johnson, Sindhu R., Larche, Maggie, Leite, Catarina, Nguyen, Christelle, Pope, Janet, Portales, Alexandra, Rannou, François, Reyna, Tatiana Sofia Rodriguez, Schouffoer, Anne A., Suarez-Almazor, Maria E., Agard, Christian, Albert, Alexandra, André, Marc, Arsenault, Guylaine, Benzidia, Ilham, Bernstein, Elana J., Berthier, Sabine, Bissonnette, Lyne, Boire, Gilles, Bruns, Alessandra, Carreira, Patricia, Casadevall, Marion, Chaigne, Benjamin, Chung, Lorinda, Cohen, Pascal, Correia, Chase, Dagenais, Pierre, Denton, Christopher, Domsic, Robyn, Dubois, Sandrine, Dunne, James V., Dunogue, Bertrand, Fare, Regina, Farge-Bancel, Dominique, Fortin, Paul R., Gill, Anna, Gordon, Jessica, Granel-Rey, Brigitte, Gyger, Genevieve, Hachulla, Eric, Hatron, Pierre-Yves, Herrick, Ariane L., Hij, Adrian, Hoa, Sabrina, Ikic, Alena, Jones, Niall, de B. Fernandes, Artur Jose, Kafaja, Suzanne, Khalidi, Nader, Lambert, Marc, Launay, David, Liang, Patrick, Maillard, Hélène, Maltez, Nancy, Manning, Joanne, Marie, Isabelle, Martin, Maria, Martin, Thierry, Masetto, Ariel, Maurier, François, Mekinian, Arsene, Melchor, Sheila, Nikpour, Mandana, Olagne, Louis, Poindron, Vincent, Proudman, Susanna, Régent, Alexis, Rivière, Sébastien, Robinson, David, Rodriguez, Esther, Roux, Sophie, Smets, Perrine, Smith, Doug, Sobanski, Vincent, Spiera, Robert, Steen, Virginia, Stevens, Wendy, Sutton, Evelyn, Terrier, Benjamin, Thorne, Carter, Varga, John, Wilcox, Pearce, Ayala, Mara Cañedo, Ostbo, Nora, Thombs, Brett D., Kwakkenbos, Linda, Carrier, Marie-Eve, Bourgeault, Angelica, Tao, Lydia, Harb, Sami, Gagarine, Maria, Rice, Danielle, Bustamante, Laura, Ellis, Kelsey, Duchek, Delaney, Wu, Yin, Bhandari, Parash Mani, Neupane, Dipika, Carboni-Jiménez, Andrea, Henry, Richard S., Krishnan, Ankur, Sun, Ying, Levis, Brooke, He, Chen, Turner, Kimberly A., Benedetti, Andrea, Culos-Reed, Nicole, El-Baalbaki, Ghassan, Hebblethwaite, Shannon, Bartlett, Susan J., Dyas, Laura, and Patten, Scott

Published
2020
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10. Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis

Author

Levis, Brooke, Benedetti, Andrea, Ioannidis, John P.A., Sun, Ying, Negeri, Zelalem, He, Chen, Wu, Yin, Krishnan, Ankur, Bhandari, Parash Mani, Neupane, Dipika, Imran, Mahrukh, Rice, Danielle B., Riehm, Kira E., Saadat, Nazanin, Azar, Marleine, Boruff, Jill, Cuijpers, Pim, Gilbody, Simon, Kloda, Lorie A., McMillan, Dean, Patten, Scott B., Shrier, Ian, Ziegelstein, Roy C., Alamri, Sultan H., Amtmann, Dagmar, Ayalon, Liat, Baradaran, Hamid R., Beraldi, Anna, Bernstein, Charles N., Bhana, Arvin, Bombardier, Charles H., Carter, Gregory, Chagas, Marcos H., Chibanda, Dixon, Clover, Kerrie, Conwell, Yeates, Diez-Quevedo, Crisanto, Fann, Jesse R., Fischer, Felix H., Gholizadeh, Leila, Gibson, Lorna J., Green, Eric P., Greeno, Catherine G., Hall, Brian J., Haroz, Emily E., Ismail, Khalida, Jetté, Nathalie, Khamseh, Mohammad E., Kwan, Yunxin, Lara, Maria Asunción, Liu, Shen-Ing, Loureiro, Sonia R., Löwe, Bernd, Marrie, Ruth Ann, Marsh, Laura, McGuire, Anthony, Muramatsu, Kumiko, Navarrete, Laura, Osório, Flávia L., Petersen, Inge, Picardi, Angelo, Pugh, Stephanie L., Quinn, Terence J., Rooney, Alasdair G., Shinn, Eileen H., Sidebottom, Abbey, Spangenberg, Lena, Tan, Pei Lin Lynnette, Taylor-Rowan, Martin, Turner, Alyna, van Weert, Henk C., Vöhringer, Paul A., Wagner, Lynne I., White, Jennifer, Winkley, Kirsty, and Thombs, Brett D.

Published
2020
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11. Trivalent and quadrivalent seasonal influenza vaccine in adults aged 60 and older: a systematic review and network meta-analysis

Author

Veroniki, Areti Angeliki, primary, Thirugnanasampanthar, Sai Surabi, additional, Konstantinidis, Menelaos, additional, Dourka, Jasmeen, additional, Ghassemi, Marco, additional, Neupane, Dipika, additional, Khan, Paul, additional, Nincic, Vera, additional, Corry, Margarita, additional, Robson, Reid, additional, Parker, Amanda, additional, Soobiah, Charlene, additional, Sinilaite, Angela, additional, Doyon-Plourde, Pamela, additional, Gil, Anabel, additional, Siu, Winnie, additional, Moqueet, Nasheed, additional, Stevens, Adrienne, additional, English, Kelly, additional, Florez, Ivan D, additional, Yepes-Nuñez, Juan J, additional, Hutton, Brian, additional, Muller, Matthew, additional, Moja, Lorenzo, additional, Straus, Sharon, additional, and Tricco, Andrea C, additional

Published
2024
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12. Probability of major depression diagnostic classification based on the SCID, CIDI and MINI diagnostic interviews controlling for Hospital Anxiety and Depression Scale – Depression subscale scores: An individual participant data meta-analysis of 73 primary studies

Author

Wu, Yin, Levis, Brooke, Sun, Ying, Krishnan, Ankur, He, Chen, Riehm, Kira E., Rice, Danielle B., Azar, Marleine, Yan, Xin Wei, Neupane, Dipika, Bhandari, Parash Mani, Imran, Mahrukh, Chiovitti, Matthew J., Saadat, Nazanin, Boruff, Jill T., Cuijpers, Pim, Gilbody, Simon, McMillan, Dean, Ioannidis, John P.A., Kloda, Lorie A., Patten, Scott B., Shrier, Ian, Ziegelstein, Roy C., Henry, Melissa, Ismail, Zahinoor, Loiselle, Carmen G., Mitchell, Nicholas D., Tonelli, Marcello, Al-Adawi, Samir, Beraldi, Anna, Braeken, Anna P.B.M., Büel-Drabe, Natalie, Bunevicius, Adomas, Carter, Gregory, Chen, Chih-Ken, Cheung, Gary, Clover, Kerrie, Conroy, Ronán M., Cukor, Daniel, da Rocha e Silva, Carlos E., Dabscheck, Eli, Daray, Federico M., Douven, Elles, Downing, Marina G., Feinstein, Anthony, Ferentinos, Panagiotis P., Fischer, Felix H., Flint, Alastair J., Fujimori, Maiko, Gallagher, Pamela, Gandy, Milena, Goebel, Simone, Grassi, Luigi, Härter, Martin, Jenewein, Josef, Jetté, Nathalie, Julião, Miguel, Kim, Jae-Min, Kim, Sung-Wan, Kjærgaard, Marie, Köhler, Sebastian, Loosman, Wim L., Löwe, Bernd, Martin-Santos, Rocio, Massardo, Loreto, Matsuoka, Yutaka, Mehnert, Anja, Michopoulos, Ioannis, Misery, Laurent, Navines, Ricard, O'Donnell, Meaghan L., Öztürk, Ahmet, Peceliuniene, Jurate, Pintor, Luis, Ponsford, Jennie L., Quinn, Terence J., Reme, Silje E., Reuter, Katrin, Rooney, Alasdair G., Sánchez-González, Roberto, Schwarzbold, Marcelo L., Senturk Cankorur, Vesile, Shaaban, Juwita, Sharpe, Louise, Sharpe, Michael, Simard, Sébastien, Singer, Susanne, Stafford, Lesley, Stone, Jon, Sultan, Serge, Teixeira, Antonio L., Tiringer, Istvan, Turner, Alyna, Walker, Jane, Walterfang, Mark, Wang, Liang-Jen, White, Jennifer, Wong, Dana K., Benedetti, Andrea, and Thombs, Brett D.

Published
2020
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14. Individual participant data meta-analysis to compare EPDS accuracy to detect major depression with and without the self-harm item

Author

Qiu, Xia, Wu, Yin, Sun, Ying, Levis, Brooke, Tian, Jizhou, Boruff, Jill T., Cuijpers, Pim, Ioannidis, John P. A., Markham, Sarah, Ziegelstein, Roy C., Vigod, Simone N., Benedetti, Andrea, Thombs, Brett, He, Chen, Krishnan, Ankur, Bhandari, Parash Mani, Neupane, Dipika, Negeri, Zelalem, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Gilbody, Simon A., Kloda, Lorie B., Patten, Scott D., Mitchell, Nicholas, Alvarado, Ruben, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, Correa, Humberto, Castro e Couto, Tiago, Chorwe-Sungani, Genesis, Eapen, Valsamma, Favez, Nicolas, Felice, Ethel, Fellmeth, Gracia, Fernandes, Michelle, Field, Sally, Figueiredo, Barbara, Fisher, Jane R. W., Green, Eric P., Honikman, Simone, Howard, Louise M., Kettunen, Pirjo A., Kohlhoff, Jane, Kozinszky, Zoltan, Leonardou, Angeliki A., Maes, Michael, Martinez, Pablo, Rados, Sandra Nakic, Nishi, Daisuke, Pawlby, Susan J., Rochat, Tamsen J., Rowe, Heather J., Sharp, Deborah J., Skalkidou, Alkistis, Smith-Nielsen, Johanne, Stein, Alan, Su, Kuan-Pin, Sundström Poromaa, Inger, Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Toereki, Annamaria D., Tran, Thach, Trevillion, Kylee, Turner, Katherine S., Vaever, Mette, van Heyningen, Thandi M., Vega-Dienstmaier, Johann, Wynter, Karen A., Yonkers, Kimberly, Qiu, Xia, Wu, Yin, Sun, Ying, Levis, Brooke, Tian, Jizhou, Boruff, Jill T., Cuijpers, Pim, Ioannidis, John P. A., Markham, Sarah, Ziegelstein, Roy C., Vigod, Simone N., Benedetti, Andrea, Thombs, Brett, He, Chen, Krishnan, Ankur, Bhandari, Parash Mani, Neupane, Dipika, Negeri, Zelalem, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Gilbody, Simon A., Kloda, Lorie B., Patten, Scott D., Mitchell, Nicholas, Alvarado, Ruben, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, Correa, Humberto, Castro e Couto, Tiago, Chorwe-Sungani, Genesis, Eapen, Valsamma, Favez, Nicolas, Felice, Ethel, Fellmeth, Gracia, Fernandes, Michelle, Field, Sally, Figueiredo, Barbara, Fisher, Jane R. W., Green, Eric P., Honikman, Simone, Howard, Louise M., Kettunen, Pirjo A., Kohlhoff, Jane, Kozinszky, Zoltan, Leonardou, Angeliki A., Maes, Michael, Martinez, Pablo, Rados, Sandra Nakic, Nishi, Daisuke, Pawlby, Susan J., Rochat, Tamsen J., Rowe, Heather J., Sharp, Deborah J., Skalkidou, Alkistis, Smith-Nielsen, Johanne, Stein, Alan, Su, Kuan-Pin, Sundström Poromaa, Inger, Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Toereki, Annamaria D., Tran, Thach, Trevillion, Kylee, Turner, Katherine S., Vaever, Mette, van Heyningen, Thandi M., Vega-Dienstmaier, Johann, Wynter, Karen A., and Yonkers, Kimberly

Abstract

Item 10 of the Edinburgh Postnatal Depression Scale (EPDS) is intended to assess thoughts of intentional self-harm but may also elicit concerns about accidental self-harm. It does not specifically address suicide ideation but, nonetheless, is sometimes used as an indicator of suicidality. The 9-item version of the EPDS (EPDS-9), which omits item 10, is sometimes used in research due to concern about positive endorsements of item 10 and necessary follow-up. We assessed the equivalence of total score correlations and screening accuracy to detect major depression using the EPDS-9 versus full EPDS among pregnant and postpartum women. We searched Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science from database inception to October 3, 2018 for studies that administered the EPDS and conducted diagnostic classification for major depression based on a validated semi-structured or fully structured interview among women aged 18 or older during pregnancy or within 12 months of giving birth. We conducted an individual participant data meta-analysis. We calculated Pearson correlations with 95% prediction interval (PI) between EPDS-9 and full EPDS total scores using a random effects model. Bivariate random-effects models were fitted to assess screening accuracy. Equivalence tests were done by comparing the confidence intervals (CIs) around the pooled sensitivity and specificity differences to the equivalence margin of delta = 0.05. Individual participant data were obtained from 41 eligible studies (10,906 participants, 1407 major depression cases). The correlation between EPDS-9 and full EPDS scores was 0.998 (95% PI 0.991, 0.999). For sensitivity, the EPDS-9 and full EPDS were equivalent for cut-offs 7-12 (difference range - 0.02, 0.01) and the equivalence was indeterminate for cut-offs 13-15 (all differences - 0.04). For specificity, the EPDS-9 and full EPDS were equivalent for all cut-offs (difference range 0.00, 0.01). The EPDS-9 performs

Published
2023
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15. An empirical comparison of statistical methods for multiple cut-off diagnostic test accuracy meta-analysis of the Edinburgh postnatal depression scale (EPDS) depression screening tool using published results vs individual participant data.

Author

Negeri, Zelalem F., Levis, Brooke, Ioannidis, John P. A., Thombs, Brett D., Benedetti, Andrea, the DEPRESsion Screening Data (DEPRESSD) EPDS Group, Sun, Ying, He, Chen, Krishnan, Ankur, Wu, Yin, Bhandari, Parash Mani, Neupane, Dipika, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Riehm, Kira E., Boruff, Jill T., Cuijpers, Pim, and Gilbody, Simon

Abstract

Background: Selective reporting of results from only well-performing cut-offs leads to biased estimates of accuracy in primary studies of questionnaire-based screening tools and in meta-analyses that synthesize results. Individual participant data meta-analysis (IPDMA) of sensitivity and specificity at each cut-off via bivariate random-effects models (BREMs) can overcome this problem. However, IPDMA is laborious and depends on the ability to successfully obtain primary datasets, and BREMs ignore the correlation between cut-offs within primary studies. Methods: We compared the performance of three recent multiple cut-off models developed by Steinhauser et al., Jones et al., and Hoyer and Kuss, that account for missing cut-offs when meta-analyzing diagnostic accuracy studies with multiple cut-offs, to BREMs fitted at each cut-off. We used data from 22 studies of the accuracy of the Edinburgh Postnatal Depression Scale (EPDS; 4475 participants, 758 major depression cases). We fitted each of the three multiple cut-off models and BREMs to a dataset with results from only published cut-offs from each study (published data) and an IPD dataset with results for all cut-offs (full IPD data). We estimated pooled sensitivity and specificity with 95% confidence intervals (CIs) for each cut-off and the area under the curve. Results: Compared to the BREMs fitted to the full IPD data, the Steinhauser et al., Jones et al., and Hoyer and Kuss models fitted to the published data produced similar receiver operating characteristic curves; though, the Hoyer and Kuss model had lower area under the curve, mainly due to estimating slightly lower sensitivity at lower cut-offs. When fitting the three multiple cut-off models to the full IPD data, a similar pattern of results was observed. Importantly, all models had similar 95% CIs for sensitivity and specificity, and the CI width increased with cut-off levels for sensitivity and decreased with an increasing cut-off for specificity, even the BREMs which treat each cut-off separately. Conclusions: Multiple cut-off models appear to be the favorable methods when only published data are available. While collecting IPD is expensive and time consuming, IPD can facilitate subgroup analyses that cannot be conducted with published data only. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Comparison of mental health symptoms before and during the covid-19 pandemic: evidence from a systematic review and meta-analysis of 134 cohorts

Author

Sun, Ying, primary, Wu, Yin, additional, Fan, Suiqiong, additional, Dal Santo, Tiffany, additional, Li, Letong, additional, Jiang, Xiaowen, additional, Li, Kexin, additional, Wang, Yutong, additional, Tasleem, Amina, additional, Krishnan, Ankur, additional, He, Chen, additional, Bonardi, Olivia, additional, Boruff, Jill T, additional, Rice, Danielle B, additional, Markham, Sarah, additional, Levis, Brooke, additional, Azar, Marleine, additional, Thombs-Vite, Ian, additional, Neupane, Dipika, additional, Agic, Branka, additional, Fahim, Christine, additional, Martin, Michael S, additional, Sockalingam, Sanjeev, additional, Turecki, Gustavo, additional, Benedetti, Andrea, additional, and Thombs, Brett D, additional

Published
2023
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17. ‘Optimal’ cutoff selection in studies of depression screening tool accuracy using the PHQ‐9, EPDS, or HADS‐D: A meta‐research study

Author

Brehaut, Eliana, primary, Neupane, Dipika, additional, Levis, Brooke, additional, Wu, Yin, additional, Sun, Ying, additional, Ioannidis, John P. A., additional, Markham, Sarah, additional, Cuijpers, Pim, additional, Patten, Scott B., additional, Benedetti, Andrea, additional, and Thombs, Brett D., additional

Published
2022
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18. 'Optimal' cutoff selection in studies of depression screening tool accuracy using the PHQ‐9, EPDS, or HADS‐D: A meta‐research study.

Author

Brehaut, Eliana, Neupane, Dipika, Levis, Brooke, Wu, Yin, Sun, Ying, Ioannidis, John P. A., Markham, Sarah, Cuijpers, Pim, Patten, Scott B., Benedetti, Andrea, and Thombs, Brett D.

Subjects
*MEDICAL screening, *EDINBURGH Postnatal Depression Scale, *MENTAL depression
Abstract

Objectives: Optimal cutoff thresholds are selected to separate 'positive' from 'negative' screening results. We evaluated how depression screening tool studies select optimal cutoffs. Methods: We included studies from previously conducted meta‐analyses of Patient Health Questionnaire‐9, Edinburgh Postnatal Depression Scale, or Hospital Anxiety and Depression Scale—Depression accuracy. Outcomes included whether an optimal cutoff was selected, method used, recommendations made, and reporting guideline and protocol citation. Results: Of 212 included studies, 172 (81%) attempted to identify an optimal cutoff, and 147 of these 172 (85%) reported one or more methods. Methods were heterogeneous with Youden's J (N = 35, 23%) most common. Only 23 of 147 (16%) studies described a rationale for their method. Rationales focused on balancing sensitivity and specificity without describing why desirable. 131 of 172 studies (76%) identified an optimal cutoff other than the standard; most did not make use recommendations (N = 56; 43%) or recommended using a non‐standard cutoff (N = 53; 40%). Only 4 studies cited a reporting guideline, and 4 described a protocol with optimal cutoff selection methods, but none used the protocol method in the published study. Conclusions: Research is needed to guide how selection of cutoffs for depression screening tools can be standardized and reflect clinical considerations. [ABSTRACT FROM AUTHOR]

Published
2023
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19. Trivalent and quadrivalent seasonal influenza vaccine in adults aged 60 and older: a systematic review and network meta-analysis

Author

Veroniki, Areti Angeliki, Thirugnanasampanthar, Sai Surabi, Konstantinidis, Menelaos, Dourka, Jasmeen, Ghassemi, Marco, Neupane, Dipika, Khan, Paul, Nincic, Vera, Corry, Margarita, Robson, Reid, Parker, Amanda, Soobiah, Charlene, Sinilaite, Angela, Doyon-Plourde, Pamela, Gil, Anabel, Siu, Winnie, Moqueet, Nasheed, Stevens, Adrienne, English, Kelly, Florez, Ivan D, Yepes-Nuñez, Juan J, Hutton, Brian, Muller, Matthew, Moja, Lorenzo, Straus, Sharon, and Tricco, Andrea C

Abstract

ObjectivesTo compare the efficacy of influenza vaccines of any valency for adults 60 years and older.Design and settingSystematic review with network meta-analysis (NMA) of randomised controlled trials (RCTs). MEDLINE, EMBASE, JBI Evidence-Based Practice (EBP) Database, PsycINFO, and Cochrane Evidence -Based Medicine database were searched from inception to 20 June 20, 2022. Two reviewers screened, abstracted, and appraised articles (Cochrane Risk of Bias (ROB) 2.0 tool) independently. We assessed certainty of findings using Confidence in Network Meta-Analysis and Grading of Recommendations, Assessment, Development and Evaluations approaches. We performed random-effects meta-analysis and network meta-analysis (NMA), and estimated odds ratios (ORs) for dichotomous outcomes and incidence rate ratios (IRRs) for count outcomes along with their corresponding 95% confidence intervals (CIs) and prediction intervals.ParticipantsOlder adults (≥60 years old) receiving an influenza vaccine licensed in Canada or the USA (vs placebo, no vaccine, or any other licensed vaccine), at any dose.Main outcome measuresLaboratory-confirmed influenza (LCI) and influenza-like illness (ILI). Secondary outcomes were the number of vascular adverse events, hospitalisation for acute respiratory infection (ARI) and ILI, inpatient hospitalisation, emergency room (ER) visit for ILI, outpatient visit, and mortality, among others.ResultsWe included 41 RCTs and 15 companion reports comprising 8 vaccine types and 206 032 participants. Vaccines may prevent LCI compared with placebo, with high-dose trivalent inactivated influenza vaccine (IIV3-HD) (NMA: 9 RCTs, 52 202 participants, OR 0.23, 95% confidence interval (CI) (0.11 to 0.51), low certainty of evidence) and recombinant influenza vaccine (RIV) (OR 0.25, 95%CI (0.08 to 0.73), low certainty of evidence) among the most efficacious vaccines. Standard dose trivalent IIV3 (IIV3-SD) may prevent ILI compared with placebo, but the result was imprecise (meta-analysis: 2 RCTs, 854 participants, OR 0.39, 95%CI (0.15 to 1.02), low certainty of evidence). Any HD was associated with prevention of ILI compared with placebo (NMA: 9 RCTs, 65 658 participants, OR 0.38, 95%CI (0.15 to 0.93)). Adjuvanted quadrivalent IIV (IIV4-Adj) may be associated with the least vascular adverse events, but the results were very uncertain (NMA: eight 8 RCTs, 57 677 participants, IRR 0.18, 95%CI (0.07 to 0.43), very low certainty of evidence). RIV on all-cause mortality may be comparable to placebo (NMA: 20 RCTs, 140 577 participants, OR 1.01, 95%CI (0.23 to 4.49), low certainty of evidence).ConclusionsThis systematic review demonstrated efficacy associated with IIV3-HD and RIV vaccines in protecting older persons against LCI. RIV vaccine may reduce all-cause mortality when compared with other vaccines, but the evidence is uncertain. Differences in efficacy between influenza vaccines remain uncertain with very low to moderate certainty of evidence.PROSPERO registration numberCRD42020177357.

Published
2024
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20. A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well.

Author

López Malo Vázquez de Lara, Aurelio, Bhandari, Parash Mani, Wu, Yin, Levis, Brooke, Thombs, Brett, Benedetti, Andrea, Sun, Ying, He, Chen, Krishnan, Ankur, Neupane, Dipika, Negeri, Zelalem, Imran, Mahrukh, Rice, Danielle B., Riehm, Kira E., Saadat, Nazanin, Azar, Marleine, Boruff, Jill, Cuijpers, Pim, Gilbody, Simon, and Ioannidis, John P. A.

Subjects
RANDOM effects model, HETEROGENEITY, MEDICAL screening, MENTAL depression, FORECASTING, SENSITIVITY & specificity (Statistics)
Abstract

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings. [ABSTRACT FROM AUTHOR]

Published
2023
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21. A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well.

Author

de Lara, Aurelio López Malo Vázquez, Bhandari, Parash Mani, Wu, Yin, Levis, Brooke, Thombs, Brett, Benedetti, Andrea, DEPRESsion Screening Data (DEPRESSD) PHQ-9 Collaboration, Sun, Ying, He, Chen, Krishnan, Ankur, Neupane, Dipika, Negeri, Zelalem, Imran, Mahrukh, Rice, Danielle B., Riehm, Kira E., Saadat, Nazanin, Azar, Marleine, Boruff, Jill, Cuijpers, Pim, and Gilbody, Simon

Subjects
HETEROGENEITY, MEDICAL screening, MENTAL depression, FORECASTING, SENSITIVITY & specificity (Statistics), RANDOM effects model, BIVARIATE analysis
Abstract

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings. [ABSTRACT FROM AUTHOR]

Published
2023
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22. External validation of a shortened screening tool using individual participant data meta-analysis: A case study of the Patient Health Questionnaire-Dep-4

Author

Harel, Daphna, primary, Levis, Brooke, additional, Sun, Ying, additional, Fischer, Felix, additional, Ioannidis, John P.A., additional, Cuijpers, Pim, additional, Patten, Scott B., additional, Ziegelstein, Roy C., additional, Markham, Sarah, additional, Benedetti, Andrea, additional, Thombs, Brett D., additional, He, Chen, additional, Wu, Yin, additional, Krishnan, Ankur, additional, Mani Bhandari, Parash, additional, Neupane, Dipika, additional, Negeri, Zelalem, additional, Imran, Mahrukh, additional, Rice, Danielle B., additional, Riehm, Kira E., additional, Azar, Marleine, additional, Levis, Alexander W., additional, Boruff, Jill, additional, Gilbody, Simon, additional, Kloda, Lorie A., additional, Amtmann, Dagmar, additional, Ayalon, Liat, additional, Baradaran, Hamid R., additional, Beraldi, Anna, additional, Bernstein, Charles N., additional, Bhana, Arvin, additional, Imma Buji, Ryna, additional, Chagas, Marcos H., additional, C. N. Chan, Juliana, additional, Fong Chan, Lai, additional, Chibanda, Dixon, additional, Conway, Aaron, additional, Daray, Federico M., additional, de Man-van Ginkel, Janneke M., additional, Diez-Quevedo, Crisanto, additional, Field, Sally, additional, R. W. Fisher, Jane, additional, Fung, Daniel, additional, Garman, Emily C., additional, Flisher, Alan J, additional, Gelaye, Bizu, additional, Gholizadeh, Leila, additional, Gibson, Lorna J., additional, Green, Eric P., additional, Hall, Brian J., additional, Hantsoo, Liisa, additional, Haroz, Emily E., additional, Härter, Martin, additional, Hegerl, Ulrich, additional, Hides, Leanne, additional, Hobfoll, Stevan E., additional, Honikman, Simone, additional, Hudson, Marie, additional, Hyphantis, Thomas, additional, Inagaki, Masatoshi, additional, Jin Jeon, Hong, additional, Jetté, Nathalie, additional, Khamseh, Mohammad E., additional, Köhler, Sebastian, additional, Kohrt, Brandon A., additional, Kwan, Yunxin, additional, Lamers, Femke, additional, Asunción Lara, Maria, additional, Levin-Aspenson, Holly F., additional, Liu, Shen-Ing, additional, Lotrakul, Manote, additional, Loureiro, Sonia R., additional, Löwe, Bernd, additional, Luitel, Nagendra P., additional, Lund, Crick, additional, Ann Marrie, Ruth, additional, Marx, Brian P., additional, Mohd Sidik, Sherina, additional, Munhoz, Tiago N., additional, Muramatsu, Kumiko, additional, E. M. Nakku, Juliet, additional, Navarrete, Laura, additional, Osório, Flávia L., additional, Persoons, Philippe, additional, Picardi, Angelo, additional, Pugh, Stephanie L., additional, Quinn, Terence J., additional, Rancans, Elmars, additional, Rathod, Sujit D., additional, Reuter, Katrin, additional, Rowe, Heather J., additional, Santos, Iná S., additional, Schram, Miranda T., additional, Shaaban, Juwita, additional, Shinn, Eileen H., additional, Spangenberg, Lena, additional, Stafford, Lesley, additional, Sung, Sharon C., additional, Suzuki, Keiko, additional, Lin Lynnette Tan, Pei, additional, Taylor-Rowan, Martin, additional, Tran, Thach D., additional, van der Feltz-Cornelis, Christina M., additional, van Heyningen, Thandi, additional, van Weert, Henk C., additional, Wagner, Lynne I., additional, Li Wang, Jian, additional, Watson, David, additional, Wynter, Karen, additional, Yamada, Mitsuhiko, additional, Zhi Zeng, Qing, additional, and Zhang, Yuying, additional

Published
2022
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23. Overestimation of Postpartum Depression Prevalence Based on a 5-item Version of the EPDS:Systematic Review and Individual Participant Data Meta-analysis

Author

Thombs, Brett D., Levis, Brooke, Lyubenova, Anita, Neupane, Dipika, Negeri, Zelalem, Wu, Yin, Sun, Ying, He, Chen, Krishnan, Ankur, Vigod, Simone N., Bhandari, Parash Mani, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., 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, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, Figueiredo, Barbara, Helle, Nadine, Howard, Louise M., Kohlhoff, Jane, Kozinszky, Zoltán, Leonardou, Angeliki A., Radoš, Sandra Nakić, Quispel, Chantal, Rochat, Tamsen J., Stein, Alan, Stewart, Robert C., Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Töreki, Annamária, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega-Dienstmaier, Johann M., and Benedetti, Andrea

Subjects
obstetrics and gynecology, SDG 3 - Good Health and Well-being, statistics and research methods, epidemiology, evidence-based medicine, psychiatry
Abstract

Objective: The Maternal Mental Health in Canada, 2018/2019, survey reported that 18% of 7,085 mothers who recently gave birth reported “feelings consistent with postpartum depression” based on scores ≥7 on a 5-item version of the Edinburgh Postpartum Depression Scale (EPDS-5). The EPDS-5 was designed as a screening questionnaire, not to classify disorders or estimate prevalence; the extent to which EPDS-5 results reflect depression prevalence is unknown. We investigated EPDS-5 ≥7 performance relative to major depression prevalence based on a validated diagnostic interview, the Structured Clinical Interview for DSM (SCID). Methods: We searched Medline, Medline In-Process & Other Non-Indexed Citations, PsycINFO, and the Web of Science Core Collection through June 2016 for studies with data sets with item response data to calculate EPDS-5 scores and that used the SCID to ascertain depression status. We conducted an individual participant data meta-analysis to estimate pooled percentage of EPDS-5 ≥7, pooled SCID major depression prevalence, and the pooled difference in prevalence. Results: A total of 3,958 participants from 19 primary studies were included. Pooled prevalence of SCID major depression was 9.2% (95% confidence interval [CI] 6.0% to 13.7%), pooled percentage of participants with EPDS-5 ≥7 was 16.2% (95% CI 10.7% to 23.8%), and pooled difference was 8.0% (95% CI 2.9% to 13.2%). In the 19 included studies, mean and median ratios of EPDS-5 to SCID prevalence were 2.1 and 1.4 times. Conclusions: Prevalence estimated based on EPDS-5 ≥7 appears to be substantially higher than the prevalence of major depression. Validated diagnostic interviews should be used to establish prevalence.

Published
2020
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24. Comparison of mental health symptoms before and during the covid-19 pandemic: evidence from a systematic review and meta-analysis of 134 cohorts.

Author

Ying Sun, Yin Wu, Suiqiong Fan, Dal Santo, Tiffany, Letong Li, Xiaowen Jiang, Kexin Li, Yutong Wang, Tasleem, Amina, Krishnan, Ankur, Chen He, Bonardi, Olivia, Boruff, Jill T., Rice, Danielle B., Markham, Sarah, Levis, Brooke, Azar, Marleine, Thombs-Vite, Ian, Neupane, Dipika, and Agic, Branka

Subjects
COVID-19, PSYCHOLOGY information storage & retrieval systems, CINAHL database, META-analysis, MEDICAL information storage & retrieval systems, SYSTEMATIC reviews, SEX distribution, MENTAL depression, RESEARCH funding, MEDLINE, ANXIETY, COVID-19 pandemic, MENTAL illness
Published
2023
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25. Accuracy of the Patient Health Questionnaire-9 for screening to detect major depression: updated systematic review and individual participant data meta-analysis

Author

Negeri, Zelalem F, Levis, Brooke, Sun, Ying, He, Chen, Krishnan, Ankur, Wu, Yin, Bhandari, Parash Mani, Neupane, Dipika, Brehaut, Eliana, Benedetti, Andrea, Thombs, Brett D, Imran, Mahrukh, Rice, Danielle B, Riehm, Kira E, Azar, Marleine, Levis, Alexander W, Boruff, Jill T, Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P A, Kloda, Lorie A, Patten, Scott B, Shrier, Ian, Ziegelstein, Roy C, Markham, Sarah, Alamri, Sultan H, Amtmann, Dagmar, Arroll, Bruce, Ayalon, Liat, Baradaran, Hamid R, Beraldi, Anna, Bernstein, Charles N, Bhana, Arvin, Bombardier, Charles H, Buji, Ryna Imma, Butterworth, Peter, Carter, Gregory, Chagas, Marcos H, Chan, Juliana C N, Chan, Lai Fong, Chibanda, Dixon, Clover, Kerrie, Conway, Aaron, Conwell, Yeates, Daray, Federico M, de Man-van Ginkel, Janneke M, Delgadillo, Jaime, Diez-Quevedo, Crisanto, Fann, Jesse R, Fischer, Felix H, Field, Sally, Fisher, Jane R W, Fung, Daniel, Garman, Emily C, Gelaye, Bizu, Gholizadeh, Leila, Gibson, Lorna J, Goodyear-Smith, Felicity, Green, Eric P, Greeno, Catherine G, Hall, Brian J, Hantsoo, Liisa, Haroz, Emily E, Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E, Honikman, Simone, Hudson, Marie, Hyphantis, Thomas, Inagaki, Masatoshi, Jeon, Hong Jin, Jetté, Nathalie, Khamseh, Mohammad E, Kӧhler, Sebastian, Kohrt, Brandon A, Kwan, Yunxin, Lamers, Femke, Lara, Maria Asunción, Levin-Aspenson, Holly F, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R, Löwe, Bernd, Luitel, Nagendra P, Lund, Crick, Marrie, Ruth Ann, Marsh, Laura, Marx, Brian P, McGuire, Anthony, Mohd Sidik, Sherina, Munhoz, Tiago N, Muramatsu, Kumiko, Nakku, Juliet E M, Navarrete, Laura, Osório, Flávia L, Pence, Brian W, Persoons, Philippe, Petersen, Inge, Picardi, Angelo, Pugh, Stephanie L, Quinn, Terence J, Rancans, Elmars, Rathod, Sujit D, Reuter, Katrin, Rooney, Alasdair G, Rowe, Heather J, Santos, Iná S, Schram, Miranda T, Shaaban, Juwita, Shinn, Eileen H, Sidebottom, Abbey, Simning, Adam, Spangenberg, Lena, Stafford, Lesley, Sung, Sharon C, Suzuki, Keiko, Tan, Pei Lin Lynnette, Taylor-Rowan, Martin, Tran, Thach D, Turner, Alyna, van der Feltz-Cornelis, Christina M, van Heyningen, Thandi, van Weert, Henk C, Vöhringer, Paul A, Wagner, Lynne I, Wang, Jian Li, Wang, Wenzheng, Watson, David, White, Jennifer, Whooley, Mary A, Winkley, Kirsty, Wynter, Karen, Yamada, Mitsuhiko, Zeng, Qing Zhi, and Zhang, Yuying

Subjects
Adult, Male, medicine.medical_specialty, MEDLINE, PsycINFO, Patient Health Questionnaire, Sex Factors, Medicine, Humans, Mini-international neuropsychiatric interview, Psychiatric Status Rating Scales, Depressive Disorder, Major, business.industry, Research, Age Factors, General Medicine, Middle Aged, Reference Standards, Random effects model, Confidence interval, ROC Curve, Meta-analysis, Family medicine, Structured interview, Female, business
Abstract

ObjectiveTo update a previous individual participant data meta-analysis and determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9), the most commonly used depression screening tool in general practice, for detecting major depression overall and by study or participant subgroups.DesignSystematic review and individual participant data meta-analysis.Data sourcesMedline, Medline In-Process, and Other Non-Indexed Citations via Ovid, PsycINFO, Web of Science searched through 9 May 2018.Review methodsEligible studies administered the PHQ-9 and classified current major depression status using a validated semistructured diagnostic interview (designed for clinician administration), fully structured interview (designed for lay administration), or the Mini International Neuropsychiatric Interview (MINI; a brief interview designed for lay administration). A bivariate random effects meta-analytic model was used to obtain point and interval estimates of pooled PHQ-9 sensitivity and specificity at cut-off values 5-15, separately, among studies that used semistructured diagnostic interviews (eg, Structured Clinical Interview for Diagnostic and Statistical Manual), fully structured interviews (eg, Composite International Diagnostic Interview), and the MINI. Meta-regression was used to investigate whether PHQ-9 accuracy correlated with reference standard categories and participant characteristics.ResultsData from 44 503 total participants (27 146 additional from the update) were obtained from 100 of 127 eligible studies (42 additional studies; 79% eligible studies; 86% eligible participants). Among studies with a semistructured interview reference standard, pooled PHQ-9 sensitivity and specificity (95% confidence interval) at the standard cut-off value of ≥10, which maximised combined sensitivity and specificity, were 0.85 (0.79 to 0.89) and 0.85 (0.82 to 0.87), respectively. Specificity was similar across reference standards, but sensitivity in studies with semistructured interviews was 7-24% (median 21%) higher than with fully structured reference standards and 2-14% (median 11%) higher than with the MINI across cut-off values. Across reference standards and cut-off values, specificity was 0-10% (median 3%) higher for men and 0-12 (median 5%) higher for people aged 60 or older.ConclusionsResearchers and clinicians could use results to determine outcomes, such as total number of positive screens and false positive screens, at different PHQ-9 cut-off values for different clinical settings using the knowledge translation tool atwww.depressionscreening100.com/phq.Study registrationPROSPERO CRD42014010673.

Published
2021

26. Data-driven methods distort optimal cutoffs and accuracy estimates of depression screening tools: a simulation study using individual participant data

Author

Bhandari, Parash Mani, primary, Levis, Brooke, additional, Neupane, Dipika, additional, Patten, Scott B., additional, Shrier, Ian, additional, Thombs, Brett D., additional, Benedetti, Andrea, additional, Sun, Ying, additional, He, Chen, additional, Rice, Danielle B., additional, Krishnan, Ankur, additional, Wu, Yin, additional, Azar, Marleine, additional, Sanchez, Tatiana A., additional, Chiovitti, Matthew J., additional, Saadat, Nazanin, additional, Riehm, Kira E., additional, Imran, Mahrukh, additional, Negeri, Zelalem, additional, Boruff, Jill T., additional, Cuijpers, Pim, additional, Gilbody, Simon, additional, Ioannidis, John P.A., additional, Kloda, Lorie A., additional, Ziegelstein, Roy C., additional, Comeau, Liane, additional, Mitchell, Nicholas D., additional, Tonelli, Marcello, additional, Vigod, Simone N., additional, Aceti, Franca, additional, Alvarado, Rubén, additional, Alvarado-Esquivel, Cosme, additional, Bakare, Muideen O., additional, Barnes, Jacqueline, additional, Bavle, Amar D., additional, Beck, Cheryl Tatano, additional, Bindt, Carola, additional, Boyce, Philip M., additional, Bunevicius, Adomas, additional, Castro e Couto, Tiago, additional, Chaudron, Linda H., additional, Correa, Humberto, additional, de Figueiredo, Felipe Pinheiro, additional, Eapen, Valsamma, additional, Favez, Nicolas, additional, Felice, Ethel, additional, Fernandes, Michelle, additional, Figueiredo, Barbara, additional, Fisher, Jane R.W., additional, Garcia-Esteve, Lluïsa, additional, Giardinelli, Lisa, additional, Helle, Nadine, additional, Howard, Louise M., additional, Khalifa, Dina Sami, additional, Kohlhoff, Jane, additional, Kozinszky, Zoltán, additional, Kusminskas, Laima, additional, Lelli, Lorenzo, additional, Leonardou, Angeliki A., additional, Maes, Michael, additional, Meuti, Valentina, additional, Radoš, Sandra Nakić, additional, García, Purificación Navarro, additional, Nishi, Daisuke, additional, Luwa E-Andjafono, Daniel Okitundu, additional, Pawlby, Susan J., additional, Quispel, Chantal, additional, Robertson-Blackmore, Emma, additional, Rochat, Tamsen J., additional, Rowe, Heather J., additional, Sharp, Deborah J., additional, Siu, Bonnie W.M., additional, Skalkidou, Alkistis, additional, Stein, Alan, additional, Stewart, Robert C., additional, Su, Kuan-Pin, additional, Sundström-Poromaa, Inger, additional, Tadinac, Meri, additional, Tandon, S. Darius, additional, Tendais, Iva, additional, Thiagayson, Pavaani, additional, Töreki, Annamária, additional, Torres-Giménez, Anna, additional, Tran, Thach D., additional, Trevillion, Kylee, additional, Turner, Katherine, additional, Vega-Dienstmaier, Johann M., additional, Wynter, Karen, additional, and Yonkers, Kimberly A., additional

Published
2021
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27. Depression prevalence based on the Edinburgh Postnatal Depression Scale compared to Structured Clinical Interview for DSM DIsorders classification: Systematic review and individual participant data meta-analysis

Author

Lyubenova, Anita Neupane, Dipika Levis, Brooke Wu, Yin and Sun, Ying He, Chen Krishnan, Ankur Bhandari, Parash M. and Negeri, Zelalem Imran, Mahrukh Rice, Danielle B. Azar, Marleine Chiovitti, Matthew J. Saadat, Nazanin Riehm, Kira E. Boruff, Jill T. Ioannidis, John P. A. Cuijpers, Pim and Gilbody, Simon Kloda, Lorie A. Patten, Scott B. Shrier, Ian and Ziegelstein, Roy C. Comeau, Liane Mitchell, Nicholas D. and Tonelli, Marcello Vigod, Simone N. Aceti, Franca Barnes, Jacqueline Bavle, Amar D. Beck, Cheryl T. Bindt, Carola and Boyce, Philip M. Bunevicius, Adomas Chaudron, Linda H. and Favez, Nicolas Figueiredo, Barbara Garcia-Esteve, Lluisa and Giardinelli, Lisa Helle, Nadine Howard, Louise M. Kohlhoff, Jane Kusminskas, Laima Kozinszky, Zoltan Lelli, Lorenzo and Leonardou, Angeliki A. Meuti, Valentina Rados, Sandra N. and Garcia, Purificacion N. Pawlby, Susan J. Quispel, Chantal and Robertson-Blackmore, Emma Rochat, Tamsen J. Sharp, Deborah J. and Siu, Bonnie W. M. Stein, Alan Stewart, Robert C. and Tadinac, Meri Tandon, S. Darius Tendais, Iva Toreki, Annamaria Torres-Gimenez, Anna Tran, Thach D. Trevillion, Kylee Turner, Katherine Vega-Dienstmaier, Johann M. and Benedetti, Andrea Thombs, Brett D.

Abstract

Objectives Estimates of depression prevalence in pregnancy and postpartum are based on the Edinburgh Postnatal Depression Scale (EPDS) more than on any other method. We aimed to determine if any EPDS cutoff can accurately and consistently estimate depression prevalence in individual studies. Methods We analyzed datasets that compared EPDS scores to Structured Clinical Interview for DSM (SCID) major depression status. Random-effects meta-analysis was used to compare prevalence with EPDS cutoffs versus the SCID. Results Seven thousand three hundred and fifteen participants (1017 SCID major depression) from 29 primary studies were included. For EPDS cutoffs used to estimate prevalence in recent studies (>= 9 to >= 14), pooled prevalence estimates ranged from 27.8% (95% CI: 22.0%-34.5%) for EPDS >= 9 to 9.0% (95% CI: 6.8%-11.9%) for EPDS >= 14; pooled SCID major depression prevalence was 9.0% (95% CI: 6.5%-12.3%). EPDS >= 14 provided pooled prevalence closest to SCID-based prevalence but differed from SCID prevalence in individual studies by a mean absolute difference of 5.1% (95% prediction interval: -13.7%, 12.3%). Conclusion EPDS >= 14 approximated SCID-based prevalence overall, but considerable heterogeneity in individual studies is a barrier to using it for prevalence estimation.

Published
2021

28. Comparison of Mental Health Symptom Changes from pre-COVID-19 to COVID-19 by Sex or Gender: A Systematic Review and Meta-analysis

Author

Santo, Tiffany Dal, primary, Sun, Ying, additional, Wu, Yin, additional, He, Chen, additional, Wang, Yutong, additional, Jiang, Xiaowen, additional, Li, Kexin, additional, Bonardi, Olivia, additional, Krishnan, Ankur, additional, Boruff, Jill T., additional, Rice, Danielle B., additional, Markham, Sarah, additional, Levis, Brooke, additional, Azar, Marleine, additional, Neupane, Dipika, additional, Tasleem, Amina, additional, Yao, Anneke, additional, Thombs-Vite, Ian, additional, Agic, Branka, additional, Fahim, Christine, additional, Martin, Michael S., additional, Sockalingam, Sanjeev, additional, Turecki, Gustavo, additional, Benedetti, Andrea, additional, and Thombs, Brett D., additional

Published
2021
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29. Comparison of different scoring methods based on latent variable models of the PHQ-9: an individual participant data meta-analysis.

Author

Fischer, Felix, Levis, Brooke, Falk, Carl, Sun, Ying, Ioannidis, John P. A., Cuijpers, Pim, Shrier, Ian, Benedetti, Andrea, Thombs, Brett D., the Depression Screening Data (DEPRESSD) PHQ Collaboration, He, Chen, Krishnan, Ankur, Wu, Yin, Negeri, Zelalem, Bhandari, Parash Mani, Neupane, Dipika, Rice, Danielle B., Riehm, Kira E., Saadat, Nazanin, and Azar, Marleine

Subjects
MEDICAL screening, MENTAL depression, QUESTIONNAIRES, DESCRIPTIVE statistics, STATISTICAL models, DATA analysis software, SECONDARY analysis
Abstract

Background: Previous research on the depression scale of the Patient Health Questionnaire (PHQ-9) has found that different latent factor models have maximized empirical measures of goodness-of-fit. The clinical relevance of these differences is unclear. We aimed to investigate whether depression screening accuracy may be improved by employing latent factor model-based scoring rather than sum scores. Methods: We used an individual participant data meta-analysis (IPDMA) database compiled to assess the screening accuracy of the PHQ-9. We included studies that used the Structured Clinical Interview for DSM (SCID) as a reference standard and split those into calibration and validation datasets. In the calibration dataset, we estimated unidimensional, two-dimensional (separating cognitive/affective and somatic symptoms of depression), and bi-factor models, and the respective cut-offs to maximize combined sensitivity and specificity. In the validation dataset, we assessed the differences in (combined) sensitivity and specificity between the latent variable approaches and the optimal sum score (⩾10), using bootstrapping to estimate 95% confidence intervals for the differences. Results: The calibration dataset included 24 studies (4378 participants, 652 major depression cases); the validation dataset 17 studies (4252 participants, 568 cases). In the validation dataset, optimal cut-offs of the unidimensional, two-dimensional, and bi-factor models had higher sensitivity (by 0.036, 0.050, 0.049 points, respectively) but lower specificity (0.017, 0.026, 0.019, respectively) compared to the sum score cut-off of ⩾10. Conclusions: In a comprehensive dataset of diagnostic studies, scoring using complex latent variable models do not improve screening accuracy of the PHQ-9 meaningfully as compared to the simple sum score approach. [ABSTRACT FROM AUTHOR]

Published
2022
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30. Shortening the Edinburgh postnatal depression scale using optimal test assembly methods: Development of the EPDS-Dep-5

Author

Harel, Daphna, Levis, Brooke, Ishihara, Miyabi, Levis, Alexander W., Vigod, Simone N., Howard, Louise M., Thombs, Brett D., Benedetti, Andrea, Sun, Ying, He, Chen, Krishnan, Ankur, Wu, Yin, Bhandari, Parash Mani, Neupane, Dipika, Negeri, Zelalem, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., 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, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, de Figueiredo, Felipe Pinheiro, Fellmeth, Gracia, Figueiredo, Barbara, Green, Eric P., Helle, Nadine, Kettunen, Pirjo A., Kohlhoff, Jane, Kozinszky, Zoltán, Leonardou, Angeliki A., Nakić Radoš, Sandra, Rochat, Tamsen J., Smith‐Nielsen, Johanne, Stein, Alan, Stewart, Robert C., Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Töreki, Annamária, Tran, Thach D., Turner, Katherine, Væver, Mette S., Vega‐Dienstmaier, Johann M., the DEPRESsion Screening Data (DEPRESSD) EPDS Collaboration, Collaboration, DEPRESsion Screening Data (DEPRESSD) EPDS, and Universidade do Minho

Subjects
Optimal test, Validity, Sensitivity and Specificity, Depression, Postpartum, 03 medical and health sciences, 0302 clinical medicine, Cronbach's alpha, Pregnancy, Optimal test assembly, Item response theory, Medicine, Cutoff, Humans, Patient-reported outcome, Psychiatric Status Rating Scales, Depressive Disorder, Major, Depression, business.industry, Reproducibility of Results, Confirmatory factor analysis, 030227 psychiatry, 3. Good health, Psychiatry and Mental health, Edinburgh Postnatal Depression Scale, Short form, depression, optimal test assembly, patient-reported outcome, short form, Female, business, 030217 neurology & neurosurgery, Clinical psychology
Abstract

Aims: This study used a large database to develop a reliable and valid shortened form of the Edinburgh Postnatal Depression Scale (EPDS), a self-report questionnaire used for depression screening in pregnancy and postpartum, based on objective criteria. Methods: Item responses from the 10-item EPDS were obtained from 5157 participants (765 major depression cases) from 22 primary screening accuracy studies that compared the EPDS to the Structured Clinical Interview for DSM (SCID). Unidimensionality of the EPDS latent construct was verified using confirmatory factor analysis, and an item response theory model was fit. Optimal test assembly (OTA) methods identified a maximally informative shortened form for each possible scale length between 1 and 9 items. The final shortened form was selected based on prespecified validity and reliability criteria and non-inferiority of screening accuracy of the EPDS as compared to the SCID. Results: A 5-item short form of the EPDS (EPDS-Dep-5) was selected. The EPDSDep-5 had a Cronbach's alpha of 0.82. Sensitivity and specificity of the EPDS-Dep-5 for a cutoff of 4 or greater were 0.83 (95% CI, 0.73, 0.89) and 0.86 (95% CI, 0.80, 0.90) and were statistically non-inferior to the EPDS. The correlation of total scores with the full EPDS was high (r = 0.91). Conclusion: The EPDS-Dep-5 is a valid short form with minimal loss of information when compared to the full-length EPDS. The EPDS-Dep-5 was developed with OTA methods using objective, pre-specified criteria, but the approach is data-driven and exploratory. Thus, there is a need to replicate results of this study in different populations., This study was funded by the Canadian Institutes of Health Research (CIHR, KRS-140994). Dr. Levis was supported by a Fonds de recherche du QuébecSanté (FRQS) Postdoctoral Training Fellowship. Drs. Thombs and Benedetti were supported by FRQS researcher salary awards. Dr. Wu was supported by a FRQS Postdoctoral Training Fellowship. Mr. Bhandari was supported by a studentship from the Research Institute of the McGill University Health Centre. Ms. Neupane was supported by G.R. Caverhill Fellowship from the Faculty of Medicine, McGill University. Ms. Rice was supported by a Vanier Canada Graduate Scholarship. Ms. Azar was supported by a FRQS Masters Training Award. The primary study by Barnes et al was supported by a grant from the Health Foundation (1665/608). The primary study by Beck et al was supported by the Patrick and Catherine Weldon Donaghue Medical Research Foundation and the University of Connecticut Research Foundation. The primary study by Helle et al was supported by the Werner Otto Foundation, the Kroschke Foundation, and the Feindt Foundation. The primary study by de Figueiredo et al was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo. The primary study by Tendais et al was supported under the project POCI/SAU-ESP/56397/2004 by the Operational Program Science and Innovation 2010 (POCI 2010) of the Community Support Board III and by the European Community Fund FEDER. This primary study by Green et al was supported by a grant from the Duke Global Health Institute (453- 0751). The primary study by Kettunen et al was supported with an Annual EVO Financing (Special government subsidies from the Ministry of Health and Welfare, Finland) by North Karelia Central Hospital and Päijät-Häme Central Hospital. The primary study by Phillips et al was supported by a scholarship from the National Health and Medical and Research Council (NHMRC). The primary study by Nakić Radoš et al was supported by the Croatian Ministry of Science, Education, and Sports (134- 0000000-2421). The primary study by Rochat et al was supported by grants from the University of Oxford (HQ5035), the Tuixen Foundation (9940), the Wellcome Trust (082384/Z/07/Z and 071571), and the American Psychological Association. Dr. Rochat receives salary support from a Wellcome Trust Intermediate Fellowship (211374/Z/18/Z). The primary study by Smith-Nielsen et al was supported by a grant from the charitable foundation Tryg Foundation (Grant ID no 107616). The primary study by Prenoveau et al was supported by The Wellcome Trust (grant number 071571). The primary study by Stewart et al was supported by Professor Francis Creed's Journal of Psychosomatic Research Editorship fund (BA00457) administered through University of Manchester. The primary study by Tandon et al was funded by the Thomas Wilson Sanitarium. The primary study by Tran et al was supported by the Myer Foundation who funded the study under its Beyond Australia scheme. Dr. Tran was supported by an early career fellowship from the Australian National Health and Medical Research Council. The primary study by Vega-Dienstmaier et al was supported by Tejada Family Foundation, Inc, and Peruvian-American Endowment, Inc.

Published
2020

31. Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis

Author

McGrath Sean, Zhao XiaoFei, Steele Russell, Thombs Brett D., Benedetti Andrea, Levis Brooke, Riehm Kira E., Saadat Nazanin, Levis Alexander W., Azar Marleine, Rice Danielle B., Sun Ying, Krishnan Ankur, He Chen, Wu Yin, Bhandari Parash Mani, Neupane Dipika, Imran Mahrukh, Boruff Jill, Cuijpers Pim, Gilbody Simon, Ioannidis John P. A., Kloda Lorie A., McMillan Dean, Patten Scott B., Shrier Ian, Ziegelstein Roy C., Akena Dickens H., Arroll Bruce, Ayalon Liat, Baradaran Hamid R., Baron Murray, Beraldi Anna, Bombardier Charles H., Butterworth Peter, Carter Gregory, Chagas Marcos H., Chan Juliana C. N., Cholera Rushina, Chowdhary Neerja, Clover Kerrie, Conwell Yeates, Ginkel Janneke M. de Man-van, Delgadillo Jaime, Fann Jesse R., Fischer Felix H., Fischler Benjamin, Fung Daniel, Gelaye Bizu, Goodyear-Smith Felicity, Greeno Catherine G., Hall Brian J., Harrison Patricia A., Harter Martin, Hegerl Ulrich, Hides Leanne, Hobfoll Stevan E., Hudson Marie, Hyphantis Thomas, INAGAKI, Masatoshi, Ismail Khalida, Jette Nathalie, Khamseh Mohammad E., Kiely Kim M., Kwan Yunxin, Lamers Femke, Liu Shen-Ing, Lotrakul Manote, Loureiro Sonia R., Loewe Bernd, Marsh Laura, McGuire Anthony, Sidik Sherina Mohd, Munhoz Tiago N., Muramatsu Kumiko, Osorio Flavia L., Patel Vikram, Pence Brian W., Persoons Philippe, Picardi Angelo, Reuter Katrin, Rooney Alasdair G., Santos Ina S., Shaaban Juwita, Sidebottom Abbey, Simning Adam, Stafford Lesley, Sung Sharon C., Tan Pei Lin Lynnette, Turner Alyna, van der Feltz-Cornelis Christina M., van Weert Henk C., Vohringer Paul A., White Jennifer, Whooley Mary A., Winkley Kirsty, Yamada Mitsuhiko, Zhang Yuying, General practice, ACS - Heart failure & arrhythmias, APH - Personalized Medicine, APH - Quality of Care, Psychiatry, APH - Mental Health, and APH - Digital Health

Subjects
Statistics and Probability, FOS: Computer and information sciences, Epidemiology, Summary data, median, Meta-analysis, first quartile, third quartile, minimum value, maximum value, Standard deviation, Article, Methodology (stat.ME), 03 medical and health sciences, 0302 clinical medicine, Outcome variable, Health Information Management, Statistics, 030212 general & internal medicine, Statistics - Methodology, Mathematics, Sample mean and sample covariance, Outcome (probability), Quartile, 030217 neurology & neurosurgery, Quantile
Abstract

Researchers increasingly use meta-analysis to synthesize the results of several studies in order to estimate a common effect. When the outcome variable is continuous, standard meta-analytic approaches assume that the primary studies report the sample mean and standard deviation of the outcome. However, when the outcome is skewed, authors sometimes summarize the data by reporting the sample median and one or both of (i) the minimum and maximum values and (ii) the first and third quartiles, but do not report the mean or standard deviation. To include these studies in meta-analysis, several methods have been developed to estimate the sample mean and standard deviation from the reported summary data. A major limitation of these widely used methods is that they assume that the outcome distribution is normal, which is unlikely to be tenable for studies reporting medians. We propose two novel approaches to estimate the sample mean and standard deviation when data are suspected to be non-normal. Our simulation results and empirical assessments show that the proposed methods often perform better than the existing methods when applied to non-normal data.

Published
2020
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32. Overestimation of Postpartum Depression Prevalence Based on a 5-item Version of the EPDS:Systematic Review and Individual Participant Data Meta-Analysis

Author

Thombs, Brett, Levis, Brooke, Lyubenov, Anita, Neupane, Dipika, Negeri, Zelalem, Wu, Yin, Sun, Ying, He, Chen, Krishnan, Ankur, Vigod, Simone N., Bhandari, Parash Mani, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., 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, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, Figueiredo, Barbara, Helle, Nadine, Howard, Louise, Kohlhoff, Jane, Kozinszky, Zoltán, Nakić Radoš, Sandra, Quispel, Chantal, Rochat, Tamsen J., Stei, Alan, Stewart, Robert C., Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Töreki, Annamária, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega‐dienstmaier, Johann M., and Benedetti, Andrea

Published
2020

33. Shortening the Edinburgh postnatal depression scale using optimal test assembly methods:Development of the EPDS-Dep-5

Author

Harel, Daphna, Levis, Brooke, Ishihara, Miyabi, Levis, Alexander W., Vigod, Simone N., Howard, Louise M., Thombs, Brett D., Benedetti, Andrea, Sun, Ying, He, Chen, Krishnan, Ankur, Wu, Yin, Bhandari, Parash Mani, Neupane, Dipika, Negeri, Zelalem, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., 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, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, de Figueiredo, Felipe Pinheiro, Fellmeth, Gracia, Figueiredo, Barbara, Green, Eric P., Helle, Nadine, Kettunen, Pirjo A., Kohlhoff, Jane, Kozinszky, Zoltán, Leonardou, Angeliki A., Nakić Radoš, Sandra, Rochat, Tamsen J., Smith-Nielsen, Johanne, Stein, Alan, Stewart, Robert C., Væver, Mette S., Harel, Daphna, Levis, Brooke, Ishihara, Miyabi, Levis, Alexander W., Vigod, Simone N., Howard, Louise M., Thombs, Brett D., Benedetti, Andrea, Sun, Ying, He, Chen, Krishnan, Ankur, Wu, Yin, Bhandari, Parash Mani, Neupane, Dipika, Negeri, Zelalem, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., 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, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, de Figueiredo, Felipe Pinheiro, Fellmeth, Gracia, Figueiredo, Barbara, Green, Eric P., Helle, Nadine, Kettunen, Pirjo A., Kohlhoff, Jane, Kozinszky, Zoltán, Leonardou, Angeliki A., Nakić Radoš, Sandra, Rochat, Tamsen J., Smith-Nielsen, Johanne, Stein, Alan, Stewart, Robert C., and Væver, Mette S.

Abstract

Aims: This study used a large database to develop a reliable and valid shortened form of the Edinburgh Postnatal Depression Scale (EPDS), a self-report questionnaire used for depression screening in pregnancy and postpartum, based on objective criteria. Methods: Item responses from the 10-item EPDS were obtained from 5157 participants (765 major depression cases) from 22 primary screening accuracy studies that compared the EPDS to the Structured Clinical Interview for DSM (SCID). Unidimensionality of the EPDS latent construct was verified using confirmatory factor analysis, and an item response theory model was fit. Optimal test assembly (OTA) methods identified a maximally informative shortened form for each possible scale length between 1 and 9 items. The final shortened form was selected based on pre-specified validity and reliability criteria and non-inferiority of screening accuracy of the EPDS as compared to the SCID. Results: A 5-item short form of the EPDS (EPDS-Dep-5) was selected. The EPDS-Dep-5 had a Cronbach's alpha of 0.82. Sensitivity and specificity of the EPDS-Dep-5 for a cutoff of 4 or greater were 0.83 (95% CI, 0.73, 0.89) and 0.86 (95% CI, 0.80, 0.90) and were statistically non-inferior to the EPDS. The correlation of total scores with the full EPDS was high (r = 0.91). Conclusion: The EPDS-Dep-5 is a valid short form with minimal loss of information when compared to the full-length EPDS. The EPDS-Dep-5 was developed with OTA methods using objective, pre-specified criteria, but the approach is data-driven and exploratory. Thus, there is a need to replicate results of this study in different populations.

Published
2021

34. Comparison of Mental Health Symptoms Prior to and During COVID-19: Evidence from a Systematic Review and Meta-analysis of 134 Cohorts

Author

Sun, Ying, primary, Wu, Yin, additional, Fan, Suiqiong, additional, Santo, Tiffany Dal, additional, Li, Letong, additional, Jiang, Xiaowen, additional, Li, Kexin, additional, Wang, Yutong, additional, Tasleem, Amina, additional, Krishnan, Ankur, additional, He, Chen, additional, Bonardi, Olivia, additional, Boruff, Jill T., additional, Rice, Danielle B., additional, Markham, Sarah, additional, Levis, Brooke, additional, Azar, Marleine, additional, Thombs-Vite, Ian, additional, Neupane, Dipika, additional, Agic, Branka, additional, Fahim, Christine, additional, Martin, Michael S., additional, Sockalingam, Sanjeev, additional, Turecki, Gustavo, additional, Benedetti, Andrea, additional, and Thombs, Brett D., additional

Published
2021
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35. Accuracy of the Hospital Anxiety and Depression Scale Depression subscale (HADS-D) to screen for major depression: systematic review and individual participant data meta-analysis

Author

Wu, Yin, primary, Levis, Brooke, additional, Sun, Ying, additional, He, Chen, additional, Krishnan, Ankur, additional, Neupane, Dipika, additional, Bhandari, Parash Mani, additional, Negeri, Zelalem, additional, Benedetti, Andrea, additional, and Thombs, Brett D, additional

Published
2021
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37. Validation of the COVID-19 Fears Questionnaires for Chronic Medical Conditions: A Scleroderma Patient-centered Intervention Network COVID-19 Cohort study

Author

Wu, Yin, primary, Kwakkenbos, Linda, additional, Henry, Richard S., additional, Tao, Lydia, additional, Harb, Sami, additional, Bourgeault, Angelica, additional, Carrier, Marie-Eve, additional, Levis, Brooke, additional, Sun, Ying, additional, Bhandari, Parash Mani, additional, Carboni-Jiménez, Andrea, additional, Gagarine, Maria, additional, He, Chen, additional, Krishnan, Ankur, additional, Negeri, Zelalem F., additional, Neupane, Dipika, additional, Mouthon, Luc, additional, Bartlett, Susan J., additional, Benedetti, Andrea, additional, Thombs, Brett D., additional, Culos-Reed, Nicole, additional, El-Baalbaki, Ghassan, additional, Hebblethwaite, Shannon, additional, Patten, Scott, additional, Varga, John, additional, Bustamante, Laura, additional, Duchek, Delaney, additional, Ellis, Kelsey, additional, Rice, Danielle, additional, Dyas, Laura, additional, Fortuné, Catherine, additional, Gietzen, Amy, additional, Guillot, Geneviève, additional, Lewis, Nancy, additional, Nielsen, Karen, additional, Richard, Michelle, additional, Sauvé, Maureen, additional, and Welling, Joep, additional

Published
2020
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38. Overestimation of Postpartum Depression Prevalence Based on a 5-item Version of the EPDS: Systematic Review and Individual Participant Data Meta-analysis

Author

Thombs, Brett D., primary, Levis, Brooke, additional, Lyubenova, Anita, additional, Neupane, Dipika, additional, Negeri, Zelalem, additional, Wu, Yin, additional, Sun, Ying, additional, He, Chen, additional, Krishnan, Ankur, additional, Vigod, Simone N., additional, Bhandari, Parash Mani, additional, Imran, Mahrukh, additional, Rice, Danielle B., additional, Azar, Marleine, additional, Chiovitti, Matthew J., additional, Saadat, Nazanin, additional, Riehm, Kira E., additional, Boruff, Jill T., additional, Cuijpers, Pim, additional, Gilbody, Simon, additional, Ioannidis, John P. A., additional, Kloda, Lorie A., additional, Patten, Scott B., additional, Shrier, Ian, additional, Ziegelstein, Roy C., additional, Comeau, Liane, additional, Mitchell, Nicholas D., additional, Tonelli, Marcello, additional, Barnes, Jacqueline, additional, Beck, Cheryl Tatano, additional, Bindt, Carola, additional, Figueiredo, Barbara, additional, Helle, Nadine, additional, Howard, Louise M., additional, Kohlhoff, Jane, additional, Kozinszky, Zoltán, additional, Leonardou, Angeliki A., additional, Radoš, Sandra Nakić, additional, Quispel, Chantal, additional, Rochat, Tamsen J., additional, Stein, Alan, additional, Stewart, Robert C., additional, Tadinac, Meri, additional, Tandon, S. Darius, additional, Tendais, Iva, additional, Töreki, Annamária, additional, Tran, Thach D., additional, Trevillion, Kylee, additional, Turner, Katherine, additional, Vega-Dienstmaier, Johann M., additional, and Benedetti, Andrea, additional

Published
2020
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39. Depression prevalence based on the Edinburgh Postnatal Depression Scale compared to Structured Clinical Interview for DSM DIsorders classification: Systematic review and individual participant data meta‐analysis

Author

Lyubenova, Anita, primary, Neupane, Dipika, additional, Levis, Brooke, additional, Wu, Yin, additional, Sun, Ying, additional, He, Chen, additional, Krishnan, Ankur, additional, Bhandari, Parash M., additional, Negeri, Zelalem, additional, Imran, Mahrukh, additional, Rice, Danielle B., additional, Azar, Marleine, additional, Chiovitti, Matthew J., additional, Saadat, Nazanin, additional, Riehm, Kira E., additional, Boruff, Jill T., additional, Ioannidis, John P. A., additional, Cuijpers, Pim, additional, Gilbody, Simon, additional, Kloda, Lorie A., additional, Patten, Scott B., additional, Shrier, Ian, additional, Ziegelstein, Roy C., additional, Comeau, Liane, additional, Mitchell, Nicholas D., additional, Tonelli, Marcello, additional, Vigod, Simone N., additional, Aceti, Franca, additional, Barnes, Jacqueline, additional, Bavle, Amar D., additional, Beck, Cheryl T., additional, Bindt, Carola, additional, Boyce, Philip M., additional, Bunevicius, Adomas, additional, Chaudron, Linda H., additional, Favez, Nicolas, additional, Figueiredo, Barbara, additional, Garcia‐Esteve, Lluïsa, additional, Giardinelli, Lisa, additional, Helle, Nadine, additional, Howard, Louise M., additional, Kohlhoff, Jane, additional, Kusminskas, Laima, additional, Kozinszky, Zoltán, additional, Lelli, Lorenzo, additional, Leonardou, Angeliki A., additional, Meuti, Valentina, additional, Radoš, Sandra N., additional, García, Purificación N., additional, Pawlby, Susan J., additional, Quispel, Chantal, additional, Robertson‐Blackmore, Emma, additional, Rochat, Tamsen J., additional, Sharp, Deborah J., additional, Siu, Bonnie W. M., additional, Stein, Alan, additional, Stewart, Robert C., additional, Tadinac, Meri, additional, Tandon, S. Darius, additional, Tendais, Iva, additional, Töreki, Annamária, additional, Torres‐Giménez, Anna, additional, Tran, Thach D., additional, Trevillion, Kylee, additional, Turner, Katherine, additional, Vega‐Dienstmaier, Johann M., additional, Benedetti, Andrea, additional, and Thombs, Brett D., additional

Published
2020
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40. Protocol for a partially nested randomised controlled trial to evaluate the effectiveness of the scleroderma patient-centered intervention network COVID-19 home-isolation activities together (SPIN-CHAT) program to reduce anxiety among at-risk scleroderma patients

Author

Thombs, Brett D., primary, Kwakkenbos, Linda, additional, Carrier, Marie-Eve, additional, Bourgeault, Angelica, additional, Tao, Lydia, additional, Harb, Sami, additional, Gagarine, Maria, additional, Rice, Danielle, additional, Bustamante, Laura, additional, Ellis, Kelsey, additional, Duchek, Delaney, additional, Wu, Yin, additional, Bhandari, Parash Mani, additional, Neupane, Dipika, additional, Carboni-Jiménez, Andrea, additional, Henry, Richard S., additional, Krishnan, Ankur, additional, Sun, Ying, additional, Levis, Brooke, additional, He, Chen, additional, Turner, Kimberly A., additional, Benedetti, Andrea, additional, Culos-Reed, Nicole, additional, El-Baalbaki, Ghassan, additional, Hebblethwaite, Shannon, additional, Bartlett, Susan J., additional, Dyas, Laura, additional, Patten, Scott, additional, Varga, John, additional, Fortuné, Catherine, additional, Gietzen, Amy, additional, Guillot, Geneviève, additional, Lewis, Nancy, additional, Nielsen, Karen, additional, Richard, Michelle, additional, Sauvé, Maureen, additional, Welling, Joep, additional, Baron, Murray, additional, Furst, Daniel E., additional, Gottesman, Karen, additional, Malcarne, Vanessa, additional, Mayes, Maureen D., additional, Mouthon, Luc, additional, Nielson, Warren R., additional, Riggs, Robert, additional, Wigley, Fredrick, additional, Assassi, Shervin, additional, Boutron, Isabelle, additional, Ells, Carolyn, additional, van den Ende, Cornelia, additional, Fligelstone, Kim, additional, Frech, Tracy, additional, Godard, Dominique, additional, Harel, Daphna, additional, Hinchcliff, Monique, additional, Hudson, Marie, additional, Johnson, Sindhu R., additional, Larche, Maggie, additional, Leite, Catarina, additional, Nguyen, Christelle, additional, Pope, Janet, additional, Portales, Alexandra, additional, Rannou, François, additional, Reyna, Tatiana Sofia Rodriguez, additional, Schouffoer, Anne A., additional, Suarez-Almazor, Maria E., additional, Agard, Christian, additional, Albert, Alexandra, additional, André, Marc, additional, Arsenault, Guylaine, additional, Benzidia, Ilham, additional, Bernstein, Elana J., additional, Berthier, Sabine, additional, Bissonnette, Lyne, additional, Boire, Gilles, additional, Bruns, Alessandra, additional, Carreira, Patricia, additional, Casadevall, Marion, additional, Chaigne, Benjamin, additional, Chung, Lorinda, additional, Cohen, Pascal, additional, Correia, Chase, additional, Dagenais, Pierre, additional, Denton, Christopher, additional, Domsic, Robyn, additional, Dubois, Sandrine, additional, Dunne, James V., additional, Dunogue, Bertrand, additional, Fare, Regina, additional, Farge-Bancel, Dominique, additional, Fortin, Paul R., additional, Gill, Anna, additional, Gordon, Jessica, additional, Granel-Rey, Brigitte, additional, Gyger, Genevieve, additional, Hachulla, Eric, additional, Hatron, Pierre-Yves, additional, Herrick, Ariane L., additional, Hij, Adrian, additional, Hoa, Sabrina, additional, Ikic, Alena, additional, Jones, Niall, additional, de B. Fernandes, Artur Jose, additional, Kafaja, Suzanne, additional, Khalidi, Nader, additional, Lambert, Marc, additional, Launay, David, additional, Liang, Patrick, additional, Maillard, Hélène, additional, Maltez, Nancy, additional, Manning, Joanne, additional, Marie, Isabelle, additional, Martin, Maria, additional, Martin, Thierry, additional, Masetto, Ariel, additional, Maurier, François, additional, Mekinian, Arsene, additional, Melchor, Sheila, additional, Nikpour, Mandana, additional, Olagne, Louis, additional, Poindron, Vincent, additional, Proudman, Susanna, additional, Régent, Alexis, additional, Rivière, Sébastien, additional, Robinson, David, additional, Rodriguez, Esther, additional, Roux, Sophie, additional, Smets, Perrine, additional, Smith, Doug, additional, Sobanski, Vincent, additional, Spiera, Robert, additional, Steen, Virginia, additional, Stevens, Wendy, additional, Sutton, Evelyn, additional, Terrier, Benjamin, additional, Thorne, Carter, additional, Wilcox, Pearce, additional, Ayala, Mara Cañedo, additional, and Ostbo, Nora, additional

Published
2020
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41. Preliminary COVID-19 Fears Questionnaire: Systemic Sclerosis and Chronic Medical Conditions Versions

Author

Thombs, Brett, primary, Tao, Lydia, additional, Wu, Yin, additional, Levis, Brooke, additional, Sun, Ying, additional, Bourgeault, Angelica, additional, Bhandari, Parash Mani, additional, Jimenez, Andrea Carboni, additional, Gagarine, Maria, additional, Harb, Sami, additional, He, Chen, additional, Krishnan, Ankur, additional, Negeri, Zelalem F., additional, Neupane, Dipika, additional, Carrier, Marie-Eve, additional, Kwakkenbos, Linda, additional, and Benedetti, Andrea, additional

Published
2020
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43. Overestimation of Postpartum Depression Prevalence Based on a 5-item Version of the EPDS: Systematic Review and Individual Participant Data Meta-analysis

Author

Thombs, Brett D. Levis, Brooke Lyubenova, Anita Neupane, Dipika Negeri, Zelalem Wu, Yin Sun, Ying He, Chen and Krishnan, Ankur Vigod, Simone N. Bhandari, Parash Mani and Imran, Mahrukh Rice, Danielle B. Azar, Marleine Chiovitti, Matthew J. Saadat, Nazanin Riehm, Kira E. Boruff, Jill T. and Cuijpers, Pim Gilbody, Simon Ioannidis, John P. A. and Kloda, Lorie A. Patten, Scott B. Shrier, Ian Ziegelstein, Roy C. Comeau, Liane Mitchell, Nicholas D. Tonelli, Marcello and Barnes, Jacqueline Beck, Cheryl Tatano Bindt, Carola and Figueiredo, Barbara Helle, Nadine Howard, Louise M. and Kohlhoff, Jane Kozinszky, Zoltan Leonardou, Angeliki A. and Rados, Sandra Nakic Quispel, Chantal Rochat, Tamsen J. and Stein, Alan Stewart, Robert C. Tadinac, Meri Tandon, S. Darius Tendais, Iva Toreki, Annamaria Tran, Thach D. and Trevillion, Kylee Turner, Katherine Vega-Dienstmaier, Johann M. and Benedetti, Andrea

Abstract

Objective: The Maternal Mental Health in Canada, 2018/2019, survey reported that 18% of 7,085 mothers who recently gave birth reported “feelings consistent with postpartum depression” based on scores >= 7 on a 5-item version of the Edinburgh Postpartum Depression Scale (EPDS-5). The EPDS-5 was designed as a screening questionnaire, not to classify disorders or estimate prevalence; the extent to which EPDS-5 results reflect depression prevalence is unknown. We investigated EPDS-5 >= 7 performance relative to major depression prevalence based on a validated diagnostic interview, the Structured Clinical Interview for DSM (SCID). Methods: We searched Medline, Medline In-Process & Other Non-Indexed Citations, PsycINFO, and the Web of Science Core Collection through June 2016 for studies with data sets with item response data to calculate EPDS-5 scores and that used the SCID to ascertain depression status. We conducted an individual participant data meta-analysis to estimate pooled percentage of EPDS-5 >= 7, pooled SCID major depression prevalence, and the pooled difference in prevalence. Results: A total of 3,958 participants from 19 primary studies were included. Pooled prevalence of SCID major depression was 9.2% (95% confidence interval [CI] 6.0% to 13.7%), pooled percentage of participants with EPDS-5 >= 7 was 16.2% (95% CI 10.7% to 23.8%), and pooled difference was 8.0% (95% CI 2.9% to 13.2%). In the 19 included studies, mean and median ratios of EPDS-5 to SCID prevalence were 2.1 and 1.4 times. Conclusions: Prevalence estimated based on EPDS-5 >= 7 appears to be substantially higher than the prevalence of major depression. Validated diagnostic interviews should be used to establish prevalence.

Published
2020

44. Accuracy of the PHQ-2 alone and in combination with the PHQ-9 for screening to detect major depression

Author

Levis, Brooke, Sun, Ying, He, Chen, Wu, Yin, Krishnan, Ankur, Bhandari, Parash Mani, Neupane, Dipika, Imran, Mahrukh, Brehaut, Eliana, Negeri, Zelalem, Fischer, Felix H, Benedetti, Andrea, Thombs, Brett D, Wynter, Karen, Levis, Brooke, Sun, Ying, He, Chen, Wu, Yin, Krishnan, Ankur, Bhandari, Parash Mani, Neupane, Dipika, Imran, Mahrukh, Brehaut, Eliana, Negeri, Zelalem, Fischer, Felix H, Benedetti, Andrea, Thombs, Brett D, and Wynter, Karen

Published
2020

45. Surestimation de la prévalence de la dépression du postpartum selon une version en 5 items de l’EDPE: Une revue systématique et une méta-analyse des données individuelles des participants

Author

Thombs, Brett D., Levis, Brooke, Lyubenova, Anita, Neupane, Dipika, Negeri, Zelalem, Wu, Yin, Sun, Ying, He, Chen, Krishnan, Ankur, Vigod, Simone N., Bhandari, Parash Mani, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., 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, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, Figueiredo, Barbara, Helle, Nadine, Howard, Louise M., Kohlhoff, Jane, Kozinszky, Zoltán, Leonardou, Angeliki A., Radoš, Sandra Nakić, Quispel, Chantal, Rochat, Tamsen J., Stein, Alan, Stewart, Robert C., Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Töreki, Annamária, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega-Dienstmaier, Johann M., Benedetti, Andrea, Thombs, Brett D., Levis, Brooke, Lyubenova, Anita, Neupane, Dipika, Negeri, Zelalem, Wu, Yin, Sun, Ying, He, Chen, Krishnan, Ankur, Vigod, Simone N., Bhandari, Parash Mani, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., 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, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, Figueiredo, Barbara, Helle, Nadine, Howard, Louise M., Kohlhoff, Jane, Kozinszky, Zoltán, Leonardou, Angeliki A., Radoš, Sandra Nakić, Quispel, Chantal, Rochat, Tamsen J., Stein, Alan, Stewart, Robert C., Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Töreki, Annamária, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega-Dienstmaier, Johann M., and Benedetti, Andrea

Abstract

Objective: The Maternal Mental Health in Canada, 2018/2019, survey reported that 18% of 7,085 mothers who recently gave birth reported “feelings consistent with postpartum depression” based on scores ≥7 on a 5-item version of the Edinburgh Postpartum Depression Scale (EPDS-5). The EPDS-5 was designed as a screening questionnaire, not to classify disorders or estimate prevalence; the extent to which EPDS-5 results reflect depression prevalence is unknown. We investigated EPDS-5 ≥7 performance relative to major depression prevalence based on a validated diagnostic interview, the Structured Clinical Interview for DSM (SCID). Methods: We searched Medline, Medline In-Process & Other Non-Indexed Citations, PsycINFO, and the Web of Science Core Collection through June 2016 for studies with data sets with item response data to calculate EPDS-5 scores and that used the SCID to ascertain depression status. We conducted an individual participant data meta-analysis to estimate pooled percentage of EPDS-5 ≥7, pooled SCID major depression prevalence, and the pooled difference in prevalence. Results: A total of 3,958 participants from 19 primary studies were included. Pooled prevalence of SCID major depression was 9.2% (95% confidence interval [CI] 6.0% to 13.7%), pooled percentage of participants with EPDS-5 ≥7 was 16.2% (95% CI 10.7% to 23.8%), and pooled difference was 8.0% (95% CI 2.9% to 13.2%). In the 19 included studies, mean and median ratios of EPDS-5 to SCID prevalence were 2.1 and 1.4 times. Conclusions: Prevalence estimated based on EPDS-5 ≥7 appears to be substantially higher than the prevalence of major depression. Validated diagnostic interviews should be used to establish prevalence.

Published
2020
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46. Selective cutoff reporting in studies of the accuracy of the Patient Health Questionnaire‐9 and Edinburgh Postnatal Depression Scale: Comparison of results based on published cutoffs versus all cutoffs using individual participant data meta‐analysis

Author

Neupane, Dipika, Levis, Brooke, Bhandari, Parash M., Thombs, Brett D., and Benedetti, Andrea

Subjects
*EDINBURGH Postnatal Depression Scale
Abstract

Objectives: Selectively reported results from only well‐performing cutoffs in diagnostic accuracy studies may bias estimates in meta‐analyses. We investigated cutoff reporting patterns for the Patient Health Questionnaire‐9 (PHQ‐9; standard cutoff 10) and Edinburgh Postnatal Depression Scale (EPDS; no standard cutoff, commonly used 10–13) and compared accuracy estimates based on published cutoffs versus all cutoffs. Methods: We conducted bivariate random effects meta‐analyses using individual participant data to compare accuracy from published versus all cutoffs. Results: For the PHQ‐9 (30 studies, N = 11,773), published results underestimated sensitivity for cutoffs below 10 (median difference: −0.06) and overestimated for cutoffs above 10 (median difference: 0.07). EPDS (19 studies, N = 3637) sensitivity estimates from published results were similar for cutoffs below 10 (median difference: 0.00) but higher for cutoffs above 13 (median difference: 0.14). Specificity estimates from published and all cutoffs were similar for both tools. The mean cutoff of all reported cutoffs in PHQ‐9 studies with optimal cutoff below 10 was 8.8 compared to 11.8 for those with optimal cutoffs above 10. Mean for EPDS studies with optimal cutoffs below 10 was 9.9 compared to 11.8 for those with optimal cutoffs greater than 10. Conclusion: Selective cutoff reporting was more pronounced for the PHQ‐9 than EPDS. [ABSTRACT FROM AUTHOR]

Published
2021
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47. 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

Author

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

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.

Published
2019

48. 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

Author

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

Published
2019
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49. 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

Author

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, Ruben, Alvarado-Esquivel, Cosme, Bakare, Muideen O., Barnes, Jacqueline, Tatano Beck, Cheryl, 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, Lluisa, 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, Rados, Sandra Nakic, Navarro Garcia, Purificacion, Nishi, Daisuke, E-Andjafono, Daniel Okitundu Luwa, Robertson-Blackmore, Emma, Rochat, Tamsen J., Rowe, Heather J., Siu, Bonnie W. M., Skalkidou, Alkistis, Stein, Alan, Stewart, Robert C., Su, Kuan-Pin, Sundström Poromaa, Inger, Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Thiagayson, Pavaani, Töreki, Annamaria, Torres-Gimenez, Anna, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega-Dienstmaier, Johann M., Wynter, Karen, Yonkers, Kimberly A., Benedetti, Andrea, Thombs, Brett D., 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, Ruben, Alvarado-Esquivel, Cosme, Bakare, Muideen O., Barnes, Jacqueline, Tatano Beck, Cheryl, 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, Lluisa, 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, Rados, Sandra Nakic, Navarro Garcia, Purificacion, Nishi, Daisuke, E-Andjafono, Daniel Okitundu Luwa, Robertson-Blackmore, Emma, Rochat, Tamsen J., Rowe, Heather J., Siu, Bonnie W. M., Skalkidou, Alkistis, Stein, Alan, Stewart, Robert C., Su, Kuan-Pin, Sundström Poromaa, Inger, Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Thiagayson, Pavaani, Töreki, Annamaria, Torres-Gimenez, Anna, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega-Dienstmaier, Johann M., Wynter, Karen, Yonkers, Kimberly A., Benedetti, Andrea, and Thombs, Brett D.

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.

Published
2019
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50. Accuracy of the Hospital Anxiety and Depression Scale Depression subscale (HADS-D) to screen for major depression: systematic review and individual participant data meta-analysis.

Author

Yin Wu, Levis, Brooke, Ying Sun, Chen He, Krishnan, Ankur, Neupane, Dipika, Bhandari, Parash Mani, Negeri, Zelalem, Benedetti, Andrea, and Thombs, Brett D.

Subjects
DIAGNOSIS of mental depression, PSYCHOLOGY information storage & retrieval systems, META-analysis, RESEARCH methodology evaluation, SYSTEMATIC reviews, MEDICAL screening, PSYCHOMETRICS, MEDLINE
Published
2021
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