35 results on '"Fischer, Felix H."'
Search Results
2. 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
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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.
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- 2024
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3. The CONVINCE randomized trial found positive effects on quality of life for patients with chronic kidney disease treated with hemodiafiltration
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Rose, Matthias, Fischer, Felix H., Liegl, Gregor, Strippoli, Giovanni F.M., Hockham, Carina, Vernooij, Robin W.M., Barth, Claudia, Canaud, Bernard, Covic, Adrian, Cromm, Krister, Cucui, Andrea M., Davenport, Andrew, Fischer, Kathrin I., Hegbrant, Jörgen, Jaha, Hanna, Schappert, Anna, Török, Marietta, Woodward, Mark, Bots, Michiel L., and Blankestijn, Peter J.
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- 2024
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4. Physical performance tasks were linked to the PROMIS physical function metric in patients undergoing hemodialysis
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Liegl, Gregor, Fischer, Felix H., Woodward, Mark, Török, Marietta, Strippoli, Giovanni F.M., Hegbrant, Jörgen, Davenport, Andrew, Cromm, Krister, Canaud, Bernard, Bots, Michiel L., Blankestijn, Peter J., Barth, Claudia, Fischer, Kathrin I., and Rose, Matthias
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- 2023
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5. Measuring maladaptive personality traits with the Structured Clinical Interview for DSM‐IV Axis II Screening Questionnaire using a common metrics approach.
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Krasniqi, Cameri, Müller, Steffen, Wendt, Leon P., Fischer, Felix H., Spitzer, Carsten, and Zimmermann, Johannes
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PERSONALITY disorder diagnosis ,SELF-evaluation ,MENTAL status examination ,CONCEPTUAL models ,QUESTIONNAIRES ,RESEARCH methodology evaluation ,INTERVIEWING ,RESEARCH evaluation ,CLASSIFICATION of mental disorders ,DESCRIPTIVE statistics ,MYERS-Briggs Type Indicator ,PSYCHOLOGY ,OBSESSIVE-compulsive disorder ,BIBLIOMETRICS ,RESEARCH methodology ,PSYCHOMETRICS ,PERSONALITY ,MEDICAL screening ,COMPARATIVE studies ,DATA analysis software ,THEORY ,PERSONALITY tests ,PATIENTS' attitudes - Abstract
The classification of personality disorder (PD) is undergoing a paradigm shift in which categorically defined specific PDs are being replaced by dimensionally defined maladaptive trait domains. To bridge the classificatory approaches, this study attempts to use items from the categorical PD model in DSM‐IV to measure the maladaptive trait domains described in DSM‐5 Section III/ICD‐11. A general population sample comprising 1228 participants completed the Screening Questionnaire of the Structured Clinical Interview for DSM‐IV Axis II (SCID‐II‐SQ), the Personality Inventory for DSM‐5 (PID‐5), and the anankastia scale of the Personality Inventory for ICD‐11 (PiCD). Using item response theory models and a psychometric linking technique, SCID‐II‐SQ items were evaluated for their contribution to measuring maladaptive trait domains. The best discriminating items were then selected to derive proxy scales. We found that convergent validity of these proxy scales was in a similar range to that of other self‐report measures for PD, except for the proxy scale for PiCD anankastia. However, only the proxy scale for negative affectivity showed acceptable reliability that would allow its application in research settings. Future studies should seek to establish a common metric between specific PDs and maladaptive trait domains using self‐report measures with higher specificity or semi‐structured interviews. [ABSTRACT FROM AUTHOR]
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- 2024
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6. The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression : An Individual Participant Data Meta-Analysis
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He, Chen, Levis, Brooke, Riehm, Kira E., Saadat, Nazanin, Levis, Alexander W., Azar, Marleine, Rice, Danielle B., Krishnan, Ankur, Wu, Yin, Sun, Ying, 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 Hortes Nisihara, Chan, Juliana C.N., Cholera, Rushina, Clover, Kerrie, Conwell, Yeates, de Man-van Ginkel, Janneke M., Fann, Jesse R., Fischer, Felix H., Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G., Hall, Brian J., Harrison, Patricia A., Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E., Hudson, Marie, Hyphantis, Thomas N., Inagaki, Masatoshi, Ismail, Khalida, Jetté, Nathalie, Khamseh, Mohammad E., Kiely, Kim M., Kwan, Yunxin, Lamers, Femke, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R., Löwe, Bernd, Marsh, Laura, McGuire, Anthony, Mohd-Sidik, Sherina, Munhoz, Tiago N., Muramatsu, Kumiko, Osório, Flávia L., Patel, Vikram, Pence, Brian W., Persoons, Philippe, Picardi, Angelo, Reuter, Katrin, Rooney, Alasdair G., da Silva dos Santos, Iná S., Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Stafford, Lesley, Sung, Sharon, Tan, Pei Lin Lynnette, Turner, Alyna, van Weert, Henk C.P.M., White, Jennifer, Whooley, Mary A., Winkley, Kirsty, Yamada, Mitsuhiko, Thombs, Brett D., and Benedetti, Andrea
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- 2020
7. Depression prevalence using the HADS-D compared to SCID major depression classification: An individual participant data meta-analysis
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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.
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- 2020
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8. Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis
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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.
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- 2020
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9. 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
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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.
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- 2020
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10. Physical performance tasks were linked to the PROMIS physical function metric in patients undergoing hemodialysis
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Cardiovasculaire Epi Team 5, Cardiovasculaire Epidemiologie, Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Nefro Vasculaire Geneeskunde, Liegl, Gregor, Fischer, Felix H, Woodward, Mark, Török, Marietta, Strippoli, Giovanni F M, Hegbrant, Jörgen, Davenport, Andrew, Cromm, Krister, Canaud, Bernard, Bots, Michiel L, Blankestijn, Peter J, Barth, Claudia, Fischer, Kathrin I, Rose, Matthias, Cardiovasculaire Epi Team 5, Cardiovasculaire Epidemiologie, Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Nefro Vasculaire Geneeskunde, Liegl, Gregor, Fischer, Felix H, Woodward, Mark, Török, Marietta, Strippoli, Giovanni F M, Hegbrant, Jörgen, Davenport, Andrew, Cromm, Krister, Canaud, Bernard, Bots, Michiel L, Blankestijn, Peter J, Barth, Claudia, Fischer, Kathrin I, and Rose, Matthias
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- 2023
11. Accuracy of the Patient Health Questionnaire-9 for screening to detect major depression: updated systematic review and individual participant data meta-analysis
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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
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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.
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- 2021
12. Differential item functioning of PROMIS physical functioning ceiling items across Argentina, Germany, and the U.S
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Plessen, Constantin Yves, Hartmann, Claudia, Heng, Marilyn, Pesantez, Rodrigo, Fischer, Felix H, and Rose, Matthias
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- 2021
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13. Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis
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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
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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.
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- 2020
14. The Accuracy of the Patient Health Questionnaire-9 (PHQ-9) Algorithm for Screening to Detect Major Depression : An Individual Participant Data Meta-analysis
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He, Chen, Levis, Brooke, Riehm, Kira E, Saadat, Nazanin, Levis, Alexander W, Azar, Marleine, Rice, Danielle B, Krishnan, Ankur, Wu, Yin, Sun, Ying, 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 L, Chagas, Marcos H, Chan, Juliana C N, Cholera, Rushina, Clover, Kerrie, Conwell, Yeates, de Man-van Ginkel, Janneke M, Fann, Jesse R, Fischer, Felix H, Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G, Hall, Brian J, Harrison, Patricia A, Härter, Martin, Thombs, Brett D, and Benedetti, Andrea
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- 2020
15. Erratum: Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: A systematic review and individual participant data meta-analysis (Journal of Physical Chemistry (2019) DOI: 10.1017/S0033291719001314)
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Wu, Yin, Levis, Brooke, Riehm, Kira E., Saadat, Nazanin, Levis, Alexander W., Azar, Marleine, Rice, Danielle B., 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, Bombardier, Charles H., Butterworth, Peter, Carter, Gregory, Chagas, Marcos H., Chan, Juliana C. N., Cholera, Rushina, Conwell, Yeates, de Manvan Ginkel, Janneke M., Fann, Jesse R., Fischer, Felix H., Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G., Hall, Brian J., Harrison, Patricia A., Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E., Hudson, Marie, Hyphantis, Thomas, Inagaki, Masatoshi, Jetté, Nathalie, Khamseh, Mohammad E., Kiely, Kim M., Kwan, Yunxin, Lamers, Femke, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R., Löwe, Bernd, McGuire, Anthony, Mohd-Sidik, Sherina, Munhoz, Tiago N., Muramatsu, Kumiko, Osório, Flávia L., Patel, Vikram, Pence, Brian W., Persoons, Philippe, Picardi, Angelo, Reuter, Katrin, Rooney, Alasdair G., Santos, Iná S., Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Stafford, Lesley, Sung, Sharon, Tan, Pei Lin Lynnette, Turner, Alyna, van Weert, Henk C., White, Jennifer, Whooley, Mary A., Winkley, Kirsty, Yamada, Mitsuhiko, Benedetti, Andrea, and Thombs, Brett D.
- Abstract
This article was published in Psychological Medicine with incorrect author information. MD Inagaki should be Masatoshi Inagaki and MD Stafford should be Lesley Stafford. This has since been updated as per the above.
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- 2020
16. Accuracy of the PHQ-2 alone and in combination with the PHQ-9 for screening to detect major depression
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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
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- 2020
17. The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis
- Author
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Verplegingswetenschap, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Brain, He, Chen, Levis, Brooke, Riehm, Kira E, Saadat, Nazanin, Levis, Alexander W, Azar, Marleine, Rice, Danielle B, Krishnan, Ankur, Wu, Yin, Sun, Ying, 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 Hortes Nisihara, Chan, Juliana C N, Cholera, Rushina, Clover, Kerrie, Conwell, Yeates, de Man-van Ginkel, Janneke M, Fann, Jesse R, Fischer, Felix H, Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G, Hall, Brian J, Harrison, Patricia A, Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E, Hudson, Marie, Hyphantis, Thomas N, Inagaki, Masatoshi, Ismail, Khalida, Jetté, Nathalie, Khamseh, Mohammad E, Kiely, Kim M, Kwan, Yunxin, Lamers, Femke, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R, Löwe, Bernd, Marsh, Laura, McGuire, Anthony, Mohd-Sidik, Sherina, Munhoz, Tiago N, Muramatsu, Kumiko, Osório, Flávia L, Patel, Vikram, Pence, Brian W, Persoons, Philippe, Picardi, Angelo, Reuter, Katrin, Rooney, Alasdair G, da Silva Dos Santos, Iná S, Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Stafford, Lesley, Sung, Sharon, Tan, Pei Lin Lynnette, Turner, Alyna, van Weert, Henk C P M, White, Jennifer, Whooley, Mary A, Winkley, Kirsty, Yamada, Mitsuhiko, Thombs, Brett D, Benedetti, Andrea, Verplegingswetenschap, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Brain, He, Chen, Levis, Brooke, Riehm, Kira E, Saadat, Nazanin, Levis, Alexander W, Azar, Marleine, Rice, Danielle B, Krishnan, Ankur, Wu, Yin, Sun, Ying, 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 Hortes Nisihara, Chan, Juliana C N, Cholera, Rushina, Clover, Kerrie, Conwell, Yeates, de Man-van Ginkel, Janneke M, Fann, Jesse R, Fischer, Felix H, Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G, Hall, Brian J, Harrison, Patricia A, Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E, Hudson, Marie, Hyphantis, Thomas N, Inagaki, Masatoshi, Ismail, Khalida, Jetté, Nathalie, Khamseh, Mohammad E, Kiely, Kim M, Kwan, Yunxin, Lamers, Femke, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R, Löwe, Bernd, Marsh, Laura, McGuire, Anthony, Mohd-Sidik, Sherina, Munhoz, Tiago N, Muramatsu, Kumiko, Osório, Flávia L, Patel, Vikram, Pence, Brian W, Persoons, Philippe, Picardi, Angelo, Reuter, Katrin, Rooney, Alasdair G, da Silva Dos Santos, Iná S, Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Stafford, Lesley, Sung, Sharon, Tan, Pei Lin Lynnette, Turner, Alyna, van Weert, Henk C P M, White, Jennifer, Whooley, Mary A, Winkley, Kirsty, Yamada, Mitsuhiko, Thombs, Brett D, and Benedetti, Andrea
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- 2020
18. Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis
- Author
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Verplegingswetenschap, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Wu, Yin, Levis, Brooke, Riehm, Kira E, Saadat, Nazanin, Levis, Alexander W, Azar, Marleine, Rice, Danielle B, 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, Bombardier, Charles H, Butterworth, Peter, Carter, Gregory, Chagas, Marcos H, Chan, Juliana C N, Cholera, Rushina, Conwell, Yeates, de Man-van Ginkel, Janneke M, Fann, Jesse R, Fischer, Felix H, Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G, Hall, Brian J, Harrison, Patricia A, Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E, Hudson, Marie, Hyphantis, Thomas, Inagaki, M D, Jetté, Nathalie, Khamseh, Mohammad E, Kiely, Kim M, Kwan, Yunxin, Lamers, Femke, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R, Löwe, Bernd, McGuire, Anthony, Mohd-Sidik, Sherina, Munhoz, Tiago N, Muramatsu, Kumiko, Osório, Flávia L, Patel, Vikram, Pence, Brian W, Persoons, Philippe, Picardi, Angelo, Reuter, Katrin, Rooney, Alasdair G, Santos, Iná S, Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Stafford, M D, Sung, Sharon, Tan, Pei Lin Lynnette, Turner, Alyna, van Weert, Henk C, White, Jennifer, Whooley, Mary A, Winkley, Kirsty, Yamada, Mitsuhiko, Benedetti, Andrea, Thombs, Brett D, Verplegingswetenschap, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Wu, Yin, Levis, Brooke, Riehm, Kira E, Saadat, Nazanin, Levis, Alexander W, Azar, Marleine, Rice, Danielle B, 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, Bombardier, Charles H, Butterworth, Peter, Carter, Gregory, Chagas, Marcos H, Chan, Juliana C N, Cholera, Rushina, Conwell, Yeates, de Man-van Ginkel, Janneke M, Fann, Jesse R, Fischer, Felix H, Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G, Hall, Brian J, Harrison, Patricia A, Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E, Hudson, Marie, Hyphantis, Thomas, Inagaki, M D, Jetté, Nathalie, Khamseh, Mohammad E, Kiely, Kim M, Kwan, Yunxin, Lamers, Femke, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R, Löwe, Bernd, McGuire, Anthony, Mohd-Sidik, Sherina, Munhoz, Tiago N, Muramatsu, Kumiko, Osório, Flávia L, Patel, Vikram, Pence, Brian W, Persoons, Philippe, Picardi, Angelo, Reuter, Katrin, Rooney, Alasdair G, Santos, Iná S, Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Stafford, M D, Sung, Sharon, Tan, Pei Lin Lynnette, Turner, Alyna, van Weert, Henk C, White, Jennifer, Whooley, Mary A, Winkley, Kirsty, Yamada, Mitsuhiko, Benedetti, Andrea, and Thombs, Brett D
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- 2020
19. Trajectories of Health-Related Quality of Life and HbA1c Values of Children and Adolescents With Diabetes Mellitus Type 1 Over 6 Months: A Longitudinal Observational Study
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Fischer, Kathrin I., Fischer, Felix H., Barthel, Dana, Otto, Christiane, Thyen, Ute, Klein, Marcus, Walter, Otto, Ravens-Sieberer, Ulrike, Rose, Matthias, and Nolte, Sandra
- Subjects
diabetes mellitus type 1 ,endocrine system diseases ,pediatrics ,nutritional and metabolic diseases ,self-report ,humanities ,health-related quality of life ,computer-adaptive testing ,Pediatrics, Perinatology and Child Health ,human activities ,patient outcome assessments ,600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit ,Original Research - Abstract
Introduction: To achieve optimized blood glucose concentrations (assessed by HbA1c) and high health-related quality of life (HRQL), children and adolescents with diabetes mellitus type 1 (T1DM) must follow strict disease management strategies. This study aims to investigate HRQL of children and adolescents with T1DM and its association with HbA1c values over the course of 6 months. Methods: Patients aged 7-17 years (n = 203) with T1DM provided HRQL data on a monthly basis. HRQL was measured using the Kids-CAT, a computer-adaptive test (CAT) comprising five generic HRQL domains. HbA1c concentrations were assessed at baseline, at 3 and 6 months. We explored the trajectory of HRQL at the domain level using linear mixed effects models. Further, we investigated the association between HRQL and HbA1c concentrations over time using path analysis models. Results: Children and adolescents with T1DM reported high scores across all HRQL domains over time. However, those with an HbA1c concentrations of >9.0% reported significantly lower scores in physical well-being and parent relations compared with those with an HbA1c concentration of 9.0% reported lower scores in selected HRQL domains. Thus, special attention should be drawn to HRQL of children and adolescents with higher HbA1c concentrations. The minimal relationship between HbA1c and HRQL indicates that the two therapy goals, i.e., achievement and maintenance of glycemic targets and high HRQL, should be considered and evaluated independently in clinical routine. Trial Registration: DRKS00006326 (German Clinical Trial Register), date of registration: August 1st, 2014.
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- 2019
20. How to compare scores from different depression scales: equating the Patient Health Questionnaire (PHQ) and the ICD-10-Symptom Rating (ISR) using Item Response Theory
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Fischer, Felix H., Tritt, Karin, Klapp, Burghard F., and Fliege, Herbert
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- 2011
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21. Trajectories of Health-Related Quality of Life and HbA1c Values of Children and Adolescents With Diabetes Mellitus Type 1 Over 6 Months: A Longitudinal Observational Study
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Fischer, Kathrin I., primary, Fischer, Felix H., additional, Barthel, Dana, additional, Otto, Christiane, additional, Thyen, Ute, additional, Klein, Marcus, additional, Walter, Otto, additional, Ravens-Sieberer, Ulrike, additional, Rose, Matthias, additional, and Nolte, Sandra, additional
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- 2020
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22. The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis
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He, Chen, primary, Levis, Brooke, additional, Riehm, Kira E., additional, Saadat, Nazanin, additional, Levis, Alexander W., additional, Azar, Marleine, additional, Rice, Danielle B., additional, Krishnan, Ankur, additional, Wu, Yin, additional, Sun, Ying, additional, Imran, Mahrukh, additional, Boruff, Jill, additional, Cuijpers, Pim, additional, Gilbody, Simon, additional, Ioannidis, John P.A., additional, Kloda, Lorie A., additional, McMillan, Dean, additional, Patten, Scott B., additional, Shrier, Ian, additional, Ziegelstein, Roy C., additional, Akena, Dickens H., additional, Arroll, Bruce, additional, Ayalon, Liat, additional, Baradaran, Hamid R., additional, Baron, Murray, additional, Beraldi, Anna, additional, Bombardier, Charles H., additional, Butterworth, Peter, additional, Carter, Gregory, additional, Chagas, Marcos Hortes Nisihara, additional, Chan, Juliana C.N., additional, Cholera, Rushina, additional, Clover, Kerrie, additional, Conwell, Yeates, additional, de Man-van Ginkel, Janneke M., additional, Fann, Jesse R., additional, Fischer, Felix H., additional, Fung, Daniel, additional, Gelaye, Bizu , additional, Goodyear-Smith, Felicity, additional, Greeno, Catherine G., additional, Hall, Brian J., additional, Harrison, Patricia A., additional, Härter, Martin, additional, Hegerl, Ulrich, additional, Hides, Leanne, additional, Hobfoll, Stevan E., additional, Hudson, Marie, additional, Hyphantis, Thomas N., additional, Inagaki, Masatoshi, additional, Ismail, Khalida, additional, Jetté, Nathalie, additional, Khamseh, Mohammad E., additional, Kiely, Kim M., additional, Kwan, Yunxin, additional, Lamers, Femke, additional, Liu, Shen-Ing, additional, Lotrakul, Manote, additional, Loureiro, Sonia R., additional, Löwe, Bernd, additional, Marsh, Laura, additional, McGuire, Anthony, additional, Mohd-Sidik, Sherina, additional, Munhoz, Tiago N., additional, Muramatsu, Kumiko, additional, Osório, Flávia L., additional, Patel, Vikram, additional, Pence, Brian W., additional, Persoons, Philippe, additional, Picardi, Angelo, additional, Reuter, Katrin, additional, Rooney, Alasdair G., additional, da Silva dos Santos, Iná S., additional, Shaaban, Juwita, additional, Sidebottom, Abbey, additional, Simning, Adam, additional, Stafford, Lesley, additional, Sung, Sharon, additional, Tan, Pei Lin Lynnette, additional, Turner, Alyna, additional, van Weert, Henk C.P.M., additional, White, Jennifer, additional, Whooley, Mary A., additional, Winkley, Kirsty, additional, Yamada, Mitsuhiko, additional, Thombs, Brett D., additional, and Benedetti, Andrea, additional
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- 2019
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23. Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression : individual participant data meta-analysis
- Author
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Akena, Dickens, Arroll, Bruce, Ayalon, Liat, Azar, Marleine, Baradaran, Hamid R, Baron, Murray, Benedetti, Andrea, Bombardier, Charles H, Boruff, Jill, Butterworth, Peter, Carter, Gregory, Chagas, Marcos H, Chan, Juliana C N, Chiovitti, Matthew J, Clover, Kerrie, Conwell, Yeates, Cuijpers, Pim, de Man-van Ginkel, Janneke M, Delgadillo, Jaime, Fann, Jesse R, Fischer, Felix H, Fung, Daniel, Gelaye, Bizu, Gilbody, Simon, Goodyear-Smith, Felicity, Greeno, Catherine G, Hall, Brian J, Hambridge, John, Harrison, Patricia A, Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E, Hudson, Marie, Inagaki, Masatoshi, Ioannidis, John P.A., Ismail, Khalida, Jetté, Nathalie, Khamseh, Mohammad E, Kiely, Kim M, Kloda, Lorie A, Kwan, Yunxin, Levis, Alexander W, Levis, Brooke, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R, Löwe, Bernd, Marsh, Laura, McGuire, Anthony, McMillan, Dean, Mohd Sidik, Sherina, Munhoz, Tiago N, Muramatsu, Kumiko, Osório, Flávia L, Patel, Vikram, Patten, Scott B, Pence, Brian W, Persoons, Philippe, Picardi, Angelo, Rice, Danielle B, Riehm, Kira E, Reuter, Katrin, Rooney, Alasdair G, Saadat, Nazanin, Sanchez, Tatiana A, Santos, Iná S, Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Shrier, Ian, Stafford, Lesley, Sung, Sharon C, Tan, Pei Lin Lynnette, Thombs, Brett D, Turner, Alyna, Van Der Feltz-Cornelis, Christina Maria, van Weert, Henk C P M, Vöhringer, Paul A, White, Jennifer, Whooley, Mary A, Winkley, Kirsty, Yamada, Mitsuhiko, Ziegelstein, Roy C, and Zhang, Yuying
- Abstract
OBJECTIVE: To determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression. DESIGN: Individual participant data meta-analysis. DATA SOURCES: Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-February 2015). INCLUSION CRITERIA: Eligible studies compared PHQ-9 scores with major depression diagnoses from validated diagnostic interviews. Primary study data and study level data extracted from primary reports were synthesized. For PHQ-9 cut-off scores 5-15, bivariate random effects meta-analysis was used to estimate pooled sensitivity and specificity, separately, among studies that used semistructured diagnostic interviews, which are designed for administration by clinicians; fully structured interviews, which are designed for lay administration; and the Mini International Neuropsychiatric (MINI) diagnostic interviews, a brief fully structured interview. Sensitivity and specificity were examined among participant subgroups and, separately, using meta-regression, considering all subgroup variables in a single model. RESULTS: Data were obtained for 58 of 72 eligible studies (total n=17 357; major depression cases n=2312). Combined sensitivity and specificity was maximized at a cut-off score of 10 or above among studies using a semistructured interview (29 studies, 6725 participants; sensitivity 0.88, 95% confidence interval 0.83 to 0.92; specificity 0.85, 0.82 to 0.88). Across cut-off scores 5-15, sensitivity with semistructured interviews was 5-22% higher than for fully structured interviews (MINI excluded; 14 studies, 7680 participants) and 2-15% higher than for the MINI (15 studies, 2952 participants). Specificity was similar across diagnostic interviews. The PHQ-9 seems to be similarly sensitive but may be less specific for younger patients than for older patients; a cut-off score of 10 or above can be used regardless of age.. CONCLUSIONS: PHQ-9 sensitivity compared with semistructured diagnostic interviews was greater than in previous conventional meta-analyses that combined reference standards. A cut-off score of 10 or above maximized combined sensitivity and specificity overall and for subgroups. REGISTRATION: PROSPERO CRD42014010673.
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- 2019
24. Comparison of the Factor Structure of the Patient Health Questionnaire for Somatic Symptoms (PHQ-15) in Germany, the Netherlands, and China. A Transcultural Structural Equation Modeling (SEM) Study
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Leonhart, R., de Vroege, Lars, Schaefert, Rainer, Nolte, Sandra, Fischer, Felix H, Fritzsche, K., van der Feltz-Cornelis, C.M., Zhang, Lan, Liu, Yang, Dong, Zaiquan, Geestelijke Gezondheidszorg, and Tranzo, Scientific center for care and wellbeing
- Subjects
GENERAL-POPULATION ,SOMATOFORM DISORDERS ,Psychiatry ,ANXIETY DISORDERS ,PRIMARY-CARE PATIENTS ,PHYSICAL SYMPTOMS ,RANDOMIZED CONTROLLED-TRIAL ,DEPRESSION ,patient health questionnaire-15 ,structural equation modeling (SEM) ,VALIDATION ,factor structure ,Psychiatry and Mental health ,PSYCHOMETRIC PROPERTIES ,HONG-KONG ,somatic symptoms ,transcultural ,Original Research - Abstract
Background: Persistent somatic symptoms are associated with psychological distress, impaired function, and medical help-seeking behavior. The Patient Health Questionnaire (PHQ)-15 is used as a screening instrument for somatization and as a monitoring instrument for somatic symptom severity. A bifactorial model has been described, with one general factor and four orthogonal specific symptom factors. The objective of the present study was to assess and to clarify the factor structure of the PHQ-15 within and between different countries in Western Europe and China. Method: Cross-sectional secondary data analysis performed in three patient data samples from two Western European countries (Germany N = 2,517, the Netherlands N = 456) and from China (N = 1,329). Confirmatory factor analyses (CFA), and structural equation modeling (SEM) analysis were performed. Results: The general factor is found in every sample. However, although the outcomes of the PHQ-15 estimate severity of somatic symptoms in different facets, these subscales may have different meanings in the European and Chinese setting. Replication of the factorial structure was possible in the German and Dutch datasets but not in the dataset from China. For the Chinese dataset, a bifactorial model with a different structure for the cardiopulmonary factor is suggested. The PHQ-15 could discern somatization from anxiety and depression within the three samples. Conclusion: The PHQ-15 is a valid questionnaire that can discern somatization from anxiety and depression within different cultures like Europe or China. It can be fitted to a bifactorial model for categorical data, however, the model can only be recommended for use of the general factor. Application of the orthogonal subscales in non-European samples is not corroborated by the results. The differences cannot be ascribed to differences in health care settings or by differences in concomitant depression or anxiety but instead, a cultural factor involving concepts of disease may play a role in this as they may play a role in the translation of the questionnaire. Further research is needed to explore this, and replication studies are needed regarding the factorial structure of the PHQ-15 in China.
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- 2018
25. Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis – ERRATUM
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Wu, Yin, primary, Levis, Brooke, additional, Riehm, Kira E., additional, Saadat, Nazanin, additional, Levis, Alexander W., additional, Azar, Marleine, additional, Rice, Danielle B., additional, Boruff, Jill, additional, Cuijpers, Pim, additional, Gilbody, Simon, additional, Ioannidis, John P.A., additional, Kloda, Lorie A., additional, McMillan, Dean, additional, Patten, Scott B., additional, Shrier, Ian, additional, Ziegelstein, Roy C., additional, Akena, Dickens H., additional, Arroll, Bruce, additional, Ayalon, Liat, additional, Baradaran, Hamid R., additional, Baron, Murray, additional, Bombardier, Charles H., additional, Butterworth, Peter, additional, Carter, Gregory, additional, Chagas, Marcos H., additional, Chan, Juliana C. N., additional, Cholera, Rushina, additional, Conwell, Yeates, additional, de Manvan Ginkel, Janneke M., additional, Fann, Jesse R., additional, Fischer, Felix H., additional, Fung, Daniel, additional, Gelaye, Bizu, additional, Goodyear-Smith, Felicity, additional, Greeno, Catherine G., additional, Hall, Brian J., additional, Harrison, Patricia A., additional, Härter, Martin, additional, Hegerl, Ulrich, additional, Hides, Leanne, additional, Hobfoll, Stevan E., additional, Hudson, Marie, additional, Hyphantis, Thomas, additional, Inagaki, Masatoshi, additional, Jetté, Nathalie, additional, Khamseh, Mohammad E., additional, Kiely, Kim M., additional, Kwan, Yunxin, additional, Lamers, Femke, additional, Liu, Shen-Ing, additional, Lotrakul, Manote, additional, Loureiro, Sonia R., additional, Löwe, Bernd, additional, McGuire, Anthony, additional, Mohd-Sidik, Sherina, additional, Munhoz, Tiago N., additional, Muramatsu, Kumiko, additional, Osório, Flávia L., additional, Patel, Vikram, additional, Pence, Brian W., additional, Persoons, Philippe, additional, Picardi, Angelo, additional, Reuter, Katrin, additional, Rooney, Alasdair G., additional, Santos, Iná S., additional, Shaaban, Juwita, additional, Sidebottom, Abbey, additional, Simning, Adam, additional, Stafford, Lesley, additional, Sung, Sharon, additional, Tan, Pei Lin Lynnette, additional, Turner, Alyna, additional, van Weert, Henk C., additional, White, Jennifer, additional, Whooley, Mary A., additional, Winkley, Kirsty, additional, Yamada, Mitsuhiko, additional, Benedetti, Andrea, additional, and Thombs, Brett D., additional
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- 2019
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26. Probability of major depression diagnostic classification using semi-structured versus fully structured diagnostic interviews
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Levis, Brooke, Benedetti, Andrea, Riehm, Kira E., Saadat, Nazanin, Levis, Alexander W., Azar, Marleine, Rice, Danielle B., Chiovitti, Matthew J., Sanchez, Tatiana A., Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P.A., Kloda, Lorie A., McMillan, Dean, Patten, Scott B., Shrier, Ian, Steele, Russell J., 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, de Man-van Ginkel, Janneke M., Delgadillo, Jaime, Fann, Jesse R., Fischer, Felix H., Fischler, Benjamin, Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G., Hall, Brian J., Hambridge, John, Harrison, Patricia A., Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E., Hudson, Marie, Hyphantis, Thomas, Inagaki, Masatoshi, Ismail, Khalida, Jetté, Nathalie, Khamseh, Mohammad E., Kiely, Kim M., Lamers, Femke, Liu, Shen Ing, Lotrakul, Manote, Loureiro, Sonia R., Löwe, Bernd, Marsh, Laura, McGuire, Anthony, Mohd Sidik, Sherina, Munhoz, Tiago N., Muramatsu, Kumiko, Osório, Flávia L., Patel, Vikram, Pence, Brian W., Persoons, Philippe, Picardi, Angelo, Rooney, Alasdair G., Santos, Iná S., Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Stafford, Lesley, Sung, Sharon, Tan, Pei Lin Lynnette, Turner, Alyna, van der Feltz-Cornelis, Christina M., van Weert, Henk C., Vöhringer, Paul A., White, Jennifer, Whooley, Mary A., Winkley, Kirsty, Yamada, Mitsuhiko, Zhang, Yuying, Thombs, Brett D., Levis, Brooke, Benedetti, Andrea, Riehm, Kira E., Saadat, Nazanin, Levis, Alexander W., Azar, Marleine, Rice, Danielle B., Chiovitti, Matthew J., Sanchez, Tatiana A., Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P.A., Kloda, Lorie A., McMillan, Dean, Patten, Scott B., Shrier, Ian, Steele, Russell J., 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, de Man-van Ginkel, Janneke M., Delgadillo, Jaime, Fann, Jesse R., Fischer, Felix H., Fischler, Benjamin, Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G., Hall, Brian J., Hambridge, John, Harrison, Patricia A., Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E., Hudson, Marie, Hyphantis, Thomas, Inagaki, Masatoshi, Ismail, Khalida, Jetté, Nathalie, Khamseh, Mohammad E., Kiely, Kim M., Lamers, Femke, Liu, Shen Ing, Lotrakul, Manote, Loureiro, Sonia R., Löwe, Bernd, Marsh, Laura, McGuire, Anthony, Mohd Sidik, Sherina, Munhoz, Tiago N., Muramatsu, Kumiko, Osório, Flávia L., Patel, Vikram, Pence, Brian W., Persoons, Philippe, Picardi, Angelo, Rooney, Alasdair G., Santos, Iná S., Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Stafford, Lesley, Sung, Sharon, Tan, Pei Lin Lynnette, Turner, Alyna, van der Feltz-Cornelis, Christina M., van Weert, Henk C., Vöhringer, Paul A., White, Jennifer, Whooley, Mary A., Winkley, Kirsty, Yamada, Mitsuhiko, Zhang, Yuying, and Thombs, Brett D.
- Abstract
BACKGROUND: Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.AimsTo evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics. METHOD: Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit. RESULTS: A total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15-3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98-10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7-15) (OR = 0.96; 95% CI = 0.56-1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26-0.97). CONCLUSIONS: The MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.Declaration of interestDrs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the I
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- 2018
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27. Probability of major depression diagnostic classification using semi-structured versus fully structured diagnostic interviews
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Verplegingswetenschap, Brain, Levis, Brooke, Benedetti, Andrea, Riehm, Kira E., Saadat, Nazanin, Levis, Alexander W., Azar, Marleine, Rice, Danielle B., Chiovitti, Matthew J., Sanchez, Tatiana A., Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P.A., Kloda, Lorie A., McMillan, Dean, Patten, Scott B., Shrier, Ian, Steele, Russell J., 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, de Man-van Ginkel, Janneke M., Delgadillo, Jaime, Fann, Jesse R., Fischer, Felix H., Fischler, Benjamin, Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G., Hall, Brian J., Hambridge, John, Harrison, Patricia A., Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E., Hudson, Marie, Hyphantis, Thomas, Verplegingswetenschap, Brain, Levis, Brooke, Benedetti, Andrea, Riehm, Kira E., Saadat, Nazanin, Levis, Alexander W., Azar, Marleine, Rice, Danielle B., Chiovitti, Matthew J., Sanchez, Tatiana A., Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P.A., Kloda, Lorie A., McMillan, Dean, Patten, Scott B., Shrier, Ian, Steele, Russell J., 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, de Man-van Ginkel, Janneke M., Delgadillo, Jaime, Fann, Jesse R., Fischer, Felix H., Fischler, Benjamin, Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G., Hall, Brian J., Hambridge, John, Harrison, Patricia A., Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E., Hudson, Marie, and Hyphantis, Thomas
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- 2018
28. Accuracy of the PHQ-2 Alone and in Combination With the PHQ-9 for Screening to Detect Major Depression: Systematic Review and Meta-analysis.
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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., Depression Screening Data (DEPRESSD) PHQ Collaboration, Che, Liying, Levis, Alexander, Riehm, Kira, Saadat, Nazanin, Azar, Marleine, and Rice, Danielle
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DIAGNOSIS of mental depression ,META-analysis ,SYSTEMATIC reviews ,MEDICAL screening ,INTERVIEWING ,MENTAL depression ,RESEARCH funding ,RECEIVER operating characteristic curves - Abstract
Importance: The Patient Health Questionnaire depression module (PHQ-9) is a 9-item self-administered instrument used for detecting depression and assessing severity of depression. The Patient Health Questionnaire-2 (PHQ-2) consists of the first 2 items of the PHQ-9 (which assess the frequency of depressed mood and anhedonia) and can be used as a first step to identify patients for evaluation with the full PHQ-9.Objective: To estimate PHQ-2 accuracy alone and combined with the PHQ-9 for detecting major depression.Data Sources: MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-May 2018).Study Selection: Eligible data sets compared PHQ-2 scores with major depression diagnoses from a validated diagnostic interview.Data Extraction and Synthesis: Individual participant data were synthesized with bivariate random-effects meta-analysis to estimate pooled sensitivity and specificity of the PHQ-2 alone among studies using semistructured, fully structured, or Mini International Neuropsychiatric Interview (MINI) diagnostic interviews separately and in combination with the PHQ-9 vs the PHQ-9 alone for studies that used semistructured interviews. The PHQ-2 score ranges from 0 to 6, and the PHQ-9 score ranges from 0 to 27.Results: Individual participant data were obtained from 100 of 136 eligible studies (44 318 participants; 4572 with major depression [10%]; mean [SD] age, 49 [17] years; 59% female). Among studies that used semistructured interviews, PHQ-2 sensitivity and specificity (95% CI) were 0.91 (0.88-0.94) and 0.67 (0.64-0.71) for cutoff scores of 2 or greater and 0.72 (0.67-0.77) and 0.85 (0.83-0.87) for cutoff scores of 3 or greater. Sensitivity was significantly greater for semistructured vs fully structured interviews. Specificity was not significantly different across the types of interviews. The area under the receiver operating characteristic curve was 0.88 (0.86-0.89) for semistructured interviews, 0.82 (0.81-0.84) for fully structured interviews, and 0.87 (0.85-0.88) for the MINI. There were no significant subgroup differences. For semistructured interviews, sensitivity for PHQ-2 scores of 2 or greater followed by PHQ-9 scores of 10 or greater (0.82 [0.76-0.86]) was not significantly different than PHQ-9 scores of 10 or greater alone (0.86 [0.80-0.90]); specificity for the combination was significantly but minimally higher (0.87 [0.84-0.89] vs 0.85 [0.82-0.87]). The area under the curve was 0.90 (0.89-0.91). The combination was estimated to reduce the number of participants needing to complete the full PHQ-9 by 57% (56%-58%).Conclusions and Relevance: In an individual participant data meta-analysis of studies that compared PHQ scores with major depression diagnoses, the combination of PHQ-2 (with cutoff ≥2) followed by PHQ-9 (with cutoff ≥10) had similar sensitivity but higher specificity compared with PHQ-9 cutoff scores of 10 or greater alone. Further research is needed to understand the clinical and research value of this combined approach to screening. [ABSTRACT FROM AUTHOR]- Published
- 2020
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29. Probability of major depression diagnostic classification using semi-structured versus fully structured diagnostic interviews
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Levis, Brooke, primary, Benedetti, Andrea, additional, Riehm, Kira E., additional, Saadat, Nazanin, additional, Levis, Alexander W., additional, Azar, Marleine, additional, Rice, Danielle B., additional, Chiovitti, Matthew J., additional, Sanchez, Tatiana A., additional, Cuijpers, Pim, additional, Gilbody, Simon, additional, Ioannidis, John P. A., additional, Kloda, Lorie A., additional, McMillan, Dean, additional, Patten, Scott B., additional, Shrier, Ian, additional, Steele, Russell J., additional, Ziegelstein, Roy C., additional, Akena, Dickens H., additional, Arroll, Bruce, additional, Ayalon, Liat, additional, Baradaran, Hamid R., additional, Baron, Murray, additional, Beraldi, Anna, additional, Bombardier, Charles H., additional, Butterworth, Peter, additional, Carter, Gregory, additional, Chagas, Marcos H., additional, Chan, Juliana C. N., additional, Cholera, Rushina, additional, Chowdhary, Neerja, additional, Clover, Kerrie, additional, Conwell, Yeates, additional, de Man-van Ginkel, Janneke M., additional, Delgadillo, Jaime, additional, Fann, Jesse R., additional, Fischer, Felix H., additional, Fischler, Benjamin, additional, Fung, Daniel, additional, Gelaye, Bizu, additional, Goodyear-Smith, Felicity, additional, Greeno, Catherine G., additional, Hall, Brian J., additional, Hambridge, John, additional, Harrison, Patricia A., additional, Hegerl, Ulrich, additional, Hides, Leanne, additional, Hobfoll, Stevan E., additional, Hudson, Marie, additional, Hyphantis, Thomas, additional, Inagaki, Masatoshi, additional, Ismail, Khalida, additional, Jetté, Nathalie, additional, Khamseh, Mohammad E., additional, Kiely, Kim M., additional, Lamers, Femke, additional, Liu, Shen-Ing, additional, Lotrakul, Manote, additional, Loureiro, Sonia R., additional, Löwe, Bernd, additional, Marsh, Laura, additional, McGuire, Anthony, additional, Mohd Sidik, Sherina, additional, Munhoz, Tiago N., additional, Muramatsu, Kumiko, additional, Osório, Flávia L., additional, Patel, Vikram, additional, Pence, Brian W., additional, Persoons, Philippe, additional, Picardi, Angelo, additional, Rooney, Alasdair G., additional, Santos, Iná S., additional, Shaaban, Juwita, additional, Sidebottom, Abbey, additional, Simning, Adam, additional, Stafford, Lesley, additional, Sung, Sharon, additional, Tan, Pei Lin Lynnette, additional, Turner, Alyna, additional, van der Feltz-Cornelis, Christina M., additional, van Weert, Henk C., additional, Vöhringer, Paul A., additional, White, Jennifer, additional, Whooley, Mary A., additional, Winkley, Kirsty, additional, Yamada, Mitsuhiko, additional, Zhang, Yuying, additional, and Thombs, Brett D., additional
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- 2018
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30. High prevalence but limited evidence in complementary and alternative medicine: guidelines for future research
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Fischer, Felix H, Lewith, George, Witt, Claudia M, Linde, Klaus, von Ammon, Klaus, Cardini, Francesco, Falkenberg, Torkel, Fønnebø, Vinjar, Johannessen, Helle, Reiter, Bettina, Uehleke, Bernhard, Weidenhammer, Wolfgang, Brinkhaus, Benno, Fischer, Felix H, Lewith, George, Witt, Claudia M, Linde, Klaus, von Ammon, Klaus, Cardini, Francesco, Falkenberg, Torkel, Fønnebø, Vinjar, Johannessen, Helle, Reiter, Bettina, Uehleke, Bernhard, Weidenhammer, Wolfgang, and Brinkhaus, Benno
- Abstract
The use of complementary and alternative Medicine (CAM) has increased over the past two decades in Europe. Nonetheless, research investigating the evidence to support its use remains limited. The CAMbrella project funded by the European Commission aimed to develop a strategic research agenda starting by systematically evaluating the state of CAM in the EU. CAMbrella involved 9 work packages covering issues such as the definition of CAM; its legal status, provision and use in the EU; and a synthesis of international research perspectives. Based on the work package reports, we developed a strategic and methodologically robust research roadmap based on expert workshops, a systematic Delphi-based process and a final consensus conference. The CAMbrella project suggests six core areas for research to examine the potential contribution of CAM to the health care challenges faced by the EU. These areas include evaluating the prevalence of CAM use in Europe; the EU cititzens’ needs and attitudes regarding CAM; the safety of CAM; the comparative effectiveness of CAM; the effects of meaning and context on CAM outcomes; and different models for integrating CAM into existing health care systems. CAM research should use methods generally accepted in the evaluation of health services, including comparative effectiveness studies and mixed-methods designs. A research strategy is urgently needed, ideally led by a European CAM coordinating research office dedicated to fostering systematic communication between EU governments, the public, charitable and industry funders, researchers and other stakeholders. A European Centre for CAM should also be established to monitor and further a coordinated research strategy with sufficient funds to commission and promote high quality, independent research focusing on the public’s health needs and pan-European collaboration. There is a disparity between highly prevalent use of CAM in Europe and solid knowledge about it. A strategic approach on CAM r
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- 2014
31. High prevalence but limited evidence in complementary and alternative medicine: guidelines for future research
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Fischer, Felix H, primary, Lewith, George, additional, Witt, Claudia M, additional, Linde, Klaus, additional, von Ammon, Klaus, additional, Cardini, Francesco, additional, Falkenberg, Torkel, additional, Fønnebø, Vinjar, additional, Johannessen, Helle, additional, Reiter, Bettina, additional, Uehleke, Bernhard, additional, Weidenhammer, Wolfgang, additional, and Brinkhaus, Benno, additional
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- 2014
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32. Comparison of the Accuracy of the 7-Item HADS Depression Subscale and 14-Item Total HADS for Screening for Major Depression: A Systematic Review and Individual Participant Data Meta-Analysis.
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Wu, Yin, Levis, Brooke, Daray, Federico M., Ioannidis, John P. A., Patten, Scott B., Cuijpers, Pim, Ziegelstein, Roy C., Gilbody, Simon, Fischer, Felix H., Fan, Suiqiong, Sun, Ying, He, Chen, Krishnan, Ankur, Neupane, Dipika, Bhandari, Parash Mani, Negeri, Zelalem, Riehm, Kira E., Rice, Danielle B., Azar, Marleine, and Yan, Xin Wei
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DIAGNOSIS of mental depression , *META-analysis , *CONFIDENCE intervals , *SYSTEMATIC reviews , *MEDICAL screening , *PSYCHOLOGICAL tests , *RESEARCH funding , *DESCRIPTIVE statistics , *PREDICTIVE validity , *SENSITIVITY & specificity (Statistics) - Abstract
The seven-item Hospital Anxiety and Depression Scale Depression subscale (HADS-D) and the total score of the 14-item HADS (HADS-T) are both used for major depression screening. Compared to the HADS-D, the HADS-T includes anxiety items and requires more time to complete. We compared the screening accuracy of the HADS-D and HADS-T for major depression detection. We conducted an individual participant data meta-analysis and fit bivariate random effects models to assess diagnostic accuracy among participants with both HADS-D and HADS-T scores. We identified optimal cutoffs, estimated sensitivity and specificity with 95% confidence intervals, and compared screening accuracy across paired cutoffs via two-stage and individual-level models. We used a 0.05 equivalence margin to assess equivalency in sensitivity and specificity. 20,700 participants (2,285 major depression cases) from 98 studies were included. Cutoffs of ≥7 for the HADS-D (sensitivity 0.79 [0.75, 0.83], specificity 0.78 [0.75, 0.80]) and ≥15 for the HADS-T (sensitivity 0.79 [0.76, 0.82], specificity 0.81 [0.78, 0.83]) minimized the distance to the top-left corner of the receiver operating characteristic curve. Across all sets of paired cutoffs evaluated, differences of sensitivity between HADS-T and HADS-D ranged from −0.05 to 0.01 (0.00 at paired optimal cutoffs), and differences of specificity were within 0.03 for all cutoffs (0.02–0.03). The pattern was similar among outpatients, although the HADS-T was slightly (not nonequivalently) more specific among inpatients. The accuracy of HADS-T was equivalent to the HADS-D for detecting major depression. In most settings, the shorter HADS-D would be preferred. Public Significance Statement: The present study suggests that the accuracy of 14-item Hospital Anxiety and Depression Scale (HADS-D) and the seven-item HADS Depression subscale (HADS-D) are equivalent for detecting major depression. Using the seven-item HADS-D for depression screening instead of the full 14-item HADS-T has minimal influence on performance of the measure but would reduce patient and participant burden in most clinical and research settings. [ABSTRACT FROM AUTHOR]
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- 2023
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33. 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
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Andrea Benedetti, Yin Wu, Ying Sun, Brooke Levis, Ankur Krishnan, Chen He, Zelalem Negeri, Brett D. Thombs, Parash Mani Bhandari, Dipika Neupane, Riehm, Kira E, Rice, Danielle B, Azar, Marleine, Yan, Xin Wei, Imran, Mahrukh, Chiovitti, Matthew J, Saadat, Nazanin, Boruff, Jill T, Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P A, Kloda, Lorie A, Patten, Scott B, Ziegelstein, Roy C, Markham, Sarah, Henry, Melissa, Ismail, Zahinoor, Loiselle, Carmen G, Mitchell, Nicholas D, Tonelli, Marcello, Al-Adawi, Samir, Beck, Kevin R, Beraldi, Anna, Bernstein, Charles N, Boye, Birgitte, Büel-Drabe, Natalie, Bunevičius, Adomas, Can, Ceyhun, Carter, Gregory, Chen, Chih-Ken, Cheung, Gary, Clover, Kerrie, Costa-Requena, Gema, Cukor, Daniel, Dabscheck, Eli, Daray, Federico M, De Souza, Jennifer, Dorow, Marie, Downing, Marina G, Feinstein, Anthony, Ferentinos, Panagiotis P, Fischer, Felix H, Flint, Alastair J, Fujimori, Maiko, Gallagher, Pamela, Gandy, Milena, Grassi, Luigi, Härter, Martin, Hernando, Asuncion, Jenewein, Josef, Jetté, Nathalie, Julião, Miguel, Keller, Monika, Kim, Sung-Wan, Kjærgaard, Marie, Köhler, Sebastian, König, Hans-Helmut, Krishna, Lalit K R, Lee, Yu, Löbner, Margrit, Loosman, Wim L, Love, Anthony W, Löwe, Bernd, Malt, Ulrik F, Marrie, Ruth Ann, Martin-Santos, Rocio, Massardo, Loreto, Matsuoka, Yutaka, Mehnert, Anja, Michopoulos, Ioannis, Misery, Laurent, Navines, Ricard, Nelson, Christian J, Ng, Chong Guan, O'Donnell, Meaghan L, O'Rourke, Suzanne J, Öztürk, Ahmet, Pabst, Alexander, Pasco, Julie A, Pečeliūnienė, Jūratė, Pintor, Luis, Ponsford, Jennie L, Pulido, Federico, Quinn, Terence J, Reme, Silje E, Reuter, Katrin, Rieckmann, Nina, Riedel-Heller, Steffi G, Rooney, Alasdair G, Sánchez-González, Roberto, Saracino, Rebecca M, Schellekens, Melanie P J, Scherer, Martin, Schwarzbold, Marcelo L, Senturk Cankorur, Vesile, Shaaban, Juwita, Sharpe, Louise, Sharpe, Michael, Simard, Sébastien, Singer, Susanne, Stafford, Lesley, Stone, Jon, Strobel, Natalie A, Sultan, Serge, Teixeira, Antonio L, Tiringer, Istvan, Tschorn, Mira, Tung, Ka-Yee, Turner, Alyna, Wagner, Michael, Walker, Jane, Walterfang, Mark, Wang, Liang-Jen, Weyerer, Siegfried B, White, Jennifer, Williams, Lana J, Wong, Lai-Yi, and Group, DEPRESsion Screening Data (DEPRESSD) HADS
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Psychometrics ,MEDLINE ,LS5_12 ,Hospital Anxiety and Depression Scale ,Corrections ,Sensitivity and Specificity ,NO ,03 medical and health sciences ,0302 clinical medicine ,purl.org/becyt/ford/3.2 [https] ,Humans ,Medicine ,030212 general & internal medicine ,Depression (differential diagnoses) ,HADS- D ,metaanalysis ,accuracy ,Mini-international neuropsychiatric interview ,Psychiatric Status Rating Scales ,HADS-D ,Depressive Disorder, Major ,Depressive Disorder ,Diagnostic and Statistical Manual of Mental Disorders ,Hospitalization ,business.industry ,Research ,Major ,General Medicine ,Confidence interval ,030227 psychiatry ,Meta-analysis ,Structured interview ,purl.org/becyt/ford/3 [https] ,business ,Clinical psychology - Abstract
Objective To evaluate the accuracy of the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) to screen for major depression among people with physical health problems. Design Systematic review and individual participant data meta-analysis. Data sources Medline, Medline In-Process and Other Non-Indexed Citations, PsycInfo, and Web of Science (from inception to 25 October 2018). Review methods Eligible datasets included HADS-D scores and major depression status based on a validated diagnostic interview. Primary study data and study level data extracted from primary reports were combined. For HADS-D cut-off thresholds of 5-15, a bivariate random effects meta-analysis was used to estimate pooled sensitivity and specificity, separately, in studies that used semi-structured diagnostic interviews (eg, Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders), fully structured interviews (eg, Composite International Diagnostic Interview), and the Mini International Neuropsychiatric Interview. One stage meta-regression was used to examine whether accuracy was associated with reference standard categories and the characteristics of participants. Sensitivity analyses were done to assess whether including published results from studies that did not provide raw data influenced the results. Results Individual participant data were obtained from 101 of 168 eligible studies (60%; 25 574 participants (72% of eligible participants), 2549 with major depression). Combined sensitivity and specificity was maximised at a cut-off value of seven or higher for semi-structured interviews, fully structured interviews, and the Mini International Neuropsychiatric Interview. Among studies with a semi-structured interview (57 studies, 10 664 participants, 1048 with major depression), sensitivity and specificity were 0.82 (95% confidence interval 0.76 to 0.87) and 0.78 (0.74 to 0.81) for a cut-off value of seven or higher, 0.74 (0.68 to 0.79) and 0.84 (0.81 to 0.87) for a cut-off value of eight or higher, and 0.44 (0.38 to 0.51) and 0.95 (0.93 to 0.96) for a cut-off value of 11 or higher. Accuracy was similar across reference standards and subgroups and when published results from studies that did not contribute data were included. Conclusions When screening for major depression, a HADS-D cut-off value of seven or higher maximised combined sensitivity and specificity. A cut-off value of eight or higher generated similar combined sensitivity and specificity but was less sensitive and more specific. To identify medically ill patients with depression with the HADS-D, lower cut-off values could be used to avoid false negatives and higher cut-off values to reduce false positives and identify people with higher symptom levels. Fil: Wu, Yin. School Of Medicine; Canadá. Lady Davis Institute For Medical Research; Canadá Fil: Levis, Brooke. Keele University; Reino Unido Fil: Sun, Ying. Lady Davis Institute For Medical Research; Canadá Fil: He, Chen. Lady Davis Institute For Medical Research; Canadá Fil: Krishnan, Ankur. Lady Davis Institute For Medical Research; Canadá Fil: Neupane, Dipika. Lady Davis Institute For Medical Research; Canadá Fil: Bhandari, Parash Mani. Lady Davis Institute For Medical Research; Canadá Fil: Negeri, Zelalem. Université Mcgill; Canadá. Lady Davis Institute For Medical Research; Canadá Fil: Benedetti, Andrea. Centre Universitaire de Santé Mcgill; Canadá Fil: Thombs, Brett D.. Mcgill Faculty Of Medicine And Health Sciences; Canadá. Lady Davis Institute For Medical Research; Canadá Fil: Daray, Federico Manuel. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Farmacologia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay; Argentina
- Published
- 2021
34. High prevalence but limited evidence in complementary and alternative medicine: guidelines for future research
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Benno Brinkhaus, George Lewith, Wolfgang Weidenhammer, Klaus von Ammon, Bernhard Uehleke, Helle Johannessen, Francesco Cardini, Torkel Falkenberg, Vinjar Fønnebø, Claudia M. Witt, Felix Fischer, Bettina Reiter, Klaus Linde, University of Zurich, and Fischer, Felix H
- Subjects
Qualitative studies ,Complementary Therapies ,medicine.medical_specialty ,Comparative effectiveness research ,MEDLINE ,Context (language use) ,610 Medicine & health ,Complementary Therapies/statistics & numerical data ,Commission ,03 medical and health sciences ,0302 clinical medicine ,Research strategy ,Correspondence ,Health care ,medicine ,Prevalence ,Humans ,030212 general & internal medicine ,Cooperative Behavior ,computer.programming_language ,Health Services Needs and Demand ,Evidence-Based Medicine ,business.industry ,Research ,2707 Complementary and Alternative Medicine ,General Medicine ,Evidence-based medicine ,Public relations ,3. Good health ,Europe ,10034 Institute of Complementary Medicine ,Complementary and alternative medicine ,030220 oncology & carcinogenesis ,Family medicine ,Randomized clinical trials ,Safety ,business ,computer ,Delivery of Health Care ,Delphi ,Qualitative research - Abstract
The use of complementary and alternative Medicine (CAM) has increased over the past two decades in Europe. Nonetheless, research investigating the evidence to support its use remains limited. The CAMbrella project funded by the European Commission aimed to develop a strategic research agenda starting by systematically evaluating the state of CAM in the EU. CAMbrella involved 9 work packages covering issues such as the definition of CAM; its legal status, provision and use in the EU; and a synthesis of international research perspectives. Based on the work package reports, we developed a strategic and methodologically robust research roadmap based on expert workshops, a systematic Delphi-based process and a final consensus conference. The CAMbrella project suggests six core areas for research to examine the potential contribution of CAM to the health care challenges faced by the EU. These areas include evaluating the prevalence of CAM use in Europe; the EU cititzens’ needs and attitudes regarding CAM; the safety of CAM; the comparative effectiveness of CAM; the effects of meaning and context on CAM out- comes; and different models for integrating CAM into existing health care systems. CAM research should use methods generally accepted in the evaluation of health services, including comparative effectiveness studies and mixed-methods designs. A research strategy is urgently needed, ideally led by a European CAM coordinating research office dedicated to fostering systematic communication between EU governments, the public, charitable and industry funders, researchers and other stakeholders. A European Centre for CAM should also be established to monitor and further a coordinated research strategy with sufficient funds to commission and promote high quality, independent research focusing on the public’s health needs and pan-European collaboration. There is a disparity between highly prevalent use of CAM in Europe and solid knowledge about it. A strategic approach on CAM research should be established to investigate the identified gaps of knowledge and to address upcoming health care challenges.Keywords: Complementary and alternative medicine, Research strategy, Randomized clinical trials, Safety, Qualitative studies, Comparative effectiveness research The use of complementary and alternative Medicine (CAM) has increased over the past two decades in Europe. Nonetheless, research investigating the evidence to support its use remains limited. The CAMbrella project funded by the European Commission aimed to develop a strategic research agenda starting by systematically evaluating the state of CAM in the EU. CAMbrella involved 9 work packages covering issues such as the definition of CAM; its legal status, provision and use in the EU; and a synthesis of international research perspectives. Based on the work package reports, we developed a strategic and methodologically robust research roadmap based on expert workshops, a systematic Delphi-based process and a final consensus conference. The CAMbrella project suggests six core areas for research to examine the potential contribution of CAM to the health care challenges faced by the EU. These areas include evaluating the prevalence of CAM use in Europe; the EU cititzens' needs and attitudes regarding CAM; the safety of CAM; the comparative effectiveness of CAM; the effects of meaning and context on CAM outcomes; and different models for integrating CAM into existing health care systems. CAM research should use methods generally accepted in the evaluation of health services, including comparative effectiveness studies and mixed-methods designs. A research strategy is urgently needed, ideally led by a European CAM coordinating research office dedicated to fostering systematic communication between EU governments, the public, charitable and industry funders, researchers and other stakeholders. A European Centre for CAM should also be established to monitor and further a coordinated research strategy with sufficient funds to commission and promote high quality, independent research focusing on the public's health needs and pan-European collaboration. There is a disparity between highly prevalent use of CAM in Europe and solid knowledge about it. A strategic approach on CAM research should be established to investigate the identified gaps of knowledge and to address upcoming health care challenges.
- Published
- 2014
35. Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis - ERRATUM.
- Author
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Wu Y, Levis B, Riehm KE, Saadat N, Levis AW, Azar M, Rice DB, Boruff J, Cuijpers P, Gilbody S, Ioannidis JPA, Kloda LA, McMillan D, Patten SB, Shrier I, Ziegelstein RC, Akena DH, Arroll B, Ayalon L, Baradaran HR, Baron M, Bombardier CH, Butterworth P, Carter G, Chagas MH, Chan JCN, Cholera R, Conwell Y, de Manvan Ginkel JM, Fann JR, Fischer FH, Fung D, Gelaye B, Goodyear-Smith F, Greeno CG, Hall BJ, Harrison PA, Härter M, Hegerl U, Hides L, Hobfoll SE, Hudson M, Hyphantis T, Inagaki M, Jetté N, Khamseh ME, Kiely KM, Kwan Y, Lamers F, Liu SI, Lotrakul M, Loureiro SR, Löwe B, McGuire A, Mohd-Sidik S, Munhoz TN, Muramatsu K, Osório FL, Patel V, Pence BW, Persoons P, Picardi A, Reuter K, Rooney AG, Santos IS, Shaaban J, Sidebottom A, Simning A, Stafford L, Sung S, Tan PLL, Turner A, van Weert HC, White J, Whooley MA, Winkley K, Yamada M, Benedetti A, and Thombs BD
- Published
- 2020
- Full Text
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