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2. The lived experience of severe mental illness and long-term conditions: a qualitative exploration of service user, carer, and healthcare professional perspectives on self-managing co-existing mental and physical conditions

Author

Carswell, C., Brown, J. V. E., Lister, J., Ajjan, R. A., Alderson, S. L., Balogun-Katung, A., Bellass, S., Double, K., Gilbody, S., Hewitt, C. E., Holt, R. I. G., Jacobs, R., Kellar, I., Peckham, E., Shiers, D., Taylor, J., Siddiqi, N., and Coventry, P.

Published
2022
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5. Measuring the digital divide among people with severe mental ill health using the essential digital skills framework.

Author

Spanakis, P, Wadman, R, Walker, L, Heron, P, Mathers, A, Baker, J, Johnston, G, Gilbody, S, and Peckham, E

Abstract

Aims: Amid the vast digitalisation of health and other services during the pandemic, people with no digital skills are at risk of digital exclusion. This risk might not abate by the end of the pandemic. This article seeks to understand whether people with severe mental ill health (SMI) have the necessary digital skills to adapt to these changes and avoid digital exclusion. Methods: Two hundred and forty-nine adults with SMI across England completed a survey online or offline. They provided information on their digital skills based on the Essential Digital Skills (EDS) framework, sociodemographic information, and digital access. This is the first time that the EDS is benchmarked in people with SMI. Results: 42.2% had no Foundation Skills, and 46.2% lacked skills for daily life (lacking Foundation or Life Skills). 23.0% of those working lacked skills for professional life (lacking Foundation or Work Skills). The most commonly missing skills were handling passwords and using the device settings (Foundation Skills) and online problem solving (Skills for Life). People were interested in learning more about approximately half of the skills they did not have. People were more likely to lack Foundation Skills if they were older, not in employment, had a psychosis-spectrum disorder, or had no Internet access at home. Conclusion: A significant portion of people with SMI lacked Foundation Skills in this objective and benchmarked survey. This points to a high risk for digital exclusion and the need for focused policy and tailored health sector support to ensure people retain access to key services and develop digital skills and confidence. To our knowledge, this is the first time this has been described using the EDS framework. Services, including the National Health Service (NHS), need to be aware of and mitigate the risks. [ABSTRACT FROM AUTHOR]

Published
2024
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6. 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

Author

Wu, Y, Levis, B, Daray, FM, Ioannidis, JPA, Patten, SB, Cuijpers, P, Ziegelstein, RC, Gilbody, S, Fischer, FH, Fan, S, Sun, Y, He, C, Krishnan, A, Neupane, D, Bhandari, PM, Negeri, Z, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Imran, M, Chiovitti, MJ, Boruff, JT, McMillan, D, Kloda, LA, Markham, S, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Al-Adawi, S, Beck, KR, Beraldi, A, Bernstein, CN, Boye, B, Buel-Drabe, N, Bunevicius, A, Can, C, Carter, G, Chen, C-K, Cheung, G, Clover, K, Conroy, RM, Costa-Requena, G, Cukor, D, Dabscheck, E, De Souza, J, Downing, M, Feinstein, A, Ferentinos, PP, Flint, AJ, Gallagher, P, Gandy, M, Grassi, L, Haerter, M, Hernando, A, Jackson, ML, Jenewein, J, Jette, N, Juliao, M, Kjaergaard, M, Kohler, S, Konig, H-H, Krishna, LKR, Lee, Y, Loebner, M, Loosman, WL, Love, AW, Loewe, B, Malt, UF, Marrie, RA, Massardo, L, Matsuoka, Y, Mehnert, A, Michopoulos, I, Misery, L, Nelson, CJ, Ng, CG, O'Donnell, ML, O'Rourke, SJ, Ozturk, A, Pabst, A, Pasco, JA, Peceliuniene, J, Pintor, L, Ponsford, JL, Pulido, F, Quinn, TJ, Reme, SE, Reuter, K, Riedel-Heller, SG, Rooney, AG, Sanchez-Gonzalez, R, Saracino, RM, Schellekens, MPJ, Scherer, M, Schwarzbold, ML, Cankorur, VS, Sharpe, L, Sharpe, M, Simard, S, Singer, S, Stafford, L, Stone, J, Strobe, NA, Sultan, S, Teixeira, AL, Tiringer, I, Turner, A, Walker, J, Walterfang, M, Wang, L-J, Weyerer, SB, White, J, Wiese, B, Williams, LJ, Wong, L-Y, Benedetti, A, Thombsi, BD, Wu, Y, Levis, B, Daray, FM, Ioannidis, JPA, Patten, SB, Cuijpers, P, Ziegelstein, RC, Gilbody, S, Fischer, FH, Fan, S, Sun, Y, He, C, Krishnan, A, Neupane, D, Bhandari, PM, Negeri, Z, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Imran, M, Chiovitti, MJ, Boruff, JT, McMillan, D, Kloda, LA, Markham, S, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Al-Adawi, S, Beck, KR, Beraldi, A, Bernstein, CN, Boye, B, Buel-Drabe, N, Bunevicius, A, Can, C, Carter, G, Chen, C-K, Cheung, G, Clover, K, Conroy, RM, Costa-Requena, G, Cukor, D, Dabscheck, E, De Souza, J, Downing, M, Feinstein, A, Ferentinos, PP, Flint, AJ, Gallagher, P, Gandy, M, Grassi, L, Haerter, M, Hernando, A, Jackson, ML, Jenewein, J, Jette, N, Juliao, M, Kjaergaard, M, Kohler, S, Konig, H-H, Krishna, LKR, Lee, Y, Loebner, M, Loosman, WL, Love, AW, Loewe, B, Malt, UF, Marrie, RA, Massardo, L, Matsuoka, Y, Mehnert, A, Michopoulos, I, Misery, L, Nelson, CJ, Ng, CG, O'Donnell, ML, O'Rourke, SJ, Ozturk, A, Pabst, A, Pasco, JA, Peceliuniene, J, Pintor, L, Ponsford, JL, Pulido, F, Quinn, TJ, Reme, SE, Reuter, K, Riedel-Heller, SG, Rooney, AG, Sanchez-Gonzalez, R, Saracino, RM, Schellekens, MPJ, Scherer, M, Schwarzbold, ML, Cankorur, VS, Sharpe, L, Sharpe, M, Simard, S, Singer, S, Stafford, L, Stone, J, Strobe, NA, Sultan, S, Teixeira, AL, Tiringer, I, Turner, A, Walker, J, Walterfang, M, Wang, L-J, Weyerer, SB, White, J, Wiese, B, Williams, LJ, Wong, L-Y, Benedetti, A, and Thombsi, BD

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. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Published
2023

9. EE449 Cost-Effectiveness of One Session Treatment (OST) for Children and Young People With Specific Phobias Compared to Multi-Session Cognitive Behavioural Therapy (CBT): Results From a Randomised Controlled Trial

Author

Wang, HI, primary, Wright, B, additional, Tindall, L, additional, Cooper, C, additional, Biggs, K, additional, Lee, E, additional, Teare, MD, additional, Gega, L, additional, Scott, AJ, additional, Hayward, E, additional, Solaiman, K, additional, Davis, T, additional, McMillan, D, additional, Gilbody, S, additional, and Parrott, S, additional

Published
2022
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11. EE214 Impact of Depression Relapse on Participant Quality of Life and Costs to the English NHS: Secondary Analysis from the Antler Study on Antidepressant Discontinuation in Well Patients in Primary Care

Author

Clarke, CS, primary, Duffy, L, additional, Lewis, G, additional, Freemantle, N, additional, Gilbody, S, additional, Kendrick, T, additional, Kessler, D, additional, King, M, additional, Lanham, P, additional, Mangin, D, additional, Moore, M, additional, Nazareth, I, additional, Wiles, N, additional, Marston, L, additional, and Hunter, RM, additional

Published
2022
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12. The lived experience of severe mental illness and long-term conditions: a qualitative exploration of service user, carer, and healthcare professional perspectives on self-managing co-existing mental and physical conditions

Author

Carswell, C, Brown, JVE, Lister, J, Ajjan, RA, Alderson, SL, Balogun-Katung, A, Bellass, S, Double, K, Gilbody, S, Hewitt, CE, Holt, RIG, Jacobs, R, Kellar, I, Peckham, E, Shiers, D, Taylor, J, Siddiqi, N, Coventry, P, Carswell, C, Brown, JVE, Lister, J, Ajjan, RA, Alderson, SL, Balogun-Katung, A, Bellass, S, Double, K, Gilbody, S, Hewitt, CE, Holt, RIG, Jacobs, R, Kellar, I, Peckham, E, Shiers, D, Taylor, J, Siddiqi, N, and Coventry, P

Abstract

Background: People with severe mental illness (SMI), such as schizophrenia, have higher rates of physical long-term conditions (LTCs), poorer health outcomes, and shorter life expectancy compared with the general population. Previous research exploring SMI and diabetes highlights that people with SMI experience barriers to self-management, a key component of care in long-term conditions; however, this has not been investigated in the context of other LTCs. The aim of this study was to explore the lived experience of co-existing SMI and LTCs for service users, carers, and healthcare professionals. Methods: A qualitative study with people with SMI and LTCs, their carers, and healthcare professionals, using semi-structured interviews, focused observations, and focus groups across the UK. Forty-one interviews and five focus groups were conducted between December 2018 and April 2019. Transcripts were coded by two authors and analysed thematically. Results: Three themes were identified, 1) the precarious nature of living with SMI, 2) the circularity of life with SMI and LTCs, and 3) the constellation of support for self-management. People with co-existing SMI and LTCs often experience substantial difficulties with self-management of their health due to the competing demands of their psychiatric symptoms and treatment, social circumstances, and access to support. Multiple long-term conditions add to the burden of self-management. Social support, alongside person-centred professional care, is a key facilitator for managing health. An integrated approach to both mental and physical healthcare was suggested to meet service user and carer needs. Conclusion: The demands of living with SMI present a substantial barrier to self-management for multiple co-existing LTCs. It is important that people with SMI can access person-centred, tailored support for their LTCs that takes into consideration individual circumstances and priorities.

Published
2022

13. Acceptability of a behavioural intervention to mitigate the psychological impacts of COVID-19 restrictions in older people with long-term conditions: a qualitative study

Author

Shearsmith, L, primary, Coventry, PA, additional, Sloan, C, additional, Henry, A, additional, Newbronner, E, additional, Littlewood, E, additional, Bailey, D, additional, Gascoyne, S., additional, Burke, L., additional, Ryde, E., additional, Woodhouse, R, additional, McMillan, D, additional, Ekers, D, additional, Gilbody, S, additional, and Chew-Graham, CA, additional

Published
2022
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14. Additional file 3 of The lived experience of severe mental illness and long-term conditions: a qualitative exploration of service user, carer, and healthcare professional perspectives on self-managing co-existing mental and physical conditions

Author

Carswell, C., Brown, J. V. E., Lister, J., Ajjan, R. A., Alderson, S. L., Balogun-Katung, A., Bellass, S., Double, K., Gilbody, S., Hewitt, C. E., Holt, R. I. G., Jacobs, R., Kellar, I., Peckham, E., Shiers, D., Taylor, J., Siddiqi, N., and Coventry, P.

Subjects
Data_FILES
Abstract

Additional file 3.

Published
2022
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15. Additional file 2 of The lived experience of severe mental illness and long-term conditions: a qualitative exploration of service user, carer, and healthcare professional perspectives on self-managing co-existing mental and physical conditions

Author

Carswell, C., Brown, J. V. E., Lister, J., Ajjan, R. A., Alderson, S. L., Balogun-Katung, A., Bellass, S., Double, K., Gilbody, S., Hewitt, C. E., Holt, R. I. G., Jacobs, R., Kellar, I., Peckham, E., Shiers, D., Taylor, J., Siddiqi, N., and Coventry, P.

Subjects
Data_FILES
Abstract

Additional file 2.

Published
2022
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16. Additional file 1 of The lived experience of severe mental illness and long-term conditions: a qualitative exploration of service user, carer, and healthcare professional perspectives on self-managing co-existing mental and physical conditions

Author

Carswell, C., Brown, J. V. E., Lister, J., Ajjan, R. A., Alderson, S. L., Balogun-Katung, A., Bellass, S., Double, K., Gilbody, S., Hewitt, C. E., Holt, R. I. G., Jacobs, R., Kellar, I., Peckham, E., Shiers, D., Taylor, J., Siddiqi, N., and Coventry, P.

Subjects
Data_FILES
Abstract

Additional file 1.

Published
2022
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17. sj-docx-1-rsh-10.1177_17579139221106399 – Supplemental material for Measuring the digital divide among people with severe mental ill health using the essential digital skills framework

Author

Spanakis, P, Wadman, R, Walker, L, Heron, P, Mathers, A, Baker, J, Johnston, G, Gilbody, S, and Peckham, E

Subjects
111708 Health and Community Services, 111799 Public Health and Health Services not elsewhere classified, FOS: Health sciences
Abstract

Supplemental material, sj-docx-1-rsh-10.1177_17579139221106399 for Measuring the digital divide among people with severe mental ill health using the essential digital skills framework by P Spanakis, R Wadman, L Walker, P Heron, A Mathers, J Baker, G Johnston, S Gilbody and E Peckham in Perspectives in Public Health

Published
2022
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18. Predicting prognosis for adults with depression using individual symptom data: a comparison of modelling approaches.

Author

Buckman, J. E. J., Cohen, Z. D., O'Driscoll, C., Fried, E. I., Saunders, R., Ambler, G., DeRubeis, R. J., Gilbody, S., Hollon, S. D., Kendrick, T., Watkins, E., Eley, T.C., Peel, A. J., Rayner, C., Kessler, D., Wiles, N., Lewis, G., and Pilling, S.

Subjects
LIFE change events, SOCIAL support, TREATMENT effectiveness, PSYCHOLOGICAL tests, MENTAL depression, ALCOHOL drinking, FACTOR analysis, PREDICTION models, ANXIETY, ADULTS
Abstract

Background: This study aimed to develop, validate and compare the performance of models predicting post-treatment outcomes for depressed adults based on pre-treatment data. Methods: Individual patient data from all six eligible randomised controlled trials were used to develop (k = 3, n = 1722) and test (k = 3, n = 918) nine models. Predictors included depressive and anxiety symptoms, social support, life events and alcohol use. Weighted sum scores were developed using coefficient weights derived from network centrality statistics (models 1–3) and factor loadings from a confirmatory factor analysis (model 4). Unweighted sum score models were tested using elastic net regularised (ENR) and ordinary least squares (OLS) regression (models 5 and 6). Individual items were then included in ENR and OLS (models 7 and 8). All models were compared to one another and to a null model (mean post-baseline Beck Depression Inventory Second Edition (BDI-II) score in the training data: model 9). Primary outcome: BDI-II scores at 3–4 months. Results: Models 1–7 all outperformed the null model and model 8. Model performance was very similar across models 1–6, meaning that differential weights applied to the baseline sum scores had little impact. Conclusions: Any of the modelling techniques (models 1–7) could be used to inform prognostic predictions for depressed adults with differences in the proportions of patients reaching remission based on the predicted severity of depressive symptoms post-treatment. However, the majority of variance in prognosis remained unexplained. It may be necessary to include a broader range of biopsychosocial variables to better adjudicate between competing models, and to derive models with greater clinical utility for treatment-seeking adults with depression. [ABSTRACT FROM AUTHOR]

Published
2023
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19. 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, D., Levis, B., Bhandari, P.M., Thombs, B.D., Benedetti, A., Sun, Y., He, C., Wu, Y., Krishnan, A., Negeri, Z., Imran, M., Rice, D.B., Riehm, K.E., Saadat, N., Azar, M., Sanchez, T.A., Chiovitti, M.J., Levis, A.W., Boruff, J.T., Cuijpers, P., Gilbody, S., Ioannidis, J.P.A., Kloda, L.A., Patten, S.B., Shrier, I., Ziegelstein, R.C., Comeau, L., Mitchell, N.D., Tonelli, M., Vigod, S.N., Akena, D.H., Alvarado, R., Arroll, B., Bakare, M.O., Baradaran, H.R., Beck, C.T., Bombardier, C.H., Bunevicius, A., Carter, G., Chagas, M.H., Chaudron, L.H., Cholera, R., Clover, K., Conwell, Y., Castro e Couto, T., de Man-van Ginkel, J.M., Delgadillo, J., Fann, J.R., Favez, N., Fung, D., Garcia-Esteve, L., Gelaye, B., Goodyear-Smith, F., Hyphantis, T., Inagaki, M., Ismail, K., Jetté, N., Khalifa, D.S., Khamseh, M.E., Kohlhoff, J., Kozinszky, Z., Kusminskas, L., Liu, S.-I., Lotrakul, M., Loureiro, S.R., Löwe, B., Sidik, S.M., Nakić Radoš, S., Osório, F.L., Pawlby, S.J., Pence, B.W., Rochat, T.J., Rooney, A.G., Sharp, D.J., Stafford, L., Su, K.-P., Sung, S.C., Tadinac, M., Darius Tandon, S., Thiagayson, P., Töreki, A., Torres-Giménez, A., Turner, A., van der Feltz-Cornelis, C.M., Vega Dienstmaier, Johann Martín, Vöhringer, P.A., White, J., Whooley, M.A., Winkley, K., Yamada, M., DEPRESsion Screening Data (DEPRESSD) Collaboration, Clinical Psychology, World Health Organization (WHO) Collaborating Center, APH - Global Health, and APH - Mental Health

Subjects
Astrophysics::High Energy Astrophysical Phenomena, Bivariate analysis, Patient Health Questionnaire, Sensitivity and Specificity, 03 medical and health sciences, 0302 clinical medicine, male, diagnostic test accuracy, individual participant data meta‐analysis, meta‐analysis, publication bias, selective cutoff reporting, Bias, Statistics, Humans, Cutoff, Medicine, controlled study, Edinburgh Postnatal Depression Scale, diagnostic test accuracy study, human, Psychiatric Status Rating Scales, Depressive Disorder, Major, business.industry, adult, Individual participant data, article, Original Articles, Publication bias, Random effects model, individual participant data meta-analysis, 030227 psychiatry, meta-analysis, Psychiatry and Mental health, female, Meta-analysis, diagnostic accuracy, Original Article, business, 030217 neurology & neurosurgery, meta analysis, Patient Health Questionnaire 9
Abstract

Objectives\ud \ud 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.\ud \ud \ud \ud Methods\ud \ud We conducted bivariate random effects meta-analyses using individual participant data to compare accuracy from published versus all cutoffs.\ud \ud \ud \ud Results\ud \ud 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.\ud \ud \ud \ud Conclusion\ud \ud Selective cutoff reporting was more pronounced for the PHQ-9 than EPDS.

Published
2021

20. Living with diabetes alongside a severe mental illness: A qualitative exploration with people with severe mental illness, family members and healthcare staff

Author

Bellass, S, Lister, J, Kitchen, CEW, Kramer, L, Alderson, SL, Doran, T, Gilbody, S, Han, L, Hewitt, C, Holt, RIG, Jacobs, R, Prady, SL, Shiers, D, Siddiqi, N, Taylor, J, Bellass, S, Lister, J, Kitchen, CEW, Kramer, L, Alderson, SL, Doran, T, Gilbody, S, Han, L, Hewitt, C, Holt, RIG, Jacobs, R, Prady, SL, Shiers, D, Siddiqi, N, and Taylor, J

Abstract

Aims: Diabetes is two to three times more prevalent in people with severe mental illness, yet little is known about the challenges of managing both conditions from the perspectives of people living with the co-morbidity, their family members or healthcare staff. Our aim was to understand these challenges and to explore the circumstances that influence access to and receipt of diabetes care for people with severe mental illness. Methods: Framework analysis of qualitative semi-structured interviews with people with severe mental illness and diabetes, family members, and staff from UK primary care, mental health and diabetes services, selected using a maximum variation sampling strategy between April and December 2018. Results: In all, 39 adults with severe mental illness and diabetes (3 with type 1 diabetes and 36 with type 2 diabetes), nine family members and 30 healthcare staff participated. Five themes were identified: (a) Severe mental illness governs everyday life including diabetes management; (b) mood influences capacity and motivation for diabetes self-management; (c) cumulative burden of managing multiple physical conditions; (d) interacting conditions and overlapping symptoms and (e) support for everyday challenges. People living with the co-morbidity and their family members emphasised the importance of receiving support for the everyday challenges that impact diabetes management, and identified barriers to accessing this from healthcare providers. Conclusions: More intensive support for diabetes management is needed when people's severe mental illness (including symptoms of depression) or physical health deteriorates. Interventions that help people, including healthcare staff, distinguish between symptoms of diabetes and severe mental illness are also needed.

Published
2021

21. Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data

Author

Furukawa, T.A., Suganuma, A., Ostinelli, E.G., Andersson, G., Beevers, C.G., Shumake, J., Berger, T., Boele, F.W., Buntrock, C., Carlbring, P., Choi, I., Christensen, H., Mackinnon, A., Dahne, J., Huibers, M.J.H., Ebert, D.D., Farrer, L., Forand, N.R., Strunk, D.R., Ezawa, I.D., Forsell, E., Kaldo, V., Geraedts, A., Gilbody, S., Littlewood, E., Brabyn, S., Hadjistavropoulos, H.D., Schneider, L.H., Johansson, R., Kenter, R., Kivi, M., Björkelund, C., Kleiboer, A., Riper, H., Klein, J.P., Schröder, J., Meyer, B., Moritz, S., Bücker, L., Lintvedt, O., Johansson, P., Lundgren, J., Milgrom, J., Gemmill, A.W., Mohr, D.C., Montero-Marin, J., Garcia-Campayo, J., Nobis, S., Zarski, A.C., O'Moore, K., Williams, A.D., Newby, J.M., Perini, S., Phillips, R., Schneider, J., Pots, W., Pugh, N.E., Richards, D., Rosso, I.M., Rauch, S.L., Sheeber, L.B., Smith, J., Spek, V., Pop, V.J., Ünlü, B., van Bastelaar, K.M.P., van Luenen, S., Garnefski, N., Kraaij, V., Vernmark, K., Warmerdam, L., van Straten, A., Zagorscak, P., Knaevelsrud, C., Heinrich, M., Miguel, C., Cipriani, A., Efthimiou, O., Karyotaki, E., Cuijpers, P., Furukawa, T.A., Suganuma, A., Ostinelli, E.G., Andersson, G., Beevers, C.G., Shumake, J., Berger, T., Boele, F.W., Buntrock, C., Carlbring, P., Choi, I., Christensen, H., Mackinnon, A., Dahne, J., Huibers, M.J.H., Ebert, D.D., Farrer, L., Forand, N.R., Strunk, D.R., Ezawa, I.D., Forsell, E., Kaldo, V., Geraedts, A., Gilbody, S., Littlewood, E., Brabyn, S., Hadjistavropoulos, H.D., Schneider, L.H., Johansson, R., Kenter, R., Kivi, M., Björkelund, C., Kleiboer, A., Riper, H., Klein, J.P., Schröder, J., Meyer, B., Moritz, S., Bücker, L., Lintvedt, O., Johansson, P., Lundgren, J., Milgrom, J., Gemmill, A.W., Mohr, D.C., Montero-Marin, J., Garcia-Campayo, J., Nobis, S., Zarski, A.C., O'Moore, K., Williams, A.D., Newby, J.M., Perini, S., Phillips, R., Schneider, J., Pots, W., Pugh, N.E., Richards, D., Rosso, I.M., Rauch, S.L., Sheeber, L.B., Smith, J., Spek, V., Pop, V.J., Ünlü, B., van Bastelaar, K.M.P., van Luenen, S., Garnefski, N., Kraaij, V., Vernmark, K., Warmerdam, L., van Straten, A., Zagorscak, P., Knaevelsrud, C., Heinrich, M., Miguel, C., Cipriani, A., Efthimiou, O., Karyotaki, E., and Cuijpers, P.

Published
2021

22. 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, D, Levis, B, Bhandari, PM, Thombs, BD, Benedetti, A, Sun, Y, He, C, Wu, Y, Krishnan, A, Negeri, Z, Imran, M, Rice, DB, Riehm, KE, Saadat, N, Azar, M, Sanchez, TA, Chiovitti, MJ, Levis, AW, Boruff, JT, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Comeau, L, Mitchell, ND, Tonelli, M, Vigod, SN, Akena, DH, Alvarado, R, Arroll, B, Bakare, MO, Baradaran, HR, Beck, CT, Bombardier, CH, Bunevicius, A, Carter, G, Chagas, MH, Chaudron, LH, Cholera, R, Clover, K, Conwell, Y, Castro e Couto, T, de Man-van Ginkel, JM, Delgadillo, J, Fann, JR, Favez, N, Fung, D, Garcia-Esteve, L, Gelaye, B, Goodyear-Smith, F, Hyphantis, T, Inagaki, M, Ismail, K, Jetté, N, Khalifa, DS, Khamseh, ME, Kohlhoff, J, Kozinszky, Z, Kusminskas, L, Liu, SI, Lotrakul, M, Loureiro, SR, Löwe, B, Sidik, SM, Nakić Radoš, S, Osório, FL, Pawlby, SJ, Pence, BW, Rochat, TJ, Rooney, AG, Sharp, DJ, Stafford, L, Su, KP, Sung, SC, Tadinac, M, Darius Tandon, S, Thiagayson, P, Töreki, A, Torres-Giménez, A, Turner, Alyna, van der Feltz-Cornelis, CM, Vega-Dienstmaier, JM, Vöhringer, PA, White, J, Whooley, MA, Winkley, K, Yamada, M, Neupane, D, Levis, B, Bhandari, PM, Thombs, BD, Benedetti, A, Sun, Y, He, C, Wu, Y, Krishnan, A, Negeri, Z, Imran, M, Rice, DB, Riehm, KE, Saadat, N, Azar, M, Sanchez, TA, Chiovitti, MJ, Levis, AW, Boruff, JT, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Comeau, L, Mitchell, ND, Tonelli, M, Vigod, SN, Akena, DH, Alvarado, R, Arroll, B, Bakare, MO, Baradaran, HR, Beck, CT, Bombardier, CH, Bunevicius, A, Carter, G, Chagas, MH, Chaudron, LH, Cholera, R, Clover, K, Conwell, Y, Castro e Couto, T, de Man-van Ginkel, JM, Delgadillo, J, Fann, JR, Favez, N, Fung, D, Garcia-Esteve, L, Gelaye, B, Goodyear-Smith, F, Hyphantis, T, Inagaki, M, Ismail, K, Jetté, N, Khalifa, DS, Khamseh, ME, Kohlhoff, J, Kozinszky, Z, Kusminskas, L, Liu, SI, Lotrakul, M, Loureiro, SR, Löwe, B, Sidik, SM, Nakić Radoš, S, Osório, FL, Pawlby, SJ, Pence, BW, Rochat, TJ, Rooney, AG, Sharp, DJ, Stafford, L, Su, KP, Sung, SC, Tadinac, M, Darius Tandon, S, Thiagayson, P, Töreki, A, Torres-Giménez, A, Turner, Alyna, van der Feltz-Cornelis, CM, Vega-Dienstmaier, JM, Vöhringer, PA, White, J, Whooley, MA, Winkley, K, and Yamada, M

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.

Published
2021

23. Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual data

Author

Furukawa, TA, Suganuma, A, Ostinelli, EG, Andersson, G, Beevers, CG, Shumake, J, Berger, T, Boele, FW, Buntrock, C, Carlbring, P, Choi, I, Christensen, H, Mackinnon, A, Dahne, J, Huibers, MJH, Ebert, DD, Farrer, L, Forand, NR, Strunk, DR, Ezawa, ID, Forsell, E, Kaldo, V, Geraedts, A, Gilbody, S, Littlewood, E, Brabyn, S, Hadjistavropoulos, HD, Schneider, LH, Johansson, R, Kenter, R, Kivi, M, Bjorkelund, C, Kleiboer, A, Riper, H, Klein, JP, Schroder, J, Meyer, B, Moritz, S, Bucker, L, Lintvedt, O, Johansson, P, Lundgren, J, Milgrom, J, Gemmill, AW, Mohr, DC, Montero-Marin, J, Garcia-Campayo, J, Nobis, S, Zarski, A-C, O'Moore, K, Williams, AD, Newby, JM, Perini, S, Phillips, R, Schneider, J, Pots, W, Pugh, NE, Richards, D, Rosso, IM, Rauch, SL, Sheeber, LB, Smith, J, Spek, V, Pop, VJ, Unlu, B, van Bastelaar, KMP, van Luenen, S, Garnefski, N, Kraaij, V, Vernmark, K, Warmerdam, L, van Straten, A, Zagorscak, P, Knaevelsrud, C, Heinrich, M, Miguel, C, Cipriani, A, Efthimiou, O, Karyotaki, E, Cuijpers, P, Furukawa, TA, Suganuma, A, Ostinelli, EG, Andersson, G, Beevers, CG, Shumake, J, Berger, T, Boele, FW, Buntrock, C, Carlbring, P, Choi, I, Christensen, H, Mackinnon, A, Dahne, J, Huibers, MJH, Ebert, DD, Farrer, L, Forand, NR, Strunk, DR, Ezawa, ID, Forsell, E, Kaldo, V, Geraedts, A, Gilbody, S, Littlewood, E, Brabyn, S, Hadjistavropoulos, HD, Schneider, LH, Johansson, R, Kenter, R, Kivi, M, Bjorkelund, C, Kleiboer, A, Riper, H, Klein, JP, Schroder, J, Meyer, B, Moritz, S, Bucker, L, Lintvedt, O, Johansson, P, Lundgren, J, Milgrom, J, Gemmill, AW, Mohr, DC, Montero-Marin, J, Garcia-Campayo, J, Nobis, S, Zarski, A-C, O'Moore, K, Williams, AD, Newby, JM, Perini, S, Phillips, R, Schneider, J, Pots, W, Pugh, NE, Richards, D, Rosso, IM, Rauch, SL, Sheeber, LB, Smith, J, Spek, V, Pop, VJ, Unlu, B, van Bastelaar, KMP, van Luenen, S, Garnefski, N, Kraaij, V, Vernmark, K, Warmerdam, L, van Straten, A, Zagorscak, P, Knaevelsrud, C, Heinrich, M, Miguel, C, Cipriani, A, Efthimiou, O, Karyotaki, E, and Cuijpers, P

Abstract

BACKGROUND: Internet cognitive behavioural therapy (iCBT) is a viable delivery format of CBT for depression. However, iCBT programmes include training in a wide array of cognitive and behavioural skills via different delivery methods, and it remains unclear which of these components are more efficacious and for whom. METHODS: We did a systematic review and individual participant data component network meta-analysis (cNMA) of iCBT trials for depression. We searched PubMed, PsycINFO, Embase, and the Cochrane Library for randomised controlled trials (RCTs) published from database inception to Jan 1, 2019, that compared any form of iCBT against another or a control condition in the acute treatment of adults (aged ≥18 years) with depression. Studies with inpatients or patients with bipolar depression were excluded. We sought individual participant data from the original authors. When these data were unavailable, we used aggregate data. Two independent researchers identified the included components. The primary outcome was depression severity, expressed as incremental mean difference (iMD) in the Patient Health Questionnaire-9 (PHQ-9) scores when a component is added to a treatment. We developed a web app that estimates relative efficacies between any two combinations of components, given baseline patient characteristics. This study is registered in PROSPERO, CRD42018104683. FINDINGS: We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42·0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD -1·83 [95% credible interval (CrI) -2·90 to -0·80]) and that relaxation might be harmful (1·20 [95% CrI 0·17 to 2·27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduc

Published
2021

24. Internet-Based Cognitive Behavioral Therapy for Depression: A Systematic Review and Individual Patient Data Network Meta-analysis.

Author

Karyotaki, E, Efthimiou, O, Miguel, C, Bermpohl, FMG, Furukawa, TA, Cuijpers, P, Individual Patient Data Meta-Analyses for Depression (IPDMA-DE) Collaboration, Riper, H, Patel, V, Mira, A, Gemmil, AW, Yeung, AS, Lange, A, Williams, AD, Mackinnon, A, Geraedts, A, van Straten, A, Meyer, B, Björkelund, C, Knaevelsrud, C, Beevers, CG, Botella, C, Strunk, DR, Mohr, DC, Ebert, DD, Kessler, D, Richards, D, Littlewood, E, Forsell, E, Feng, F, Wang, F, Andersson, G, Hadjistavropoulos, H, Christensen, H, Ezawa, ID, Choi, I, Rosso, IM, Klein, JP, Shumake, J, Garcia-Campayo, J, Milgrom, J, Smith, J, Montero-Marin, J, Newby, JM, Bretón-López, J, Schneider, J, Vernmark, K, Bücker, L, Sheeber, LB, Warmerdam, L, Farrer, L, Heinrich, M, Huibers, MJH, Kivi, M, Kraepelien, M, Forand, NR, Pugh, N, Lindefors, N, Lintvedt, O, Zagorscak, P, Carlbring, P, Phillips, R, Johansson, R, Kessler, RC, Brabyn, S, Perini, S, Rauch, SL, Gilbody, S, Moritz, S, Berger, T, Pop, V, Kaldo, V, Spek, V, Forsell, Y, Karyotaki, E, Efthimiou, O, Miguel, C, Bermpohl, FMG, Furukawa, TA, Cuijpers, P, Individual Patient Data Meta-Analyses for Depression (IPDMA-DE) Collaboration, Riper, H, Patel, V, Mira, A, Gemmil, AW, Yeung, AS, Lange, A, Williams, AD, Mackinnon, A, Geraedts, A, van Straten, A, Meyer, B, Björkelund, C, Knaevelsrud, C, Beevers, CG, Botella, C, Strunk, DR, Mohr, DC, Ebert, DD, Kessler, D, Richards, D, Littlewood, E, Forsell, E, Feng, F, Wang, F, Andersson, G, Hadjistavropoulos, H, Christensen, H, Ezawa, ID, Choi, I, Rosso, IM, Klein, JP, Shumake, J, Garcia-Campayo, J, Milgrom, J, Smith, J, Montero-Marin, J, Newby, JM, Bretón-López, J, Schneider, J, Vernmark, K, Bücker, L, Sheeber, LB, Warmerdam, L, Farrer, L, Heinrich, M, Huibers, MJH, Kivi, M, Kraepelien, M, Forand, NR, Pugh, N, Lindefors, N, Lintvedt, O, Zagorscak, P, Carlbring, P, Phillips, R, Johansson, R, Kessler, RC, Brabyn, S, Perini, S, Rauch, SL, Gilbody, S, Moritz, S, Berger, T, Pop, V, Kaldo, V, Spek, V, and Forsell, Y

Abstract

IMPORTANCE: Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them. OBJECTIVE: To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information. DATA SOURCES: We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019. STUDY SELECTION: Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization. DATA EXTRACTION AND SYNTHESIS: We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression. MAIN OUTCOMES AND MEASURES: Patient Health Questionnaire-9 (PHQ-9) scores. RESULTS: Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, -0.8; 95% CI, -1.4 to -0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ

Published
2021

26. Identifying determinants of diabetes risk and outcomes for people with severe mental illness: a mixed-methods study

Author

Lister, J, Han, L, Bellass, S, Taylor, J, Alderson, SL, Doran, T, Gilbody, S, Hewitt, C, Holt, RIG, Jacobs, R, Kitchen, CEW, Prady, SL, Radford, J, Ride, JR, Shiers, D, Wang, H-I, Siddiqi, N, Lister, J, Han, L, Bellass, S, Taylor, J, Alderson, SL, Doran, T, Gilbody, S, Hewitt, C, Holt, RIG, Jacobs, R, Kitchen, CEW, Prady, SL, Radford, J, Ride, JR, Shiers, D, Wang, H-I, and Siddiqi, N

Abstract

Background People with severe mental illness experience poorer health outcomes than the general population. Diabetes contributes significantly to this health gap. Objectives The objectives were to identify the determinants of diabetes and to explore variation in diabetes outcomes for people with severe mental illness. Design Under a social inequalities framework, a concurrent mixed-methods design combined analysis of linked primary care records with qualitative interviews. Setting The quantitative study was carried out in general practices in England (2000–16). The qualitative study was a community study (undertaken in the North West and in Yorkshire and the Humber). Participants The quantitative study used the longitudinal health records of 32,781 people with severe mental illness (a subset of 3448 people had diabetes) and 9551 ‘controls’ (with diabetes but no severe mental illness), matched on age, sex and practice, from the Clinical Practice Research Datalink (GOLD version). The qualitative study participants comprised 39 adults with diabetes and severe mental illness, nine family members and 30 health-care staff. Data sources The Clinical Practice Research Datalink (GOLD) individual patient data were linked to Hospital Episode Statistics, Office for National Statistics mortality data and the Index of Multiple Deprivation. Results People with severe mental illness were more likely to have diabetes if they were taking atypical antipsychotics, were living in areas of social deprivation, or were of Asian or black ethnicity. A substantial minority developed diabetes prior to severe mental illness. Compared with people with diabetes alone, people with both severe mental illness and diabetes received more frequent physical checks, maintained tighter glycaemic and blood pressure control, and had fewer recorded physical comorbidities and elective admissions, on average. However, they had more emergency admissions (incidence rate ratio 1.14, 95% confidence interval 0.96 t

Published
2021

28. Predicting prognosis for adults with depression using individual symptom data: a comparison of modelling approaches

Author

Buckman, J. E. J., primary, Cohen, Z. D., additional, O'Driscoll, C., additional, Fried, E. I., additional, Saunders, R., additional, Ambler, G., additional, DeRubeis, R. J., additional, Gilbody, S., additional, Hollon, S. D., additional, Kendrick, T., additional, Watkins, E., additional, Eley, T.C., additional, Peel, A. J., additional, Rayner, C., additional, Kessler, D., additional, Wiles, N., additional, Lewis, G., additional, and Pilling, S., additional

Published
2021
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29. Accuracy of the PHQ-2 Alone and in Combination With the PHQ-9 for Screening to Detect Major Depression: Systematic Review and Meta-analysis

Author

Levis B, Sun Y, He C, Wu Y, Krishnan A, Bhandari PM, Neupane D, Imran M, Brehaut E, Negeri Z, Fischer FH, Benedetti A, Thombs BD, Depression Screening Data (DEPRESSD) PHQ Collaboration, Che L, Levis A, Riehm K, Saadat N, Azar M, Rice D, Boruff J, Kloda L, Cuijpers P, Gilbody S, Ioannidis J, McMillan D, Patten S, Shrier I, Ziegelstein R, Moore A, Akena D, Amtmann D, Arroll B, Ayalon L, Baradaran H, Beraldi A, Bernstein C, Bhana A, Bombardier C, Buji RI, Butterworth P, Carter G, Chagas M, Chan J, Chan LF, Chibanda D, Cholera R, Clover K, Conway A, Conwell Y, Daray F, de Man-van Ginkel J, Delgadillo J, Diez-Quevedo C, Fann J, Field S, Fisher J, Fung D, Garman E, Gelaye B, Gholizadeh L, Gibson L, Goodyear-Smith F, Green E, Greeno C, Hall B, Hampel P, Hantsoo L, Haroz E, Harter M, Hegerl U, Hides L, Hobfoll S, Honikman S, Hudson M, Hyphantis T, Inagaki M, Ismail K, Jeon HJ, Jetté N, Khamseh M, Kiely K, Kohler S, Kohrt B, Kwan Y, Lamers F, Asunción Lara M, Levin-Aspenson H, Lino V, Liu S-I, Lotrakul M, Loureiro S, Löwe B, Luitel N, Lund C, Marrie RA, Marsh L, Marx B, McGuire A, Mohd Sidik S, Munhoz T, Muramatsu K, Nakku J, Navarrete L, Osório F, Patel V, Pence B, Persoons P, Petersen I, Picardi A, Pugh S, Quinn T, Rancans E, Rathod S, Reuter K, Roch S, Rooney A, Rowe H, Santos I, Schram M, Shaaban J, Shinn E, Sidebottom A, Simning A, Spangenberg L, Stafford L, Sung S, Suzuki K, Swartz R, Tan PLL, Taylor-Rowan M, Tran T, Turner A, van der Feltz-Cornelis C, van Heyningen T, van Weert H, Wagner L, Li Wang J, White J, Winkley K, Wynter K, Yamada M, Zhi Zeng Q, and Zhang Y

Subjects
Adult, Male, Depressive Disorder, Major, Patient Health Questionnaire, behavioral disciplines and activities, Sensitivity and Specificity, humanities, Interviews as Topic, ROC Curve, General & Internal Medicine, mental disorders, Humans, Mass Screening, Female, 11 Medical and Health Sciences
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.

Published
2020

30. Optimised patient information materials and recruitment to a study of behavioural activation in older adults: an embedded study within a trial [version 1; peer review: 2 approved]

Author

Knapp, P, Gilbody, S, Holt, J, Keding, A, Mitchell, N, Raynor, DK, Silcock, J, and Torgerson, DJ

Subjects
lcsh:R, lcsh:Medicine, lcsh:Q, lcsh:Science
Abstract

Background: Printed participant information about randomised controlled trials is often long, technical and difficult to navigate. Improving information materials is possible through optimisation and user-testing, and may impact on participant understanding and rates of recruitment. Methods: A study within a trial (SWAT) was undertaken within the CASPER trial. Potential CASPER participants were randomised to receive either the standard trial information or revised information that had been optimised through information design and user testing. Results: A total of 11,531 patients were randomised in the SWAT. Rates of recruitment to the CASPER trial were 2.0% in the optimised information group and 1.9% in the standard information group (odds ratio 1.027; 95% CI 0.79 to 1.33; p=0.202). Conclusions: Participant information that had been optimised through information design and user testing did not result in any change to rate of recruitment to the host trial. Registration: ISRCTN ID ISRCTN02202951; registered on 3 June 2009.

Published
2020

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

Author

Wu, Y. Levis, B. Ioannidis, J.P.A. Benedetti, A. Thombs, B.D. Sun, Y. He, C. Krishnan, A. Bhandari, P.M. Neupane, D. Negeri, Z. Imran, M. Rice, D.B. Riehm, K.E. Saadat, N. Azar, M. Levis, A.W. Sanchez, T.A. Chiovitti, M.J. Yan, X.W. Boruff, J. Kloda, L.A. Cuijpers, P. Gilbody, S. McMillan, D. Patten, S.B. Shrier, I. Ziegelstein, R.C. Comeau, L. Mitchell, N.D. Tonelli, M. Vigod, S.N. Henry, M. Ismail, Z. Loiselle, C.G. Akena, D.H. Al-Adawi, S. Alamri, S.H. Alvarado, R. Alvarado-Esquivel, C. Amtmann, D. Arroll, B. Ayalon, L. Bakare, M.O. Baradaran, H.R. Barnes, J. Bavle, A.D. Beck, C.T. Beraldi, A. Bernstein, C.N. Bhana, A. Bindt, C. Bombardier, C.H. Boyce, P.M. Büel-Drabe, N. Buji, R.I. Bunevicius, A. Butnoriene, J. Bunevicius, R. Butterworth, P. Carter, G. Chagas, M.H. Chan, J.C.N. Chan, L.F. Chaudron, L.H. Chen, C.-K. Cholera, R. Clover, K. Conroy, R.M. Conway, A. Conwell, Y. Correa, H. Castro E Couto, T. Cukor, D. Dabscheck, E. Daray, F.M. De Figueiredo, F.P. De Man-Van Ginkel, J.M. Diez-Quevedo, C. Douven, E. Downing, M.G. Eapen, V. Fann, J.R. Feinstein, A. Ferentinos, P.P. Fernandes, M. Field, S. Figueiredo, B. Fischer, F.H. Fisher, J.R.W. Flint, A.J. Fujimori, M. Fung, D.S.S. Gallagher, P. Gandy, M. Garcia-Esteve, L. Garman, E.C. Gelaye, B. Gholizadeh, L. Giardinelli, L. Gibson, L.J. Goodyear-Smith, F. Grassi, L. Green, E.P. Greeno, C.G. Hall, B.J. Hantsoo, L. Haroz, E.E. Harter, M. Hegerl, U. Helle, N. Hides, L. Hobfoll, S.E. Honikman, S. Howard, L.M. Hudson, M. Hyphantis, T. Inagaki, M. Jenewein, J. Jeon, H.J. Jette, N. Keller, M. Khalifa, D.S. Khamseh, M.E. Kiely, K.M. Kim, S.-W. Kjargaard, M. Kohler, S. Kohlhoff, J. Kohrt, B.A. Kozinszky, Z. Kusminskas, L. Kwan, Y. Lamers, F. Lara, M.A. Lelli, L. Leonardou, A.A. Levin-Aspenson, H.F. Lotrakul, M. Loureiro, S.R. Lowe, B. Luitel, N.P. Lund, C. Maes, M. Marrie, R.A. Marsh, L. Martin-Santos, R. Marx, B.P. Massardo, L. Matsuoka, Y. Mehner, A. Meuti, V. Michopoulos, I. Misery, L. Sidik, S.M. Munhoz, T.N. Muramatsu, K. Radoš, S.N. Nakku, J.E.M. Navarrete, L. Garcia, P.N. Navines, R. Nishi, D. O'Donnell, M.L. Luwa E-Andjafono, D.O. Osório, F.L. Öztürk, A. Peceliuniene, J. Pence, B.W. Persoons, P. Picardi, A. Pintor, L. Ponsford, J.L. Pugh, S.L. Quinn, T.J. Rancans, E. Rathod, S.D. Reme, S.E. Reuter, K. Robertson-Blackmore, E. Rochat, T.J. Rooney, A.G. Rowe, H.J. Sánchez-González, R. Santos, I.S. Schram, M.T. Schwarzbold, M.L. Cankorur, V.S. Shaaban, J. Sharpe, L. Shinn, E.H. Sidebottom, A. Simard, S. Simning, A. Singer, S. Siu, B.W.M. Skalkidou, A. Spangenberg, L. Stafford, L. Stein, A. Stewart, R.C. Stone, J. Su, K.-P. Sultan, S. Sundström-Poromaa, I. Sung, S.C. Suzuki, K. Tadinac, M. Tan, P.L.L. Tandon, S.D. Taylor-Rowan, M. Teixeira, A.L. Tendais, I. Thiagayson, P. Tiringer, I. Töreki, A. Torres-Giménez, A. Tran, T.D. Trevillion, K. Tung, K.-Y. Turner, A. Turner, K. Van Der Feltz-Cornelis, C.M. Van Heyningen, T. Van Weert, H.C. Vega-Dienstmaier, J.M. Vöhringer, P.A. Wagner, L.I. Walterfang, M. Wang, J.L. Wang, W. Wang, L.-J. White, J. Wong, D.K. Wynter, K. Yamada, M. Yonkers, K.A. Zeng, Q.Z. Zhang, Y. DEPRESsion Screening Data (DEPRESSD) Collaboration

Abstract

Introduction: Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results. Objective: To compare the odds of the major depression classification based on the SCID, CIDI, and MINI. Methods: We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis. Results: In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies; 25,749 participants) classified major depression more often than the SCID (108 studies; 21,953 participants; aOR 1.46; 95% confidence interval [CI] 1.11-1.92]). Classification odds for the CIDI (30 studies; 21,703 participants) and the SCID did not differ overall (aOR 1.19; 95% CI 0.79-1.75); however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64; 95% CI 0.52-0.80). Conclusions: Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics. © 2020

Published
2020

32. 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, Y. Levis, B. Sun, Y. Krishnan, A. He, C. Riehm, K.E. Rice, D.B. Azar, M. Yan, X.W. Neupane, D. Bhandari, P.M. Imran, M. Chiovitti, M.J. Saadat, N. Boruff, J.T. Cuijpers, P. Gilbody, S. McMillan, D. Ioannidis, J.P.A. Kloda, L.A. Patten, S.B. Shrier, I. Ziegelstein, R.C. Henry, M. Ismail, Z. Loiselle, C.G. Mitchell, N.D. Tonelli, M. Al-Adawi, S. Beraldi, A. Braeken, A.P.B.M. Büel-Drabe, N. Bunevicius, A. Carter, G. Chen, C.-K. Cheung, G. Clover, K. Conroy, R.M. Cukor, D. da Rocha e Silva, C.E. Dabscheck, E. Daray, F.M. Douven, E. Downing, M.G. Feinstein, A. Ferentinos, P.P. Fischer, F.H. Flint, A.J. Fujimori, M. Gallagher, P. Gandy, M. Goebel, S. Grassi, L. Härter, M. Jenewein, J. Jetté, N. Julião, M. Kim, J.-M. Kim, S.-W. Kjærgaard, M. Köhler, S. Loosman, W.L. Löwe, B. Martin-Santos, R. Massardo, L. Matsuoka, Y. Mehnert, A. Michopoulos, I. Misery, L. Navines, R. O'Donnell, M.L. Öztürk, A. Peceliuniene, J. Pintor, L. Ponsford, J.L. Quinn, T.J. Reme, S.E. Reuter, K. Rooney, A.G. Sánchez-González, R. Schwarzbold, M.L. Senturk Cankorur, V. Shaaban, J. Sharpe, L. Sharpe, M. Simard, S. Singer, S. Stafford, L. Stone, J. Sultan, S. Teixeira, A.L. Tiringer, I. Turner, A. Walker, J. Walterfang, M. Wang, L.-J. White, J. Wong, D.K. Benedetti, A. Thombs, B.D.

Abstract

Objective: Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). Methods: Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores. Results: There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96)). Conclusion: Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity. © 2019 Elsevier Inc.

Published
2020

33. The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis

Author

He, C, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Krishnan, A, Wu, Y, Sun, Y, Imran, M, Boruff, J, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, Turner, Alyna, He, C, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Krishnan, A, Wu, Y, Sun, Y, Imran, M, Boruff, J, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, and Turner, Alyna

Published
2020

34. 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, Y, Levis, B, Sun, Y, Krishnan, A, He, C, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Neupane, D, Bhandari, PM, Imran, M, Chiovitti, MJ, Saadat, N, Boruff, JT, Cuijpers, P, Gilbody, S, McMillan, D, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Tonelli, M, Al-Adawi, S, Beraldi, A, Braeken, APBM, Bueel-Drabe, N, Bunevicius, A, Carter, G, Chen, C-K, Cheung, G, Clover, K, Conroy, RM, Cukor, D, Rocha e Silva, CE, Dabscheck, E, Daray, FM, Douven, E, Downing, MG, Feinstein, A, Ferentinos, PP, Fischer, FH, Flint, AJ, Fujimori, M, Gallagher, P, Gandy, M, Goebel, S, Grassi, L, Haerter, M, Jenewein, J, Jette, N, Juliao, M, Kim, J-M, Kim, S-W, Kjaergaard, M, Kohler, S, Loosman, WL, Loewe, B, Martin-Santos, R, Massardo, L, Matsuoka, Y, Mehnert, A, Michopoulos, I, Misery, L, Navines, R, O'Donnell, ML, Ozturk, A, Peceliuniene, J, Pintor, L, Ponsford, JL, Quinn, TJ, Reme, SE, Reuter, K, Rooney, AG, Sanchez-Gonzalez, R, Schwarzbold, ML, Cankorur, VS, Shaaban, J, Sharpe, L, Sharpe, M, Simard, S, Singer, S, Stafford, L, Stone, J, Sultan, S, Teixeira, AL, Tiringer, I, Turner, A, Walker, J, Walterfang, M, Wang, L-J, White, J, Wong, DK, Benedetti, A, Thombs, BD, Wu, Y, Levis, B, Sun, Y, Krishnan, A, He, C, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Neupane, D, Bhandari, PM, Imran, M, Chiovitti, MJ, Saadat, N, Boruff, JT, Cuijpers, P, Gilbody, S, McMillan, D, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Tonelli, M, Al-Adawi, S, Beraldi, A, Braeken, APBM, Bueel-Drabe, N, Bunevicius, A, Carter, G, Chen, C-K, Cheung, G, Clover, K, Conroy, RM, Cukor, D, Rocha e Silva, CE, Dabscheck, E, Daray, FM, Douven, E, Downing, MG, Feinstein, A, Ferentinos, PP, Fischer, FH, Flint, AJ, Fujimori, M, Gallagher, P, Gandy, M, Goebel, S, Grassi, L, Haerter, M, Jenewein, J, Jette, N, Juliao, M, Kim, J-M, Kim, S-W, Kjaergaard, M, Kohler, S, Loosman, WL, Loewe, B, Martin-Santos, R, Massardo, L, Matsuoka, Y, Mehnert, A, Michopoulos, I, Misery, L, Navines, R, O'Donnell, ML, Ozturk, A, Peceliuniene, J, Pintor, L, Ponsford, JL, Quinn, TJ, Reme, SE, Reuter, K, Rooney, AG, Sanchez-Gonzalez, R, Schwarzbold, ML, Cankorur, VS, Shaaban, J, Sharpe, L, Sharpe, M, Simard, S, Singer, S, Stafford, L, Stone, J, Sultan, S, Teixeira, AL, Tiringer, I, Turner, A, Walker, J, Walterfang, M, Wang, L-J, White, J, Wong, DK, Benedetti, A, and Thombs, BD

Abstract

OBJECTIVE: Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). METHODS: Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores. RESULTS: There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96)). CONCLUSION: Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity.

Published
2020

35. Improving diabetes outcomes for people with severe mental illness : a longitudinal observational and qualitative study in England

Author

Lister, J, Han, L, Bellass, S, Taylor, J, Alderson, S, Doran, T, Gilbody, S, Hewitt, C, Holt, R, Jacobs, R, Kitchen, C, Prady, S, Radford, J, Ride, J, Shiers, D, Wang, HI, Siddiqi, N, Lister, J, Han, L, Bellass, S, Taylor, J, Alderson, S, Doran, T, Gilbody, S, Hewitt, C, Holt, R, Jacobs, R, Kitchen, C, Prady, S, Radford, J, Ride, J, Shiers, D, Wang, HI, and Siddiqi, N

Published
2020

36. The association between primary care quality and health-care use, costs and outcomes for people with serious mental illness: a retrospective observational study

Author

Jacobs, R, Aylott, L, Dare, C, Doran, T, Gilbody, S, Goddard, M, Gravelle, H, Gutacker, N, Kasteridis, P, Kendrick, T, Mason, A, Rice, N, Ride, J, Siddiqi, N, Williams, R, Jacobs, R, Aylott, L, Dare, C, Doran, T, Gilbody, S, Goddard, M, Gravelle, H, Gutacker, N, Kasteridis, P, Kendrick, T, Mason, A, Rice, N, Ride, J, Siddiqi, N, and Williams, R

Abstract

Background

Serious mental illness, including schizophrenia, bipolar disorder and other psychoses, is linked with high disease burden, poor outcomes, high treatment costs and lower life expectancy. In the UK, most people with serious mental illness are treated in primary care by general practitioners, who are financially incentivised to meet quality targets for patients with chronic conditions, including serious mental illness, under the Quality and Outcomes Framework. The Quality and Outcomes Framework, however, omits important aspects of quality.

Objectives

We examined whether or not better quality of primary care for people with serious mental illness improved a range of outcomes.

Design and setting

We used administrative data from English primary care practices that contribute to the Clinical Practice Research Datalink GOLD database, linked to Hospital Episode Statistics, accident and emergency attendances, Office for National Statistics mortality data and community mental health records in the Mental Health Minimum Data Set. We used survival analysis to estimate whether or not selected quality indicators affect the time until patients experience an outcome.

Participants

Four cohorts of people with serious mental illness, depending on the outcomes examined and inclusion criteria.

Interventions

Quality of care was measured with (1) Quality and Outcomes Framework indicators (care plans and annual physical reviews) and (2) non-Quality and Outcomes Framework indicators identified through a systematic review (antipsychotic polypharmacy and continuity of care provided by general practitioners).

Main outcome measures

Several outcomes were examined: emergency admissions for serious mental illness and ambulatory care sensitive conditions; all unplanned admissions; accident and emergency attendances; mortality; re-entry into specialist mental health services; and costs attributed to primary, secondary and community mental health c

Published
2020

37. Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis.

Author

Wu, Y, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Boruff, J, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, Akena, DH, Arroll, B, Ayalon, L, Baradaran, HR, Baron, M, Bombardier, CH, Butterworth, P, Carter, G, Chagas, MH, Chan, JCN, Cholera, R, Conwell, Y, de Man-van Ginkel, JM, Fann, JR, Fischer, FH, Fung, D, Gelaye, B, Goodyear-Smith, F, Greeno, CG, Hall, BJ, Harrison, PA, Härter, M, Hegerl, U, Hides, L, Hobfoll, SE, Hudson, M, Hyphantis, T, Inagaki, MD, Jetté, N, Khamseh, ME, Kiely, KM, Kwan, Y, Lamers, F, Liu, S-I, Lotrakul, M, Loureiro, SR, Löwe, B, McGuire, A, Mohd-Sidik, S, Munhoz, TN, Muramatsu, K, Osório, FL, Patel, V, Pence, BW, Persoons, P, Picardi, A, Reuter, K, Rooney, AG, Santos, IS, Shaaban, J, Sidebottom, A, Simning, A, Stafford, MD, Sung, S, Tan, PLL, Turner, A, van Weert, HC, White, J, Whooley, MA, Winkley, K, Yamada, M, Benedetti, A, Thombs, BD, Wu, Y, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Boruff, J, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, Akena, DH, Arroll, B, Ayalon, L, Baradaran, HR, Baron, M, Bombardier, CH, Butterworth, P, Carter, G, Chagas, MH, Chan, JCN, Cholera, R, Conwell, Y, de Man-van Ginkel, JM, Fann, JR, Fischer, FH, Fung, D, Gelaye, B, Goodyear-Smith, F, Greeno, CG, Hall, BJ, Harrison, PA, Härter, M, Hegerl, U, Hides, L, Hobfoll, SE, Hudson, M, Hyphantis, T, Inagaki, MD, Jetté, N, Khamseh, ME, Kiely, KM, Kwan, Y, Lamers, F, Liu, S-I, Lotrakul, M, Loureiro, SR, Löwe, B, McGuire, A, Mohd-Sidik, S, Munhoz, TN, Muramatsu, K, Osório, FL, Patel, V, Pence, BW, Persoons, P, Picardi, A, Reuter, K, Rooney, AG, Santos, IS, Shaaban, J, Sidebottom, A, Simning, A, Stafford, MD, Sung, S, Tan, PLL, Turner, A, van Weert, HC, White, J, Whooley, MA, Winkley, K, Yamada, M, Benedetti, A, and Thombs, BD

Abstract

BACKGROUND: Item 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most positive responses are not associated with suicidality. The PHQ-8, which omits Item 9, is thus increasingly used in research. We assessed equivalency of total score correlations and the diagnostic accuracy to detect major depression of the PHQ-8 and PHQ-9. METHODS: We conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic accuracy. RESULTS: 16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard (N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (-0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies (N = 27), with similar results for studies that used other types of interviews (N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01). CONCLUSIONS: PHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.

Published
2020

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

Author

McGrath, S, Zhao, X, Steele, R, Thombs, BD, Benedetti, A, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Sun, Y, Krishnan, A, He, C, Wu, Y, Bhandari, PM, Neupane, D, Imran, M, 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, Beraldi, A, Bombardier, CH, Butterworth, P, Carter, G, Chagas, MH, Chan, JCN, Cholera, R, Chowdhary, N, Clover, K, Conwell, Y, Ginkel, JMDM-V, Delgadillo, J, Fann, JR, Fischer, FH, Fischler, B, Fung, D, Gelaye, B, Goodyear-Smith, F, Greeno, CG, Hall, BJ, Harrison, PA, Harter, M, Hegerl, U, Hides, L, Hobfoll, SE, Hudson, M, Hyphantis, T, Inagaki, M, Ismail, K, Jette, N, Khamseh, ME, Kiely, KM, Kwan, Y, Lamers, F, Liu, S-I, Lotrakul, M, Loureiro, SR, Loewe, B, Marsh, L, McGuire, A, Sidik, SM, Munhoz, TN, Muramatsu, K, Osorio, FL, Patel, V, Pence, BW, Persoons, P, Picardi, A, Reuter, K, Rooney, AG, Santos, IS, Shaaban, J, Sidebottom, A, Simning, A, Stafford, L, Sung, SC, Tan, PLL, Turner, A, van der Feltz-Cornelis, CM, van Weert, HC, Vohringer, PA, White, J, Whooley, MA, Winkley, K, Yamada, M, Zhang, Y, McGrath, S, Zhao, X, Steele, R, Thombs, BD, Benedetti, A, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Sun, Y, Krishnan, A, He, C, Wu, Y, Bhandari, PM, Neupane, D, Imran, M, 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, Beraldi, A, Bombardier, CH, Butterworth, P, Carter, G, Chagas, MH, Chan, JCN, Cholera, R, Chowdhary, N, Clover, K, Conwell, Y, Ginkel, JMDM-V, Delgadillo, J, Fann, JR, Fischer, FH, Fischler, B, Fung, D, Gelaye, B, Goodyear-Smith, F, Greeno, CG, Hall, BJ, Harrison, PA, Harter, M, Hegerl, U, Hides, L, Hobfoll, SE, Hudson, M, Hyphantis, T, Inagaki, M, Ismail, K, Jette, N, Khamseh, ME, Kiely, KM, Kwan, Y, Lamers, F, Liu, S-I, Lotrakul, M, Loureiro, SR, Loewe, B, Marsh, L, McGuire, A, Sidik, SM, Munhoz, TN, Muramatsu, K, Osorio, FL, Patel, V, Pence, BW, Persoons, P, Picardi, A, Reuter, K, Rooney, AG, Santos, IS, Shaaban, J, Sidebottom, A, Simning, A, Stafford, L, Sung, SC, Tan, PLL, Turner, A, van der Feltz-Cornelis, CM, van Weert, HC, Vohringer, PA, White, J, Whooley, MA, Winkley, K, Yamada, M, and Zhang, Y

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

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

Author

Levis, B, Benedetti, A, Ioannidis, JPA, Sun, Y, Negeri, Z, He, C, Wu, Y, Krishnan, A, Bhandari, PM, Neupane, D, Imran, M, Rice, DB, Riehm, KE, Saadat, N, Azar, M, Boruff, J, Cuijpers, P, Gilbody, S, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, Alamri, SH, Amtmann, D, Ayalon, L, Baradaran, HR, Beraldi, A, Bernstein, CN, Bhana, A, Bombardier, CH, Carter, G, Chagas, MH, Chibanda, D, Clover, K, Conwell, Y, Diez-Quevedo, C, Fann, JR, Fischer, FH, Gholizadeh, L, Gibson, LJ, Green, EP, Greeno, CG, Hall, BJ, Haroz, EE, Ismail, K, Jetté, N, Khamseh, ME, Kwan, Y, Lara, MA, Liu, S-I, Loureiro, SR, Löwe, B, Marrie, RA, Marsh, L, McGuire, A, Muramatsu, K, Navarrete, L, Osório, FL, Petersen, I, Picardi, A, Pugh, SL, Quinn, TJ, Rooney, AG, Shinn, EH, Sidebottom, A, Spangenberg, L, Tan, PLL, Taylor-Rowan, M, Turner, A, van Weert, HC, Vöhringer, PA, Wagner, LI, White, J, Winkley, K, Thombs, BD, Levis, B, Benedetti, A, Ioannidis, JPA, Sun, Y, Negeri, Z, He, C, Wu, Y, Krishnan, A, Bhandari, PM, Neupane, D, Imran, M, Rice, DB, Riehm, KE, Saadat, N, Azar, M, Boruff, J, Cuijpers, P, Gilbody, S, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, Alamri, SH, Amtmann, D, Ayalon, L, Baradaran, HR, Beraldi, A, Bernstein, CN, Bhana, A, Bombardier, CH, Carter, G, Chagas, MH, Chibanda, D, Clover, K, Conwell, Y, Diez-Quevedo, C, Fann, JR, Fischer, FH, Gholizadeh, L, Gibson, LJ, Green, EP, Greeno, CG, Hall, BJ, Haroz, EE, Ismail, K, Jetté, N, Khamseh, ME, Kwan, Y, Lara, MA, Liu, S-I, Loureiro, SR, Löwe, B, Marrie, RA, Marsh, L, McGuire, A, Muramatsu, K, Navarrete, L, Osório, FL, Petersen, I, Picardi, A, Pugh, SL, Quinn, TJ, Rooney, AG, Shinn, EH, Sidebottom, A, Spangenberg, L, Tan, PLL, Taylor-Rowan, M, Turner, A, van Weert, HC, Vöhringer, PA, Wagner, LI, White, J, Winkley, K, and Thombs, BD

Abstract

OBJECTIVES: Depression symptom questionnaires are not for diagnostic classification. Patient Health Questionnaire-9 (PHQ-9) scores ≥10 are nonetheless often used to estimate depression prevalence. We compared PHQ-9 ≥10 prevalence to Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID) major depression prevalence and assessed whether an alternative PHQ-9 cutoff could more accurately estimate prevalence. STUDY DESIGN AND SETTING: Individual participant data meta-analysis of datasets comparing PHQ-9 scores to SCID major depression status. RESULTS: A total of 9,242 participants (1,389 SCID major depression cases) from 44 primary studies were included. Pooled PHQ-9 ≥10 prevalence was 24.6% (95% confidence interval [CI]: 20.8%, 28.9%); pooled SCID major depression prevalence was 12.1% (95% CI: 9.6%, 15.2%); and pooled difference was 11.9% (95% CI: 9.3%, 14.6%). The mean study-level PHQ-9 ≥10 to SCID-based prevalence ratio was 2.5 times. PHQ-9 ≥14 and the PHQ-9 diagnostic algorithm provided prevalence closest to SCID major depression prevalence, but study-level prevalence differed from SCID-based prevalence by an average absolute difference of 4.8% for PHQ-9 ≥14 (95% prediction interval: -13.6%, 14.5%) and 5.6% for the PHQ-9 diagnostic algorithm (95% prediction interval: -16.4%, 15.0%). CONCLUSION: PHQ-9 ≥10 substantially overestimates depression prevalence. There is too much heterogeneity to correct statistically in individual studies.

Published
2020

40. A meta-review of 'lifestyle psychiatry': the role of exercise, smoking, diet and sleep in the prevention and treatment of mental disorders

Author

Firth, J, Solmi, M, Wootton, RE, Vancampfort, D, Schuch, FB, Hoare, E, Gilbody, S, Torous, J, Teasdale, SB, Jackson, SE, Smith, L, Eaton, M, Jacka, FN, Veronese, N, Marx, W, Ashdown-Franks, G, Siskind, D, Sarris, J, Rosenbaum, S, Carvalho, AF, Stubbs, B, Firth, J, Solmi, M, Wootton, RE, Vancampfort, D, Schuch, FB, Hoare, E, Gilbody, S, Torous, J, Teasdale, SB, Jackson, SE, Smith, L, Eaton, M, Jacka, FN, Veronese, N, Marx, W, Ashdown-Franks, G, Siskind, D, Sarris, J, Rosenbaum, S, Carvalho, AF, and Stubbs, B

Abstract

There is increasing academic and clinical interest in how "lifestyle factors" traditionally associated with physical health may also relate to mental health and psychological well-being. In response, international and national health bodies are producing guidelines to address health behaviors in the prevention and treatment of mental illness. However, the current evidence for the causal role of lifestyle factors in the onset and prognosis of mental disorders is unclear. We performed a systematic meta-review of the top-tier evidence examining how physical activity, sleep, dietary patterns and tobacco smoking impact on the risk and treatment outcomes across a range of mental disorders. Results from 29 meta-analyses of prospective/cohort studies, 12 Mendelian randomization studies, two meta-reviews, and two meta-analyses of randomized controlled trials were synthesized to generate overviews of the evidence for targeting each of the specific lifestyle factors in the prevention and treatment of depression, anxiety and stress-related disorders, schizophrenia, bipolar disorder, and attention-deficit/hyperactivity disorder. Standout findings include: a) convergent evidence indicating the use of physical activity in primary prevention and clinical treatment across a spectrum of mental disorders; b) emerging evidence implicating tobacco smoking as a causal factor in onset of both common and severe mental illness; c) the need to clearly establish causal relations between dietary patterns and risk of mental illness, and how diet should be best addressed within mental health care; and d) poor sleep as a risk factor for mental illness, although with further research required to understand the complex, bidirectional relations and the benefits of non-pharmacological sleep-focused interventions. The potentially shared neurobiological pathways between multiple lifestyle factors and mental health are discussed, along with directions for future research, and recommendations for the imp

Published
2020

41. Role of age, gender and marital status in prognosis for adults with depression: An individual patient data meta-analysis

Author

Buckman, J. E. J., primary, Saunders, R., additional, Stott, J., additional, Arundell, L.-L., additional, O'Driscoll, C., additional, Davies, M. R., additional, Eley, T. C., additional, Hollon, S. D., additional, Kendrick, T., additional, Ambler, G., additional, Cohen, Z. D., additional, Watkins, E., additional, Gilbody, S., additional, Wiles, N., additional, Kessler, D., additional, Richards, D., additional, Brabyn, S., additional, Littlewood, E., additional, DeRubeis, R. J., additional, Lewis, G., additional, and Pilling, S., additional

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, B, McMillan, D, Sun, Y, He, C, Rice, DB, Krishnan, A, Wu, Y, Azar, M, Sanchez, TA, Chiovitti, MJ, Bhandari, PM, Neupane, D, Saadat, N, Riehm, KE, Imran, M, Boruff, JT, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Comeau, L, Mitchell, ND, Tonelli, M, Vigod, SN, Aceti, F, Alvarado, R, Alvarado-Esquivel, C, Bakare, MO, Barnes, J, Beck, CT, Bindt, C, Boyce, PM, Bunevicius, A, Couto, TCE, Chaudron, LH, Correa, H, de Figueiredo, FP, Eapen, V, Fernandes, M, Figueiredo, B, Fisher, JRW, Garcia-Esteve, L, Giardinelli, L, Helle, N, Howard, LM, Khalifa, DS, Kohlhoff, J, Kusminskas, L, Kozinszky, Z, Lelli, L, Leonardou, AA, Lewis, BA, Maes, M, Meuti, V, Nakić Radoš, S, Navarro García, P, Nishi, D, Okitundu Luwa E-Andjafono, D, Robertson-Blackmore, E, Rochat, TJ, Rowe, HJ, Siu, BWM, Skalkidou, A, Stein, A, Stewart, RC, Su, KP, Sundström-Poromaa, I, Tadinac, M, Tandon, SD, Tendais, I, Thiagayson, P, Töreki, A, Torres-Giménez, A, Tran, TD, Trevillion, K, Turner, K, Vega-Dienstmaier, JM, Wynter, K, Yonkers, KA, Benedetti, A, Thombs, BD, Levis, B, McMillan, D, Sun, Y, He, C, Rice, DB, Krishnan, A, Wu, Y, Azar, M, Sanchez, TA, Chiovitti, MJ, Bhandari, PM, Neupane, D, Saadat, N, Riehm, KE, Imran, M, Boruff, JT, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Comeau, L, Mitchell, ND, Tonelli, M, Vigod, SN, Aceti, F, Alvarado, R, Alvarado-Esquivel, C, Bakare, MO, Barnes, J, Beck, CT, Bindt, C, Boyce, PM, Bunevicius, A, Couto, TCE, Chaudron, LH, Correa, H, de Figueiredo, FP, Eapen, V, Fernandes, M, Figueiredo, B, Fisher, JRW, Garcia-Esteve, L, Giardinelli, L, Helle, N, Howard, LM, Khalifa, DS, Kohlhoff, J, Kusminskas, L, Kozinszky, Z, Lelli, L, Leonardou, AA, Lewis, BA, Maes, M, Meuti, V, Nakić Radoš, S, Navarro García, P, Nishi, D, Okitundu Luwa E-Andjafono, D, Robertson-Blackmore, E, Rochat, TJ, Rowe, HJ, Siu, BWM, Skalkidou, A, Stein, A, Stewart, RC, Su, KP, Sundström-Poromaa, I, Tadinac, M, Tandon, SD, Tendais, I, Thiagayson, P, Töreki, A, Torres-Giménez, A, Tran, TD, Trevillion, K, Turner, K, Vega-Dienstmaier, JM, Wynter, K, Yonkers, KA, Benedetti, A, and Thombs, BD

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. Shortening self-report mental health symptom measures through optimal test assembly methods: Development and validation of the Patient Health Questionnaire-Depression-4

Author

Ishihara, M., Harel, D., Levis, B., Levis, A.W., Riehm, K.E., Saadat, N., Azar, M., Rice, D.B., Sanchez, T.A., Chiovitti, M.J., Cuijpers, P., Gilbody, S., Ioannidis, J.P.A., Kloda, L.A., McMillan, D., Patten, S.B., Shrier, I., Arroll, B., Bombardier, C.H., Butterworth, P., Carter, G., Clover, K., Conwell, Y., Goodyear-Smith, F., Greeno, C.G., Hambridge, J., Harrison, P.A., Hudson, M., Jetté, N., Kiely, K.M., McGuire, A., Pence, B.W., Rooney, A.G., Sidebottom, A., Simning, A., Turner, A., White, J., Whooley, M.A., Winkley, K., Benedetti, A., Thombs, B.D., Ishihara, M., Harel, D., Levis, B., Levis, A.W., Riehm, K.E., Saadat, N., Azar, M., Rice, D.B., Sanchez, T.A., Chiovitti, M.J., Cuijpers, P., Gilbody, S., Ioannidis, J.P.A., Kloda, L.A., McMillan, D., Patten, S.B., Shrier, I., Arroll, B., Bombardier, C.H., Butterworth, P., Carter, G., Clover, K., Conwell, Y., Goodyear-Smith, F., Greeno, C.G., Hambridge, J., Harrison, P.A., Hudson, M., Jetté, N., Kiely, K.M., McGuire, A., Pence, B.W., Rooney, A.G., Sidebottom, A., Simning, A., Turner, A., White, J., Whooley, M.A., Winkley, K., Benedetti, A., and Thombs, B.D.

Abstract

Background: The objective of this study was to develop and validate a short form of the Patient Health Questionnaire-9 (PHQ-9), a self-report questionnaire for assessing depressive symptomatology, using objective criteria. Methods: Responses on the PHQ-9 were obtained from 7,850 English-speaking participants enrolled in 20 primary diagnostic test accuracy studies. PHQ unidimensionality was verified using confirmatory factor analysis, and an item response theory model was fit. Optimal test assembly (OTA) methods identified a maximally precise short form for each possible length between one and eight items, including and excluding the ninth item. The final short form was selected based on prespecified validity, reliability, and diagnostic accuracy criteria. Results: A four-item short form of the PHQ (PHQ-Dep-4) was selected. The PHQ-Dep-4 had a Cronbach's alpha of 0.805. Sensitivity and specificity of the PHQ-Dep-4 were 0.788 and 0.837, respectively, and were statistically equivalent to the PHQ-9 (sensitivity = 0.761, specificity = 0.866). The correlation of total scores with the full PHQ-9 was high (r = 0.919). Conclusion: The PHQ-Dep-4 is a valid short form with minimal loss of information of scores when compared to the full-length PHQ-9. Although OTA methods have been used to shorten patient-reported outcome measures based on objective, prespecified criteria, further studies are required to validate this general procedure for broader use in health research. Furthermore, due to unexamined heterogeneity, there is a need to replicate the results of this study in different patient populations.

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, B., McMillan, D., Sun, Y., He, C., Rice, D. B., Krishnan, A., Wu, Y., Azar, M., Sanchez, T. A., Chiovitti, M. J., Bhandari, P. M., Neupane, D., Saadat, N., Riehm, K. E., Imran, M., Boruff, J. T., Cuijpers, P., Gilbody, S., Ioannidis, J. P. A., ., Wynter, K., Levis, B., McMillan, D., Sun, Y., He, C., Rice, D. B., Krishnan, A., Wu, Y., Azar, M., Sanchez, T. A., Chiovitti, M. J., Bhandari, P. M., Neupane, D., Saadat, N., Riehm, K. E., Imran, M., Boruff, J. T., Cuijpers, P., Gilbody, S., Ioannidis, J. P. A., ., and Wynter, K.

Published
2019

50. Association Between Antipsychotic Polypharmacy and Outcomes for People With Serious Mental Illness in England

Author

Kasteridis, P, Ride, J, Gutacker, N, Aylott, L, Dare, C, Doran, T, Gilbody, S, Goddard, M, Gravelle, H, Kendrick, T, Mason, A, Rice, N, Siddiqi, N, Williams, R, Jacobs, R, Kasteridis, P, Ride, J, Gutacker, N, Aylott, L, Dare, C, Doran, T, Gilbody, S, Goddard, M, Gravelle, H, Kendrick, T, Mason, A, Rice, N, Siddiqi, N, Williams, R, and Jacobs, R

Abstract

OBJECTIVE: Although U.K. and international guidelines recommend monotherapy, antipsychotic polypharmacy among patients with serious mental illness is common in clinical practice. However, empirical evidence on its effectiveness is scarce. Therefore, the authors estimated the effectiveness of antipsychotic polypharmacy relative to monotherapy in terms of health care utilization and mortality. METHODS: Primary care data from Clinical Practice Research Datalink, hospital data from Hospital Episode Statistics, and mortality data from the Office of National Statistics were linked to compile a cohort of patients with serious mental illness in England from 2000 to 2014. The antipsychotic prescribing profile of 17,255 adults who had at least one antipsychotic drug record during the period of observation was constructed from primary care medication records. Survival analysis models were estimated to identify the effect of antipsychotic polypharmacy on the time to first occurrence of each of three outcomes: unplanned hospital admissions (all cause), emergency department (ED) visits, and mortality. RESULTS: Relative to monotherapy, antipsychotic polypharmacy was not associated with increased risk of unplanned hospital admission (hazard ratio [HR]=1.14; 95% confidence interval [CI]=0.98-1.32), ED visit (HR=0.95; 95% CI=0.80-1.14), or death (HR=1.02; 95% CI=0.76-1.37). Relative to not receiving antipsychotic medication, monotherapy was associated with a reduced hazard of unplanned admissions to the hospital and ED visits, but it had no effect on mortality. CONCLUSIONS: The study results support current guidelines for antipsychotic monotherapy in routine clinical practice. However, they also suggest that when clinicians have deemed antipsychotic polypharmacy necessary, health care utilization and mortality are not affected.

Published
2019

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