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

Toshi A. Furukawa; Aya Suganuma; Edoardo G. Ostinelli; Gerhard Andersson; Christopher G. Beevers; Jason Shumake; Thomas Berger; Florien Willemijn Boele; Claudia Buntrock; Per Carlbring; Isabella Choi; Helen Christensen; Andrew Mackinnon; Jennifer Dahne; Marcus J. H. Huibers; David D. Ebert; Louise Farrer; Nicholas R. Forand; Daniel R. Strunk; Iony D. Ezawa; Erik Forsell; Viktor Kaldo; Anna Geraedts; Simon Gilbody; Elizabeth Littlewood; Sally Brabyn; Heather D. Hadjistavropoulos; Luke H. Schneider; Robert Johansson; Robin Kenter; Marie Kivi; Cecilia Bjorkelund; Annet Kleiboer; Heleen Riper; Jan Philipp Klein; Johanna Schroder; Bjorn Meyer; Steffen Moritz; Lara Bucker; Ove Lintvedt; Peter Johansson; Johan Lundgren; Jeannette Milgrom; Alan W. Gemmill; David C. Mohr; Jesus Montero-Marin; Javier Garcia-Campayo; Stephanie Nobis; Anna-Carlotta Zarski; Kathleen O'Moore; Alishia D. Williams; Jill M. Newby; Sarah Perini; Rachel Phillips; Justine Schneider; Wendy Pots; Nicole E. Pugh; Derek Richards; Isabelle M. Rosso; Scott L. Rauch; Lisa B. Sheeber; Jessica Smith; Viola Spek; Victor J. Pop; Burcin Unlu; Kim M. P. van Bastelaar; Sanne van Luenen; Nadia Garnefski; Vivian Kraaij; Kristofer Vernmark; Lisanne Warmerdam; Annemieke van Straten; Pavle Zagorscak; Christine Knaevelsrud; Manuel Heinrich; Clara Miguel; Andrea Cipriani; Orestis Efthimiou; Eirini Karyotaki; Pim Cuijpers

doi:10.1016/S2215-0366(21)00077-8

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

Toshi A. Furukawa, Aya Suganuma, Edoardo G. Ostinelli, Gerhard Andersson, Christopher G. Beevers, Jason Shumake, Thomas Berger, Florien Willemijn Boele, Claudia Buntrock, Per Carlbring, Isabella Choi, Helen Christensen, Andrew Mackinnon, Jennifer Dahne, Marcus J. H. Huibers, David D. Ebert, Louise Farrer, Nicholas R. Forand, Daniel R. Strunk, Iony D. EzawaErik Forsell, Viktor Kaldo, Anna Geraedts, Simon Gilbody, Elizabeth Littlewood, Sally Brabyn, Heather D. Hadjistavropoulos, Luke H. Schneider, Robert Johansson, Robin Kenter, Marie Kivi, Cecilia Bjorkelund, Annet Kleiboer, Heleen Riper, Jan Philipp Klein, Johanna Schroder, Bjorn Meyer, Steffen Moritz, Lara Bucker, Ove Lintvedt, Peter Johansson, Johan Lundgren, Jeannette Milgrom, Alan W. Gemmill, David C. Mohr, Jesus Montero-Marin, Javier Garcia-Campayo, Stephanie Nobis, Anna-Carlotta Zarski, Kathleen O'Moore, Alishia D. Williams, Jill M. Newby, Sarah Perini, Rachel Phillips, Justine Schneider, Wendy Pots, Nicole E. Pugh, Derek Richards, Isabelle M. Rosso, Scott L. Rauch, Lisa B. Sheeber, Jessica Smith, Viola Spek, Victor J. Pop, Burcin Unlu, Kim M. P. van Bastelaar, Sanne van Luenen, Nadia Garnefski, Vivian Kraaij, Kristofer Vernmark, Lisanne Warmerdam, Annemieke van Straten, Pavle Zagorscak, Christine Knaevelsrud, Manuel Heinrich, Clara Miguel, Andrea Cipriani, Orestis Efthimiou, Eirini Karyotaki, Pim Cuijpers

Research output: Contribution to Journal › Review article › Academic › peer-review

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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 reduced dropouts from treatment (incremental odds ratio, 0·32 [95% CrI 0·13 to 0·93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components.

Interpretation
The individual patient data cNMA revealed potentially helpful, less helpful, or harmful components and delivery formats for iCBT packages. iCBT packages aiming to be effective and efficient might choose to include beneficial components and exclude ones that are potentially detrimental. Our web app can facilitate shared decision making by therapist and patient in choosing their preferred iCBT package.

Funding
Japan Society for the Promotion of Science.

Original language	English
Pages (from-to)	500-511
Number of pages	12
Journal	The Lancet. Psychiatry
Volume	8
Issue number	6
Early online date	3 May 2021
DOIs	https://doi.org/10.1016/S2215-0366(21)00077-8
Publication status	Published - Jun 2021

Funding

TAF reports grants from Japan Society for Promotion of Science, during the conduct of the study; grants and personal fees from Mitsubishi-Tanabe, personal fees from MSD, grants and personal fees from Shionogi, outside the submitted work; a patent 2018-177688 concerning smartphone CBT apps pending; and an intellectual properties for Kokoro-app licensed to Tanabe-Mitsubishi. AC reports personal fees from Italian Network for Paediatric Trials and CARIPLO Foundation; and grants and personal fees from Angelini Pharma, outside the submitted work. EGO reports personal fees from Angelini Pharma, outside the submitted work. PCa reports personal fees from Osmond Foundation and Sandoz, outside the submitted work. JD is co-owner of Behavioral Activation Tech LLC, a small business that develops and evaluates mobile app-based treatments for depression and co-occurring disorders. DDE has served as a consultant to or on the scientific advisory boards of Sanofi, Novartis, Minddistrict, Lantern, Schoen Kliniken, Ideamed, German health insurance companies (BARMER, Techniker Krankenkasse), and a number of federal chambers for psychotherapy; is a stakeholder of the Institute for health training online (GET.ON), which aims to implement scientific findings related to digital health interventions into routine care. NRF is an employee of AbleTo. JPK reports grants and personal fees from Servier; personal fees from Beltz, Elsevier, Hogrefe, and Springer, outside the submitted work; funding for clinical trials (German Federal Ministry of Health and Servier); payments for presentations on internet interventions (Servier); and payments for workshops and books (Beltz, Elsevier, Hogrefe, and Springer) on psychotherapy for chronic depression and on psychiatric emergencies. BM is an employee of GAIA AG. DCM reports personal fees from Apple, Pear Therapeutics, and Otsuka Pharmaceuticals and has an equity interest in Adaptive Health, outside the submitted work. JMM is supported by a Wellcome Trust Grant (104908/Z/14/Z). SN is an employee of GET.ON Institut. DR is an employee of SilverCloud Health. LBS is an employee of Influents Innovations. PZ reports grants and non-financial support from Techniker Krankenkasse (German public health insurance company), outside the submitted work. CK reports personal fees from Oberbergklinik and Servier; and grants and non-financial support from Techniker Krankenkasse, outside the submitted work. MH reports grants and non-financial support from Techniker Krankenkasse, outside the submitted work. All other authors declare no competing interests. This study was supported, in part, by the Japan Society for the Promotion of Science grant-in-aid for scientific research (grant number 17K19808) to TAF. EGO is supported by the National Institute for Health Research (NIHR) Oxford Cognitive Health Clinical Research Facility and by the NIHR Oxford Health Biomedical Research Centre (grant BRC-1215-20005). JD is supported by the National Institute on Drug Abuse (NIDA K23 DA045766). HDH is supported by the Canadian Institutes of Health Research (152917). DCM is supported by grants from the National Institute of Mental Health (P50 MH119029, R01 MH111610). AC is supported by the NIHR Oxford Cognitive Health Clinical Research Facility, by an NIHR Research Professorship (grant RP-2017?08ST2?006), the NIHR Oxford and Thames Valley Applied Research Collaboration, and the NIHR Oxford Health Biomedical Research Centre (grant BRC-1215?20005). OE was supported by project grant number 180083 from the Swiss National Science Foundation. EK was supported by the Netherlands Organisation for Health Research and Development (project number 019.182SG.001). The views expressed are those of the authors and not necessarily those of any of the funding agencies listed here. This study was supported, in part, by the Japan Society for the Promotion of Science grant-in-aid for scientific research ( grant number 17K19808 ) to TAF. EGO is supported by the National Institute for Health Research (NIHR) Oxford Cognitive Health Clinical Research Facility and by the NIHR Oxford Health Biomedical Research Centre ( grant BRC-1215-20005 ). JD is supported by the National Institute on Drug Abuse ( NIDA K23 DA045766 ). HDH is supported by the Canadian Institutes of Health Research ( 152917 ). DCM is supported by grants from the National Institute of Mental Health ( P50 MH119029 , R01 MH111610 ). AC is supported by the NIHR Oxford Cognitive Health Clinical Research Facility, by an NIHR Research Professorship (grant RP-2017\u201308ST2\u2013006), the NIHR Oxford and Thames Valley Applied Research Collaboration, and the NIHR Oxford Health Biomedical Research Centre (grant BRC-1215\u201320005). OE was supported by project grant number 180083 from the Swiss National Science Foundation. EK was supported by the Netherlands Organisation for Health Research and Development (project number 019.182SG.001). The views expressed are those of the authors and not necessarily those of any of the funding agencies listed here.

Funders	Funder number
Techniker Krankenkasse
Oxford Cognitive Health Clinical Research Facility
National Institute for Health Research
Fondazione Cariplo
Wellcome Trust	104908, 104908/Z/14/Z
National Institute of Mental Health	P50MH119029, R01MH111610, 006, RP-2017, RP-2017–08ST2–006
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung	180083
Canadian Institutes of Health Research	152917
NIHR Oxford and Thames Valley	20005, BRC-1215
ZonMw	019.182SG.001
National Institute on Drug Abuse	K23DA045766
Japan Society for the Promotion of Science	17K19808
NIHR Oxford Biomedical Research Centre	BRC-1215–20005

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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., ... Cuijpers, P. (2021). Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual data: a systematic review and component network meta-analysis using individual participant data. The Lancet. Psychiatry, 8(6), 500-511. https://doi.org/10.1016/S2215-0366(21)00077-8

Furukawa, Toshi A. ; Suganuma, Aya ; Ostinelli, Edoardo G. et al. / Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual data : a systematic review and component network meta-analysis using individual participant data. In: The Lancet. Psychiatry. 2021 ; Vol. 8, No. 6. pp. 500-511.

@article{07f8be7e70824185b7a3aa2c3cb0ba0b,

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

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 reduced dropouts from treatment (incremental odds ratio, 0·32 [95\% CrI 0·13 to 0·93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. Interpretation The individual patient data cNMA revealed potentially helpful, less helpful, or harmful components and delivery formats for iCBT packages. iCBT packages aiming to be effective and efficient might choose to include beneficial components and exclude ones that are potentially detrimental. Our web app can facilitate shared decision making by therapist and patient in choosing their preferred iCBT package. Funding Japan Society for the Promotion of Science.",

author = "Furukawa, \{Toshi A.\} and Aya Suganuma and Ostinelli, \{Edoardo G.\} and Gerhard Andersson and Beevers, \{Christopher G.\} and Jason Shumake and Thomas Berger and Boele, \{Florien Willemijn\} and Claudia Buntrock and Per Carlbring and Isabella Choi and Helen Christensen and Andrew Mackinnon and Jennifer Dahne and Huibers, \{Marcus J. H.\} and Ebert, \{David D.\} and Louise Farrer and Forand, \{Nicholas R.\} and Strunk, \{Daniel R.\} and Ezawa, \{Iony D.\} and Erik Forsell and Viktor Kaldo and Anna Geraedts and Simon Gilbody and Elizabeth Littlewood and Sally Brabyn and Hadjistavropoulos, \{Heather D.\} and Schneider, \{Luke H.\} and Robert Johansson and Robin Kenter and Marie Kivi and Cecilia Bjorkelund and Annet Kleiboer and Heleen Riper and Klein, \{Jan Philipp\} and Johanna Schroder and Bjorn Meyer and Steffen Moritz and Lara Bucker and Ove Lintvedt and Peter Johansson and Johan Lundgren and Jeannette Milgrom and Gemmill, \{Alan W.\} and Mohr, \{David C.\} and Jesus Montero-Marin and Javier Garcia-Campayo and Stephanie Nobis and Anna-Carlotta Zarski and Kathleen O'Moore and Williams, \{Alishia D.\} and Newby, \{Jill M.\} and Sarah Perini and Rachel Phillips and Justine Schneider and Wendy Pots and Pugh, \{Nicole E.\} and Derek Richards and Rosso, \{Isabelle M.\} and Rauch, \{Scott L.\} and Sheeber, \{Lisa B.\} and Jessica Smith and Viola Spek and Pop, \{Victor J.\} and Burcin Unlu and \{van Bastelaar\}, \{Kim M. P.\} and \{van Luenen\}, Sanne and Nadia Garnefski and Vivian Kraaij and Kristofer Vernmark and Lisanne Warmerdam and \{van Straten\}, Annemieke and Pavle Zagorscak and Christine Knaevelsrud and Manuel Heinrich and Clara Miguel and Andrea Cipriani and Orestis Efthimiou and Eirini Karyotaki and Pim Cuijpers",

year = "2021",

month = jun,

doi = "10.1016/S2215-0366(21)00077-8",

language = "English",

volume = "8",

pages = "500--511",

journal = "The Lancet. Psychiatry",

issn = "2215-0374",

publisher = "Elsevier Ltd",

number = "6",

}

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 2021, 'Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual data: a systematic review and component network meta-analysis using individual participant data', The Lancet. Psychiatry, vol. 8, no. 6, pp. 500-511. https://doi.org/10.1016/S2215-0366(21)00077-8

Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual data: a systematic review and component network meta-analysis using individual participant data. / Furukawa, Toshi A.; Suganuma, Aya; Ostinelli, Edoardo G. et al.
In: The Lancet. Psychiatry, Vol. 8, No. 6, 06.2021, p. 500-511.

Research output: Contribution to Journal › Review article › Academic › peer-review

TY - JOUR

T1 - Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual data

T2 - a systematic review and component network meta-analysis using individual participant data

AU - Furukawa, Toshi A.

AU - Suganuma, Aya

AU - Ostinelli, Edoardo G.

AU - Andersson, Gerhard

AU - Beevers, Christopher G.

AU - Shumake, Jason

AU - Berger, Thomas

AU - Boele, Florien Willemijn

AU - Buntrock, Claudia

AU - Carlbring, Per

AU - Choi, Isabella

AU - Christensen, Helen

AU - Mackinnon, Andrew

AU - Dahne, Jennifer

AU - Huibers, Marcus J. H.

AU - Ebert, David D.

AU - Farrer, Louise

AU - Forand, Nicholas R.

AU - Strunk, Daniel R.

AU - Ezawa, Iony D.

AU - Forsell, Erik

AU - Kaldo, Viktor

AU - Geraedts, Anna

AU - Gilbody, Simon

AU - Littlewood, Elizabeth

AU - Brabyn, Sally

AU - Hadjistavropoulos, Heather D.

AU - Schneider, Luke H.

AU - Johansson, Robert

AU - Kenter, Robin

AU - Kivi, Marie

AU - Bjorkelund, Cecilia

AU - Kleiboer, Annet

AU - Riper, Heleen

AU - Klein, Jan Philipp

AU - Schroder, Johanna

AU - Meyer, Bjorn

AU - Moritz, Steffen

AU - Bucker, Lara

AU - Lintvedt, Ove

AU - Johansson, Peter

AU - Lundgren, Johan

AU - Milgrom, Jeannette

AU - Gemmill, Alan W.

AU - Mohr, David C.

AU - Montero-Marin, Jesus

AU - Garcia-Campayo, Javier

AU - Nobis, Stephanie

AU - Zarski, Anna-Carlotta

AU - O'Moore, Kathleen

AU - Williams, Alishia D.

AU - Newby, Jill M.

AU - Perini, Sarah

AU - Phillips, Rachel

AU - Schneider, Justine

AU - Pots, Wendy

AU - Pugh, Nicole E.

AU - Richards, Derek

AU - Rosso, Isabelle M.

AU - Rauch, Scott L.

AU - Sheeber, Lisa B.

AU - Smith, Jessica

AU - Spek, Viola

AU - Pop, Victor J.

AU - Unlu, Burcin

AU - van Bastelaar, Kim M. P.

AU - van Luenen, Sanne

AU - Garnefski, Nadia

AU - Kraaij, Vivian

AU - Vernmark, Kristofer

AU - Warmerdam, Lisanne

AU - van Straten, Annemieke

AU - Zagorscak, Pavle

AU - Knaevelsrud, Christine

AU - Heinrich, Manuel

AU - Miguel, Clara

AU - Cipriani, Andrea

AU - Efthimiou, Orestis

AU - Karyotaki, Eirini

AU - Cuijpers, Pim

PY - 2021/6

Y1 - 2021/6

N2 - 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 reduced dropouts from treatment (incremental odds ratio, 0·32 [95% CrI 0·13 to 0·93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. Interpretation The individual patient data cNMA revealed potentially helpful, less helpful, or harmful components and delivery formats for iCBT packages. iCBT packages aiming to be effective and efficient might choose to include beneficial components and exclude ones that are potentially detrimental. Our web app can facilitate shared decision making by therapist and patient in choosing their preferred iCBT package. Funding Japan Society for the Promotion of Science.

AB - 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 reduced dropouts from treatment (incremental odds ratio, 0·32 [95% CrI 0·13 to 0·93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. Interpretation The individual patient data cNMA revealed potentially helpful, less helpful, or harmful components and delivery formats for iCBT packages. iCBT packages aiming to be effective and efficient might choose to include beneficial components and exclude ones that are potentially detrimental. Our web app can facilitate shared decision making by therapist and patient in choosing their preferred iCBT package. Funding Japan Society for the Promotion of Science.

UR - https://www.scopus.com/pages/publications/85107088551

UR - https://www.scopus.com/inward/citedby.url?scp=85107088551&partnerID=8YFLogxK

U2 - 10.1016/S2215-0366(21)00077-8

DO - 10.1016/S2215-0366(21)00077-8

M3 - Review article

SN - 2215-0374

VL - 8

SP - 500

EP - 511

JO - The Lancet. Psychiatry

JF - The Lancet. Psychiatry

IS - 6

ER -

Furukawa TA, Suganuma A, Ostinelli EG, Andersson G, Beevers CG, Shumake J et al. Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual data: a systematic review and component network meta-analysis using individual participant data. The Lancet. Psychiatry. 2021 Jun;8(6):500-511. Epub 2021 May 3. doi: 10.1016/S2215-0366(21)00077-8

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

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