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Dismantling, personalising and optimising internet cognitive–behavioural therapy for depression: a study protocol for individual participant data component network meta-analysis
  1. Toshi A Furukawa1,
  2. Eirini Karyotaki2,
  3. Aya Suganuma1,3,
  4. Alessandro Pompoli4,
  5. Edoardo G Ostinelli5,
  6. Andrea Cipriani6,7,
  7. Pim Cuijpers2,3,
  8. Orestis Efthimiou8
  1. 1 Departments of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine/ School of Public Health, Kyoto, Japan
  2. 2 Department of Clinical, Neuro-, and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
  3. 3 Amsterdam Public Health research institute, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam, The Netherlands
  4. 4 Psychiatric Rehabilitation Clinic Villa San Pietro, Trento, Italy
  5. 5 Department of Health Sciences, University of Milan, Milan, Italy
  6. 6 Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
  7. 7 Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
  8. 8 Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland
  1. Correspondence to Professor Pim Cuijpers; p.cuijpers{at}vu.nl

Abstract

Introduction Psychotherapy is a complex intervention, consisting of various components and being implemented flexibly in consideration of individual patient’s characteristics. It is then of utmost importance to know which of the various components or combinations thereof are more efficacious, what their specific effect sizes are and which types of patients may benefit more from different components or their combinations.

Methods and analysis Internet-delivered cognitive–behavioural therapy (iCBT) offers a unique opportunity to systematically review and quantitatively disentangle the efficacy of various components because, unlike face-to-face cognitive–behavioural therapy, it allows identification of constituent components that are actually delivered to patients. We will systematically identify all randomised controlled trials that compared any form of iCBT against another form or a control intervention in the acute phase treatment of adult depression. We will apply component network meta-analysis (cNMA) to dismantle efficacy of individual components. We will use individual participant data in the cNMA to identify participant-level prognostic factors and effect modifiers for different components.

Ethics and dissemination The investigators of the primary trials will have obtained ethical approval for the data used in the present study and for sharing the data, if this was necessary, according to local requirements and was not covered from the initial ethic assessment. Results from this study will be published in peer-reviewed journals and presented at relevant conferences.

PROSPERO registration number CRD42018104683.

  • depressive disorder
  • internet-delivered cognitive-behavioral therapy
  • network meta-analysis
  • individual participant data meta-analysis

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Footnotes

  • TAF and EK contributed equally.

  • Contributors TAF and OE conceived the study. TAF, EK, PC and OE designed the study. TAF, EK and OE drafted the protocol, and AS, AP, EGO, AC and PC critically revised it. EK and PC have conducted the original study search, and AS, AP and EGO will search results for inclusion and conduct data extraction. TAF and AC will assist with data extraction. EK, PC and TAF will build the individual participant dataset. OE will conduct the analyses. AS will draft the final manuscript, and all authors will critically revise it. All authors have contributed to and have approved the final protocol paper.

  • Funding This work is supported in part by JSPS Grant-in-Aid for Scientific Research (Grant Number 17K19808) and by a grant-in-aid from Japan Agency for Medical Research and Development (AMED) (Grant Number JP18dk0307072) to TAF.

  • Competing interests TAF has received lecture fees from Meiji, Mitsubishi-Tanabe, MSD and Pfizer. He has received research support from Mitsubishi-Tanabe. He has a patent 2018-177688 pending. All the other authors report no conflict of interest.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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