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Predictors of treatment dropout in self-guided web-based interventions for depression: an ‘individual patient data’ meta-analysis

Published online by Cambridge University Press:  17 April 2015

E. Karyotaki
Affiliation:
Department of Clinical psychology, Vu University Amsterdam, Amsterdam, The Netherlands EMGO, Institute of Health Care Research, Vu University Medical Centre, Amsterdam, The Netherlands
A. Kleiboer
Affiliation:
Department of Clinical psychology, Vu University Amsterdam, Amsterdam, The Netherlands EMGO, Institute of Health Care Research, Vu University Medical Centre, Amsterdam, The Netherlands
F. Smit
Affiliation:
Department of Clinical psychology, Vu University Amsterdam, Amsterdam, The Netherlands EMGO, Institute of Health Care Research, Vu University Medical Centre, Amsterdam, The Netherlands Trimbus Institute (Netherlands Institute of Mental Health and Addiction), The Netherlands
D. T. Turner
Affiliation:
Department of Clinical psychology, Vu University Amsterdam, Amsterdam, The Netherlands EMGO, Institute of Health Care Research, Vu University Medical Centre, Amsterdam, The Netherlands
A. M. Pastor
Affiliation:
Department of Psychology and Technology, Jaume University, Castellon, Spain
G. Andersson
Affiliation:
Department of Behavioural Sciences and Learning, Sweden Institute for Disability Research, Linköping; University, Sweden Department of Clinical Neuroscience, Psychiatry Section, Karolinska Institute for Disability Research, Stockholm, Sweden
T. Berger
Affiliation:
Department of Clinical Psychology and Psychotherapy, University of Bern, Bern, Switzerland
C. Botella
Affiliation:
Department of Psychology and Technology, Jaume University, Castellon, Spain CIBER Fisiopatología Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, Spain
J. M. Breton
Affiliation:
Department of Psychology and Technology, Jaume University, Castellon, Spain
P. Carlbring
Affiliation:
Department of Psychology, Stockholm University, Stockholm, Sweden
H. Christensen
Affiliation:
Black Dog Institute and University of New South Wales, Prince of Wales Hospital, Sydney, Australia
E. de Graaf
Affiliation:
Department of Clinical Psychological Science, Faculty of Psychology, Maastricht University, The Netherlands Department of Medical Psychology & Psychotherapy, Erasmus Medical Centre, Rotterdam, The Netherlands
K. Griffiths
Affiliation:
National Institute of Mental Health Research, The Australian National University, Sydney, Australia
T. Donker
Affiliation:
Department of Clinical psychology, Vu University Amsterdam, Amsterdam, The Netherlands EMGO, Institute of Health Care Research, Vu University Medical Centre, Amsterdam, The Netherlands
L. Farrer
Affiliation:
National Institute of Mental Health Research, The Australian National University, Sydney, Australia
M. J. H. Huibers
Affiliation:
Department of Clinical psychology, Vu University Amsterdam, Amsterdam, The Netherlands EMGO, Institute of Health Care Research, Vu University Medical Centre, Amsterdam, The Netherlands
J. Lenndin
Affiliation:
Department of Behavioural Sciences and Learning, Linkoping University, Linkoping, Sweden
A. Mackinnon
Affiliation:
Centre for Youth Mental Health Research, University of Melbourne, Melbourne, Australia
B. Meyer
Affiliation:
Research Department, Gaia AG, Hamburg, Germany Department of Psychology, City University, London, UK
S. Moritz
Affiliation:
Department of Psychiatry and Psychotherapy, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
H. Riper
Affiliation:
Department of Clinical psychology, Vu University Amsterdam, Amsterdam, The Netherlands EMGO, Institute of Health Care Research, Vu University Medical Centre, Amsterdam, The Netherlands
V. Spek
Affiliation:
Avans Hogeschool, University of Tilburg, Tilburg, The Netherlands
K. Vernmark
Affiliation:
Department of Behavioural Sciences and Learning, Linkoping University, Linkoping, Sweden Psykologpartners, Linkoping, Sweden
P. Cuijpers
Affiliation:
Department of Clinical psychology, Vu University Amsterdam, Amsterdam, The Netherlands EMGO, Institute of Health Care Research, Vu University Medical Centre, Amsterdam, The Netherlands
Corresponding
E-mail address:

Abstract

Background

It is well known that web-based interventions can be effective treatments for depression. However, dropout rates in web-based interventions are typically high, especially in self-guided web-based interventions. Rigorous empirical evidence regarding factors influencing dropout in self-guided web-based interventions is lacking due to small study sample sizes. In this paper we examined predictors of dropout in an individual patient data meta-analysis to gain a better understanding of who may benefit from these interventions.

Method

A comprehensive literature search for all randomized controlled trials (RCTs) of psychotherapy for adults with depression from 2006 to January 2013 was conducted. Next, we approached authors to collect the primary data of the selected studies. Predictors of dropout, such as socio-demographic, clinical, and intervention characteristics were examined.

Results

Data from 2705 participants across ten RCTs of self-guided web-based interventions for depression were analysed. The multivariate analysis indicated that male gender [relative risk (RR) 1.08], lower educational level (primary education, RR 1.26) and co-morbid anxiety symptoms (RR 1.18) significantly increased the risk of dropping out, while for every additional 4 years of age, the risk of dropping out significantly decreased (RR 0.94).

Conclusions

Dropout can be predicted by several variables and is not randomly distributed. This knowledge may inform tailoring of online self-help interventions to prevent dropout in identified groups at risk.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2015 

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