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

Karyotaki, E.; Kleiboer, A.; Smit, F.; Turner, D. T.; Pastor, A. M.; Andersson, G.; Berger, T.; Botella, C.; Breton, J. M.; Carlbring, P.; Christensen, H.; de Graaf, E.; Griffiths, Kathleen M; Donker, T.; Farrer, L.; Huibers, M. J. H.; Lenndin, J.; Mackinnon, A.; Meyer, B.; Moritz, S.; Riper, H.; Spek, V.; Vernmark, K.; Cuijpers, P.


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...[Show more]

CollectionsANU Research Publications
Date published: 2015-10
Type: Journal article
Source: Psychological Medicine
DOI: 10.1017/S0033291715000665


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