• Janke Oosterhaven, Harriet Wittink, Jurgen Mollema, Cas Kruitwagen, and Walter Devillé.
• Research Group Lifestyle and Health, University of Applied Sciences Utrecht, 3584 CS Utrecht, The Netherlands. janke.oosterhaven@hu.nl.
• J Rehabil Med. 2019 Jan 1; 51 (1): 2-10.

ObjectiveSystematic review to identify predictors for dropout during interdisciplinary pain management programmes.Data SourcesPubMed, PsycINFO, CINAHL, Embase, and SPORTDiscus were searched from inception to 22 June 2017.Study SelectionScreening, data-extraction and quality assessment was carried out independently by 2 researchers.Data SynthesisEight studies with low methodological quality were included in this review. Out of 63 potential predictors identified in univariate analyses, significant results were found for 18 predictors of dropout in multiple logistic regression analyses in 4 domains, as described by Meichenbaum & Turk: (i) sociodemographic domain (2); (ii) patient domain (8); (iii) disease domain (6); and (iv) treatment domain (2).ConclusionThis systematic review presents an overview of predictors of dropout. The literature with regard to the prediction of dropout has focused mainly on patient characteristics and is still in the stage of model development. Future research should focus on therapist/therapy-related predictors and the interaction between these predictors. This review suggests future research on this topic, in order to generate better outcomes in interdisciplinary pain management programmes.

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