B van Oosterhout1, F Smit2, L Krabbendam3, S Castelein4, A B P Staring5, M van der Gaag6. 1. GGzE,De Woenselse Poort,PO Box 909,Eindhoven,The Netherlands. 2. Trimbos Institute (Netherlands Institute of Mental Health and Addiction),PO Box 725,Utrecht,The Netherlands. 3. Department of Educational Neuroscience and Research Institute Learn!,Faculty of Psychology and Education,VU University,Van der Boechorststraat 1,Amsterdam,The Netherlands. 4. Lentis Psychiatric Institute,Lentis Research,PO Box 86,Groningen,The Netherlands. 5. Altrecht Psychiatric Institute,Mimosastraat 2-4,Utrecht,The Netherlands. 6. Department of Clinical Psychology,EMGO Institute for Health and Care Research,VU University,PO Box 7057,Amsterdam,The Netherlands.
Abstract
BACKGROUND: Metacognitive training (MCT) for schizophrenia spectrum is widely implemented. It is timely to systematically review the literature and to conduct a meta-analysis. METHOD: Eligible studies were selected from several sources (databases and expert suggestions). Criteria included comparative studies with a MCT condition measuring positive symptoms and/or delusions and/or data-gathering bias. Three meta-analyses were conducted on data gathering (three studies; 219 participants), delusions (seven studies; 500 participants) and positive symptoms (nine studies; 436 participants). Hedges' g is reported as the effect size of interest. Statistical power was sufficient to detect small to moderate effects. RESULTS: All analyses yielded small non-significant effect sizes (0.26 for positive symptoms; 0.22 for delusions; 0.31 for data-gathering bias). Corrections for publication bias further reduced the effect sizes to 0.21 for positive symptoms and to 0.03 for delusions. In blinded studies, the corrected effect sizes were 0.22 for positive symptoms and 0.03 for delusions. In studies using proper intention-to-treat statistics the effect sizes were 0.10 for positive symptoms and -0.02 for delusions. The moderate to high heterogeneity in most analyses suggests that processes other than MCT alone have an impact on the results. CONCLUSIONS: The studies so far do not support a positive effect for MCT on positive symptoms, delusions and data gathering. The methodology of most studies was poor and sensitivity analyses to control for methodological flaws reduced the effect sizes considerably. More rigorous research would be helpful in order to create enough statistical power to detect small effect sizes and to reduce heterogeneity. Limitations and strengths are discussed.
BACKGROUND: Metacognitive training (MCT) for schizophrenia spectrum is widely implemented. It is timely to systematically review the literature and to conduct a meta-analysis. METHOD: Eligible studies were selected from several sources (databases and expert suggestions). Criteria included comparative studies with a MCT condition measuring positive symptoms and/or delusions and/or data-gathering bias. Three meta-analyses were conducted on data gathering (three studies; 219 participants), delusions (seven studies; 500 participants) and positive symptoms (nine studies; 436 participants). Hedges' g is reported as the effect size of interest. Statistical power was sufficient to detect small to moderate effects. RESULTS: All analyses yielded small non-significant effect sizes (0.26 for positive symptoms; 0.22 for delusions; 0.31 for data-gathering bias). Corrections for publication bias further reduced the effect sizes to 0.21 for positive symptoms and to 0.03 for delusions. In blinded studies, the corrected effect sizes were 0.22 for positive symptoms and 0.03 for delusions. In studies using proper intention-to-treat statistics the effect sizes were 0.10 for positive symptoms and -0.02 for delusions. The moderate to high heterogeneity in most analyses suggests that processes other than MCT alone have an impact on the results. CONCLUSIONS: The studies so far do not support a positive effect for MCT on positive symptoms, delusions and data gathering. The methodology of most studies was poor and sensitivity analyses to control for methodological flaws reduced the effect sizes considerably. More rigorous research would be helpful in order to create enough statistical power to detect small effect sizes and to reduce heterogeneity. Limitations and strengths are discussed.
Authors: D J Hauke; V Roth; P Karvelis; R A Adams; S Moritz; S Borgwardt; A O Diaconescu; C Andreou Journal: Schizophr Bull Date: 2022-06-21 Impact factor: 7.348
Authors: Philippa A Garety; Thomas Ward; Daniel Freeman; David Fowler; Richard Emsley; Graham Dunn; Elizabeth Kuipers; Paul Bebbington; Helen Waller; Kathryn Greenwood; Mar Rus-Calafell; Alison McGourty; Amy Hardy Journal: Trials Date: 2017-11-02 Impact factor: 2.279