Sudden gains have been shown to be a common phenomenon and an important predictor of outcome in psychotherapy (Tang & DeRubeis, 1999). The present meta-analysis examined the growing literature on sudden gains in psychotherapy, their effects on outcome, and moderators of these effects. We searched PsycINFO, PubMed, ProQuest Dissertations & Theses, Scholar and Web of Science databases for articles between January 1st 1999 and May 31st 2019 and included 50 studies (n = 6355) in the meta-analysis. Sudden gains were found to significantly predict outcome at post-treatment (g = 0.68) and follow up (g = 0.61) above and beyond treatments, disorders and settings. Studies using Tang and DeRubies's (1999) criteria for identification of sudden gains had smaller effect sizes compared to studies using altered criteria. Pretreatment severity levels did not significantly predict the effects of sudden gains and neither did treatment setting (randomized controlled trials vs. naturalistic settings). Finally, number of sessions and sudden gains' reversal rates were both negatively associated with the effect sizes of sudden gains. These findings suggest that sudden gains are a ubiquitous phenomenon in psychotherapy but their effects may be moderated by a number of factors. Research and clinical implications are discussed.

A meta-analysis of sudden gains in psychotherapy: Outcome and moderators.

Analysis of rare binary events is an important problem for biomedical researchers. Due to the sparsity of events in such problems, meta-analysis that integrates information across multiple studies can be applied to increase the efficiency of statistical inference. Although it is critical to examine whether the effect sizes are homogeneous across all studies, a comprehensive review of homogeneity tests has been lacking, and in particular, no attention has been paid to infrequent dichotomous outcomes. We systematically review statistical methods for homogeneity testing. By conducting an extensive simulation analysis and two case studies, we examine the performance of 30 tests in meta-analysis of rare binary outcomes. When using log-odds ratio as the association measure, our simulation results suggest that there is no uniform winner. However, we recommend the test proposed by Kulinskaya and Dollinger (BMC Med Res Methodol, 2015, 15), which uses a gamma distribution to approximate the null distribution, for its generally good performance; for very rare events coupled with small within-study sample sizes, in addition to the Kulinskaya-Dollinger test, we further recommend the conditional score test based on the random-effects hypergeometric model proposed by Liang and Self (Biometrika, 1985, 72:353-358). One should be cautious about the use of the Wald tests, the Lipsitz tests (Biometrics, 1998, 54:148-160), and tests proposed by Bhaumik et al (J Am Stat Assoc, 2012, 107:555-567).

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