From living systematic reviews to meta-analytical research domains

被引:18
|
作者
Cuijpers, Pim [1 ,2 ]
Miguel, Clara [1 ]
Papola, Davide [3 ]
Harrer, Mathias [4 ,5 ]
Karyotaki, Eirini [1 ]
机构
[1] Vrije Univ, Amsterdam Publ Hlth Res Inst, Dept Clin Neuro & Dev Psychol, Amsterdam, Netherlands
[2] Babes Bolyai Univ, Int Inst Psychotherapy, Cluj Napoca, Romania
[3] Univ Verona, WHO Collaborating Ctr Res & Training Mental Hlth, Dept Neurosci Biomed & Movement Sci, Verona, Italy
[4] Friedrich Alexander Univ Erlangen, Dept Clin Psychol & Psychotherapy, Nurnberg, Germany
[5] Tech Univ Munich, Dept Hlth Sci, Psychol & Digital Mental Hlth Care, Munich, Germany
关键词
adult psychiatry; depression & mood disorders; SERIES; METAANALYSIS; DEPRESSION; SCIENCE; DECADES;
D O I
10.1136/ebmental-2022-300509
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
Because of the rapidly increasing number of randomised controlled trials (RCTs) and meta-analyses in many fields, there is an urgent need to step up from meta-analyses to higher levels of aggregation of outcomes of RCTs. Network meta-analyses and umbrella reviews allow higher levels of aggregation of RCT outcomes, but cannot adequately cover the evidence for a whole field. The 'Meta-Analytic Research Domain' (MARD) may be a new methodology to aggregate RCT data of a whole field. A MARD is a living systematic review of a research domain that cannot be covered by one PICO. For example, a MARD of psychotherapy for depression covers all RCTs comparing the effects of all types of psychotherapy to control conditions, to each other, to pharmacotherapy and combined treatment. It also covers all RCTs comparing treatment formats, the effects in different target groups, subtypes of depression and secondary outcomes. Although the time and resources needed to build a MARD are considerable, they offer many advantages, including a comprehensive and consistent overview of a research field and important meta-analytic studies that cannot be conducted with conventional methods. MARDs are a promising method to step up the aggregation of RCTs to a next level and it is highly relevant to work out the methods of this approach in a more detailed way.
引用
收藏
页码:145 / 147
页数:3
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