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Network meta-analysis in psychology and educational sciences: A systematic review of their characteristics

Network meta-analysis (NMA) allows the combination of evidence on the effectiveness of several interventions. NMA has mainly been applied in the medical science field, whereas in the domain of psychology and educational sciences its use is less frequent. Consequently, systematic reviews that describ...

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Detalles Bibliográficos
Autores principales: Fernández-Castilla, Belén, Van den Noortgate, Wim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10250269/
https://www.ncbi.nlm.nih.gov/pubmed/35821493
http://dx.doi.org/10.3758/s13428-022-01905-5
Descripción
Sumario:Network meta-analysis (NMA) allows the combination of evidence on the effectiveness of several interventions. NMA has mainly been applied in the medical science field, whereas in the domain of psychology and educational sciences its use is less frequent. Consequently, systematic reviews that describe the characteristics of published NMAs are limited to the field of medicine, and nothing is known about the characteristics of NMAs published in the psychology and educational sciences field. However, this information is still relevant for the design of future simulation studies and for detecting good and bad research practices. Thus, this study describes the features of the meta-analytic datasets of NMAs published in the field of psychology and educational sciences, as well as their methodological characteristics, and compares them to those observed in the medical domain. Results show that the number of studies included is larger in NMAs from psychology and educational sciences, the most commonly used effect size is the standardized mean difference (unlike the odds ratio in medicine), the sample size is smaller, more intervention groups are included, and inconsistent effects are observed more often. These results can be used in future simulation studies to generate realistic datasets. Finally, we warn about the poor quality of reporting of some technical aspects of the NMA, such as the statistical model used. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.3758/s13428-022-01905-5.