Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Обзор на основе PRISMA× | Систематический обзор литературы× | |
|---|---|---|
| Область | Наукометрия | Наукометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2009 (original PRISMA statement); updated 2020 | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Автор метода≠ | David Moher and PRISMA Group | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Тип≠ | Structured reporting framework for systematic reviews | Evidence synthesis methodology |
| Основополагающий источник≠ | Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, n71. DOI ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Другие названия | PRISMA review, PRISMA-guided systematic review, PRISMA 2020 review, PRISMA-compliant review | SLR, systematic review, evidence synthesis review, structured literature review |
| Связанные | 5 | 5 |
| Сводка≠ | A PRISMA-based review is a systematic literature review conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Originally published by Moher et al. in 2009 and updated as PRISMA 2020 by Page et al., the framework specifies a 27-item checklist and a four-phase flow diagram covering identification, screening, eligibility, and inclusion — ensuring full transparency and reproducibility in the review process. | A systematic literature review (SLR) is a structured, reproducible method for identifying, appraising, and synthesizing all relevant studies on a research question. Unlike a narrative review, it follows an explicit, pre-specified protocol — from database search strings through inclusion criteria to data extraction — so that the process is transparent, auditable, and replicable by other researchers. It is widely used in medicine, education, software engineering, and the social sciences to produce the most comprehensive possible evidence base on a topic. |
| ScholarGateНабор данных ↗ |
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