Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Огляд на основі PRISMA× | Систематичний огляд літератури× | |
|---|---|---|
| Галузь | Наукометрія | Наукометрія |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2009 (original PRISMA statement); updated 2020 | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Автор методу≠ | 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 |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви | PRISMA review, PRISMA-guided systematic review, PRISMA 2020 review, PRISMA-compliant review | SLR, systematic review, evidence synthesis review, structured literature review |
| Пов'язані | 5 | 5 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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