Porovnať metódy
Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.
| Scoping Review asistovaná VOSviewerom× | Systematický prehľad literatúry× | |
|---|---|---|
| Odbor | Scientometria | Scientometria |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | 2010s–present | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Tvorca≠ | Combination: Arksey & O'Malley (scoping review, 2005); van Eck & Waltman (VOSviewer, 2010) | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Typ≠ | Hybrid review methodology | Evidence synthesis methodology |
| Pôvodný zdroj≠ | van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. DOI ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Ďalšie názvy | VOSviewer scoping review, bibliometric-enhanced scoping review, VOS-assisted scoping review, science-mapping scoping review | SLR, systematic review, evidence synthesis review, structured literature review |
| Príbuzné | 5 | 5 |
| Zhrnutie≠ | A VOSviewer-assisted scoping review integrates the structured, broad-mapping purpose of a scoping review with VOSviewer's bibliometric visualization capabilities. After standard database searching and eligibility screening, the retained records are exported to VOSviewer, which produces co-authorship, keyword co-occurrence, and citation-based cluster maps. These visual outputs guide thematic synthesis, reveal intellectual structure, and make the scope of a field immediately transparent. | 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. |
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