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| Ulasan Pantas× | Tinjauan Literatur Sistematik× | |
|---|---|---|
| Bidang | Saintometrik | Saintometrik |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 2000s (rapidly adopted after 2005; Cochrane guidance 2020–2021) | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Pengasas≠ | Developed and formalised by health technology assessment agencies and the Cochrane Collaboration | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Jenis≠ | Evidence synthesis review | Evidence synthesis methodology |
| Sumber perintis≠ | Garritty, C., Gartlehner, G., Nussbaumer-Streit, B., King, V. J., Hamel, C., Kamel, C., Affengruber, L., & Stevens, A. (2021). Cochrane Rapid Reviews Methods Group offers evidence-informed guidance to conduct rapid reviews. Journal of Clinical Epidemiology, 130, 13–22. DOI ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Alias | rapid evidence review, accelerated systematic review, rapid evidence assessment, REA | SLR, systematic review, evidence synthesis review, structured literature review |
| Berkaitan | 5 | 5 |
| Ringkasan≠ | A rapid review is a streamlined form of systematic review that deliberately simplifies or omits certain steps — such as dual screening, exhaustive grey-literature search, or full risk-of-bias assessment — in order to deliver timely, policy-relevant evidence synthesis within weeks rather than years. It is increasingly used by health agencies, governments, and organisations facing urgent decision-making needs where a full systematic review is not feasible within the available time and resources. | 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. |
| ScholarGateSet data ↗ |
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