方法对比
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| 基于方案的系统性文献综述× | 系统性文献综述× | |
|---|---|---|
| 领域 | 科学计量学 | 科学计量学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2015 (Cochrane Handbook 1st ed. 1994; PRISMA-P 2015) | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| 提出者≠ | Cochrane Collaboration; Moher et al. (PRISMA-P) | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| 类型≠ | Evidence synthesis method with pre-specified protocol | Evidence synthesis methodology |
| 开创性文献≠ | Higgins, J. P. T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. A. (Eds.). (2023). Cochrane Handbook for Systematic Reviews of Interventions (Version 6.4). Cochrane. Retrieved from https://training.cochrane.org/handbook link ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| 别名 | protocol-registered SLR, pre-registered systematic review, PROSPERO-registered systematic review, protocol-driven systematic review | SLR, systematic review, evidence synthesis review, structured literature review |
| 相关 | 5 | 5 |
| 摘要≠ | A protocol-based systematic literature review is a systematic review conducted according to a fully pre-specified and publicly registered research protocol. By committing the review question, eligibility criteria, search strategy, and planned analyses to a registered document before data collection begins, this approach minimises post-hoc decision-making, selective outcome reporting, and the accumulation bias that can undermine the credibility of unregistered reviews. Registration platforms such as PROSPERO and the Open Science Framework provide permanent, time-stamped records of the protocol. | 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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