قارن الطرق

	مراجعة منهجية قائمة على بروتوكول	مراجعة الأدبيات المنهجية
المجال	القياسات العلمية	القياسات العلمية
العائلة	Process / pipeline	Process / pipeline
سنة النشأة	1990s–2015 (Cochrane Handbook 1st ed. 1994; PRISMA-P 2015)	1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines)
صاحب الطريقة	Cochrane Collaboration; Moher et al. (PRISMA-P)	Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004)
النوع	Evidence synthesis method with pre-specified protocol	Evidence synthesis methodology
المصدر التأسيسي	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	Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401.
الأسماء البديلة	protocol-registered SLR, pre-registered systematic review, PROSPERO-registered systematic review, protocol-driven systematic review	SLR, systematic review, evidence synthesis review, structured literature review
ذات صلة	5	5
الملخص	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.