A step by step guide for conducting a systematic review and meta-analysis with simulation data
Ain Shams University · Online Technologies (United States) · +7 more institutions
Abstract
The massive abundance of studies relating to tropical medicine and health has increased strikingly over the last few decades. In the field of tropical medicine and health, a well-conducted systematic review and meta-analysis (SR/MA) is considered a feasible solution for keeping clinicians abreast of current evidence-based medicine. Understanding of SR/MA steps is of paramount importance for its conduction. It is not easy to be done as there are obstacles that could face the researcher. To solve those hindrances, this methodology study aimed to provide a step-by-step approach mainly for beginners and junior researchers, in the field of tropical medicine and other health care fields, on how to properly conduct a SR/MA, in which all the steps here depicts our experience and expertise combined with the already well-known and accepted international guidance.We suggest that all steps of SR/MA should be done independently by 2-3 reviewers' discussion, to ensure data quality and accuracy.
SR/MA steps include the development of research question, forming criteria, search strategy, searching databases, protocol registration, title, abstract, full-text screening, manual searching, extracting data, quality assessment, data checking, statistical analysis, double data checking, and manuscript writing.
Citation impact
- FWCI
- 41.45
- Percentile
- 100%
- References
- 24
Authors
7- GMGehad Mohamed Tawfik
Ain Shams University, Online Technologies (United States)
- KAKadek Agus Surya Dila
Online Technologies (United States), Universitas Panji Sakti
- MYMuawia Yousif Fadlelmola Mohamed
University of Khartoum, Online Technologies (United States)
- DNDao Ngoc Hien Tam
Online Technologies (United States), Pharmaceutical Biotechnology (Czechia)
- NDNguyen Dang Kien
Online Technologies (United States), Thai Binh University of Medicine and Pharmacy
Topics & keywords
- Field (mathematics)
- Computer science
- Protocol (science)
- Data science
- Quality (philosophy)
- Data quality
- Health care
- Management science