Article type
Year
Abstract
Background: Systematic literature searches (SLS) are a core element of systematic reviews (SR) in evidence-based medicine. Ideally, for reasons of quality assurance, they follow a strict methodology: they have not only to be comprehensive, exhaustive and error-robust, but also documented by a protocol. Main sources for systematic reviews are original works, usually published in journals and referenced in bibliographic databases. Due to systematic distortions of the literary landscape (1), clinical trial registries and grey literature as sources of information are becoming increasingly relevant in recent years. This makes searching a resource-consuming process in which the development of optimal and reproduceable search strategies with a focus on optimizing recall and precision is a crucial task (2).
Successful efforts were made to support individual steps of the LSP through text mining applications (3–7), but a systematic classification of those methods and tools in the context of search and retrieval processes is still missing (4, 5), as well as a complete framework of effective strategies in SLS (8).
Objectives: Since the 1970s a variety of models have been used to describe search processes and design information retrieval systems (9–15). Some of these were referenced in the methodology of SRs (16, 17), but they have not yet been critically verified concerning their appropriateness to describe search processes in SRs (16). Connecting the views of information and library sciences will make a sustainable contribution to the understanding of seeking and searching in SLS.
Methods: Our work bases on a comprehensive literature review on the methodology of SLS and observational studies with focus on tactics for search term identification and the development of search strategies using bibliographic databases. It presents a comparison and classification of terminologies and taxonomies of SLS’s in both research directions and combines them into a common model.
Conclusions: Our future model may be useful as a theoretical base for the development of software systems that can automate and simplify single aspects of the systematic literature searches.
Successful efforts were made to support individual steps of the LSP through text mining applications (3–7), but a systematic classification of those methods and tools in the context of search and retrieval processes is still missing (4, 5), as well as a complete framework of effective strategies in SLS (8).
Objectives: Since the 1970s a variety of models have been used to describe search processes and design information retrieval systems (9–15). Some of these were referenced in the methodology of SRs (16, 17), but they have not yet been critically verified concerning their appropriateness to describe search processes in SRs (16). Connecting the views of information and library sciences will make a sustainable contribution to the understanding of seeking and searching in SLS.
Methods: Our work bases on a comprehensive literature review on the methodology of SLS and observational studies with focus on tactics for search term identification and the development of search strategies using bibliographic databases. It presents a comparison and classification of terminologies and taxonomies of SLS’s in both research directions and combines them into a common model.
Conclusions: Our future model may be useful as a theoretical base for the development of software systems that can automate and simplify single aspects of the systematic literature searches.