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15 Búsqueda de los artículos

Qué bases de datos utilizar

En Which academic search systems are suitable for systematic reviews or meta-analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources (2020) se puede leer:

To date, it remains unclear which search systems are most appropriate for evidence synthesis and why. Advice on which search engines and bibliographic databases to choose for systematic searches is limited and lacking systematic, empirical performance assessments.

Según este estudio, Google Scholar no es un buen buscador de artículos científicos:

Nevertheless, overall, Google Scholar's search precision has been found to be significantly lower than 1% for systematic searches [25]. This is not surprising, since our findings show that Google Scholar does not support many of the features required for systematic searches. Our findings support the criticism of Bramer et al [33], Bramer et al [34], and Boeker et al [25] and indicate that Google Scholar's coverage and recall is an inadequate reason to use it as principal search system in systematic searches [53]. If a system such as Google Scholar fails to deliver retrieval capabilities that allow a reviewer to search systematically with high levels of recall, precision, transparency, and reproducibility, its coverage is irrelevant for query-based search. Google Scholar's extraordinary coverage acting as a multidisciplinary compendium of scientific world knowledge should not blind users to the fact that users' ability to access this compendium is severely limited, especially in terms of a systematic search.

En Improving the Reliability of Literature Reviews: Detection of Retracted Articles through Academic Search Engines (2022) se puede leer:

In summary, no database provides 100% coverage of the scientific production in a specific area, which makes it necessary to use several of them in order to obtain greater coverage of the information retrieved.

[...]

It is a recommended practice to use several scientific search engines that both allow access to many scientific articles and provide information on whether these can be considered as solid scientific evidence or, on the contrary, whether they have been retracted and should not be used in scientific studies.

Cómo buscar los artículos

Según el artículo Systematic mapping studies in software engineering (2008), un mapeo sistemático se compone de las siguientes etapas:

  1. Definition of Research Questions (Research Scope).
  2. Conduct Search for Primary Studies (All Papers).
  3. Screening of Papers for Inclusion and Exclusion (Relevant Papers).
  4. Keywording of Abstracts (Classification Scheme).
  5. Data Extraction and Mapping of Studies (Systematic Map).

El paso 2 del proceso de un mapeo sistemático es Conduct Search for Primary Studies (All Papers). En Systematic literature studies: database searches vs. backward snowballing (2012) se analizan y comparan dos de los métodos clásicos de búsqueda de artículos para realizar una revisión sistemática:

En Guidelines for snowballing in systematic literature studies and a replication in software engineering (2014) se explica la técnica de snowballing:

Snowballing refers to using the reference list of a paper or the citations to the paper to identify additional papers. However, snowballing could benefit from not only looking at the reference lists and citations, but to complement it with a systematic way of looking at where papers are actually referenced and where papers are cited. Using the references and the citations respectively is referred to as backward and forward snowballing.

La siguiente imagen muestra un proceso de selección de artículos en una revisión sistemática:

'Selection process' del artículo 'Guidelines for conducting systematic mapping studies in software engineering: An update' de Petersen, Vakkalanka y Kuzniarz (2015)

El proceso de selección de los artículos influye enormemente en los resultados obtenidos. En Effectiveness and efficiency of search methods in systematic reviews of complex evidence: audit of primary sources (2005) se analizó la efectividad para seleccionar los diferentes métodos que se emplean normalmente: