Article Text
Abstract
Objectives Several PubMed search filters have been developed in contexts other than environmental. We aimed at identifying efficient PubMed search filters for the study of environmental determinants of diseases related to outdoor air pollution.
Methods We compiled a list of Medical Subject Headings (MeSH) and non-MeSH terms seeming pertinent to outdoor air pollutants exposure as determinants of diseases in the general population. We estimated proportions of potentially pertinent articles to formulate two filters (one ‘more specific’, one ‘more sensitive’). Their overall performance was evaluated as compared with our gold standard derived from systematic reviews on diseases potentially related to outdoor air pollution. We tested these filters in the study of three diseases potentially associated with outdoor air pollution and calculated the number of needed to read (NNR) abstracts to identify one potentially pertinent article in the context of these diseases. Last searches were run in January 2016.
Results The ‘more specific’ filter was based on the combination of terms that yielded a threshold of potentially pertinent articles ≥40%. The ‘more sensitive’ filter was based on the combination of all search terms under study. When compared with the gold standard, the ‘more specific’ filter reported the highest specificity (67.4%; with a sensitivity of 82.5%), while the ‘more sensitive’ one reported the highest sensitivity (98.5%; with a specificity of 47.9%). The NNR to find one potentially pertinent article was 1.9 for the ‘more specific’ filter and 3.3 for the ‘more sensitive’ one.
Conclusions The proposed search filters could help healthcare professionals investigate environmental determinants of medical conditions that could be potentially related to outdoor air pollution.
- STATISTICS & RESEARCH METHODS
- PREVENTIVE MEDICINE
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Statistics from Altmetric.com
Footnotes
Contributors SC and SM contributed to the conception and study design; acquisition, analysis and interpretation of the data; drafting of the manuscript; critical revision of the manuscript for important intellectual content as whole. DG contributed to the conception and study design; acquisition, analysis and interpretation of the data; drafting of the manuscript. VDG contributed to the acquisition; critical revision of the manuscript for important intellectual content. AF, MPF, DCC and FSV contributed to the analysis and interpretation of the data; critical revision of the manuscript for important intellectual content. AB contributed to the conception and study design; critical revision of the manuscript for important intellectual content. All the authors read and approved the final version of the manuscript.
Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement No additional data are available.