Skip to main content

Advertisement

SpringerLink
Log in

Precision and Recall of Search Strategies for Identifying Studies on Return-To-Work in Medline

  • Published:
Journal of Occupational Rehabilitation Aims and scope Submit manuscript

Abstract

Introduction The purpose of this study was to report on the qualities of various search strategies and keywords to find return to work (RTW) studies in the Medline bibliographic database. Methods We searched Medline for articles on RTW published in 2003, using multiple search strings, and hand searched 16 major periodicals of rehabilitation or occupational medicine. Among the retrieved articles, those considered to be relevant, were pooled in a Gold Standard Database. From this database, we identified candidate text words or MeSH terms for search strategies using a word frequency analysis of the abstracts and a MEDLINE categorization algorithm. According to the frequency of identified terms, searches were run for each term independently and in combination. We computed Recall, Precision, and number needed to read (NNR = 1/Precision) of each keyword or combination of keywords. Results Among the 8,073 articles examined, 314 (3.9%) were considered relevant and included in the Gold Standard Database. The search strings (“Rehabilitation, Vocational” [MeSH]), (“Return to work”[All]) and (“Back to work”[All]) had Recall/Precision ratio of 30.46/19.11, 59.55/87.38 and 3.18/90.91%, respectively. Their combination with the Boolean operator OR yielded to a Recall/Precision ratio of 73.89/58.44% and a NNR of 1.7. For the end user requiring comprehensive literature search, the best string was (“Return to work” OR “Back to work” OR “Rehabilitation, vocational”[MeSH] OR “rehabilitation”[Subheading]), with a Recall of 88.22% and a NNR of 18. Conclusions No single MeSH term is available to help the physician to identify relevant studies on RTW in Medline. Locating these types of studies requires the use of various MeSH and non-MeSH terms in combination to obtain a satisfactory Recall. Nevertheless, enhancing the Recall of search strategies may lead to lower Precision, and higher NNR, although with a non linear trend. This factor must be taken into consideration by the end user in order to improve the cost-effectiveness ratio of the search in Medline.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. The multiplication of books. JAMA. 1901;XXXVII:647–8.

  2. Wyatt J. Uses and sources of medical knowledge. Lancet. 1991;338:1368–72.

    Article  PubMed  CAS  Google Scholar 

  3. Alper BS, Hand JA, Elliott SG, Kinkade S, Hauan MJ, Onion DK, et al. How much effort is needed to keep up with the literature relevant for primary care? J Med Libr Assoc. 2004;92:429–37.

    PubMed  Google Scholar 

  4. Saint S, Christakis DA, Saha S, Elmore JG, Welsh DE, Baker P, et al. Journal reading habits of internists. J Gen Intern Med. 2000;15:881–4.

    Article  PubMed  CAS  Google Scholar 

  5. Gehanno JF, Paris C, Thirion B, Caillard JF. Assessment of bibliographic databases performance in information retrieval for occupational and environmental toxicology. Occup Environ Med. 1998;55:562–6.

    Article  PubMed  CAS  Google Scholar 

  6. Haafkens J, Moerman C, Schuring M, van Dijk F. Searching bibliographic databases for literature on chronic disease and work participation. Occup Med. 2006;56:39–45.

    Article  Google Scholar 

  7. Greenhalgh T. How to read a paper: the Medline database. BMJ. 1997;315:180–3.

    PubMed  CAS  Google Scholar 

  8. Adams CE, Power A, Frederick K, Lefebre C. An investigation of the adequacy of MEDLINE searches for randomized controlled trials (RCTs) of the effects of mental health care. Psychol Med. 1994;24:741–8.

    Article  PubMed  CAS  Google Scholar 

  9. Nwosu CR, Khan KS, Chien PF. A two-term MEDLINE search strategy for identifying randomized trials in obstetrics and gynecology. Obstet Gynecol. 1998;91:618–22.

    Article  PubMed  CAS  Google Scholar 

  10. Watson RJ, Richardson PH. Identifying randomized controlled trials of cognitive therapy for depression: comparing the efficiency of Embase, MEDLINE and PsycINFO bibliographic databases. Br J Med Psychol. 1999;72:535–42.

    Article  PubMed  Google Scholar 

  11. Marson AG, Chadwick DW. How easy are randomized controlled trials in epilepsy to find on Medline? The sensitivity and precision of two Medline searches. Epilepsia. 1996;37:377–80.

    Article  PubMed  CAS  Google Scholar 

  12. Devillé WL, Bezemer PD, Bouter LM. Publications on diagnostic test evaluation in family medicine journals: an optimal search strategy. J Clin Epidemiol. 2000;53:65–9.

    Article  PubMed  Google Scholar 

  13. Van der Weijden T, Ijzermans CJ, Dinant GJ, van Duijn NP, de Vet R, Buntinx F. Identifying relevant diagnostic studies in MEDLINE. The diagnostic value of the erythrocyte sedimentation rate (ESR) and dipstick as an example. Fam Pract. 1997;14:204–8.

    Article  PubMed  Google Scholar 

  14. Felber SH. Searching for evidence-based oncology: tips and tools for finding evidence in the medical literature. Cancer Control. 2000;7:469–75.

    PubMed  CAS  Google Scholar 

  15. Montori VM, Wilczynski NL, Morgan D, Haynes RB. Hedges Team. Optimal search strategies for retrieving systematic reviews from Medline: analytical survey. BMJ. 2005;330:68–71.

    Article  PubMed  Google Scholar 

  16. Verbeek J, Salmi J, Pasternack I, Jauhiainen M, Laamanen I, Schaafsma F, et al. A search strategy for occupational health intervention studies. Occup Environ Med. 2005;62:682–7.

    Article  PubMed  CAS  Google Scholar 

  17. Shaw W, Hong QN, Pransky G, Loisel P. A literature review describing the role of return-to-work coordinators in trial programs and interventions designed to prevent workplace disability. J Occup Rehabil. 2008;18:2–15.

    Article  PubMed  Google Scholar 

  18. Gehanno JF, Thirion B. How to select publications on occupational health: the usefulness of Medline and the impact factor. Occup Environ Med. 2000;57:706–9.

    Article  PubMed  CAS  Google Scholar 

  19. Dong P, Wong LL, Ng S, Loh M, Mondry A. Quantitative evaluation of recall and precision of CAT Crawler, a search engine specialized on retrieval of critically appraised topics. BMC Med Inform Decis Mak. 2004;4:21.

    Article  PubMed  Google Scholar 

  20. Darmoni SJ, Neveol A, Renard JM, Gehanno JF, Soualmia LF, Dahamna B, et al. A MEDLINE categorization algorithm. BMC Med Inform Decis Mak. 2006;6:7.

    Article  PubMed  Google Scholar 

  21. Bachmann LM, Coray R, Estermann P, Ter Riet G. Identifying diagnostic studies in MEDLINE: reducing the number needed to read. J Am Med Inform Assoc. 2002;9:653–8.

    Article  PubMed  Google Scholar 

  22. Verbeek JH, van Dijk FJ, Malmivaara A, Hulshof CT, Räsänen K, Kankaanpää EE, et al. Evidence-based medicine for occupational health. Scand J Work Environ Health. 2002;28:197–204.

    PubMed  Google Scholar 

  23. Jenuwine ES, Floyd JA. Comparison of medical subject headings and text-word searches in MEDLINE to retrieve studies on sleep in healthy individuals. J Med Libr Assoc. 2004;92:349–53.

    PubMed  Google Scholar 

  24. Chang AA, Heskett KM, Davidson TM. Searching the literature using medical subject headings versus text word with PubMed. Laryngoscope. 2006;116:336–40.

    Article  PubMed  Google Scholar 

  25. Schaafsma F, Hulshof C, Verbeek J, Bos J, Dyserinck H, van Dijk F. Developing search strategies in Medline on the occupational origin of diseases. Am J Ind Med. 2006;49:127–37.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

Acknowledgment of financial support: this work was supported by Canadian Institutes of Health Research (CIHR) grant(s) FRN: 53909. The authors thank Richard Medeiros, Rouen University Medical Editor, for editing the final version of the manuscript.

Author information

Authors and Affiliations

  1. Institute of Occupational Health, Rouen University Hospital, 1 rue de Germont, 76000, Rouen, France

    Jean-François Gehanno, Laetitia Rollin & Alexandre Louvel

  2. Department of Rehabilitation Medicine, General Hospital of Dieppe, Dieppe, France

    Tony Le Jean

  3. GCSIS Laboratory, Rouen University Hospital, Rouen, France

    Jean-François Gehanno & Stefan Darmoni

  4. Liberty Mutual Research Institute for Safety, Hopkinton, MA, USA

    William Shaw

Authors
  1. Jean-François Gehanno
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Laetitia Rollin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tony Le Jean
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alexandre Louvel
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Stefan Darmoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. William Shaw
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jean-François Gehanno.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gehanno, JF., Rollin, L., Le Jean, T. et al. Precision and Recall of Search Strategies for Identifying Studies on Return-To-Work in Medline. J Occup Rehabil 19, 223–230 (2009). https://doi.org/10.1007/s10926-009-9177-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10926-009-9177-0

Keywords

Search

Navigation