Searching bibliographic databases for literature on chronic disease and work participation
Open Access
- 11 November 2005
- journal article
- research article
- Published by Oxford University Press (OUP) in Occupational Medicine
- Vol. 56 (1) , 39-45
- https://doi.org/10.1093/occmed/kqi193
Abstract
Background The work participation of people with chronic diseases is a growing concern within the field of occupational medicine. Information on this topic is dispersed across a variety of data sources, making it difficult for health professionals to find relevant studies for literature reviews and guidelines. Aim The goal of this project was to identify bibliographic databases and search terms that could be most useful for retrieving relevant studies on this topic. Methods Five broad questions regarding work participation and chronic disease were formulated, focusing on angina pectoris, depression, diabetes mellitus, hearing impairment and rheumatoid arthritis. A search strategy for retrieving information on these questions was developed and run in five bibliographic databases: Medline, EMBASE, PsycINFO, Cinahl and OSHROM. Relevant publications were selected from the search results. The utility of the selected databases and search terms was evaluated by analysing the number of relevant publications that were retrieved. Results The number of relevant publications retrieved from each database varied. Most (84%) of the relevant publications that were retrieved from each database were unique to that source. For each database, specific search terms for the concept of ‘work’ were useful for retrieving relevant publications. Conclusion Medline, EMBASE and PsycINFO are useful databases for quick searches. Useful search terms for the concept of ‘work’ are work capacity, work disability, vocational rehabilitation, occupational health, sick leave, absenteeism, return to work, retirement, employment status and work status. For comprehensive searches, we recommend additional searches in Cinahl and OSHROM, adapting the search terms to specific databases.Keywords
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