Population groups: indexing, coverage, and retrieval effectiveness of ethnically related health care issues in health sciences databases.
OBJECTIVE
This study examined methods of accessing (for indexing and retrieval purposes) medical research on population groups in the major abstracting and indexing services of the health sciences literature.


METHODS
The study of diseases in specific population groups is facilitated by the indexing of both diseases and populations in a database. The MEDLINE, PsycINFO, and Embase databases were selected for the study. The published thesauri for these databases were examined to establish the vocabulary in use. Indexing terms were identified and examined as to their representation in the current literature. Terms were clustered further into groups thought to reflect an end user's perspective and to facilitate subsequent analysis. The medical literature contained in the three online databases was searched with both controlled vocabulary and natural language terms.


RESULTS
The three thesauri revealed shallow pre-coordinated hierarchical structures, rather difficult-to-use terms for post-coordination, and a blurring of cultural, genetic, and racial facets of populations. Post-coordination is difficult because of the system-oriented terminology, which is intended mostly for information professionals. The terminology unintentionally restricts access by the end users who lack the knowledge needed to use the thesauri effectively for information retrieval.


CONCLUSIONS
Population groups are not represented adequately in the index languages of health sciences databases. Users of these databases need to be alerted to the difficulties that may be encountered in searching for information on population groups. Information and health professionals may not be able to access the literature if they are not familiar with the indexing policies on population groups. Consequently, the study points to a problem that needs to be addressed, through either the redesign of existing systems or the design of new ones to meet the goals of Healthy People 2000 and beyond.
Efthimiadis
E N
EN
Department of Library and Information Science Graduate, School of Education & Information Studies, University of California at Los Angeles 90095, USA.
Afifi
M
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D000043:Abstracting and Indexing; D003663:Decision Trees; D005006:Ethnicity; D005544:Forecasting; D006302:Health Services Research; D006801:Humans; D016247:Information Storage and Retrieval; D016239:MEDLINE; D009862:Online Systems; D011157:Population Dynamics; D044469:Racial Groups; D009626:Terminology as Topic; D014481:United States; D018875:Vocabulary, Controlled