Related Experiment Videos
Primary journal selection using citations from an indexing service journal: a method and example from nursing
Bulletin of the Medical Library Association
|October 1, 1976
Summary
Library journal selection is challenging. This study uses citation analysis of Medical Subject Headings (MeSH) to predict collection demand efficiently, aiding librarians in making informed periodical acquisition decisions.
Area of Science:
- Library and Information Science
- Medical Informatics
Background:
- Serial literature is crucial for libraries but presents significant selection and cost challenges.
- Increasing journal costs and economic pressures necessitate re-evaluating periodical collection policies.
- Small to intermediate libraries face difficulties in maintaining comprehensive collections.
Purpose of the Study:
- To develop an efficient and economical method for predicting library collection demand for serials.
- To assist librarians in establishing periodical subscription policies and prioritizing resource allocation.
- To identify specialty journals within specific disciplines, using nursing as a case study.
Main Methods:
- Citation analysis of Medical Subject Headings (MeSH) and subheadings from the MEDLARS database.
- Utilizing the online capabilities of the MEDLARS database for efficient data retrieval.
- Analyzing a four-year period of citations to identify specialty journals in nursing.
Main Results:
- Rank-order listings of journals by MeSH term productivity were generated.
- A composite list of 16,355 unique citations was compiled.
- The methodology provides data for informed decisions on periodical subscriptions, binding, and microform purchases.
Conclusions:
- The citation analysis technique effectively predicts collection demand for serials.
- This approach offers an economical method for library collection development and policy setting.
- Data-driven insights can optimize resource allocation for serials in academic and medical libraries.