A multi-level model of information seeking in the clinical domain. Academic Article uri icon

Overview

MeSH

  • Computer Simulation
  • Databases, Factual

MeSH Major

  • Clinical Medicine
  • Database Management Systems
  • Decision Support Systems, Clinical
  • Information Storage and Retrieval
  • Models, Theoretical
  • User-Computer Interface

abstract

  • Clinicians often have difficulty translating information needs into effective search strategies to find appropriate answers. Information retrieval systems employing an intelligent search agent that generates adaptive search strategies based on human search expertise could be helpful in meeting clinician information needs. A prerequisite for creating such systems is an information seeking model that facilitates the representation of human search expertise. The purpose of developing such a model is to provide guidance to information seeking system development and to shape an empirical research program. The information seeking process was modeled as a complex problem-solving activity. After considering how similarly complex activities had been modeled in other domains, we determined that modeling context-initiated information seeking across multiple problem spaces allows the abstraction of search knowledge into functionally consistent layers. The knowledge layers were identified in the information science literature and validated through our observations of searches performed by health science librarians. A hierarchical multi-level model of context-initiated information seeking is proposed. Each level represents (1) a problem space that is traversed during the online search process, and (2) a distinct layer of knowledge that is required to execute a successful search. Grand strategy determines what information resources will be searched, for what purpose, and in what order. The strategy level represents an overall approach for searching a single resource. Tactics are individual moves made to further a strategy. Operations are mappings of abstract intentions to information resource-specific concrete input. Assessment is the basis of interaction within the strategic hierarchy, influencing the direction of the search. The described multi-level model provides a framework for future research and the foundation for development of an automated information retrieval system that uses an intelligent search agent to bridge clinician information needs and human search expertise.

publication date

  • April 2008

has subject area

  • Clinical Medicine
  • Computer Simulation
  • Database Management Systems
  • Databases, Factual
  • Decision Support Systems, Clinical
  • Information Storage and Retrieval
  • Models, Theoretical
  • User-Computer Interface

Research

keywords

  • Journal Article

Identity

Language

  • eng

PubMed Central ID

  • PMC2384229

Digital Object Identifier (DOI)

  • 10.1016/j.jbi.2007.09.005

PubMed ID

  • 18006383

Additional Document Info

start page

  • 357

end page

  • 370

volume

  • 41

number

  • 2