Lost in PubMed. Factors influencing the success of medical information retrieval

Abstract

With the explosion of information available on the Web, finding specific medical information in an efficient way has become a considerable challenge. PubMed/MEDLINE offers an alternative to freetext searching on the web, allowing searchers to do a keyword-based search using Medical Subject Headings. However, finding relevant information within a limited time frame remains a difficult task.The current study is based on an error analysis of data from a retrieval experiment conducted at the nursing departments of two Belgian universities and a British university. We identified the main difficulties in query formulation and relevance judgment and compared the profiles of the best and worst performers in the test.For the analysis, a query collection was built from the queries submitted by our test participants. The queries in this collection are all aimed at finding the same specific information in PubMed, which allowed us to identify what exactly went wrong in the query formulation step. Another crucial aspect for efficient information retrieval is relevance judgment. Differences between potential and actual recall of each query offered indications of the extent to which participants overlooked relevant citations.The test participants were divided into "worst", "average" and "best" performers based on the number of relevant citations they selected: zero, one or two and three or more, respectively. We tried to find out what the differences in background and in search behavior were between these three groups.

Google Scholar as replacement for systematic literature searches: good relative recall and precision are not enough

“…For many scientists, especially in the life-science domains, the literature retrieval process is tedious, error-prone and nontransparent [ 1 - 4 ]. On the other hand, the quality of literature search has been recognized as one of the key features for the generation of high quality scientific evidence [ 5 , 6 ].…”

Lost in translation? A multilingual Query Builder improves the quality of PubMed queries: a randomised controlled trial

“…However, the quality of the query is strongly associated to the quality of the results. Vanopstal et al demonstrated that under-specified queries led to an increase of noise and our data show that under-specification is the main error compensated by querying in users’ first language [9]. An evaluation of the queries is planned as a second step.…”

Factors that influence query reformulations and search performance in health information retrieval: A multilevel modeling approach

“…On the contrary, in SimpleMed users were likely to rely on trial and error, which resulted in more query reformulations. Users with limited knowledge of medical terms tend to select incorrect terms and to adopt a completely new query based on trial and error (Vanopstal et al, ). MeshMed helps users replace inadequate terms with more correct ones, which could potentially reduce the iteration of reformulation attempts.…”

“…More recent studies have explored the impact of contextual factors on users' query reformulation behavior (e.g., Liu, Gwizdka, & Belkin, ). Besides contextual factors, system features and interface design may have an impact on users' search behavior, and thus influence query reformulation behavior (e.g., Vanopstal, Buysschaert, Laureys, & Vander Stichele, ). This can be especially true in health IR, where users have been found to have difficulty in constructing effective queries due to the complex terminology system (Zeng, Kogan, Ash, Greenes, & Boxwala, ).…”