This study analyzes the search behavior of Dutch‐speaking nursing students with a nonnative knowledge of English who searched for information in MEDLINE/PubMed about a specific theme in nursing. We examine whether and to what extent their search efficiency is affected by their language skills. Our task‐oriented approach focuses on three stages of the information retrieval process: need articulation, query formulation, and relevance judgment. The test participants completed a pretest questionnaire, which gave us information about their overall experience with the search system and their self‐reported computer and language skills. The students were briefly introduced to the use of PubMed and MeSH (medical subject headings) before they conducted their keyword‐driven subject search. We assessed the search results in terms of recall and precision, and also analyzed the search process. After the search task, a satisfaction survey and a language test were completed. We conclude that language skills have an impact on the search results. We hypothesize that language support might improve the efficiency of searches conducted by Dutch‐speaking users of PubMed.

本文的目的是演示“模拟翻译教室”的整体方法如何让翻译专业的学生熟悉新的工作方式和技能，将曾经需要在单独的课程中学习的各种新技术整合起来学习。

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.

Terms like "thesaurus", "taxonomy", "classification", "glossary", "ontology" and "controlled vocabulary" can be used in diverse contexts, causing confusion and vagueness about their denotation. Is a thesaurus a tool to enrich a writer's style or an indexing tool used in bibliographic retrieval? Or can it be both? A literature study was to clear the confusion, but rather than giving us consensus definitions, it provided us with conflicting descriptions. We classified these definitions into three domains: linguistics, knowledge management and bibliographic retrieval. The scope of the terms is therefore highly dependent on the context. We propose one definition per term, per context. In addition to this intra-conceptual confusion, there is also inter-conceptual vagueness. This leads to the introduction of misnomers, like "ontology" in the Gene Ontology. We examined some important (bio)medical systems for their compatibility with the definitions proposed in the first part of this paper. To conclude, an overview of these systems and their classification into the three domains is given.

BackgroundThe construction of EBMPracticeNet, a national electronic point-of-care information platform in Belgium, began in 2011 to optimize quality of care by promoting evidence-based decision making. The project involved, among other tasks, the translation of 940 EBM Guidelines of Duodecim Medical Publications from English into Dutch and French. Considering the scale of the translation process, it was decided to make use of computer-aided translation performed by certificated translators with limited expertise in medical translation. Our consortium used a hybrid approach, involving a human translator supported by a translation memory (using SDL Trados Studio), terminology recognition (using SDL MultiTerm terminology databases) from medical terminology databases, and support from online machine translation. This resulted in a validated translation memory, which is now in use for the translation of new and updated guidelines.ObjectiveThe objective of this experiment was to evaluate the performance of the hybrid human and computer-assisted approach in comparison with translation unsupported by translation memory and terminology recognition. A comparison was also made with the translation efficiency of an expert medical translator.MethodsWe conducted a pilot study in which two sets of 30 new and 30 updated guidelines were randomized to one of three groups. Comparable guidelines were translated (1) by certificated junior translators without medical specialization using the hybrid method, (2) by an experienced medical translator without this support, and (3) by the same junior translators without the support of the validated translation memory. A medical proofreader who was blinded for the translation procedure, evaluated the translated guidelines for acceptability and adequacy. Translation speed was measured by recording translation and post-editing time. The human translation edit rate was calculated as a metric to evaluate the quality of the translation. A further evaluation was made of translation acceptability and adequacy.ResultsThe average number of words per guideline was 1195 and the mean total translation time was 100.2 minutes/1000 words. No meaningful differences were found in the translation speed for new guidelines. The translation of updated guidelines was 59 minutes/1000 words faster (95% CI 2-115; P=.044) in the computer-aided group. Revisions due to terminology accounted for one third of the overall revisions by the medical proofreader.ConclusionsUse of the hybrid human and computer-aided translation by a non-expert translator makes the translation of updates of clinical practice guidelines faster and cheaper because of the benefits of translation memory. For the translation of new guidelines, there was no apparent benefit in comparison with the efficiency of translation unsupported by translation memory (whether by an expert or non-expert translator).