How doctors search: A study of query behaviour and the impact on search results

Lykke, Marianne; Price, Susan; Delcambre, Lois

doi:10.1016/j.ipm.2012.02.006

Cited by 16 publications

(20 citation statements)

References 34 publications

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“…However, synonym/acronym/hypernym factors only accounted for 5% of all dissatisfaction events. This conflicts with assertions that the vocabulary problem is the dominant reason for search task dissatisfaction in the enterprise [100,103]. One explanation may be related to the large scale and longitudinal nature of this study compared to previous narrower studies.…”

Section: Discussioncontrasting

confidence: 96%

Enterprise search and discovery capability: The factors and generative mechanisms for user satisfaction

Cleverley

Burnett

2018

Journal of Information Science

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Many organisations are re-creating the ‘Google-like’ experience behind their firewall to exploit their information. However, surveys show dissatisfaction with enterprise search is commonplace. No prior study has investigated unsolicited user feedback from an enterprise search user interface to understand the underlying reasons for dissatisfaction. A mixed-methods longitudinal study was undertaken analysing feedback from over 1000 users and interviewing search service staff in a multinational corporation. Results show that 62% of dissatisfaction events were due to human (information and search literacy) rather than technology factors. Cognitive biases and the ‘Google Habitus’ influence expectations and information behaviour and are postulated as deep underlying generative mechanisms. The current literature focuses on ‘structure’ (technology and information quality) as the reason for enterprise search satisfaction, agency (search literacy) appears downplayed. Organisations which emphasise ‘systems thinking’ and bimodal approaches towards search strategy and information behaviour may improve capabilities.

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Section: Discussioncontrasting

confidence: 96%

Enterprise search and discovery capability: The factors and generative mechanisms for user satisfaction

Cleverley

Burnett

2018

Journal of Information Science

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“…The results contrast findings by [7,8,11] that search success depends on searchers' ability to articulate and structure the search facets, and cover them exhaustively. The findings support later results that selection of few, key search facets are more important compared to lengthy, exhaustive coverage [12]. The results might be explained by the fact that participants in the present and latter study were subject experts with strong and work-related interest in the search topic as opposed to previous studies where study subjects were students with lesser connection to search topics.…”

Section: Figure 2: Ndcg For Task Length and Document Typessupporting

confidence: 86%

Physicists' information tasks

Lykke

Ingwersen

Bogers

et al. 2010

Proceedings of the Third Symposium on Information Interaction in Context

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In this poster, we describe central aspects of 65 natural information tasks from 23 senior researchers, PhDs, and experienced MSc students from three different university departments of physics. We analyze 1) the main purpose of the information task, 2) which and how many search facets were used to describe the tasks, 3) what semantic categories were used to express the search facets, and 4) retrieval performance. Results show variety in structure and length across task descriptions and task purposes. The results indicate effect of length and, in particular, of task purpose on retrieval performance of different document description levels that should be examined further.

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“…The notations and the measurements used for the definition of the feature facets are presented, respectively, in Tables and . Query length. We consider the query length as a relevant attribute as investigated in previous work (Dogan et al., ; Eysenbach & Kohler, ; Lykke et al., ; Maghrabi, Coreira, Westbrook, Gosling, & Vickland, ; Spink et al., ). Furthermore, bearing in mind the fact that experts might make use of medical terminologies, we retain two facets regarding query components: (a) length as the number of stems or significant words (not including empty words), LgW ( Q ), and (b) length as the number of terms referencing preferred entries of concepts issued from MeSH terminology, LgC ( Q ). Query specificity.…”

Section: Methodsmentioning

confidence: 99%

“…Many studies in the literature have investigated different aspects of medical‐ and health‐related information seeking and retrieval. These studies generally relied on empirical evaluations conducted with samples of users in order to investigate the users' information need peculiarities (Lykke, Price, & Delcambre, ; Spink et al., ; Zhang & Fu, ), query difficulty (Lykke et al., ; W. Hersh et al., ; Boudin, Nie, & Dawes, ), user behavior (Dogan, Muray, Neveol, & Lu, ; Ely et al., ), the effect of context on search (Cartright, While, & Horvitz, ; Freund, Toms, & Waterhouse, ; Lykke et al., ; White, Dumais, & Teevan, ), the search accuracy, the quality and the reliability of medical information (Moturu, Liu, & Johnson, ; Pandolfini, ), etc. Related findings provide insights into medical information search activity and suggest implications for the design of improved medical IR systems.…”

Section: Studies On Medical‐ and Health‐related Information Needs Andmentioning

confidence: 99%

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Analysis of biomedical and health queries: Lessons learned fromTRECandCLEFevaluation benchmarks

Tamine

Chouquet

Palmer

2015

Asso for Info Science & Tech

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A large body of research work examined, from both the query side and the user behavior side, the characteristics of medical‐ and health‐related searches. One of the core issues in medical information retrieval (IR) is diversity of tasks that lead to diversity of categories of information needs and queries. From the evaluation perspective, another related and challenging issue is the limited availability of appropriate test collections allowing the experimental validation of medically task oriented IR techniques and systems. In this paper, we explore the peculiarities of TREC and CLEF medically oriented tasks and queries through the analysis of the differences and the similarities between queries across tasks, with respect to length, specificity, and clarity features and then study their effect on retrieval performance. We show that, even for expert oriented queries, language specificity level varies significantly across tasks as well as search difficulty. Additional findings highlight that query clarity factors are task dependent and that query terms specificity based on domain‐specific terminology resources is not significantly linked to term rareness in the document collection. The lessons learned from our study could serve as starting points for the design of future task‐based medical information retrieval frameworks.

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How doctors search: A study of query behaviour and the impact on search results

Cited by 16 publications

References 34 publications

Enterprise search and discovery capability: The factors and generative mechanisms for user satisfaction

Enterprise search and discovery capability: The factors and generative mechanisms for user satisfaction

Physicists' information tasks

Analysis of biomedical and health queries: Lessons learned fromTRECandCLEFevaluation benchmarks

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