Overcoming the linguistic divide: a barrier to consumer health information

Boden, Catherine

doi:10.5596/c09-020

Cited by 12 publications

(9 citation statements)

References 34 publications

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“…Looking through the lens of the conceptual framework of tasks (Byström & Hansen, 2005), the topic of interest and the information goal were attributes of search tasks, with the former defining the subject of information that users need, and the latter defining the type and amount of information needed, as well as the level of effort demanded. Consistent with previous studies (Boden, 2009), this study observed that users misspelled terms, used acronyms, and had difficulties expressing their needs in proper medical terms. These difficulties could prevent users from retrieving optimal search results (Fidel, 1991;Zeng et al, 2004).…”

Section: Layered Model Of Context For Consumer Health Information Seasupporting

confidence: 90%

“…Understanding contexts is even more important in the case of health information searching, as health concerns are not only extremely personal, but also require highly specialized knowledge to comprehend. The personal nature of health concerns indicates that users need information that is not only relevant to their health conditions, but also applicable to their specific social and cognitive conditions; the specialized nature of health information implies that consumers often lack medical domain knowledge, and thus have difficulties both in articulating their needs (Boden, ; Zeng et al., ), and in making relevance judgments (Arora et al., ). Thus, an enhanced ability of a system to support health information searching hinges on its ability to provide users with more personalized interactions.…”

Section: Introductionmentioning

confidence: 99%

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Toward a layered model of context for health information searching: An analysis of consumer‐generated questions

Zhang

2013

J Am Soc Inf Sci Tec

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Designing effective consumer health information systems requires deep understanding of the context in which the systems are being used. However, due to the elusive nature of the concept of context, few studies have made it a focus of examination. To fill this gap, we studied the context of consumer health information searching by analyzing questions posted on a social question and answer site: Yahoo! Answers. Based on the analysis, a model of context was developed. The model consists of 5 layers: demographic, cognitive, affective, situational, and social and environmental. The demographic layer contains demographic factors of the person of concern; the cognitive layer contains factors related to the current search task (specifically, topics of interest and information goals) and users' cognitive ability to articulate their needs. The affective layer contains different affective motivations and intentions behind the search. The situational layer contains users' perceptions of the current health condition and where the person is in the illness trajectory. The social and environmental layer contains users' social roles, social norms, and various information channels. Several novel system functions, including faceted search and layered presentation of results, are proposed based on the model to help contextualize and improve users' interactions with health information systems.

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Section: Layered Model Of Context For Consumer Health Information Seasupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Toward a layered model of context for health information searching: An analysis of consumer‐generated questions

Zhang

2013

J Am Soc Inf Sci Tec

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“…It seems that to better support specific health‐related tasks, systems should provide a more “natural” user interface to accommodate users' behavior of writing full sentences rather than artificial keywords (Hearst, ). This function could be particularly useful for health information searching, as users tend to have difficulties with medical vocabularies (Boden, ). Allowing them to provide longer descriptions of their needs will likely enhance the chance of finding information that matches their cognitive situations.…”

Section: Discussionmentioning

confidence: 99%

“…Three levels of difficulty have been identified. At the term level, they misspelled medical terms; at the conceptual level, they were not able to formulate specific keywords to describe their intentions; and at the mental model level, they tended to misunderstand their current conditions (Boden, ; Zeng et al., ; Zhang, ). These difficulties could lead to failed searches and subsequent user frustration (Zeng et al., ).…”

Section: Related Literaturementioning

confidence: 99%

Searching for specific health‐related information in MedlinePlus: Behavioral patterns and user experience

Zhang

2013

Asso for Info Science & Tech

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Searches for specific factual health information constitute a significant part of consumer health information requests, but little is known about how users search for such information. This study attempts to fill this gap by observing users' behavior while using MedlinePlus to search for specific health information. Nineteen students participated in the study, and each performed 12 specific tasks. During the search process, they submitted short queries or complete questions, and they examined less than 1 result per search. Participants rarely reformulated queries; when they did, they tended to make a query more specific or more general, or iterate in different ways. Participants also browsed, primarily relying on the alphabetical list and the anatomical classification, to navigate to specific health topics. Participants overall had a positive experience with MedlinePlus, and the experience was significantly correlated with task difficulty and participants' spatial abilities. The results suggest that, to better support specific item search in the health domain, systems could provide a more "natural" interface to encourage users to ask questions; effective conceptual hierarchies could be implemented to help users reformulate queries; and the search results page should be reconceptualized as a place for accessing answers rather than documents. Moreover, multiple schemas should be provided to help users navigate to a health topic. The results also suggest that users' experience with information systems in general and health-related systems in particular should be evaluated in relation to contextual factors, such as task features and individual differences.

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“…There are common semantic category associations (Dogan et al, 2009); Terms do not always match standard vocabularies (Keselman et al, 2008;Zhang & Fu, 2011), inappropriate terms due to misspelling errors and abbreviations are common (Boden, 2009;Zhang & Fu, 2011), a query may contain two or three subqueries covering different facets of the information need (Zhang & Fu, 2011)…”

Section: Query Structure Vocabularymentioning

confidence: 99%

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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Overcoming the linguistic divide: a barrier to consumer health information

Cited by 12 publications

References 34 publications

Toward a layered model of context for health information searching: An analysis of consumer‐generated questions

Toward a layered model of context for health information searching: An analysis of consumer‐generated questions

Searching for specific health‐related information in MedlinePlus: Behavioral patterns and user experience

Analysis of biomedical and health queries: Lessons learned fromTRECandCLEFevaluation benchmarks

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