Search (6 results, page 1 of 1)

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Abstract

A systematic understanding of factors and criteria that affect consumers' selection of sources for health information is necessary for the design of effective health information services and information systems. However, current studies have overly focused on source attributes as indicators for 2 criteria, source quality and accessibility, and overlooked the role of other factors and criteria that help determine source selection. To fill this gap, guided by decision-making theories and the cognitive perspective to information search, we interviewed 30 participants about their reasons for using a wide range of sources for health information. Additionally, we asked each of them to report a critical incident in which sources were selected to fulfill a specific information need. Based on the analysis of the transcripts, 5 categories of factors were identified as influential to source selection: source-related factors, user-related factors, user-source relationships, characteristics of the problematic situation, and social influences. In addition, about a dozen criteria that mediate the influence of the factors on source-selection decisions were identified, including accessibility, quality, usability, interactivity, relevance, usefulness, familiarity, affection, anonymity, and appropriateness. These results significantly expanded the current understanding of the nature of costs and benefits involved in source-selection decisions, and strongly indicated that a personalized approach is needed for information services and information systems to provide effective access to health information sources for consumers.

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Abstract

Understanding specific patterns or knowledge of self-disclosing health information could support public health surveillance and healthcare. This study aimed to develop an analytical framework to identify self-disclosing health information with unusual messages on web forums by leveraging advanced text-mining techniques. To demonstrate the performance of the proposed analytical framework, we conducted an experimental study on 2 major human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) forums in Taiwan. The experimental results show that the classification accuracy increased significantly (up to 83.83%) when using features selected by the information gain technique. The results also show the importance of adopting domain-specific features in analyzing unusual messages on web forums. This study has practical implications for the prevention and support of HIV/AIDS healthcare. For example, public health agencies can re-allocate resources and deliver services to people who need help via social media sites. In addition, individuals can also join a social media site to get better suggestions and support from each other.

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Abstract

Although considered proxies for people to interact with a system, mental models have produced limited practical implications for system design. This might be due to the lack of exploration of the elements of mental models resulting from the methodological challenge of measuring mental models. This study employed a new method, concept listing, to elicit people's mental models of an information-rich space, MedlinePlus, after they interacted with the system for 5 minutes. Thirty-eight undergraduate students participated in the study. The results showed that, in this short period of time, participants perceived MedlinePlus from many different aspects in relation to four components: the system as a whole, its content, information organization, and interface. Meanwhile, participants expressed evaluations of or emotions about the four components. In terms of the procedural knowledge, an integral part of people's mental models, only one participant identified a strategy more aligned to the capabilities of MedlinePlus to solve a hypothetical task; the rest planned to use general search and browse strategies. The composition of participants' mental models of MedlinePlus was consistent with that of their models of information-rich Web spaces in general.

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Abstract

Web search engines are important gateways for users to access health information. This study explored whether a search interface based on the Bing API and enabled by Scatter/Gather, a well-known document-clustering technique, can improve health information searches. Forty participants without medical backgrounds were randomly assigned to two interfaces: a baseline interface that resembles typical web search engines and a Scatter/Gather interface. Both groups performed two lookup and two exploratory health-related tasks. It was found that the baseline group was more likely to rephrase queries and less likely to access general-purpose sites than the Scatter/Gather group when completing exploratory tasks. Otherwise, the two groups did not differ in behavior and task performance, with participants in the Scatter/Gather group largely overlooking the features (key words, clusters, and the recluster function) designed to facilitate the exploration of semantic relationships between information objects, a potentially useful means for users in the rather unfamiliar domain of health. The results suggest a strong effect of users' mental models of search on their use of search interfaces and a high cognitive cost associated with using the Scatter/Gather features. It follows that novel features of a search interface should not only be compatible with users' mental models but also provide sufficient affordance to inform users of how they can be used. Compared with the interface, tasks showed more significant impacts on search behavior. In future studies, more effort should be devoted to identify salient features of health-related information needs.

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Abstract

The quality of online health information for consumers has been a critical issue that concerns all stakeholders in healthcare. To gain an understanding of how quality is evaluated, this systematic review examined 165 articles in which researchers evaluated the quality of consumer-oriented health information on the web against predefined criteria. It was found that studies typically evaluated quality in relation to the substance and formality of content, as well as to the design of technological platforms. Attention to design, particularly interactivity, privacy, and social and cultural appropriateness is on the rise, which suggests the permeation of a user-centered perspective into the evaluation of health information systems, and a growing recognition of the need to study these systems from a social-technical perspective. Researchers used many preexisting instruments to facilitate evaluation of the formality of content; however, only a few were used in multiple studies, and their validity was questioned. The quality of content (i.e., accuracy and completeness) was always evaluated using proprietary instruments constructed based on medical guidelines or textbooks. The evaluation results revealed that the quality of health information varied across medical domains and across websites, and that the overall quality remained problematic. Future research is needed to examine the quality of user-generated content and to explore opportunities offered by emerging new media that can facilitate the consumer evaluation of health information.

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Abstract

This article reports the author's recent research in developing a holistic model for various levels of digital library (DL) evaluation in which perceived important criteria from heterogeneous stakeholder groups are organized and presented. To develop such a model, the author applied a three-stage research approach: exploration, confirmation, and verification. During the exploration stage, a literature review was conducted followed by an interview, along with a card sorting technique, to collect important criteria perceived by DL experts. Then the criteria identified were used for developing an online survey during the confirmation stage. Survey respondents (431 in total) from 22 countries rated the importance of the criteria. A holistic DL evaluation model was constructed using statistical techniques. Eventually, the verification stage was devised to test the reliability of the model in the context of searching and evaluating an operational DL. The proposed model fills two lacunae in the DL domain: (a) the lack of a comprehensive and flexible framework to guide and benchmark evaluations, and (b) the uncertainty about what divergence exists among heterogeneous DL stakeholders, including general users.