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Big Data, Bigger Dilemmas: A Critical Review

Overview of attention for article published in Journal of the Association for Information Science and Technology, December 2014
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Title
Big Data, Bigger Dilemmas: A Critical Review
Published in
Journal of the Association for Information Science and Technology, December 2014
DOI 10.1002/asi.23294
Authors

Hamid Ekbia, Michael Mattioli, Inna Kouper, G. Arave, Ali Ghazinejad, Timothy Bowman, Venkata Ratandeep Suri, Andrew Tsou, Scott Weingart, Cassidy R. Sugimoto

Abstract

Health research shows that knowing about health risks may not translate into behavior change. However, such research typically operationalizes health information acquisition with knowledge tests. Information scientists who investigate socially embedded information behaviors could help improve understanding of potential associations between information behavior-as opposed to knowledge-and health behavior formation, thus providing new opportunities to investigate the effects of health information. We examine the associations between information behavior and HIV testing intentions among young men who have sex with men (YMSM), a group with high rates of unrecognized HIV infection. We used the theory of planned behavior (TPB) to predict intentions to seek HIV testing in an online sample of 163 YMSM. Multiple regression and recursive path analysis were used to test two models: (a) the basic TPB model and (b) an adapted model that added the direct effects of three information behaviors (information exposure, use of information to make HIV-testing decisions, prior experience obtaining an HIV test) plus self-rated HIV knowledge. As hypothesized, our adapted model improved predictions, explaining more than twice as much variance as the original TPB model. The results suggest that information behaviors may be more important predictors of health behavior intentions than previously acknowledged.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 547 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
Netherlands 2 <1%
Brazil 2 <1%
Luxembourg 2 <1%
Taiwan 2 <1%
Canada 2 <1%
Austria 1 <1%
United Kingdom 1 <1%
Finland 1 <1%
Other 5 <1%
Unknown 526 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 114 21%
Student > Master 87 16%
Researcher 54 10%
Student > Doctoral Student 44 8%
Student > Bachelor 39 7%
Other 102 19%
Unknown 107 20%
Readers by discipline Count As %
Computer Science 105 19%
Social Sciences 99 18%
Business, Management and Accounting 81 15%
Engineering 23 4%
Arts and Humanities 21 4%
Other 86 16%
Unknown 132 24%