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      The Charlie Sheen Effect on Rapid In-home Human Immunodeficiency Virus Test Sales.

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          Abstract

          One in eight of the 1.2 million Americans living with human immunodeficiency virus (HIV) are unaware of their positive status, and untested individuals are responsible for most new infections. As a result, testing is the most cost-effective HIV prevention strategy and must be accelerated when opportunities are presented. Web searches for HIV spiked around actor Charlie Sheen's HIV-positive disclosure. However, it is unknown whether Sheen's disclosure impacted offline behaviors like HIV testing. The goal of this study was to determine if Sheen's HIV disclosure was a record-setting HIV prevention event and determine if Web searches presage increases in testing allowing for rapid detection and reaction in the future. Sales of OraQuick rapid in-home HIV test kits in the USA were monitored weekly from April 12, 2014, to April 16, 2016, alongside Web searches including the terms "test," "tests," or "testing" and "HIV" as accessed from Google Trends. Changes in OraQuick sales around Sheen's disclosure and prediction models using Web searches were assessed. OraQuick sales rose 95% (95% CI, 75-117; p < 0.001) of the week of Sheen's disclosure and remained elevated for 4 more weeks (p < 0.05). In total, there were 8225 more sales than expected around Sheen's disclosure, surpassing World AIDS Day by a factor of about 7. Moreover, Web searches mirrored OraQuick sales trends (r = 0.79), demonstrating their ability to presage increases in testing. The "Charlie Sheen effect" represents an important opportunity for a public health response, and in the future, Web searches can be used to detect and act on more opportunities to foster prevention behaviors.

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          Most cited references10

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          Escaping affect: how motivated emotion regulation creates insensitivity to mass suffering.

          As the number of people in need of help increases, the degree of compassion people feel for them ironically tends to decrease. This phenomenon is termed the collapse of compassion. Some researchers have suggested that this effect happens because emotions are not triggered by aggregates. We provide evidence for an alternative account. People expect the needs of large groups to be potentially overwhelming, and, as a result, they engage in emotion regulation to prevent themselves from experiencing overwhelming levels of emotion. Because groups are more likely than individuals to elicit emotion regulation, people feel less for groups than for individuals. In Experiment 1, participants displayed the collapse of compassion only when they expected to be asked to donate money to the victims. This suggests that the effect is motivated by self-interest. Experiment 2 showed that the collapse of compassion emerged only for people who were skilled at emotion regulation. In Experiment 3, we manipulated emotion regulation. Participants who were told to down-regulate their emotions showed the collapse of compassion, but participants who were told to experience their emotions did not. We examined the time course of these effects using a dynamic rating to measure affective responses in real time. The time course data suggested that participants regulate emotion toward groups proactively, by preventing themselves from ever experiencing as much emotion toward groups as toward individuals. These findings provide initial evidence that motivated emotion regulation drives insensitivity to mass suffering. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
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            Abstract and concrete data in the perseverance of social theories: When weak data lead to unshakeable beliefs

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              Applying Public Health Principles to the HIV Epidemic--How Are We Doing?

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                Author and article information

                Journal
                Prev Sci
                Prevention science : the official journal of the Society for Prevention Research
                Springer Nature
                1573-6695
                1389-4986
                May 18 2017
                Affiliations
                [1 ] Keck School of Medicine, University of Southern California, 2001 N. Soto Street, 3rd Floor Mail, Los Angeles, CA, 90032, USA.
                [2 ] University of California San Diego School of Medicine, La Jolla, CA, USA.
                [3 ] Graduate School of Public Health, San Diego State University, San Diego, CA, USA.
                [4 ] The Wharton School, University of Pennsylvania, Philadelphia, PA, USA.
                [5 ] Drug Policy Institute, College of Medicine, University of Florida, Gainesville, FL, USA.
                [6 ] Human Language Technology Center of Excellence, Johns Hopkins University, Baltimore, MD, USA.
                [7 ] Bloomberg L.P, New York, NY, USA.
                [8 ] Institute for Disease Modeling, Bellevue, WA, USA.
                [9 ] Santa Fe Institute, Santa Fe, NM, USA.
                [10 ] New Mexico State University, Las Cruces, NM, USA.
                [11 ] School of Media and Journalism, University of North Carolina, Chapel Hill, NC, USA.
                [12 ] Graduate School of Public Health, San Diego State University, San Diego, CA, USA. ayers.john.w@gmail.com.
                Article
                10.1007/s11121-017-0792-2
                10.1007/s11121-017-0792-2
                28516308
                4f698413-7754-4ba3-bb6e-6a53a6c2193b
                History

                HIV,HIV prevention,Health informatics,Human immunodeficiency virus,Surveillance

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