Visual cues that predict intuitive risk perception in the case of HIV
Field studies indicate that people may form impressions about potential partners' HIV risk, yet lack insight into what underlies such intuitions. The present study examined which cues may give rise to the perception of riskiness. Towards this end, portrait pictures of persons that are represent...
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description | Field studies indicate that people may form impressions about potential partners' HIV risk, yet lack insight into what underlies such intuitions. The present study examined which cues may give rise to the perception of riskiness. Towards this end, portrait pictures of persons that are representative of the kinds of images found on social media were evaluated by independent raters on two sets of data: First, sixty visible cues deemed relevant to person perception, and second, perceived HIV risk and trustworthiness, health, and attractiveness. Here, we report correlations between cues and perceived HIV risk, exposing cue-criterion associations that may be used to infer intuitively HIV risk. Second, we trained a multiple cue-based model to forecast perceived HIV risk through cross-validated predictive modelling. Trained models accurately predicted how 'risky' a person was perceived (r = 0.75) in a novel sample of portraits. Findings are discussed with respect to HIV risk stereotypes and implications regarding how to foster effective protective behaviors. |
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The present study examined which cues may give rise to the perception of riskiness. Towards this end, portrait pictures of persons that are representative of the kinds of images found on social media were evaluated by independent raters on two sets of data: First, sixty visible cues deemed relevant to person perception, and second, perceived HIV risk and trustworthiness, health, and attractiveness. Here, we report correlations between cues and perceived HIV risk, exposing cue-criterion associations that may be used to infer intuitively HIV risk. Second, we trained a multiple cue-based model to forecast perceived HIV risk through cross-validated predictive modelling. Trained models accurately predicted how 'risky' a person was perceived (r = 0.75) in a novel sample of portraits. Findings are discussed with respect to HIV risk stereotypes and implications regarding how to foster effective protective behaviors.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0211770</identifier><identifier>PMID: 30785898</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adolescent ; Adult ; Behavior ; Biology and Life Sciences ; Cues ; Digital media ; Female ; Health ; Health risks ; HIV ; HIV Infections ; Human immunodeficiency virus ; Humans ; Intuition ; Magnetic resonance imaging ; Male ; Mathematical models ; Medical diagnosis ; Medicine and Health Sciences ; Novels ; Perception ; Perceptions ; Personality ; Pictures ; Portraits ; Prevention ; Psychology ; Risk factors ; Risk perception ; Sexual Behavior ; Sexual Partners ; Sexually transmitted diseases ; Social media ; Social Sciences ; STD ; Stereotypes (Psychology) ; Studies ; Trustworthiness ; Visual Perception ; Visual stimuli</subject><ispartof>PloS one, 2019-02, Vol.14 (2), p.e0211770-e0211770</ispartof><rights>COPYRIGHT 2019 Public Library of Science</rights><rights>2019 Schmälzle et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2019 Schmälzle et al 2019 Schmälzle et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-fcf16114a9fe7fd73925a8032f2a370c08421f9487961d10b2ce5437c82c49563</citedby><cites>FETCH-LOGICAL-c692t-fcf16114a9fe7fd73925a8032f2a370c08421f9487961d10b2ce5437c82c49563</cites><orcidid>0000-0002-0179-1364</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6382111/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6382111/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30785898$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Shook, Natalie J.</contributor><creatorcontrib>Schmälzle, Ralf</creatorcontrib><creatorcontrib>Hartung, Freda-Marie</creatorcontrib><creatorcontrib>Barth, Alexander</creatorcontrib><creatorcontrib>Imhof, Martin A</creatorcontrib><creatorcontrib>Kenter, Alex</creatorcontrib><creatorcontrib>Renner, Britta</creatorcontrib><creatorcontrib>Schupp, Harald T</creatorcontrib><title>Visual cues that predict intuitive risk perception in the case of HIV</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Field studies indicate that people may form impressions about potential partners' HIV risk, yet lack insight into what underlies such intuitions. The present study examined which cues may give rise to the perception of riskiness. Towards this end, portrait pictures of persons that are representative of the kinds of images found on social media were evaluated by independent raters on two sets of data: First, sixty visible cues deemed relevant to person perception, and second, perceived HIV risk and trustworthiness, health, and attractiveness. Here, we report correlations between cues and perceived HIV risk, exposing cue-criterion associations that may be used to infer intuitively HIV risk. Second, we trained a multiple cue-based model to forecast perceived HIV risk through cross-validated predictive modelling. Trained models accurately predicted how 'risky' a person was perceived (r = 0.75) in a novel sample of portraits. 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The present study examined which cues may give rise to the perception of riskiness. Towards this end, portrait pictures of persons that are representative of the kinds of images found on social media were evaluated by independent raters on two sets of data: First, sixty visible cues deemed relevant to person perception, and second, perceived HIV risk and trustworthiness, health, and attractiveness. Here, we report correlations between cues and perceived HIV risk, exposing cue-criterion associations that may be used to infer intuitively HIV risk. Second, we trained a multiple cue-based model to forecast perceived HIV risk through cross-validated predictive modelling. Trained models accurately predicted how 'risky' a person was perceived (r = 0.75) in a novel sample of portraits. 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subjects | Adolescent Adult Behavior Biology and Life Sciences Cues Digital media Female Health Health risks HIV HIV Infections Human immunodeficiency virus Humans Intuition Magnetic resonance imaging Male Mathematical models Medical diagnosis Medicine and Health Sciences Novels Perception Perceptions Personality Pictures Portraits Prevention Psychology Risk factors Risk perception Sexual Behavior Sexual Partners Sexually transmitted diseases Social media Social Sciences STD Stereotypes (Psychology) Studies Trustworthiness Visual Perception Visual stimuli |
title | Visual cues that predict intuitive risk perception in the case of HIV |
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