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Sunbelt XXXI International Network for Social Network ... - INSNA

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Impact Of Team Faultlines On Socio‐cognitive <strong>Network</strong>s And Team Per<strong>for</strong>manceWax, Amy; Huang, Meikuan; DeChurch, Leslie A.; Contractor, NoshirSports, Teams and <strong>Network</strong>sTeam Per<strong>for</strong>mance, Socio‐Cognitive <strong>Network</strong>s, Emergent States, Team faultlinesFRI.PM2Faultlines are theoretical divisions that split a group into subgroups based on member differences. <strong>Social</strong> category faultlines occur due to differences in socialcategory demographic variables of group members, such as sex or race, while in<strong>for</strong>mation‐based faultlines occur with regards to job‐related attributes ofmembers, such as general mental ability (Bezrukova, Jehn, Zanutto, & Thatcher, 2009). We submit that faultlines shape the development of team sociocognitivenetworks. In particular, that social category faultlines shape affective networks, whereas in<strong>for</strong>mational faultlines shape cognitive networks.Furthermore, we link changes in affective and cognitive networks to team action process, team in<strong>for</strong>mation sharing, and team per<strong>for</strong>mance. We test theseideas in a sample of 120, 6‐person teams per<strong>for</strong>ming a PC‐based strategy game modeling a cross‐functional emergency response team. We measure faultlines(sex, personality, psychological collectivism, general mental ability, and motives), affective networks (social identity and trust), cognitive networks (transactivememory and mental models), and action process, in<strong>for</strong>mation sharing, and per<strong>for</strong>mance.Importance Of Where Low‐income Adolescents Met Their Most Recent Sexual PartnerStaras, Stephanie A.; Maldonado‐Molina, Mildred M.; Livingston, Melvin D.; Komro, Kelli A.<strong>Social</strong> <strong>Network</strong>s and HealthHIV/STD, Adolescents, Prevention, Sex, Meeting and matingSUN.AM1Introduction: Unprotected sex and acquiring HIV are more common among age discordant sexual partnerships than among similarly aged partners. The placewhere low‐income adolescents met their sexual partners may influence age discordance and condom use. Methods: Between 2008 and 2009, 2996 lowincomeadolescents from the Project Northland Chicago cohort, mean age 17 to 18 years old, reported their sexual history. The 1931 adolescents who ever hadsex reported characteristics of the last time they had sex (e.g., type of sex, condom use, partner’s age, and where they met their partner). Among adolescentswho reported having vaginal or anal sex the last time they had sex (n=1657), we used logistic regression to estimate associations between partner meetingplace, age discordance (&#8805; 5 years), and unprotected sex. Results: Adolescents met their partner at school (43%), through interpersonal connections(31%), in the community (13%), and in public (12%). Age discordant partnerships increased with partner meeting place: 1% at school, 7% through interpersonalconnections, 12% in the community, and 16% in public. Compared to meeting partners at school, the odds of unprotected sex was similar when adolescentsmet their partner through interpersonal connections [Odds Ratio (OR)= 1.2, 95% Confidence Interval (CI) = 0.9 to 1.5], and greater when adolescents met theirpartners in their community (OR=1.7, 95% CI = 1.2 to 2.3) or in public (OR=1.7, 95% CI= 1.2 to 2.5). Associations between partner meeting place andunprotected sex were similar when adjusting <strong>for</strong> age discordance. Conclusions: Adolescent sexual partners’ meeting place likely influences the risk of acquiringHIV, and may represent an important target or site <strong>for</strong> preventive interventions.

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