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Cross-Gender Social Normative Effects for Violence in Middle School: Do Girls Carry a Social Multiplier Effect for At-Risk Boys?

Journal of Youth and Adolescence volume 43, pages 1465–1485 (2014)Cite this article

Abstract

A social multiplier effect is a social interaction in which the behavior of a person in a social network varies with the normative behavior of others in the network, also known as an endogenous interaction. Policies and intervention efforts can harness social multiplier effects because, in theory, interventions on a subset of individuals will have “spillover effects” on other individuals in the network. This study investigates potential social multiplier effects for violence in middle schools, and whether there is evidence for a social multiplier effect transmitted from girls to boys. Three years of longitudinal data (2003–2005) from Project Northland Chicago were used to investigate this question, with a sample consisting of youth in Grades 6 through 8 in 61 Chicago Public Schools (N = 4,233 at Grade 6, N = 3,771 at Grade 7, and N = 3,793 at Grade 8). The sample was 49.3 % female, and primarily African American (41.9 %) and Latino/a (28.7 %), with smaller proportions of whites (12.9 %), Asians (5.2 %) and other ethnicities. Results from two sets of regression models estimating the effects of 20th (low), 50th (average), and 80th (high) percentile scores for girls and boys on levels of violence in each gender group revealed evidence for social multiplier effects. Specifically, boys and girls were both influenced by social multiplier effects within their own gender group, and boys were also affected by normative violence scores among girls, typically those of the best-behaved (20th percentile) girls. The finding that girls may have positive social influence on boys’ levels of violent behavior extends prior findings of beneficial social effects of girls on boys in the domains of education and risky driving. Further, this social normative effect presents a potential opportunity to improve school-based intervention efforts for reducing violence among youth by leveraging girls as carriers of a social multiplier effect for reduced violence in the middle school environmental context, particularly among boys, who are at greater risk.

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Notes

  1. Assignment to intervention or control condition in PNC was at the neighborhood level (groups of schools), and interventions lasted all three middle school years. However, there was no effect of the intervention on alcohol use, drug use, or any hypothesized mediating factors, such that the intervention was rendered ineffective (Komro et al. 2008). It is possible that the intervention had carry-over effects on levels of violence among students, though this was unintended by the design; however, as mentioned, we utilize a regression model that parses changes at the individual level from effects that are constant over time, such as intervention versus control condition, thus removing from our estimates any effect of assignment to treatment or control condition.

  2. For instance, Schafer and colleagues argue that in the social sciences, it is unlikely that missingness related to the variable at hand occurs at a sharp cutoff the way it may in the natural sciences, but more than likely is related in a gradually increasing or decreasing (curvilinear) fashion, such the relationship between the score and missingness is weak. Further, in social sciences research, attrition or nonparticipation is likely due to several causes (i.e., not exclusively caused by higher levels of the variable at hand). Given these rationales, we felt comfortable with an assumption of MAR for our modeling in Stata.

  3. As a statistical note, three-way interactions are more difficult to detect because the unreliability of interaction terms is a product of the unreliability of its component terms. Three-way interactions are thus laden with measurement error, reducing the statistical power to detect a significant interaction (Aiken and West 1991). Further, research has suggested that when the assumption of homogeneity of error variances across groups is violated (as may be the case if our regression model fit better for one gender than the other), the power to detect significant interactions varies considerably (Keith 2006). In fact, we did run preliminary models across gender groups, including all possible two-way and three-way interaction terms, and found that none of these interactions were significant. However, because of the reasons stated here, we present in our text the results of the more powerful, flexible, and nuanced models run in each gender group.

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Conflict of interest

All authors claim no conflicts of interest.

Author Contributions

L.M.Y. conceived of the study, conducted the analyses, and created initial drafts of the manuscript. K.E.P. contributed to the literature review and made improvements to the presentation of literature and results. H.S.B., III contributed to the literature review, contributed Stata code for normative scores and quantile regression, and provided guidance on presentation of quantile regressions. C.L.P. contributed to the literature review and made improvements to the presentation of literature and results. K.A.K. provided initial suggestions for the study, contributed theory on intervention and policy implications, and guided on the background, organization, and interpretation of the data. All authors have read and approve of this manuscript.

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Affiliations

  1. Department of Psychology, University of Southern California, SGM 826B, Mailroom 501, Los Angeles, CA, 90089-1061, USA

    Lisa M. Yarnell

  2. Department of Kinesiology and Health Education, University of Texas at Austin, 2109 San Jacinto D3700, Austin, TX, 78712-0360, USA

    Keryn E. Pasch

  3. Division of Management, Policy, and Community Health, University of Texas School of Public Health, Austin Regional Campus, University of Texas Administration Building (UTA), 1616 Guadalupe Street, Suite 6.300, Austin, TX, 78701, USA

    H. Shelton Brown III

  4. Division of Health Promotion and Behavioral Sciences, University of Texas School of Public Health, Austin Regional Campus, University of Texas Administration Building (UTA), 1616 Guadalupe Street, Suite 6.300, Austin, TX, 78701, USA

    Cheryl L. Perry

  5. Department of Health Outcomes and Policy, Institute for Child Health Policy, College of Medicine, University of Florida, 1329 SW 16th Street, Room 5130, P.O. Box 100177, Gainesville, FL, 32610-0177, USA

    Kelli A. Komro

Authors
  1. Lisa M. Yarnell
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  2. Keryn E. Pasch
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  3. H. Shelton Brown III
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  4. Cheryl L. Perry
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  5. Kelli A. Komro
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Correspondence to Lisa M. Yarnell.

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Yarnell, L.M., Pasch, K.E., Brown, H.S. et al. Cross-Gender Social Normative Effects for Violence in Middle School: Do Girls Carry a Social Multiplier Effect for At-Risk Boys?. J Youth Adolescence 43, 1465–1485 (2014). https://doi.org/10.1007/s10964-014-0104-0

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  • DOI: https://doi.org/10.1007/s10964-014-0104-0

Keywords

  • Violence
  • Middle school
  • Social norms
  • Gender