Students and Perceived School Safety: The Impact of School Security Measures

Abstract

Although secondary school violence has actually decreased, public concern over student safety is still prevalent. One response to publicized school violence has been the implementation of security measures (metal detectors, cameras) and policies (visitor sign in, locked doors). While these changes may decrease school violence, little research has examined the effect these security measures have on student perceptions of school safety. Utilizing the National Longitudinal Study of Adolescent Health (AddHealth), this study found that metal detectors and the number of visible security measures employed in school were associated with a decrease in student reports of feeling safe. Students who were male, White, had higher GPAs, and reported feeling safe in their neighborhood were more likely to report feeling safe at school, while those who experienced prior victimizations, had larger class sizes, and who attended schools that had disorder problems were more likely to report not feeling safe at school.

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Notes

  1. 1.

    Because we had a large sample size and our primary outcome of interest was the opinion of those who endorsed either a feeling of safety or not, we chose not to include those individuals who were indifferent and responded “Neither agree nor disagree.” Initial crosstabs indicated there was no gender or racial differences among this indifferent group. The remaining four categories were strongly disagree (n = 348), disagree (n = 1,088), agree (n = 5,642), and strongly agree (n = 2,941). Through visual inspection, we recoded the variable based on the obvious dichotomy of agree and disagree. Any inclusion of the indifferent group (17.7 % prior to complete case analysis) at this time into the “agree” group would have increased this category well over 90 %. The resulting minimal variability in the safety variable would have led to questionable reliability of the estimates. Therefore, we are confident in our categorization of this variable.

  2. 2.

    The Wave II school administration questionnaire was used to update the information about the schools. Due to the rapidly changing school environment, questions were asked in the 1996 Wave II phone survey about issues that may not have been relevant in 1994 or Wave I. (personal communication with Dr. Joyce Tabor, AddHealth, 8/21/2012).

  3. 3.

    Due to errors in the measurement of gender at Wave I, gender measured at Wave II was used in the analyses as recommended by AddHealth (University of North Carolina Population Center, 2010).

  4. 4.

    Race was originally coded as White, Black, American Indian, Asian, and other race. The categories, American Indian (n = 342), Asian (n = 962), and other race (n = 159), accounted for only 11 % of the variable which would not justify creating a third race category. In addition, we needed to preserve the degrees of freedom in the multivariate analysis. Thus, we chose to create a dichotomous race variable of White and Non-White.

  5. 5.

    School size was based on the actual school roster which was positively skewed (ranging from 47 to 3,546 students per school). The natural log was used to transform this variable to approximate a more normal distribution.

  6. 6.

    Ordinary least squares (OLS) regression is not appropriate for this type of data given the violation of the assumption of independent error terms (Bingenheimer & Raudenbush, 2004; Kreft & De Leeuw, 2007; Raudenbush & Bryk, 2002).

  7. 7.

    The results are available from the first author on request.

  8. 8.

    According to Van Belle (2002), multivariate regression analyses should include a minimum of 10 cases per variable included in the regression equation to ensure the stability of the regression coefficients. The number of school level units determines the accuracy of estimation of the Level-2 variance-covariance matrix (Raudenbush & Bryk, 2002). Therefore, we applied this restriction to the Level 2 (i.e., schools) sample size.

  9. 9.

    Because the school context is unique to each school regarding its combined use of physical and non-physical security measures and policies, we need to account for the relative differences of student fear within each school (i.e., group mean center) instead of looking simply at the main effects of the security measures adjusting for student covariates (i.e., grand mean center) (Bingenheimer & Raudenbush, 2004; Hofmann & Gavin, 1998; Kreft & De Leeuw, 2007; Raudenbush & Bryk, 2002).

  10. 10.

    Although several variables appear not to have a large enough variation (i.e., video, bars, hall passes, visitor, closed campus, public school, rural, and northeast), initial crosstabs indicate that the expected frequencies for these variables were above the minimum requirement.

  11. 11.

    Initial multivariate analyses (not shown) included three additional dichotomous school variables (urban and suburban/rural, south and other, and traumatic events). These three variables were not significant predictors of school safety and were removed from the final analyses to preserve degrees of freedom.

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Acknowledgments

This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis. The authors would like to thank Lynn Addington, John Sloan III, Heith Copes, and the two anonymous reviewers for their comments on a draft of this manuscript.

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Correspondence to Suzanne E. Perumean-Chaney.

Appendix A

Appendix A

Table 3 Correlations for Level-1 and Level-2 Variables (N = 13,386)

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Perumean-Chaney, S.E., Sutton, L.M. Students and Perceived School Safety: The Impact of School Security Measures. Am J Crim Just 38, 570–588 (2013). https://doi.org/10.1007/s12103-012-9182-2

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Keywords

  • School safety
  • School security measures
  • AddHealth
  • Student perceptions