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The 2011 FCD-CWI Special Focus Report on Trends in Violent

Bullying Victimization in School Contexts for 8th, 10th, and 12th

Graders, 1991-2009

Kenneth C. Land, Vicki L. Lamb and Qiang FuDuke University

Presentation to the Foundation for Child DevelopmentApril 26, 2012

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Research Questions:

Child and youth bullying behaviors, especially in school contexts, have received increased attention during the past three or four years from the media, parents and the public, policy makers, and school administrators.

While this recent spotlight on bullying behaviors is undergirded by real incidents, important questions remain as to:

the extent of numerical increases in bullying behaviors,

the extent to which the recent upsurge in school bullying is historically unique,

and how anti-bullying efforts affect the prevalence and intensification of school bullying.

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Data Source: The Monitoring the Future (MTF) Project, a nationally representative study designed to explore trends and changes in values, behaviors, and orientations of American adolescents.

The MTF survey of 12th graders was initiated in 1975 and surveys of 8th and 10th graders have been conducted since 1991.

Every year, thousands of 8th, 10th, and 12th graders participate in this survey and respond to questions on a series of subjects, such as drug use, religious orientation, school performance, violence, and socio-economic status of their parents.

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Questions regarding four specific, serious forms of school bullying appear in the MTF questionnaire for the 12th graders since 1982 and the 8th and 10th graders since 1991:

“The next questions are about some things which may have happened TO YOU

while you were at school (inside or outside or in a school-bus). During the LAST 12 MONTHS, how often …”

1. Has an unarmed person threatened you with injury, but not actually injured you?2. Has someone threatened you with a weapon, but not actually injured you?3. Has someone injured you on purpose without using a weapon?4. Has someone injured you with a weapon (like a knife, gun, or club)?

The response categories are: 1="Not At All" 2="Once" 3="Twice" 4="3 or 4 Times" 5="5 or More Times“

Figure 1 shows the temporal trends of responses for 12th graders, 1982-2009.

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Statistical analyses of these data are complicated by two features illustrated in Figure 1:

1)the groupings of the frequency counts in the response categories,

and 2) the substantial year-to-year stochastic (random) variability in the responses

To address these analytic challenges, we applied statistical models to smooth the data so that major temporal trends can be detected and to estimate parameters of statistical frequency distributions that characterize the entire frequency distributions of responses in each year.

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Statistical Methods: To focus on temporal trends in the data, data smoothing by application of three-point moving averages first was applied to the observed frequency distributions in each of three adjacent years centered in each focal year.

Then the smoothed frequency distributions were analyzed by

application of zero-inflated Poisson (ZIP) statistical models. ZIP models are appropriate for modeling data on frequency distributions that have so-called extra density or more observations than expected by conventional Poisson models at the zero frequency, which is the case for the bullying frequency data.

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The charts shown below show two estimated ZIP parameters for smoothed data series of the annual frequency distributions of bullying victimization for each of the four forms of bullying for the past two decades: (1)the percent of students exposed to, or at risk of, bullying behaviors (P),

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(2) Among those students at risk of bullying, the intensity of bullying as measured by the average number (λ) of times students exposed to bullying were bullied in the past 12 months.

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Statistical Methods: Graphs of the time trends in the estimated P and λ parameters of the ZIP bullying frequency distributions for the 8th, 10th, and 12th graders show evidence of age, time period, and birth cohort dependence.

Accordingly, these estimated parameters were subjected to an age-period-cohort (APC) analysis by application of the Intrinsic Estimator (IE) method recently described by Yang, Schulhofer-Wohl, Fu, and Land (2008):

Yang Yang, Sam Schulhofer-Wohl, Wenjiang J. Fu, and Kenneth C. Land 2008 “The Intrinsic Estimator for Age-Period-Cohort Analysis: What It Is and How To Use It,” American Journal of Sociology, 114(May):1697-1736.

The results are shown in the following charts.

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Summary

The trends over the past two decades in the estimated exposure (P) and intensity (λ) of the ZIP distributions of the four types of bullying behaviors lead to the following conclusions:

Overall, there is a tendency for the age, time period, and birth cohort components of trends in the exposure and intensity parameters of the two “threat” and the two “injury” forms of bullying behaviors, respectively, to move together, that is, to covary over time.

This two-by-two covariation is most pronounced for the exposure parameter.

The intensity parameter for the injury with a weapon form of bullying shows the strongest time period and birth cohort effects.

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Summary, Continued

Age/Grade Effects:

Eighth graders had the highest percentages exposed (P) and intensity (λ) to each of the four bullying behaviors, followed by 10th graders, with the 12th grade having the lowest rates of exposure and intensities of bullying among those bullied.

Correspondingly, the age-period-cohort analyses show that the estimated age/grade effects for both the bullying exposure (P) and intensity (λ) parameters show monotonic declines from the age-13/8th grade to age-15/10th grade to age-17/12th grade.

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Summary, Continued

Time Period Effects:

The percents of 8th graders exposed (P) to the four specific types of bullying behavior all began an upward trend starting around 2002-2003 – a time period effect.

For all three ages/grades, there were higher rates of being exposed (P) to bullying behavior during the early 1990s than in the 2000s, with the exception of being injured without a weapon. The highest exposure rates for the latter type of bullying occurred in the 2006-2010 years.

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Summary, Continued

Birth Cohort Effects:

There was a cohort effect from 10th to 12th grade for increases in the percent exposed (P) to being threatened with a weapon – as they aged into the 12th grade, the 10th graders brought with them their higher prevalence of this form of bullying.

A longer cohort effect was shown from 8th to 10th to 12th grade in the increased intensity (λ) of occurrences of being threatened with a weapon.

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Summary, Continued

Birth Cohort Effects:

The age-period-cohort analysis shows striking cohort effects on the percent exposed (P) to the four bullying behaviors – reaching a low point with the 1987 birth cohort, increasing to the 1993 birth cohort, and then leveling off with the 1994 cohort. These effects are stronger for the two most severe forms of bullying behaviors involving injuries.

The age-period-cohort analysis estimates of cohort effects for the intensity of these bullying behaviors for those bullied (λ) show an opposite cohort trend – peaking with the 1987 birth cohort and declining to the 1993-1994 cohort.

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Summary, Continued

In other words, there is evidence of an inverse relationship between the prevalence rate/percent exposed to bullying parameter (P) and the intensity of bullying among those bullied parameter (λ) – when the prevalence rate declines, the intensity rate tends to increase, that is, when the overall likelihood of bullying goes down, the intensity of bullying among those bullied tends to go up.

This inverse relationship is evidenced in the second half of the 2000-2010 decade: As increased attention has been given to bullying by the media, parents, school administrators, and policy makers, the percentages of adolescents exposed to these serious forms of bullying behaviors declined – but adolescents who were victims of bullying during the 2006-2010 years experienced higher numbers of bullying incidents.

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Summary, Continued

Numerical Implications of the Temporal Trends in the Estimated Percents Exposure: The implications of these statistical models and estimated parameters for numbers of middle- and high-school students who were exposed to each of the four serious forms of bullying behaviors for each year from 1991 to 2010 are shown in Figure 15.

Since some students may have experienced two or more of the bullying behaviors during any given year, the estimated numbers cannot be summed across all four types for any given year.

Nonetheless, given the severity of these forms of bullying behaviors, the numbers are quite large.

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CONCLUSIONS

Findings from CWI analyses of school bullying:

help to place recent levels and trends in exposure to, and intensity of, serious forms of bullying in historical perspective; establish that the most recent upturn in school bullying began in the early part of the 2000-2010 decade – in the aftermath of the 911 terrorist attacks and at the dawn of the spread of availability of the high-speed Internet; show how a period effect (in 2002-2003) on the upturn in bullying among 8th graders turns into a cohort effect as they became 10th and then 12th graders; and help us to identify demographic, socioeconomic, and behavioral characteristics of students that are related to the risk of bullying victimization.