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The two coders assigned to each publication subsequently met to discuss any discrepancies. When two coders did not agree on a code, the other team members were consulted and provided recommendations, so that a consensus was reached among all team members.

IBM SPSS Statistics 21 was used to conduct analyses focused on characterizing the features of included measurement strategies with frequencies and other descriptive statistics. In several situations, specifically those requiring analysis of responses to open-ended questions from the data extraction form, new variables were created to re-code the data extracted from the measurement strategies.

This process was used to determine all relevant bullying behavior contents. A total of 17 behavior content categories were identiied. One setting 2. The included measures were administered among youth between the ages of 3 and 25; the average age range was Table 1 provides more information on measure characteristics. The use of varying terminology by authors was captured in this review. About a third of the strategies used the term bullying either as a precursor to the measure e.

In two measures, self-report, peer nomination, and teacher-report were used in conjunction. The author-reported type s of bullying were captured for 38 of the 41 measures 7. For 29 measures However, 13 The content of the items included in the measures also varied drastically across publications. While we captured the author-stated type of bullying being measured as mentioned earlier i.

Table 2 lists the 17 behavioral content categories developed by analyzing the items in all measures and reports the measures that assessed each construct. Eleven measurement strategies Three Because most measures did not include an explicit definition of bullying, we identified which components of the recommended bullying definition were assessed by the measure e.

For the 32 measures where repetition was denoted, the study team determined how repetition was measured. How many times in the last week did you say these things to a friend? How physically strong is this student? Table 3 provides additional information about the measures that included definitions, the components included in the definition, and a detailed breakdown of these components.

Scoring strategies for each measure varied by publication. This summed score was then used as a continuous outcome variable where higher scores were predictive of higher levels of perpetration, victimization, or bystander experiences. Eleven measures Scores range from 0 to 24 for victimization and 0 to 20 for perpetration, with higher scores indicating more experiences as a victim or bully.

However, not all strategies reported the same types of statistics. Specifically, 13 Comparisons found convergent validity with significant mean differences on self-reports of being bullied between victims and non-victims among all four main factors—physical victimization, verbal victimization, social manipulation, and attacks on property.

Of the 41 measurement strategies, 37 See Table 3 for details on the reliability of each measure. Only one measure reported an overall test—retest i. One measure reported split-half reliability, where the measure was split into two sections and scores for each section were compared to determine consistency in measurement. The aim of the current study was to conduct a systematic review and content analysis of bullying measures administered to youth, teachers, and parents in an effort to gain a better understanding of the strategies employed and the specific components of bullying being measured.

Findings suggest that there are important discrepancies between bullying measurement strategies, such as the time frame used to assess when bullying occurred, the components included in bullying definitions, and the behavioral content of measures provided to participants. Of the 41 measures included in this review, most were implemented in school settings, and very few measured bullying occurring outside of schools or in homes.

Cyber-bullying, which has traditionally been viewed as an issue not addressed by schools, was not assessed by most of the measures included in this study. The most predominant method used to assess bullying was youth self-report. Because it is important to achieve the most accurate assessment of the frequency and magnitude of these behaviors, multiple methods should be considered.

For instance, prevalence estimates may increase as the awareness of what constitutes bullying increases, thus self-report alone may not be sensitive enough to detect real changes in the rate of bullying. In addition, the field knows very little about the accuracy of self-report bullying measurement. In fact, research by Cornell and Brockenbrough found very low agreement among student self-report, peer nomination, and teacher nomination of students as victims of bullying in a rural sample of middle school youth.

Interestingly, they found better agreement between peer nomination and teacher nomination at identifying both bullying perpetrators and victims. Because this research raises concern about the sole use of student self-report measurement methods, future research should aim to implement multiple-source reporting to assess bullying behaviors with a national sample of youth.

Regardless of reporting method, almost all of the measures in this review captured both victimization and perpetration of bullying. With increasing evidence that youth are often both victims and perpetrators, it is important to continue to capture both behaviors in measurement. Without capturing victimization, perpetration, and bystanding behavior measurement, it could be more difficult to target interventions for those most at risk.

The field of bullying is in desperate need of uniform terminology and definitions to describe these behaviors Swearer et al. In this review, authors used several terms to discuss bullying behaviors, including peer victimization and peer aggression. The use of inconsistent terminology is problematic for several reasons.

However, one of the key constructs in bullying definitions, as mentioned earlier, is the presence of a power differential or imbalance in the relationship between the victim and the perpetrator. Thus, this terminology is in direct conflict with the construct of bullying.

Many researchers have developed subscales that measure fighting separate from bullying. It is possible that these forms of aggression and violence differ by perceived reasoning and decision processes. Research by Crick and Dodge interpreted the differences between children who use proactive i. This illustrates the need to address bullying as a distinct construct that should be examined separately from physical fighting and aggression that is neither repeated, nor involves a power imbalance.

Further, this review uncovered 13 measures that included the term bullying in their strategy and 11 that included a bullying definition. Using the term bullying without providing additional guidance for youth in the form of a definition or list of behaviors may be problematic, as research is mixed on how youth perceive this term.

Using the term bullying in measurement may also impact prevalence. Land presented several terms to students i. The author found that a key component of bullying e. Similarly, research from Vaillancourt et al. Skepticism around using a researcher-developed definition without explicit examples of bullying behaviors has increased over time.

Vaillancourt et al. This finding has important implications for establishing accurate prevalence rates of bullying. In the current review, the components most often included in the definitions of bullying that prefaced bullying measures were power imbalance, intention to cause harm, and aggressive behaviors, and only four measures included all five components of bullying as recognized by experts in the field.

The exclusion of specific components of bullying behaviors from measures of bullying calls into question the validity of the construct being measured. The vast majority of publications included in this review did not provide a definition in their measurement strategy.

The current review provides a thorough examination of how measurement strategies with and without explicit definitions integrate the definitional components of bullying and can be used as a guide for bullying researchers in their plans for measuring bullying-related behaviors. Because bullying has been used as a catch-all phrase to encompass a broad category of behaviors i. The time frames used for reporting also vary drastically based on measurement strategy.

In fact, most of the measures included in the review did not provide a specified time range, which presents problems in terms of both comparing bullying rates within the sample of interest and between multiple samples. Among those that did provide a time frame, there were variations in the time frames assessed e. Although these variations in reporting periods may seem slight, the differences can result in great disparities in prevalence estimates, particularly depending on the time of year when measures are administered.

Estimating prevalence rates using such broad terms can be problematic since individuals may interpret the meanings of such terms differently. Overall, the differences in reporting time frames make comparing prevalence rates between samples difficult, if not impossible.

Almost all of the included measures provided Likert-type response options, less than half used binary response options e. The variation in response options likely impacts not only overall prevalence rates, but also the kind of information being reported. For instance, responses to open-ended questions may garner more or less detail about bullying behaviors, depending on the extent to which the respondent elaborates.

Finally, in terms of scoring the measures that assess bullying behaviors, it is difficult to synthesize results across measures. Most often, measures were summed to yield a total score and then characterized as continuous.

The characterization of bullying in a sample greatly depends on how measures are scored and on how bullies and victims are identified. Thus, scoring techniques are critical in establishing accurate estimates of bullying rates. In addition to the variability in establishing solid prevalence estimates based on the criteria described earlier, most bullying measurement strategies used in the field lack sufficient psychometric properties, including reliability and validity.

These characteristics are fundamental to accurately assessing bullying prevalence. In this review, almost all studies reported moderate to high reliability for their measures, indicating that they consistently yielded similar findings, but most did not assess the validity of the measure, thus leaving the question of whether the surveys accurately measured what they aimed to measure unanswered. Those that did assess validity mostly reported low convergent, discriminant, concurrent, and predictive validity, suggesting that these measures did not clearly assess the intended construct s.

While it is important for measures to be reliable so that researchers can be sure that they are consistently measuring their construct of interest, reliability does not imply validity. It is critical that researchers aiming to assess bullying behaviors are accurately measuring those behaviors, not only in terms readily interpreted by the researchers themselves, but also in terms that recognize the differing perspectives of the youths being surveyed.

Thus, in future implementation of measurement strategies, researchers should determine both the reliability and validity of their measures. There are several limitations of this review. One particular limitation is that several measures were excluded due to developer non-response to repeated emails for additional information. It is possible that the measures not included based on this factor may be different from the ones included, thus affecting our results.

Second, the publications with enough information to describe the measurement strategy tended not to include prevalence data, and therefore we were unable to analyze the data on prevalence by measurement strategy. Next steps should determine how to capture best the relevant prevalence or incidence data to make comparisons across measurement strategies.

Lastly, very few measures meeting our inclusion criteria included cyber-bullying items or were dedicated solely to measuring cyber-bullying behavior. A systematic review of cyber-bullying measurement conducted by Berne et al. The authors found that very few cyber-bullying measures stated that their aim was to measure bullying, nor were most measures assessed for reliability and validity.

Additional research is needed to better integrate cyber-bullying measures with traditional bullying measurement. Despite these limitations, the results of this study still provide important information about the measures currently being used to assess bullying behaviors, including the measurement strategies employed and the behavioral content assessed by the measures. There is much inconsistency in the manner in which bullying is measured by researchers.

These inconsistencies range from differences in terminology and temporal referent period to differences in definitional components and actual behaviors measured by the surveys. While these inconsistencies may seem minor, they most likely explain the wide variation in bullying prevalence rates obtained by researchers in the field. Our results further highlight the need for a consistent definition of bullying, which has major implications for the measurement of the construct and the prevention of its occurrence.

Future research should focus on integrating a honed definition of bullying into the development of new or improved measurement strategies so that bullying can be more accurately and precisely assessed. The authors would like to thank Dr. Laura Salazar for contributing feedback on drafts of the manuscript. The authors have no financial relationships relevant to this article to disclose. All authors certify that the abovementioned manuscript represents valid work and not been submitted for publication elsewhere.

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. National Center for Biotechnology Information , U.

Aggress Violent Behav. Author manuscript; available in PMC Jan 6. Alana M. Martell , a Kristin M. Holland , a and Ruth Westby b. Brandi N. Kristin M. Author information Copyright and License information Disclaimer. Copyright notice. See other articles in PMC that cite the published article. Abstract Bullying has emerged as a behavior with deleterious effects on youth; however, prevalence estimates vary based on measurement strategies employed. Goal of the current study This review identifies various measurement strategies of bullying behaviors among youth and provides suggestions for standardizing measurement for research and surveillance purposes.

Method 2. Literature search A systematic search was conducted for all bullying and cyber-bullying measurement strategies published between and Search results The search began in October, and concluded in April, Open in a separate window. Data extraction and coding process 2. Data extraction form A data extraction form was developed to capture all information required to complete this review.

Coding process Prior to coding all publications, all four members of the study team independently coded the same publication. Data analyses IBM SPSS Statistics 21 was used to conduct analyses focused on characterizing the features of included measurement strategies with frequencies and other descriptive statistics. Results 3. Table 1 Characteristics of the 41 included measures. Terminology and types of bullying The use of varying terminology by authors was captured in this review.

Assessment of behavioral content The content of the items included in the measures also varied drastically across publications. Table 2 Behavior content of the 41 included measures. Behavior content Count Percent Making fun, teasing, embarrassing 33 Use of definitions and measuring definitional components Eleven measurement strategies Table 3 Definition characteristics and measured components of included measures.

Scoring strategies Scoring strategies for each measure varied by publication. Test—retest reliability Only one measure reported an overall test—retest i. Split-half reliability One measure reported split-half reliability, where the measure was split into two sections and scores for each section were compared to determine consistency in measurement.

Discussion The aim of the current study was to conduct a systematic review and content analysis of bullying measures administered to youth, teachers, and parents in an effort to gain a better understanding of the strategies employed and the specific components of bullying being measured. Research limitations There are several limitations of this review. Conclusion There is much inconsistency in the manner in which bullying is measured by researchers.

Acknowledgments The authors would like to thank Dr. Financial disclosure The authors have no financial relationships relevant to this article to disclose. Conflict of interest The authors have no conflicts of interest to disclose. Disclaimer All authors certify that the abovementioned manuscript represents valid work and not been submitted for publication elsewhere. Funding source None.

References Atik G. Assessment of school bullying in Turkey: A critical review of self-report instruments. Procedia Social and Behavioral Sciences. British Journal of Educational Psychology. Cyberbullying assessment instruments: A systematic review. Aggression and violent behavior. Conventional wisdom on measurement: A structural equation perspective.

Psychological bulletin. A comparison of the Gatehouse bullying scale and the peer relations questionnaire for students in secondary school. Journal of School Health. Factors associated with bullying behavior in middle school students. Journal of Early Adolescence. Educational Psychology. Cyber victim and bullying scale: A study of validity and reliability.

The efficacy of non-anonymous measures of bullying. School Psychology International. Bullying status and behavior patterns of preadolescents and adolescents with behavioral disorders. Education and Treatment of Children. Variability in the prevalance of bullying and victimization: A cross-national and methodological analysis.

Handbook of bullying in schools: An international perspective. New York: NY: Routledge; Adult psychiatric outcomes of bullying and being bullied by peers in childhood and adolescence. JAMA Psychiatry. Identification of bullies and victims: A comparison of methods. Journal of School Violence. Assessment of bullying.

In: Jimerson S, Furlong M, editors. Handbook of school violence and school safety: From research to practice. Mahwah, NJ: Erlbaum; Social information-processing mechanisms in reactive and proactive aggression. Child development. Relational aggression, gender, and social psychological adjustment. Child Development. National Center for Education Statistics; Measurement in health behavior: Methods for research and evaluation.

San Francisco, CA: Wiley; Peer harassment, school connectedness, and academic achievement.

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