School violence and efforts to curb school violence have been given more attention in recent years due to recent national events. Research findings indicate that school violence is manifested in different forms and at different rates depending on the age group. Findings from the School Survey on Crime and Safety: 2015-2016 (Diliberti et al., 2017), determined that the rate of violent encounters per 1,000 students was greater in middle schools (27 incidents) than in high schools (16 incidents) and primary schools (15 incidents). This same study discovered that about 39 percent of schools reported at least one student threat of physical attack without a weapon, compared with 9 percent of schools that reported threats with weapons. Additionally, a higher percentage of middle schools reported daily bullying by students or bullying occurring at least once a week (22 percent) than did high schools (15 percent) or primary schools (8 percent).

Also, cyberbullying appears to be a significant concern per this study. Of the schools with a student enrollment size of 1,000 or more, during the 2015–16 school year, 27 percent reported cyberbullying occurring between daily and at least once weekly. Moreover, the statistics on efforts to curb violence through the School Survey on Crime and Safety: 2015-2016, compared programs geared towards preventing violence in suburbs, cities, and rural areas. They ascertained that there are a higher percentage of schools in suburbs (74 percent) and cities (73 percent) with such programs as compared to schools in towns (62 percent) and rural areas (51 percent).

Violence Needs to Be Addressed

Overall, it seems clear that violence, regardless of the form, is a significant issue needing to be further addressed in school systems. When analyzing this issue, it is necessary to look at the nature of problem behaviors in the school systems across different age groups. To that end, a study by Harrison et al. (2012) investigated the most common problem behaviors seen in a sample of 3,600 children and adolescents. They discovered 17 common problem behaviors that fit four different domains. The primary internalizing type behavior problem seen in children was in anxiety, which often manifests in the form of distractibility, poor attention span, and hyperactivity. Academic problems were also common and took the form of not following directions and problems with spelling, math, reading, and writing.

With respect to the adolescent population, teachers rated anxiety as the only internalizing problem area and the externalizing problem area again took the form of distractibility, hyperactivity, and “immature behavior.” Learning problems with adolescents primarily involved an inability to follow directions with task accuracy. While some of these behaviors may appear to be relatively benign compared to the violence discussed earlier in this review, it is necessary to take these problem areas just as seriously as they can develop into more severe behaviors if unaddressed. For example, a child who is having difficulty completing school work due to poor attention span, may later develop more maladaptive behaviors and conduct problems if his or her academic needs are not being met.

Role of Mental Health

While the review thus far has addressed general problem areas, a more detailed analysis of the manifestation of specific mental health diagnoses can guide teachers to know the symptoms to look for in at-risk students as well as guiding mental health professionals towards evidenced-based interventions. Another reason to review the breakdown of mental health diagnoses is the high prevalence in which we see mental health related diagnoses in both children and adolescents. Parent-reported information from the 2011-12 National Survey of Children’s Health indicated that one out of U.S. children aged 2 to 8 years had a diagnosed mental, behavior, or developmental disorder (MBDD). Children of the following three categories were more likely to have a MBDD: Boys, those children aged 6 to 8 years, and Non-Hispanic white children. Also, children were more likely to have a MBDD if they were from families living at less than 100 percent of the federal poverty level, and English-speaking families. This survey further broke down the mental health diagnoses of children and adolescents by age group. They looked at statistics of a larger age group including 3-17 years as well as a more focused analysis of adolescents ages 12-17 years.

Within ages 3-17 years, children were identified as having diagnoses of: Attention-deficit/hyperactivity disorder (6.8 percent), Behavioral or conduct problems (3.5 percent, Anxiety (3.0 percent), Depression (2.1 percent), Autism spectrum disorder (1.1 percent), and Tourette syndrome (.2 percent). Tourette’s syndrome was identified primarily among children aged 6-17 years. When looking more specifically at the adolescent population (aged 12-17 years), the most common diagnoses seen were an illicit drug use disorder in the past year (4.7 percent), alcohol use disorder in the past year (4.2 percent), and cigarette dependence in the past month (2.8 percent). Also noteworthy is that suicide was the second leading cause of death in the adolescent group aged 12-17 years in 2010.

Additional research has focused on depression, particularly within the adolescent population (Kaltiala-Heino et al., 1999; Kaltiala-Heino, et al., 2000; and Csorba et al., 2009). Kaltiala-Heino and colleagues (1999) discovered an increased prevalence of depression and suicidal ideation among a sample of adolescent students aged 14 to 16, who were both the perpetrators and recipients of bullying behavior. Kaltiala-Heino et al. (2000) also found that depression was commonly associated with bullying and being bullied, but also noted that symptoms of anxiety and psychosomatic presentation were also seen. Moreover, Csorba et al. (2009) found that in a sample of 105 Western-Hungary adolescent outpatients, 60 percent of the clinical self-injury subgroup experienced a present or past episode of major depression. Thus, it would appear that the identification of symptoms of depression in school-aged children, particularly around the middle school to high school years, would be of great importance when intervening with at-risk youth.

Moreover, attention deficit concerns appear to be another significant concern seen both in younger children and adolescents, which can have both academic and behavioral implications. Attention-Deficit Hyperactivity Disorder (ADHD) is a diagnosis frequently discussed in the literature pertaining to children and adolescents. Goldman and colleagues (1998) analyzed epidemiologic studies using standard diagnostic criteria and ascertained that between 3 percent to 6 percent of school-aged children suffer from ADHD. Also, this disorder is often over identified by teachers. Havey et al. (2005) discovered that teachers identify students as having ADHD at higher rates than the expected prevalence rates specified in the DSM-IV.

Other Environmental Factors

At this juncture, a discussion on other student and environment factors is also warranted as it gives teachers and school administrators other issues to consider when determining who is at-risk for behavioral and emotional problems. Several studies have focused on the specific characteristics, traits, and environmental factors of students considered to be at-risk for emotional disturbances and violent behavior. Truancy and GPA have been tied to such issues as substance use, suicide, and delinquency in at-risk students (Hallfors et al., 2006). Mitchell and company (2015) discovered a linear relationship between the number of adversities a student has experienced and subsequent depression and aggression scores. Another study analyzed the role of rejection and other specific interests of those students who were the perpetrators of recent school shootings (Leary et al., 2003).

Not surprisingly, the researchers discovered that both acute and chronic rejection were common experiences with these school shooters. An in interest in firearms or bombs, a fascination with death or Satanism, or psychological problems including depression, impulse control, or sadistic tendencies were also common. Also, students who have threatened or attempted suicide made up ¾ of school shootings in a study by Vossekuil et al. (2000). Other factors in at-risk students that seem to go unnoticed include on-going patterns of teasing; being the victim or perpetrator of bullying; ostracism; history of being taunted, teased, harassed, and publicly humiliated; recent romantic rejections, depression, alleged abuse of animals, and irritability (Leary et al., 2003).

Furthermore, researchers have examined the influence of various support people on curbing violent behavior in at-risk students and the various methods of detecting those students who are at-risk. Kalil (2001) found that a school training for teachers, students, administrators, and parents using psychoeducational workshops had an impact on subsequent violent behavior reduction six months later. However, also important is the ability of teachers and administrators in detecting the behaviors, characteristics, personality traits, and general background factors that are often seen in at-risk students. Lane (2003) examined the ability of teachers, using their own judgment without the aid of external devices such as screening instruments, in recognizing those at-risk students. Results of this study suggest that teachers are effective (on their own) at differentiating at risk versus normally developing students.

Screening Methods

Screening instruments have also been developed that can help to aid teachers and other support staff. Cook et al. (2011) discovered that a student internalizing behavior screening instrument was able to identify students who were behaviorally and emotionally at-risk. Also, a study in Europe found that a school-based screener significantly increased the successful detection of students requiring mental health services (Kaess et al. 2013). Thus, it would appear that successful detection of at risk-students is possible if appropriate measures are used in identifying those factors often portrayed by these students.

However, while detection of at-risk students is a necessary step when making the referral to mental health services, it is not enough. An efficient systematic method for teachers to make such referrals would also need to be involved. A school-based mental health task-force or mental health referral committee may help alleviate some of the pressure placed on teachers when attempting to get at-risk students the help they need. A review of the literature discovered studies addressing the involvement and implementation of crisis intervention teams (Knox & Roberts; Poland, 1994). However, there does not appear to be any research on the prevalence of mental health task forces within schools (pre-crisis) and their effectiveness. Thus, future efforts to improve systemic mental health referral channels should involve such committees as this may prove to be a missing link within the structure.

Furthermore, the systemic flaws and recent school shootings prompted a “toolkit” which was assembled and written recently by the Melissa Institute: For Violence Prevention and Treatment, a non-profit educational organization based in Miami, following the “March for Our Lives” demonstration which took place in Washington, D.C., on March 24, 2018. This toolkit proposed possible next steps schools can implement to promote safety and prevent violence. “Tool 5: Principal’s Checklist” provided specific steps principals can implement and divided these steps into three categories: primary (basic prevention for all students), secondary (specific interventions for at-risk students), and tertiary (more intensive measures for the most at-risk students) prevention measures.

Primary prevention measures may include trainings on school safety, crisis management, bullying intervention to teachers, staff, and other school administrators; implementing a reporting system for bullying and school violence; teaching students skills in self-regulation, social problem-solving, and conflict resolution; executing a peer-warning system that supports confidential student communication to identified adults; and establish a crisis intervention team. Secondary prevention methods comprise school-wide policies and procedures such as data collection to evaluate intervention programs; efforts to reinforce students integration with schools; evaluating existing interventions for at-risk students; a push to treat office referrals as teaching opportunities; and trainings to reduce both in-school and out-of-school suspensions.

Finally, the tertiary prevention measures which, by nature, are more intervention-based for those at-risk students with the more severe behavioral and emotional concerns may include intensive behavior intervention plans for those students exhibiting chronic and persistent behavior problems; evidence-based skills training for chronic anger management and aggression problems; trainings directed to school personnel on how to de-escalate and defuse students with aggression and violent behaviors; and procedures identifying students with a background of Adverse Childhood Experiences (high ACE scores).

Moreover, while each of the three categories constitutes problem behaviors and concerns of varying severities with tertiary prevention involving the most severe cases, all three should be given equal importance and value as the idea is to curb problem behavior (and even prevent problem behavior) at the early stages. Thus, this checklist of sorts can be considered as a type of “Principal Report Card” and accents the requisite “to pay attention to small things” as a way of promoting physical, social, and emotional safety. Tool 6 of the kit provides further instruction on the implementation of these procedures and stresses the importance of ameliorating any newly established fears associated with violence in schools. While recent school shootings have made the news and the implications should be given attention, one must also not neglect base rate data. As the Melissa Institute points out, schools continue to be the safest places for children and youth. The actual probability of any child at random being murdered inside a school is upwards of 1 in 4 million.

In addition, Tool 6 further delineates the challenges associated with implementing new policies and procedures such as those described herein and emphasizes the need for schools to recognize the challenges at the outset. New polices often necessitate changes in social norms and such changes should involve, not simply the schools themselves, but outside support from families, neighbors, the mass media, and government. New programs should be tailored to the specific culture and linguistic needs of the communities in which the schools inhabit. Finally, schools are encouraged to implement new procedures geared towards safer learning environments in a systematic, progressive, and data-informed manner.

Thus, it would seem plausible that the implementation of an organized system involving the tools would be effective at treating the issues discussed here. Some schools may already have a few of the key components in place, but lack others. Other schools may include all components but lack the organization necessary to execute an efficient and well-coordinated effort among school teachers and administrators towards effective detection, referral, and prevention.

Safety Gap

Overall, the literature suggests that there exists a gap between educators and other school personnel and the necessary training, knowledge, and expertise needed to effectively combat problematic behaviors, mental health issues, and other contributing factors, which negatively impact the safety of the learning environment. There exists a need for mental health professionals who are seasoned and trained in these areas to provide direction and instruction to administrators and teachers on evidence-based detection and intervention with at-risk students.

A mental health professional or mental health consultant team can advise on the detection of bullying, particularly those subtle behaviors that go un-noticed, including when to refer to an outside mental health professional. The consultant team can educate teachers on the influence of certain academic issues/learning disabilities which may contribute to the development of conduct disturbances and when these students should be directed to a mental health professional. The team can instruct teachers and administrators on the most common and salient mental health diagnoses observed in students of different age groups, how to initially intervene with such students, and then how/when to relegate to a mental health referral team.

Furthermore, while a mental health consultant team can help accelerate the assignment of an at-risk student to a local mental health professional, it is the role of the teacher and the teacher/student relationship that should be given paramount attention as it is the teacher who is generally the first contact. An effective partnership between mental health providers and educational staff aimed at providing support and education to the teachers on effective identification of at-risk students could be the key to instilling teachers with a new set of skills in this area. An additional component of this training would be to provide teachers with skills in verbal de-escalation and other crisis intervention strategies. Future research should take this literature into account and move toward program development in this area to increase early detection and intervention for at risk youth in the hopes of increasing safety in school settings.

Ann Monis (drann@mhcflorida.com) is the CEO of the Mental Health Center of Florida where Elizabeth B. Hooper (drbetsi@mhcflorida.com) is training director and senior staff psychologist. J. Bryan Conrad. Ph.D., (drbryan@mhcflorida.com) is a licensed psychologist and practices out of Coastal Neuropsychology in Clearwater, Florida.

References:

2011/12 National Survey of Children’s Health. Child and Adolescent Health Measurement Initiative (CAHMI), “2011- 2012 NSCH: Child Health Indicator and Subgroups SAS Codebook, Version 1.0” 2013, Data Resource Center for Child and Adolescent Health, sponsored by the Maternal and Child Health Bureau. www.childhealthdata.org.

Cook, C. R., Rasetshwane, K. B., Truelson, E., Grant, S., Dart, E. H., Collins, T. A., & Sprague, J. (2011). Development and validation of the student internalizing behavior screener: Examination of reliability, validity, and classification accuracy. Assessment for Effective Intervention, 36(2), 71-79.

Csorba J, Dinya E, Plener P, Nagy E, & Pali E. (2009). Clinical diagnoses, characteristics of risk behaviour, differences between suicidal and non-suicidal subgroups of Hungarian adolescent outpatients practising self-injury. European Child and Adolescent Psychiatry,18(5), 309–320.

Diliberti, M., Jackson, M., & Kemp, J. (2017). Crime, Violence, Discipline, and Safety in U.S. Public Schools: Findings From the School Survey on Crime and Safety: 2015–16 (NCES 2017-122). U.S. Department of Education, National Center for Education Statistics. Washington, DC. Retrieved April 8, 2018 from http://nces.ed.gov/pubsearch.

Hallfors, D., Vevea, J. L., Iritani, B., Cho, H. S., Khatapoush, S., & Saxe, L. (2002). Truancy, grade point average, and sexual activity: a meta-analysis of risk indicators for youth substance use. J Sch Health. 2002 May; 72(5), 205–211.

Harrison, J. R., Vannest, K., Davis, J., & Reynolds, C. (2012). Common problems behaviors of children and adolescents in general education classrooms in the United States. Journal of Emotional and Behavioral Disorders, 20(1), 55-64. https://doi.org/10.1177/1063426611421157

Havey, J.M., Olson, J. M., McCormick, C, & Cates G. L. (2010) Teachers' Perceptions of the Incidence and Management of Attention-Deficit Hyperactivity Disorder, Applied Neuropsychology, 12(2) 120-127,DOI: 10.1207/s15324826an1202_7

Goldman LS, Genel M, Bezman RJ, Slanetz PJ, for the Council on Scientific Affairs, American Medical Association. (1998). Diagnosis and Treatment of Attention-Deficit/Hyperactivity Disorder in Children and Adolescents. JAMA, 279(14), 1100–1107. doi:10.1001/jama.279.14.1100

Kaess, M., Brunner, R., Parzer, P., et al.. (2014). Risk-behaviour screening for identifying adolescents with mental health problems in Europe. Eur Child Adolesc Psychiatry 23(7), 611-620. https://doi.org/10.1007/s00787-013-0490-y

Kalill, P. M. (2001). Developing an effective prevention strategy for school violence through psycho-educational training. Dissertation Abstracts International: Section B: The Sciences and Engineering, 61(10-B), 5621.

Kaltiala-Heino, R., Rimpela, M., Marttunen, M., Rimpella, A., & Rantanen, P. (1999). Bullying, depression, and suicidal ideation in Finnish adolescents: school survey. BMJ, 319(7206), 348-351. doi: https://doi.org/10.1136/bmj.319.7206.348

Kaltiala-Heino, R., Rimpela, M., Rantanen, P., & Rimpela, A. (2000). Bullying at school – an indicator of adolescents at risk for mental disorders. Journal of Adolescence, 23(6), 661-674. https://doi.org/10.1006/jado.2000.0351

Knox, Karen & R Roberts, Albert. (2005). Crisis Intervention and Crisis Team Models in Schools. Children & Schools. 27. 10.1093/cs/27.2.93.

Lane, K. L. (2003). Identifying young students at risk for antisocial behavior: The utility of “teachers at tests.” Behavioral Disorders, 28(4), 360-369.

Leary, M. R., Kowalski, R. M., Smith, L., & Phillips, S. (2003). Teasing, rejection, and violence: Case studies of the school shootings. Aggressive Behavior, (29), 202-214. DOI:10.1002/ab.10061

Mitchell, K. J, Tynes, B., Umana-Taylor, A. J., & Williams, D. Cumulative experiences with life adversity: Identifying critical levels for targeting prevention efforts. Journal of Adolescence, 43(August 2015), 63-71. https://doi.org/10.1016/j.adolescence.2015.05.008

Poland, S. (1994). The role of school crisis intervention teams to prevent and reduce school violence and trauma. School Psychology Review, 23(2), 175-189.

 

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