Parents expect when they send their children to school, those children will return home safely every afternoon. The sad reality is that with the rise in school violence, many parents no longer feel confident in this. The burden on school personnel has shifted from simply education to a much more daunting task of providing mental health services. Unfortunately, this shift has not been accompanied by a significant increase in mental health education and training for teachers. Mental health issues in schools are an increasingly problem today.

Recently escalating difficulties with violence, bullying, substance abuse, and other challenges surrounding the emotional well-being of students can leave school personnel struggling to provide safe and supportive environments for students while still meeting their educational needs. The ever-increasing demands paired with limited training and resources have left educators feeling frustrated, overwhelmed, and demoralized. They often say they feel ill-equipped to meet all of the educational, developmental, and emotional needs of students. This takes a heavy toll on their own emotional and mental well-being.

With this knowledge, the authors of this study set out to design a program aimed at helping educators and school staff recognize warning signs early to better identify students who may otherwise fail to be effectively assessed and treated appropriately. The overall goal of the training program is to more effectively help educators learn how to identify and ultimately connect at-risk youth with valuable mental health services. A literature review of school violence determined 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. It is clear that 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 (Monis et al, 2018, p. 5).

Methods

In order to test the efficacy of the training designed, the researchers developed a series of 20 vignettes, each of which described a hypothetical student and behaviors that might be observed by an educator. These vignettes were distributed in paper format to a group of 10 psychologists who were asked, based on their clinical experience and work with school-aged children, to identify whether the hypothetical student described in each vignette was or was not at risk for current or future emotional, functional, or behavioral problems that would warrant referral to a mental health professional.

The responses of this group of psychologists were analyzed. Vignettes that required revision for clarity were identified based on both scoring trends and feedback. The revised series of 20 vignettes was then distributed in paper format to a different group of 19 psychologists who were once again asked to identify if each hypothetical student was or was not at risk for current or future emotional, functional, or behavioral problems that would warrant referral to a mental health professional.

It is important to note that of the students described in the 20 vignettes, only five should have been identified as not at-risk. The psychologists used in this study had a wide variety of experience working in various areas of clinical psychology, including forensics, trauma, major affective disorders, psychotic disorders, early behavioral intervention, and family therapy. They treat patients across a wide age range from preschool to geriatrics. As a group, the psychologists had been practicing with a valid psychology license in at least one U.S. state from just under one year to over 25 years.

Following data collection from the second group of psychologists, 20 teachers were given a pre-test of the 20 vignettes in the results of paper format and without any training or ability to ask questions. They were asked, based on the information included in the vignettes, to identify students who they felt were at risk for emotional, functional, or behavioral problems.

Following completion of the pre-test, teachers participated in a 60-minute training aimed at helping them to identify risk factors for mental illness in children and adolescents. This training included identifying subtle and overt symptoms of mental illness or troubled students, differences in the clinical presentation among different age groups for conduct disorder, various teacher interventions and addressing commonly identified teacher concerns.

They were given a detailed review of warning signs and risk factors identified in the School Safety Program At-Risk Student Screener for youth developed by the Mental Health Center of Florida. The screener covers 20 known risk factors, including oppositional attitudes, irritability, aggression, anxiety, bullying, inattention, hyperactivity, depressed mood, deviant and delinquent behaviors, self-injury, drug and alcohol use, and suicidality, etc. Special attention was called to the ways in which risk factors and emotional difficulties may manifest differently across varying age groups, the rise in cyber-bullying, and other factors such as gender, socioeconomic status, and geographical region which may impact the normative factors involved in risk.

Following the presentation and discussion, the teachers were given a copy of the At-Risk Student Screener and a post-test containing the same 20 vignettes in paper format. They were instructed to once again identify students who they felt were at risk for emotional, functional, or behavioral problems, this time based on the knowledge they had gained from the training.

Following completion of the post-test, teachers were given the opportunity to discuss their answers and self-report of how their opinions had changed in various scenarios based on the training they received. The teachers who participated in the study had a wide range of experience teaching preschool through high-school aged students. Their years of experience ranged from first year teacher to over 30 years of classroom experience. It was hypothesized that the teachers would perform significantly better on the post-test following the training.

Results

To explore the unique contribution of the screening tool, a paired-samples t-test was conducted. Specifically, the analysis determined whether there was a statistically significant mean difference between the pre-test and post-test in terms of the teachers’ ability to better identify at-risk students based on their knowledge of risk factors. Prior to the analysis, a set of assumptions were considered. There were no outliers in the data as assessed by inspection of a boxplot for values greater than 1.5 box-lengths from the edge of the box. The difference scores for the pre-test and post-test were not normally distributed, as assessed by Shapiro-Wilk's test. However, the test was conducted since the paired-samples t-test is fairly robust to deviations from normality.

 

More specifically, the post-test elicited a mean increase of 2.30, 95% CI [1.375, 3.225] in performance when compared to the pre-test. There was a statistically significant increase in post-test performance when compared to pre-test performance, t(19) = 5.205, p < .000. Further, as reported by Cohen (1988), results revealed a large effect, d = 1.16.

 

Discussion

The data showed that the intervention and training for the teachers was effective at helping them to increase their knowledge about common risk factors in school-aged students to identify which students more accurately may be at risk. Following the training, teachers were better prepared to identify overt and subtle signs of common problematic, maladaptive, and risky behaviors, varying presentations of emotional distress, and other signs that a student may be at current or future risk for psychological, educational, or other significant problems.

 

This highlights not only the current deficits in knowledge among educators as a group, but also the value in training school personnel using a brief educational presentation and discussion, paired with the opportunity to use the developed At-Risk Student Screener as a guide to aid in better identification of at-risk students across a range of ages and various other factors. Future research should be conducted with a wider sample of teachers to better determine outcomes.

 

Additionally, it would be helpful, given a larger sample size, to break teachers into groups according to years of experiences and the ages of the students with whom they primarily work. This would better inform future amendments and additions to the overall training in order to improve global efficacy.

 

Ann Monis is the chief executive officer at the Mental Health Center of Florida, Fort Lauderdale. Elizabeth B. Hooper is the training director and senior staff psychologist at the Mental Health Center of Florida. Ricardo Buitrago is clinical director at the Mental Health Center of Florida.

Michael DeDonno is assistant professor at Florida Atlantic University, Boca Raton.

 

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.

 

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.

 

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

 

Monis, A., Conrad, J.B., & Hooper, E.B. Violence in Schools, Trends and Prevention: A Literature Review. American School Board Journal, 2018                

 

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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