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Introduction
Students entering today’s high schools bring with them a variety of experiences – from family interactions to school activities, and sports participation to community involvement. As the definition and dynamics of these institutions change over time, so too are the experiences of the students. Looking specifically at changes within families; some result in negative impacts on student’s experiences and lives. What is the impact of negative family experiences on a child/student? How many negative experiences can they withstand? And what can our schools do to support the students affected?
In today’s environment, it is no longer sufficient for the educational system to relegate itself to reading, writing, and arithmetic. Instead, to adequately support the development of students, education must reach beyond mere academics. One area of additional support would be students’ mental health and wellness. Too often deficiencies in mental health and wellness support results in silent suffering, which can bubble over to today’s headlines of abuse, bullying, suicide, and even mass shootings.
Each year a new class of students enters high school. How can Education assess the relative mental health and wellness of each class? How can it assess the wellness of an individual student? What trending information is available to reflect changing health demographics of the student body? Most important, how can education help to repair the mental health and wellness of the students?
This paper will analyze the results of an Adverse Childhood Experiences (ACE) test. This mental health and wellness tool, as leveraged through Data Analytics, can describe, predict, and prescribe Education toward a targeted response leading to the overall benefit and wellbeing of their students.
Related Work
The Adverse Childhood Experience [ACE] test came to fruition in the 1990s as a result of sustained high dropout rates of 50% among participants enrolled successfully in a weight loss program under the San Diego clinic. Vincent Felitti, head of Kaiser Permanente’s Department of Preventive Medicine in San Diego (Felitti et al., 2019), interviewed 286 people who had left the program and realized a majority had experienced some form of childhood sexual abuse. Thus, the ACE test was designed with the goal to measure an individual’s mental health and wellness and study the impact on later-life health and well-being.
Developed by Kaiser Permanente and the Centers for Disease Control and Prevention, the ACE test asks ten “Yes/No” questions involving life events. These include their experiences involving alcoholism, verbal and physical abuse, household stability, etc. Specifically, the ten questions asked at the 2018 Mental Health Fair were as follows:
- Q1: Did a parent or other adult in the household often or very often… Swear at you, insult you, put you down, or humiliate you? or act in a way that made you afraid that you might be physically hurt?
- Q2: Did a parent or other adult in the household often or very often… Push, grab, slap, or throw something at you? or ever hit you so hard that you had marks or were injured?
- Q3: Did an adult or person at least 5 years older than you ever… Touch or fondle you or have you touch their body in a sexual way? or attempt to actually have oral, anal, or vaginal intercourse with you?
- Q4: Did you often or very often feel that… No one in your family loved you or thought you were important or special? or your family didn’t look out for each other, feel close to each other, or support each other?
- Q5: Did you often or very often feel that… You didn’t have enough to eat, had to wear dirty clothes, and had no one to protect you? or your parent were too drunk or high to take care of you or take you to the doctor if you needed it?
- Q6: Were your parents ever separated or divorced?
- Q7: Was your mother or stepmother: Often or very often pushed, grabbed, slapped, or had something thrown at her? or sometimes, often, or very often kicked, bitten, hit with a fist, or hit with something hard? or ever repeatedly hit over at least a few minutes or threatened with a gun or knife?
- Q8: Did you live with anyone who was a problem drinker or alcoholic, or who used street drugs?
- Q9: Was a household member depressed or mentally ill, or did a household member attempt suicide?
- Q10: Did a household member go to prison?
Ideally, an individual would respond “No” to each of the 10 questions. Each “Yes” response corresponds to an increased Adverse Childhood Experience. Research shows that an increasing number of “Yes” responses has a negative impact on an individual’s mental health, resulting in a greater likelihood of suicide and a decreased life expectancy, (Storrs, 2009).
Data Screening and Sanitization
The data was compiled during a 2018 Mental Health Fair at a Central Pennsylvania high school. Among the many stations at the Fair was one that invited students to take the ACE Test. The ACE Test station had a brief description as to the nature of the questions and was administered by two students from the 12th grade class. Due to its personal and serious nature, students were given the option of stopping their test at any time; and guidance counselors were prepared to talk with any students who became upset.
Besides a time-stamp of participation, there was intentionally no record of student identification. Respondents were advised that results were totally confidential. Along with the ten “Yes/No” ACE question responses, students were asked for their Gender and Grade. ACE Test results were compiled electronically. Below is a screenshot of the summary of the raw dataset for all independent variables. From original dataset of 457 students, 407 student’s data records made it to the final analysis. Detailed analysis is mentioned below.[image: ]The initial raw data had 457 students who participated in the ACE Test. Data screening involved examination of test results with inaccurate data or missing data. The gender portion of the test provided choices for male, female, and other. Twenty-seven test results were removed because of unreliable responses to the “other” option of the gender question. Another 18 tests were removed because not all ten questions were answered. It is the responses from these resulting 407 students that comprise the data from this paper.
Technical Details of the Analysis
Student Body Analysis
The ACE Test score by student is shown in the table below.
Among all ACE Test scores, 189 respondents scored 0, while 59 scored 1. This is not surprising, as we would hope and expect that most students do not have any Adverse Childhood Experiences with a majority of ACE Test scores at zero or one. The distribution of the data’s total ACE Test score has a positive skew.
The distribution of the data’s total ACE Test score has a positive skew. It would be surprising if any school’s ACE Test distribution did not have a right skew.
The usefulness of this data is at two levels. First, the quantifiable amount of skewness can be used to estimate the relative mental health and wellness of the student body. This can be interpreted as a trend within the high school itself, or compared against other high schools for relative mental health and wellness. Second, individual student results show that two answered “Yes” to each of the ten ACE questions, while another eight responded “Yes” to nine questions. Research suggests that a score of six on the ACE test reduces life expectancy by 20 years, (Storrs, 2009). Thirty-four of the 407 respondents, or 8%, reached this threshold. There is an opportunity for Education to uses results of the ACE Test to initiate targeted intervention for their most as-risk population.
Gender Analysis
229 of the 407 respondents [56%] were female, while 178 [44%] were male. The mean female ACE Test score was 1.9 “Yes” responses, while mean male score was 1.5 “Yes” responses. This higher mean is partially explained by the higher percentage of females who met or exceeded the at-risk threshold of 4 or more affirmative responses. 48 of 229 females [21%] met or exceeded the at-risk threshold of 4 or more “Yes” responses, while 29 of 178 males [16%] met or exceeded the threshold.
A summary of response by Gender, by Question, is shown in the table below:
The most frequent affirmative responses are Q1 [verbal intimidation], Q4 [lack of loving affiliation], and Q9 [family history of mental health, depression, or suicide]. The frequency of affirmative responses by females is greater among these three questions than males, and especially within Q4 by a two-to-one ratio.
Grade Analysis
There was more participation from 9th and 11th grade students, 32% and 35% respectively. There does not appear to be any trending from one class to the next, although results differ by class. [For future study, the high school could correlate disciplinary incidents by grade with that class’s relative skewness.] A summary of response by Class, by Question is shown in the table below:
A summary of percent at-risk students by class is shown in the table below.
There is no discernable trending of at-risk percentage by class; however, it is very revealing to note that the highest percentage of at-risk students came from the two classes with the least voluntary participation in the ACE Test. Recall that this was a voluntary station at a high school’s Mental Health Fair. Would a student with many Adverse Childhood Experiences be more likely to volunteer to participate in this kind of test? Their participation could be tantamount to a cry for help. On the other hand, a student might avoid this kind of test either to avoid detection or to not have to re-live painful memories. This issue suggests that there should be discussion about making participation mandatory. Which leads to the conclusion that the ACE Test should not be administered by students, but rather an appropriate high school professional, such as the School Nurse.
Mediation Effect Test
Based on initial analysis, we observed that female students have a higher mean of ACE Score compared to male students. The graph on the right indicates the spread of ACE SCORES for male and female students across the different grades. The size of bubble indicates the # of responses. This analysis confirms our earlier analysis i.e., a female student is more likely to have an affirmative response compared to the male counterpart. However, it also shows that the male students are highly concentrated towards the higher ACE scores.
Based on the spread, we wanted to answer the question – “Does Grade have an indirect effect on the ACE Scores? Is gender a good enough predictor for ACE Scores?
In order to test above thesis, we consider three variables –
- Predictor Variable (X) – Gender
- Mediator Variable(M) – Grades
- Outcome Variable(Y) – ACE Score
We also assume Male =’1’ and Female = ‘0’ for this analysis.
Scenario 1 (X ->Y): Controlling for Grades, we observe that Gender negatively impacts ACE Score (path = -0.41). We can conclude that between a female and a male student from same grade, the female student is more likely to have a higher ACE score. This is keeping in mind the assumption that Males are labeled as ‘1’ and Female are considered ‘0’ for this analysis.
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.9083 0.1517 12.582 M): Gender has a positive effect on Grades (path = 0.03)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.33216 1.14299 1.165 0.245
Grade 0.03852 0.11087 0.347 0.728
Scenario 3(X+M->Y): Factoring in both Grades and Gender, the overall effect is still negative on ACE Score. The value changes from -0.4139 to -0.41225. Since the effect is minor, it shows that the indirect impact of Grade is minimal in this model.
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.56064 1.14696 1.361 0.1744
Mgen -0.41225 0.22967 -1.795 0.0734 .
Grade 0.03382 0.11060 0.306 0.7599
Therefore, we can conclude that no mediation has occurred. Also, it is not necessary to run further tests such as Sobel test.
Question by Question Correlation Analysis
Mental health services in the U.S. are insufficient and limited options and waiting lines are usual norms. (Source: National Council for Behavioral Health). Additionally, Mental Health America (MHA) research says that over 70% of the youth with major depression are still in needed of the treatment. This clearly calls for a need to match effective, accessible and engaging student mental care with available resources. Finding the likelihood of how one affirmative response may be influenced by other, we can focus on core reasons that might be leading to depression and anxiety, and other mental health problems among the students.
This analysis aims to answer a simple question: What is the likelihood that an affirmative response to one question leads to an affirmative response to another? In order to understand the effect of one question response on another, we ran a simple correlation test to understand questions that showed significant correlation.
From the figures below, one can observe significant correlation between the following questions-
· Q1 and Q2 (0.53), Q1 and Q4 (0.52), and Q2 and Q7 (0.56)
There was also significant correlation observed between the following question responses
· Q8 and Q10 (0.46)
Based on the questions whose responses saw a significant correlation, our interpretation could be vetted out with a chi-squared analysis of response by question. For Chi-Square tests, we set the hypothesis as following:
H0 (Null Hypothesis): The responses to questions are independent
H1 (Alternative Hypothesis): The responses to questions are dependent one each other
Test #1: Q1 and Q2 data: ace_data$Q1 and ace_data$Q2
X-squared = 109.81, df = 1, p-value < 2.2e-16
Since the chi-square value is 109.81 and p-value is less than the significance level of 0.05, we reject the null hypothesis and can conclude that the variables are in fact dependent.
We can conclude that before 18th birthday if a student was insulted or humiliated by their parents, there is a high probability that the same student is also subjected to physical harm by parents.
Test #2: data: ace_data$Q4 and ace_data$Q1
X-squared = 106.95, df = 1, p-value < 2.2e-16
Since the chi-square value is 106.95 and p-value is less than the significance level of 0.05, we reject the null hypothesis and can conclude that the variables are in fact dependent.
We can conclude that if a student felt a lack of love and support for themselves and within their family, there is a high probability that such environment led to the student feeling humiliated or insulted and subsequently afraid that they might get physically hurt.
Test #3: data: ace_data$Q2 and ace_data$Q7
X-squared = 121.51, df = 1, p-value < 2.2e-16
Since the chi-square value is 121.51 and p-value is less than the significance level of 0.05, we reject the null hypothesis and can conclude that the variables are in fact dependent.
We can conclude that is a student has faced any sort of physical harm or abuse at home, there is a very high probability that their mother or stepmother were a victim of domestic violence as well.
Test #4: data: ace_data$Q8 and ace_data$Q10
X-squared = 82.486, df = 1, p-value < 2.2e-16
Since the chi-square value is 82.486 and p-value is less than the significance level of 0.05, we reject the null hypothesis and can conclude that the variables are in fact dependent.
We can conclude that is a student has lived with anyone who has a drinking problem, or has used street drugs, there is fair probability that some member of the household has been to prison.
From the chi-square tests, it is easy to conclude that there are a few common themes that are contributing to the ACE scores irrespective of the grade or gender. In order to
The outcome of this analysis might reveal various demographics among high-scoring ACE Test respondents.
Conclusions and Direction
Trends in society suggest that in order to help students be successful, the education system must reach beyond academics in order to manage and care for all aspects of development. Currently, there are plenty of tools available to measure a student’s academic progress; however, in order to measure the more wholistic well-being of students, schools must also develop tests to measure mental health and wellness. The Adverse Childhood Experiences Test could be one such measurement device. Based on ACE test results, there is a clear need for student mental health services to be more proactive, expeditious, and preventive in nature. In terms of determining risk factors, the services should target sub-groups that have students who lack support or love from parents or have families with a record of domestic violence. The teachers and school can be proactive in noticing any trends that indicate such behavior through interaction with parents and students. Another key thing that we noticed was depression trajectory among male and female students. We can conclude that pre-adolescence, the ACE Scores were observed to be higher in male students. However, post-adolescence it seemed that higher ACE Scores were observed more within the female students when compared to male students from similar age groups or grade (Grade range from 11 to 12).
The transition of students from childhood to adolescence to university represents a critical opportunity for testing tools such as ACE, researchers, clinicians, and schools to effectively screen students suffering from mental illness. We are confident that our research outcomes can help achieve a more evidence-based model for effective screening of mental health cases.
References
- About the CDC-Kaiser ACE Study. (2019, April 2). In Center for Disease Control and Prevention. Retrieved September 25, 2019, from https://www.cdc.gov/violenceprevention/childabuseandneglect/acestudy/about.html
- Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., … & Marks, J. S. (2019). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American journal of preventive medicine, 56(6), 774-786.
- Storrs, Carina (2009). Is Life Expectancy Reduced by a Traumatic Childhood? Scientific American. Retrieved October 11, 2019, from https://www.scientificamerican.com/article/childhood-adverse-event-life-expectancy-abuse-mortality/
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