ISSN: 1522-4821

International Journal of Emergency Mental Health and Human Resilience
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  • Research Article   
  • Int J Emer Ment Health, Vol 26(2)
  • DOI: 10.4172/1522-4821.1000625

Influence of students’ mental health on unrest in secondary schools in Kisii County, Kenya.

Dr. Eric Kabuka*
Department of Educational Psychology, Moi University, Kenya
*Corresponding Author: Dr. Eric Kabuka, Department of Educational Psychology, Moi University, Kenya, Email: erickiago@yahoo.co.in

Received: 26-Feb-2024 / Manuscript No. ijemhhr-24-124546 / Editor assigned: 29-Feb-2024 / PreQC No. ijemhhr-24-124546 / Reviewed: 12-Mar-2024 / QC No. ijemhhr-24-124546 / Revised: 16-Mar-2024 / Manuscript No. ijemhhr-24-124546 / Accepted Date: 26-Feb-2024 / Published Date: 23-Mar-2024 DOI: 10.4172/1522-4821.1000625 QI No. / ijemhhr-24-124546

Abstract

Mental health issues are becoming increasingly common among students worldwide. Kenya has not been spared. Studies have shown that approximately 20% of school students are affected by diagnosable mental illnesses, with half of all mental issues developing by 14 years. It is further indicated that mental health problems are the leading cause of behavioral adjustment among adolescents in schools. A survey carried out in Kisii County in 2017 showed that 23% of the students had symptoms of depression. Studies have shown that depression is associated with violence among high school students. Despite this, little has been done to establish the influence of depression as a mental health issue on unrest. The purpose of this study was to examine the influence of depression on unrest. The study was based on Strain theory by Robert Merton (1938). Descriptive and correlational research designs were adopted. Target population was 30,955 form two students. Yamane's formula was employed to determine the sample size of 395 students. A questionnaire was used to collect data.  A pilot study was carried out among 40 students using test- retest method of reliability. Reliability coefficient index of the instrument was determined at.83 while validity of the instrument was ascertained by experts. Quantitative data was analyzed using descriptive and inferential statistics. Findings indicated that students in 101 schools (96.2%) had moderate cognitive aspect of depression which was significant at r=-.34, p=.00. Mood and motivation aspects of depression had a non-significant positive correlation with unrest (r=0.04,r=0.08).It was concluded that most schools had students with moderate cognitive aspect of depression. The study recommends that schools should raise awareness on mental health issues among students. This finding is useful to the school administrators and the Ministry of Education in shedding light on the importance of addressing students’ mental health.

Keywords: Depression, Mental Health, Unrest

Keywords

Depression, Mental Health, Unrest.

Introduction

Student unrest is a worldwide phenomenon that has devastated many countries. It is defined as any sort of disruptive behavior, class boycott, disturbance, wanton destruction, or extreme danger performed by students as well-defined student unrest as student demonstrations that end in the destruction of lives and property as a result of protesting their demands. According to UNICEF, half of the students aged 13 to 15 (around 150 million) worldwide have experienced classroom violence (Abela JRZ,2016) . Based on data from the US National Center for Education Statistics  it was found that approximately 77% of public schools reported at least one occurrence of criminal activity during the 2019-20 academic year, resulting in a cumulative total of 1.4 million incidents. This corresponds to a prevalence of 29 occurrences per 1,000 students enrolled during the academic year of 2019-20. Based on the findings of the Youth Risk Behavior Survey (YRBS) conducted by the Center for Disease Control and Prevention (CDC), it was determined that 24% of students in the United States of America (USA) had engaged in multiple physical altercations within one year (Abobo F,2014).

According to South Africa exhibits the highest incidence of student unrest. In the year 2017, an outbreak of violence and social disorder occurred at Klipspruit West Secondary School in Johannesburg, South Africa (Adeyemi TO,2019). This was as a result of the community's refusal to accept the appointment of a new school principal, leading to a state of governability within the school. Community members took on the responsibility of assuming professional management of the school, making decisions regarding the appointment of the principal, procurement of books, and selection of service providers (Blakemore SJ,2018). While the parents, teachers, and school administration were addressing the aforementioned disruption, the students engaged in loitering, gambling, and drug use within the school premises. Consequently, this environment fostered the emergence of gangsterism, witnessed racist incidents, experienced chronic tardiness and early departures among students, and subjected teachers to verbal insults and physical assaults (Frojd SA, 2018).

Secondary schools in Kenya have experienced a significant amount of unrest. According to  the initial occurrence of school violence was documented in 1908 at Maseno School. The Republic of Kenya has experienced a surge in incidents of violence within the premises of public secondary educational institutions. According to  incidents of school violence during the period spanning from the 1990s to the 2000s led to the unfortunate loss of student lives, the deliberate destruction of educational institutions through arson, and extensive damage to school infrastructure. Consequently, the Ministry of Education has enacted several measures aimed at mitigating instances of school violence. Kenya has implemented various programs since 2008 to promote peaceful coexistence, recognizing the pivotal role of education as a foundation for this objective. In that year, the teaching of Life Skills Education (LSE) was made compulsory in public secondary schools in Kenya as a means to address conflict. Despite the various interventions, and mitigation measures taken to solve this problem, school violence persists (Grahek I, 2019).

Students in secondary schools are in the adolescence period. Adolescence has been defined as a time of great emotional turmoil and transition. A journey from childhood to adulthood that entails significant physical, psychological, cognitive, and social changes that can be traumatic for adolescents.  This period is stressful and is typically a period at risk of the onset of several mental distress including depression. The WHO estimates that globally 10%–20% of children and adolescents are affected by mental health problems. The term depression refers to a wide range of emotional lows, ranging from sadness, mood disorder, poor dietary habits, violent behavior, drugs and substance abuse, diminished interest or pleasure, feelings of guilt or diminished self-esteem, fatigue, pessimistic thoughts about the future, contemplation of death or suicide, disturbances in sleep patterns, impaired concentration among students and alcohol consumption among students. A sad person should be able to recover to their normal emotional stability in a reasonable amount of time. In cases where the said individual remains in such a state for prolonged periods, a diagnosis of depression should be made. The World Health Organization (WHO) has identified depressive disorders as the fourth most prevalent health issue globally and the second leading cause of disability among humans in the year 2020 (Hecht D,2013).

Research has shown an association between the intensity of depressive symptoms and behavioral issues such as aggression among students in schools.  According to statistical data, a significant proportion of adolescents in the United States, specifically seven out of ten individuals aged between 13 and 17 years, experience symptoms of depression. These students reported experiencing emotions such as anger, sadness, fear, or stress during their time in school. Further, these students attributed their restlessness and agitation to these emotions. In another study conducted by among high school students in Jordan, results indicated that depression among adolescents was associated with disruptive behaviors, aggression, and violence in school (Iverson GL, 2022).

Depression can be classified into different dimensions, cognitive, mood and motivation. Cognitive depression refers to the inclination to perceive and interpret various occurrences in life through a pessimistic lens. It is widely believed that this factor plays a significant role in the development of depression . Mood aspect refers to the emotional and psychological state characterized by persistent and profound feelings of sadness, hopelessness, and a lack of interest or pleasure in previously enjoyed activities . While  the motivation aspect refers to the profound and persistent lack of motivation, energy, and drive that is commonly associated with depressive disorders.

In a study conducted by Iverson and Iverson  in the US, on the phenomenon of perceived cognitive impairment among high school students, results indicated that the participants (38%) had significant challenges in their ability to concentrate, remember information, and make decisions, which were attributed to various physical, mental, or emotional issues. The study further indicated that these students who had cognitive impairment issues reported being frustrated with school life in general and lost motivation to learn and this led them to cause disruptions in school by boycotting classes. In contrast, students who engaged in regular exercises exhibited a significantly reduced likelihood of encountering cognitive impairment. The study's findings also indicated that there was a correlation between perceived cognitive impairment in students and various factors such as experiencing feelings of unsafely or threat within the school environment, achieving significantly low grades, experiencing inadequate sleep, and engaging in illicit drug use. These factors and grounds for restlessness and agitations among students in school (Okello J, 2017).

According to a study conducted by cognitive vulnerability is a risk factor for depression in both Canadian and Chinese adolescents, and individuals will express their cognitive vulnerability according to their cultures/ environments. In their study, which involved 372 Canadian adolescents and 335 Chinese adolescents, the authors found that cognitive vulnerability was significantly associated with depressive symptoms in both Canadian and Chinese adolescents. For example, among Canadian adolescents, a negative outlook on themselves was the strongest predictor of depressive symptoms, while among Chinese adolescents, hopelessness was the strongest predictor. These depressive symptoms were associated with frustrations among students which led to aggressive behaviors in schools.

Based on the statistics from the Center for Disease Control  high levels of depression a mental health issue encouraged adolescents/ young people in the United States to act out in violent ways. Students resorted to violent assaults, stabbing, and shooting others because they felt isolated and they did not fit in or were not accepted by their peers in the school. The study further stated that depressed individuals were openly hostile and had anger attacks . In a sample of Finnish students aged 13–17, agitation and aggression in school were associated with self-reported depression concentration difficulties, poorer social relationships, self-learning, poorer academic performance, and worse reading and writing outcomes . Therefore, it is not surprising that young people with depression are likely to cause chaos in schools, as shown in a 15-year longitudinal study of Swedish adolescents (Scherf KS, 2017).

The findings of a study done in Homabay County- Kenya by among 783 adolescents who were also assessed for symptoms of depression and anxiety by use of the Beck Depression Inventory (BDI-II) and Beck Anxiety Inventory (BAI), it was revealed that 57.5% of the adolescents had depression. Results from the study indicated that there was an association between depression and aggression/ violence in schools. These percentages are high and if these students are not assisted and helped, they will carry their depressive symptoms into their adult lives, and thus their functions as human beings will not be optimal.

Based on the aforementioned studies it is clear that depression can contribute to various forms of unrest, such as aggression, violation of school rules, truancy, or social withdrawal. Students who experience depression may have difficulty managing their emotions, resulting in outbursts of anger or frustration that can lead to disruptive behavior. Depression can also affect students' motivation, engagement, and academic performance, which may contribute to a sense of frustration and agitation. Students with depression struggle to focus on their studies, complete assignments, or interact positively with peers and teachers, which can further exacerbate feelings of distress and discontent.

In Kenya, effects of mental health issues such as depression among students is a topic that has not been largely explored and only a few applicable studies have been done. Prior studies have centered on mental health issues among adolescents in marginalized people like People living with Disabilities (PLWD)  and persons living with human immune deficiency virus (HIV) infection. Additionally, studies on mental health concerns among students in secondary schools have mostly looked at the effects of alcohol and substance use on academic achievement. Majority of the studies have documented an association between adolescent mental issues such as depression and violence have been done in different regions globally. Little research attention however has been given to the influence of depression as a mental health issue on unrest yet mental health and well-being of students is very crucial. When students are not mentally stable and are psychologically disturbed they speak up by projecting their emotions through violence and riots in school and this is a cry for help. Students from Kisii County secondary schools suffer from depressive symptoms as indicated by a survey done by yet not much research has been done to determine its influence on unrest in schools. It is on this ground that the researchers sought to establish the influence of depression as a mental health issue on unrest in secondary schools in Kisii County, Kenya. 

Research Methodology

The study was anchored on the Strain theory this theory postulates that individuals engage in deviant behavior when they experience strain or stress due to a gap between societal goals and available means for achieving those goals. If an individual is unable to reach the culturally dominant aim (of success), it can be frustrating and lead to the individual breaking away into illegal escape routes or delinquency. Population of the study included 30,955 form two students in Public Secondary Schools in Kisii County, Kenya. Form two students were favored since it was presumed that they are in a transition year in the education system, marked by changes in curriculum, increased academic pressure and shifts in social dynamics. These changes can trigger instability such as irritation which may cause unrest. Stratified random sampling technique was used.

According to Hayes (2023), stratified random sampling technique involves a process of stratification followed by random selection of subjects from each stratum. In the study, schools were stratified into purely boys boarding schools, girls boarding schools and mixed boarding and mixed day schools. From the 350 secondary schools, 105 schools representing 30% schools in Kisii County were proportionately selected for the study as follows: 24 boys boarding schools, 24 girls boarding schools, 23 mixed boarding and 34 mixed day schools thus having a ratio of 24:24:23:34. Yamane's formula was used to sample 395 form two students. The ratio for students in each category were: 90:90:87:128 respectively. This was arrived at by using Hayes stratified sampling formula for sample size. Simple random sampling technique was also used to select students to participate in the study. This was done by placing cards bearing the words ‘YES’ and ‘NO’ in a container and shuffling was done. Students who picked cards written “yes” were selected. This ensured that each student had an equal chance of being selected. Piloting involved 40 students using test-retest method of reliability and its reliability coefficient index was determined at .78. Face and content validity of the data collection instruments were ascertained by experts. Data was collected using a questionnaire and were analyzed using descriptive statistics in the form of frequencies and percentages and inferential statistics such as spearman’s rho and ordinal regression.

Analysis of correlation studies of the study was based on Amendore (2021) yardstick as follows:

➢ 8- very strong positive correlation

➢ 8-0.6- strong positive correlation

➢ 6- 0.4- moderate positive correlation

➢ 4-0.2- weak positive correlation

➢ 2- 0.0- very weak positive correlation

➢ No correlation

➢ - 0.2- very weak negative correlation

➢ -0.2- -0.4- weak negative correlations

➢ -0.4- -0.6- moderate negative correlation

➢ -0.6- -0.8- strong negative correlation

➢ -0.8- -1.0- very strong negative correlation

Results and Discussion

The researchers set out to establish the influence of depression as a mental health variable on unrest in secondary schools in Kisii County, Kenya. Depression as a mental health variable was further subdivided into three variables; cognitive aspect, mood aspect and motivation aspect. To measure the cognitive aspect, mood aspect and motivation aspect of depression, a questionnaire in the form of Likert type scale was administered to 395 form 2 students, who were expected to give a response based on their level of agreement or disagreement with the statement i.e., strongly agree, agree, disagree and strongly disagree. When a student gave the answer as Strongly agree he/she was awarded 4 points, Agree-3 points, Disagree- 2 points and strongly disagree- 1 point. The means scores for each sub-scale of depression are presented in (Table 1).

Descriptive Statistics
  COGNITIVE MOOD MOTIVATION
N - Valid 105 105 105
Missing 0 0 0
Mean 25.92 28.14 26.29
Median 26.00 28.00 25.00
Std. Deviation 2.344 0.777 3.458
Minimum 22 27 22
Maximum 33 30 34

Table 1. Descriptive Statistics for depression aspects (cognitive, mood and motivation).

The remaining 4 schools (3.8%) had students with mild cognitive aspect of depression. This finding suggests that most of the schools had students with moderate cognitive aspect of depression. Results from the mood aspect of depression indicated that students in all schools experienced moderate type of depression (105) (100%) while results from the motivation aspect of depression indicated that students in 97 schools (92.3%) in Kisii County had moderate type of motivation depression while students in 8 (7.6%) schools had severe motivation depression. The current study finding therefore concluded that most students in Kisii County secondary schools had moderate type of depression (Table 2).

  COGNITIVE MOOD MOTIVATON
  f % f % f %
Moderate 101 96.2 105 100 97 92.3
Mild 4 3.2 0 0 0 0
Severe 0 0 0 0 8 7.6
Total 105 100 105 100 105 100

Table 2. Descriptive Statistics for student`s depression in schools.

The dependent variable in the study was unrest which had 5 ordered levels (5- Severe, 4- Major, 3- Moderate, 2- Mild, 1- Minor). 5 being the highest level of unrest and 1 being the lowest level of unrest. The researcher took the highest level of unrest ticked by the respondents. The distinguishing characteristic of each level was as follows.

➢ Students rioting/burning of dormitories and classrooms/breaking of windows and attacking teachers

➢ students shouting at teachers/ howling, booing

➢ students boycotting classes/ school assembly

➢ students fighting each other

➢ students refusing to take food/ students going slow

Researchers also did a correlation between depression aspects (cognitive, mood and depression) and unrest using Spearman's rho as shown in (Table 3).

Correlations
Cognitive Mood Motivation Unrest
Spearman's rho    Cognitive Correlation Coefficient 1.000 -012 -004 -.336**
Sig. (2-tailed)   .900 .967 .000
N 105 105 105 105
Mood Correlation Coefficient -012 1.000 0.57 0.04
  Sig. (2-tailed) .900   .562 .687
  N 105 105 105 105
Motivation Correlation Coefficient -004 0.57 1.000 0.75
  Sig. (2-tailed) .967 .562   .448
  N 105 105 105 105
Unrest Correlation Coefficient -.336** .040 .075 1.000
  Sig. (2-tailed) 000 .687 .448 .
  N 105 105 105 105

Table 3. Spearman`s rho correlation matrix for depression aspects and unrest.

Based on the correlation matrix, cognitive aspect of depression had a statistically significant negative correlation with unrest (-.34). The negative correlation coefficient suggested a negative relationship with a statistical significance of 0.00 at 0.05 level. In other words, when cognitive distortions thinking negatively, feeling hopeless and sadness increase, there is a tendency for unrest levels to decrease. The mood and motivation aspects of depression were not statistically significant (04; .08) respectively at 0.05 level.

As indicated  yardstick was further used to interpret the strength and direction of the correlation between the independent and dependent variables. Based on this, the correlation matrix in Table 3 shows that the cognitive aspect of depression had a moderate negative correlation with unrest.

Yardstick for interpretation, the mood aspect of depression according to the correlation matrix showed a weak positive correlation (0.04). The motivation aspect of depression as well showed a weak positive correlation (0.08).

Researchers further employed ordinal regression to establish the influence of depression on unrest. Results in the summary of unrest in secondary schools in Kisii County and shows the inferential statistics for cognitive aspect of depression (Table 4-7).

Case Processing Summary
    N Marginal Percentage
Unrest Minor 17 16.2
  Mild 28 26.7
  Moderate 32 30.5
  Major 20 19.0
  Severe 8 7.6
Valid   105 100.0
Missing   0  
Total   105  

Table 4. Case summary of unrest in schools.

Model Fitting Information
Model -2 Log Likelihood Chi-Square df Sig.
Intercept Only 106.110      
Final 102.018 4.091 1 0.43
Link function: Logit

Table 5. Model fitting for cognitive aspect of depression.

Goodness-of-Fit
  Chi-Square df Sig.
Pearson 37.736 43 0.698
Deviance 40.896 43 0.563
Link function: Logit

Table 6. Goodness -of-fit for cognitive aspect of depression.

Parameter Estimates
    Estimate Std. Error Wald df Sig 95% Interval Confidence
      Lower Bound Upper Bound
Threshold [Unrest = 1] 0.125 3.599 0.001 1 972 -6.929 7.179
  [Unrest = 2] 1.485 3.600 170 1 680 -5.571 8.541
  [Unrest = 3] 2.787 3.608 597 1 440 -4.284 9.858
  [Unrest = 4] 4.271 3.624 1.389 1 239 2.831 11.373
Location COGNITIVE 3.057 116 242 1 047 0.171 0.285
Link function: Logit

Table 7. Parameter estimates for cognitive aspect of depression.

Based on the parameter estimates from the logistic regression model, it was clear that there was an influence of cognitive depression on students’ unrest (b= 3.057; p=.047). This meant that the cognitive aspect of depression had a positive association on the outcome variable unrest. This implied that higher cognitive distortions thinking negatively, feeling hopeless and sadness) are associated with a higher probability of unrest.

The results obtained from the study on cognitive depression align with the outcomes reported in a study conducted by pertaining to the perceived cognitive impairment experienced by high school students in the United States. According to the findings of the study, a significant proportion of students, specifically 38%, indicated experiencing substantial challenges in terms of concentration, memory, and decision-making abilities which are indicative of cognitive depression. These challenges were a source of frustration which caused agitation and aggressive behavior among the students.  The findings of the present study as well align with those of as both indicate that students experiencing cognitive depression exhibit difficulties in concentration during class, feelings of hopelessness regarding the future, disrupted sleep patterns, and changes in appetite symptoms of cognitive depression led to discontent and disruptive behaviors among learners.

Furthermore, the present findings agree with the findings of a study conducted by regarding the association between cognitive vulnerability and depression risk in a sample comprising 372 Canadian and 335 Chinese adolescents. The findings revealed that Canadian adolescents exhibited a pessimistic perception of self, whereas Chinese adolescents manifested symptoms of hopelessness, which is indicative of cognitive depression. These feelings of hopelessness and pessimism resulted in students being demotivated and frustrated and thus becoming agitated with the school program. The results of this study also are consistent with the findings of a study conducted in Rajkot City, India, which employed binary logistic regression analysis . The findings revealed that a total of 31.99% of the student population exhibited symptoms of depression. The study identified several factors that have predictive value for depression, including insufficient nutrition, academic stressors, and pessimistic cognitions which led to disruptive behaviors and violence in school.

Based on WHO findings and the current study`s findings, it is clear that students in high schools, experience depression, with the cognitive aspect having a higher influence of the students behaviors. Poor concentration in class, feelings of hopelessness, thinking negatively about themselves and having irrational faulty thoughts have made the students to be frustrated and thus project their emotions by causing chaos and violence in school.

Studying cognitive depression among high school students is of significance because the onset of most of the lifetime mental disorders occurs during this period. From the findings of this study, it is evident that students in Kisii County Secondary Schools suffer from cognitive depression which is a mental health issue. They experience feelings of hopelessness, reduced interests in their daily routine/social relations, worthlessness, negative self-evaluation and self-criticism, lack of concentration, reduced appetite, weight loss, insomnia or increased sleep, and low motivation. When students feel their mental health concerns are not acknowledged or addressed adequately, they might express their discontent through protests, chaos or other forms of unrest.

It is therefore imperative that the mental health of students especially their cognitive aspects be checked and regularly assessed so as to curb issues of depression among students in high school.

Conclusion

Based on the study’s findings, it can be concluded that the cognitive aspect of depression had a negative correlation with unrest which was statistically significant, mood and motivation aspects had a positive non significant correlation with unrest. The study therefore recommends that schools should raise awareness on students mental health issues while putting emphasis on their cognitive aspects.

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