Effects of Gambling on Academic Performance among University Students in Nairobi County, Kenya

Effects of Gambling on Academic Performance among University Students in Nairobi County, Kenya

Michael Otieno, Prof. Anne Sande and Dr. Christopher Kiboro

Department of Social Sciences, Chuka university, P. O. Box 109 – 60400, Chuka, Kenya

DOI: https://dx.doi.org/10.47772/IJRISS.2024.8110063

Received: 10 October 2024; Accepted: 15 October 2024; Published: 03 December 2024

ABSTRACT

Gambling has become increasingly popular especially among the youth because of its potential economic benefits. However, there seems to be a general feeling by the society that gambling has negative effects on the social, mental, economic and the general well-being of youths. Although studies conducted on gambling among various categories of youth reflect higher frequencies among the university students, there is limited information on whether it has relationship with academic performance. Thus, the purpose of the study was to determine the influence of gambling on academic performance among university students in Kenya. Descriptive research design was used. Study objective was to determine the effects of gambling on academic performance among university students in Nairobi County, Kenya. Study population was 81,056 people. Target population were university students and university students’ counselors. A sample size of 384 respondents was used based on the table for sampling by Krejcie and Morgan, (1970). Data was collected using the questionnaires and interviews. The data collected were analyzed using both quantitative (descriptive and inferential) and qualitative statistics. Gambling negatively affected academic performance among university students (p=0.024, p<0.005). The study recommended incorporation of gambling effects into university curriculum just as the other addictive behaviors among young people. Findings are useful in informing policy formulation geared towards curbing gambling problem among youth.

Key words; Academic Performance, Gambling and University Students

BACKGROUND INFORMATION

The popularity of gambling among the youth is on the rise due to its assumed and potential benefits. Gambling is defined as placing something valuable at risk or placing a gamble on the result of a wager whose outcome is subject to random chances (Korn & Shaeffer, 1999). Gambling has been established to having behavioral addiction, which has been shown to have detrimental implications on the gambler’s social relationships, mental wellness, as well their physical health and general lifestyle (Chimezie, 2015). Good academic performance has been considered a gateway from poverty for an extended period. Many people argue that it is through academics that the gap between the rich and the poor can be reduced or even closed; therefore, excelling in academics has acquired high premium in society.

During adolescence, there is a connection between gambling behavior and poor academic scores (Ladouceur et al., 1999). However, it is unclear what causes this link, according to Frank Vitaro, Mara Brendgen, Alain Girard, Ginette Dionne, & Michel Boivin (2018). Poor academic performance is correlated with gambling activity, which becomes more robust from early to late adolescence (Bergevin et al., 2006; Ladouceur et al., 1999). It is possible that gambling affects academic performance (Frank et al., 2018). As an alternative, (Frank et al., 2018) contend that shared risk characteristics, including impulsivity and socio-family distress, may aid in understanding the association between gambling engagement and poor academic achievement. It might also be described by other recent problematic behaviors that are connected, like juvenile substance abuse.

Moreover, any financial issues that come with it can interfere with schoolwork. The “Causal model” suggests that engaging in gambling could lead to poor academic performance. For instance, time wasted on gambling after school is time that could have been spent on schoolwork (Frank et al., 2018). Additionally, gambling makes it difficult to attend classes during school hours because many gamblers have been observed skipping class (Ladouceur et al., 1999). Finally, gambling activities may expose teenagers to unsociable peer groups, resulting in an undesirable outcome for academic accomplishment and school involvement, either directly or through increasing social and behavioral issues.

The ‘Common Antecedents model,’ in contrast to the ‘Causal model,’ indicates that the cross-sectional and longitudinal correlations between gambling engagement and low academic achievement may result from shared vulnerability traits, such as impulsivity and socio-family disadvantage (Frank et al., 2018). Several studies highlight the importance of impulsivity as a predictor of early gambling engagement and the later onset of gambling disorders in adolescents (Barnes et al., 1999; Pagani et al., 2009; Vitaro et al., 1999). Low academic performance and early school dropout have both been associated with impulsivity (Vitaro et al., 2005). This suggests that impulsivity may influence the correlation between frequent gambling and poor academic achievement. The association between gambling and academic success may be partially explained by socio-family risk. The term “socio-family risk” encompasses a diverse range of issues, including but not restricted to financial hardship, family instability, a lack of formal education for parents, and having children at a young age. These family and social conditions have been linked to increased rates of teen gambling and poor academic achievement, mainly when they occur together (Fisher, 1993; Shaw & Emery, 1988).

The ‘Correlated Behavior Problems model’ suggests that confounding factors like substance abuse may mask the association between gambling and academic success. Longitudinally and simultaneously, substance abuse has been linked extensively to problem gambling and poor educational outcomes (Bradley & Greene, 2013; King et al., 2006). As proposed by (Frank et al., 2018), the three models, as mentioned earlier, are not necessarily incompatible. For example, it is plausible that once established, gambling and poor academic performance in the early teenage years continue to impact each other throughout the rest of adolescence, even if similar antecedent circumstances describe the relationship between the two activities (Frank et al., 2018).

After-school gambling takes time away from studying or other academic pursuits. In addition, many students who gamble have been observed to be absent from the classroom (Ladouceur et al., 1999). Adolescent gamblers may become involved with antisocial peer groups, hurting their motivation to learn and academic achievement. Last but not least, researchers discovered a reversible, longitudinal correlation between frequent gambling and substance abuse. These results are not the focus of the current investigation, but they should be noted because they are consistent with prior research (Wanner et al., 2009) and point to potential indirect routes between gambling and academic performance through increased substance use.

According to the Common Antecedent model, impulsivity and socio-family risk explain the parallel relationships between gambling behavior and academic achievement. These conclusions are consistent with prior research showing that, in addition to various other behavioral symptoms and socio-family characteristics, teacher-rated and self-reported impulsivity in childhood predicts engagement in gambling in adolescence (e.g., Barnes et al. 1999; Vitaro et al., 1999). The findings by Frank et al. (2018) also support the pervasiveness of socio-familial risk, which has previously been linked to both high levels of teenage gambling engagement and poor academic performance (Fisher, 1993). Decreasing these risk variables through prevention should lead to a decline in substance use and betting and an enhancement in academic achievement. However, once developed, the relationship between gambling and academic achievement becomes only loosely reliant on the antecedent variables, with the result that one conduct (gambling) affects the other (academic performance) (Frank et al., 2018).

In Kenya 54% of the youths aged between 17-35years have been established to be actively engaged in gambling GeoPoll survey (2019). The gambling industry is valued at Ksh. 200 billion according to Pricewaterhousecoopers (PwC 2021). FinAccess (2021), Established that Kenya leads in mobile betting in sub-Saharan Africa with over 80% of Kenyan gamblers using mobile phones. African Journal of Addiction Studies (2022), estimated that between 10-15% of gamblers in Nairobi exhibited signs of compulsive gambling impacting their social life, academic and financial life.

Statement of the Problem

Gambling has become increasingly popular because of its assumed or potential economic benefits. Studies have established that, gambling activities and gambling firms have contributed to increase in revenue for countries and increased employment opportunities for individuals in various countries. However, gambling has been associated with severe social and health problems. The youth has been identified as a risk group in gambling. Results from previous studies show that over 76% of youth in Kenya had at one point been involved in gambling. Empirical evidence also indicates increased gambling among university students. However, there is very limited data and evidence showing how gambling especially among university students affects their performance in academics. This research aimed to address this void by producing tangible empirical evidence that can be used to formulate policies and inform legislation for regulating gambling in the country.

Objectives of the study

To establish the effects of gambling on academic performance among university students in Nairobi county Kenya.

Research hypothesis

H₀1: There is no statistical relationship between gambling and academic performance among university students in Nairobi County Kenya.

METHODOLOGY

The study adopted descriptive research design. The study population was 81,056 people. The target population were university students and university students’ counselors. A sample size of 384 respondents was used based on the table for sampling by Krejcie and Morgan, (1970). Multi-cluster sampling method was used to sample the respondents. Data was collected using the questionnaires and interviews. The data collected were analyzed using both quantitative (descriptive and inferential) and qualitative statistics.

Table 1: Sample Size of Nairobi County Universities Selected.

Source: Various Universities database 2022.

FINDINGS AND DISCUSSIONS

Results on the analysis of data from the questionnaires as well as the summary of the information found in the frequency tables and graphs have been comprehensively discussed in order to visualize the subject under study.

Demographic information of the respondents

Demographic data of the respondents was collected and analyzed. This information is vital in understanding the background information of the study population. This is because these characteristics of the respondent are most likely to affect or influence the behavior of the study respondents hence it’s important to understand them. Results of the demographic information on; gender, age, education level, and marital status of the respondents is summarized and presented using frequency distribution tables and bar charts.

Gender of the Respondents

Table 2: Gender of the Respondents

Source: The Researcher 2023

The findings in Table 3 present the gender distribution of the study respondents. It was revealed that the female respondents were 96(31.6%) and the males 208(68.4%) this distribution is considered adequate and balanced and thus a fair distribution and a reflection of study findings on both gender.

Age of the Respondents

The study sought to understand the age brackets of the study respondents. The age brackets of the respondents were categorized into three groups. Results were presented in Figure 1.

Figure 1: Age Group of the Respondents.

Source: The Researcher 2023

Based on the results it was visible that majority (43.8%) of the respondents were in the age category of 18-25 years. 31.6% of the respondents were in the age bracket of 26-30 years and 24.7% were between age brackets of 31-35 years. This distribution was considered adequate since most of the university students age falls between the age brackets of 18-25 years.

Education Level of the Respondents

The study investigated the levels of education of the respondents. Two levels of education were considered; undergraduate and post graduate levels. The results were presented in Table 4.

Table 3: Frequency Distribution of Education Level

Source: The Researcher 2023

Literature has demonstrated that level of study of university students influence their gambling behavior. It was therefore important to determine the educational level of the study participants. The findings indicated that majority (70.7%) of the respondents were undergraduates while (29.3%) of the respondents were post graduates. This results are a fair distribution since most of the university students are in their undergraduate levels of study.

Marital Status of the Respondents

The marital status of the respondents was inquired. This was important since there is literature suggesting that marital status affects or influence gambling behavior among university students. This study therefore sought to determine the marital status of the respondents. The results were presented in Table 5

Table 4: Frequency Distribution of Marital Status.

Source: The Researcher 2023

It was observed that majority (66.8%) of the respondents were not married while (33.2%) of them were married. It could also be assumed that majority of the university students were not married and were still under parental care and had few or no family obligations and responsibilities. This can encourage students to practice gambling and other risk activities due to lack of responsibility and availability of time.

Effects of Gambling on Academic Performance

The Table 4 presented information regarding gambling’s consequences on academic achievement.

Table 5: Effects of Gambling on Academic Performance

Source: The Researcher 2023

The findings found that those who agreed that gambling negatively impacted their academic grades were 148(81.9%) and those who claimed it did not were 33(18.1%) of those who claimed to have skipped classes because of gambling, 82(45.1%) and those who claimed to have not been 99(54.9%). Those respondents who indicated to have lost time in school due to gambling were 36(19.7%), and those who claimed to have not lost any time were 145(80.3%). On whether the students have ever repeated academic classes due to gambling, 18(9.9%) of the respondents affirmed that to have done so, and 163(90.1%) claimed they had not. Lastly, those who agreed that they gambled money meant for school fees and lost were 55(30.3%), and those who did not were 126(69.7%). Generally, we can say that gambling affects the student’s academic performance that is, loss of money and time meant for attending classes. This results are in line with study results from Ladouceur et al. (1999), which established that gambling during after school hours reduces time for school related work, it also found out that many gamblers skipped classes during school hours.

Chi-Square Analysis to Determine the Effects of Gambling on Academic Performance among University Students in Nairobi County, Kenya

The analysis of the relationship between the effects of gambling and academic performance among university students was analyzed inferentially using the chi-square test for independence. This is because the effects of gambling and performance were both categorical variables. The variable “effects of gambling” involved the effect on their academics that were as a result of their involvement in gambling had, items such as: skipping classes due to gambling, lost time for school related work due to gambling and gambling or spending money meant for school fees and lost. The categories for the variable “effects of gambling” were either the students suffered from the said effects as result of gambling versus the students did not suffer the said effects as a result of gambling. The categories for the variable performance were either the student’s grades had been affected by gambling versus the student academic grades had not been affected by gambling. Additionally, the variable performance had categories on whether a student was to graduate on time versus the student was not to graduate on time. The null hypothesis tested was that gambling had no significant effect on academic performance among university students. This hypothesis was tested at 5% level of significance. The results from the inferential analysis yielded a p-value of 0.024 which is less than 0.05 (level of significance) (Table 5). This result led to rejection of the null hypothesis. Consequently, this results showed that gambling had significant effect on academic performance among university students.

Table 6: Chi-Square Analysis for the Effects of Gambling on Academic Performance among University Students

Source: The Researcher 2023

CONCLUSION

Gambling participation was established to have effects on students’ academic performance as a result of gambling preoccupation. With the current heavy investments on gambling advertisement on the main stream media and social media channels, gambling will most likely increase going into the future attracting more young people who are consumers of media communications. Therefore, institutions should strive to put in place primary prevention measures to help curb gambling problem among university students.

RECOMMENDATION

From the findings, this study therefore recommends the following measures;

Policy Recommendation

Universities or institutions of higher learning should come up with regulation measures such as limiting access to gambling sites from their networks during school hours, this will help reduce access to these sites by students.

Other Recommendations

1. Higher institutions of learning should create and strengthen existing peer counseling groups within the institutions to help in counseling those in gambling addiction.
2. Effects of gambling should be incorporated into the university curriculum just as the other addictive behaviors such as drug abuse and alcohol use to caution university students from such effects.
3. Universities should provide alternative recreational activities for students; this way students will have alternatives to gambling activities for recreational purposes.

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