Data may be available when requested from the corresponding author, K.E.M., according to data-sharing principles of Sefako Makgatho Health Sciences University.
In South Africa, many studies conducted on substance abuse among in-school youth focus on urban areas. However, anecdotal evidence suggests that rural areas are experiencing an increase in substance abuse, though there is dearth of studies in these areas.
This study used a quantitative design to collect data from 629 high school learners who were in Grades 10 and 11 in public schools in rural Free State Province, to determine the prevalence of, and factors associated with substance use.
The sample consisted of 46% males and 54% females. Their ages ranged from 14 to 20 years, with a mean of 16.9 years. The prevalence of substance abuse was 47% (n = 295) with alcohol consumption, cigarette and dagga smoking being the most common substances used. Socio-demographically, age and gender were significantly associated with substance abuse. While behavioural variables of physical fights, serious problems with parents and friends, poor academic performance, trouble with police, having sex without condom, and having sex and regretted the next day were significantly associated with substance abuse (p = 0.05).
The prevalence of substance abuse is very high for this rural school community, which highlights the need to pay attention to rural schools regarding substance abuse challenges.
Keywords: substance abuse, high school, rural area, Free State province, South AfricaSouth Africa has a high rate of substance abuse among young people, which includes both in and out of school youth. Despite reported stigma and associated reluctance to seek treatment for substance abuse, 1 an increase in young people aged 20 years seeking treatment for substance abuse, 2 is an indication of the gravity of the problem. Variations in the trends of substance use have been reported between urban and rural youth, 3 with substance use among learners in urban area being more than those in rural areas. 4 However, rural areas are increasingly experiencing problems of adolescent substance use. 5
Substance abuse among learners is associated with a range of criminal acts, 6,7 which includes violence and bullying. 8,9 It has also been associated with a range of mental disorders 10 ; while socially, it is associated with social disorganisation, deviant behaviour, and social interaction with deviant groups, 11 depending on which substances are used. Risky sexual behaviours are also likely to manifest into sexually transmitted infections.
In the school environment and academic context, substance abuse has been associated with challenges in school discipline, 12 appetitive aggression 7 and other classroom management challenges. 13 These frustrate the achievement of intended education outcomes, and result in poor academic performance, including possible dropping out of school.
The social environment is often a significant determinant of substance abuse, 14 with adolescents being often influenced by their peers. 15 Other determinants of drug use among young people include: curiosity, sense of growing up, amount or lack of parental discipline and monitoring, and family cohesion. 16 Availability and easy access of illicit drugs within the community or the household, 17 economic hardship, high unemployment, lack of adequate social support networks, pressure to meet daily family needs, family conflicts, 18 were all associated with use of illicit drugs.
In the context of schooling, substance abuse has been significantly associated with poor academic performance, 19 which often results in dropping out of school. 20,21,22,23,24 The perceptions that rural areas experience less substance abuse among learners often result in inadequate attention being paid to such areas. With the precise intention of expanding substance abuse studies to areas other than cities, the purpose of this study was to determine the prevalence of substance abuse, as well as explore the associations between substance abuse and a range of demographic variables among learners in a rural school district of Free State Province, South Africa.
A cross-sectional quantitative survey, using a self-developed questionnaire, was conducted among learners attending local high schools in the rural school district of Free State Province, South Africa.
The study was conducted at high schools at Setsoto local municipality, Thabo Mofutsanyane District of the Eastern Free State, which is largely rural. The municipality is comprised of four rural towns namely Clocolan/Hlohlolwane, Marquard/Moemaneng, Senekal/Matwabeng, and Ficksburg/Meqheleng. According to the Census 2011, the municipality has a population of 1 10 335, and of those aged 20 years and above approximately 8.7% have no formal schooling, 22.6% have completed matric, and 6.9% have some form of tertiary education. Agriculture is the main economic activity in the municipality, and the unemployment rate of those aged between 15 and 34 is high at 46%.
The study population was high school learners in public schools of Setsoto municipality. There are eight public schools in the sub-district, and using the hat method, four schools from each rural town were randomly selected. An additional school was used for the pilot study. The estimated population of Grades 10 and 11 in the eight schools is 2100.
The sample consisted of learners who were in Grades 10 and 11 at the time of data collection. From estimated population size of 2100 from eight schools, the Raosoft sample calculator was used to determine a minimum sample for the study. Using a 5% margin of error, a confidence level of 95% and a distribution of 50%, a minimum sample size of 323 was calculated. Because a survey was used, in which all learners willing to participate in the study were invited, 800 learners in 42 classrooms participated, but 629 were analysed, with the rest having missing information of more than 10%.
Recruitment was done at the identified school, with the researcher addressing the Grades 10 and 11 learners by telling them about the study and requesting them to participate. Those who agreed to participate were given letters for their parents to provide informed consent.
An English self-administered questionnaire, which was modified from a risk behaviour survey, was used to collect data. The tool was pilot tested among 20 learners at another school before data collection. The tool collected learner-related demographic data like age, gender, grade, and whether they have ever repeated a class, as well as the socio-economic data of the family, such as employment status of parents, highest education attained by the parents and who the participants live with. Substance use related data collected included the substances of current use, age at which they first experimented with substances, use of substances in their social environment and ease of access of substances. Behaviour related data included whether they were involved in physical fights, were in trouble with police, were engaged in risky sexual behaviour, (such as having sex without using a condom or having sex and regretted it the next day), and problems with parents and friends.
On the day of data collection, learners whose parents had provided the informed consent were assembled in the school hall or classroom and an explanation about the study was repeated. The learners were given an opportunity to ask questions or seek clarification. Informed consent was administered to learners who were over the age of 18, while learners under the age of 18, whose parents had provided consent, were requested to provide assent by signing the appropriate forms. The data collection tool was then distributed to all the learners. Adequate time was given to complete the questionnaires, and the learners left the venue after all had completed the process.
The data were captured into Microsoft Excel and transported to STATA version 13 for analysis. Descriptive statistics were used to analyse socio-demographic data prevalence of substance use, and these were reflected in the form of frequencies and percentages. Chi-square test was used to explore associations between a range of demographical variables and substance abuse among the sample. Statistical significance was set at ≤ 0.05.
At sub-district district level, selection bias was minimised by random selection of schools. The use of the survey at school minimised selection bias as all learners in the selected grades who were prepared to participate were included in the study. The questionnaire was pilot tested to identify any challenges before the actual data collection commenced.
Ethical approval for the study was obtained from the Sefako Makgatho Health Sciences University Research and Ethics Committee (number: SMUREC/H/95/2016). Permissions to conduct the study were obtained from the offices of the Provincial Department of Education, the Thabo Mofutsanyane District of Education, the Setsoto sub-district and the management of each participating school. Informed consent was obtained from parents for participants who were younger than 18 years of age, and these minors provided assent to participate in the study. Informed consent was obtained from participants who were 18 years and above.
Eight hundred (800) learners participated in the survey, and of these, 629 were analysed, with the others being excluded because of missing data of 10% or more. Of the 629 students whose data were analysed, more than half (55%) were in the age group 16–17 years followed by those aged 18 years and above (33%). Their ages ranged from 14 to 20 years, with a mean of 16.9.
The prevalence of substance use among the study participants was 47%, and of those using substances, the highest proportion consume alcohol (87%) followed by cigarette (45%) and (24%) dagga smoking ( Table 1 ).
Prevalence and types of substance use among learners (n = 295).
| Substance | No | % |
|---|---|---|
| Alcohol | 256 | 87 |
| Cigarette | 134 | 45 |
| Dagga | 72 | 24 |
| Nyaope | 11 | 4 |
| Cocaine | 7 | 2 |
| Ecstasy | 6 | 2 |
| Other | 18 | 6 |
Note: The total exceeds 100% because some participants reported more than one substance.
Association between demographics and substance use.
| Variables | Total | Non-user | User | p | ||
|---|---|---|---|---|---|---|
| N | % | N | % | |||
| Age in years | ||||||
| ≤ 15 | 78 | 51 | 65 | 27 | 35 | 0.002 |
| 16–17 | 346 | 193 | 56 | 153 | 44 | |
| ≥ 18 | 205 | 90 | 44 | 115 | 56 | |
| Gender | ||||||
| Male | 288 | 136 | 47 | 152 | 53 | 0.007 |
| Female | 341 | 198 | 58 | 143 | 42 | |
| Grades | ||||||
| 10 | 459 | 252 | 55 | 207 | 45 | 0.137 |
| 11 | 170 | 82 | 48 | 88 | 52 | |
| Employment status of parents | ||||||
| Both employed | 107 | 53 | 49 | 54 | 51 | 0.560 |
| Mother employed | 179 | 90 | 50 | 89 | 50 | |
| Father employed | 163 | 89 | 55 | 74 | 45 | |
| Both unemployed | 179 | 101 | 56 | 78 | 44 | |
| Stay with | ||||||
| Alone | 24 | 17 | 71 | 7 | 29 | 0.107 |
| Both parents | 221 | 112 | 51 | 109 | 49 | |
| Father | 36 | 14 | 39 | 22 | 61 | |
| Mother | 194 | 112 | 58 | 82 | 42 | |
| Grand parents | 134 | 67 | 50 | 67 | 50 | |
| Family | 20 | 12 | 60 | 8 | 40 | |
| Who introduced them to substances | ||||||
| Parent | 9 | 3 | 33 | 6 | 67 | < 0.001 |
| Friends | 261 | 67 | 26 | 194 | 74 | |
| Sibling | 27 | 10 | 37 | 17 | 63 | |
| Not stated | 310 | 236 | 76 | 74 | 24 | |
Table 3 illustrates behaviours that were significantly associated with substance use.
Associations between behaviours and substance use.
| Behaviour | Non-user | User | p | ||
|---|---|---|---|---|---|
| n | % | n | % | ||
| Physical fights | 75 | 23 | 122 | 42 | < 0.001 |
| Accident or injury | 68 | 21 | 78 | 27 | 0.070 |
| Serious problems with parents | 87 | 26 | 121 | 41 | < 0.001 |
| Serious problems with friends | 128 | 37 | 154 | 53 | < 0.001 |
| Performed poorly at school | 149 | 45 | 175 | 60 | < 0.001 |
| Being a victim of robbery | 28 | 8 | 37 | 13 | 0.078 |
| Trouble with police | 13 | 4 | 32 | 11 | < 0.001 |
| Had sex without condom | 79 | 24 | 107 | 37 | < 0.001 |
| Had sex and regretted the next day | 62 | 19 | 89 | 31 | < 0.001 |
The purpose of the study is to determine the prevalence of substance abuse, as well as explore the association between substance abuse and a range of demographic variables. The prevalence of substance abuse among this sample is high at 47%, which is close to the 47.9% reported in a similar sample in Ethiopia, 25 but higher than the 6% reported in another study conducted in a rural setting in South Africa. 4 The finding that many learners started using substances at a young age of 15 years confirms findings of a previous study conducted in South Africa. 16 Although cigarettes and alcohol are legal, they are still illegal for minors such as most of the sample. Of greater concern is the use of illicit drugs such as dagga, nyaope, ecstasy and cocaine, which indicates criminality as these are prohibited substances. Dagga is easily cultivated and commonly used in South Africa, and nyaope is a cocktail drug that has destroyed many lives among Black communities in South Africa because of its high addictive characteristics. 26,27,28,29,30
Adolescents who use drugs have been reported to have significantly lower levels of psychological well-being and life satisfaction, 31,32 which implies mental and social risks for the sample. Although peer pressure may influence young people to use drugs, they still feel guilty and stigmatised by family and community, which increases the chances of social ill-health, 33 which increases the shame associated with the behaviour of using substance. 34 The challenge of substance abuse should therefore be understood comprehensively as a problem of adolescent social ill-health.
Males had a significant higher prevalence of substance use than females (p = 0.007), which is similar to previous studies which reported that males were up to 10 times more likely to use substances than females. 35,36 The finding that older learners are more likely to use substances than younger ones is similar to a study conducted among learners in the Western Cape, which reported the odds ratio of 1.6 among older learners. 36 Also similar is the finding that substance use by other members of the household and friends, increases the risk of use among learners two-fold. 36 These findings highlight the need for comprehensive interventions to influence the comprehensive well-being of young people, especially among young learners. Such interventions also need a community component, 37,38 which is likely to improve the effectiveness of substance use prevention amongst learners, and thus improve the overall well-being of these young people.
Substance use has been shown to be associated with poor academic performance, 39,40,41 a serious barrier to reaching the goals of the education system. The finding of a significant association between substance use and risky sexual behaviour 42 confirms the negative impact of substance abuse on overall youth health.
The significant association of substance abuse with a range of anti-social behaviours of physical fights, serious problems with parents and friends, poor academic performance, trouble with police, having sex without condom and having sex and regretted the next day, all with p-values of 0.001, are similar to the findings reported in previous studies, which reported statistically significant associations ranging from p-values of 0.001–0.05. 36,43 These findings put substance abuse at the centre of various problems experienced at South African schools and communities. These associations also identify the need to target substance abuse as a barrier to overall social development because the outcomes, be they academic, physical health, social and/or mental have long-term implications for the affected learners.
Alcohol, cannabis and cigarettes were found to be the most commonly used substances, which is similar to another study conducted in Durban, South Africa. 44 The ease of access for these substances increases the levels of challenges as this cannot be addressed without the involvement of other sectors, including the law enforcement and behavioural scientists. The complexity of the situation also indicates the urgency of stakeholders to work together to develop interventions that are focused on both prevention and management. Currently, there are no such interventions accessible by the general learner in any South African public-school setting.
Despite the challenges of substance abuse in schools, it does not seem that the Department of Education has any specific intervention to address the problem, other than relying on the Life Orientation (LO) learning area, which aims to address a wide range of learner developmental areas. which include personal, psychological, neuro-cognitive, motor, physical, moral, spiritual, cultural and socio-economic areas. 45 However, the delivery of LO has been reported to have serious challenges because of constraints at the individual, interpersonal, school, and community levels. 46 Another shortcoming of LO as a resource for substance abuse is that it is general, and does not address personal experiences, 47 and therefore is limited in assisting learners with substance abuse challenges. Of serious concern is that the Department of Basic Education’s policy on management of substance abuse in schools is neither known nor implemented, 48 which implies that there is not much at school level that addresses the serious problem of substance abuse among learners.
As with other survey studies, 21% of the questionnaires could not be analysed because of missing data. However, the high response rate of 78% and a relatively large sample size of 629 counteracted the non-usable questionnaires. A limitation which applies to other survey studies is the response bias, in which the sample may under- or over-estimate the population parameter. However, this potential bias was minimised by sampling from various schools and more than one class in a school. Societal lack of approval of substance abuse by learners may have contributed to bias in their responses, but this was minimised by the privacy afforded to the participants, which meant that others would not have known about their responses.
The result of the study contributes to highlight the need for interventions to address the challenge of substance abuse in schools, which will improve the academic outcomes with long-term social and career impacts. As substance abuse is more of a societal rather than just a school’s challenge, the required interventions need not be limited to schools, but extend to other young people in communities, including rural areas.
It is recommended that the substance abuse problem be outsourced to public health and/or behavioural health specialist and not be left to the Department of Education, as this is not their focus areas. This will enable consistent application, monitoring and evaluation of such interventions, and enhance the implementation of necessary modifications.
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
J.N.S. conducted the study and initiated the draft manuscript. K.E.M. supervised the study and refined the manuscript. Both authors finalised the manuscript.
The study and its publication were jointly supported by the DST/NRF/Nedbank Research Chair (Substance Abuse and Population Mental Health) grant (SARCI170807259060), and the South African Medical Research Council (SAMRC) Mid-Career Scientists Programme grant (M052).
Data may be available when requested from the corresponding author, K.E.M., according to data-sharing principles of Sefako Makgatho Health Sciences University.
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agencies of the authors.
How to cite this article: Mokwena KE, Setshego NJ. Substance abuse among high school learners in a rural education district in the Free State province, South Africa. S Afr Fam Pract. 2021;63(1), a5302. https://doi.org/10.4102/safp.v63i1.5302
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