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 Table of Contents  
Year : 2021  |  Volume : 18  |  Issue : 1  |  Page : 52-62

Mitigating the risk of alcohol use among university students: Examining the feasibility and effects of screening and brief intervention - A quasi-experimental study

1 Department of Psychiatry, College of Medicine, University of Lagos; Department of Psychiatry, Lagos University Teaching Hospital, Lagos, Nigeria
2 Department of Psychiatry, College of Medicine, University of Lagos; Department of Psychiatry, Lagos University Teaching Hospital, Lagos, Nigeria; Discipline of Psychiatry, University of Adelaide, North Terrace, Adelaide, SA, Australia; Department of Psychiatry and Behavioral Neurosciences, McMaster University/St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
3 Department of Psychiatry, Lagos University Teaching Hospital, Lagos, Nigeria
4 Department of Psychiatry, Olabisi Onabanjo University, Ago-Iwoye, Nigeria

Date of Submission08-Jun-2020
Date of Acceptance28-Aug-2020
Date of Web Publication2-Feb-2021

Correspondence Address:
Dr. Adebayo Rasheed Erinfolami
Department of Psychiatry, College of Medicine, University of Lagos, Lagos
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcls.jcls_50_20

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Background: The rising prevalence of alcohol use among youths in low resource settings is a major public health issue of concern, especially as alcohol use remains a leading contributor to deaths and disability globally. This study aimed to evaluate the effects of screening and brief intervention (SBI) on alcohol use risk among university students. Methods: In this quasi-experimental study, a total of 636 students were screened for alcohol use risk with the World Health Organization Alcohol, Smoking, and Substance Involvement Screening Test (WHO-ASSIST) version 3.1. All participants with moderate and high risk of alcohol use were administered brief intervention (BI) delivered by trained students at baseline, 1 month, and 3 months, with a final assessment in 6 months. Longitudinal data on their alcohol use risk were analyzed. Results: The mean age (standard deviation) of the participants was 21.13 (3.05) years and 44.5% were female. The prevalence of the current alcohol use based on the WHO-ASSIST was 49.2% (n = 315). Following three sessions of BI, the repeated measures ANOVA indicated that the WHO-ASSIST mean score for high-risk alcohol users (n = 44) fell from 33.23 (3.82) at baseline to 18.3 (9.84) at 6th month. This difference was statistically significant. Similarly, the mean score for moderate alcohol users fell from 19.62 (2.97) at baseline to 11.31 (5.52) at 6 months. The difference was statistically significant. There were significant group-level differences in the risk score over the study period, for the low risk, moderate risk, and high-risk users at the end of the study. Conclusion: Screening and BI showed significant benefits on alcohol use risk. Our findings suggest SBI as a feasible and effective intervention for mitigating the risk of alcohol use among young students in resource-restricted settings. Further research using a robust sample to reflect differences in setting and student characteristics is warranted.

Keywords: Alcohol, peer-led, screening and brief intervention, students, youth

How to cite this article:
Erinfolami AR, Olagunju AT, Akije AO, Ogunsemi O. Mitigating the risk of alcohol use among university students: Examining the feasibility and effects of screening and brief intervention - A quasi-experimental study. J Clin Sci 2021;18:52-62

How to cite this URL:
Erinfolami AR, Olagunju AT, Akije AO, Ogunsemi O. Mitigating the risk of alcohol use among university students: Examining the feasibility and effects of screening and brief intervention - A quasi-experimental study. J Clin Sci [serial online] 2021 [cited 2021 May 16];18:52-62. Available from: https://www.jcsjournal.org/text.asp?2021/18/1/52/308600

  Introduction Top

Globally, around 2·4 billion people were current drinkers in 2016, and alcohol use remains a leading risk factor for substantial health loss and deaths among young people. For example, about 8·9% of disability-adjusted life years (DALYs) and 12·2% deaths in males aged 15 – 49 years resulted from alcohol use; and the 2·3% DALYs and 3·8% of deaths in females in the same age group was attributable to alcohol in 2016.[1] In the same vein, several health and psychosocial complications of alcohol use have been identified among students, including poor academic performance, intimate partner and sexual violence, risky sexual behavior, criminal tendencies, physical and aggressive behavior, substance-related deaths, and medical comorbidities.[2],[3],[4],[5],[6],[7]

While abstinence is desirable to mitigate alcohol use risk, several characteristics of youths such as desire for experimentation, lifestyle changes, and psychosocial vulnerabilities often perpetrate continued use of alcohol, and make relapse more likely despite treatment.[8],[9],[10] Consequently, interventions are often targeted towards prevention among nonusers, and mitigation of risk to enhance harm reduction or abstinence among current users.[11],[12]

Screening and brief intervention (SBI) is a widely accepted intervention for substance abuse in adolescents and youths.[13],[14],[15] Importantly, SBI involves the use of structured questions to detect substance use problems and categorize risk levels. This is followed by a brief talk-therapy or counseling using the information elicited on risk. Clients can also be referred to specialized addiction treatment if the screening test indicates problematic or addictive pattern of use.[16],[17],[18] Earlier findings on the effectiveness of SBI to manage substance abuse in youths is somewhat mixed.[11],[19],[20] While some studies showed significant reduction in substance abuse among patients under SBI-linked treatment,[21],[22],[23] other reports have suggested nonsignificant reduction in substance use and harm of use.[24],[25]

The trend in alcohol use among youths is now a huge concern given the negative consequences of risky alcohol use on health loss, and the pivotal roles of young people to national development and productivity. The peer-led intervention has been proposed as findings from a meta-analysis of similar studies suggest that peer-led interventions play a role in preventing tobacco, alcohol, and cannabis use in young people.[26]

Despite the popularity of SBI-linked interventions to mitigate the risk of alcohol, empirical evidence on its effectiveness for youths in resource-restricted settings is limited. For instance, there are only a few context-specific and community-based studies on SBI-linked interventions.[22],[23] Again, while enactment of drug policies and the introduction of other interventions to curb risky alcohol use is common, evidence-based studies to support the introduction of SBI-linked intervention for students is patchy. This study will presents findings on the effectiveness or otherwise of SBI-linked intervention on alcohol use risks among youth students. The study aimed at ascertain if SBI can significantly reduce moderate and high-risk alcohol use among undergraduates, determining the prevalence of alcohol use among undergraduate students as well as to determine the significant sociodemographic predictors of alcohol use among undergraduates.

  Methodology Top

Study design and sample size

This quasi-experimental study reports data collected from undergraduate students of University of Lagos, Nigeria. The study approval was granted by the institutional ethics and student affairs committee before the study commenced. The selection of participants was based on multi-stage probability sampling. It began with a random selection of five faculties from a sampling frame containing all 12 faculties in the University. The faculties selected are arts (n = 3107), basic medical sciences (540), clinical sciences (1058), management sciences (4465), and law (n = 1868). In the second stage, the sample size for each faculty was computed using the sample size formula, s = (χ2 × Np [1 − p]) ÷ d2 [N − 1] + (χ2 [p × (1 − p)]).[27] Computations for the sample size for each faculty was conducted using a margin of error (d) of 0.05, a confidence level of 95% (with χ2 = 3.8416), and response distribution (p) of 15.0%. The estimated sample size was 861 and made up 185, 144, 166, 188, and 178 from each faculty in proportion to the number of students described above. Eligible participants aged 16 years and older were selected through a random sampling technique after obtaining written informed consent from all of them.

Study instruments

All participants were administered a study designed sociodemographic questionnaire to collect information on age, gender, marital status, ethnicity, monthly income, religious orientation, school year, and faculty. This was followed by the World Health Organization Alcohol, Smoking, and Substance Involvement Screening Test (WHO-ASSIST) version 3.1. The WHO-ASSIST is an 8-item questionnaire measuring levels of risk for the use of ten substances. This instrument can capture risk for poly-substance use, however, this present study focused on alcohol use. It is a valid and well-used instrument in multicultural settings among youths.[28],[29] In terms of construct, item one was used to determine lifetime use of alcohol, while current alcohol use was determined by item 2 based on participant choosing between the “monthly,” “weekly,” and the “daily/almost daily” response options.[22] Alcohol use risk profiles was determined by the WHO-ASSIST total scores based on summation of individual item score from items two to seven. These total scores were used to categorize participants into low-risk users (score 0–10), moderate risk users,[11],[12],[13],[14],[15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25],[26] and high-risk users of alcohol (27 and above).[30]

Preintervention and training of field assistants for screening and brief intervention

The study was structured into three phases spanning 10-month period (April 2018 to February 2019). In preparation for recruitment, field assistants, (made up of medical students while on psychiatry rotations) were trained with the WHO Manual for Brief Intervention for Substance Use by experienced trainers.[31] Simulation and role-play were employed during training sessions to ensure effective skill transfer and quality control in the administration of brief intervention (BI). Herein, 10 students who were using substances were presented to role play as the recipients of the BI to both the field assistants and the trainers independently.[31],[32] They were asked to rate the quality of the intervention received from students versus trainers across eight criteria adapted from the Standardized Patient Motivational Interviewing Rating Scale (SPMIRS).[33] The SPMIRS score ranges from 8 to 40, with higher scores indicating higher motivational proficiency on the part of the interviewer. The responses from the 10 role players were compared using the intraclass correlation coefficient (ICC), the analysis yielded a score of 0.747 and as such supporting high correlation in the quality of the BI given by the students and trainers.

Intervention phase and data collection

All participants with low risk for alcohol use (n = 363) were not enrolled to progress into BI phase. On the other hand, participants with moderate risk (n = 225) and high risk (n = 48) for alcohol use were administered BI at baseline, 1- and 3-month from baseline. WHO-ASSIST scores for participants were collated at every point of the BI phases as well as a final assessment was conducted at 6-month from baseline. Each intervention session lasted up to approximately 15 min. The BI was based on the FRAMES model of motivational interviewing which had shown to be applicable to problematic substance users in general.[33],[34] BIs after baseline were carried out by the medical students (field assistants) at a clinic weekly within the wellness outpatient facility of the Medical Centre in the University. Participant with high-risk levels of alcohol use after each ASSIST scoring were continually referred for more extensive treatment at the Addiction Treatment Unit of Lagos University Teaching Hospital [Figure 1].
Figure 1: Intervention Progression of Moderate and High-Risk Users of Alcohol from Baseline to Final Assessment Stage of the Study

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Data analysis

Statistical analyses were performed withSPSS version 23.0 (SPSS Statistics for Windows, version 23.0 (IBM Corp., Armonk, N.Y., USA). Descriptive statistics included were frequencies and percentages for categorical variables while continuous variables were reported with mean and standard deviations. The Chi-square test was used to check for significant associations between sociodemographic variables and current alcohol use. Significant sociodemographic predictors of alcohol use risk were determined using odds ratios, obtained from an ordinal regression analysis of the use risk category on the sociodemographic variables of the users. The effectiveness of the SBI was assessed with the repeated measures ANOVA (with corrections for violations of sphericity, with the Greenhouse–Geisser correction) to ascertain if there were any significant difference in the mean alcohol use risk scores across baseline and the other three intervention points. The Bonferroni post hoc test was used to make pair-wise comparisons of use risk scores between the four time periods. All statistical inferences were made at the 0.05 significance level.

  Results Top

Sociodemographic characteristics of participants and association with the current alcohol use

Of the targeted 861 participants, only 636 students consented to participate in the study at baseline, resulting in a response rate of 73.3%. The mean age of study participants (n = 636) was 23.16 ± 4.23 years, and 317 (49.8%) were female. Majority belonged to 16–20 years (n = 230; 36.2%) and 21–25 (n = 208; 32.7%) age groups. Most of the participants were single (n = 551; 86.6%). Monthly allowance for the students averaged N71,150 ± N24,003, about 197USD (exchange rate of one US dollar = N362), with the bulk of students (308; 48.4%) coming from the low-income group (income ranging between $27.62 – $110.50, based on income groupings).[35] There were more students in their 2 years of study, 200 level (226; 35.5%), with fairly the same number of students from the 3 years of study, 300 level (180; 28.3%) and 400 level (29.15). A little above a third of the students rated themselves as average in academic performance (235; 36.9%) while 193 of them (30.3%) indicated they have good academic performance. There were relatively more students from the faculty of management sciences (175; 27.5%), with a relatively smaller number of students from the faculty of law, with 64 students (10.1%). The sociodemographic variables that are significantly associated with the current use of alcohol includes gender (P < 0.001), age group (P < 0.001), socioeconomic status (P = 0.022), level of study (P < 0.001), and level of academic performance (P < 0.001) [Table 1]. Marital status, religious orientation, ethnic origin, and faculty of study were not significantly associated with the current use of alcohol.
Table 1: Sociodemographic distribution of respondents and association with current alcohol use at baseline

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Lifetime and current use, and risk levels of alcohol use

The lifetime prevalence for alcohol use was 72.9% while the current use prevalence was 49.52%. The alcohol use risk category of the students at baseline indicated that there are more moderate risk users (71.4%) compared to the low-risk users (13.3%). Only 15.3% of the students were found to be high-risk users of alcohol at baseline [Table 2].
Table 2: Lifetime and current use, and risk levels of alcohol use at baseline

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Sociodemographic predictors of risk of alcohol use at baseline

The level of risk for alcohol use was found to be significantly predicted by gender (being female) (P < 0.05), age group (being within the age group of 21–25 years) (P < 0.05), marital status (being single) (P < 0.05), and the faculties or areas of study (being in management sciences) (P < 0.05). All other sociodemographic variable did not show significant predictive tendencies to alcohol use risk [Table 3].
Table 3: Ordinal regression estimates of sociodemographic predictors of alcohol use risk at baseline

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Comparing changes in the World Health Organization Alcohol, Smoking, and Substance Involvement Screening Test scores of moderate and high-risk users of alcohol following the interventions

For the moderate risk alcohol users who completed the study (n = 216), the WHO-ASSIST score averaged 19.62 ± 2.97 at baseline and 11.31 ± 5.52 at month 6, respectively. The analysis of the changes in mean scores of participants across various intervention stages indicated that the BIs significantly reduced the alcohol use risk evident from the repeated measures ANOVA (F [2.073, 445.695] = 327.602; P < 0.01). The post hoc test showed that there was relatively more reduction in alcohol use risk among moderate risk users between month 1 and month 3 (mean difference = 4.278; P < 0.01), as it was higher than the reduction in mean score between month 3 and month 6 (mean difference = 3.394; P < 0.01). Similarly, the repeated measures ANOVA (F [1.173, 50.493] = 74.104; P < 0.01) for the high-risk alcohol users who completed the study (n = 44), indicated a significant difference in the WHO-ASSIST mean scores falling from 33.23 ± 3.82 at baseline to 18.30 ± 9.84 at month-6. For consecutive time periods, the post hoc tests, however, indicated a more significant reduction in alcohol use risk between month 3 and month 6 of the intervention period (mean difference = 10.159; P < 0.01) [Table 4].
Table 4: Comparing changes in World Health Organization alcohol, smoking, and substance involvement screening test scores of moderate and high-risk users of alcohol following the interventions

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  Discussion Top

The limited empirical evidence on the effectiveness of alcohol intervention programs on health and psychosocial challenges of its use among students' population in resource-limited settings like Nigeria led to this study. Our study has attempted to assess the possibility and effects of reducing the risk of alcohol use among university undergraduate with the use of BIs. This article is one of the few intervention studies on alcohol use among this population in sub-Saharan Africa. The results showed that ASSIST-linked BIs significantly reduced the risk of alcohol use in substantial proportion of University undergraduates with moderate and high risk, that the prevalence of lifetime use and current use of alcohol at baseline were 72.9% and 49.5%, respectively, and that the sociodemographic predictors of alcohol use among this population included gender, age group, marital status, and course of study.

As for the effectiveness of the ASSIST-linked BI among undergraduates using alcohol, this study showed that phased administration of BIs to moderate and high-risk users of alcohol provided by students (medical students) significantly reduced their use risk scores. This maybe so as each session of BI act as short reminder of the danger involved in continuous use of alcohol, aside from being as short counseling session. This replicates the findings of Lasebikan et al., among residents of a Nigerian semirural community where significant reductions in participants' alcohol use risk score was reported following BIs.[22] In the same vein, it corroborates the results of Gryczynski et al. regarding significant reductions in WHO-ASSIST scores among residents in a rural community in New Mexico after both person-administered and computer-administered BIs Further analysis comparing socio-demographic variables among participants who were lost to follow-up against those who were successfully followed up is presented in Appendix 1.[36] These three studies share some similarities in the questionnaires used, however, despite the difference in the settings and subjects studied, findings in those studies seems to emphasized the importance of BIs in substance use across different setting and varied subjects. Similarly, our finding is in tandem with the results of Reyes-Rodríguez et al. with respect to significant reductions in the frequency and amount of alcohol consumed, as well as the risk of use on the part of Colombian high school adolescents exposed to sessions of motivational interviewing-based BI.[37] Significant reductions in alcohol use risk found in this study following BIs refute the findings of insignificant reductions in the frequency of alcohol use among participants exposed to alcohol BIs by Platt et al.[38] In similar contradictions, the result of this study does not reinforce the findings of Butler et al. where BIs had no significant effect on behavioral changes in alcohol use after 3 months as well as biometric measures at 12 months among their subjects.[39] In addition, the results of this study conflict the findings of Kaner et al. during which three sessions of BIs did not significantly reduce adverse alcohol use even after 6 and 12 months.[24] The differences in these studies could be accounted for by methodological differences, assessment tools, study locations as well as population studied.

Our study, also indicated that there was a sustained reduction in alcohol use risk as the intervention progressed, given the larger mean differences alcohol use risk scores between month 1 and month 3 compared with month 3 to month 6 for both the high risk and moderate risk users. This point to the fact the prevalence of alcohol use reduced significantly between baseline and month 6 as well as significant conversion of students from high risk to moderate and low risk drinkers. This implies that BI is an effective tool that can significantly reduce alcohol use risk on a large scale. Herein, high-risk users can become moderate risk users, and on fewer occasions become low-risk users. Moderate risk alcohol users can have their substance use risk significantly reduced, with most of them becoming low-risk users. This, however, conflicted with the findings of Merchant et al.[40] when they reported significant reductions in alcohol use risk within the first 3 months of the intervention, but fizzled out in the latter part of the study.

The lifetime prevalence of alcohol use in this study was higher than the previously reported among other Nigerian students which ranged from 56.5% to 72%; similarly, the current use prevalence of alcohol was higher than previously reported range, 27.3%–33.3%.[41],[42],[43] A possible reason for this may be that many of these studies were conducted in the different part of Nigeria, with varied cultural and religious differences. The current study was conducted in Lagos, commercial nerve center of Nigeria where youth are exposed early in life to various vices which may include introduction to alcohol use. Another plausible reason for the discrepancies may be methodology and study instruments explored in the study. Similarly, the lifetime prevalence of alcohol use (72.9%) among these undergraduates varies from lifetime prevalence from a study done in another clime within the sub region by Tesfaye et al. where they recorded 53.8%.[44] These differences may be due to differences in methodology and study instruments employed in the study. Alcohol is generally not considered a drug in many quarters and its use is socially acceptable except in areas where it is prohibited on religious grounds or some other setting where there were other forms of restrictions. This may explain the relatively high lifetime and current rate of alcohol use among this students population where it may be difficult to enforce rules and regulation against sales and use of alcohol within the campus. This may also apply to students residing outside the campus or may be worst especially among students staying in private hostel accommodation, a common practice due inadequate hostel within the campus. These off-campus hostels are devoid of necessary restriction. Earlier reports by Ebirim and Morakinyo[45] had documented similar rates while Adelekan et al.[46] recorded a much higher figures among subjects in comparable settings.

Notably, gender, age-group, socioeconomic grouping, level of study, and academic performance were the significant sociodemographic correlates of current alcohol use. The findings of significant relations between gender, age, and socioeconomic grouping and current alcohol use are in line with recent findings by Ajayi et al. among Nigerian students.[43] This also corroborates the work of Eze and Uzoeghe,[47] as they reported gender and age as significant correlates of the current alcohol use in Nigerian students. Notwithstanding, contrasting findings had been reported that age was predictive of alcohol abuse among Nigerian undergraduates.[41] The course of study reported as a significant correlate of alcohol use in our report was equally corroborated with similar results obtained by Duru et al.[41] The significance of academic performance as a correlate of alcohol use risk was in tandem with the report documented by Johnson et al., where they found that cumulative grade point aggregates of Nigerian undergraduates was significantly correlated with their use of psychoactive substances.[48]

Our findings on predictors of alcohol use risk indicated that female gender reduces the likelihood of higher use risk of alcohol on the part of the students. This can be explained based on the cultural/religious believes in Nigeria which seems to discourage the use of alcohol openly by female gender and as such similar attitude may be seen among student population. This report is similar to the results of Zadarko-Domaradzka et al. where being male increased the likelihood of European students indulging in risky drinking.[49] It also corroborates the study findings of Erevik et al. that being male increases the likelihood of riskier harmful alcohol use among Norwegian students.[50] Furthermore, the finding of younger age-groups having significant likelihood of riskier alcohol use was not surprising especially among students population as young adolescent who are having total freedom from parental restrictions at early age will likely indulge in riskier alcohol use. This was in keeping with the findings of Erevik et al. that increase in age (being in older age groups) reduces the likelihood of risky and harmful alcohol use.[50] The significant increase in the likelihood of riskier alcohol use among single Nigerian students found in this study are based on similar reasons as the former. This corroborates the findings of Erevik et al. that being single makes it 1.52 more times likely for Norwegian students to indulge in harmful alcohol use.[50]

Clinical practice implications

The study results speak to several existing practices aimed at reducing alcohol use among the undergraduate population, as well as points out new insights as to what future directions should be in substance use reduction efforts. Importantly, the prevalence and reported risk levels of alcohol use among undergraduates remain high and justify addiction intervention services as an integral components of health care need of students. This will ensure that every student with alcohol use problems is provided the opportunity to receive care regardless of the nature of their presentation. Such services should include the integration of screening for alcohol and other drug use problems into student mental and wellbeing services. Efficient data collection and its use to develop targeted interventions are needed. Furthermore, this study findings revisited the benefits of BIs as an effective measure to mitigate alcohol use risk and its related consequences among undergraduate. Notable outcomes that are possible with SBI included reduction in the frequency or amount of use, readiness to change, positive behavioral adjustments, changes in perception about drug use risk, attempts to quit, as well as reduced adverse consequences.

In addition, the use of fellow students from the same institution to provide screening and BI is unique. This was intended to give some degree of peer support to alcohol drinkers which were known to demonstrate increased treatment retention, improved relationships with treatment providers and social supports, increased satisfaction from the services rendered. This was case in this study as dropout rate of participants was minimal.

The more significant reductions in risk of alcohol use among the moderate and high-risk users between month 1 and month 3 compared to any other stage in the study show that the time apart or space between intervention periods may have an implications for intervention effectiveness. As such, the period between which interventions are administered should not be too far apart.

In the case of the high-risk users, the BI can be employed as a tool to initiate substance use reduction, while also attempting to expose these users to more specialized treatment via the referrals to more intensive treatment options. Even in cases where BIs do not bring about desired outcomes in drug use behavior over a planned intervention period, the process can provide clinicians with relevant data and experience on what works and does not work with the different cross-sections of undergraduates.

Study strengths and limitations

This present study is the first longitudinal study to evaluate the effectiveness of SBI for mitigating alcohol use risk among Nigerian undergraduates to the best of our knowledge. Despite the absence of a control group in the study, the within-subjects approach in the study, with the phased introduction of the BIs at different time periods and subsequent follow-ups during the study helped to maximize the benefits of BI on substance use risk. While most related studies tend to focus on the sociodemographic correlates of the frequency of substance use or use status of students, the present study provides empirical evidence on the sociodemographic correlates of substance use risk, which is a more composite substance use measure that can be targeted by interventions.

The study is limited by the “one size fits all” approach in which the same BI was provided to both moderate and high-risk users of alcohol. This could explain the lack of improvement in alcohol use risk in some of the participants. Again, this has relevant implications for the likelihood of poor maintenance of the benefits of the intervention over a long period. However, the reliability tests of the BIs administered by the field assistants and mental health professionals gave an ICC of 0.747. This gave credence to the quality of the BI as the study progresses with subsequent interventions at first and 3rd month were administered by field assistants.

The reliance of the study on the self-reports of the participants throughout the study, without drug testing to confirm their self-reports is another limitation, particularly because students might understate their frequency of use or extent of adverse effects from use.

  Conclusion Top

The study provides ample evidence that BI can be effectively employed to mitigate alcohol use risk among undergraduates. While alcohol use remains a common and a complex problem, SBI showed notable benefits as a feasible, time-efficient, and cost-effective intervention to deal with alcohol use problems among students in resource-poor setting. Effective screening procedures can provide reliable database to design alternative drug interventions or programs for youths. Future direction to mitigate alcohol use risk should include making sure that BIs are contextually relevant and individualized as much as possible to increase effectiveness at both the individual user and group levels.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  Appendix Top

Appendix 1: Comparison of respondents who completed the study with those who dropped out

A drop-out rate of 4.76% was obtained. The dropout participants were not significantly different from those who completed the study in most of the variables except in academic performance where a higher proportion of participant who dropped out were of poor academic performance (P < 0.05) and socioeconomic status as a significant proportion of those who completed the study are within low socioeconomic group (P < 0.05) [Table 1]a.

  References Top

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  [Figure 1]

  [Table 1], [Table 2], [Table 3], [Table 4]


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