A cross-sectional study of epidemiological factors associated with drug use among secondary school students

Al-Gburi, Karrar Mohammed Hasan; Al-Murshedi, Roaa; Alridha, Ali Mohammed Abd; Baiee, Hasan Alwan

doi:10.1080/14659891.2020.1736664

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…Specifically, male youths are strongly associated with the consumption of psychotropic substances (Rule 1) while female youths often consume cannabis sativa (Rule 4). This agrees with the findings of a study by Al-Gburi, Al-Murshedi, Alridha, and Baiee (2020) which found drug use prevalent among secondary school students. Most of the respondents in that study blamed drug use to peer influence and the zeal to experience new sensations.…”

Section: Discussionsupporting

confidence: 92%

Association Rules on Attributes of Illicit Drugs, Suspect’s Demographics and Offence Categories

Atsa’am

Gbaden²,

Wario

2022

Journal of Drug Issues

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Association rules mining technique was employed to extract 6 rules that show the co-occurrences of the attributes on illicit drug types, suspects’ demographics, and categories of drug offences. A dataset on 262 arrestees of various drug offences was utilized for rules extraction using the apriori algorithm. The rules reveal the different levels of involvement with various illicit drugs by suspects of varying ages. The established rules provide a form of drug suspects segmentation which could guide how drug control and intervention programs are designed and deployed. Further, the rules could serve as a reference tool for security agents when dealing with drug suspects and offenders.

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Section: Discussionsupporting

confidence: 92%

Association Rules on Attributes of Illicit Drugs, Suspect’s Demographics and Offence Categories

Atsa’am

Gbaden²,

Wario

2022

Journal of Drug Issues

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“…Vulnerable children and adolescents are frequently drawn into this complex and dangerous enterprise, most of who attribute several reasons for using drugs to peer pressure (Li et al, 1999). For instance, a research conducted among secondary school students in Iran shows that most respondents attributed the reasons for using drugs to peer pressure, psychological stress, and self-evaluating attempt (Al-Gburi et al, 2020). Black and Ricardo (1994) found that 12% of African American males recruited from recreation centers in low-income urban communities in the United States were involved in drug trafficking.…”

Section: Drug Trafficking and Consumptionmentioning

confidence: 99%

A Model for Predicting the Class of Illicit Drug Suspects and Offenders

Atsa’am

Balogun

Agjei

et al. 2021

Journal of Drug Issues

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In this study, the artificial neural network was deployed to develop a classification model for predicting the class of a drug-related suspect into either the drug peddler or non-drug peddler class. A dataset consisting of 262 observations on drug suspects and offenders in central Nigeria was used to train the model which uses parameters such as exhibit type, suspect’s age, exhibit weight, and suspect’s gender to predict the class of a suspect, with a predictive accuracy of 83%. The model sets the pace for the implementation of a full system for use at airports, seaports, police stations, and by security agents concerned with drug-related matters. The accurate classification of suspects and offenders will ensure a faster and correct reference to the sections of the drug law that correspond to a particular offence for appropriate actions such as prosecution or rehabilitation.

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