Prevalence and determinants of recreational drug use and related health effects among youths
Bibliographic record
Abstract
Background Recreational drug use among youths has emerged as a significant public health concern, particularly in Nigeria's South-South Geopolitical Zone. This study assessed the prevalence and determinants of the use of recreational drugs among youths in Abraka, Delta State. Methods A cross-sectional study was conducted over a period of approximately 4 months, from January 2024 to April 2024, involving 470 youths residing in Abraka, selected through a multistage sampling. Data were collected using a validated structured self-administered questionnaire, while data management and statistical analysis were performed using Microsoft Excel and SPSS version 25, employing descriptive statistics, Chi-square tests, and multivariable logistic regression to identify predictors of drug use. Results The respondents were 64.5% male, 66.8% aged 21–30, 75.1% single, 56.2% had secondary education, 45.5% were skilled workers, 94.5% Christians, and 42.1% had a family history of drug use. Regarding knowledge, 82.6% recognized the risk of long-term dependence, 88.9% acknowledged marijuana's short-term effects, 89.4% understood the risk of kidney and liver damage, and 79.1% were aware of suicidal tendencies associated with severe drug use. Knowledge was rated good in 63.2%, fair in 31.3%, and poor in 5.5%. Attitudes varied: 47.0% strongly disagreed with drug use, 46.6% did not view drugs as harmful, 65.1% agreed that illegal drug possession leads to arrest, and 81.1% had a positive attitude toward drug use. Awareness was high (98.7%), particularly for codeine (85.0%), alcohol (82.9%), and cannabis (76.2%). The prevalence of drug use was 41.9%, with alcohol (59.1%), tobacco (35.1%), and marijuana (22.3%) being the most commonly used substances. Married individuals were 1.6 times more likely to use drugs compared to singles (AOR = 1.6, 95% CI: 1.0–2.6, p = 0.030), and those with tertiary education were 2.1 times more likely to use drugs than those with secondary education or less (AOR = 2.1, 95% CI: 1.5–3.1, p < 0.001). These associations were statistically significant, indicating that marital status and educational level are important socio-demographic predictors of recreational drug use Conclusion The study stresses the need for drug education addressing health risks and social factors. Targeted interventions, including peer-influenced education and community support, are essential to reduce drug use among youths in Abraka. Nonetheless, future studies should address some limitations, such as examining the prevalence and predictors of recreational drug use in a more diverse demographic, including various age groups and gender representations, and reducing reliance on self-reported data regarding drug use behaviors and related health issues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".