Table 6.
SN | Authors | Methodology description | Findings | Key strengths and limitations | Quality score | |||||
---|---|---|---|---|---|---|---|---|---|---|
Study design | Sample size (n) | Continent/country | Age range | SES measure | Methodology | |||||
1 | Simetin et al. (2013) | Cross-sectional | 1,601 | Croatia | 15 years | SES | Multi-level logistic regression | Adolescents from high SES backgrounds had a higher likelihood of cannabis consumption (OR: 1.49; SE: 0.22) compared to those from low SES. | High-SES adolescents have more disposable income, making cannabis and other drugs easier to afford. However, the association between socioeconomic factors and risk behaviors may be influenced by adolescents’ relative resilience to socioeconomic inequalities | 8 |
2 | Doku et al. (2012) | Cross-sectional | 1,195 | Ghana | 12–18 years | SES | Logistic regression | Adolescents from low parental SES were more likely to use marijuana (OR: 12.4, 95% CI: 3.7–41.0) and illicit drugs (OR: 15.9, 95% CI: 3.7–67.8) than those from high parental SES. | Economic pressures can increase teenage stress and anxiety. They may be more tempted to utilize drugs. However, data was collected using self-report measures and utilized a cross-sectional research design. So, it cannot establish a causal association and there might be a chance of biases in the findings. | 7 |
3 | Lee et al. (2018) | Longitudinal | 3,395 | USA | 12–16 years | Parental education | Adolescents with lower parental education were more likely to use illicit drugs (β: 0.08, 95% CI: 0.004–0.158) compared to those with higher parental education | Inequality in information and peer pressure enhance illicit drug use. However, the findings were distorted due to the measurement bias. | 9 |