Risk and Protective Factors in Substance Abuse: Systematic Literature Review - Widyarini, Nurlaela; Utama, J. Seno Aditya (Personifikasi: Jurnal Ilmu Psikologi, 2025)
Substance abuse among adolescents and young adults is a significant global public health concern with complex consequences. Understanding the interplay between risk and protective factors is vital for developing effective prevention and intervention strategies. This systematic review aims to synthesize knowledge on these factors across diverse cultural contexts. Adhering to PRISMA guidelines, a systematic literature search was performed in four databases: PubMed, Scopus, PsycINFO, and Web of Science. Keywords related to substance abuse, risk and protective factors, and relevant populations were used, focusing on studies published between 2014 and 2023 involving adolescents and young adults with either quantitative or qualitative designs. From an initial pool of 3,152 articles, 36 studies met the inclusion criteria and underwent thematic analysis. The findings reveal significant interacting risk factors: social and environmental risks, including permissive peer influences, high-risk settings, and substance availability; familial risks, such as lack of parental supervision and unstable family dynamics; and psychological risks, such as sensation-seeking, impulsivity, and mental health issues.  Moreover, genetic predispositions interact with environmental exposures. Protective factors, such as strong family bonds, positive peer relations, resilience, prosocial behaviours, and community support, mitigate these risks. The review’s findings are aligned with Social Influence, Attachment, and Sensation-Seeking and Impulsivity theories, emphasizing the complex dynamics between risks and protective factors. While protective factors counter risks, the intricate interactions necessitate addressing multiple influences concurrently. The limitations of cross-sectional studies underscore the need for longitudinal research, exploring temporal and causal pathways within diverse populations using robust frameworks.