Facility-Based Focus Group Exploration of Psychoactive Substance Use
Abstract:
The abuse of psychoactive substances significantly impacts individual behavior and perception, posing a substantial public health challenge, particularly in psychiatric hospitals, and negatively affecting treatment outcomes. This study employs a facility-based, cross-sectional design utilizing focus group discussions to gain insights into attitudes, beliefs, and practices. The study examined subjects' awareness of substance use, its consequences, and the relationship between psychoactive substance use and academic attainment. The results are as follows: N = 55; 76.4% (n = 44) are male and 23.6% (n = 23) are female. The mean age is 30.87 years with a standard deviation of 8.25. The modal age of onset for substance use is 17 years, with a mean of 18.18 and a standard deviation of 7.58. The presence of mental illness resulting from psychoactive substance use was observed in 58.2% (n = 32) of cases. The educational status of subjects was significantly lower than that of their parents, with Pearson X² = 49.8, df = 24, and p = 0.001 with a 95% confidence interval. The majority of participants indicated that they commenced substance use in schools, and the behavior continued despite awareness of the consequences, as evidenced by 94%. Consequently, educational institutions should implement extensive substance use preventive strategies, such as mandatory drug use screening prior to university admission, regular random drug testing within the university premises, and zero tolerance to substance-indulging behaviors.References:
[1]. NIDA, 2020, Drugs, Brain, Behavior: The Science of Addiction. Sci Addict [Accessed 10/9/2022]. 2020;7(3):1–32. Available from: https://www.drugabuse.gov/publications/drugs-brains-behavior-science-addiction/drugs-brain
[2]. Janik, P., et al., 2017, M. “Categorization of psychoactive substances into ‘hard drugs’ and ‘soft drugs’: a critical review of terminology used in current scientific literature,” Am. J. Drug Alcohol Abuse, 43 (6), 636–646, Doi: 10.1080/00952990.2017.1335736.
[3]. Anghel, C., & Baconi, D.,.2023 “Understanding the Mechanisms of Action and Effects of Drugs of Abuse,” Mol. Basel Switz. 28 (13) 4969. Doi: 10.3390/molecules28134969.
[4]. Nawi, A., M., et al., 2021 “Risk and protective factors of drug abuse among adolescents: a systematic review,” BMC Public Health. 21(1) 2088. Doi: 10.1186/s12889-021-11906-2.
[5]. Jatau, A. I., et al., 2021, The Burden of Drug Abuse in Nigeria: A Scoping Review of Epidemiological Studies and Drug Laws. Public Health Rev. 42(January):1–11.
[6]. Goldstein, R. Z., & Volkow, N, D., 2011, Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat. Rev. Neuroscience. 12 (11) 652–669. Doi: 10.1038/nrn3119.
[7]. Bakhshani. N. M., 2014, Impulsivity: a predisposition toward risky behaviors,” Int. J. High Risk Behavior. Addict. 3 (2) 20428. Doi: 10.5812/ijhrba.20428.
[8]. Chuang. W. I., et al., 2017, Impulsivity and history of behavioral addictions are associated with drug use in adolescents. Addict. Behavior. Vol 74, pp. 41–47. Doi: 10.1016/j.addbeh.2017.05.021.
[9]. Zubairu, I., 2017, Sexual and Reproductive Behavior of HIV-positive Men and the Response of the Health Care Service: A Mixed Methods Study in Kano, Northern Nigeria.
[10]. Bhattacharjee, D., 2024, Knowledge, attitude, and practice of adolescents on psychoactive substance addiction: a survey in Jharkhand, India. J. Ment. Health Behavior Sci. M. 2(1) 1-8. Doi: 10.61577/jmhbs.2024.100001.
[11]. Chen, C. Y., et al., 2009, Early-onset drug use and risk for drug dependence problems, Addict. Behavior. 34 (3) 319–322. Doi: 10.1016/j.addbeh.2008.10.021.
[12]. Perino, J., et al., 2022, Psychoactive substance use among students: A cross‐sectional analysis. Fundamental Clin. Pharmacology. 36 (5) 908–914. Doi: 10.1111/fcp.12771.
[13]. Casey, B. J., et al., 2018, The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites. Dev. Cognition Neuroscience. 32() 43–54. Doi: 10.1016/j.dcn.2018.03.001.
[14]. Zilverstand, A., & Goldstein, R. Z., 2020, Dual models of drug addiction: the impaired response inhibition and salience attribution model. Elsevier Journal Cognition and Addiction. Chapter 3 pp. 17–23, ISBN 9780128152980, https://doi.org/10.1016/B978-0-12-815298-0.00003-4
[15]. Dresp-Langley B., & Hutt, A., 2022, Digital Addiction and Sleep. Int. J. Environ. Res. Public. Health. 19 (11) 6910. Doi: 10.3390/ijerph19116910.
[16]. Union E., 2019, Drug Use Survey in Nigeria. UNODC J [Accessed 4/30/2023]. 2019;1–40. Available from: unodc-pdmu@un.org
[17]. Bhondoekhan, F., et al., 2023, The impact of polysubstance use patterns on engagement of substance use disorder treatment among emergency department patients at high risk of opioid overdose. Addict. Behavior. Rep. 18 p.100512. Doi: 10.1016/j.abrep.2023.100512.
[18]. Caron, R. M., et al., 2024, Health Promotion, Health Protection, and Disease Prevention: Challenges and Opportunities in a Dynamic Landscape. AJPM Focus. 3 (1) 100167. Doi: 10.1016/j.focus.2023.100167.
[19]. Agwogie, M. O., & Kliewer, W., 2024. Parenting and other potential protective factors associated with polysubstance use among public school students in Lagos, Nigeria. Int. J. Psychol. 59 (3) 432–440. Doi: 10.1002/ijop.13122.
[20]. Rogowska, A. M., 2016, Problematic use of psychoactive substances in undergraduates: a comparison of four patterns of substance use. J. Subst. Use. 21(3)304–308. Doi: 10.3109/14659891.2015.1021865.
[21]. AbdulRaheem, Y., 2023, Unveiling the Significance and Challenges of Integrating Prevention Levels in Healthcare Practice. J. Prim. Care Community Health. 14(1) 1-6. Doi: 10.1177/21501319231186500.
