Skip to main content

Cognitive dysfunction in adolescents with substance use disorder



Substance abuse is a major health problem, associated with multiple clinical correlates. Cognitive dysfunctions were among the most relevant health problems associated with substance abuse among adolescents. The aim of the study is investigate the main cognitive domains affected in a sample of adolescents with substance use disorders. A case-control comparison was performed between 100 substance abusers versus 40 controls. The Mini-International Neuropsychiatric Interview v.5, Addiction Severity Index, Wisconsin Card Sorting Test, socioeconomic scale, and multiple historical variables investigated.


Substance abusers showed higher mean than control as regard all other WCST domains. The difference between two groups was statistically significant. Cannabis substance mostly affects early conceptualization and problem-solving abilities, while inhalants affect predominantly sustained attention, and alcohol mostly affect cognitive flexibility. Polysubstance use is more harmful to most of the executive function domain than mono substance use.


The substance use disorders are a major health problem accompanied cognitive dysfunction among adolescents and associated with increased rates of executive dysfunction. Cognitive flexibility, sustained attention, problem-solving abilities, and early conceptualization are the most domains affected.


Adolescence had a vulnerable developmental time where important changes take place in young cases’s bodies, brains, and sociocultural environments, perhaps making them more susceptible to substance use and psychiatric comorbidity [1]. According to numerous studies, the majority of individuals who eventually start using drugs or alcohol did it when they were still teenagers [2].

During youth, early adulthood, cases had most prone to start abusing substances, including alcohol, illegal narcotics, and prescription medicines. By the time they had been seniors, about 70% of high school kids would had tried alcohol, 50% would had used illegal drugs, and more than 20% would had used prescription medications for purposes other than those prescribed [3].

Biologically, the teenage years are a critical window of vulnerability to drug abuse, because the brain is still developing and malleable (a property known as neuroplasticity), and some brain areas are less mature than others. The parts of the brain that process feelings of reward and pain, crucial drivers of drug use, are the first to mature during childhood. What remains incompletely developed during the teen years are the PFC and its connections to other brain regions. PFC is responsible for assessing situations, making sound decisions, and controlling our emotions and impulses; typically, this circuitry is not mature until a person is in his or her mid-20s [4].

Substance abuse has a major impact on individuals, families, and communities as its effects are cumulative, contributing to costly social, physical, and mental health problems. Substance use often initiates during adolescence, and over 80% of drug users began using during adolescence [5].

The substance use disorders are a major health problem among youth, and it is more prevalent in male sex in Egyptian population. Tramadol dependency is at the top of all substances abused in Egypt, followed by polysubstances. Smoking, cannabis, and opiate are the most prevalent types [6]. Smoking, cannabis, and opiates are more frequent, and polysubstance use is much common worldwide [7].

Substance exposure during adolescence may adversely affect cognitive functioning, as measured by neuropsychological tests and functional neuroimaging tasks. Adolescent alcohol and marijuana users have poorer performance on working memory, verbal learning and memory, visuospatial functioning, and psychometric motor speed tasks, and poorer performance has been observed with higher doses and an earlier age of onset [8, 9]. Moreover, marijuana users appear to suffer additional attentional deficits [10], and the cognitive deficits may be sustained in chronic users [11].

There had many different estimates that range from roughly 30–80% of cases with substance use disorders who had cognitive impairment. These deficiencies could be as mild as the brief effects of cannabis use or as severe as the moderate executive control deficits seen in long-term cocaine users, even after several months of abstinence. These estimates include the long-term visuospatial information processing abnormalities found in non-demented individuals with alcohol use disorders, even if they do not include alcoholics who had permanent deficits such Wernicke-Korsakoff syndrome [12].

Recent studies had found deficiencies in a variety of functions, including learning, memory, executive functioning, problem-solving, visuospatial, verbal ability, speed of information processing, connected to excessive alcohol, and other substance use problems [13, 14]. Additionally, polysubstance use disorder had linked to widespread deficits, critical deficiencies on neuropsychological tests of working memory, inhibition, flexibility, self-regulation, and decision-making had been described [15].


This case-control study had carried out on 100 cases (as case group) who attended the Suez Canal University Hospital, Addiction Centers and Clinics in the Suez Canal region. They had been evaluated, after meeting inclusion criteria between October 2019 and December 2021, with 40 healthy control subjects (as control group) chosen from the healthy blood donors who had matched to the case group in terms of sociodemographic data.

The study included cases between the ages of 13 to 19 who had of either gender and had substance use disorders diagnosed in accordance with the International Classification of Diseases (ICD-10) criteria. Cases with neurodevelopmental disorders, epilepsy, severe head trauma, neurologic deficits, sensory deficits such as hearing or vision loss, low IQ, had intoxicated, or had undergone withdrawal had not been included.

Each participant in the study underwent the following:

  • A full thorough psychiatric sheet including sociodemographic information

  • Full physical and neurological testing to rule out organic or neurological comorbidities

  • A structured interview conducted by a psychiatrist using the Arabic version of the Mini-International Neuropsychiatric Interview v.5 (M.I.N.I. child) [16, 17].

  • Testing for urine toxicity both during and after detoxification

  • Psychometric evaluation

Teen-addiction severity index

It had a structured, objective face-to-face interview that allowed the assessor to comment, including confidence ratings to show whether the information might be misinterpreted as well as severity ratings (indicating how severe the assessor believes had the need for treatment or counseling). Chemical usage, school performance, employment, support, family ties, peer, social interactions, legal status (involvement with criminal justice programme), mental health status, and a list of contacts for more information are among the issues that had been assessed [18].

It was translated into Arabic by official office. The Arabic draft was translated into English again.

The back-translated version was compared with the original English version to verify that the questions were properly translated. All of the back-translated items were worded similarly to the original ones. Under the direction of the research supervisors, a pilot study with a sample of adolescents had been conducted.

El-Gilany et al. socioeconomic’s scale

The occupation domain, education domain, home sanitation domain, family possessions domain, family domain, economic domain, and healthcare domain made comprised the socioeconomic rating in this study sample [19].

The Wisconsin Card Sorting Test

The test could be given to individuals between the ages of 6.5 and 89; it makes use of several abilities, such as attention, working memory, and visual processing. It had been used to assess a person’s proficiency in abstract reasoning as well as their capacity to switch up their problem-solving methods when necessary.

The WCST consists of 128 response cards, four stimulus cards with variously shaped shapes (crosses, circles, triangles, or stars), colours (red, blue, green, or yellow), and numbers on them (one, two, three, or four). Before the subject, on the table, are the four stimulus cards [20].

Following WCST scoring, the following domains had been offered:

  • The total number of trials conducted

  • Number of categories completed

  • Tries to successfully finish first category

  • Perseverative response

  • Error numbers

  • Non-perseverative errors and failure to maintain set

Statistical analysis

The statistical analysis of data was done by using Excel programme for figures, SPSS (SPSS, Inc., Chicago, IL, USA) program, and Statistical Package for Social Science version 16. To test the normality of data distribution, K-S (Kolmogorov-Smirnov) test had been done. Only critical data revealed to be nonparametric. N.B: All tested data revealed to be parametric. One-way analysis of variance (ANOVA) was used to explore group differences in age, years of education, and other variables when appropriate in subsequent analysis. Group differences regarding gender were examined using ×2 analysis.

Group differences on the subscale scores were examined using a multivariate analysis of covariance (MANCOVA), including years of education and economic subscales as covariates. Group differences on the WCST were analysed using univariate ANOVAs. In all these comparisons, we conducted post hoc one-way ANOVAs or Mann-Whitney tests to examine possible differences between subgroups of adolescents with substance use disorder classified according to their primary drug of choice. We conducted three multiple regression analyses to examine the predictive effects of severity of addiction (as measured by the teen addiction severity index subscales) on WCST scales scores. p-value had been critical if ≤ 0.05.


The study, which involved 100 adolescent substance users who attended the psychiatric clinic as previously described and 40 matched healthy adolescents who underwent comprehensive evaluations and psychometric assessments using the aforementioned methods, produced the following findings:

  • The difference between two groups had no statistical significance regarding father and mothers’ education, daily income, socioeconomic scale, residency, and religion as shown in Table 1.

  • There is lower mean than control as regard number of category completed (reflect the overall efficiency in the test performance), while they showed higher mean than control as regard all other WCST domains. The difference between two groups had statistically significance (p = 0.05) as shown in Table 2.

  • The mono and polysubstance case groups had lower mean than control group as regard number of category completed and higher mean than control group as regard other WCST domains, and the difference between mono and polysubstance users’cases and control groups had statistically significance (p = 0.05). Polysubstance use case group shows higher mean than mono substance use group as regard number of perseverative errors; the difference between two groups had statistically significance (p = 0.003). Polysubstance use case groups show higher mean than mono substance use group as regard failure to maintain set, but the difference between two groups had no statistically significance as shown in Table 3.

  • The combined cannabis use group had lower mean than non-cannabis use group and control group as regard all domains except failure to maintain set, and the difference had statistically significance (p = 0.05) which means that cannabis use might affect the executive function domains except sustained attention as shown in Table 4.

  • The mono alcohol use group showed a higher mean than control, non-alcohol use group as regard number of perseverative errors, and the difference had statistically significance (p = 0.029) which means that alcohol use might affect flexibility domain critical. Mono alcohol use control groups showed a lower mean than combined alcohol use group and in non-alcohol user group as regard total number of errors; the difference had been statistically critical p = 0. 038. Mono, combined, and non-alcohol use groups show lower mean than control groups as regard number of category completed and higher mean than control as regard numbers of trial to first category, and the difference had statistically significance p = 0.05 as shown in Table 5.

  • The combined opioid use group shows a higher mean than control group, non-opioid use group as regard number of perseverative response, total number of errors, and the difference had statistically significance (p = 0.039) and (p = 0.05), respectively, which means that opioid use impairs flexibility critical. Combined opioid and non-opioid use groups show a lower mean than control group as regard number of category completed, and the difference had statistically significance p = 0.043. Combined opioid and non-opioid use groups show a higher mean than control group as regard number of perseverative errors, failure to maintain set, and trials to first category, but it had no statistically significance as shown in Table 6.

  • The combined benzodiazepine use group shows a lower mean than non-benzodiazepine use group as regard number of perseverative errors, and the difference had statistically significance p = 0.01. Combined benzodiazepine use groups show a lower mean than control group as regard number category completed, higher mean than control group as regard number of non-perseverative errors, trials to first category, and the difference had statistically significance p = 0.05 as shown in Table 7.

  • The combined inhalant use group shows lower mean than control group, non-inhalant use group as regard number of category completed, and the difference had statistically significance p = 0.034. Combined inhalant use group shows higher mean than control, non-inhalants use groups as regard trial to first category, failure to maintain set, total number of errors, number of perseverative errors, number of perseverative responses, and the difference had statistically significance p = 0.05, which means that inhalant’s use impairs early conceptualization and sustained attention and flexibility domains. Combined inhalant use group shows higher mean than control and non-inhalants use groups as regard number of non-perseverative errors, but the difference had no statistically significance as shown in Table 8.

Table 1 Sociodemographic variables
Table 2 Comparison between cases and control group regarding the WCST domains
Table 3 Comparison between mono and polysubstance use groups with control group regarding WCST domains
Table 4 Comparison between combined cannabis and non-cannabis use cases with control group regarding WCST domains
Table 5 Comparison between alcohol, combined alcohol, and non-alcohol use groups with control group regarding WCST domains
Table 6 Comparison between mono opioid, combined opioid, and non-opioid use groups with control group regarding WCST domains
Table 7 Comparison between combined benzodiazepine and non-benzodiazepine use groups with control group regarding WCST domains
Table 8 Comparison between combined inhalants and non-inhalants use groups with control group regarding WCST domains


The study, conducted in 2021 at the Faculty of Medicine Suez Canal University Hospital, the psychiatric hospitals, Clinics of the Suez Canal regional area, examined the relationship between substance use and executive function in a sample of adolescents who had been mostly from the same cultural background and who did not had developmental or psychological delays. Toxicology screening, semi-structured interviews (mini-kid), the Teen Addiction Severity Index scale, the WCST, and a social classification scale had all been performed on the 140 cases we evaluated, who had split into two groups of 100 cases and 40 controls.

In this investigation, there had no discernible difference in the sociodemographic characteristics of the cases and the control group.

In all WCST domains, our investigation discovered a substantial difference between the case and control groups. On the basis of our findings, the majority of research conducted to evaluate this issue, including those conducted in Spain [21,22,23], the USA [24], 2011, and Brazil [25], reached to the same conclusion: there had been a global decline in executive function related to substance use. Adolescent substance use might had a negative impact on performance as determined by neuropsychological testing and functional neuroimaging activities [8].

This conclusion might be explained by the fact that altered function, including changes in the well-known “executive” domains of attention, inhibition/regulation, working memory, and decision-making, had a defining characteristic of substance use disorders. It had been acknowledged that a fundamental impairment in addiction, a potentially critical target for intervention, had poor (sometimes referred to as “top down”) regulation of downstream motivational processes, whether appetitive (reward, incentive salience) or aversive (stress, negative affect) [26].

In this study, polydrug use impaired executive functions in the majority of domains more than mono substance use, which had been consistent with research from Meyerhoff [27], Gustavson [28], Schmidt et al. [29], Formiga et al. (2001), and studies from San Francisco, Brazil [30], while this could be explained biologically and socially, it had been challenging to compare or assess substance use patterns across cases with various backgrounds.

Due to the short sample size, lack of cases who only used cannabis at the time of the trial, there had been no cases who only used cannabis. Cannabis use critically affects all executive function domains, as demonstrated by studies conducted in the Netherlands by Jager et al. [31], Boston by Dahlgren et al. [32], and in Israel by Cohen K., Weinstein [33]; more specifically, it critical affects adolescents’ working memory and flexibility, as demonstrated by Morinet al [34].. Block et al. [35] also found this in his study using a sample of Europeans and Americans, respectively. This conclusion had backed by convergent evidence from structural neuroimaging studies, which show that regular cannabis use had linked to neuronal changes in a number of areas of the brain that had been important for working memory, including a shrinkage of the hippocampus and amygdala. These changes also had a relationship with the quantity of cannabis use dependence [36].

The flexibility and initial conceptualization of the adolescent cases had been critically impacted by alcohol use in our study, which had been consistent with Sanhueza et al. [37]’s findings in a related study conducted in Madrid. Powell et al. [38]’s mega study, however, found that alcohol had an impact on every domain of the executive functions; this might be explained by the smaller sample size. Numerous studies revealed that heavy drinkers had lower cerebellar activity in response to a reward processing test (wheel of fortune), frontal, parietal brain activation in response to inhibition, and working memory tasks [39, 40].

In line with research conducted in Egypt by Bassiony et al. [41] and Tehran by Rezapour et al. [42], opioid usage severely impacted executive functioning in our study, particularly flexibility [42]. Although other studies conducted in China by Li et al. [43], Germany by Brand et al. [44], Florida by Valdes, Lunsford [45], Finland by Rapeli et al. [46], and Finland by Brand et al. [44] did not arrive at the same precise results, this had likely because they used different psychometric tools for evaluating the executive functions. This had been explained by research that shows how opiates cause atrophy, apoptosis by upregulating GDNF, downregulating apoptotic markers including Caspase 3 and 8, and inducing pro-inflammatory indicators.

Additionally, it causes prefrontal cortex neuronal loss, microgliosis, and astrogliosis. Other negative effects of opiate use include behavioural disruption and impairment. Overall, opiate use led to the activation of the neuroinflammatory response, which in turn caused neurodegeneration in the prefrontal cortex [47].

In line with research conducted in Italy by Federico et al., benzos usage in this study adversely impacted executive functioning, particularly flexibility and problem-solving skills [48]. Despite the fact that studies conducted in Bangladesh by Chowdhury et al. [49] and Mexico by Contreras-González et al. [49], it indicated that benzodiazepines influence all domains of executive function.

This study found that inhalant use considerably affected executive functions, which had been consistent with research from studies conducted in Australia, the USA, Turkey, and Mexico. These investigations found that inhalant use critical affected all domains of executive function. Recent research on the executive functioning of inhalant users had found impairments in information processing speed, self-monitoring, visual, motor speed, working memory, psychomotor function, and spatial problem-solving [50, 51].


Adolescents’ substance use problems had a serious health issue that had also accompanied by impairment. Cannabis had the greatest impact on early conceptualization and problem-solving skills, whereas alcohol and inhalants mostly impair flexibility and sustained attention, respectively. Contrary to mono substance use, polysubstance use had been more detrimental to the majority of the executive function area.

Availability of data and materials

Available data and material.



International Classification of Diseases


The Wisconsin Card Sorting Test

M.I.N.I. kid:

The Mini-International Neuropsychiatric Interview v.5


  1. Storr CL, Pacek LR, Martins SS (2012) Substance use disorders, adolescent psychopathology. Public Health Rev 34(2):1–42

    Article  Google Scholar 

  2. Gutierrez A, Sher L (2015) Alcohol, drug use among adolescents: an educational overview. Int J Adolesc Med Health 27(2):207–212

    Article  Google Scholar 

  3. Terry-McElrath YM, O’Malley PM, Johnston LD (2013) Simultaneous alcohol, marijuana use among US high school seniors from 1976 to 2011: trends, reasons, situations. Drug Alcohol Depend 133(1):71–79

    Article  Google Scholar 

  4. Robertson EB, David SL, Rao SA (2003) Preventing drug use among children and adolescents: a research-based guide for parents, educators, and community leaders, 2nd ed. NIH Pub. No. 04-4212(A). National Institute on Drug Abuse, Bethesda Available at:

    Google Scholar 

  5. Das JK, Salam RA, Arshad A, Finkelstein Y, Zulfiqar A (2016) Bhutta. Interventions for adolescent substance abuse: an overview of systematic reviews. J Adolesc Health 59(4 Suppl):S61–S75

    Article  Google Scholar 

  6. El-Awady SA, Elsheshtawy EA, Elbahaey WA, Elboraie OA (2017) Impact of familial risk factors on the severity of addiction in a sample of Egyptian adolescents. Egypt J Psychiatr 38(2):70–78

    Article  Google Scholar 

  7. Jessica A, Kims. (2019) Grisworld. Adolescent substance use and misuse: recognition and management. Am Fam Physician 99(11):689–696

    Google Scholar 

  8. Nguyen-Louie TT, Castro N, Matt GE, Squeglia LM, Brumback T, Tapert SF (2015) Effects of emerging alcohol and marijuana use behaviors on adolescents' neuropsychological functioning over four years. J Stud Alcohol Drugs 76:738–748

    Article  Google Scholar 

  9. Ganzer F, Broning S, Kraft S, Sack PM, Thomasius R (2016) Weighing the evidence: a systematic review on long-term neurocognitive effects of cannabis use in abstinent adolescents and adults. Neuropsychol Rev 26:186–222

    Article  Google Scholar 

  10. Randolph K, Turull P, Margolis A, Tau G (2013) Cannabis and cognitive systems in adolescents. Adolesc Psychiatry 3(2):135–147 Ref Type: Journal (Full)

    Article  Google Scholar 

  11. Renard J, Krebs MO, Le PG, Jay TM (2014) Long-term consequences of adolescent cannabinoid exposure in adult psychopathology. Front Neurosci 8:361

    Article  Google Scholar 

  12. Copersino ML, Fals-Stewart W, Fitzmaurice G, Schretlen DJ, Sokoloff J, Weiss RD (2009) Rapid screening of cases with substance use disorders. Exp Clin Psychopharmacol 17(5):337

    Article  Google Scholar 

  13. Gonzalez R (2007) Acute, non-acute effects of cannabis on brain functioning, neuropsychological performance. Neuropsychol Rev 17(3):347–361

    Article  Google Scholar 

  14. Gruber SA, Silveri MM, Yurgelun-Todd DA (2007) Neuropsychological consequences of opiate use. Neuropsychol Rev 17(3):299–315

    Article  Google Scholar 

  15. Moreno-López L, Stamatakis EA, Fernández-Serrano MJ, Gómez-Rio M, Rodríguez-Fernández A, Pérez-García M, Verdejo-García A (2012) Neural correlates of hot, cold executive functions in polysubstance addiction: association between neuropsychological performance, resting brain metabolism as measured by positron emission tomography. Psychiatry Res Neuroimaging 203(2-3):214–221

    Article  Google Scholar 

  16. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, Hergueta T, Baker R, Dunbar GC (1998) The Mini-International Neuropsychiatric Interview (MINI): the development, validation of a structured diagnostic psychiatric interview for DSM-IV, ICD-10. J Clin Psychiatry 59(20):22–33

    Google Scholar 

  17. Ghanem M, Ibrahim M, Elbehery A, Elmerghany H (2000) The translation group of the Arabic version of the Mini International Neuropsychiatric Interview for Children (MINI-Kid) by Sheehan DV et al, 1998. Department of Neuropsychiatry Ain Shams University

    Google Scholar 

  18. Kaminer Y, Wagner E, Plummer B, Seifer R (1993) Validation of the teen addiction severity index (T-ASI): preliminary findings. Am J Addict 2(3):250–254

    Google Scholar 

  19. El-Gilany A, El-Wehady A, El-Wasify M (2012) Updating and validation of the socioeconomic status scale for health research in Egypt. East Mediterr Health J 18(9)

  20. Romine CB, Lee D, Wolfe ME, Homack S, George C, Riccio CA (2004) Wisconsin Card Sorting Test with children: a meta-analytic study of sensitivity, specificity. Arch Clin Neuropsychol 19(8):1027–1041

    Article  Google Scholar 

  21. Verdejo-Garcia AJ, López-Torrecillas F, Aguilar de Arcos F, Perez-Garcia M (2005) Differential effects of MDMA, cocaine, cannabis use severity on distinctive components of the executive functions in polysubstance users: a multiple regression analysis. Addict Behav 30(1):89–101

    Article  Google Scholar 

  22. Verdejo-García A, Rivas-Pérez C, López-Torrecillas F, Pérez-García M (2006) Differential impact of severity of drug use on frontal behavioral symptoms. Addict Behav 31(8):1373–1382

    Article  Google Scholar 

  23. Fernández-Serrano MJ, Pérez-García M, Schmidt Río-Valle J, Verdejo-García A (2009) Neuropsychological consequences of alcohol, drug abuse on different components of executive functions. J Psychopharmacol 24(9):1317–1332

    Article  Google Scholar 

  24. Crean RD, Crane NA, Mason BJ (2011) An evidence based review of acute, long-term effects of cannabis use on executive functions. J Addict Med 5(1):1–8

    Article  Google Scholar 

  25. Formiga MB, Galdino MK, Vasconcelos SC, Neves JW, Lima MD (2021) Executive functions and emotion regulation in substance use disorder. J Bras Psiquiatr 70:236

  26. Tatiana RS, Regier PS (2018) Cognitive impairment in substance use disorders. CNS Spectrums 1–12

  27. Meyerhoff DJ (2016) Multimodal Magnetic Resonance Neuroimaging and Cognition in Polysubstance Users. InNeuropathology of Drug Addictions and Substance Misuse (pp. 872-883). Academic Press.

  28. Gustavson DE, Stallings MC, Corley RP, Miyake A, Hewitt JK, Friedman NP (2017) Executive functions, substance use: relations in late adolescence, early adulthood. J Abnorm Psychol 126(2):257

    Article  Google Scholar 

  29. Schmidt TP, Pennington DL, Cardoos SL, Durazzo TC, Meyerhoff DJ (2017) Neurocognition, inhibitory control in polysubstance use disorders: comparison with alcohol use disorders, changes with abstinence. J Clin Exp Neuropsychol 39(1):22–34

    Article  Google Scholar 

  30. Formiga MB, Galdino MK, Vasconcelos SC, Neves JW, Lima MD (2021) Executive functions, emotion regulation in substance use disorder. J Brasileiro de Psiquiatria 70:236

    Article  Google Scholar 

  31. Jager G, Kahn RS, Van Den Brink W, Van Ree JM, Ramsey NF (2006) Long-term effects of frequent cannabis use on working memory, attention: an fMRI study. Psychopharmacology 185(3):358–368

    Article  CAS  Google Scholar 

  32. Dahlgren MK, Sagar KA, Racine MT, Dreman MW, Gruber SA (2016) Marijuana use predicts performance on tasks of executive function. J Stud Alcohol Drugs 77(2):298–308

    Article  Google Scholar 

  33. Cohen K, Weinstein A (2018) The effects of cannabinoids on executive functions: evidence from cannabis, synthetic cannabinoids—a systematic review. Brain Sci 8(3):40

    Article  Google Scholar 

  34. Morin JF, Afzali MH, Bourque J, Stewart SH, Séguin JR, O’Leary-Barrett M, Conrod PJ (2019) A population-based analysis of the relationship between substance use, adolescent development. Am J Psychiatr 176(2):98–106

    Article  Google Scholar 

  35. Block RI, Jager G, Luijten M, Ramsey NF (2022) Associations of regular marijuana use by adolescent boys with verbal memory, perseveration. Psychol Rep 125(2):839–861

    Article  Google Scholar 

  36. Cousijn J, Wiers RW, Ridderinkhof KR, van den Brink W, Veltman DJ, Goudriaan AE (2012) Grey matter alterations associated with cannabis use: results of a VBM study in heavy cannabis users, healthy controls. Neuroimage. 59:3845–3851

    Article  Google Scholar 

  37. Sanhueza C, García-Moreno LM, Expósito J (2011) Weekend alcoholism in youth, neuroaging. Psicothema. 31:209–214

    Google Scholar 

  38. Powell A, Sumnall H, Kullu C, Owens L, Montgomery C (2021) Subjective executive function deficits in hazardous alcohol drinkers. J Psychopharmacol 35(11):1375–1385

    Article  CAS  Google Scholar 

  39. Squeglia LM, Pulido C, Wetherill RR, Jacobus J, Brown GG, Tapert SF (2012) Brain response to working memory over three years of adolescence: influence of initiating heavy drinking. J Stud Alcohol Drugs 73:749–760

    Article  Google Scholar 

  40. Cservenka A, Jones SA, Nagel BJ (2015) Reduced cerebellar brain activity during reward processing in adolescent binge drinkers. Dev Cogn Neurosci 16:110–120

    Article  Google Scholar 

  41. Bassiony MM, Youssef UM, Hassan MS, El-Deen GM, El-Gohari H, Abdelghani M, Abdalla A, Ibrahim DH (2017) Impairment, tramadol dependence. J Clin Psychopharmacol 37(1):61–66

    Article  CAS  Google Scholar 

  42. Rezapour T, Hatami J, Farhoudian A, Noroozi A, Daneshmand R, Sofuoglu M, Baldacchino A, Ekhtiari H (2021) Baseline executive functions, receiving rehabilitation could predict treatment response in cases with opioid use disorder. J Subst Abus Treat 131:108558

    Article  CAS  Google Scholar 

  43. Li J, Weidacker K, Mandali A, Zhang Y, Whiteford S, Ren Q, Zhou Z, Zhou H, Jiang H, Du J, Zhang C (2021) Impulsivity, craving in subjects with opioid use disorder on methadone maintenance treatment. Drug Alcohol Depend 219:108483

    Article  CAS  Google Scholar 

  44. Brand M, Roth-Bauer M, Driessen M, Markowitsch HJ (2008) Executive functions, risky decision-making in cases with opiate dependence. Drug Alcohol Depend 97(1-2):64–72

    Article  Google Scholar 

  45. Valdes K, Lunsford D (2021) Executive functioning of individuals with substance use disorder. Ann Int Occup Ther 4(4):e220–e227

    Article  Google Scholar 

  46. Rapeli P, Kivisaari R, Autti T, Kähkönen S, Puuskari V, Jokela O, Kalska H (2006) Cognitive function during early abstinence from opioid dependence: a comparison to age, gender, and verbal intelligence matched controls. Bmc Psychiatry 6(1):1–0

  47. Aghajanpour F, Boroujeni ME, Jahanian A, Soltani R, Ezi S, Khatmi A, Mohammad-Amin et al (2020) Tramadol: a potential neurotoxic agent affecting prefrontal cortices in adult Male Rats, PC-12 Cell Line. Neurotox Res 38:385–397

    Article  CAS  Google Scholar 

  48. Federico A, Tamburin S, Maier A, Faccini M, Casari R, Morbioli L, Lugoboni F (2017) Multifocal dysfunction in high-dose benzodiazepine users: a cross-sectional study. Neurol Sci 38(1):137–142

    Article  Google Scholar 

  49. Chowdhury ZS, Morshed MM, Shahriar M, Bhuiyan MA, Islam SM, Bin Sayeed MS (2016) The effect of chronic alprazolam intake on memory, attention, and psychomotor performance in healthy human male volunteers. Behav Neurol 2016

  50. Marín-Navarrete R, Toledo-Fernández A, Villalobos-Gallegos L, Pérez-López A, Medina-Mora ME (2018) Neuropsychiatric characterization of individuals with inhalant use disorder, polysubstance use according to latent profiles of executive functioning. Drug Alcohol Depend 190:104–111

    Article  Google Scholar 

  51. Dingwall KM, Maruff P, Fredrickson A, Cairney S (2011) Recovery during, after treatment for volatile solvent abuse. e. Drug Alcohol Depend 118(2-3):180–185

    Article  Google Scholar 

Download references


Delighted to appreciate all subjects who participated in the study or withdrawal


Spent by research team.

Author information

Authors and Affiliations



Study conception and design, AA, OY, AT, and HH. Data collection, HH, AA, and HE. Data analysis and interpretation, HH, AA, OY, and HE. Drafting of the article, AA, AT, and HH. Critical revision of the article, AA, AT, OY, and HH. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Haydy Hassan.

Ethics declarations

Ethics approval and consent to participate

An informed permission taken from the Medical Ethical Committee, Number: 3684 (30/8/2018). Consent from the case or the case legal guardian as cases had still minors taken at the beginning of the study based on information given about the nature of the study.

Consent for publication

Oral consent from the study subjects had been obtained for publication.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abdulaal, A., El Tantawy, A., Ibrahim, O. et al. Cognitive dysfunction in adolescents with substance use disorder. Middle East Curr Psychiatry 30, 13 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: