The following is the unedited copy of a final paper submitted to the Golden Gate University graduate psychology course on research design. The title of this project was “Adult Consequences of Chronic Cannabis Use in Adolescence” and followed the format stipulated in the course.
Researchers in the United States and abroad have conducted studies examining the effects of early adolescent use of cannabis, severity of use, and life outcomes such as the impact of chronic use on later development in adulthood. Negative outcomes such as mental illness have been observed as connected to chronic cannabis use (Galvez-Buccollini et al., 2012). The findings were consistent with showing an increased likelihood of neural damage in chronic cannabis users that would eventually lead to a clinical mental illness. Duration and severity of use are factors in how the human brain is affected in its maturation process (Brook, Lee, Brown, Finch, & Brook, 2011).
The main part of the brain involved in executive tasks is the prefrontal cortex (PFC), which is a region of the brain responsible for executive function. According to neuroscientist Sarah-Jayne Blakemore of the Institute of Cognitive Neuroscience at University College London, the human brain may not be fully mature until age 30 years or older (Edwards, 2010). A fully developed PFC controls emotional traits such as impulse control, long-term planning, organization, complex problem-solving, and decision making. As an individual ages and moves into the life stages associated with adulthood, such as parenthood or increased work responsibilities, their cognitive load increases and it is the PFC which determines their ability to handle the tasks associated with these greater responsibilities.
Adolescence is a critical growth period during which the PFC is in an immature stage of development (Fergusson & Boden, 2008). The introduction of cannabis use between ages 12 to 16 can impair the brain’s ability to grow the neural capacity for reasoning and problem-solving tasks later in life (Samson, 2010). Consequently, individuals are at an increased risk for negative life outcomes associated with poor judgment, lack of psychosocial skills, and risk-taking behavior that results from an underdeveloped PFC. In 1997, the World Health Organization (WHO) report cited recent studies at the time (Fletcher et al., 1996) that found a connection between cannabis use and cognitive impairment. The WHO report (1997) also stated that cannabis use differs by individuals.
The neurotransmitter (NT) responsible for learning and memory is dopamine (DA) (Fergusson & Boden, 2008). It is also involved in cognitive tasks involving motor skills, attention, motivation, and connecting behavior to rewards or understanding consequences. According to the Canadian Institutes of Health Research and Institute of Neuroscience, Mental Health and Addiction (INMHA) (n.d.), the active ingredient of cannabis is called THC, which, when introduced to the brain can adversely affect functions that involve DA. THC binds to the CB1 receptors and reduces the amount of the brain’s natural NTs, which causes users who are “high” to appear lethargic. Because cannabis is an opiate, more DA is released since the drug inhibits the GABA neurons responsible for controlling the amount of DA in the brain. Over the long term a chronic user’s brain will lose CB1 receptors, which leads to decreased blood flow in the brain.
Positron emission tomography (PET) scans conducted by the National Institute on Drug Abuse on light, moderate, and severe long-term cannabis consumers showed varying degrees of reduced brain activity in the CB1 receptors (Medina & Tapert, 2008). Because the adolescent brain has not reached full maturity, the introduction of regular cannabis use appears to arrest brain maturation (Medina & Tapert, 2008). Not only does it lead to drug dependence, but regular cannabis use also appears to result in permanent brain damage. Such individuals have stunted cognitive skills, poor emotional self-regulation, lower quality of life outcomes, and increased risk for mental illness compared to those who have had limited or no exposure to cannabis. Studies conducted by Medina and Tapert (2008) indicated that females had increased risk of damage to their neurocognitive development if they began cannabis use in adolescence. Medina and Tapert presented these findings at the 2008 American Academy of Pediatrics Annual Meeting in Boston in a paper titled “Neuroimaging Marijuana Use and its Effects on Cognitive Function.”
In longitudinal studies, researchers found that chronic cannabis users have twice the risk for clinical depression in adulthood, reduced employment, unsatisfactory relationships, lower levels of education, financial instability, poor coping skills in response to stress, and greater emotional deregulation (Brook, Balka, & Whiteman, 1999; Brook et al., 2011; Fergusson & Boden, 2008; Hyman & Sinha, 2009). The compounding effects of cannabis use and the negative psychosocial outcomes have a correlational link to brain damage suffered from chronic use. Specific negative psychological health outcomes have been observed in recent studies (Brook et al., 2011; Green & Ensminger, 2006; Hall, 2006; Hayatbakhsh et al., 2007). While the Brook et al. (2011) study was limited to African-American and Hispanic populations, the research used the conjecturing model in its longitudinal study to measure and analyzes data. Psychosocial factors such as home life and exposure to criminal behavior or abuse by partners or family members were taken into account. The researchers then examined how external factors in addition to cannabis use lead to antisocial or maladaptive activity. It appears that damage to the PFC, and the lack of ability to perform advanced cognitive tasks resulting from such impairment, may be irreversible after a certain period of time of chronic cannabis use (Brook et al., 2011).
Researchers from Australia, the Netherlands, New Zealand, Sweden, and the United Kingdom have also found increased risk for mental illness, such as psychosis and schizophrenia. The schizophrenia (Andreasson, Allebeck, Engstrom, & Rydberg, 1987) risk was higher among heavy users; the Swedish researchers determined that cannabis was an independent risk factor in the development of schizophrenia and that risk increased along with severity of use. Longitudinal studies by researchers in Germany, the Netherlands, and New Zealand had similar findings of repeated exposure to cannabis and increased likelihood of clinical psychosis and paranoia. Results were obtained in each study even after controlling for confounding variables or threats to internal validity in the respective designs (Hall, 2006). The researchers took into account that individuals with genetic tendencies toward mental illness will have a higher risk of developing psychiatric problems compared to those who do not.
A meta-analysis conducted by the VA Boston Healthcare System recruited 57 sample subjects diagnosed with non-affective psychoses who consumed cannabis prior to their first psychotic break (Galvez-Buccollini et al., 2012). Researchers used the Diagnostic Interview for Genetic Studies (DIGS) and the Family Interview for Genetic Studies (FIGS) to interview subjects and family members to determine each individual’s pre-existing genetic risk for mental illness prior to cannabis use. Data was adjusted for confounding variables. Researchers found that it was approximately seven years from when the subject first began using cannabis to their first psychotic episode or psychiatric hospitalization. The younger a subject was at the age of onset of cannabis use, the sooner the likelihood is of their first psychotic episode (Galvez-Buccollini et al., 2012).
In November 2010 researchers from McLean Hospital, a Harvard-affiliated facility, presented a paper at the Annual Meeting for the Society of Neuroscience in San Diego. Staci A. Gruber, PhD., Director of the Cognitive and Clinical Neuroimaging Core at McLean Hospital and Assistant Professor of Psychiatry at Harvard Medical School, reported that chronic cannabis users before the age of 16 demonstrated significant deficits in cognitive tasks requiring executive function skills (McLean Hospital, n.d.; Rabin, 2010). Dr. Gruber reported that those who began chronic cannabis use before their sixteenth birthday had double the amount of errors compared to later onset users. The study cited several factors to account for a higher error rate, such as attentional deficit and difficulty following instructions. Functional MRI (fMRI) scans performed on the 33 subjects while they were completing the study tests showed increased neural activity in the frontal area of the brain critical for attention, inhibition, and error processing in cannabis users (McLean Hospital, n.d.; Rabin, 2010).
Those who began cannabis use before 16, however, showed activity in a different part of that same region, which researchers suggested could be the result of neural compensation for brain damage due to early cannabis exposure (McLean Hospital, n.d.; Rabin, 2010). Dr. Gruber concluded that her team’s findings provide clinical evidence that the younger an individual is at the age of onset, the more severe the damage to their cognitive processing abilities (McLean Hospital, n.d.; Rabin, 2010). The combined cognitive and psychological effects of early onset and severity of use for cannabis users suggest that the effectiveness of mental health treatment on such subjects is dependent on the degree of brain dysfunction resulting from drug use. An impaired PFC is also linked to other neurological disorders such as attention-deficit disorder (ADD), attention-deficit/hyperactivity disorder (ADHD), bipolar disorder, antisocial personality disorder, depression, and in severe cases, criminality and sociopathic behavior.
Chronic cannabis abusers who have been using from the ages of 12 to 28 will respond to Drug Therapy (DT) most effectively if Cognitive Behavioral Treatment (CBT) is combined with clinical psychotherapy in the treatment of a mood disorder.
Description of Methodology
Data will be collected from a six-wave longitudinal study based on a random sample of 300 adults aged 29 to 45. The research subjects, all long-term chronic users of cannabis, will be divided into three groups of 100 people each with equal numbers of males and females. Groups will be divided into three categories based on the treatment that will be administered to them: CBT alone, psychotherapy alone, and a combined CBT and psychotherapy. The experiment will not divide individuals within each group on socioeconomic status but will include equal numbers of people from various ethnic groups defined by Caucasian, Mixed-Race, African American, Asian, Native American, or Pacific Islander.
Potential subjects will be screened to determine if they are candidates for a clinical diagnosis of a neurological disorder such as ADD or ADHD, bipolar I or II disorder, dyslexia, schizophrenia, borderline personality, psychosis, traumatic brain injury, or any mood disorder listed in the DSM-IV-TR (American Psychiatric Association, 2000). Only those who have been diagnosed or receive an Axis I diagnosis for generalized anxiety disorder (GAD), panic disorder, or depressive disorder will be included in the research study. However, ADD or ADHD subjects with a comorbid mood disorder will be included. Those who are diagnosed as having a more severe mental illness such as psychosis, dementia, or schizophrenia will be referred to a qualified physician for treatment but will not be included in the sample. Other factors that will eliminate a potential test subject are a pre-existing condition that has been tied to cognitive decline, such as a thyroid disorder or other autoimmune diseases. Women who are on the birth control pill or are undergoing hormone replacement therapy (HRT) are eligible to participate in the study if they get approval from their primary physician. All accepted participants will be fluent in English and fully literate and have a minimum of a high school diploma. Participants will not be on any prescription medication with the exception of females on hormone treatment unrelated to addressing a clinical mood disorder.
Instruments and Measures
All three groups will complete the following psychometric tests on their first intake session, which are self-report inventories: Minnesota Multiphasic Personality Inventory, Beck Anxiety Inventory, Beck Depression Inventory, Beck Hopelessness Scale, Hirschfield Mood Disorder Questionnaire, and Major Depression Inventory. Following the first session all subsequent appointments will require completion of the Hirschfield Mood Disorder Questionnaire at the end of each session. In addition, at the beginning and end of each month all subjects must complete the following positive psychology self-reports: Hope Scale, Inspiration Scale, Meaning in Life Questionnaire, Psychological Well-Being Scales, Satisfaction with Life Scale, State-Trait-Cheerfulness Inventory, and Subjective Happiness Scale. Each participant will be assigned an investigator who will collect this test data and share with their treating physician or psychologist.
The research is a longitudinal study for the duration of one year. All three test groups will be randomly assigned to investigators who will collect data. This is a double-blind study as neither investigators, including the treating psychiatrists and psychologists, nor the test subjects will know what the research is testing for. Group A will be those who are treated with DT alone, Group B with psychotherapy alone, and Group C will receive a combined treatment. The purpose of dividing treatment models into three distinct categories is to determine which type of treatment is most effective in mood stabilization for a patient who has a cannabis-induced mood disorder. For this research design, the dependent variable is the patient’s mood disorder and the independent variable is the treatment used on the patient. Since there are three types of treatment the research design has three independent variables. For the purposes of this study, gender differences will not be examined as a separate independent variable in the data analysis.
Group A participants will be assigned to a psychiatrist, who will see them three times a week. They will be prescribed a psychiatric medication depending on their diagnosis. Each subject will have their dosage monitored to maintain optimized levels for the entire time they are in the study. In between sessions participants will be asked to maintain a mood journal to record their emotional state during the day. Participants will keep track of the number of times a day they had a particular negative thought, such as sadness, hopelessness, fear, etc.
Group B participants will be required to meet with a clinical psychologist three times a week. These subjects will not be prescribed medication and will only receive CBT. Like Group A, they will also be required to keep a mood journal for the duration of the study. Their assigned psychologist will utilize other psychotherapeutic modalities as he or she feels are necessary to address the patient’s underlying mood disorder.
Group C will receive combined treatment from both a psychiatrist and clinical psychologist. They will also keep a mood diary but the clinicians assigned to them will work in conjunction together. Group C participants will have three weekly sessions but the first half will be medication management followed by CBT. However, the treating psychiatrist will see these patients in a separate room than their assigned clinical psychologist. This eliminates collusion between the clinicians.
The double-blind experimental design will eliminate threats to external validity and prevent the Hawthorne effect from influencing the data (Jones, 1992). To eliminate threats to internal validity, control of confounding variables will be implemented, and the study will use more than one group in the sample population. Random selection and assignment of test subjects will be conducted to control for extraneous variables. The hypothesis for this study is a one-tail directional prediction.
For the study, alpha will be set at 0.01%, which will increase Type 1 error in order to not make the error of identifying effective mental health treatment outcomes for chronic cannabis users that are a false positive. The number of subjects was increased from the initial proposal of 150 to 300 in order to build power in the study design. Threats to external and internal validity have been eliminated to decrease error rate. The magnitude of the independent variable has also been increased by only selecting psychiatrists and clinical psychologists for the treatment team who have a minimum of 20 years of experience as specialists who only treat long-term cannabis users. Furthermore, these clinicians were selected based on their peer-reviewed published abstracts that have been specific to treatment plans specific to the target patient population, which had demonstrated significant improvement beyond random occurrence in other related quantitative studies these clinicians participated in.
Analysis of Data
Subjects undergoing DT, CBT, and combined treatment will be compared before the treatment in relation to response rates of non-cannabis users in the same demographic variables subjected to the same types of treatments. Scores will be scaled on severity of symptoms, quality of life satisfaction rates, and the final results of the corresponding self-report inventory based on their initial diagnosis, such as the Beck Depression Inventory (BDI).
A non-parametric test will be run to analyze this data since the self-report inventories completed by the test subjects are considered nominal or ordinal numbers. Therefore, a chi-square test will be used to measure the frequency data between the three groups to compare the means and medians. This will be a multiple sample chi-square test to determine if results were due to chance alone or through the treatment applied to the test subjects. All three test groups will be treated the same except for the independent variable, which is the treatment they receive throughout the study. The differences in the data, if found, will suggest whether what experimenters did to the test subjects may have caused the results. The chi-square test looks at the obtained outcome compared to the expected outcome. Based on the calculations of the degrees of freedom based on the obtained and expected results, and the setting of alpha at 0.01, researchers will be able to determine if the data reflects random occurrence or not.
Research data will be collected on an interval basis of twice per month. Because the data obtained are ordinal numbers based on rating scales and self-reports, a t test will be run to compare the mean of all three groups. Expected findings are that the heaviest users will have little or no improvement in mood improvement scores, while the moderate users will have average or above average improvements and the light users will have a significantly higher improvement rate. If response rates yield no significant improvement in all three groups, then the null hypothesis will be disproven. Because sigma will be set at 0.01 and results will not be due to random occurrence, the conclusion will be that permanent brain damage as a result of chronic long-term cannabis use in adolescence has significantly impaired the emotional well-being of the patients.
American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., Text rev.). Washington, DC: Author
Andreasson, S., Allebeck, P., Engstrom, A., & Rydberg, U. (1987). Cannabis and schizophrenia. A longitudinal study of Swedish conscripts. Lancet, 26(2) (8574), 1483-1486. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/2892048
Brook, J. S., Balka, E. B., & Whiteman, M. (1999). The risks for late adolescence of early adolescent marijuana use. American Journal of Public Health, 89(10), 1549-1554. Retrieved from http://ajph.aphapublications.org/doi/pdf/10.2105/AJPH.89.10.1549
Brook, J. S., Lee, J. Y., Brown, E. N., Finch, S. J., & Brook, D. W. (2011). Developmental trajectories of marijuana use from adolescence to adulthood: Personality and social role outcomes. Psychological Reports, 108(2), 339-357. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117277/
Canadian Institutes of Health Research and Institute of Neuroscience, Mental Health and Addiction (INMHA). (n.d.). How drugs affect neurotransmitters: Cannabis. Retrieved from http://thebrain.mcgill.ca/flash/i/i_03/i_03_m/i_03_m_par/i_03_m_par_cann…
Edwards, L. (2010, December 22). Brain is not fully mature until 30s and 40s. PhysOrg.com News. Retrieved from http://phys.org/news/2010-12-brain-fully-mature-30s-40s.html#jCp
Fergusson, D. M., & Boden, J. M. (2008). Cannabis use and later life outcomes. Addiction, 103(6), 969-978. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18482420
Fletcher, J. M., Page, J. B., Francis, D. J., Copeland, K., Naus, M. J., Davis, C. M., . . . Satz, P. (1996). Cognitive correlates of long-term cannabis use in Costa Rican men. Archives of General Psychiatry, 53(11), 1051-1057.
Galvez-Buccollini, J. A., Proal, A. C., Tomaselli, V., Trachtenberg, M., Coconcea, C., Chun, J., . . . Delisi, L. E. (2012). Association between age at onset of psychosis and age at onset of cannabis use in non-affective psychosis. Schizophrenia Research, 139(1-3), 157-160. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22727454
Green, K. M., & Ensminger, M. E. (2006). Adult social behavioral effects of heavy adolescent marijuana use among African Americans. Developmental Psychology, 42(6), 1168-1178. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/17087550
Hall, W. (2006). The mental health risks of adolescent cannabis use. PLOS Medicine, 3(2), e39. doi:10.1371/journal.pmed.0030039
Hayatbakhsh, M. R., Najman, J. M., Jamrozik, K., Mamun, A. A., Alati, R., & Bor, W. (2007). Cannabis and anxiety and depression in young adults: A large prospective study. Journal of the American Academy of Child and Adolescent Psychiatry, 46(3), 408-417. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/17314727
Hyman, S. M., & Sinha, R. (2009). Stress-related factors in cannabis use and misuse: Implications for prevention and treatment. Journal of Substance Abuse Treatment, 36(4), 400-413. doi:10.1016/j.jsat.2008.08.005
Jones, S. R. G. (1992). Was there a Hawthorne effect? American Journal of Sociology, 98(3), 451-468. Retrieved from http://www.jstor.org/discover/10.2307/2781455?uid=3739960&uid=2&uid=4&ui…
McLean Hospital. (n.d.). Neuroimaging Center: Cognitive and Clinical Neuroimaging Core (CCNC): Overview. Retrieved from http://www.mclean.harvard.edu/research/neuroimaging/ccnc.php
Medina, K. L., & Tapert, S. (2008). Neuroimaging marijuana use and its effects on cognitive function. Paper presented at the annual meeting of the American Academy of Pediatrics, Boston, MA.
Rabin, R. C. (2010, November 15). Marijuana smokers who start early are at greatest risk, study finds. The New York Times. Retrieved from http://www.nytimes.com/2010/11/15/health/research/15marijuana.html
Samson, K. (2010). Adolescent marijuana use may cause lasting cognitive deficits. Neurology Today, 10(24), 7. Retrieved from http://www.aan.com/elibrary/neurologytoday/?event=home.showArticle&id=ov…
World Health Organization. (1997). Cannabis: A health perspective and research agenda. Division of Mental Health and Prevention of Substance Abuse. Geneva, Switzerland: Author. Retrieved from http://whqlibdoc.who.int/hq/1997/WHO_msa_PSA_97.4.pdf