WikiJournal Preprints/Resources for the Assessment and Treatment of Substance Use Disorder in Adolescents
Emily Pender; Liana Kostak; Kelsey Sutton; Cody Naccarato; Angelina Tsai; Tammy Chung; Stacey Daughters, "Resources for the Assessment and Treatment of Substance Use Disorder in Adolescents", WikiJournal Preprints, Wikidata Q104417487
This paper is intended for clinicians and lay people to gain a deeper understanding of SUD in adolescents, particularly relating to alcohol, cannabis, nicotine, and opioids. Alcohol, cannabis, and nicotine are the substances most commonly used by this age demographic nationally. Each of these substances can have adverse, long-lasting effects on health if not managed properly, resulting in seriously compromised lifelong wellbeing.
This article explores SUD prevalence and reviews diagnostic criteria in relation to adolescence, including a synopsis of changes in SUD classification between the DSM-IV and DSM-5 and discussion of ICD-11 and the Research Domain Criteria (RDoC) system as a basis for research related to substance use. Effective assessment and consideration of co-occurring disorders are covered as well. Although the prognosis of SUD varies by an individual's environment and circumstances, a modal developmental course for SUD is discussed. Finally, a curated list of nationally recognized resources, including hotlines, clinics, and informational sites, is provided, along with an example of a compilation of local resources in North Carolina to illustrate how national resources might be augmented with local ones to provide a more effective continuum for education and intervention. By addressing these aspects of adolescent SUD, the research team offers a broader view of its prevalence in the United States, key warning signs and comorbidities, and reviews possible assessments and treatments for adolescents with SUD.
Diagnostic Criteria[edit | edit source]
Diagnostic and Statistical Manual of Mental Disorders[edit | edit source]
Substance use disorder is defined in the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (5th ed.) as “a problematic pattern of substance use leading to clinically significant impairment or distress”. The DSM-5, like the International Classification of Diseases (ICD-11), lacks any developmentally-specific or age-specific considerations in the diagnostic criteria specific to adolescent presentation of SUD.
The DSM-5 recognizes ten substance classes for SUD, which include: alcohol, cannabis, nicotine, opioids, sedatives, stimulants, inhalants, phencyclidine, other hallucinogens, and other/unknown. To warrant a diagnosis of SUD, at least two of the eleven criteria outlined in the table below must be met in a period of one year. These eleven criteria can be understood as indicators of withdrawal, tolerance, loss of control of usage, prioritization of substance use above most everything, risky or hazardous use, and physical, psychological, and interpersonal consequences of substance use.
|DSM-5 Criteria for Substance Use Disorder with Examples|
|Craving or a strong drive for substance use||Craving a cigarette upon waking up|
|Desire or unsuccessful attempts to decrease substance use||Flushing all prescription painkillers in the house, then buying more and using them later that night|
|Difficulty keeping to intentionally set limits on how much of a substance one plans to use, or how long (how much time) one plans to spend using a substance||Planning to have only one drink at a casual party, but end up having eight drinks|
|Substance use interfering with ability to meet school, home, or work obligations||Repeatedly coming to school high from smoking cannabis and failing all final exams|
|Significant time spent acquiring, using, or recovering from use of the substance||Drinking for hours each night, lying in bed for hours the next morning with a hangover, and showing up to work late due to recovering from the hangover|
|Continuance of substance use even when usage causes or worsens interpersonal problems||Getting dumped by a significant other due to constant angry behavior and arguments when drunk|
|Tolerance, either increased amount of substance used to get the same effect or decreased effect with continued use of the same amount of the substance||Smoking a joint and realizing the buzz lasts a much shorter amount of time than when you started smoking regularly six months ago|
|Withdrawal, either withdrawal symptoms or taking the substance to relieve or avoid withdrawal symptoms||Going on a long family vacation without access to opioids and experiencing insomnia, sweating, aches, dilated pupils, and vomiting upon stopping use|
|Continued substance use despite a physical or psychological problem that was probably caused or worsened by substance use||Continuing opioid use despite harm to self (e.g., injection-related cysts, abscesses, ulcers, and infections), and suicidal ideations that can follow opioid use|
|Substance use in situations where it could cause physical harm||Driving friends to McDonalds after drinking shots every Friday night|
|Giving up or cutting back on social, occupational, or recreational activities due to substance use||Quitting the school basketball team, even though this is an important activity (and tied to a scholarship) because the sport requires regular drug testing|
The DSM-5 outlines specifiers for severity, remission, and treatment environment. The severity specifier is based on the number of DSM-5 criteria that are met. The presence of two or three criteria indicates mild SUD, four to five indicates moderate SUD, and six or more indicates severe SUD. Remission specifiers give context to SUD that has not been active for some length of time. “In early remission” is specified if criteria have not been met in the past three months but have been met at some point in the past 12 months, with the exception of craving, and “in sustained remission” is indicated if the criteria have not been met for the past year. To provide more context around someone who is in treatment, the environment specifier “In a controlled environment” indicates that the person does not have access to any substances because they are currently residing in a restricted environment, such as a rehabilitation center.
The DSM-5 classifies Substance-Related and Addictive Disorders, which includes gambling disorder. Moreover, the DSM-5 consolidated substance abuse and substance dependence, which were separate in the DSM-IV, into one set of criteria for a diagnosis of SUD. In addition to these structural changes, criteria-level changes were made. DSM-5 added the criterion of craving, and it removed the DSM-IV criterion of recurrent substance-related legal problems. These changes came from an analysis of 39 studies totaling over 200,000 subjects which plotted criterion severity against how well a criterion discriminates between subjects of high or low severity. Ultimately, a pattern emerged such that substance abuse and substance dependence criteria were related to severity, with the exception of the legal issues criterion and the addition of craving criterion. Further, the legal issues criterion displayed low endorsement and poor discrimination. The addition of a craving criterion also helped to improve cross-classification system continuity, as this criterion was already used in the ICD-10. Additionally, a threshold of two criteria to receive a diagnosis was set given the urgency of early intervention for successful treatment outcomes. Given findings that meeting an increasing number of SUD criteria was associated with increasing consequences of the disorder, current nosologies designate severity as mild, moderate, or severe based on the total count of criteria present. A study estimating the impact of diagnostic criteria changes on diagnoses of SUD found that using DSM-IV criteria tends to underestimate SUD prevalence compared to DSM-5 criteria. Particular substances such as alcohol, hallucinogens, and prescription painkillers were at the highest risk of this misclassification, likely due to the addition of the craving criterion in the DSM-5.
International Classification of Diseases[edit | edit source]
The International Classification of Diseases (ICD) is a global diagnostic system under the World Health Organization oriented around clinical use and scientific validity used to categorize and diagnose disorders. The ICD-11 first segments these disorders by substance.  Specified substances include all substances recognized by the DSM-5 and additional substances of synthetic cannabinoids, synthetic cathinones (bath salts), MDMA, dissociative drugs, and non-psychoactive substances. After the substance itself is specified, the ICD-11 categorizes the disorder as either harmful use or dependence. Harmful use could constitute physical or mental harm to oneself (ex: injuries sustained from car crash while driving high) or to another (ex: PTSD developed by victim of drug-induced rage). Dependence, the more severe diagnosis, is characterized primarily by impaired control over substance use and a strong drive to use the substance. Finally, a harmful use disorder is categorized as episodic or continuous. To qualify as episodic use, the substance use and symptoms must be present over the past year. In cases of heavy use, with near-daily use and symptoms, the disorder is classified as continuous use.
The following table provides examples of ICD-11 diagnoses of harmful use for alcohol (episodic) and cannabis (continuous); and ICD-11 diagnoses of dependence for nicotine (current) and opioid (current) use.
|ICD-11 Diagnoses of Substance Use Disorder|
|Harmful pattern of use of alcohol, episodic||A pattern of episodic or intermittent alcohol use that has caused damage to a person’s physical or mental health or has resulted in behavior leading to harm to the health of others. The pattern of episodic alcohol use is evident over a period of at least 12 months.|
|Harmful pattern of use of cannabis, continuous||A pattern of continuous (daily or almost daily) cannabis use that has caused damage to a person’s physical or mental health or has resulted in behavior leading to harm to the health of others. The pattern of continuous cannabis use is evident over a period of at least one month.|
|Nicotine dependence, current use||Current nicotine dependence with nicotine use within the past month. Diagnosis of ICD-11 nicotine dependence would require impaired control over nicotine use (e.g., difficulty quitting nicotine use; at least one serious unsuccessful attempt to stop) and a strong drive to use nicotine (e.g., craving)|
|Opioid dependence, current use||Opioid dependence, with use of an opioid within the past month. Diagnosis of ICD-11 opioid dependence would require impaired control over opioid use (e.g., try to limit use to 1 pill per day, but repeatedly used more than planned due to subjective compulsion to use) and a strong drive to use opiate (e.g., craving).|
A major strength of the ICD-11 is the ease of interfacing with a diverse range of clinical and healthcare settings. The ICD-11 is widely accepted by hospitals, practitioners, and insurance companies both in the US and abroad for physical and mental health disorders. Aside from the high-level benefit of ease of use, the differentiation of disorder by substance class allows for specification in substance-specific medical interventions and treatment of withdrawal symptoms. Moreover, segmenting diagnoses as harmful use or dependence can provide an opportunity to tailor level of intervention to pattern of use, allowing for early intervention at a crucial stage of harmful use or more intensive levels of intervention for dependence. However, the ICD-11, similar to the DSM-5, lacks any adolescent-specific criteria or diagnoses for SUDs.
Research Domain Criteria[edit | edit source]
Developed by the National Institute of Mental Health in 2009 for research rather than clinical use, the Research Domain Criteria (RDoC) is a system rooted in neuroscience to understand classification of mental disorders from a dimensional perspective. Although traditional diagnostic systems focus on symptoms and clinical presentation, the RDoC pays special attention to biological mechanisms on multiple levels of analysis. The RDoC outlines major transdiagnostic neurobiological and observable behavior domains. For each domain, RDoC organizes a matrix of operational definitions, with the goal of understanding links between different levels of analysis extending from genes to molecules, cells, circuits, and physiological systems, up to observable behaviors and subjective experiences usually assessed by self-report. RDoC also seeks to organize operational definitions of different domains at the level of animal models and laboratory tasks for use with humans (which it refers to as "paradigms").
Regarding substance use disorder, at least three of these domains are clearly implicated: cognitive systems, positive valence, and negative valence. The cognitive systems domain covers executive functioning and preoccupation with obtaining or using substances, while the positive valence domain includes reward pathways, and the negative valence domain involves general negative emotional and stress responses.  These three domains meet in the model of addiction such that individuals who are more sensitive to rewards are at risk of initial substance use, which can escalate to heavier use through the interaction of cognitive systems and negative valence systems. For example, according to the "self-medication" hypothesis, chronic heavy substance use may serve to reduce negative valence subjective states, such as anxiety; and heavy substance use might be used to prevent or relieve withdrawal (note that negative affect might be a symptom of withdrawal).
The RDoC was developed as a tool for researching domains and functions based on neurobiological phenomena, but it has been proposed to be adapted for assessment of substance use disorder. Although intended to be transdiagnostic, the original formulations did not specifically have addictive disorders in mind, and it is not clear whether RDoC domains currently provide comprehensive coverage of the constructs and systems important to understanding substance use. The National Institute on Alcohol Abuse and Alcoholism (NIAAA) is exploring the development of an "Alcohol Addiction RDoC" (AARDoC) to address some of these concerns. The Addictions Neuroclinical Assessment (ANA) grew out of this initiative. The ANA assesses the RDoC domains relevant to addiction (cognitive--specifically focusing on executive function, positive valence--specifically on incentive salience, and negative valence--specifically negative affect as a part of withdrawal) through an amalgam of self-report questionnaires, various behavioral tasks, and neuroimaging (including fMRI) which amounts to approximately a 10 hour comprehensive battery. Though the ANA is a recent development, it has shown promising validity in measuring negative valence in men and women seeking treatment for alcohol use disorder. Support for aberrant brain functioning at each stage of the ANA’s proposed addiction cycle (binge/intoxication, withdrawals/negative affect, and preoccupation/anticipation) has been identified. Future research will test if the ANA can effectively specify treatment based on measurements of AARDoC domains. Currently, however, the RDoC remains predominantly used in research settings rather than clinical settings.
Prevalence[edit | edit source]
Trends in substance use over time are assessed using an annual survey by Monitoring the Future, which measures the substance use of 8th, 10th, and 12th graders in a nationally-representative sample. In 2019, the survey sample included 42,531 students in 397 schools across the US. Annual use of any illicit drug in 8th and 10th graders in 2019 was 14.8% and 31%, up 1.5% and 1.1% respectively from 2018 results. Meanwhile, 12th grader’s usage of any illicit drug decreased by 0.8% between 2018 and 2019. The most common substance used each year is alcohol, with a prevalence of 36.1% in 2018, down from 48.7% in 2008. Following alcohol in prevalence is cannabis, with an annual prevalence of 24.3% in 2018, up from 21.5% in 2008. For all of these categories, prevalence increased as grade level increased. In 2019, the National Survey on Drug Use and Health (NSDUH) found that 4.5% of adolescents in the sample population between the ages of 12-17 had a SUD in the past year for either illicit drugs or alcohol.
Nicotine use prevalence was reported for 8th, 10th, and 12th graders combined across different modalities in Monitoring the Future. Cigarette use in the past 30 days was 4.6% for 8th, 10th, and 12th graders combined in 2018, down from 12.6% in 2008. Smokeless tobacco use in the past 30 days was 3.4% in 2018, down from 4.9% in 2008. Nicotine vaping data was only collected beginning in 2017, with a 30 day prevalence of 14.2% in 2018, up from 7.5% in 2017. 30 day use of large cigars, flavored little cigars, regular little cigars, and tobacco using hookah have all been trending down in the past few years, with 30 day prevalence in 2018 of 3.2%, 5.5%, 3.4%, and 2.7%, respectively.
The Substance Abuse and Mental Health Services Administration's National Survey on Drug Use and Health (NSDUH) provides another national source of information on the prevalence of adolescent substance use, and unlike Monitoring the Future, assesses substance use disorder. In the 2018 NSDUH, past year prevalence of opioid misuse (i.e., use of a medication, such as opiates, in any way that a doctor did not direct) among 12-17 year olds was 2.8%, down from 3.9% in 2015.
In the 2018 NSDUH, for any alcohol or illicit drug SUD, past year prevalence among 12-17 year-olds was 3.7%, down significantly from 5.0% in 2015. Past year alcohol use disorder (AUD) was 1.6% in 2018, significantly less than 4.9% in 2008. Prevalence of past year cannabis use disorder was 2.1% in 2018, which is a significant decrease from 3.4% in 2008.[Note 1] Past year opioid use disorder prevalence among 12-17 year olds was 0.4% in 2018, which is not significantly different than 0.5% in 2015.
|National Household Survey on Drug Use and Health: Percentages of 12-17-Year-Olds with SUD for Specific Substances|
|Any substance (alcohol or illicit drugs)||3.7%||4.5%|
Substance use and SUD prevalence differs significantly across gender, race, ethnicity, and sexual orientation. In early adolescence, females have higher rates of substance use than males. However, by mid-adolescence and early adulthood, males generally surpass females in substance use. Differences by race and ethnicity also emerged, such that Hispanics had the highest rate of substance use in early adolescence, but Caucasians had the highest rate by mid-adolescence. Regarding sexual orientation, a meta-analysis found that sexual minority adolescents have a higher prevalence of SUD than heterosexual adolescents, such that on average, the odds of SUD for a sexual minority youth were 190% more than their heterosexual counterpart.
Beyond the baseline rate of SUD in the general population, it is helpful to know SUD prevalence across diverse settings. A study from 2001 in California assessed past year prevalence rates of SUD in adolescents across five clinical settings. In formal alcohol and drug sectors of care, 42.6% of participants reported SUD in the past year. Juvenile justice settings had a 36.9% prevalence rate. In mental health care settings, prevalence was 22.9%. Public school services for adolescents with severe emotional disturbance had a prevalence rate of 16.0%. Child welfare settings had a prevalence rate of 11.0%. A review found that homeless adolescents were at a particularly elevated risk of SUD (e.g., ranging from 44-86% of substance-using homeless youth).
Comorbid Disorders[edit | edit source]
Approximately 60% of adolescents with SUD satisfy diagnostic criteria for one or more co-occurring psychological disorders. A review found that the most common comorbidity for adolescents was a category of disruptive behavior disorders including oppositional defiant disorder (ODD) and conduct disorder (CD). The median prevalence of co-occurring ODD and CD was 46.0%. There is some evidence for a cyclical relationship between substance use and behaviors associated with conduct disorders, such that one condition increases the other and vice versa, leading to increasing severity of both conditions over time. Depression was also common, with a median comorbidity rate of 18.8%. Comorbid attention deficit hyperactivity disorder (ADHD) had a prevalence of about 12.3%, however, it is important to note that this may be partially explained by the high degree of correlation between ADHD and ODD/CD.
Prevalence of substance use among adolescents is highest for those with prior anxiety disorders (such as generalized anxiety disorder, panic disorder, and post-traumatic stress disorder) and behavior disorders (such as ADHD, CD, and ODD). Having any prior mental health disorder was found to significantly increase the risk of starting alcohol use and escalating alcohol use, and similar associations were found between prior mental health disorders and illicit drug use. 17.3% of adolescents with prior anxiety disorders experienced alcohol-related problems and 20% experienced drug-related problems. For adolescents with prior behavioral disorders, 15.6% experienced alcohol-related problems and 24% experienced drug-related problems.
SUD is also associated with suicide in adolescents. Teenagers with SUD are about three times more likely to attempt suicide than their counterparts who do not use substances. The issue of suicide is particularly relevant to adolescents, because it is the third leading cause of death in Americans ages 10 to 19.
Comorbidities are typically more common in clinical settings for the treatment of SUD. Co-occurring mental health problems range in prevalence from 64-88% among adolescents in SUD treatment settings. For example, one review found that among adolescents with SUD, prevalence of co-occurring conduct problems was 69%, depression was 30%, and anxiety was 38%. In 2018, 65.7% of adolescents with co-occurring SUD and major depressive episodes received some type of mental health services or substance use services. 59.5% received mental health services only, 0.8% received substance use services only, and 5.4% received both mental health and substance use services. Best clinical treatment outcomes are associated with parallel utilization of both mental health services and substance use services, targeting both the comorbid psychiatric disorder and substance use issues. Multisystemic therapy (MST) works well with treating comorbid conduct disorders (CD) and SUD, showing long-term beneficial effects on adolescents. Other therapies that show positive benefits for CD and SUD in terms of reducing delinquent behavior include multidimensional family therapy (MDFT) and the Adolescent Community Reinforcement Approach (A-CRA). Cognitive Behavioral therapy (CBT) with Motivational Interviewing (MI) has been shown to reduce issues associated with comorbid internalizing disorders and SUD.
|Rate of SUD Comorbid Disorders in Adolescents|
|Comorbid Disorder||Prevalence||Prevalence in SUD Clinical Setting|
|Any Comorbid Disorder||60.0%||64-88%|
|Conduct Problems (CD/ODD)||46.0%||69%|
Prognosis or Developmental Course[edit | edit source]
Substance use and SUD prevalence rises throughout adolescence and reaches a peak in early adulthood. Developmental stage is important in understanding SUD, as substance use among adolescents manifests differently than among adults. Moreover, adolescence is a time of intense change within the individual and their social networks; these processes and interactions increase both opportunities and motives for substance use and experimentation. Adolescent substance use and risks are shaped by legal and logistical barriers to obtaining substances which can increase risk of binge use, increased sensitivity to peer influence, and still-developing brains that make substance use at this age particularly dangerous. For example, because a minor cannot purchase alcohol, adolescents drink less frequently than adults yet are more likely to engage in binge drinking with peers (who may provide access to alcohol). Binge drinking is a high-risk activity, as it may lead to neurological damage or accidental injury/death.
Early onset substance use, defined as use prior to age 14-15 for alcohol and age 16 for cannabis, is associated with a higher risk of consistent and long-term SUD. Early substance use progresses to either an adolescent-limited course or a chronic course with high risk for SUD throughout adulthood. Those with comorbid disorders and certain temperament characteristics, such as behavioral disinhibition, are at higher risk for developing a chronic course of SUD.
Adolescents are often referred to substance use treatment by external sources, such as parents and family members, the school, and the juvenile justice system. In 2015, for adolescents aged 12-17, referrals to publicly funded substance use treatment by the court/criminal justice system represented 43% of adolescent admissions, while individual referrals comprised 20%, and school referrals, 13%. Furthermore, according to the 2019 NSDUH, 0.5% of adolescents aged 12-17 reported that they received treatment for substance use within the last year, representing a fraction of those meeting criteria for substance use disorder.
Factors associated with better treatment outcomes and positive prognosis include completion of treatment, high motivation to abstain, low substance use when commencing treatment (i.e., milder presentation), and more social support from non-using family and friends. Course and outcome are influenced by factors such as co-occurring disorders, ethnic background, and gender.
There are also various predictors of poor adolescent SUD outcomes. A comprehensive review of the role of personality traits found that impulsivity is a key predictor of negative outcomes in individuals with substance use disorder. Substance dependence during adolescence also predicts a poor prognosis. Moreover, initiating substance use early in life is a predictor of increased use of multiple substances (e.g., alcohol, cannabis, opiates). Predictors of substance use have been demonstrated to differ across race as well, where lower distress tolerance was significantly related to higher past year alcohol use among Caucasian adolescents but had no significant relationship among African-American adolescents.
Relapse rates are high for adolescents who have received outpatient treatment for SUD; one study found a six-month relapse rate of 66% and a median time to relapse of 54 days without any significant difference by demographic factors or comorbid disorders. A large review showed six-month relapse rates at 62% and one-year relapse rates at 68%. Reported reasons for relapse differ between adolescents and adults: adolescents tend to attribute relapse to social situations and peer use, while adults often attribute relapse to coping with negative emotions. However, relapse for cigarette use is an exception: teens tend to attribute cigarette use to a compulsion to use rather than peer pressure. Recovery is not guaranteed with any initial intervention, and often those with SUD will require numerous attempts to overcome SUD before long-term success is achieved.
Evidence-Based Assessment[edit | edit source]
This section is intended to provide an assessment model for clinicians who may not be specialized in substance use disorder. For clinicians who are specialized in substance use disorder, this resource kit may be more applicable.
|Assessment measures for Substance Use Disorder|
|Questionnaire/Interview||Age Range||Administration/ Completion Time||Qualifications to Give Assessment||Substance(s) Assessed||Purpose of Assessment||Cost||PDF/Link|
|Problem Oriented Screen Instrument for Teenagers (POSIT)||Adolescents||20-30 mins||None required||Any||Treatment Planning||Free||Link Here|
|Problem Oriented Screen Instrument for Parents (POSIP)||Adults||10-15 mins||None required||Any||Treatment Planning||Free||Link Here|
|Screening to Brief Intervention (S2BI)||12-17||5 mins||None required||Alcohol, Cannabis, Tobacco, Others||Initial Screening||Free||Link Here|
|Brief Screener for Tobacco, Alcohol, and Other Drugs (BSTAD)||12-17||5 mins||None required||Alcohol, Tobacco, Others||Initial Screening||Free||Assessment Here|
|Teen Addiction Severity Index (T-ASI)||Adolescents||20-45 mins||Professional||Any||Treatment Planning, Assess Treatment||Free||Link Here|
|Time Line Follow-Back (TLFB)||Adolescents||10-15 mins||Minimum training||Alcohol, Tobacco, Others||Treatment Planning, Assess Treatment||Free||Link Here|
|Rutgers Alcohol Problems Index and Marijuana Adolescent Problem Inventory (RAPI/MAPI)||Adolescents||10 mins||None required||Alcohol, Cannabis||Treatment Planning||Free||RAPI Link|
|GAIN-SS (Global Appraisal of Individual Needs-Short Screener)||Adolescents, Adults||5 minutes||Minimum training||Any||Initial Screening||$100 for 5 years of all GAIN measures||Link Here|
|GAIN-I (Global Appraisal of Individual Needs-Initial)||Adolescents, Adults||60-120 mins||Minimum training||Any||Diagnosis, Treatment Planning, Assess Treatment||$100 for 5 years of all GAIN measures||Link Here|
|Drinking Motives Questionnaire (DMQ)||Any||10 mins||None required||Alcohol||Treatment Planning||Free||Link Here|
|Comprehensive Marijuana Motives Questionnaire (CMMQ)||Any||10 mins||None required||Cannabis||Treatment Planning||Free||Link Here|
|The Contemplation Ladder||Any||5 mins||None required||Any||Treatment Planning, Assess Treatment||Free||Link Here|
|The Readiness Ruler||Any||5 mins||None required||Any||Treatment Planning, Assess Treatment||Free||Link Here|
|Urine Drug Screen||Any||10 mins||Trained collector/ Certified
|Cannabis, Opiates, Others||Initial Screening, Treatment Planning, Assess Treatment||Varied||N/A|
|CRAFFT (Car, Relax, Alone, Friends/Family, Forget, Trouble)||Adolescents||5 mins||None required||Any||Initial Screening||Free||Link Here|
|Alcohol Use Disorders Identification Test (AUDIT)||Adults,
|5 mins||None required||Alcohol||Initial Screening||Free||Link Here|
While assessments are often used as screeners or diagnostic tools, they can also be helpful tools throughout treatment. The integrative Evidence-Based Assessment (EBA) model is a framework for using clinical psychological assessments at all stages of clinical care: for prediction, prescription, and process. With "prediction" of adolescent substance disorder, consistent use of brief screeners for substance use in mental health and medical care settings can catch substance use that would otherwise go undetected, allowing for early intervention and treatment implementation. In the absence of these screeners, clinical judgement alone underestimates adolescent substance use and often doesn't identify the problem until late-stage behavioral issues become apparent. With "prescription," assessments can help a clinician determine the best treatment plan for an adolescent with a substance use disorder, considering the individual holistically. In this vein, assessments can help the clinician determine the substance use severity, motivation for the substance use, and the adolescent's readiness for change, while also considering caretaker reports, toxicology testing, and external school, medical, and legal reports. After developing a treatment plan in collaboration with the adolescent based on the comprehensive evaluation, assessments should be continuously used throughout the treatment to gauge the "process," allowing for the treatment plan to adapt as needs change and for outcome goals to be measured.
There are many options for evidence-based screeners for initial assessment of adolescent substance use. These validated screeners assess substance use along a continuum based on frequency and intensity of use. Screening to Brief Intervention (S2BI) asks about the frequency of use in the past year of eight types of substances (tobacco, alcohol, cannabis, illegal drugs like cocaine or ecstasy, non-prescribed prescription drugs, misuse of OTC medication, inhalants, and herbs or synthetic drugs) with six frequency responses ranging from "never" to "daily". The Brief Screener for Tobacco, Alcohol, and Other Drugs (BSTAD) asks about the individual's and their friends' substance use in the past year, along with one's individual frequency of use in the past 30, 90, and 365 days. The Global Appraisal of Individual Needs Short Screener (GAIN-SS) is a broader assessment, looking at four subscales for internalizing disorders, externalizing disorders, substance use disorder, and crime/violence. This can be helpful in determining comorbid disorders, in addition to substance use issues. The substance use items focus on the frequency of usage, priorities of substance use, and problems related to substance use. The CRAFFT screener is an acronym for Car, Relax, Alone, Friends/Family, Forget, Trouble. This screener asks pre-screener questions about frequency of substance use and identifies problems associated with substance use related to the dimensions represented by the acronym. Alcohol Use Disorders Identification Test (AUDIT) specifically screens for hazardous drinking, asking questions about frequency of use, alcohol dependence, and alcohol-related problems. While the screener was created for adults, research supports its use for adolescents ages 14 to 18 as well.
If substance use is indicated in a brief screener, further assessment can help a clinician gain insight on the severity of substance use, along with other individual and environmental characteristics that can aid and inform the optimal treatment plan. The Problem Oriented Screening Instrument for Teenagers (POSIT) is a longer screener with 139 items that explores an adolescent's current functioning, focusing on substance use, physical and mental health, family and peer relations, educational and vocational status, social skills, recreational activities, and aggressive/criminal behavior. The Problem Oriented Screening Instrument for Parents (POSIP) is the parental version of the POSIT, asking similar questions from the caregiver's perspective. The Teen Addiction Severity Index (T-ASI) is a semi-structured interview that assesses the adolescent's functioning across seven domains: substance use, school, vocation, family, legal status, peer relationships, and mental health status. Each domain is rated from one to five in terms of both perceptions of impairment and need for treatment. The Global Appraisal of Individual Needs Initial (GAIN-I) is a semi-structured diagnostic interview that can help diagnose substance use disorder and can be used to inform treatment placement and planning along with outcome monitoring. The GAIN-I focuses on the same four subscales as the GAIN-SS: substance problems, internal mental distress, behavior complexity, and crime/violence. If a clinician specifically wants to know more about an adolescent's alcohol-related problem behavior, The Rutgers Alcohol Problems Index (RAPI) is an 18 item questionnaire that asks about the frequency of issues like going to school drunk, avoiding responsibilities, and blacking out. Similarly, the 23 item Marijuana Adolescent Problem Inventory (MAPI) assesses problem behavior related specifically to cannabis use.
In addition to assessing severity of use and substance use-related problems in functioning, learning about the adolescent's context of substance use, motives for substance use, and readiness to change their behavior can help inform treatment planning and assess ongoing treatment. The Time Line Follow-Back (TLFB) is a calendar-based method of reporting substance use in the past month. This assessment not only gives information on the frequency and severity of use but can also highlight the contexts in which the adolescent tends to use the substance and illuminate patterns of their use. A demo of an online version of the TLFB with scripts for clinicians to use to make their own version can be found here. The Drinking Motives Questionnaire Revised (DMQ-R) and Comprehensive Marijuana Motives Questionnaire (CMMQ) assess the adolescent's reasons for substance use. The DMQ-R looks at four main motives for alcohol use: drinking to be social, drinking to cope, drinking to enhance positive emotions, and drinking to conform with peers. The CMMQ looks at 12 main motives for cannabis use: enjoyment, conformity, coping, experimentation, boredom, alcohol, celebration, altered perception, social anxiety, relative low risk (e.g., "because it is safer than drinking alcohol"), sleep/rest, and availability (e.g., "because it is there"). In both measures, "using to cope" was associated with more negative consequences, as was "using to sleep/rest" for the CMMQ. To assess motivation to change substance use behavior at the onset or during treatment, clinicians can use the Contemplation Ladder or the Readiness Ruler. The Contemplation Ladder has 11 "rungs" that range from statements of no desire to change, to ambivalence, to taking action. The Readiness Ruler is a visual scale from one to ten with similar markers along the continuum of change. These tools can help the clinician gauge the adolescent's feelings about treatment and desire or resistance to changing their substance use.
In addition to self-report and interview assessments, toxicological tests of urine, blood, or hair are recommended to detect substance use at the onset of and throughout treatment. However, a negative test does not necessarily mean the adolescent is not using drugs, as drugs only temporarily remain in urine and results can vary based on the type of substance and frequency of use. While some studies have found self-report measures to be highly correlated with urine tests, others have found self-report measures to be inconsistent with urine tests, with some adolescents who report substance use having negative urinalysis and other adolescents who deny substance use having positive urinalysis. Therefore, the results from multiple types of assessments should be considered by the clinician. Adolescents may under-report or deny use in a clinical setting due to fear of negative ramifications like legal repercussions or parental consequences. In addition to supplementing adolescent self-report by cross-referencing with parental-reports and biological testing, validity of adolescent self-report can be improved by building rapport with motivational interviewing techniques and by discussing confidentiality guidelines and limitations prior to assessment.
Evidence-Based Treatment[edit | edit source]
Determining the optimal treatment for adolescent substance use disorder requires careful consideration of multiple factors. According to the American Society of Addiction Medicine (ASAM) criteria, clinicians should consider the patient on six dimensions to approach their treatment planning from a holistic perspective. These include the individual's addiction history, severity, and withdrawal potential, their physical health/medical conditions (including STIs, HIV, and pain), their mental health, their readiness to change, their risk of relapse, and their recovery situation/support. With these factors in mind, the clinician can determine the best intensity of treatment for the patient on the continuum of care options, ranging from brief intervention, to outpatient services, to intensive outpatient services, to residential/inpatient services, to medically managed intensive inpatient services. Adolescents should be treated in the least restrictive care setting that still provides necessary care and a safe environment. While more intensive residential programs may be needed in more serious cases, outpatient therapy is the most common treatment for adolescents and can foster generalization of treatment gains. There is not a "one-size fits all" treatment for adolescent substance use disorders, and the best treatment varies based upon the type of substance and the adolescent's particular needs and problems. These needs will likely change over time and treatment should be continually assessed and adapted through a continuing care approach.
The least intensive of the ASAM criteria levels of care is early intervention. This is often implemented through a brief intervention delivered by a primary care provider or other medical professional. This brief intervention is a short conversation between the provider and patient that is tailored to the severity of substance use that the patient disclosed on a screener assessment. The focus should be on preventing, reducing, or stopping substance use. The provider should give clear advice to abstain from the substance, information on negative effects of usage, and discuss a plan to stop usage that emphasizes individual strengths and positive behaviors of the patient that will help them abstain. Specific training guidelines by the American Academy of Pediatrics for primary care providers on how to deliver a brief intervention for adolescent substance use can be found here.
For adolescents who need more than a brief intervention, the next level of care according to ASAM criteria is outpatient therapy. This treatment may consist of many different elements and forms of therapy in order to address the multiple needs of the adolescent around their substance usage including family therapy, individual behavioral therapy, support groups, medication, and legal services. Given high comorbidity rates among adolescents with SUD, co-occurring disorders should be screened in all SUD treatment settings. Along with the SUD, these co-occurring disorders must be appropriately addressed with evidence-based methods in order for the adolescent to return to developmentally-appropriate functioning. Throughout treatment, it is beneficial for treatment providers to continually assess substance use as relapse is common and recovery is a long term process. Abstinence from drug use is strongly recommended, with a focus on motivation, family engagement and support, skills-building and relapse prevention, co-occurring disorder treatment, multi-system intervention, and completion of treatment and follow-up. Ensuring that services that are developmentally, culturally, and gender-appropriate is also necessary when determining treatment for adolescent substance use. This means that adolescents should not be treated at adult-based programs and providers should work to be culturally responsive.
In general, the most efficacious therapies for adolescent substance use disorder are family-based ecological treatment, cognitive behavioral therapy (individual, group, and family), motivational enhancement treatment with CBT, or some combination of all three therapies. Family therapy is important as family relationships and context are important risk factors for adolescent SUD and families can institute important environmental changes. Cognitive behavioral therapy helps the adolescent anticipate their problems and enhance their self-control. CBT helps individuals recognize cravings and situations that are high-risk for their substance use and build adaptive coping skills and strategies to avoid or manage cravings. Developing adolescent buy-in to therapy is crucial to treatment completion and relapse prevention, especially since adolescents rarely self-refer and instead are typically pressured or forced into treatment by a caregiver, the school system, or the juvenile justice system. Motivational Enhancement Treatment can help drive treatment compliance and retention in adolescents with SUD by helping individuals increase their motivation for recovery and build a plan for change. In addition to these therapies, twelve-step groups such as AA or NA have been shown to be beneficial as supplemental or continuing treatment, with the caveat of locating groups with age-similar members to increase the adolescent's engagement and identification with other members at the meeting. Similarly, building peer support systems of non-substance using peers can be a driver of sustained behavior change and help prevent relapse. The NIH has suggestions on how to find adolescent treatment support groups here, and this toolbox from University of Massachusetts Medical School helps practitioners effectively employ peer support programs.
There are many forms of evidence-based family therapy for adolescent substance use disorder. Family Behavior Therapy focuses on the substance use issues along with other simultaneous problems including conduct disorders, depression, mistreatment (e.g., physical, sexual abuse; neglect), and family conflict. The therapist meets with the adolescent and at least one of their caregivers and helps them create behavioral goals for substance abstinence and build new skills to cope with co-occurring issues. The therapy also utilizes contingency management and allows the patients to contribute to the treatment planning. Brief Strategic Family Therapy (BSFT) focuses on identifying and changing family patterns that are thought to continue or worsen adolescent substance use and conduct problems. The approach of BSFT is flexible and can be adapted to many settings and modalities of treatment from outpatient therapy to being a part of a residential program or continuing care plan.
Other forms of family therapy are more comprehensive and community based, addressing the influence of school, peers, and community in the treatment. Since family, school, and peer systems significantly shape adolescent behavior and exert considerable structure and control on their lives, aligning these systems with recovery-focused goals can be highly influential to decrease instances of relapse and to address and overcome trauma that might be a root cause of the SUD. One of these types of comprehensive substance use disorder treatments that works with the adolescent and their family is Multisystemic Therapy (MST). MST is especially helpful for adolescents who display antisocial behavior along with their substance use. The intensive treatment occurs in natural environments in patient's home, school, and/or community and addresses individual factors, family conflict, peer influence, school issues, and neighborhood cultural influences on drug use. MST has high retention rates and has been found to significantly reduce substance use for at least six months after treatment. Multidimensional Family Therapy (MDFT) considers adolescent drug use through the lens of multiple interconnected networks of the individual, family, peer group, and community. The therapist works with the individual to build important developmental skills for problem solving, decision making, and communication along with vocational skills. MDFT works to increase desirable behavior and decrease drug use and other problem behaviors across many different settings with multiple strategies. Parallel sessions with the caregiver focus on examining parenting styles and negotiating developmentally appropriate levels of control and influence.
While pharmacological treatment is often a significant component of treatment for adult substance use disorder, there are limited addiction medications that are approved by the FDA for people under 18. Currently, over-the-counter nicotine chewing gum, lozenges, and skin patches are the only FDA approved medications for adolescent substance users and should only be used with physician consultation. Recent research suggests that buprenorphine, a prescription medication for treating opioid addiction, may be effective for adolescents 16 and older, but the medication has not yet been approved by the FDA for adolescents under the age of 18. Other medications for treating opioid, nicotine, and alcohol substance use disorder are currently being researched to determine their safety for adolescent populations.
Resources[edit | edit source]
The goal of this section is to illustrate a range of informational and clinical resources, using internet searches as the point of entry because smartphone and internet searches are the main way that the general public looks for information and treatment options. The reliance on internet search is likely to be even more true for information-seeking related to substance use, because of factors such as the comorbidity described above and the splitting of services into separate silos for general health, mental health, and substance use. Additionally, the high level of stigma around the topic of substance use makes the privacy of online searches particularly well-suited for initial information gathering.
Online search is also a primary strategy for health professionals. The value of online search for professionals is accentuated with regard to substance use due to the fragmentation of services combined with the value of integrated care models for addressing the multiple needs of many people. Online searches for resources also are a key component of "foregrounding" information gathering as providers start their practices, relocate to a new area, or seek to support patients who themselves are relocating or inquiring about resources for friends and family in other geographic locations.
This section combines two different approaches. One is to focus on high quality and nationally accessible sources, such as content from federal agencies and national hotlines. The other is to seek local resources along a continuum of care, which is crucial for finding and identifying services such as individual counseling, support groups, and intensive-outpatient, partial hospital, inpatient, and residential programs. The full continuum of services may not be available at all geographic locations. We use a relatively resource-rich location as an example to show possibilities, so that gaps in offerings will be easier to identify in other settings.
National resources[edit | edit source]
In the event of a life-threatening emergency, immediately call 911, which is available throughout the United States and Canada. Similar emergency services are available in many other countries. An individual in crisis looking for immediate support may also either call a crisis support line at 1-800-273-8255 or text START to 741-741 to talk to a trained call operator anytime in a free, confidential setting. An individual with suicidal thoughts seeking immediate support can call the National Suicide Prevention Lifeline at 1-800-273-TALK. In the United States, a national three-digit prevention hotline will launch in 2022.
National resources are available to provide information hubs on SUD for adolescents and their support systems. The Substance Abuse and Mental Health Services Administration’s (SAMHSA) website is an easily accessible resource that provides confidential and free information services for individuals and family members facing substance use disorder. Moreover, SAMHSA National Helpline is available 24/7 at 1-800-662-4357. Furthermore, the Society for Adolescent Health and Medicine (SAHM) offers a plethora of resources for young adults to find resources pertaining to SUD. From the Partnership for Drug-Free Kids, a resource aimed at assisting families and individuals with SUD, to the Kelty Mental Health Resource Centre, which offers information on SUD and comorbid disorders, there are many ways to find help at the national level. Likewise, NIDA for Teens is a website covering national research findings related to SUD.
National resources are available to locate treatment options for adolescents with SUD. Higher Ed allows for drug rehab searches by state or city and details service options, level of care, treatment type, payment type, clients served, and contact information for each resource. The SAMHSA website also provides information on thousands of state-licensed providers who specialize in treating substance use disorder, addiction, and mental illness. People seeking help can use the Substance Abuse Treatment Facility Locator and the Opioid Treatment Program Directory features and filter by location, treatment type, age, and language. Search results include extensive details on each treatment program. To find a psychiatrist that treats adolescents, the American Academy of Child and Adolescent Psychiatry's Psychiatrist Finder is available.
For those in recovery, national support groups might be a beneficial way to further one's rehabilitation journey; Alcohol Anonymous and Narcotics Anonymous offer support to adolescents and young adults, and meetings nearby can be found on their respective websites. SMART Recovery is also a resource that teens can utilize to access self-empowering support, in person meetings, and a powerful online community. These models started as face-to-face group meetings, and developed into national networks that people could use to find meetings when traveling or relocating. In response to the COVID-19 pandemic and social distancing policies, these organizations have rapidly developed videoconferencing models for their meetings that further increase accessibility for many people.
|Crisis Support Line||Crisis||1-800-273-8255|
|Crisis Support Text Line||Crisis||Text START to 741-741|
|National Suicide Prevention Lifeline||Crisis||1-800-273-TALK|
|SAMHSA National Helpline||Informative||1-800-662-4357|
|Society for Adolescent Health and Medicine||Informative||--|
|Partnership for Drug-Free Kids||Informative||--|
|Kelty Mental Health Resource Centre||Informative||--|
|NIDA for Teens||Informative||--|
|Family Resource Center||Informative||--|
|Society of Addiction Psychology||Informative||--|
|SAMHSA Substance Abuse Treatment Facility Locator||Treatment Locator||--|
|SAMHSA Opioid Treatment Program Directory||Treatment Locator||--|
|Higher Ed||Treatment Locator||--|
|AACAP Psychiatrist Finder||Treatment Locator||--|
|Alcohol Anonymous||Support Group||--|
|Narcotics Anonymous||Support Group||--|
|SMART Recovery||Support Group||--|
Local resources[edit | edit source]
Local resources that offer evidence-based treatment for adolescent SUD often can be compiled from these national search engines. At a local level, there could be a multitude of resources to connect adolescents with SUD to professionals who can provide evidence-based treatment, but they may not be immediately obvious, and quality of services can be highly variable. It is important to carefully assess each local resource to determine which best meets the specific needs of the individual adolescent. Then, relevant treatment programs can be contacted to initiate assessment and treatment.
To illustrate how these local resources can be collected and presented in a relatively research-rich location, an example for the Research Triangle Park, North Carolina is analyzed. For assistance in finding the best treatment options locally in North Carolina to fit the specific needs of an individual adolescent, Easterseals provides a CARES program found at their website. This service connects a family in crisis with a qualified staff member who personally assists the family in finding comprehensive clinical services and appropriate care. Around Research Triangle Park, North Carolina, options for various levels of outpatient care are available for adolescents with SUD at universities such as Duke University and The University of North Carolina at Chapel Hill and their respective medical centers and campuses. These local programs are strongly rooted in evidence-based approaches and accept insurance; however, they lack the ability to handle higher levels of care. An option for drug and alcohol addiction treatment for adolescents offering higher levels of care located in Raleigh, North Carolina is Triangle Springs. This facility offers detox services, inpatient treatment, outpatient treatment, an alumni support group, and a 24/7 confidential helpline. A compilation of local resources in a table can be a helpful tool for adolescents and their support system to start to seek assessment and treatment for SUD.
|Sample of Local Resources: Research Triangle Park, North Carolina|
|Treatment Program||Evaluation Offered||Level of Care||Therapeutic Modality||Insurance Accepted||Address||Phone Number|
|UNC Adolescent Substance Abuse Service||No||
||Yes||101 Manning Dr
Chapel Hill, NC 27514
|Carolina Behavioral Care||Yes||
||Yes||4102 Ben Franklin Blvd
Durham NC 27704
||Yes||2301 Erwin Rd
Durham, NC 27705
||Yes||10901 World Trade Blvd
Raleigh, NC 27617
Conclusion[edit | edit source]
Summary[edit | edit source]
This research paper investigated substance use disorder in adolescents through studies conducted in the United States. By describing differences in diagnostic criteria between the DSM-IV and DSM-5, as well as the ICD-11, we have outlined some of the common indicators of SUD as well as common misclassifications. Intended primarily for medical and mental health professionals with limited knowledge of SUD, the prevalence of substance use and SUD among adolescents was presented, particularly for the commonly used substances of alcohol, nicotine, and cannabis, as well as common comorbid disorders. Some common comorbidities with SUD include ODD/CD, depression, and ADHD. The developmental course of SUD was found to be highly dependent on many specific factors related to the individual, and thus the age of onset, temperament, and comorbidities, among others, affected the prognosis of SUD and influenced the type of assessment and treatment offered to the individual. Numerous assessments for SUD in adolescents exist, and it is important for clinicians to consider cost, accessibility, and type of substance use and severity of use when determining which assessment is needed in the context of a specific individual at a certain point in time. Likewise, evidence-based treatments, including individual, family, and community therapy are available and can offer relief to those with SUD.
A plethora of resources, both national and local, are readily available through simple internet searches that locate websites and phone lines to provide further context around preemptive risks and warning signs of SUD development, anonymous crisis support, how and where to receive support, and treatment clinics open to new patients.A key factor to address among adolescents who engage in substance use is enhancing and maintaining motivation to reduce substance use, since most youth are referred to substance use treatment by others (e.g., parents, school, juvenile justice system).
Having a deeper understanding of what SUD is and how it affects adolescents' well-being is an important first step in reducing the prevalence of SUD, negating the long-term consequences of addiction, and preparing for unexpected but relevant issues that could exacerbate mental health disorders that heighten the risk of substance use disorder in adolescents.
Limitations[edit | edit source]
While this paper is a general overview of adolescent substance use disorder diagnosis, assessment and treatment, this review is limited in scope to a United States context. Developmental norms for adolescents and clinical concepts of substance use and SUD vary across cultures and countries. Similarly, context is key to determining the best treatment plans; there is no one-size-fits-all for substance use disorder. Age of onset of use, type of substance, co-occurring disorders, social determinants of health, and frequency and quantity of use can all drastically affect patient needs and outcomes in ways that are not fully covered in the scope of this paper. An additional limitation to this paper is variation between states in the US on legal issues such disclosure of medical records, or the right for minors to consent to substance use treatment. Determining if, when, and how to break confidentiality to inform parents depends on the context, clinical judgements, and the minor consent laws of the specific state. The variance in the legalization of recreational cannabis and medical cannabis for adults across the US also affects the prevalence of cannabis use and variance in legal ramifications for adolescents in different states. Finally, this paper is intended for medical and mental health professionals with little experience with substance use disorder. Therefore, this paper may be less relevant for the general public or medical and mental health professions well-versed in substance use disorder.
Future Directions[edit | edit source]
Future directions for research in this field include cross-comparisons of trends in different countries as well as with research conducted in different languages. Furthermore, including life-course trajectory perspectives is essential for understanding later-life treatment outcomes and potential interventions. This paper provided a broad overview of many substances, yet much remains unknown about what roles specific substances may play and how different substances may interact with one another. Future work should determine similarities and differences in how specific substances help maintain addiction and interact with comorbid mental health disorders.
Future reviews on adolescent substance use disorder could also focus on the effect of widespread crises such as natural disasters, social unrest, and pandemics. Current research on COVID-19 has suggested increased isolation during the pandemic has heightened risks associated with SUD, such as stress, fear, and anxiety, as well as reducing the potential for intervention and treatment. For example, in the cases of opioid overdose, there is a lower probability of someone being in proximity who could administer life-saving measures like naloxone. Researchers have found that the usual contexts of adolescent substance use have changed in the pandemic, with increases in solitary use (which is associated with depression) and increases in using substances with parents. Recent research on bipolar disorder suggests that COVID-19 presents both challenges, such as stigma, interruption of treatment, stress, and medical risks, as well as opportunities, such as increased resilience and adaptations of mental health treatment delivery, for those with bipolar disorder. As the COVID-19 global pandemic continues, more research on how these impacts specifically impact adolescents with SUD can help to increase understanding of the role that external forces have on adolescents with substance use disorder.
Additional Information[edit | edit source]
Acknowledgements[edit | edit source]
The author team wants to acknowledge the assistance of Eric A. Youngstrom, PhD, for his guidance and feedback in the creation of this paper.
We would also like to acknowledge Rachel Sorenson, Elizabeth Lang, and John Nicholas Fogg for their initial contributions to the project.
Conflict of Interest[edit | edit source]
The research team does not have any conflicts of interest to declare.
Ethics statement[edit | edit source]
There are no primary results from human or animal subjects research presented in this paper.
Ways of sharing information from this article[edit | edit source]
Note: Clicking the Mendeley button will offer to import all of the citations in the references below into your library.
Notes[edit | edit source]
- However, it is important to note that though prevalence of cannabis use in adolescents of the 2018 NSDUH were found to decrease, another study by Compton et al. found that cannabis use among adults increased from 10.4% to 15.3% during the period between 2002-2017. It also found that past year cannabis use disorder prevalence stayed relatively consistent at 1.5-1.4%, potentially as a result of limitations of DSM-IV criteria.
References[edit | edit source]
- McGorry, Patrick D; Purcell, Rosemary; Goldstone, Sherilyn; Amminger, G Paul (2011-07). "Age of onset and timing of treatment for mental and substance use disorders: implications for preventive intervention strategies and models of care:". Current Opinion in Psychiatry 24 (4): 301–306. doi:10.1097/YCO.0b013e3283477a09. ISSN 0951-7367. http://journals.lww.com/00001504-201107000-00008.
- Principles of Addiction: Comprehensive Addictive Behaviors and Disorders, Volume 1 (in en). Academic Press. 2013-05-17. ISBN 978-0-12-398361-9. https://books.google.com/books?hl=en&lr=&id=5gRNl3oIwWEC&oi=fnd&pg=PA97&dq=course+of+adolescent+substance+use&ots=j7Ljd60bwA&sig=_yXK9AJQjFekwnRaGd5r9ZUHtec#v=onepage&q=course%20of%20adolescent%20substance%20use&f=false. p.103
- SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2018 and 2019, Table 1.2B. https://www.samhsa.gov/data/report/2019-nsduh-detailed-tables
- SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2018 and 2019, Table 5.1B. https://www.samhsa.gov/data/report/2019-nsduh-detailed-tables
- Johnston, L. D., Miech, R. A., O’Malley, P. M., Bachman, J. G., Schulenberg, J. E., & Patrick, M. E. (2019). Monitoring the future national survey results on drug use 1978-2018: Overview, key findings on adolescent drug use. Ann Arbor: Institute for Social Research, University of Michigan.
- Gray, K. M., & Squeglia, L. M. (2018). Research Review: What have we learned about adolescent substance use? Journal of Child Psychology and Psychiatry, 59(6), 618–627. https://doi.org/10.1111/jcpp.12783
- American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596
- World Health Organization. (2018). The ICD-11 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. London: World Health Organization.
- Saunders, John B. (2017-07). "Substance use and addictive disorders in DSM-5 and ICD 10 and the draft ICD 11". Current Opinion in Psychiatry 30 (4): 227–237. doi:10.1097/YCO.0000000000000332. ISSN 0951-7367. https://journals.lww.com/00001504-201707000-00002.
- Substance Abuse and Mental Health Services Administration. (2016). Impact of the DSM-IV to DSM-5 Changes on the National Survey on Drug Use and Health. CBHSQ Methodology Report. Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, Rockville, MD.
- Hasin, D. S., O’Brien, C. P., Auriacombe, M., Borges, G., Bucholz, K., Budney, A., Compton, W. M., Crowley, T., Ling, W., Petry, N. M., Schuckit, M., & Grant, B. F. (2013). DSM-5 criteria for substance use disorders: Recommendations and rationale. American Journal of Psychiatry, 170(8), 834–851. https://doi.org/10.1176/appi.ajp.2013.12060782
- Grant, Jon E.; Chamberlain, Samuel R. (2016-08). "Expanding the definition of addiction: DSM-5 vs. ICD-11". CNS Spectrums 21 (4): 300–303. doi:10.1017/S1092852916000183. ISSN 1092-8529. PMID 27151528. PMC PMC5328289. https://www.cambridge.org/core/product/identifier/S1092852916000183/type/journal_article.
- Reed, G. M. et al. (2019). Innovations and changes in the ICD-11 classification of mental, behavioural and neurodevelopmental disorders. World Psychiatry, 18(1), 3–19. https://doi.org/10.1002/wps.20611
- "ICD-11 - Mortality and Morbidity Statistics". icd.who.int. Retrieved 2020-09-05.
- Mack, K.A., Jones, C.M., & Ballesteros, M.F. (2017). Illicit Drug Use, Illicit Drug Use Disorders, and Drug Overdose Deaths in Metropolitan and Nonmetropolitan Areas - United States. American Journal of Transplantation, 17(12), 1-12. https://www.cdc.gov/mmwr/volumes/66/ss/ss6619a1.htm
- First, Michael B.; Reed, Geoffrey M.; Hyman, Steven E.; Saxena, Shekhar (2015-02). "The development of the ICD-11 Clinical Descriptions and Diagnostic Guidelines for Mental and Behavioural Disorders". World Psychiatry 14 (1): 82–90. doi:10.1002/wps.20189. PMID 25655162. PMC PMC4329901. http://doi.wiley.com/10.1002/wps.20189.
- Cuthbert, Bruce N; Insel, Thomas R (2013-12). "Toward the future of psychiatric diagnosis: the seven pillars of RDoC". BMC Medicine 11 (1): 126. doi:10.1186/1741-7015-11-126. ISSN 1741-7015. PMID 23672542. PMC PMC3653747. http://bmcmedicine.biomedcentral.com/articles/10.1186/1741-7015-11-126.
- Sanislow, Charles A.; Pine, Daniel S.; Quinn, Kevin J.; Kozak, Michael J.; Garvey, Marjorie A.; Heinssen, Robert K.; Wang, Philip Sung-En; Cuthbert, Bruce N. (2010). "Developing constructs for psychopathology research: Research domain criteria.". Journal of Abnormal Psychology 119 (4): 631–639. doi:10.1037/a0020909. ISSN 1939-1846. http://doi.apa.org/getdoi.cfm?doi=10.1037/a0020909.
- Clark, Lee Anna; Cuthbert, Bruce; Lewis-Fernández, Roberto; Narrow, William E.; Reed, Geoffrey M. (2017-11). "Three Approaches to Understanding and Classifying Mental Disorder: ICD-11, DSM-5 , and the National Institute of Mental Health’s Research Domain Criteria (RDoC)". Psychological Science in the Public Interest 18 (2): 72–145. doi:10.1177/1529100617727266. ISSN 1529-1006. http://journals.sagepub.com/doi/10.1177/1529100617727266.
- Kwako, Laura E.; Momenan, Reza; Litten, Raye Z.; Koob, George F.; Goldman, David (2016-08). "Addictions Neuroclinical Assessment: A Neuroscience-Based Framework for Addictive Disorders". Biological Psychiatry 80 (3): 179–189. doi:10.1016/j.biopsych.2015.10.024. PMID 26772405. PMC PMC4870153. https://linkinghub.elsevier.com/retrieve/pii/S0006322315009543.
- Brooks, Samantha J.; Lochner, Christine; Shoptaw, Steve; Stein, Dan J. (2017-01-01). Calvey, Tanya. ed. Progress in Brain Research (in en). Brain Research in Addiction. 235. Elsevier. pp. 177–218. doi:10.1016/bs.pbr.2017.08.002. http://www.sciencedirect.com/science/article/pii/S0079612317301036.
- Koob, George F; Volkow, Nora D (2016-08). "Neurobiology of addiction: a neurocircuitry analysis". The Lancet Psychiatry 3 (8): 760–773. doi:10.1016/S2215-0366(16)00104-8. PMID 27475769. PMC PMC6135092. https://linkinghub.elsevier.com/retrieve/pii/S2215036616001048.
- Litten, Raye Z.; Ryan, Megan L.; Falk, Daniel E.; Reilly, Matthew; Fertig, Joanne B.; Koob, George F. (2015-04). "Heterogeneity of Alcohol Use Disorder: Understanding Mechanisms to Advance Personalized Treatment". Alcoholism: Clinical and Experimental Research 39 (4): 579–584. doi:10.1111/acer.12669. http://doi.wiley.com/10.1111/acer.12669.
- Votaw, Victoria R.; Pearson, Matthew R.; Stein, Elena; Witkiewitz, Katie (2020). "The Addictions Neuroclinical Assessment Negative Emotionality Domain Among Treatment-Seekers with Alcohol Use Disorder: Construct Validity and Measurement Invariance". Alcoholism: Clinical and Experimental Research 44 (3): 679–688. doi:10.1111/acer.14283. ISSN 1530-0277. PMID 31957027. PMC PMC7069798. https://onlinelibrary.wiley.com/doi/abs/10.1111/acer.14283.
- Voon, Valerie; Grodin, Erica; Mandali, Alekhya; Morris, Laurel; Doñamayor, Nuria; Weidacker, Kathrin; Kwako, Laura; Goldman, David et al. (2020-06). "Addictions NeuroImaging Assessment (ANIA): Towards an integrative framework for alcohol use disorder". Neuroscience & Biobehavioral Reviews 113: 492–506. doi:10.1016/j.neubiorev.2020.04.004. https://linkinghub.elsevier.com/retrieve/pii/S0149763419311492.
- Carcone, Dean; Ruocco, Anthony C. (2017-03-03). "Six Years of Research on the National Institute of Mental Health’s Research Domain Criteria (RDoC) Initiative: A Systematic Review". Frontiers in Cellular Neuroscience 11. doi:10.3389/fncel.2017.00046. ISSN 1662-5102. PMID 28316565. PMC PMC5334510. http://journal.frontiersin.org/article/10.3389/fncel.2017.00046/full.
- Miech, R. A., Johnston, L. D., O’Malley, P. M., Bachman, J. G., Schulenberg, J. E., & Patrick, M. E. (2020). Monitoring the Future national survey results on drug use, 1975–2019: Volume I, Secondary school students. Ann Arbor: Institute for Social Research, The University of Michigan. Available at http://monitoringthefuture.org/pubs.html#monographs
- Johnston, L. D., Miech, R. A., O’Malley, P. M., Bachman, J. G., Schulenberg, J. E., & Patrick, M. E. (2019). Monitoring the future national survey results on drug use 1978-2018: Overview, key findings on adolescent drug use. Ann Arbor: Institute for Social Research, University of Michigan.
- Substance Abuse and Mental Health Services Administration. (2019). Key substance use and mental health indicators in the United States: Results from the 2018 National Survey on Drug Use and Health (HHS Publication No. PEP19-5068, NSDUH Series H-54). Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. Retrieved from https://store.samhsa.gov/product/key-substance-use-and-mental-health-indicators-in-the-united-states-results-from-the-2018-national-survey-on-Drug-Use-and-Health/PEP19-5068
- Compton WM, Han B, Jones CM, Blanco C. Cannabis use disorders among adults in the United States during a time of increasing use of cannabis. Drug Alcohol Depend. 2019 Nov 1;204:107468. doi: 10.1016/j.drugalcdep.2019.05.008. Epub 2019 Sep 12. PMID: 31586809; PMCID: PMC7028308.
- Chen, Pan; Jacobson, Kristen C. (2012-02). "Developmental Trajectories of Substance Use From Early Adolescence to Young Adulthood: Gender and Racial/Ethnic Differences". Journal of Adolescent Health 50 (2): 154–163. doi:10.1016/j.jadohealth.2011.05.013. PMID 22265111. PMC PMC3264901. https://linkinghub.elsevier.com/retrieve/pii/S1054139X11001923.
- Treatment Methods & Evidence-Based Practices. National Association of Addiction Treatment Providers. https://www.naatp.org/evidence-based-addiction-treatment
- Marshal, Michael P.; Friedman, Mark S.; Stall, Ron; King, Kevin M.; Miles, Jonathan; Gold, Melanie A.; Bukstein, Oscar G.; Morse, Jennifer Q. (2008-04). "Sexual orientation and adolescent substance use: a meta-analysis and methodological review". Addiction 103 (4): 546–556. doi:10.1111/j.1360-0443.2008.02149.x. ISSN 0965-2140. PMID 18339100. PMC PMC2680081. http://doi.wiley.com/10.1111/j.1360-0443.2008.02149.x.
- Aarons, Gregory A.; Brown, Sandra A.; Hough, Richard L.; Garland, Ann F.; Wood, Patricia A. (2001-04). "Prevalence of Adolescent Substance Use Disorders Across Five Sectors of Care". Journal of the American Academy of Child & Adolescent Psychiatry 40 (4): 419–426. doi:10.1097/00004583-200104000-00010. https://linkinghub.elsevier.com/retrieve/pii/S0890856709603907.
- Medlow, Sharon; Klineberg, Emily; Steinbeck, Kate (2014-07-01). "The health diagnoses of homeless adolescents: A systematic review of the literature". Journal of Adolescence 37 (5): 531–542. doi:10.1016/j.adolescence.2014.04.003. ISSN 0140-1971. http://www.sciencedirect.com/science/article/pii/S0140197114000554.
- Armstrong, T. D., & Costello, E. J. (2002). Community studies on adolescent substance use, abuse, or dependence and psychiatric comorbidity. Journal of Consulting and Clinical Psychology, 70(6), 1224–1239. https://doi.org/10.1037/0022-006X.70.6.1224
- NIDA. 2020, May 28. Part 1: The Connection Between Substance Use Disorders and Mental Illness. Retrieved from https://www.drugabuse.gov/publications/research-reports/common-comorbidities-substance-use-disorders/part-1-connection-between-substance-use-disorders-mental-illness on 2020, December 9
- Schulte, M. T., & Hser, Y. (2013). Substance use and associated health conditions throughout the lifespan. Public Health Reviews, 35(2), 3. https://doi.org/10.1007/BF03391702
- Conway, Kevin P.; Swendsen, Joel; Husky, Mathilde M.; He, Jian-Ping; Merikangas, Kathleen R. (2016-04). "Association of Lifetime Mental Disorders and Subsequent Alcohol and Illicit Drug Use: Results From the National Comorbidity Survey–Adolescent Supplement". Journal of the American Academy of Child & Adolescent Psychiatry 55 (4): 280–288. doi:10.1016/j.jaac.2016.01.006. ISSN 0890-8567. https://doi.org/10.1016/j.jaac.2016.01.006.
- Chan, Ya-Fen; Dennis, Michael L.; Funk, Rodney R. (2008-01). "Prevalence and comorbidity of major internalizing and externalizing problems among adolescents and adults presenting to substance abuse treatment". Journal of Substance Abuse Treatment 34 (1): 14–24. doi:10.1016/j.jsat.2006.12.031. PMID 17574804. PMC PMC2238174. https://linkinghub.elsevier.com/retrieve/pii/S0740547207000918.
- Brewer, Stanley; Godley, Mark D.; Hulvershorn, Leslie A. (2017-01). "Treating Mental Health and Substance Use Disorders in Adolescents: What Is on the Menu?". Current Psychiatry Reports 19 (1): 5. doi:10.1007/s11920-017-0755-0. ISSN 1523-3812. http://link.springer.com/10.1007/s11920-017-0755-0.
- "Key Substance Use and Mental Health Indicators in the United States: Results from the 2018 National Survey on Drug Use and Health | Publications and Digital Products". store.samhsa.gov. Retrieved 2020-12-12.
- Schulenberg J., Patrick M.E., Maslowsky J., Maggs J.L. (2014) The Epidemiology and Etiology of Adolescent Substance Use in Developmental Perspective. In: Lewis M., Rudolph K. (eds) Handbook of Developmental Psychopathology. Springer, Boston, MA. https://doi-org.libproxy.lib.unc.edu/10.1007/978-1-4614-9608-3_30
- Moffi tt, T. E., & Caspi, A. (2001). Childhood predictors differentiate life-course persistent and adolescence-limited antisocial pathways among males and females. Development and Psychopathology, 13 , 355–375.
- Lees, Briana; Meredith, Lindsay R.; Kirkland, Anna E.; Bryant, Brittany E.; Squeglia, Lindsay M. (05 2020). "Effect of alcohol use on the adolescent brain and behavior". Pharmacology, Biochemistry, and Behavior 192: 172906. doi:10.1016/j.pbb.2020.172906. ISSN 1873-5177. PMID 32179028. PMC 7183385. https://pubmed.ncbi.nlm.nih.gov/32179028.
- Chung, Tammy; Creswell, Kasey G.; Bachrach, Rachel; Clark, Duncan B.; Martin, Christopher S. (2018). "Adolescent Binge Drinking". Alcohol Research: Current Reviews 39 (1): 5–15. ISSN 2169-4796. PMID 30557142. PMC 6104966. https://pubmed.ncbi.nlm.nih.gov/30557142.
- Kaminer, Yifrah; Bukstein, Oscar G. (2011-03-17). Adolescent Substance Abuse: Psychiatric Comorbidity and High Risk Behaviors (in en). Routledge. ISBN 978-1-136-91501-7. https://books.google.com/books?hl=en&lr=&id=z4xaBwAAQBAJ&oi=fnd&pg=PA29&dq=course+of+adolescent+substance+use&ots=BDxRgx6TPA&sig=lwwVaGTutVhimol5srOE1Hhqsd8#v=onepage&q=course%20of%20adolescent%20substance%20use&f=false.
- Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality. Treatment Episode Data Set (TEDS): 2005-2015. National Admissions to Substance Abuse Treatment Services. BHSIS Series S-91, HHS Publication No. (SMA) 17-5037. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2017.
- SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2018 and 2019, Table 5.10B. https://www.samhsa.gov/data/report/2019-nsduh-detailed-tables
- Williams, R. J., & Chang, S. Y. (2000). A comprehensive and comparative review of adolescent substance abuse treatment outcome. Clinical Psychology: Science and Practice, 7(2), 138–166. https://doi.org/10.1093/clipsy.7.2.138
- Douaihy, A., & Daley, D. (2013). Substance use disorders. ProQuest Ebook Central https://ebookcentral-proquest-com.libproxy.lib.unc.edu. pp. 250.
- Loree, A. M., Lundahl, L. H., & Ledgerwood, D. M. (2015). Impulsivity as a predictor of treatment outcome in substance use disorders: Review and synthesis. Drug and Alcohol Review, 34(2), 119–134. https://doi.org/10.1111/dar.12132
- Bukstein, O. G. (2005). Practice parameter for the assessment and treatment of children and adolescents with substance use disorders. Journal of the American Academy of Child & Adolescent Psychiatry, 44(6), 609–621. https://doi.org/10.1097/01.chi.0000159135.33706.37
- McMahon, T.J., & Luthar, S.S. (2006). Patterns and Correlates of Substance Use Among Affluent, Suburban High School Students. Journal of Clinical Child and Adolescent Psychology, 35(1), 72-89. doi: 10.1207/s15374424jccp3501_7
- Daughters, Stacey B.; Reynolds, Elizabeth K.; MacPherson, Laura; Kahler, Christopher W.; Danielson, Carla K.; Zvolensky, Michael; Lejuez, C. W. (2009-03-01). "Distress tolerance and early adolescent externalizing and internalizing symptoms: The moderating role of gender and ethnicity". Behaviour Research and Therapy 47 (3): 198–205. doi:10.1016/j.brat.2008.12.001. ISSN 0005-7967. PMID 19135649. PMC PMC2653593. http://www.sciencedirect.com/science/article/pii/S0005796708002684.
- Cornelius, J. R., Maisto, S. A., Pollock, N. K., Martin, C. S., Salloum, I. M., Lynch, K. G., & Clark, D. B. (2003). Rapid relapse generally follows treatment for substance use disorders among adolescents. Addictive Behaviors, 28(2), 381–386. https://doi.org/10.1016/S0306-4603(01)00247-7
- Douglas Coatsworth, J., Santisteban, D. A., Mcbride, C. K., & Szapocznik, J. (2001). Brief strategic family therapy versus community control: Engagement, retention, and an exploration of the moderating role of adolescent symptom severity. Family Process, 40(3), 313-332. https://doi.org/10.1111/j.1545-5300.2001.4030100313.x
- Youngstrom, Eric A.; Meter, Anna Van; Frazier, Thomas W.; Hunsley, John; Prinstein, Mitchell J.; Ong, Mian-Li; Youngstrom, Jennifer K. (2017). "Evidence-Based Assessment as an Integrative Model for Applying Psychological Science to Guide the Voyage of Treatment". Clinical Psychology: Science and Practice 24 (4): 331–363. doi:10.1111/cpsp.12207. ISSN 1468-2850. https://onlinelibrary.wiley.com/doi/abs/10.1111/cpsp.12207.
- Levy, Sharon J. L.; Williams, Janet F.; Prevention, Committee on Substance Use And (2016-07-01). "Substance Use Screening, Brief Intervention, and Referral to Treatment". Pediatrics 138 (1). doi:10.1542/peds.2016-1211. ISSN 0031-4005. PMID 27325634. https://pediatrics.aappublications.org/content/138/1/e20161211.
- Chung, T., & Wang, F. (2020). Assessment of adolescent substance use problems In E. A. Youngstrom, M. J. Prinstein, E. J. Mash, & R. Barkley (Eds.), Assessment of Disorders in Childhood and Adolescence (5th ed., pp. 543-568). New York: Guilford Press.
- American Academy of Pediatrics. (2016). Substance Use Screen and Intervention Implementation Guide: No Amount of Substance Use Is Safe for Adolescents. https://www.aap.org/en-us/Documents/substance_use_screening_implementation.pdf
- Kuntsche, Emmanuel; Kuntsche, Sandra (2009-11-17). "Development and Validation of the Drinking Motive Questionnaire Revised Short Form (DMQ–R SF)". Journal of Clinical Child & Adolescent Psychology 38 (6): 899–908. doi:10.1080/15374410903258967. ISSN 1537-4416. http://www.tandfonline.com/doi/abs/10.1080/15374410903258967.
- "APA PsycNet". doi.apa.org. doi:10.1037/0022-006x.51.3.390. Retrieved 2020-09-14.
- Levy, Sharon; Weiss, Roger; Sherritt, Lon; Ziemnik, Rosemary; Spalding, Allegra; Van Hook, Shari; Shrier, Lydia A. (2014-09-01). "An Electronic Screen for Triaging Adolescent Substance Use by Risk Levels". JAMA Pediatrics 168 (9): 822. doi:10.1001/jamapediatrics.2014.774. ISSN 2168-6203. PMID 25070067. PMC PMC4270364. http://archpedi.jamanetwork.com/article.aspx?doi=10.1001/jamapediatrics.2014.774.
- Kelly, Sharon M.; Gryczynski, Jan; Mitchell, Shannon Gwin; Kirk, Arethusa; O'Grady, Kevin E.; Schwartz, Robert P. (2014-05). "Validity of brief screening instrument for adolescent tobacco, alcohol, and drug use". Pediatrics 133 (5): 819–826. doi:10.1542/peds.2013-2346. ISSN 1098-4275. PMID 24753528. PMC 4006430. https://www.ncbi.nlm.nih.gov/pubmed/24753528.
- Dennis, Michael L.; Chan, Ya-Fen; Funk, Rodney R. (2006-01). "Development and Validation of the GAIN Short Screener (GSS) for Internalizing, Externalizing and Substance Use Disorders and Crime/Violence Problems Among Adolescents and Adults". American Journal on Addictions 15 (s1): 80–91. doi:10.1080/10550490601006055. ISSN 1055-0496. http://doi.wiley.com/10.1080/10550490601006055.
- Knight, John R.; Sherritt, Lon; Shrier, Lydia A.; Harris, Sion Kim; Chang, Grace (2002-06-01). "Validity of the CRAFFT Substance Abuse Screening Test Among Adolescent Clinic Patients". Archives of Pediatrics & Adolescent Medicine 156 (6): 607. doi:10.1001/archpedi.156.6.607. ISSN 1072-4710. http://archpedi.jamanetwork.com/article.aspx?doi=10.1001/archpedi.156.6.607.
- Mitchell, Shannon Gwin; Kelly, Sharon M.; Gryczynski, Jan; Myers, C. Patrick; O'Grady, Kevin E.; Kirk, Arethusa S.; Schwartz, Robert P. (2014). "The CRAFFT cut-points and DSM-5 criteria for alcohol and other drugs: a reevaluation and reexamination". Substance Abuse 35 (4): 376–380. doi:10.1080/08897077.2014.936992. ISSN 1547-0164. PMID 25036144. PMC 4268117. https://www.ncbi.nlm.nih.gov/pubmed/25036144.
- Knight, John R.; Sherritt, Lon; Harris, Sion Kim; Gates, Elizabeth C.; Chang, Grace (2003-01). "Validity of brief alcohol screening tests among adolescents: a comparison of the AUDIT, POSIT, CAGE, and CRAFFT". Alcoholism, Clinical and Experimental Research 27 (1): 67–73. doi:10.1097/01.ALC.0000046598.59317.3A. ISSN 0145-6008. PMID 12544008. https://www.ncbi.nlm.nih.gov/pubmed/12544008.
- Santisteban, Daniel A.; Tejeda, Manuel; Dominicis, Carmenchu; Szapocznik, José (1999-01-01). "An Efficient Tool for Screening for Maladaptive Family Functioning in Adolescent Drug Abusers: The Problem Oriented Screening Instrument for Teenagers". The American Journal of Drug and Alcohol Abuse 25 (2): 197–206. doi:10.1081/ADA-100101855. ISSN 0095-2990. https://doi.org/10.1081/ADA-100101855.
- Kaminer, Yifrah; Bukstein, Oscar; Tarter, Ralph E. (1991-01). "The Teen-Addiction Severity Index: Rationale and Reliability". International Journal of the Addictions 26 (2): 219–226. doi:10.3109/10826089109053184. ISSN 0020-773X. http://www.tandfonline.com/doi/full/10.3109/10826089109053184.
- Dennis, M., Titus, J., White, M., Unsicker, J. & Hodkgins, D. (2002). Global Appraisal of Individual Needs (GAIN): Administration Guide for the GAIN and Related Measures. Bloomington, IL: Chestnut Health Systems. [Online] Available: www.chestnut.org/li/gain/gadm1299.pdf.
- White, H R; Labouvie, E W (1989-01-01). "Towards the assessment of adolescent problem drinking.". Journal of Studies on Alcohol 50 (1): 30–37. doi:10.15288/jsa.1989.50.30. ISSN 0096-882X. https://www.jsad.com/doi/10.15288/jsa.1989.50.30.
- Knapp, Ashley A.; Babbin, Steven F.; Budney, Alan J.; Walker, Denise D.; Stephens, Robert S.; Scherer, Emily A.; Stanger, Catherine (04 2018). "Psychometric assessment of the marijuana adolescent problem inventory". Addictive Behaviors 79: 113–119. doi:10.1016/j.addbeh.2017.12.013. ISSN 1873-6327. PMID 29288984. PMC 5851012. https://www.ncbi.nlm.nih.gov/pubmed/29288984.
- Sobell, L. C., & Sobell, M. B. (1995). Alcohol Timeline Followback Users’ Manual. Toronto, Canada: Addiction Research Foundation.
- Dennis, Michael L.; Funk, Rodney; Godley, Susan Harrington; Godley, Mark D.; Waldron, Holly (2004-11). "Cross-validation of the alcohol and cannabis use measures in the Global Appraisal of Individual Needs (GAIN) and Timeline Followback (TLFB; Form 90) among adolescents in substance abuse treatment". Addiction (Abingdon, England) 99 Suppl 2: 120–128. doi:10.1111/j.1360-0443.2004.00859.x. ISSN 0965-2140. PMID 15488110. https://www.ncbi.nlm.nih.gov/pubmed/15488110.
- Lewis-Esquerre, Johanna M.; Colby, Suzanne M.; Tevyaw, Tracy O'Leary; Eaton, Cheryl A.; Kahler, Christopher W.; Monti, Peter M. (2005-07). "Validation of the timeline follow-back in the assessment of adolescent smoking". Drug and Alcohol Dependence 79 (1): 33–43. doi:10.1016/j.drugalcdep.2004.12.007. ISSN 0376-8716. PMID 15943942. https://www.ncbi.nlm.nih.gov/pubmed/15943942.
- Cooper, M. L. (1994). Motivations for alcohol use among adolescents: Development and validation of a four-factor model. Psychological Assessment, 6(2), 117–128. https://doi.org/10.1037/1040-35220.127.116.11
- Lee, Christine M.; Neighbors, Clayton; Hendershot, Christian S.; Grossbard, Joel R. (2009-03). "Development and preliminary validation of a comprehensive marijuana motives questionnaire". Journal of Studies on Alcohol and Drugs 70 (2): 279–287. doi:10.15288/jsad.2009.70.279. ISSN 1937-1888. PMID 19261240. PMC 2653613. https://www.ncbi.nlm.nih.gov/pubmed/19261240.
- Biener, L.; Abrams, D. B. (1991). "The Contemplation Ladder: validation of a measure of readiness to consider smoking cessation". Health Psychology: Official Journal of the Division of Health Psychology, American Psychological Association 10 (5): 360–365. doi:10.1037//0278-618.104.22.1680. ISSN 0278-6133. PMID 1935872. https://www.ncbi.nlm.nih.gov/pubmed/1935872.
- Moyers, Theresa B.; Martin, Tim; Houck, Jon M.; Christopher, Paulette J.; Tonigan, J. Scott (2009-12). "From in-session behaviors to drinking outcomes: a causal chain for motivational interviewing". Journal of Consulting and Clinical Psychology 77 (6): 1113–1124. doi:10.1037/a0017189. ISSN 1939-2117. PMID 19968387. PMC 2819223. https://www.ncbi.nlm.nih.gov/pubmed/19968387.
- Slavet, James D.; Stein, L. a. R.; Colby, Suzanne M.; Barnett, Nancy P.; Monti, Peter M.; Golembeske, Charles; Lebeau-Craven, Rebecca (2006-06-09). "The Marijuana Ladder: measuring motivation to change marijuana use in incarcerated adolescents". Drug and Alcohol Dependence 83 (1): 42–48. doi:10.1016/j.drugalcdep.2005.10.007. ISSN 0376-8716. PMID 16289930. PMC 2754131. https://www.ncbi.nlm.nih.gov/pubmed/16289930.
- Maisto, Stephen A.; Krenek, Marketa; Chung, Tammy; Martin, Christopher S.; Clark, Duncan; Cornelius, Jack (2011-12). "A comparison of the concurrent and predictive validity of three measures of readiness to change alcohol use in a clinical sample of adolescents.". Psychological Assessment 23 (4): 983–994. doi:10.1037/a0024136. ISSN 1939-134X. PMID 21767028. PMC PMC3433156. http://doi.apa.org/getdoi.cfm?doi=10.1037/a0024136.
- Stone, Andrea L.; Latimer, William W. (2005-01). "Adolescent Substance Use Assessment: Concordance Between Tools Using Self-Administered and Interview Formats". Substance Use & Misuse 40 (12): 1865–1874. doi:10.1080/10826080500260925. ISSN 1082-6084. http://www.tandfonline.com/doi/full/10.1080/10826080500260925.
- Donohue, Brad; Hill, Heather H.; Azrin, Nathan H.; Cross, Chad; Strada, Marilyn J. (2007-09). "Psychometric support for contemporaneous and retrospective youth and parent reports of adolescent marijuana use frequency in an adolescent outpatient treatment population". Addictive Behaviors 32 (9): 1787–1797. doi:10.1016/j.addbeh.2006.12.005. https://linkinghub.elsevier.com/retrieve/pii/S0306460306003856.
- Williams, Robert J.; Nowatzki, Nadine (2005-01). "Validity of Adolescent Self-Report of Substance Use". Substance Use & Misuse 40 (3): 299–311. doi:10.1081/JA-200049327. ISSN 1082-6084. http://www.tandfonline.com/doi/full/10.1081/JA-200049327.
- Buchan, Betty J.; L. Dennis, Michael; Tims, Frank M.; Diamond, Guy S. (2002-12). "Cannabis use: consistency and validity of self-report, on-site urine testing and laboratory testing". Addiction 97: 98–108. doi:10.1046/j.1360-0443.97.s01.1.x. http://doi.wiley.com/10.1046/j.1360-0443.97.s01.1.x.
- O’Leary Tevyaw, T., Spirito, A., Colby, S. M., & Monti, P. M. (2018). Motivational Enhancement in Medical Settings for Adolescent Substance Use. In P. M. Monti, S. M. Colby, & T. O'Leary Tevyaw (Eds.), Brief Interventions for Adolescent Alcohol and Substance Abuse (pp. 153-187). New York: Guilford.
- Mee-Lee D, Shulman GD, Fishman MJ, Gastfriend DR, Miller, eds. The ASAM Criteria: Treatment Criteria for Addictive, Substance-Related, and Co-Occurring Conditions. 3rd ed. Carson City, NV: The Change Companies; 2013. Copyright 2013 by the American Society of Addiction Medicine.
- National Institute on Drug Abuse. 2020, May 29. Principles of Drug Addiction Treatment: A Research-Based Guide (3rd ed.). National Institute of Health.
- Winters, Ken C.; Botzet, Andria M.; Fahnhorst, Tamara (2011-10). "Advances in Adolescent Substance Abuse Treatment". Current Psychiatry Reports 13 (5): 416–421. doi:10.1007/s11920-011-0214-2. ISSN 1523-3812. PMID 21701838. PMC PMC3166985. http://link.springer.com/10.1007/s11920-011-0214-2.
- Substance Abuse and Mental Health Services Administration. Improving Cultural Competence. Treatment Improvement Protocol (TIP) Series No. 59. HHS Publication No. (SMA) 14-4849. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2014.
- Cornelius, T., Earnshaw, V. A., Menino, D., Bogart, L. M., & Levy, S. (2017). Treatment motivation among caregivers and adolescents with substance use disorders. Journal of Substance Abuse Treatment, 75, 10–16. https://doi.org/10.1016/j.jsat.2017.01.003
- PhD, John F. Kelly; PhD, Mark G. Myers; PhD, Sandra A. Brown (2005-12-05). "The Effects of Age Composition of 12-Step Groups on Adolescent 12-Step Participation and Substance Use Outcome". Journal of Child & Adolescent Substance Abuse 15 (1): 63–72. doi:10.1300/J029v15n01_05. ISSN 1067-828X. PMID 18080000. PMC PMC2136436. https://doi.org/10.1300/J029v15n01_05.
- Azrin, N. H., Donohue, B., Besalel, V. A., Kogan, E. S., & Acierno, R. (1994). Youth drug abuse treatment: A controlled outcome study. Journal of Child & Adolescent Substance Abuse, 3(3), 1–16. https://doi.org/10.1300/J029v03n03_01
- Zajac, Kristyn; Randall, Jeff; Swenson, Cynthia Cupit (2015-07). "Multisystemic Therapy for Externalizing Youth". Child and Adolescent Psychiatric Clinics of North America 24 (3): 601–616. doi:10.1016/j.chc.2015.02.007. ISSN 1558-0490. PMID 26092742. PMC 4475575. https://pubmed.ncbi.nlm.nih.gov/26092742.
- Henggeler, S. W., Clingempeel, W. G., Brondino, M. J., & Pickrel, S. G. (2002). Four-year follow-up of multisystemic therapy with substance-abusing and substance-dependent juvenile offenders. Journal of the American Academy of Child and Adolescent Psychiatry, 41(7), 868–874. https://doi.org/10.1097/00004583-200207000-00021
- Huey, S. J.; Henggeler, S. W.; Brondino, M. J.; Pickrel, S. G. (2000-06). "Mechanisms of change in multisystemic therapy: reducing delinquent behavior through therapist adherence and improved family and peer functioning". Journal of Consulting and Clinical Psychology 68 (3): 451–467. ISSN 0022-006X. PMID 10883562. https://www.ncbi.nlm.nih.gov/pubmed/10883562.
- van der Stouwe, Trudy; Asscher, Jessica J.; Stams, Geert Jan J. M.; Deković, Maja; van der Laan, Peter H. (2014-08). "The effectiveness of Multisystemic Therapy (MST): a meta-analysis". Clinical Psychology Review 34 (6): 468–481. doi:10.1016/j.cpr.2014.06.006. ISSN 1873-7811. PMID 25047448. https://pubmed.ncbi.nlm.nih.gov/25047448.
- Liddle, Howard A.; Rowe, Cynthia L.; Dakof, Gayle A.; Ungaro, Rocio A.; Henderson, Craig E. (2004-03). "Early intervention for adolescent substance abuse: pretreatment to posttreatment outcomes of a randomized clinical trial comparing multidimensional family therapy and peer group treatment". Journal of Psychoactive Drugs 36 (1): 49–63. doi:10.1080/02791072.2004.10399723. ISSN 0279-1072. PMID 15152709. https://www.ncbi.nlm.nih.gov/pubmed/15152709.
- Liddle, H. A.; Dakof, G. A.; Parker, K.; Diamond, G. S.; Barrett, K.; Tejeda, M. (2001-11). "Multidimensional family therapy for adolescent drug abuse: results of a randomized clinical trial". The American Journal of Drug and Alcohol Abuse 27 (4): 651–688. doi:10.1081/ada-100107661. ISSN 0095-2990. PMID 11727882. https://www.ncbi.nlm.nih.gov/pubmed/11727882.
- Woody, George E.; Poole, Sabrina A.; Subramaniam, Geetha; Dugosh, Karen; Bogenschutz, Michael; Abbott, Patrick; Patkar, Ashwin; Publicker, Mark et al. (2008-11-05). "Extended vs short-term buprenorphine-naloxone for treatment of opioid-addicted youth: a randomized trial". JAMA 300 (17): 2003–2011. doi:10.1001/jama.2008.574. ISSN 1538-3598. PMID 18984887. PMC 2610690. https://www.ncbi.nlm.nih.gov/pubmed/18984887.
- Marsch, Lisa A.; Bickel, Warren K.; Badger, Gary J.; Stothart, Marne E.; Quesnel, Kimberly J.; Stanger, Catherine; Brooklyn, John (2005-10). "Comparison of pharmacological treatments for opioid-dependent adolescents: a randomized controlled trial". Archives of General Psychiatry 62 (10): 1157–1164. doi:10.1001/archpsyc.62.10.1157. ISSN 0003-990X. PMID 16203961. https://www.ncbi.nlm.nih.gov/pubmed/16203961.
- Stephens-Davidowitz, Seth; Pinker, Steven. Everybody lies : big data, new data, and what the Internet can tell us about who we really are (First ed.). [New York, NY]. ISBN 978-0-06-239085-1. OCLC 985108386. https://www.worldcat.org/oclc/985108386.
- Straus, Sharon E.; Glasziou, Paul; Richardson, W. Scott (Warren Scott); Haynes, R. Brian. Evidence-based medicine : how to practice and teach EBM (Fifth ed.). Edinburgh. ISBN 978-0-7020-6296-4. OCLC 999475258. https://www.worldcat.org/oclc/999475258.
- Heilman, James M; West, Andrew G (2015-03-04). "Wikipedia and Medicine: Quantifying Readership, Editors, and the Significance of Natural Language". Journal of Medical Internet Research 17 (3): e62. doi:10.2196/jmir.4069. ISSN 1438-8871. PMID 25739399. PMC PMC4376174. http://www.jmir.org/2015/3/e62/.
- Shafee, Thomas; Masukume, Gwinyai; Kipersztok, Lisa; Das, Diptanshu; Häggström, Mikael; Heilman, James (2017-11-01). "Evolution of Wikipedia’s medical content: past, present and future". J Epidemiol Community Health 71 (11): 1122–1129. doi:10.1136/jech-2016-208601. ISSN 0143-005X. PMID 28847845. PMC PMC5847101. https://jech.bmj.com/content/71/11/1122.
- Burnam, M. Audrey; Watkins, Katherine E. (2006-05). "Substance Abuse With Mental Disorders: Specialized Public Systems And Integrated Care". Health Affairs 25 (3): 648–658. doi:10.1377/hlthaff.25.3.648. ISSN 0278-2715. http://www.healthaffairs.org/doi/10.1377/hlthaff.25.3.648.
- Society for Adolescent Health and Medicine (SAHM). (2020). Substance use resources for adolescents and young adults. https://www.adolescenthealth.org/Resources/Clinical-Care-Resources/Substance-Use/Substance-Use-Resources-For-Adolesc.aspx
- Canady, Valerie A. (2020). "Field lauds congressional support of 988 suicide prevention, MH crisis line". Mental Health Weekly 30 (37): 1–3. doi:10.1002/mhw.32517. ISSN 1556-7583. https://onlinelibrary.wiley.com/doi/abs/10.1002/mhw.32517.
- National drug abuse hotline and treatment locator service. (2020). Higher ED Centers. Retrieved March 22, 2020, from https://www.higheredcenter.org/
- Substance Abuse and Mental Health Services Administration (SAMHSA).(2020). Millions of Americans have a substance use disorder. Find treatment. https://findtreatment.gov/
- Bergman, Brandon G.; Kelly, John F.; Fava, Maurizio; Eden Evins, A. (2021-02). "Online recovery support meetings can help mitigate the public health consequences of COVID-19 for individuals with substance use disorder". Addictive Behaviors 113: 106661. doi:10.1016/j.addbeh.2020.106661. PMID 33038682. PMC PMC7493730. https://linkinghub.elsevier.com/retrieve/pii/S0306460320307917.
- Easterseals. (2020). CARES. Easterseals UCP.https://www.easterseals.com/NCVA/our-programs/childrens-services/cares.html
- Duke University School of Medicine. (2020). Duke center for adolescent and youth substance use treatment (CAST). Duke integrated pediatric mental health. https://ipmh.duke.edu/content/cast
- UNC Health Care. (2020). Alcohol and substance abuse. UNC medical center. https://www.uncmedicalcenter.org/uncmc/care-treatment/alcohol-and-substance-abuse/
- English, Abigail (2010). State minor consent laws : a summary. Center for Adolescent Health & the Law. ISBN 0974410829. OCLC 690022211. https://www.worldcat.org/oclc/690022211.
- Ornell, Felipe; Moura, Helena Ferreira; Scherer, Juliana Nichterwitz; Pechansky, Flavio; Kessler, Felix Henrique Paim; von Diemen, Lisia (2020-07). "The COVID-19 pandemic and its impact on substance use: Implications for prevention and treatment". Psychiatry Research 289: 113096. doi:10.1016/j.psychres.2020.113096. PMID 32405115. PMC PMC7219362. https://linkinghub.elsevier.com/retrieve/pii/S0165178120309033.
- Volkow, Nora D. (2020-04-02). "Collision of the COVID-19 and Addiction Epidemics". Annals of Internal Medicine 173 (1): 61–62. doi:10.7326/M20-1212. ISSN 0003-4819. PMID 32240293. PMC PMC7138334. https://www.acpjournals.org/doi/10.7326/M20-1212.
- Dumas, Tara M.; Ellis, Wendy; Litt, Dana M. (2020-09). "What Does Adolescent Substance Use Look Like During the COVID-19 Pandemic? Examining Changes in Frequency, Social Contexts, and Pandemic-Related Predictors". Journal of Adolescent Health 67 (3): 354–361. doi:10.1016/j.jadohealth.2020.06.018. ISSN 1054-139X. PMID 32693983. PMC PMC7368647. https://doi.org/10.1016/j.jadohealth.2020.06.018.
- Youngstrom, Eric A.; Hinshaw, Stephen P.; Stefana, Alberto; Chen, Jun; Michael, Kurt; Van Meter, Anna; Maxwell, Victoria; Michalak, Erin E. et al. (2020). "Working with Bipolar Disorder During the COVID-19 Pandemic: Both Crisis and Opportunity". WikiJournal of Medicine 7 (1): 4. doi:10.15347/WJM/2020.004. https://en.wikiversity.org/wiki/WikiJournal_of_Medicine/Working_with_Bipolar_Disorder_During_the_COVID-19_Pandemic:_Both_Crisis_and_Opportunity.