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Research led by people who use drugs: centering the expertise of lived experience

• Zach R. Salazar   ORCID: orcid.org/0000-0002-6211-835X 1 ,
• Louise Vincent 1 ,
• Mary C. Figgatt 2 , 3 ,
• Michael K. Gilbert 4 &
• Nabarun Dasgupta 2 , 3  

Substance Abuse Treatment, Prevention, and Policy volume  16 , Article number:  70 ( 2021 ) Cite this article

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Research collaborations between people who use drugs (PWUD) and researchers are largely underutilized, despite the long history of successful, community-led harm reduction interventions and growing health disparities experienced by PWUD. PWUD play a critical role in identifying emerging issues in the drug market, as well as associated health behaviors and outcomes. As such, PWUD are well positioned to meaningfully participate in all aspects of the research process, including population of research questions, conceptualization of study design, and contextualization of findings.

We argue PWUD embody unparalleled and current insight to drug use behaviors, including understanding of novel synthetic drug bodies and the dynamics at play in the drug market; they also hold intimate and trusting relationships with other PWUD. This perfectly situates PWUD to collaborate with researchers in investigation of drug use behaviors and development of harm reduction interventions. While PWUD have a history of mistrust with the medical community, community-led harm reduction organizations have earned their trust and are uniquely poised to facilitate research projects. We offer the North Carolina Survivors Union as one such example, having successfully conducted a number of projects with reputable research institutions. We also detail the fallacy of meaningful engagement posed by traditional mechanisms of capturing community voice. As a counter, we detail the framework developed and implemented by the union in hopes it may serve as guidance for other community-led organizations. We also situate research as a mechanism to diversify the job opportunities available to PWUD and offer a real-time example of the integration of these principles into public policy and direct service provision.

In order to effectively mitigate the risks posed by the fluid and volatile drug market, research collaborations must empower PWUD to play meaningful roles in the entirety of the research process. Historically, the most effective harm reduction interventions have been born of the innovation and heart possessed by PWUD; during the current overdose crisis, there is no reason to believe they will not continue to be.

Research collaborations between people who use drugs (PWUD) and researchers are underacknowledged, misinterpreted, and undervalued. The most effective evidence-based harm reduction interventions, such as needle-exchange [ 1 ], peer-delivered naloxone [ 2 ] and community-based drug checking [ 3 ], were designed and implemented by PWUD well before they had the backing of the greater public health community. PWUD play significant roles in identifying cross-disciplinary issues of import and contextualizing significance of findings. Therefore, collaborations with PWUD are necessary to produce effective and relevant research. Ultimately, we aim to argue the necessity of research collaborations with PWUD; detail the optimal positioning of harm reduction organizations in facilitating research projects; provide a framework for successfully conducting these partnerships; propose a potential career path for PWUD; and provide real-world application of the presented concepts.

Community contextualization

PWUD are experiencing a fluid illicit drug market where changes to products and potency can be extremely volatile, posing a series of unpredictable, and potentially deadly, risks to the consumer. The recent increase in novel synthetic drug types bodes ill for public health and safety because new psychoactive substances (e.g., fentanyl analogs) are frequently unknown by law enforcement and undetected by conventional drug screens, with associated health risks unfamiliar to public health. Evidently, though, people who consume these substances know what they are, or what they are intended to imitate, including what they look like, the places where they are sold, how much they cost, who is using them, methods and techniques for using (e.g., routes of administration), and the social network dynamics that facilitate contacts between consumers (i.e., dyadic pairings) [ 4 ].

The knowledge inhabited by PWUD, and the trusting and intimate relationships they have with other PWUD and their social networks, begs for collaboration in all areas of research involving illicit drug use or the population of PWUD. PWUD are needed at all stages of the research process: from conceptualizing ideas and constructing research questions to interpreting study findings and helping develop effective responses.

Situatedness of harm reduction organizations

PWUD are conventionally mistrusting and skeptical of medical professionals and social workers, and rightfully so, due to a long history of mistreatment and deeply ingrained stigma. Harm reduction organizations, such as syringe service programs (SSPs), and the workers who deliver services have secured the trust and respect of participants and have a unique opportunity to provide health care services and mobilize community involvement in research [ 5 , 6 ].

When researchers view PWUD solely as research subjects and within a strict binary of researcher/researched—where PWUD are interpolated as either vectors of information or a means to recruit study participants—they fail to recognize (or communicate) how circumstantial complications can influence health outcomes and how the combined factors of agent, host, and environment contribute to disease transmission and/or acquisition of injury. By collaborating with people who actually perform the drug use behaviors under investigation in a genuine and transparent relationship, all components of the research process described above are enhanced. For example, the North Carolina Survivors Union (NCSU), a robust, drug-user union in central North Carolina, maintains strong professional relationships with researchers and academic institutions and welcomes collaboration. NCSU has served as a subcontractor on numerous NIH, FDA, and industry-funded research projects. The union has been involved in cutting edge research led by PWUD, including hepatitis testing and linkage-to-care, fentanyl test strip distribution [ 3 ], and community-based drug checking. Successful collaboration between NCSU and external research organizations has been driven by attainment of genuine “meaningful collaboration.”

Tokenistic attempts at involving PWUD in research (i.e., advisory boards) might look good at face value, but refuse to give community members the power needed to make change and offer consequential insight to the research process. In fact, advisory boards can cause more harm than good, furthering the divide between PWUD and researchers. With this considered, NCSU has installed processes, largely informed by the principles of community driven research (CDR) [ 7 ], to avoid such experiences. Research collaborations begin with an informal meeting between NCSU and researchers to discuss objectives, methods, findings dissemination, party responsibilities, and other logistics. Project ideas are born out of mutual collaboration, as opposed to researchers approaching the organization with a fully developed project in hand. Instead, the proposed framework encourages community-initiated research questions, centering the needs of those performing the behaviors in question. This meeting lays the groundwork for a mutually beneficial and respectful collaboration, while developing relevant research ideas aimed to directly benefit the community. As projects materialize, infrastructure is created to allow for expression of needed modifications and expectations. Collaborations have resulted in conducting on-site needs assessment surveys, in-person interviews, development of health education materials, and more. Following project implementation, dispersal of results prioritizes community-based utilization. NCSU, along with its research partners, ensures undertaken projects will be as beneficial for community members as they are for academics.

Many other harm reduction programs like NCSU exist across the country. These organizations present a unique opportunity for collaborations between researchers and PWUD. In fact, researchers and PWUD should not be considered as two mutually exclusive roles. Rather, research institutions should make a concerted effort to hire PWUD and create opportunities for career growth. This may be sought through a number of potential paths, including collaboration with community-led organizations who can facilitate ongoing, mutually beneficial relationships between PWUD and research institutions, and emphasis on recruiting PWUD who are in pursuit of careers in research through traditional channels (i.e., higher education and formal research training) to join staff. However, it is important to note institutional barriers lock many PWUD out of conventional mechanisms of research training, and consequently long-term employment in the field of research. Obstructions are frequently due to prior felony convictions, as the war on drugs has pushed so many PWUD into encounters with the criminal justice system. As such, it is imperative to the growth of the field of substance use research that research institutions learn to better navigate the line between accountability and flexibility. As long as research institutions uphold these obstacles to the advancement of PWUD in the field of research, they amplify the influence of the criminalization of substance use and inhibit maximized benefit of research efforts on public health. Still, we caution researchers from simply hiring or collaborating with PWUD without thorough thought about how to establish and maintain a relationship grounded in respect and openness, in addition to holding a mission to improve the health and wellbeing of PWUD.

Research as a career path for PWUD

Currently, the common career paths for PWUD accepted by society are limited to those serving other PWUD in social service settings, such as peer support specialists. While providing services to others can be beneficial to both the persons receiving and delivering the services, these jobs are often underpaid and can lack critical benefits that traditionally accompany other types of full-time employment (e.g., health insurance, retirement benefits) [ 8 ]. We argue research is another field in which employment of PWUD would be mutually beneficial. The field of research is filled with many accomplished individuals with respective areas of expertise. PWUD, too, hold their own area of expertise: drug use and the many related health factors and outcomes. Rather than stigmatize PWUD for their use, we should see them for their value as experts. Due to long held stigmatization of drug use, discrimination can present in the researcher themselves, their organizations, and the policies that fund research. Researchers may even suppress or withhold information about their own drug use in order to protect their professional reputation and employment status from drug-related stigma. Therefore, to change the landscape of drug use research, we argue it is the responsibility of researchers to enact change by creating employment opportunities for PWUD in which their expertise is valued and respected and where they are seen as equals with their colleagues [ 9 ].

To this end, the power imbalances between PWUD and formally trained researchers must be dismantled. While we would certainly encourage PWUD hoping to pursue research as a career path to follow continuing education and relevant certification opportunities, barriers to these formalized systems of education must be acknowledged. Furthermore, a credential or degree does not replace the invaluable experiential knowledge held by PWUD. As such, credentials and degrees should not serve as the standard by which we judge a person’s capacity to contribute to the research process. Rather, it is the responsibility of the researcher, and relevant partnering organizations, to empower PWUD to participate in the research process in a meaningful way. Dependent upon the research project, we recommend project and role specific training for PWUD, as well as equitable allocation of legitimate decision-making power. Likewise, it is essential researchers nurture long-lasting relationships with non-profits and other community-led organizations they intend to work with. As opposed to only interacting during the project period, which is not conducive to ongoing training for PWUD, enduring relationships foster continuing professional development as well as collaborations built in trust. These strategies will furnish PWUD with the skills and opportunities necessary to genuinely influence the research process.

To be clear: we are not suggesting researchers include any and all people who have used drugs. Instead, we are advocating for increasing the participation of PWUD who have the relevant experience and expertise with the drug types, consumption techniques, and environments being investigated. Particularly given the current fluidity of the drug market, those actively engaged are best situated to speak to present-day trends. Moreover, it is vital PWUD included in the research process possess the situational understanding to critically assess the current use environment and contribute to impactful investigation. These individuals are well positioned to provide accurate and timely information that can strengthen analyses of the drug, set, and setting factors that influence consumption behavior and negative health outcomes [ 10 ]. Drug user unions like NCSU are already playing an integral role in public health research by aiding researchers to better involve PWUD in research efforts. Concisely stated: something can be statistically meaningful when chasing p -values but be socially and medically irrelevant for effectiveness and successful implementation.

Representation and guidance from PWUD is also critical to translating scientific knowledge gained through research into improved public policies and direct service practices. Some public health authorities approach that translation process through advisory boards or other bodies with a nominal ‘voice’, but the inclusion of PWUD among bodies with a formal ‘vote’ remains rare. Oregon’s Drug Addiction Treatment and Recovery Act of 2020, passed by ballot initiative in November 2020, decriminalized possession of small amounts of controlled substances and redirected cannabis tax revenues to an Oversight and Accountability Council tasked with overseeing grants to implement Addiction Recovery Centers and increase access to community care [ 11 ]. The Oversight and Accountability Council is required to include at least two members, “who suffered or suffer from substance use disorder,” and while that language would be improved by centering on members’ lived experience without the characterization of ‘suffering’, the inclusion of people who use(d) drugs as voting members of a body empowered to direct public funding for drug-related health and social services provides an opportunity for increasingly equitable structures of public policy and governance.

Conclusions

If the goal, especially during a lethal overdose epidemic, is to conduct research that can contribute to the development of useful, evidence-based interventions the likes of needle exchange, lay naloxone distribution, onsite wound care, safer injection education, fentanyl test strips, and peer navigation, then it is plainly obvious researchers need to include and expand efforts to collaborate with PWUD. Given the rising rates of drug-involved morbidity and mortality, it is high time to include people who use drugs in public health efforts. Our lives depend on it.

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Abbreviations

• People who use drugs
• Syringe service programs

North Carolina Survivors Union

National Institutes of Health

U.S. Food and Drug Administration

• Community driven research

Heller D, Paone D. Access to sterile syringes for injecting drug users in new York City: politics and perception (1984-2010). Subst Use Misuse. 2011. https://doi.org/10.3109/10826084.2011.523319 .

Taha S, Maloney-Hall B, Buxton J. Lessons learned from the opioid crisis across the pillars of the Canadian drugs and substances strategy. Subst Abuse Treat Prev Policy. 2019. https://doi.org/10.1186/s13011-019-0220-7 .

Peiper NC, Duhart Clarke S, Vincent LB, Ciccarone D, Kral AH, Zibbell JE. Fentanyl test strips as an opioid overdose prevention strategy: findings from a syringe services program in the southeastern United States. Int J Drug Policy. 2019. https://doi.org/10.1016/j.drugpo.2018.08.007 .

Zibbell JE, Peiper NC, Duhart Clarke SE, Salazar ZR, Vincent LB, Kral AH, et al. Consumer discernment of fentanyl in illicit opioids confirmed by fentanyl test strips: lessons from a syringe services program in North Carolina. Int J Drug Policy. 2021. https://doi.org/10.1016/j.drugpo.2021.103128 .

Treloar C, Rance J, Yates K, Mao L. Trust and people who inject drugs: the perspectives of clients and staff of needle syringe programs. Int J Drug Policy. 2016. https://doi.org/10.1016/j.drugpo.2015.08.018 .

MacNeil J, Pauly B. Needle exchange as a safe haven in an unsafe world. Drug Alcohol Rev. 2011. https://doi.org/10.1111/j.1465-3362.2010.00188.x .

Simon C, Brothers S, Strichartz K, Coulter A, Voyles N, Herdlein A, et al. We are the researched, the researchers, and the discounted: the experiences of drug user activists as researchers. Int J Drug Policy. 2021. https://doi.org/10.1016/j.drugpo.2021.103364 .

People with Lived Expertise of Drug Use National Working Group, Austin T, Boyd J. Having a voice and saving lives: a qualitative survey on employment impacts of people with lived experience of drug use working in harm reduction. Harm Reduct J. 2021. https://doi.org/10.1186/s12954-020-00453-5 .

Jones N, Atterbury K, Byrne L, Carras M, Brown M, Phalen P. Lived experience, research leadership, and the transformation of mental health services: building a researcher pipeline. Psychiatr Serv. 2021. https://doi.org/10.1176/appi.ps.202000468 .

Dasgupta N. “He is the object of information”: the intersection of big data and the opioid crisis. Am J Public Health. 2018. https://doi.org/10.2105/AJPH.2018.30460 .

Drug Addiction Treatment and Recovery Act. http://oregonvotes.org/irr/2020/044text.pdf . Accessed 26 Apr 2021.

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Acknowledgements

We are appreciative of Dr. Jon E. Zibbell, who offered critical review and formative conversation in development of this article.

This project was supported in part through a U.S. Food and Drug Administration contract to the University of North Carolina (HHSF223201810183C). The funding organization was not involved in any aspect of the development, writing, or submission of this manuscript.

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All authors contributed significantly to the conceptualization of this manuscript. ZS led drafting, assisted by MF and MG. ZS and MF conducted literature searches. All authors revised and approved the final manuscript.

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ND’s participation in this research was conducted solely as part of academic duties as a member of the faculty at the University of North Carolina at Chapel Hill. ND is a part-time methods consultant to the RADARS System, which was not involved in nor had knowledge of this manuscript. The RADARS System is supported by subscriptions from pharmaceutical manufacturers, governmental and non-governmental agencies for data, research and reporting services. RADARS System is the property of Denver Health and Hospital Authority, a political subdivision of the State of Colorado (United States of America). Subscribers do not participate in data collection nor do they have access to raw data; Denver Health retains exclusive ownership of all data, databases and systems. Employees are prohibited from personal financial relationships with any biopharmaceutical company. The other authors declare that they have no competing interests.

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Salazar, Z.R., Vincent, L., Figgatt, M.C. et al. Research led by people who use drugs: centering the expertise of lived experience. Subst Abuse Treat Prev Policy 16 , 70 (2021). https://doi.org/10.1186/s13011-021-00406-6

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Article Contents

Introduction.

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Understanding reasons for drug use amongst young people: a functional perspective

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Annabel Boys, John Marsden, John Strang, Understanding reasons for drug use amongst young people: a functional perspective, Health Education Research , Volume 16, Issue 4, August 2001, Pages 457–469, https://doi.org/10.1093/her/16.4.457

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This study uses a functional perspective to examine the reasons young people cite for using psychoactive substances. The study sample comprised 364 young poly-drug users recruited using snowball-sampling methods. Data on lifetime and recent frequency and intensity of use for alcohol, cannabis, amphetamines, ecstasy, LSD and cocaine are presented. A majority of the participants had used at least one of these six drugs to fulfil 11 of 18 measured substance use functions. The most popular functions for use were using to: relax (96.7%), become intoxicated (96.4%), keep awake at night while socializing (95.9%), enhance an activity (88.5%) and alleviate depressed mood (86.8%). Substance use functions were found to differ by age and gender. Recognition of the functions fulfilled by substance use should help health educators and prevention strategists to make health messages about drugs more relevant and appropriate to general and specific audiences. Targeting substances that are perceived to fulfil similar functions and addressing issues concerning the substitution of one substance for another may also strengthen education and prevention efforts.

The use of illicit psychoactive substances is not a minority activity amongst young people in the UK. Results from the most recent British Crime Survey show that some 50% of young people between the ages of 16 and 24 years have used an illicit drug on at least one occasion in their lives (lifetime prevalence) ( Ramsay and Partridge, 1999 ). Amongst 16–19 and 20–24 year olds the most prevalent drug is cannabis (used by 40% of 16–19 year olds and 47% of 20–24 year olds), followed by amphetamine sulphate (18 and 24% of the two age groups respectively), LSD (10 and 13%) and ecstasy (8 and 12%). The lifetime prevalence for cocaine hydrochloride (powder cocaine) use amongst the two age groups is 3 and 9%, respectively. Collectively, these estimates are generally comparable with other European countries ( European Monitoring Centre for Drugs and Drug Addiction, 1998 ) and the US ( Johnston et al ., 1997 , 2000 ).

The widespread concern about the use of illicit drugs is reflected by its high status on health, educational and political agendas in many countries. The UK Government's 10-year national strategy on drug misuse identifies young people as a critical priority group for prevention and treatment interventions ( Tackling Drugs to Build a Better Britain 1998 ). If strategies to reduce the use of drugs and associated harms amongst the younger population are to be developed, particularly within the health education arena, it is vital that we improve our understanding of the roles that both licit and illicit substances play in the lives of young people. The tendency for educators, practitioners and policy makers to address licit drugs (such as alcohol) separately from illegal drugs may be unhelpful. This is partly because young illicit drug users frequently drink alcohol, and may have little regard for the illicit and licit distinction established by the law. To understand the roles that drug and alcohol use play in contemporary youth culture, it is necessary to examine the most frequently used psychoactive substances as a set.

It is commonplace for young drug users to use several different psychoactive substances. The terms `poly-drug' or `multiple drug' use have been used to describe this behaviour although their exact definitions vary. The term `poly-drug use' is often used to describe the use of two or more drugs during a particular time period (e.g. over the last month or year). This is the definition used within the current paper. However, poly-drug use could also characterize the use of two or more psychoactive substances so that their effects are experienced simultaneously. We have used the term `concurrent drug use' to denote this pattern of potentially more risky and harmful drug use ( Boys et al. 2000a ). Previous studies have reported that users often use drugs concurrently to improve the effects of another drug or to help manage its negative effects [e.g. ( Power et al ., 1996 ; Boys et al. 2000a ; Wibberley and Price, 2000 )].

The most recent British Crime Survey found that 5% of 16–29 year olds had used more than one drug in the last month ( Ramsay and Partridge, 1999 ). Given that 16% of this age band reported drug use in the month prior to interview, this suggests that just under a third of these individuals had used more than one illicit substance during this time period. With alcohol included, the prevalence of poly-drug use is likely to be much higher.

There is a substantial body of literature on the reasons or motivations that people cite for using alcohol, particularly amongst adult populations. For example, research on heavy drinkers suggested that alcohol use is related to multiple functions for use ( Edwards et al ., 1972 ; Sadava, 1975 ). Similarly, research with a focus on young people has sought to identify motives for illicit drug use. There is evidence that for many young people, the decision to use a drug is based on a rational appraisal process, rather than a passive reaction to the context in which a substance is available ( Boys et al. 2000a ; Wibberley and Price, 2000 ). Reported reasons vary from quite broad statements (e.g. to feel better) to more specific functions for use (e.g. to increase self-confidence). However, much of this literature focuses on `drugs' as a generic concept and makes little distinction between different types of illicit substances [e.g. ( Carman, 1979 ; Butler et al ., 1981 ; Newcomb et al ., 1988 ; Cato, 1992 ; McKay et al ., 1992 )]. Given the diverse effects that different drugs have on the user, it might be proposed that reasons for use will closely mirror these differences. Thus stimulant drugs (such as amphetamines, ecstasy or cocaine) will be used for reasons relating to increased nervous system arousal and drugs with sedative effects (such as alcohol or cannabis), with nervous system depression. The present study therefore selected a range of drugs commonly used by young people with stimulant, sedative or hallucinogenic effects to examine this issue further.

The phrase `instrumental drug use' has been used to denote drug use for reasons specifically linked to a drug's effects ( WHO, 1997 ). Examples of the instrumental use of amphetamine-type stimulants include vehicle drivers who report using to improve concentration and relieve tiredness, and people who want to lose weight (particularly young women), using these drugs to curb their appetite. However, the term `instrumental substance use' seems to be used when specific physical effects of a drug are exploited and does not encompass use for more subtle social or psychological purposes which may also be cited by users. In recent reports we have described a `drug use functions' model to help understand poly-substance use phenomenology amongst young people and how decisions are made about patterns of consumption ( Boys et al ., 1999a , b , 2000a ). The term `function' is intended to characterize the primary or multiple reasons for, or purpose served by, the use of a particular substance in terms of the actual gains that the user perceives that they will attain. In the early, 1970s Sadava suggested that functions were a useful means of understanding how personality and environmental variables impacted on patterns of drug use ( Sadava, 1975 ). This work was confined to functions for cannabis and `psychedelic drugs' amongst a sample of college students. To date there has been little research that has examined the different functions associated with the range of psychoactive substances commonly used by young poly-drug users. It is unclear if all drugs with similar physical effects are used for similar purposes, or if other more subtle social or psychological dimensions to use are influential. Work in this area will help to increase understanding of the different roles played by psychoactive substances in the lives of young people, and thus facilitate health, educational and policy responses to this issue.

Previous work has suggested that the perceived functions served by the use of a drug predict the likelihood of future consumption ( Boys et al ., 1999a ). The present study aims to develop this work further by examining the functional profiles of six substances commonly used by young people in the UK.

Patterns of cannabis, amphetamine, ecstasy, LSD, cocaine hydrochloride and alcohol use were examined amongst a sample of young poly-drug users. Tobacco use was not addressed in the present research.

Sampling and recruitment

A snowball-sampling approach was employed for recruitment of participants. Snowball sampling is an effective way of generating a large sample from a hidden population where no formal sampling frame is available ( Van Meter, 1990 ). A team of peer interviewers was trained to recruit and interview participants for the study. We have described this procedure in detail elsewhere and only essential features are described here ( Boys et al. 2000b ). Using current or ex-drug users to gather data from hidden populations of drug using adults has been found to be successful ( Griffiths et al ., 1993 ; Power, 1995 ).

Study participants

Study participants were current poly-substance users with no history of treatment for substance-related disorders. We excluded people with a treatment history on the assumption that young people who have had substance-related problems requiring treatment represent a different group from the general population of young drug users. Inclusion criteria were: aged 16–22 years and having used two or more illegal substances during the past 90 days. During data collection, the age, gender and current occupation of participants were recorded and monitored to ensure that sufficient individuals were recruited to the groups to permit subgroup analyses. If an imbalance was observed in one of these variables, the interviewers were instructed to target participants with specific characteristics (e.g. females under the age of 18) to redress this imbalance.

Study measures

Data were collected using a structured interviewer-administered questionnaire developed specifically for the study. In addition to recording lifetime substance use, questions profiled consumption patterns of six substances in detail. Data were collected between August and November 1998. Interviews were audiotaped with the interviewee's consent. This enabled research staff to verify that answers had been accurately recorded on the questionnaire and that the interview had been conducted in accordance with the research protocol. Research staff also checked for consistency across different question items (e.g. the total number of days of drug use in the past 90 days should equal or exceed the number of days of cannabis use during the same time period). On the few occasions where inconsistencies were identified that could not be corrected from the tape, the interviewer was asked to re-contact the interviewee to verify the data.

Measures of lifetime use, consumption in the past year and past 90 days were based on procedures developed by Marsden et al . ( Marsden et al ., 1998 ). Estimated intensity of consumption (amount used on a typical using day) was recorded verbatim and then translated into standardized units at the data entry stage.

Functions for substance use scale

The questionnaire included a 17-item scale designed to measure perceived functions for substance use. This scale consisted of items developed in previous work ( Boys et al ., 1999a ) in addition to functions derived from qualitative interviews ( Boys et al ., 1999b ), new literature and informal discussions with young drug users. Items were drawn from five domains (Table I ).

Participants were asked if they had ever used a particular drug in order to fulfil each specific function. Those who endorsed the item were then invited to rate how frequently they had used it for this purpose over the past year, using a five-point Likert-type scale (`never' to `always'; coded 0–4). One item differed between the function scales used for the stimulant drugs and for alcohol and cannabis. For the stimulant drugs (amphetamines, cocaine and ecstasy) the item `have you ever used [named drug] to help you to lose weight' was used, for cannabis and alcohol this item was replaced with `have you ever used [drug] to help you to sleep?'. (The items written in full as they appeared in the questionnaire are shown in Table III , together with abbreviations used in this paper.)

Statistical procedures

The internal reliability of the substance use functions scales for each of the six substances was judged using Chronbach's α coefficient. Chronbach's α is a statistic that reflects the extent to which each item in a measurement scale is associated with other items. Technically it is the average of correlations between all possible comparisons of the scale items that are divided into two halves. An α coefficient for a scale can range from 0 (no internal reliability) to 1 (complete reliability). Analyses of categorical variables were performed using χ 2 statistic. Differences in scale means were assessed using t -tests.

The sample consisted of 364 young poly-substance users (205 males; 56.3%) with a mean age of 19.3 years; 69.8% described their ethnic group as White-European, 12.6% as Black and 10.1% were Asian. Just over a quarter (27.5%) were unemployed at the time of interview; a third were in education, 28.8% were in full-time work and the remainder had part-time employment. Estimates of monthly disposable income (any money that was spare after paying for rent, bills and food) ranged from 0 to over £1000 (median = £250).

Substance use history

The drug with the highest lifetime prevalence was cannabis (96.2%). This was followed by amphetamine sulphate (51.6%), cocaine hydrochloride (50.5%) (referred to as cocaine hereafter) and ecstasy (48.6%). Twenty-five percent of the sample had used LSD and this was more common amongst male participants (χ 2 [1] = 9.68, P < 0.01). Other drugs used included crack cocaine (25.5%), heroin (12.6%), tranquillizers (21.7%) and hallucinogenic mushrooms (8.0%). On average, participants had used a total of 5.2 different psychoactive substances in their lives (out of a possible 14) (median = 4.0, mode = 3.0, range 2–14). There was no gender difference in the number of different drugs ever used.

Table II profiles use of the six target drugs over the past year, and the frequency and intensity of use in the 90 days prior to interview.

There were no gender differences in drug use over the past year or in the past 90 days with the exception of amphetamines. For this substance, females who had ever used this drug were more likely to have done so during the past 90 days than males (χ 2 [1] = 4.14, P < 0.05). The mean number of target drugs used over the past 90 days was 3.2 (median = 3.0, mode = 3.0, range 2–6). No gender differences were observed. Few differences were also observed in the frequency and intensity of use. Males reported drinking alcohol more frequently during the three months prior to interview ( t [307] = 2.48, P < 0.05) and using cannabis more intensively on a `typical using day' ( t [337] = 3.56, P < 0.001).

Perceived functions for substance use

There were few differences between the functions endorsed for use of each drug `ever' and those endorsed for use during `the year prior to interview'. This section therefore concentrates on data for the year prior to interview. We considered that in order to use a drug for a specific function, the user must have first hand knowledge of the drug's effects before making this decision. Consequently, functions reported by individuals who had only used a particular substance on one occasion in their lives (i.e. with no prior experience of the drug at the time they made the decision to take it) were excluded from the analyses. Table III summarizes the proportion of the sample who endorsed each of the functions for drugs used in the past year. Roman numerals have been used to indicate the functions with the top five average scores. Table III also shows means for the total number of different items endorsed by individual users and the internal reliability of the function scales for each substance using Chronbach's α coefficients. There were no significant gender differences in the total number of functions endorsed for any of the six substances.

The following sections summarize the top five most popular functions drug-by-drug together with any age or gender differences observed in the items endorsed.

Cannabis use ( n = 345)

Overall the most popular functions for cannabis use were to `RELAX' (endorsed by 96.8% of people who had used the drug in the last year), to become `INTOXICATED' (90.7%) and to `ENHANCE ACTIVITY' (72.8%). Cannabis was also commonly used to `DECREASE BOREDOM' (70.1%) and to `SLEEP' (69.6%) [this item was closely followed by using to help `FEEL BETTER' (69.0%)]. Nine of the 17 function items were endorsed by over half of those who had used cannabis on more than one occasion in the past year. There were no significant gender differences observed, with the exception of using to `KEEP GOING', where male participants were significantly more likely to say that they had used cannabis to fulfil this function in the past year (χ 2 [1] = 6.10, P < 0.05).

There were statistically significant age differences on four of the function variables: cannabis users who reported using this drug in the past year to help feel `ELATED/EUPHORIC' or to help `SLEEP' were significantly older than those who had not used cannabis for these purposes (19.6 versus 19.0; t [343] = 3.32, P < 0.001; 19.4 versus 19.0; t [343] = 2.01, P < 0.05). In contrast, those who had used cannabis to `INCREASE CONFIDENCE' and to `STOP WORRYING' tended to be younger than those who did not (19.0 versus 19.4; t [343] = –2.26, P < 0.05; 19.1 versus 19.5; t [343] = –1.99, P < 0.05).

Amphetamines ( n = 160)

Common functions for amphetamine use were to `KEEP GOING' (95.6%), to `STAY AWAKE' (91.3%) or to `ENHANCE ACTIVITY' (66.2%). Using to help feel `ELATED/EUPHORIC' (60.6%) and to `ENJOY COMPANY' (58.1%) were also frequently mentioned. Seven of the 17 function items were endorsed by over half of participants who had used amphetamines in the past year. As with cannabis, gender differences were uncommon: females were more likely to use amphetamines to help `LOSE WEIGHT' than male participants (χ 2 [1] = 21.67, P < 0.001).

Significant age differences were found on four function variables. Individuals who reported using amphetamines in the past year to feel `ELATED/EUPHORIC' were significantly older than those who did not (19.9 versus 19.0; t [158] = 2.87, P < 0.01). In contrast, participants who used amphetamines to `STOP WORRYING' (18.8 versus 19.8; t [158] = –2.77, P < 0.01), to `DECREASE BOREDOM' (19.2 versus 19.9; t [158] = –2.39, P < 0.05) or to `ENHANCE ACTIVITY' (19.3 versus 20.1; t [158] = –2.88, P < 0.01) were younger than those who had not.

Ecstasy ( n = 157)

The most popular five functions for using ecstasy were similar to those for amphetamines. The drug was used to `KEEP GOING' (91.1%), to `ENHANCE ACTIVITY' (79.6%), to feel `ELATED/EUPHORIC' (77.7%), to `STAY AWAKE' (72.0%) and to get `INTOXICATED' (68.2%). Seven of the 17 function items were endorsed by over half of those who had used ecstasy in the past year. Female users were more likely to use ecstasy to help `LOSE WEIGHT' than male participants (Fishers exact test, P < 0.001).

As with the other drugs discussed above, participants who reported using ecstasy to feel `ELATED/EUPHORIC' were significantly older than those who did not (19.8 versus 18.9; t [155] = 2.61, P < 0.01). In contrast, those who had used ecstasy to `FEEL BETTER' (19.3 versus 20.0; t [155] = –2.29, P < 0.05), to `INCREASE CONFIDENCE' (19.2 versus 19.9; t [155] = –2.22, P < 0.05) and to `STOP WORRYING' (19.0 versus 19.9; t [155] = –2.96, P < 0.01) tended to be younger.

LSD ( n = 58)

Of the six target substances examined in this study, LSD was associated with the least diverse range of functions for use. All but two of the function statements were endorsed by at least some users, but only five were reported by more than 50%. The most common purpose for consuming LSD was to get `INTOXICATED' (77.6%). Other popular functions included to feel `ELATED/EUPHORIC' and to `ENHANCE ACTIVITY' (both endorsed by 72.4%), and to `KEEP GOING' and to `ENJOY COMPANY' (both endorsed by 58.6%). Unlike the other substances examined, no gender or age differences were observed.

Cocaine ( n = 168)

In common with ecstasy and amphetamines, the most widely endorsed functions for cocaine use were to help `KEEP GOING' (84.5%) and to help `STAY AWAKE' (69.0%). Consuming cocaine to `INCREASE CONFIDENCE' and to get `INTOXICATED' (both endorsed by 66.1%) were also popular. However, unlike the other stimulant drugs, 61.9% of the cocaine users reported using to `FEEL BETTER'. Ten of the 17 function items were endorsed by over half of those who had used cocaine in the past year.

Gender differences were more common amongst functions for cocaine use than the other substances surveyed. More males reported using cocaine to `IMPROVE EFFECTS' of other drugs (χ 2 [1] = 4.00, P < 0.05); more females used the drug to help `STAY AWAKE' (χ 2 [1] = 12.21, P < 0.001), to `LOSE INHIBITIONS' (χ 2 [1] = 9.01, P < 0.01), to `STOP WORRYING' (χ 2 [1] = 8.11, P < 0.01) or to `ENJOY COMPANY' of friends (χ 2 [1] = 4.34, P < 0.05). All participants who endorsed using cocaine to help `LOSE WEIGHT' were female.

Those who had used cocaine to `FEEL BETTER' (18.9 versus 19.8; t [166] = –3.06, P < 0.01), to `STOP WORRYING' (18.6 versus 19.7; t [166] = –3.86, P < 0.001) or to `DECREASE BOREDOM' (18.9 versus 19.6; t [166] = –2.52, P < 0.05) were significantly younger than those who did not endorse these functions. Similar to the other drugs, participants who had used cocaine to feel `ELATED/EUPHORIC' in the past year tended to be older than those who had not (19.6 versus 18.7; t [166] = 3.16, P < 0.01).

Alcohol ( n = 312)

The functions for alcohol use were the most diverse of the six substances examined. Like LSD, the most commonly endorsed purpose for drinking was to get `INTOXICATED' (89.1%). Many used alcohol to `RELAX' (82.7%), to `ENJOY COMPANY' (74.0%), to `INCREASE CONFIDENCE' (70.2%) and to `FEEL BETTER' (69.9%). Overall, 11 of the 17 function items were endorsed by over 50% of those who had drunk alcohol in the past year. Male participants were more likely to report using alcohol in combination with other drugs either to `IMPROVE EFFECTS' of other drugs (χ 2 [1] = 4.56, P < 0.05) or to ease the `AFTER EFFECTS' of other substances (χ 2 [1] = 7.07, P < 0.01). More females than males reported that they used alcohol to `DECREASE BOREDOM' (χ 2 [1] = 4.42, P < 0.05).

T -tests revealed significant age differences on four of the function variables: those who drank to feel `ELATED/EUPHORIC' were significantly older (19.7 versus 19.0; t [310] = 3.67, P < 0.001) as were individuals who drank to help them to `LOSE INHIBITIONS' (19.6 versus 19.0; t [310] = 2.36, P < 0.05). In contrast, participants who reported using alcohol just to get `INTOXICATED' (19.2 versus 20.3; t [310] = –3.31, P < 0.001) or to `DECREASE BOREDOM' (19.2 versus 19.6; t [310] = –2.25, P < 0.05) were significantly younger than those who did not.

Combined functional drug use

The substances used by the greatest proportion of participants to `IMPROVE EFFECTS' from other drugs were cannabis (44.3%), alcohol (41.0%) and amphetamines (37.5%). It was also common to use cannabis (64.6%) and to a lesser extent alcohol (35.9%) in combination with other drugs in order to help manage `AFTER EFFECTS'. Amphetamines, ecstasy, LSD and cocaine were also used for these purposes, although to a lesser extent. Participants who endorsed the combination drug use items were asked to list the three main drugs with which they had combined the target substance for these purposes. Table IV summarizes these responses.

Overall functions for drug use

In order to examine which functions were most popular overall, a dichotomous variable was created for each different item to indicate if one or more of the six target substances had been used to fulfil this purpose during the year prior to interview. For example, if an individual reported that they had used cannabis to relax, but their use of ecstasy, amphetamines and alcohol had not fulfilled this function, then the variable for `RELAX' was scored `1'. Similarly if they had used all four of these substances to help them to relax in the past year, the variable would again be scored as `1'. A score of `0' indicates that none of the target substances had been used to fulfil a particular function. Table V summarizes the data from these new variables.

Over three-quarters of the sample had used at least one target substance in the past year for 11 out of the 18 functions listed. The five most common functions for substance use overall were to `RELAX' (96.7%); `INTOXICATED' (96.4%); `KEEP GOING' (95.9%); `ENHANCE ACTIVITY' (88.5%) and `FEEL BETTER' (86.8%). Despite the fact that `SLEEP' was only relevant to two substances (alcohol and cannabis), it was still endorsed by over 70% of the total sample. Using to `LOSE WEIGHT' was only relevant to the stimulant drugs (amphetamines, ecstasy and cocaine), yet was endorsed by 17.3% of the total sample (almost a third of all female participants). Overall, this was the least popular function for recent substance use, followed by `WORK' (32.1%). All other items were endorsed by over 60% of all participants.

Gender differences were identified in six items. Females were significantly more likely to have endorsed the following: using to `INCREASE CONFIDENCE' (χ 2 [1] = 4.41, P < 0.05); `STAY AWAKE' (χ 2 [1] = 5.36, P < 0.05), `LOSE INHIBITIONS' (χ 2 [1] = 4.48, P < 0.05), `ENHANCE SEX' (χ 2 [1] = 5.17, P < 0.05) and `LOSE WEIGHT' (χ 2 [1] = 29.6, P < 0.001). In contrast, males were more likely to use a substance to `IMPROVE EFFECTS' of another drug (χ 2 [1] = 11.18, P < 0.001).

Statistically significant age differences were identified in three of the items. Those who had used at least one of the six target substances in the last year to feel `ELATED/EUPHORIC' (19.5 versus 18.6; t [362] = 4.07, P < 0.001) or to `SLEEP' (19.4 versus 18.9; t [362] = 2.19, P < 0.05) were significantly older than those who had not used for this function. In contrast, participants who had used in order to `STOP WORRYING' tended to be younger (19.1 versus 19.7; t [362] = –2.88, P < 0.01).

This paper has examined psychoactive substance use amongst a sample of young people and focused on the perceived functions for use using a 17-item scale. In terms of the characteristics of the sample, the reported lifetime and recent substance use was directly comparable with other samples of poly-drug users recruited in the UK [e.g. ( Release, 1997 )].

Previous studies which have asked users to give reasons for their `drug use' overall instead of breaking it down by drug type [e.g. ( Carman, 1979 ; Butler et al ., 1981 ; Newcomb et al ., 1988 ; Cato, 1992 ; McKay et al ., 1992 )] may have overlooked the dynamic nature of drug-related decision making. A key finding from the study is that that with the exception of two of the functions for use scale items (using to help sleep or lose weight), all of the six drugs had been used to fulfil all of the functions measured, despite differences in their pharmacological effects. The total number of functions endorsed by individuals for use of a particular drug varied from 0 to 15 for LSD, and up to 17 for cannabis, alcohol and cocaine. The average number ranged from 5.9 (for LSD) to 9.0 (for cannabis). This indicates that substance use served multiple purposes for this sample, but that the functional profiles differed between the six target drugs.

We have previously reported ( Boys et al. 2000b ) that high scores on a cocaine functions scale are strongly predictive of high scores on a cocaine-related problems scale. The current findings support the use of similar function scales for cannabis, amphetamines, LSD and ecstasy. It remains to be seen whether similar associations with problem scores exist. Future developmental work in this area should ensure that respondents are given the opportunity to cite additional functions to those included here so that the scales can be further extended and refined.

Recent campaigns that have targeted young people have tended to assume that hallucinogen and stimulant use is primarily associated with dance events, and so motives for use will relate to this context. Our results support assumptions that these drugs are used to enhance social interactions, but other functions are also evident. For example, about a third of female interviewees had used a stimulant drug to help them to lose weight. Future education and prevention efforts should take this diversity into account when planning interventions for different target groups.

The finding that the same functions are fulfilled by use of different drugs suggests that at least some could be interchangeable. Evidence for substituting alternative drugs to fulfil a function when a preferred drug is unavailable has been found in other studies [e.g. ( Boys et al. 2000a )]. Prevention efforts should perhaps focus on the general motivations behind use rather than trying to discourage use of specific drug types in isolation. For example, it is possible that the focus over the last decade on ecstasy prevention may have contributed inadvertently to the rise in cocaine use amongst young people in the UK ( Boys et al ., 1999c ). It is important that health educators do not overlook this possibility when developing education and prevention initiatives. Considering functions that substance use can fulfil for young people could help us to understand which drugs are likely to be interchangeable. If prevention programmes were designed to target a range of substances that commonly fulfil similar functions, then perhaps this could address the likelihood that some young people will substitute other drugs if deterred from their preferred substance.

There has been considerable concern about the perceived increase in the number of young people who are using cocaine in the UK ( Tackling Drugs to Build a Better Britain 1998 ; Ramsay and Partridge, 1999 ; Boys et al. 2000b ). It has been suggested that, for a number of reasons, cocaine may be replacing ecstasy and amphetamines as the stimulant of choice for some young people ( Boys et al ., 1999c ). The results from this study suggest that motives for cocaine use are indeed similar to those for ecstasy and amphetamine use, e.g. using to `keep going' on a night out with friends, to `enhance an activity', `to help to feel elated or euphoric' or to help `stay awake'. However, in addition to these functions which were shared by all three stimulants, over 60% of cocaine users reported that they had used this drug to `help to feel more confident' in a social situation and to `feel better when down or depressed'. Another finding that sets cocaine aside from ecstasy and amphetamines was the relatively common existence of gender differences in the function items endorsed. Female cocaine users were more likely to use to help `stay awake', `lose inhibitions', `stop worrying', `enjoy company of friends' or to help `lose weight'. This could indicate that women are more inclined to admit to certain functions than their male counterparts. However, the fact that similar gender differences were not observed in the same items for the other five substances, suggests this interpretation is unlikely. Similarly, the lack of gender differences in patterns of cocaine use (both frequency and intensity) suggests that these differences are not due to heavier cocaine use amongst females. If these findings are subsequently confirmed, this could point towards an inclination for young women to use cocaine as a social support, particularly to help feel less inhibited in social situations. If so, young female cocaine users may be more vulnerable to longer-term cocaine-related problems.

Many respondents reported using alcohol or cannabis to help manage effects experienced from another drug. This has implications for the choice of health messages communicated to young people regarding the use of two or more different substances concurrently. Much of the literature aimed at young people warns them to avoid mixing drugs because the interactive effects may be dangerous [e.g. ( HIT, 1996 )]. This `Just say No' type of approach does not take into consideration the motives behind mixing drugs. In most areas, drug education and prevention work has moved on from this form of communication. A more sophisticated approach is required, which considers the functions that concurrent drug use is likely to have for young people and tries to amend messages to make them more relevant and acceptable to this population. Further research is needed to explore the motivations for mixing different combinations of drugs together.

Over three-quarters of the sample reported using at least one of the six target substances to fulfil 11 out of the 18 functions. These findings provide strong evidence that young people use psychoactive drugs for a range of distinct purposes, not purely dependent on the drug's specific effects. Overall, the top five functions were to `help relax', `get intoxicated', `keep going', `enhance activity' and `feel better'. Each of these was endorsed by over 85% of the sample. Whilst all six substances were associated to a greater or lesser degree with each of these items, there were certain drugs that were more commonly associated with each. For example, cannabis and alcohol were popular choices for relaxation or to get intoxicated. In contrast, over 90% of the amphetamine and ecstasy users reported using these drugs within the last year to `keep going'. Using to enhance an activity was a common function amongst users of all six substances, endorsed by over 70% of ecstasy, cannabis and LSD users. Finally, it was mainly alcohol and cannabis (and to a lesser extent cocaine) that were used to `feel better'.

Several gender differences were observed in the combined functions for recent substance use. These findings indicate that young females use other drugs as well as cocaine as social supports. Using for specific physical effects (weight loss, sex or wakefulness) was also more common amongst young women. In contrast, male users were significantly more likely to report using at least one of the target substances to try to improve the effects of another substance. This indicates a greater tendency for young males in this sample to mix drugs than their female counterparts. Age differences were also observed on several function items: participants who had used a drug to `feel elated or euphoric' or to `help sleep' tended to be older and those who used to `stop worrying about a problem' were younger. If future studies confirm these differences, education programmes and interventions might benefit from tailoring their strategies for specific age groups and genders. For example, a focus on stress management strategies and coping skills with a younger target audience might be appropriate.

Some limitations of the study need to be acknowledged. The sample for this study was recruited using a snowball-sampling methodology. Although it does not yield a random sample of research participants, this method has been successfully used to access hidden samples of drug users [e.g. ( Biernacki, 1986 ; Lenton et al ., 1997 )]. Amongst the distinct advantages of this approach are that it allows theories and models to be tested quantitatively on sizeable numbers of subjects who have engaged in a relatively rare behaviour.

Further research is now required to determine whether our observations may be generalized to other populations (such as dependent drug users) and drug types (such as heroin, tranquillizers or tobacco) or if additional function items need to be developed. Future studies should also examine if functions can be categorized into primary and subsidiary reasons and how these relate to changes in patterns of use and drug dependence. Recognition of the functions fulfilled by substance use could help inform education and prevention strategies and make them more relevant and acceptable to the target audiences.

Structure of functions scales

Profile of substance use over the past year and past 90 days ( n = 364)

Proportion (%) of those who have used [substance] more than once, who endorsed each functional statement for their use in the past year

Combined functional substance use reported by the sample over the past year

Percentage of participants who reported having used at least one of the target substances to fulfil each of the different functions over the past year ( n = 364)

We gratefully acknowledge research support from the Health Education Authority (HEA). The views expressed in this paper are those of the authors and do not necessarily reflect those of the HEA. We would also like to thank the anonymous referees for helpful comments and suggestions on an earlier draft of this paper.

Biernacki, P. (1986) Pathways from Heroin Addiction: Recovery without Treatment . Temple University Press, Philadelphia, PA.

Boys, A., Marsden, J., Griffiths, P., Fountain, J., Stillwell, G. and Strang, J. ( 1999 ) Substance use among young people: the relationship between perceived functions and behavioural intentions. Addiction , 94 , 1043 –1050.

Boys, A., Marsden, J., Fountain, J., Griffiths, P., Stillwell, G. and Strang, J. ( 1999 ) What influences young people's use of drugs? A qualitative study of decision-making. Drugs: Education, Prevention and Policy , 6 , 373 –389.

Boys, A., Marsden, J. and Griffiths. P. ( 1999 ) Reading between the lines: is cocaine becoming the stimulant of choice for urban youth? Druglink , 14 , 20 –23.

Boys, A., Fountain, J., Marsden, J., Griffiths, P., Stillwell, G. and Strang, J. (2000a) Drug Decisions: A Qualitative Study of Young People , Drugs and Alcohol . Health Education Authority, London.

Boys, A., Marsden, J., Griffiths, P. and Strang, J. ( 2000 ) Drug use functions predict cocaine-related problems. Drug and Alcohol Review , 19 , 181 –190.

Butler, M. C., Gunderson, E. K. E. and Bruni, J. R. ( 1981 ) Motivational determinants of illicit drug use: an assessment of underlying dimensions and their relationship to behaviour. International Journal of the Addictions , 16 , 243 –252.

Carman, R. S. ( 1979 ) Motivations for drug use and problematic outcomes among rural junior high school students. Addictive Behaviors , 4 , 91 –93.

Cato, B. M. ( 1992 ) Youth's recreation and drug sensations: is there a relationship? Journal of Drug Education , 22 , 293 –301.

Edwards, G., Chandler, J. and Peto, J. ( 1972 ) Motivation for drinking among men in a London suburb, Psychological Medicine , 2 , 260 –271.

European Monitoring Centre for Drugs and Drug Addiction (1998) Annual Report on the State of the Drugs Problem in the European Union . EMCDDA, Lisbon.

Griffiths, P., Gossop, M., Powis, B. and Strang, J. ( 1993 ) Reaching hidden populations of drug users by privileged access interviewers: methodological and practical issues. Addiction , 88 , 1617 –1626.

HIT (1996) Chill Out: A Clubber's Guide—The Second Coming . HIT, Liverpool.

Johnston, L. D., O'Malley, P. M. and Bachman J. G. (1997) National Survey Results on Drug Use from the Monitoring the Future Study , 1975–1996: Secondary School Students . US DHHS, National Institute on Drug Abuse, Rockville, MD.

Johnston, L. D., O'Malley, P. M. and Bachman J. G. (2000) The Monitoring the Future National Results on Adolescent Drug Use: Overview of Key Findings 1999 . US DHHS, National Institute on Drug Abuse, Rockville, MD.

Lenton, S., Boys, A. and Norcross, K. ( 1997 ) Raves, drugs and experience: drug use by a sample of people who attend raves in Western Australia. Addiction , 92 , 1327 –1337.

Marsden, J., Gossop, M., Stewart, D., Best, D., Farrell, M., Edwards, C., Lehmann, P. and Strang, J. ( 1998 ) The Maudsley Addiction Profile (MAP): a brief instrument for assessing treatment outcome. Addiction , 93 , 1857 –1867.

McKay, J. R., Murphy, R. T., McGuire, J., Rivinus, T. R. and Maisto, S. A. ( 1992 ) Incarcerated adolescents' attributions for drug and alcohol use. Addictive Behaviors , 17 , 227 –235.

Newcomb. M. D., Chou, C.-P., Bentler, P. M. and Huba, G. J. ( 1988 ) Cognitive motivations for drug use among adolescents: longitudinal tests of gender differences and predictors of change in drug use. Journal of Counselling Psychology , 35 , 426 –438.

Power, R. ( 1995 ) A model for qualitative action research amongst illicit drug users. Addiction Research , 3 , 165 –181.

Power, R., Power, T. and Gibson, N. ( 1996 ) Attitudes and experience of drug use amongst a group of London teenagers. Drugs: Education, Prevention and Policy , 3 , 71 –80.

Ramsay, M. and Partridge, S. (1999) Drug Misuse Declared in 1998: Results from the British Crime Survey . Home Office, London.

Release (1997) Release Drugs and Dance Survey: An Insight into the Culture . Release, London.

Sadava, S. ( 1975 ) Research approaches in illicit drug use: a critical review. Genetic Psychology Monographs , 91 , 3 –59.

Tackling Drugs to Build a Better Britain (1998) The Government's 10-year Strategy on Drug Misuse. Central Drugs Co-ordinating Unit, London.

Van Meter, K. M. (1990) Methodological and design issues: techniques for assessing the representatives of snowball samples. In Lambert, E. Y. (ed.), The Collection and Interpretation of Data from Hidden Populations . US DHHS, National Institute on Drug Abuse, Rockville, MD, pp. 31–33.

Wibberley, C. and Price, J. ( 2000 ) Patterns of psycho-stimulant drug use amongst `social/operational users': implications for services. Addiction Research , 8 , 95 –111.

WHO (1997) Amphetamine-type Stimulants: A Report from the WHO Meeting on Amphetamines , MDMA and other Psychostimulants , Geneva, 12–15 November 1996. Programme on Substance Abuse, Division of Mental Health and Prevention of Substance Abuse, WHO, Geneva.

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How physicians interpret information about prescription drugs in scientific publications vs. promotional pieces

CDER researchers have conducted a randomized study to better understand how physicians make prescribing decisions.

As they make decisions about which drug products should be prescribed to their patients, physicians must process a great deal of relevant information in a limited amount of time. This information is from a wide range of sources, including but not limited to, FDA-approved labeling, peer-reviewed research published in scientific journals, continuing medical education, discussions with colleagues, and clinical practice guidelines. Physicians may also obtain information from drug advertising and promotion, including materials such as sales aids provided in person by sales representatives. CDER researchers recently conducted a randomized controlled study among primary care physicians to better understand how physicians process and interpret information that could guide prescribing decisions, and how such factors as time pressure, whether the information source is promotional in nature, and indicators of methodological rigor (e.g., sample size or duration) may influence physician’s perceptions of a drug product and prescribing.

The design of this study was based on concepts from the field of cognitive psychology and previous work that showed that when given a limited amount of time, people use heuristic or peripheral cues

(mental shortcuts) more than content in making decisions about a message. Over 600 doctors specializing in internal, family, or primary care medicine were asked to answer survey questions about a medical journal abstract describing the results of a clinical trial of a hypothetical diabetes. The physicians were randomly assigned to see the abstract presented in one of three ways: prominently labeled as a journal abstract, a sales aid without graphics, or sales aid with graphics. At two succeeding stages of randomization (Figure 1), physicians saw a version of the text that was either high or low in methodological rigor, and they had either unlimited time or only 30 seconds to view the text. Thus, this 3 x 2 x 2 design led to 12 different conditions to which the physicians could be assigned. Participants were asked a set of questions about their perceptions of the described study, the perceived benefits of the hypothetical drug, its riskiness, and whether they would prescribe it. CDER investigators statistically tested a set of relevant hypotheses about how information source (abstract, or promotion with or without graphics), methodologic rigor, and time pressure (Figure 2) influenced these outcome variables.

Among the main findings of the study were the following:

• Participants who viewed the abstract of the high-methodological rigor clinical study reported more perceived credibility and importance of the data, less need for interpreting the study data with caution, and less bias in the described study than those who viewed a low-rigor study (although there were not significant differences in perceptions of the benefits of using the hypothetical drug).

In discussing these findings, CDER researchers suggested that physicians consider methodological rigor when making decisions. Prominently disclosing information related to the methodological rigor of a study may help the audience form an accurate perception of the strength of the study and the support for claims in promotional communications. To better understand the impact of other advertising content, future research efforts could explore how physicians perceive studies that do not disclose detailed information about methodological rigor. The researchers also proposed that future examination of the role of evidence-based medicine training in physicians’ understanding of promotional materials.

• Study participants who were not under time pressure to read the text rated the fictitious study description as more credible, rigorous, and important, and had more confidence in study data than those who were under time pressure.

According to the authors, these results suggest that time pressure results in decisional caution, and that that future research could explore how selective attention, such as disinterest in a new drug to treat a specific disease, may influence time spent on an information piece. This finding may better explain how time pressure works in real-world scenarios. Additional research could also explore how time pressure when evaluating prescription drug promotional material increases the use of heuristic shortcuts, such as relying on brand names or study funding sources.

• No effects of source type (abstract, or promotion with or without graphics) were observed.

The authors of the study noted that when participants had unlimited time, they rated the information in the medical journal as more credible than they rated the sales aid, but when participants were pressed for time, they did not distinguish between the two. The investigators suggest that future work could also examine how different selection or framing of content may influence perceptions of source (e.g., promotional advertising or academic journal).

How does the source and quality of medical product information impact physician perceptions?

The results of this study suggest that prominently disclosing methodological rigor helps the audience form an accurate perception of the presented information. Further, additional findings showed that promotional communications without graphics that appear to be more closely related to study reprints or summaries may be approached and interpreted with less caution by physicians than promotional communications that fit the classic expectation of “promotion.” This highlights the importance that any promotional communications should be truthful and non-misleading.

Figure 2. study objectives, hypotheses and research questions addressed in the CDER research.

Aikin, Kathryn J., Amie C. O'Donoghue, Stephanie Miles, Maria DelGreco, and Panne Burke. "Physician interpretation of information about prescription drugs in scientific publications vs. promotional pieces." Research in Social and Administrative Pharmacy (2024).

Related Story: Advancing Our Understanding of How Drug Promotion Influences Consumers and Health Care Providers

August 19, 2021

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April 23, 2024

Research in Context: Treating depression

Finding better approaches.

While effective treatments for major depression are available, there is still room for improvement. This special Research in Context feature explores the development of more effective ways to treat depression, including personalized treatment approaches and both old and new drugs.

Everyone has a bad day sometimes. People experience various types of stress in the course of everyday life. These stressors can cause sadness, anxiety, hopelessness, frustration, or guilt. You may not enjoy the activities you usually do. These feelings tend to be only temporary. Once circumstances change, and the source of stress goes away, your mood usually improves. But sometimes, these feelings don’t go away. When these feelings stick around for at least two weeks and interfere with your daily activities, it’s called major depression, or clinical depression.

In 2021, 8.3% of U.S. adults experienced major depression. That’s about 21 million people. Among adolescents, the prevalence was much greater—more than 20%. Major depression can bring decreased energy, difficulty thinking straight, sleep problems, loss of appetite, and even physical pain. People with major depression may become unable to meet their responsibilities at work or home. Depression can also lead people to use alcohol or drugs or engage in high-risk activities. In the most extreme cases, depression can drive people to self-harm or even suicide.

The good news is that effective treatments are available. But current treatments have limitations. That’s why NIH-funded researchers have been working to develop more effective ways to treat depression. These include finding ways to predict whether certain treatments will help a given patient. They're also trying to develop more effective drugs or, in some cases, find new uses for existing drugs.

Finding the right treatments

The most common treatments for depression include psychotherapy, medications, or a combination. Mild depression may be treated with psychotherapy. Moderate to severe depression often requires the addition of medication.

Several types of psychotherapy have been shown to help relieve depression symptoms. For example, cognitive behavioral therapy helps people to recognize harmful ways of thinking and teaches them how to change these. Some researchers are working to develop new therapies to enhance people’s positive emotions. But good psychotherapy can be hard to access due to the cost, scheduling difficulties, or lack of available providers. The recent growth of telehealth services for mental health has improved access in some cases.

There are many antidepressant drugs on the market. Different drugs will work best on different patients. But it can be challenging to predict which drugs will work for a given patient. And it can take anywhere from 6 to 12 weeks to know whether a drug is working. Finding an effective drug can involve a long period of trial and error, with no guarantee of results.

If depression doesn’t improve with psychotherapy or medications, brain stimulation therapies could be used. Electroconvulsive therapy, or ECT, uses electrodes to send electric current into the brain. A newer technique, transcranial magnetic stimulation (TMS), stimulates the brain using magnetic fields. These treatments must be administered by specially trained health professionals.

“A lot of patients, they kind of muddle along, treatment after treatment, with little idea whether something’s going to work,” says psychiatric researcher Dr. Amit Etkin.

One reason it’s difficult to know which antidepressant medications will work is that there are likely different biological mechanisms that can cause depression. Two people with similar symptoms may both be diagnosed with depression, but the causes of their symptoms could be different. As NIH depression researcher Dr. Carlos Zarate explains, “we believe that there’s not one depression, but hundreds of depressions.”

Depression may be due to many factors. Genetics can put certain people at risk for depression. Stressful situations, physical health conditions, and medications may contribute. And depression can also be part of a more complicated mental disorder, such as bipolar disorder. All of these can affect which treatment would be best to use.

Etkin has been developing methods to distinguish patients with different types of depression based on measurable biological features, or biomarkers. The idea is that different types of patients would respond differently to various treatments. Etkin calls this approach “precision psychiatry.”

One such type of biomarker is electrical activity in the brain. A technique called electroencephalography, or EEG, measures electrical activity using electrodes placed on the scalp. When Etkin was at Stanford University, he led a research team that developed a machine-learning algorithm to predict treatment response based on EEG signals. The team applied the algorithm to data from a clinical trial of the antidepressant sertraline (Zoloft) involving more than 300 people.

EEG data for the participants were collected at the outset. Participants were then randomly assigned to take either sertraline or an inactive placebo for eight weeks. The team found a specific set of signals that predicted the participants’ responses to sertraline. The same neural “signature” also predicted which patients with depression responded to medication in a separate group.

Etkin’s team also examined this neural signature in a set of patients who were treated with TMS and psychotherapy. People who were predicted to respond less to sertraline had a greater response to the TMS/psychotherapy combination.

Etkin continues to develop methods for personalized depression treatment through his company, Alto Neuroscience. He notes that EEG has the advantage of being low-cost and accessible; data can even be collected in a patient’s home. That’s important for being able to get personalized treatments to the large number of people they could help. He’s also working on developing antidepressant drugs targeted to specific EEG profiles. Candidate drugs are in clinical trials now.

“It’s not like a pie-in-the-sky future thing, 20-30 years from now,” Etkin explains. “This is something that could be in people's hands within the next five years.”

New tricks for old drugs

While some researchers focus on matching patients with their optimal treatments, others aim to find treatments that can work for many different patients. It turns out that some drugs we’ve known about for decades might be very effective antidepressants, but we didn’t recognize their antidepressant properties until recently.

One such drug is ketamine. Ketamine has been used as an anesthetic for more than 50 years. Around the turn of this century, researchers started to discover its potential as an antidepressant. Zarate and others have found that, unlike traditional antidepressants that can take weeks to take effect, ketamine can improve depression in as little as one day. And a single dose can have an effect for a week or more. In 2019, the FDA approved a form of ketamine for treating depression that is resistant to other treatments.

But ketamine has drawbacks of its own. It’s a dissociative drug, meaning that it can make people feel disconnected from their body and environment. It also has the potential for addiction and misuse. For these reasons, it’s a controlled substance and can only be administered in a doctor’s office or clinic.

Another class of drugs being studied as possible antidepressants are psychedelics. These include lysergic acid diethylamide (LSD) and psilocybin, the active ingredient in magic mushrooms. These drugs can temporarily alter a person’s mood, thoughts, and perceptions of reality. Some have historically been used for religious rituals, but they are also used recreationally.

In clinical studies, psychedelics are typically administered in combination with psychotherapy. This includes several preparatory sessions with a therapist in the weeks before getting the drug, and several sessions in the weeks following to help people process their experiences. The drugs are administered in a controlled setting.

Dr. Stephen Ross, co-director of the New York University Langone Health Center for Psychedelic Medicine, describes a typical session: “It takes place in a living room-like setting. The person is prepared, and they state their intention. They take the drug, they lie supine, they put on eye shades and preselected music, and two therapists monitor them.” Sessions last for as long as the acute effects of the drug last, which is typically several hours. This is a healthcare-intensive intervention given the time and personnel needed.

In 2016, Ross led a clinical trial examining whether psilocybin-assisted therapy could reduce depression and anxiety in people with cancer. According to Ross, as many as 40% of people with cancer have clinically significant anxiety and depression. The study showed that a single psilocybin session led to substantial reductions in anxiety and depression compared with a placebo. These reductions were evident as soon as one day after psilocybin administration. Six months later, 60-80% of participants still had reduced depression and anxiety.

Psychedelic drugs frequently trigger mystical experiences in the people who take them. “People can feel a sense…that their consciousness is part of a greater consciousness or that all energy is one,” Ross explains. “People can have an experience that for them feels more ‘real’ than regular reality. They can feel transported to a different dimension of reality.”

About three out of four participants in Ross’s study said it was among the most meaningful experiences of their lives. And the degree of mystical experience correlated with the drug’s therapeutic effect. A long-term follow-up study found that the effects of the treatment continued more than four years later.

If these results seem too good to be true, Ross is quick to point out that it was a small study, with only 29 participants, although similar studies from other groups have yielded similar results. Psychedelics haven’t yet been shown to be effective in a large, controlled clinical trial. Ross is now conducting a trial with 200 people to see if the results of his earlier study pan out in this larger group. For now, though, psychedelics remain experimental drugs—approved for testing, but not for routine medical use.

Unlike ketamine, psychedelics aren’t considered addictive. But they, too, carry risks, which certain conditions may increase. Psychedelics can cause cardiovascular complications. They can cause psychosis in people who are predisposed to it. In uncontrolled settings, they have the risk of causing anxiety, confusion, and paranoia—a so-called “bad trip”—that can lead the person taking the drug to harm themself or others. This is why psychedelic-assisted therapy takes place in such tightly controlled settings. That increases the cost and complexity of the therapy, which may prevent many people from having access to it.

Better, safer drugs

Despite the promise of ketamine or psychedelics, their drawbacks have led some researchers to look for drugs that work like them but with fewer side effects.

Depression is thought to be caused by the loss of connections between nerve cells, or neurons, in certain regions of the brain. Ketamine and psychedelics both promote the brain’s ability to repair these connections, a quality called plasticity. If we could understand how these drugs encourage plasticity, we might be able to design drugs that can do so without the side effects.

Dr. David Olson at the University of California, Davis studies how psychedelics work at the cellular and molecular levels. The drugs appear to promote plasticity by binding to a receptor in cells called the 5-hydroxytryptamine 2A receptor (5-HT2AR). But many other compounds also bind 5-HT2AR without promoting plasticity. In a recent NIH-funded study, Olson showed that 5-HT2AR can be found both inside and on the surface of the cell. Only compounds that bound to the receptor inside the cells promoted plasticity. This suggests that a drug has to be able to get into the cell to promote plasticity.

Moreover, not all drugs that bind 5-HT2AR have psychedelic effects. Olson’s team has developed a molecular sensor, called psychLight, that can identify which compounds that bind 5-HT2AR have psychedelic effects. Using psychLight, they identified compounds that are not psychedelic but still have rapid and long-lasting antidepressant effects in animal models. He’s founded a company, Delix Therapeutics, to further develop drugs that promote plasticity.

Meanwhile, Zarate and his colleagues have been investigating a compound related to ketamine called hydroxynorketamine (HNK). Ketamine is converted to HNK in the body, and this process appears to be required for ketamine’s antidepressant effects. Administering HNK directly produced antidepressant-like effects in mice. At the same time, it did not cause the dissociative side effects and addiction caused by ketamine. Zarate’s team has already completed phase I trials of HNK in people showing that it’s safe. Phase II trials to find out whether it’s effective are scheduled to begin soon.  

“What [ketamine and psychedelics] are doing for the field is they’re helping us realize that it is possible to move toward a repair model versus a symptom mitigation model,” Olson says. Unlike existing antidepressants, which just relieve the symptoms of depression, these drugs appear to fix the underlying causes. That’s likely why they work faster and produce longer-lasting effects. This research is bringing us closer to having safer antidepressants that only need to be taken once in a while, instead of every day.

—by Brian Doctrow, Ph.D.

Related Links

• How Psychedelic Drugs May Help with Depression
• Biosensor Advances Drug Discovery
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• How Ketamine Relieves Symptoms of Depression
• Protein Structure Reveals How LSD Affects the Brain
• Predicting The Usefulness of Antidepressants
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• When Sadness Lingers: Understanding and Treating Depression
• Psychedelic and Dissociative Drugs

References:  An electroencephalographic signature predicts antidepressant response in major depression.  Wu W, Zhang Y, Jiang J, Lucas MV, Fonzo GA, Rolle CE, Cooper C, Chin-Fatt C, Krepel N, Cornelssen CA, Wright R, Toll RT, Trivedi HM, Monuszko K, Caudle TL, Sarhadi K, Jha MK, Trombello JM, Deckersbach T, Adams P, McGrath PJ, Weissman MM, Fava M, Pizzagalli DA, Arns M, Trivedi MH, Etkin A.  Nat Biotechnol.  2020 Feb 10. doi: 10.1038/s41587-019-0397-3. Epub 2020 Feb 10. PMID: 32042166. Rapid and sustained symptom reduction following psilocybin treatment for anxiety and depression in patients with life-threatening cancer: a randomized controlled trial. Ross S, Bossis A, Guss J, Agin-Liebes G, Malone T, Cohen B, Mennenga SE, Belser A, Kalliontzi K, Babb J, Su Z, Corby P, Schmidt BL. J Psychopharmacol . 2016 Dec;30(12):1165-1180. doi: 10.1177/0269881116675512. PMID: 27909164. Long-term follow-up of psilocybin-assisted psychotherapy for psychiatric and existential distress in patients with life-threatening cancer. Agin-Liebes GI, Malone T, Yalch MM, Mennenga SE, Ponté KL, Guss J, Bossis AP, Grigsby J, Fischer S, Ross S. J Psychopharmacol . 2020 Feb;34(2):155-166. doi: 10.1177/0269881119897615. Epub 2020 Jan 9. PMID: 31916890. Psychedelics promote neuroplasticity through the activation of intracellular 5-HT2A receptors.  Vargas MV, Dunlap LE, Dong C, Carter SJ, Tombari RJ, Jami SA, Cameron LP, Patel SD, Hennessey JJ, Saeger HN, McCorvy JD, Gray JA, Tian L, Olson DE.  Science . 2023 Feb 17;379(6633):700-706. doi: 10.1126/science.adf0435. Epub 2023 Feb 16. PMID: 36795823. Psychedelic-inspired drug discovery using an engineered biosensor.  Dong C, Ly C, Dunlap LE, Vargas MV, Sun J, Hwang IW, Azinfar A, Oh WC, Wetsel WC, Olson DE, Tian L.  Cell . 2021 Apr 8: S0092-8674(21)00374-3. doi: 10.1016/j.cell.2021.03.043. Epub 2021 Apr 28. PMID: 33915107. NMDAR inhibition-independent antidepressant actions of ketamine metabolites. Zanos P, Moaddel R, Morris PJ, Georgiou P, Fischell J, Elmer GI, Alkondon M, Yuan P, Pribut HJ, Singh NS, Dossou KS, Fang Y, Huang XP, Mayo CL, Wainer IW, Albuquerque EX, Thompson SM, Thomas CJ, Zarate CA Jr, Gould TD. Nature . 2016 May 26;533(7604):481-6. doi: 10.1038/nature17998. Epub 2016 May 4. PMID: 27144355.

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Research Review: What Have We Learned About Adolescent Substance Use?

Adolescence is a critical biological, psychological, and social developmental stage involving heightened risk for substance use and associated adverse consequences. This review, synthesizing emerging findings on this complex topic, is intended to inform research and clinical care focused on adolescents.

Literature searches were conducted using PubMed, yielding a cross-section of observational and interventional studies focused on adolescent substance use. Findings were organized and categorized to cover key areas of epidemiology, neurobiology, prevention, and treatment.

Adolescent substance-related attitudes and use patterns have evolved over time, informed by adult and peer behaviors, public policy, media messaging, substance availability, and other variables. A number of risk and resiliency factors contribute to individual differences in substance use and related consequences. Advances in observational techniques have provided enhanced understanding of adolescent brain development, and its implications for substance use. Prevention efforts have yielded mixed results, and while a number of adolescent-targeted evidence-based treatments for substance use disorders have been developed, effect sizes are generally modest, indicating the need for further research to enhance prevention and treatment outcomes.

Conclusions

Substance use in adolescence is heterogeneous, ranging from normative to pathological, and can lead to significant acute and long-term morbidity and mortality. Understanding risk and resiliency factors, underlying neurobiology, and optimal developmentally-sensitive interventions is critical in addressing substance-associated problems in adolescence.

Introduction

Adolescence is a critical developmental phase involving significant physical, cognitive, emotional, social, and behavioral changes. The neurobiological alterations underlying these complex developmental processes may predispose adolescents to initiate substance use, to develop substance use disorders, and to experience potentially serious and long-lasting substance-related adverse consequences. Given the high prevalence of problematic substance use in this age range, and given the unique biopsychosocial context, research has increasingly focused on characterizing adolescent substance use disorders, with particular focus on optimizing and disseminating evidence-based prevention, assessment, and treatment interventions. The present review was conducted to provide an overview of recent clinically relevant advances in the field.

Literature searches were conducted via PubMed, and information was compiled to yield an overview of clinically relevant advances in knowledge regarding adolescent substance use, spanning epidemiology, neurobiology, assessment, and interventions.

Epidemiology

Prevalence of use.

Substance use is typically initiated during adolescence. Alcohol is the most commonly used substance among adolescents, with 64% of 18 year olds endorsing lifetime alcohol use, followed by marijuana (45%) and cigarette use (31%) ( Johnston et al., 2017 ). Overall, rates of adolescent substance use have remained relatively stable over the past several years, with a few notable exceptions. Cigarette use has declined dramatically over the past several decades, while e-cigarette use has become more prevalent in recent years. Thirteen percent of teens report using e-cigarettes in the past month, compared to 3% reporting cigarette use, with a concerning increase in the number of never-smoking youth reporting e-cigarette use ( Bunnell et al., 2015 ). Another recent trend includes increased frequency of marijuana use, with 6% of 18 year olds reporting using marijuana daily ( Johnston et al., 2017 ). Attitudes about marijuana use continue to move toward greater acceptance; the perception of risk about using marijuana is at the lowest point ever recorded, with a third of 18 year olds reporting that regular marijuana use is harmful. While overall rates of marijuana use have remained relatively stable over the past several years, decreased perception of harm typically corresponds with increased use. Other drug use is relatively uncommon, with less than 6% of adolescents reporting past month use of other illicit drugs ( Johnston et al., 2017 ). A brief summary of rates of current substance use, by substance and by grade level, among adolescents in the United States is presented in Table 1 ( Johnston et al., 2017 ).

Rates (%) of current (30-day) substance use among adolescents in the United States, by substance and grade level ( Johnston et al., 2017 ).

NR=Not Reported

Prevalence of Substance Use Disorders

Adolescent substance use is heterogeneous, ranging from normative early experimentation with substance use to heavier and higher-risk patterns of use. Most youth who use substances do not become addicted; however, the prevalence of substance use disorders is still quite high, with 15% of youth meeting diagnostic criteria for alcohol abuse and 16% for drug abuse by age 18 ( Swendsen et al. 2012 ). Tobacco, alcohol, and marijuana are typically the first addictive substances that youth try. The likelihood of developing a substance use disorder increases significantly when individuals initiate alcohol and drug use during adolescence. Youth who begin drinking before age 15 have four to six times the rate of lifetime alcohol dependence than those who remain abstinent from alcohol use until age 21 ( Grant & Dawson, 1997 ; SAMHSA, 2014 ). The majority of adults who have a substance use disorder started using before age 18 and develop their disorder by age 20, highlighting the need to delay initiation of substance use for as long as possible ( Dennis et al., 2002 ).

Neurobiology

The brain undergoes significant neurodevelopment between childhood and young adulthood, with maturation continuing until around age 25 ( Pfefferbaum et al., 1994 ; Giedd 2004 ). Brain gray matter, which includes mostly nerve cell bodies and dendrites, tends to decrease during adolescence via synaptic pruning and changes in the extracellular matrix ( Gogtay et al., 2004 ; Paus, 2005 ; Petjanek et al., 2011; Raznahan et al., 2014 ; Sowell et al., 1999 ; Stiles & Jernigan, 2010 ). Concurrently, white-matter volume and white matter integrity increases over this time, which allows for more efficient and rapid communication between brain regions ( Giedd, 2004 ; Lebel et al., 2011 ; 2012 ). Brain regions have time-varying developmental trajectories, with lower-order sensorimotor regions maturing first, and regions associated with higher-order cognitive functioning (e.g., frontal and subcortical brain regions) developing later in adolescence and young adulthood ( Sowell et al., 1999 , 2004 ; Shaw et al., 2008 ; Giedd and Rapoport, 2010 ; Stiles & Jernigan, 2010 ). Healthy brain development throughout adolescence is imperative, with even minor changes in neurodevelopmental trajectories affecting a range of cognitive, emotional, and social functioning ( Nagy et al., 2004 ; Casey et al., 2008 ). Altered brain development due to exposure of neurotoxins during adolescence, particularly alcohol and other drug use, could set the stage for cognitive problems into adulthood, conferring functional consequences throughout life.

Adolescents are known to be particularly vulnerable, compared to children and adults, to initiation of substance use and progression to problematic use. Dopaminergic systems are significantly reorganized in the adolescent brain, with decreases in dopamine in striatal structures such as the nucleus accumbens, in the context of limited inhibitory control, potentially precipitating high-risk behaviors to compensate for dopaminergic void ( Chambers et al., 2003 ; Spear, 2002 ). Theories have suggested an “imbalance” in brain development underlying a propensity for risk behavior, including substance use, during adolescence, with emotion and reward systems (e.g., amygdala, nucleus accumbens) developing before cognitive control systems (e.g., prefrontal cortex) ( Casey et al., 2008 ; Somerville et al., 2010 ). Within the window of this imbalance, adolescents’ decisions may be based on brain processes favoring immediate reward over consideration of longer-term consequences ( Casey & Jones, 2010 ). This theoretical model has been supported by a number of recent experimental studies ( Baker et al., 2015 ; Mills et al., 2014 ; van Duijvenvoorde et al., 2016 ).

In the past 10 years, there has been a proliferation of neuroimaging and neurocognitive studies that have attempted to understand neural risk factors that predate adolescent substance use, as well as determine the effect of substance use on the developing brain. Because alcohol and marijuana are the two most commonly used substances, most existing research has focused on these substances. Several large-scale, multisite longitudinal studies are currently underway to help further understand the consequences of alcohol and marijuana use on cognitive functioning, as well as determine the effects of tobacco and other less frequently used drugs on adolescent brain development. These studies include the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) which is following >800 youth across 5 different sites in the US for at least 10 years ( Brown et al., 2015 ); the IMAGEN study which has followed 2,000 youth from England, Ireland, Germany, and France for the past 8 years ( https://imagen-europe.com/ ); and the recently launched Adolescent Brain Cognitive Development (ABCD; http://abcdstudy.org/ ), which will follow 11,500 youth across 21 US sites for at least 10 years. Existing studies have relatively small, homogeneous samples; therefore, these large scale studies will allow for a more complex understanding how demographic, social, genetic, and environmental factors play a role in the impact of substance use on brain development.

Several neurocognitive features have been identified as risk factors for initiation of alcohol and other drug use during adolescence ( Squeglia & Gray, 2016 ; Squeglia & Cservenka, 2017 ). Findings suggest poorer performance on tasks of inhibition and working memory ( Heitzeg et al., 2015 ; Khurana et al., 2013 ; López-Caneda et al., 2014; Squeglia et al., 2014a , 2017 ), smaller brain volumes in reward and cognitive control regions ( Cheetham et al., 2012 , 2014 ; Squeglia et al., 2014a ; Urošević et al., 2015 ; Weiland et al., 2014 ; Whelan et al., 2014 ), less brain activation during executive functioning tasks, and heightened reward responsivity are important predictors of adolescent substance use ( Dager et al., 2014 ; Heitzeg et al., 2014 ; Mahmood et al., 2013 ; Norman et al., 2011 ; Ramage et al., 2015 ; Squeglia et al., 2012 , 2017 ; Wetherill et al., 2013a ; Whelan et al., 2014 ).

Alcohol and marijuana use during adolescence has been associated with poorer performance on a range of cognitive domains. In a sample of 234 healthy adolescents, greater alcohol and marijuana use between approximately ages 13 to 17 was associated with poorer verbal memory, visuospatial functioning, and psychomotor speed ( Nguyen-Louie et al., 2015 ). Gender specific effects have also been found, with heavy-drinking girls showing worsening performance on tests of visuospatial functioning compared to non-using girls, and alcohol-using boys showing poorer attention compared to alcohol-naïve boys ( Squeglia et al., 2009 ). In a 10-year longitudinal study, treatment-seeking youth who continued to use alcohol and other substances showed poorer verbal learning and memory, visuospatial functioning, and working memory and attention by age 25 ( Hanson et al., 2011a , 2011b ). A dose-dependent relationship was found, with heavier use patterns and greater hangover and withdrawal symptoms relating to poorer cognitive functioning. Youth who were in remission from alcohol and drug use performed similarly to those who continued to meet criteria for a substance use disorder, suggesting substance use during adolescence could have persisting effects into adulthood ( Hanson et al., 2011b ).

There is some suggestion that cognitive domains are differentially impacted by marijuana use in adolescence, with attention, declarative memory, and cognitive control particularly affected ( Randolph et al., 2013 ). In a longitudinal study of marijuana and alcohol-using youth, substance use was related to worsening performance on several cognitive domains when compared to non-using youth, including worse performance on tests of complex attention, memory, processing speed, and visuospatial functioning, with early use (before age 16) relating to worse performance ( Jacobus et al., 2015 ). A large longitudinal birth cohort study from New Zealand (N=1,037) found that persistent adolescent-onset marijuana use was associated with an IQ decline of more than 5 points in the most persistent marijuana-use group, with deficits persisting into adulthood ( Meier et al., 2012 ). However, a recent longitudinal twin study found that IQ deficits observed in marijuana users may be attributable to confounding factors like familial and environmental influences rather than the direct neurotoxic effect of marijuana ( Jackson et al., 2016 ). The follow-up assessment periods for these studies differed, with the Meier study ending at age 38 and the Jackson study following youth until age ~20; regular use over a prolonged period may result in more deleterious effects.

Adolescent alcohol and marijuana use has also been associated with a range of structural and functional brain changes. In the largest prospective study to date on this topic ( N =134), alcohol-using adolescents showed abnormal neurodevelopmental trajectories when compared to continuously non-using controls, including accelerated decreases in gray matter volume (particularly in frontal and temporal regions) and attenuated increases in white matter volume over the ~5 year follow-up ( Squeglia et al., 2015 ), replicating earlier studies with smaller sample sizes ( Luciana et al., 2013 ; Squeglia et al., 2014b ). These findings suggest potentially non-beneficial pruning or, alternatively, premature cortical gray matter decline in alcohol-using youth. In a study examining white matter development, adolescents with extensive marijuana- and alcohol-use histories showed worsening white matter integrity over an 18 month (Baba et al., 2013) and 3-year follow-up ( Jacobus et al., 2013a , 2013b ) in a number of important white matter tracts when compared to non-using youth, as well as poorer performance on tests of neurocognitive functioning. In conjunction with structural changes, adolescent alcohol and marijuana use appears to also affect brain functioning. On several functional MRI studies, youth who initiated heavy alcohol use during adolescence have shown increasing brain activation over time on tests of visual working memory ( Squeglia et al., 2012 ) and inhibition ( Wetherill et al., 2013a , 2013b ), when compared to non-using peers.

Risk Factors

Several factors increase the likelihood of an individual developing a substance use problem, including familial, social, and individual risk factors ( Whitesell et al., 2013 ). Vulnerability for developing substance-related problems is especially heightened among individuals with a family history of substance use disorder ( Cservenka, 2016 ). A recent meta-analysis of twin and adoption studies found that alcohol use disorder is approximately 50% heritable ( Verhulst, Neale, & Kendler, 2015 ); however, identifying specific genes has been challenging, highlighting the complexity and heterogeneity of the disorder ( Hart & Kranzler, 2015 ; Tawa, Hall, & Lohoff, 2016 ). Findings suggest there are a number of genes, each with relatively small effects, that interact with each other and with the environment ( Enoch, 2012 ) to make an individual more or less susceptible to having a substance use disorder ( Meyers & Dick, 2010 ). While specific genes have not been consistently identified, youth with a family history of alcohol use disorder are 3–5 times more likely to develop an alcohol use disorder than youth without a family history of alcoholism ( Cotton, 1979 ).

Males tend to have higher rates of substance use than females ( SAMSHA, 2014 ). Other important risk factors for adolescent substance use include environmental factors such as early exposure to traumatic life events ( Dube et al., 2006 ), prenatal exposure to alcohol and other drugs ( Enoch et al., 2011 ), lack of parental supervision and monitoring ( Nash et al., 2005 ), sleep problems (Shibely et al., 2008), being involved in romantic relationships ( Squeglia et al., 2017 ; Whelan et al., 2014 ), and peer substance use ( Leung et al., 2014 ). Co-occurring psychopathology, including ADHD and depression have been shown to significantly increase the risk of adolescent alcohol use ( Charach et al, 2011 ; Lee et al., 2011 ; Libby et al., 2005 ; Rao et al., 1999 ; Taylor, 2011 ; Wu et al., 2008 ). Additionally, childhood depression and conduct disorder symptoms predict persistence of substance dependence in adulthood ( Meier et al., 2016 ). Other research suggests that externalizing, but not internalizing, mental health problems in childhood predict later substance use in males and females, while among females adolescent substance use predicts internalizing disorders in adulthood ( Miettunen et al., 2014 ).

Prevention science is grounded in the premise that modulation of risk and protective factors may affect the probability of later problems ( Coie et al., 1993 ). Applied to adolescent substance use, this has been implemented across a number of modalities and settings, with the goal of reducing modifiable risk factors and enhancing/reinforcing modifiable protective factors ( Harrop & Catalano, 2016 ). Most commonly, programs have been developed and evaluated in school, family, and community settings. Evidence is mixed amid heterogeneity of methodology and outcomes between studies, but there is some support for parenting-focused ( Allen et al., 2016 ), school-based teacher-led ( Lize et al., 2017 ), and peer-led prevention programs ( MacArthur et al., 2016 ).

Screening and Assessment

Despite the serious implications of adolescent substance use, many clinical providers do not conduct routine screening, and most that do fail to utilize a validated screening method ( Harris et al., 2012 ). In light of this, considerable recent effort has focused on developing and disseminating efficient and reliable screening methods for adolescent substance use ( Levy et al., 2016 ). Screening tools can potentially be used across a number of settings where adolescents are present, though to date most research in this area has focused on primary care practice. The ideal tool would be both sensitive and specific to substance use and related problems, and would guide subsequent in-depth assessment and intervention when appropriate. This must be balanced with the need for time efficiency amid busy clinical practice in which a wide variety of health screening assessments are indicated.

Two brief screeners have strong evidence of achieving the balance of the aforementioned goals, and can be delivered via interview or electronic administration. The Screening to Brief Intervention (S2BI), which queries the adolescent regarding frequency of using 8 types of drugs in the past year, yields high sensitivity and specificity for identifying use and substance use disorders ( Levy et al., 2014 ). Similarly, the Brief Screener for Tobacco, Alcohol, and Other Drugs (BSTAD) queries frequency of use in the past year, with optimal cutoff points for identifying substance use disorders as ≥6 days of tobacco use, ≥2 days of alcohol use, and ≥2 days of marijuana use ( Kelly et al., 2014 ). Both screeners can be delivered electronically, which is a preferred method for adolescents. In practice, adolescent patients can complete the screener via mobile electronic device in the waiting area, and the results can be delivered to the provider in anticipation of the visit and interview.

Initial screeners such as the S2BI and BSTAD can be complemented with subsequent brief assessments to evaluate level of substance involvement and severity of substance-related problems. These assessments can help determine the level and modality of treatment that may be needed, spanning from psychoeducation and/or brief intervention in the primary care office to more intensive service referrals. The CRAFFT (Car, Relax, Alone, Friends/Family, Forget, Trouble), ASSIST (Alcohol, Smoking and Substance Involvement Screening Test) and GAIN (Global Appraisal of Individual Needs) are all validated for this purpose. The CRAFFT and ASSIST serve as adolescent-validated analogues to the adult screener CAGE, the latter of which is not developmentally appropriate for adolescents ( Gryczynski et al., 2015 ; Knight et al., 1999 ). The GAIN assesses for both substance use disorders and potentially associated mental health disorders, including four subscales assessing substance use, internalizing disorders, externalizing disorders, and crime/violence ( Dennis et al., 2006 ).

When more thorough and formal evaluation is indicated (i.e., when brief screening is highly suggestive of substance-related problems requiring intervention), diagnostic evaluation via the Diagnostic and Statistical Manual of Mental Disorders, 5 th Edition (DSM-5), may be undertaken ( American Psychiatric Association, 2013 ). Within this framework, problematic substance use may be diagnostically categorized as a substance use disorder (e.g., Cannabis Use Disorder), with severity of mild, moderate, or severe, depending on the number of substance use disorder symptoms endorsed for a given substance. Diagnostic evaluation should be complemented by functional behavioral analysis, in which substance use is evaluated as a problem behavior with antecedents and consequences which may be unique to a given adolescent’s substance use. The functional analysis framework is used to determine what antecedents and consequences are potentially modifiable to reduce the likelihood of ongoing problem behavior ( Randall et al., 2001 ).

Laboratory testing, most commonly urine drug testing, is often used to complement self-report when evaluating adolescent substance use; it is, however, not generally supported as a standalone screening or assessment for substance use ( Hadland & Levy, 2016 ). Particularly in situations when trust has been eroded within a family and the veracity of an adolescent’s self-report is in doubt, urine testing may serve as a useful, though imperfect, method for objective assessment. With some exceptions, most studies have shown reasonable agreement between adolescent self-report and urine drug test results ( Gignac et al., 2005 ). Parental report is comparatively less consistent with urine testing, reflecting that parents may not often be aware of the adolescent’s day-to-day substance use patterns. Variations in detection times due to substance, dose, chronicity of use, cutoff used, and metabolism of user, should be noted as potential limits of urine testing. Additionally, some “designer” and synthetic substances may not be included among commonly available urine drug testing panels. Home drug testing kits are widely available, but often lack informational guidance to inform parents/guardians of empirically supported strategies to incorporate them as a part of treatment and monitoring, indicating that clear guidance by the provider is critical when considering drug testing at home rather than in clinic ( Washio et al., 2014 ).

Treatment development for adolescent substance use disorders has focused primarily on psychosocial interventions, spanning individual, group, and family modalities. The intensity and duration of investigated treatments has varied from brief (even single-session) interventions to extended multimodal strategies. The majority of studies have evaluated office-based outpatient interventions, many of which were developmentally adapted from established adult-targeted treatments.

Despite the considerable appeal of brief interventions as part of the Screening, Brief Intervention, and Referral to Treatment (SBIRT) model, standalone brief interventions have demonstrated very limited effects when provided to adolescents with substance use disorders ( Young et al., 2014 ). This is similarly the case with brief school-based interventions ( Carney et al., 2016 ) and brief standalone motivational interviewing approaches ( Li et al., 2016 ). These strategies appear more useful when provided as a component of multimodal intervention with increased overall intensity and duration.

A recent comprehensive review indicated that the most well established efficacious treatments include ecological family-based treatment, group cognitive-behavioral therapy (CBT), and individual CBT, while fair evidence supports behavioral family therapy and motivational enhancement therapy (MET) ( Hogue et al., 2014 ). Substantial evidence supports combined treatment approaches, incorporating elements from the aforementioned modalities and others to enhance outcomes. Given that adolescent substance use disorders are heterogeneous and multidetermined, treatment approaches that address multiple biopsychosocial targets are often indicated. Among combined treatments, strong evidence supports combined MET and CBT, as well as combined MET, CBT, and behavioral family-based treatment ( Hogue et al., 2014 ). Outcomes are further enhanced by complementing the aforementioned treatments with contingency management (CM), a behavioral treatment based on operant conditioning principles, in which tangible rewards are provided for objectively confirmed desired behaviors (e.g., token provided for negative urine drug test) ( Stanger et al., 2015 , 2016 ). In general, evaluated treatments in large-scale trials have demonstrated short-term substance reduction and/or cessation, but adolescents with substance use disorders, even with the best evidence-based care, rarely achieve long-term abstinence ( Dennis et al., 2004 ; Hogue et al., 2014 ; Waldron & Turner, 2008 ).

Pharmacotherapy is an established complement to psychosocial treatment for adults with substance use disorders, with several medications receiving United States Food and Drug Administration (FDA) approval for treatment of alcohol, tobacco, and opioid use disorders. While the neuropathology of adolescent substance use disorders is increasingly recognized, relatively little work has focused on developing pharmacotherapies for this age group. To date, only buprenorphine-naloxone possesses FDA approval for opioid use disorder in youth ages 16 and older. Other medications have been studied at least preliminarily for youth alcohol, tobacco, cannabis, and opioid use disorders, yielding mixed results ( Hammond & Gray, 2016 ). Findings from randomized controlled trials, though not yet exhaustive, indicate that select pharmacotherapies may be considered as adjunctive treatments to psychosocial interventions: buprenorphine-naloxone maintenance to improve treatment retention and outcomes for opioid use disorder ( Marsch et al., 2005 ; Woody et al., 2008 ), N -acetylycysteine as an adjunct to cessation counseling and contingency management for cannabis use disorder ( Gray et al., 2012 ), and nicotine patch or bupropion SR to improve tobacco cessation rates ( Gray et al., 2011 , Moolchan et al., 2005 ; Muramoto et al., 2007 ).

Given the ubiquity of mobile technology among adolescents, and the considerable logistical barriers to office-based care (e.g., transportation, accessibility), recent research has focused on translating evidence-based care for delivery via electronic platforms. A meta-analysis revealed a small positive effect size for text messaging interventions for youth with substance use problems ( Mason et al., 2015 ), and a pilot study demonstrated the feasibility of using smartphones to provide recovery support for adolescents after discharge from residential treatment ( Dennis et al., 2015 ). Ongoing work is focused on combining ecological momentary assessment and smartphone application intervention in adolescents with substance use and co-occurring psychiatric disorders ( Benarous et al., 2016 ).

Limitations

This review provides a general overview of a broad, complex topic area, with multiple lines of ongoing research. The methodology of the review was by design not structured or meta-analytic, but rather a general cross-section of recent advances and findings. Additionally, the review focused largely, but not exclusively, on data derived from United States samples. As such, caution should be taken in interpreting findings, acknowledging the potential for limitations in generalizability across populations, policies, and cultural and environmental factors.

Recent research has significantly advanced the understanding of substance use in adolescence. Survey-based epidemiological studies have identified trends in substance-related attitudes and rates of use of various substances, while emerging longitudinal neuroimaging studies have elucidated the neurobiology underlying adolescents’ propensity for substance initiation and progression to substance use disorders, with potentially lasting substance-related adverse consequences. A variety of prevention programs have been implemented across settings with varying degrees of success. Novel screening and assessment instruments have been developed to efficiently identify youth with particular risk for serious substance-related problems, and a number of evidence-based treatment approaches have been shown to be effective in reducing substance use and substance-related problems. Unfortunately, adolescents with substance use disorders rarely achieve long-term abstinence even with the most robust evidence-based treatments, indicating that further work is needed to optimize methods to understand and address this important public health issue.

• ▪ Adolescents, amid rapid biopsychosocial development, are more prone than children or adults to initiating substance use and suffering lasting substance-related adverse consequences
• ▪ Recent research has elucidated the neurobiological processes underlying substance use risk in adolescents, as well as substance-related neuropathology among adolescents with substance use disorders
• ▪ Advances in prevention, screening, assessment, and treatment research have yielded evidence-based interventions to address adolescent substance use disorders
• ▪ Further research is needed to enhance outcomes and reduce the considerable public health burden of adolescent substance use disorders

Acknowledgments

Dr. Gray has received research support (medication only) from Pfizer.

Dr. Squeglia reports no competing interests.

• Allen ML, Garcia-Huidobro D, Porta C, Curran D, Patel R, Miller J, Borowsky I. Effective parenting interventions to reduce youth substance use: A systematic review. Pediatrics. 2016; 138 (2):e20154425. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5. Washington, DC: Author; 2013. [ Google Scholar ]
• Baker ST, Lubman DI, Yücel M, Allen NB, Whittle S, Fulcher BD, Zalesky A, Fornito A. Developmental changes in brain network hub connectivity in late adolescence. Journal of Neuroscience. 2015; 35 (24):9078–9087. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Bava S, Jacobus J, Thayer RE, Tapert SF. Longitudinal changes in white matter integrity among adolescent substance users. Alcoholism: Clinical and Experimental Research. 2013; 37 (Suppl 1):E181–189. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Benarous X, Edel Y, Consoli A, Brunelle J, Etter JF, Cohen D, Khazaal Y. Ecological momentary assessment and smartphone application intervention in adolescents with substance use and comorbid severe psychiatric disorders: Study protocol. Frontiers in Psychiatry. 2016; 7 :157. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Brown SA, Brumback T, Tomlinson K, Cummins K, Thompson WK, Nagel BJ, De Bellis MD, Hooper SR, Clark DB, Chung T, Hasler BP, Colrain IM, Baker FB, Prouty D, Pfefferbaum A, Sullivan EV, Pohl KM, Rohlfing T, Nichols BN, Chu W, Tapert SF. The National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA): A multi-site study of adolescent development and substance use. Journal of Studies on Alcohol and Drugs. 2015; 76 :895–908. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Bunnell R, Agaku IT, Arrazola RA, Apelberg BJ, Caraballo RS, Corey CG, Coleman BN, Dube SR, King BA. Intentions to smoke cigarettes among never-smoking US middle and high school electronic cigarette users: National Youth Tobacco Survey, 2011–2013. Nicotine & Tobacco Research. 2015; 17 (2):228–235. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Carney T, Myers BJ, Louw J, Okwundu CI. Brief school-based interventions and behavioural outcomes for substance-using adolescents. Cochrane Database of Systematic Reviews. 2016:CD008969. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Casey BJ, Jones RM. Neurobiology of the adolescent brain and behavior: Implications for substance use disorders. Journal of the American Academy of Child and Adolescent Psychiatry. 2010; 49 (12):1189–1201. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Casey BJ, Jones RM, Hare TA. The adolescent brain. Annals of the New York Academy of Sciences. 2008; 1124 :111–126. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Chambers RA, Taylor JR, Potenza MN. Developmental neurocircuitry of motivation in adolescence: A critical period of addiction vulnerability. American Journal of Psychiatry. 2003; 160 (6):1041–1052. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Charach A, Yeung E, Climans T, Lillie E. Childhood attention-deficit/hyperactivity disorder and future substance use disorders: Comparative meta-analyses. Journal of the American Academy of Child and Adolescent Psychiatry. 2011; 50 (1):9–21. [ PubMed ] [ Google Scholar ]
• Cheetham A, Allen NB, Whittle S, Simmons J, Yücel M, Lubman DI. Volumetric differences in the anterior cingulate cortex prospectively predict alcohol-related problems in adolescence. Psychopharmacology. 2014; 231 :1731–1742. [ PubMed ] [ Google Scholar ]
• Cheetham A, Allen NB, Whittle S, Simmons JG, Yücel M, Lubman DI. Orbitofrontal volumes in early adolescence predict initiation of cannabis use: A 4-year longitudinal and prospective study. Biological Psychiatry. 2012; 71 :684–692. [ PubMed ] [ Google Scholar ]
• Coie JD, Watt NF, West SG, Hawkins JD, Asarnow JR, Markman HJ, Ramey SL, Shure MB, Long B. The science of prevention: A conceptual framework and some directions for a national research program. American Psychologist. 1993; 48 (10):1013–1022. [ PubMed ] [ Google Scholar ]
• Cotton NS. The familial incidence of alcoholism: A review. Journal of Studies on Alcohol. 1979; 40 :89–116. [ PubMed ] [ Google Scholar ]
• Cservenka A. Neurobiological phenotypes associated with a family history of alcoholism. Drug and Alcohol Dependence. 2016; 158 :8–21. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Dager AD, Anderson BM, Rosen R, Khadka S, Sawyer B, Jiantonio-Kelly RE, Austad CS, Raskin SA, Tennen H, Wood RM, Fallahi CR, Pearlson GD. Functional magnetic resonance imaging (fMRI) response to alcohol pictures predicts subsequent transition to heavy drinking in college students. Addiction. 2014; 109 :585–595. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Dennis M, Babor TF, Roebuck C, Donaldson J. Changing the focus: The case for recognizing and treating cannabis use disorders. Addiction. 2002; 97 (s1):4–15. [ PubMed ] [ Google Scholar ]
• Dennis ML, Chan YF, Funk RR. 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 Addiction. 2006; 15 (suppl 1):80–91. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Dennis M, Godley SH, Diamond G, Tims FM, Babor T, Donaldson J, Liddle H, Titus JC, Kaminer Y, Webb C, Hamilton N, Funk R. The Cannabis Youth Treatment (CYT) Study: Main findings from two randomized trials. Journal of Substance Abuse Treatment. 2004; 27 (3):197–213. [ PubMed ] [ Google Scholar ]
• Dennis ML, Scott CK, Funk RR, Nicholson L. A pilot study to examine the feasibility of potential effectiveness of using smartphones to provide recovery support for adolescents. Substance Abuse. 2015; 36 (4):486–492. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Meyers JL, Dick DM. Genetic and environmental risk factors for adolescent-onset substance use disorders. Child & Adolescent Psychiatric Clinics of North America. 2010; 19 (3):465–477. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Dube SR, Miller JW, Brown DW, Giles WH, Felitti VJ, Dong M, Anda RF. Adverse childhood experiences and the association with ever using alcohol and initiating alcohol use during adolescence. Journal of Adolescent Health. 2006; 38 (4):444.e1–10. [ PubMed ] [ Google Scholar ]
• Enoch MA. The role of early life stress as a predictor for alcohol and drug dependence. Psychopharmacology (Berl) 2011; 214 (1):17–31. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Enoch MA. The influence of gene-environment interactions on the development of alcoholism and drug dependence. Current Psychiatry Reports. 2012; 14 (2):150–158. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Giedd JN. Structural magnetic resonance imaging of the adolescent brain. Annals of the New York Academy of Sciences. 2004; 1021 :77–85. [ PubMed ] [ Google Scholar ]
• Giedd JN, Rapoport JL. Structural MRI of pediatric brain development: what have we learned and where are we going? Neuron. 2010; 67 :728–734. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Gignac M, Wilens TE, Biederman J, Kwon A, Mick E, Swezey A. Assessing cannabis use in adolescents and young adults: What do urine screen and parental report tell you? Journal of Child and Adolescent Psychopharmacology. 2005; 15 :742–750. [ PubMed ] [ Google Scholar ]
• Gogtay N, Giedd JN, Lusk L, Hayashi KM, Greenstein D, Vaituzis AC, Nugent TF, 3rd, Herman DH, Clasen LS, Toga AW, Rapaport JL, Thompson PM. Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences of the United States of America. 2004; 101 (21):8174–8179. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Grant BF, Dawson DA. Age at onset of alcohol use and its association with DSM-IV alcohol abuse and dependence: Results from the National Longitudinal Alcohol Epidemiologic Survey. Journal of Substance Abuse. 1997; 9 :103–110. [ PubMed ] [ Google Scholar ]
• Gray KM, Carpenter MJ, Baker NL, Hartwell KJ, Lewis AL, Hiott DW, Deas D, Upadhyaya HP. Bupropion SR and contingency management for adolescent smoking cessation. Journal of Substance Abuse Treatment. 2011; 40 :77–86. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Gray KM, Carpenter MJ, Baker NL, DeSantis SM, Kryway E, Hartwell KJ, McRae-Clark AL, Brady KT. A double-blind randomized controlled trial of N -acetylcysteine in cannabis-dependent adolescents. American Journal of Psychiatry. 2012; 169 :805–812. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Gryczynski J, Kelly SM, Mitchell SG, Kirk A, O’Grady KE, Schwartz RP. Validation and performance of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) among adolescent primary care patients. Addiction. 2015; 110 (2):240–247. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hadland SE, Levy S. Objective testing: urine and other drug tests. Child and Adolescent Psychiatric Clinics of North America. 2016; 25 (3):549–565. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hammond CJ, Gray KM. Pharmacotherapy for substance use disorders in youths. Journal of Child and Adolescent Substance Abuse. 2016; 25 (4):292–316. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hanson KL, Cummins K, Tapert SF, Brown SA. Changes in neuropsychological functioning over 10 years following adolescent substance abuse treatment. Psychology of Addictive Behaviors. 2011a; 25 (1):127–142. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hanson KL, Medina KL, Padula CB, Tapert SF, Brown SA. Impact of adolescent alcohol and drug use on neuropsychological functioning in young adulthood: 10-year outcomes. Journal of Child and Adolescent Substance Abuse. 2011b; 20 (2):135–154. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Harris SK, Herr-Zaya K, Weinstein Z, Whelton K, Perfas F, Jr, Castro-Donlan C, Straus J, Schoneman K, Botticelli M, Levy S. Results of a statewide survey of adolescent substance use screening rates and practices in primary care. Substance Abuse. 2012; 33 :321–326. [ PubMed ] [ Google Scholar ]
• Harrop E, Catalano RF. Evidence-based prevention for adolescent substance use. Child and Adolescent Psychiatric Clinics of North America. 2016; 25 :387–410. [ PubMed ] [ Google Scholar ]
• Hart AB, Kranzler HR. Alcohol dependence genetics: Lessons learned from genome-wide association studies (GWAS) and post-GWAS analyses. Alcoholism: Clinical and Experimental Research. 2015; 39 (8):1312–1327. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Heitzeg MM, Cope LM, Martz ME, Hardee JE. Neuroimaging risk markers for substance abuse: Recent findings on inhibitory control and reward system functioning. Current Addiction Reports. 2015; 2 :91–103. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Heitzeg MM, Nigg JT, Hardee JE, Soules M, Steinberg D, Zubieta JK, Zucker RA. Left middle frontal gyrus response to inhibitory errors in children prospectively predicts early problem substance use. Drug and Alcohol Dependence. 2014; 141 :51–57. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hogue A, Henderson CE, Ozechowski TJ, Robbins MS. Evidence base on outpatient behavioral treatments for adolescent substance use: Updates and recommendations 2007–2013. Journal of Clinical Child & Adolescent Psychology. 2014; 43 (5):695–720. [ PubMed ] [ Google Scholar ]
• Jacobus J, Squeglia LM, Infante MA, Castro N, Brumback T, Meruelo AD, Tapert SF. Neuropsychological performance in adolescent marijuana users with co-occurring alcohol use: A three-year longitudinal study. Neuropsychology. 2015; 29 (6):829–843. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Khurana A, Romer D, Betancourt LM, Brodsky NL, Giannetta JM, Hurt H. Working memory ability predicts trajectories of early alcohol use in adolescents: The mediational role of impulsivity. Addiction. 2013; 108 :506–515. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Jackson NJ, Isen JD, Khoddam R, Irons D, Tuvblad C, Iacono WG, McGue M, Raine A, Baker LA. Impact of adolescent marijuana use on intelligence: Results from two longitudinal twin studies. Proceedings of the National Academy of Sciences of the United States of America. 2016; 113 (5):E500–E508. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Jacobus J, Squeglia LM, Bava S, Tapert SF. White matter characterization of adolescent binge drinking with and without co-occurring marijuana use: A 3-year investigation. Psychiatry Research. 2013a; 214 (3):374–381. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Jacobus J, Squeglia LM, Infante MA, Bava S, Tapert SF. White matter integrity pre- and post marijuana and alcohol initiation in adolescence. Brain Sciences. 2013b; 3 (1):396–414. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Johnston LD, O’Malley PM, Miech RA, Bachman JG, Schulenberg JE. Monitoring the Future national survey results on drug use, 1975–2016: Overview, key findings on adolescent drug use. Ann Arbor: Institute for Social Research, The University of Michigan; 2017. [ Google Scholar ]
• Kelly SM, Gryczynski J, Mitchell SG, Kirk A, O’Grady KE, Schwartz RP. Validity of brief screening instrument for adolescent tobacco, alcohol, and drug use. Pediatrics. 2014; 133 (5):819–826. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Knight JR, Shrier LA, Bravender TD, Farrell M, Vander Bilt J, Shaffer HJ. A new brief screen for adolescent substance abuse. Archives of Pediatrics and Adolescent Medicine. 1999; 153 (6):591–596. [ PubMed ] [ Google Scholar ]
• Lebel C, Beaulieu C. Longitudinal development of human brain wiring continues from childhood into adulthood. Journal of Neuroscience. 2011; 31 :10937–10947. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lebel C, Gee M, Camicioli R, Wieler M, Martin W, Beaulieu C. Diffusion tensor imaging of white matter tract evolution over the lifespan. Neuroimage. 2012; 60 :340–352. [ PubMed ] [ Google Scholar ]
• Lee SS, Humphreys KL, Flory K, Liu R, Glass K. Prospective association of childhood attention-deficit/hyperactivity disorder (ADHD) and substance use and abuse/dependence: A meta-analytic review. Clinical Psychology Review. 2011; 31 (3):328–341. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Leung RK, Toumbourou JW, Hemphill SA. The effect of peer influence and selection processes on adolescent alcohol use: A systematic review of longitudinal studies. Health Psychology Review. 2014; 8 (4):426–457. [ PubMed ] [ Google Scholar ]
• Levy S, Weiss R, Sherritt L, Ziemnik R, Spalding A, Van Hook S, Shrier LA. An electronic screen for triaging adolescent substance use by risk levels. JAMA Pediatrics. 2014; 168 (9):822–828. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Levy SJ, Williams JF AAP Committee on Substance Use and Prevention. Substance use screening, brief intervention, and referral to treatment. Pediatrics. 2016; 138 (1):e20161211. [ PubMed ] [ Google Scholar ]
• Li L, Zhu S, Tse N, Tse S, Wong P. Effectiveness of motivational interviewing to reduce illicit drug use in adolescents: A systematic review and meta-analysis. Addiction. 2016; 111 :795–805. [ PubMed ] [ Google Scholar ]
• Libby AM, Orton HD, Stover SK, Riggs PD. What came first, major depression or substance use disorder? Clinical characteristics and substance use comparing teens in a treatment cohort. Addictive Behaviors. 2005; 30 (9):1649–1662. [ PubMed ] [ Google Scholar ]
• Lize SE, Iachini AL, Tang W, Tucker J, Seay KD, Clone S, DeHart D, Browne T. A meta-analysis of the effectiveness of interactive middle school cannabis prevention programs. Prevention Science. 2017; 18 :50–60. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• López-Caneda E, Rodríguez Holguín S, Cadaveira F, Corral M, Doallo S. Impact of alcohol use on inhibitory control (and vice versa) during adolescence and young adulthood: A review. Alcohol and Alcoholism. 2015; 49 :173–181. [ PubMed ] [ Google Scholar ]
• Luciana M, Collins PF, Muetzel RL, Lim KO. Effects of alcohol use initiation on brain structure in typically developing adolescents. American Journal of Drug and Alcohol Abuse. 2013; 39 (6):345–355. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• MacArthur GJ, Harrison S, Caldwell DM, Hickman M, Campbell R. Peer-led interventions to prevent tobacco, alcohol and/or drug use among young people aged 11–21 years: A systematic review and meta-analysis. Addiction. 2016; 111 :391–407. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Mahmood OM, Goldenberg D, Thayer R, Migliorini R, Simmons AN, Tapert SF. Adolescents’ fMRI activation to a response inhibition task predicts future substance use. Addictive Behaviors. 2013; 38 :1435–1441. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Marsch LA, Bickel WK, Badger GJ, Stothart ME, Quesnel KJ, Stanger C, Brooklyn J. Comparison of pharmacological treatments for opioid-dependent adolescents. Archives of General Psychiatry. 2005; 62 :1157–1164. [ PubMed ] [ Google Scholar ]
• Mason M, Ola B, Zaharakis N, Zhang J. Text messaging interventions for adolescent and young adult substance use: A meta-analysis. Prevention Science. 2015; 16 :181–188. [ PubMed ] [ Google Scholar ]
• Meier MH, Caspi A, Ambler A, Harrington H, Houts R, Keefe RS, McDonald K, Ward A, Poulton R, Moffitt TE. Persistent cannabis users show neuropsychological decline from childhood to midlife. Proceedings of the National Academ of Sciences of the United States of America. 2012; 109 :E2657–E2664. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Meier MH, Hall W, Caspi A, Belsky DW, Cerdá M, Harrington HL, Houts R, Poulton R, Moffitt TE. Which adolescents develop persistent substance dependence in adulthood? Using population-representative longitudinal data to inform universal risk assessment. Psychological Medicine. 2016; 46 :877–889. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Miettunen J, Murray GK, Jones PB, Mäki P, Ebeling H, Taanila A, Joukamaa M, Savolainen J, Törmänsen S, Järvelin MR, Veijola J, Moilanen I. Longitudinal associations between childhood and adulthood externalizing and internalizing psychopathology and adolescent substance use. Psychological Medicine. 2014; 44 (8):1727–1738. [ PubMed ] [ Google Scholar ]
• Mills KL, Goddings AL, Clasen LS, Giedd JN, Blakemore SJ. The developmental mismatch in structural brain maturation during adolescence. Developmental Neuroscience. 2014; 36 (3–4):147–160. [ PubMed ] [ Google Scholar ]
• Moolchan ET, Robinson ML, Ernst M, Cadet JL, Pickworth WB, Heishman SJ, Schroeder JR. Safety and efficacy of the nicotine patch and gum for the treatment of adolescent tobacco addiction. Pediatrics. 2005; 115 :e407–e414. [ PubMed ] [ Google Scholar ]
• Muramoto ML, Leischow SJ, Sherrill D, Matthews E, Strayer LJ. Randomized, double-blind, placebo-controlled trial of 2 dosages of sustained-release bupropion for adolescent smoking cessation. Archives of Pediatrics and Adolescent Medicine. 2007; 161 :1068–1074. [ PubMed ] [ Google Scholar ]
• Nagy Z, Westerberg H, Klingberg T. Maturation of white matter is associated with the development of cognitive functions during childhood. Journal of Cognitive Neuroscience. 2004; 16 :1227–1233. [ PubMed ] [ Google Scholar ]
• Nash SG, McQueen A, Bray JH. Pathways to adolescent alcohol use: Family environment, peer influence, and parental expectations. Journal of Adolescent Health. 2005; 37 (1):19–28. [ PubMed ] [ Google Scholar ]
• Nguyen-Louie TT, Castro N, Matt GE, Squeglia LM, Brumback T, Tapert SF. Effects of emerging alcohol and marijuana use behaviors on adolescents’ neuropsychological functioning over four years. Journal of Studies on Alcohol and Drugs. 2015; 76 (5):738–748. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Norman AL, Pulido C, Squeglia LM, Spadoni AD, Paulus MP, Tapert SF. Neural activation during inhibition predicts initiation of substance use in adolescence. Drug and Alcohol Dependence. 2011; 119 :216–223. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Paus T. Mapping brain maturation and cognitive development during adolescence. Trends in Cognitive Science. 2005; 9 (2):60–68. [ PubMed ] [ Google Scholar ]
• Petanjek Z, Judas M, Simic G, Rasin MR, Uylings HB, Rakic P, Kostovic I. Extraordinary neoteny of synaptic spines in the human prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America. 2011; 108 (32):13281–13286. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Pfefferbaum A, Mathalon DH, Sullivan EV, Rawles JM, Zipursky RB, Lim KO. A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood. Archives of Neurology. 1994; 51 :874–887. [ PubMed ] [ Google Scholar ]
• Ramage AE, Lin AL, Olvera RL, Fox PT, Williamson DE. Resting- state regional cerebral blood flow during adolescence: associations with initiation of substance use and prediction of future use disorders. Drug and Alcohol Dependence. 2015; 149 :40–48. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Randall J, Henggeler SW, Cunningham PB, Rowland MD, Swenson CC. Adapting multisystemic therapy to treat adolescent substance abuse more effectively. Cognitive and Behavioral Practice. 2001; 8 (4):359–366. [ Google Scholar ]
• Randolph K, Turull P, Margolis A, Tau G. Cannabis and cognitive systems in adolescents. Adolescent Psychiatry. 2013; 3 (2):135–147. [ Google Scholar ]
• Rao U, Ryan ND, Dahl RE, Birmaher B, Williamson DE, Perel JM. Factors associated with the development of substance use disorder in depressed adolescents. Journal of the American Academy of Child and Adolescent Psychiatry. 1999; 38 (9):1109–1117. [ PubMed ] [ Google Scholar ]
• Raznahan A, Shaw PW, Lerch JP, Clasen LS, Greenstein D, Berman R, Pipitone J, Chakravarty MM, Giedd JN. Longitudinal four-dimensional mapping of subcortical anatomy in human development. Proceedings of the National Academy of Sciences of the United States of America. 2014; 111 (4):1592–1597. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Shaw P, Kabani NJ, Lerch JP, Eckstrand K, Lenroot R, Gogtay N, Greenstein D, Clasen L, Evans A, Rapaport JL, Giedd JN, Wise SP. Neurodevelopmental trajectories of the human cerebral cortex. Journal of Neuroscience. 2008; 28 :3586–3594. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Shibley HL, Malcolm RJ, Veatch LM. Adolescents with insomnia and substance abuse: Consequences and comorbidities. Journal of Psychiatric Practice. 2008; 14 :146–153. [ PubMed ] [ Google Scholar ]
• Somerville LH, Jones RM, Casey BJ. A time of change: Behavioral and neural correlates of adolescent sensitivity to appetitive and aversive emotional cues. Brain and Cognition. 2010; 72 (1):124–133. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sowell ER, Thompson PM, Holmes CJ, Jernigan TL, Toga AW. In vivo evidence for post-adolescent brain maturation in frontal and striatal regions. Nature Neuroscience. 1999; 2 (10):859–861. [ PubMed ] [ Google Scholar ]
• Sowell ER, Thompson PM, Holmes CJ, Jernigan TL, Toga AW. In vivo evidence for post adolescent brain maturation in frontal and striatal regions. Nature Neuroscience. 1999; 2 :859–861. [ PubMed ] [ Google Scholar ]
• Sowell ER, Thompson PM, Leonard CM, Welcome SE, Kan E, Toga AW. Longitudinal mapping of cortical thickness and brain growth in normal children. Journal of Neuroscience. 2004; 24 :8223–8231. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Spear LP. The adolescent brain and the college drinker: Biological basis of propensity to use and misuse alcohol. Journal of Studies on Alcohol Supplement. 2002; 14 :71–81. [ PubMed ] [ Google Scholar ]
• Squeglia LM, Ball TM, Jacobus J, Brumback T, McKenna BS, Nguyen-Louie TT, Sorg SF, Paulus MP, Tapert SF. Neural predictors of alcohol use initiation during adolescence. American Journal of Psychiatry. 2017; 174 (2):172–185. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Squeglia LM, Cservenka A. Adolescence and drug use vulnerability: Findings from neuroimaging. Current Opinion in Behavioral Sciences. 2017; 13 :164–170. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Squeglia LM, Gray KM. Alcohol and drug use and the developing brain. Current Psychiatry Reports. 2016; 18 (5):46. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Squeglia LM, Jacobus J, Nguyen-Louie TT, Tapert SF. Inhibition during early adolescence predicts alcohol and marijuana use by late adolescence. Neuropsychology. 2014; 28 :782–790. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Squeglia LM, Pulido C, Wetherill RR, Jacobus J, Brown GG, Tapert SF. Brain response to working memory over three years of adolescence: influence of initiating heavy drinking. Journal of Studies on Alcohol and Drugs. 2012; 73 :749–760. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Squeglia LM, Rinker DA, Bartsch H, Castro N, Chung Y, Dale AM, Jernigan TL, Tapert SF. Brain volume reductions in adolescent heavy drinkers. Developmental Cognitive Neuroscience. 2014b; 9 :117–125. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Squeglia LM, Spadoni AD, Infante MA, Myers MG, Tapert SF. Initiating moderate to heavy alcohol use predicts changes in neuropsychological functioning for adolescent girls and boys. Psychology of Addictive Behaviors. 2009; 23 (4):715–722. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Squeglia LM, Tapert SF, Sullivan EV, Jacobus J, Meloy MJ, Rohlfing T, Pfefferbaum A. Brain development in heavy-drinking adolescents. American Journal of Psychiatry. 2015; 172 (6):531–542. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Stanger C, Lansing AH, Budney AJ. Advances in research on contingency management for adolescent substance use. Child and Adolescent Psychiatric Clinics of North America. 2016; 25 (4):645–659. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Stanger C, Ryan SR, Scherer EA, Norton GE, Budney AJ. Clinic- and home-based contingency management plus parent training for adolescent cannabis use disorders. Journal of the American Academy of Child and Adolescent Psychiatry. 2015; 54 (6):445–453. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Stiles J, Jernigan TL. The basics of brain development. Neuropsychology Review. 2010; 20 (4):327–348. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Substance Abuse and Mental Health Services Administration. Results from the 2013 National Survey on Drug Use and Health: Summary of National Findings [PDF-3.2MB]NSDUH Series H-48, HHS Publication No(SMA) 14-4863. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2014. [ Google Scholar ]
• Swendsen J, Burstein M, Case B, Conway KP, Dierker L, He J, Merikangas KR. Use and abuse of alcohol and illicit drugs in US adolescents: Results of the National Comorbidity Survey-Adolescent Supplement. Archives of General Psychiatry. 2012; 69 (4):390–398. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Tawa EA, Hall SD, Lohoff FW. Overview of the genetics of alcohol use disorder. Alcohol and Alcoholism. 2016; 51 (50):507–514. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Taylor OD. Adolescent depression as a contributing factor to the development of substance use disorders. Journal of Human Behavior in the Social Environment. 2011; 21 (6):696–710. [ Google Scholar ]
• Urošević S, Collins P, Muetzel R, Schissel A, Lim K, Luciana M. Effects of reward sensitivity and regional brain volumes on substance use initiation in adolescence. Social Cognitive and Affective Neuroscience. 2015; 10 :106–113. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Van Duijvenvoorde AC, Achterberg M, Braams BR, Peters S, Crone EA. Testing a dual-systems model of adolescent brain development using resting-state connectivity analysis. Neuroimage. 2016; 124 :409–420. [ PubMed ] [ Google Scholar ]
• Verhulst B, Neale MC, Kendler KS. The heritability of alcohol use disorders: A meta-analysis of twin and adoption studies. Psychological Medicine. 2015; 45 (5):1061–1072. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Waldron HB, Turner CW. Evidence-based psychosocial treatments for adolescent substance abuse. Journal of Clinical Child and Adolescent Psychology. 2008; 37 (1):238–261. [ PubMed ] [ Google Scholar ]
• Washio Y, Fairfax-Columbo J, Ball E, Cassey H, Arria AM, Bresani E, Curtis BL, Kirby KC. A review of guidelines on home drug testing web sites for parents. Journal of Addiction Medicine. 2014; 8 (4):258–263. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Weiland BJ, Korycinski ST, Soules M, Zubieta JK, Zucker RA, Heitzeg MM. Substance abuse risk in emerging adults associated with smaller frontal gray matter volumes and higher externalizing behaviors. Drug and Alcohol Dependence. 2014; 137 :68–75. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wetherill RR, Castro N, Squeglia LM, Tapert SF. Atypical neural activity during inhibitory processing in substance-naïve youth who later experience alcohol-induced blackouts. Drug and Alcohol Dependence. 2013; 128 :243–249. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wetherill RR, Squeglia LM, Yang TT, Tapert SF. A longitudinal examination of adolescent response inhibition: neural differences before and after the initiation of heavy drinking. Psychopharmacology (Berl) 2013; 230 (4):663–671. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Whelan R, Watts R, Orr CA, Althoff RR, Artiges E, Banaschewski T, Barker GJ, Bokde AL, Büchel C, Carvalho FM, Conrod PJ, Flor H, Fauth-Bühler M, Frouin V, Gallinat J, Gan G, Gowland P, Heinz A, Ittermann B, Lawrence C, Mann K, Martinot JL, Nees F, Ortiz N, Paillère-Martinot ML, Paus T, Pausova Z, Rietschel M, Robbins TW, Smolka MN, Ströhle A, Schumann G, Garavan H IMAGEN Consortium. Neuropsychosocial profiles of current and future adolescent alcohol misusers. Nature. 2014; 512 :185–189. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Whitesell M, Bachand A, Brown M. Familial, social, and individual factors contributing to risk for adolescent substance use. Journal of Addiction. 2013; 2013 :579310. doi: 10.1155/2013/579310. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Woody GE, Poole SA, Subramaniam G, Duosh K, Bogenschu M, Abbott P, Patkar A, Publicker M, McCain K, Potter JS, Forman R, Vetter V, McNicholas L, Blaine J, Lynch KG, Fudala P. Extended versus short-term buprenorphine-naloxone for treatment of opioid-addicted youth. Journal of the American Medical Association. 2008; 300 (17):2003–2011. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wu P, Hoven CW, Okezie N, Fuller CJ, Cohen P. Alcohol abuse and depression in children and adolescents. Journal of Child and Adolescent Substance Abuse. 2008; 17 (2):51–69. [ Google Scholar ]
• Young MM, Stevens A, Galipeau J, Pirie T, Garritty C, Singh K, Yazdi F, Golfam M, Pratt M, Turner L, Porath-Waller A, Arratoon C, Haley N, Leslie K, Reardon R, Sproule B, Grimshaw J, Moher D. Effectiveness of brief interventions as part of the Screening, Brief Intervention and Referral to Treatment (SBIRT) model for reducing the nonmedical use of psychoactive substances: A systematic Review. Systematic Reviews. 2014; 3 :50. [ PMC free article ] [ PubMed ] [ Google Scholar ]

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Accelerating scientific and drug discovery in an AI-powered lab

In Gaurav Chopra’s lab, discovery starts with a conversation with an artificial intelligence (AI) agent manager that helps to plan, execute and analyze experiments. Researchers chat in natural language and make a query, perhaps asking to design a drug for a particular target or synthesize a specific molecule. The tool — an AI agent manager — identifies all the resources to fulfill the task and communicates with lower-level agents that represent an instrument in the lab; or domain- or task-specific knowledge; or analysis AI and constructs a workflow to address the query given the resources available in the lab.

The AI agent manager plans the workflow to execute on instruments and identifies the procedures that will be part of the experiment. At the individual agent level, the workflow includes scheduling the instrument with appropriate settings and commands needed for execution and even running specific computer code for operating the instrument.   

And then the work begins.

“The agent manager is like ChatGPT for the lab, and it works with the individual agents for each instrument or for domain-specific knowledge,” said Chopra, a Purdue associate professor of chemistry and (by courtesy) of computer science. “It’s a generalized, modular AI infrastructure that can do any task based on your objective. A lot of people are developing AI agents for one specific task. Our approach is task agnostic — I can swap out lab instruments or datasets and, if I do, I don’t have to change out the entire software infrastructure.”

Chopra is also a steering committee member for the Institute for Physical AI (IPAI) and core member of Regenstrief Center for Healthcare Engineering, and Purdue Institutes for Drug Discovery, Cancer Research and Integrative Neuroscience.

With the goal of accelerating scientific discovery, his lab has been developing the artificial intelligence/machine learning (AI/ML) infrastructure with the support of the National Institutes of Health National Center for Advancing Translational Sciences (NCATS). In 2022, Chopra and a team used the AI/ML infrastructure as part of a project that won the grand prize in the NCATS A Specialized Platform for Innovative Research Exploration (ASPIRE) competition. More recently, the NIH awarded a grant to Chopra’s lab to develop a blockchain-based, open science AI framework . The researchers will use blockchain-distributed ledger technology from AI technology developer Onai Inc. to protect IP-sensitive information to promote greater collaboration and reproducibility among different organizations and laboratories.

In a tongue-in-cheek reference to fictional AI developer Skynet, Chopra’s team calls the AI agent’s infrastructure SCINET (Scientific Communication Interaction NETwork). It runs on an “operating system” dubbed LINQX (Ledger for INteractive Query eXecution) that can be expanded or adapted to AI agent-based applications for any instrument or scientific discipline.

To incorporate a new instrument, for example, the team creates a new agent, which is a “living digital twin” of the instrument, with access to the instrument’s command libraries and the ability to learn from usage. The agent can physically control some instruments in the lab, but if the instrument commands are not integrated, the instrument can be manually operated with the AI agent offering instructions from an adjacent laptop. Chopra recently published a new automation workflow for lipidomics on arXiv with the support of instrument manufacturer Agilent Technologies Inc.

As it formulates its workflow, the AI agent manager presents its reasoning for the actions it proposes in a series of “thought, action, observation” steps generated based on the question and the resources available.

“The AI isn’t a black box, it shows you what it is thinking based on your question and what’s available to it,” Chopra said.

And Chopra said the developers in his lab — including graduate students Matthew Muhoberac, Connor Beveridge and Sanjay Iyer — want the AI to augment human effort.

“A lot of the efforts out there are trying to replace humans. We’re not trying to replace the human, we’re trying to augment their work. The whole system helps and works with the user, and plans things from a user perspective,” Chopra said. The human sets the path and the system accelerates workflows with datasets, computational models, accelerates analysis, accelerates experiments to be done based on the plan.”

At its current level, Chopra said SCINET also softens the learning curve for new students who may not know how to code, don’t know protocols for specific tasks, or have no experience in how to use or troubleshoot a particular instrument. Unlike other AI agents, the Chopra team has implemented a memory feature in which the system learns with each query and could eventually become a true research partner.

“The agents start off as technicians, but over time I think they will become scientists to help plan and execute the best way of doing these experiments on these instruments and develop new workflows to accelerate scientific and drug discovery with humans,” Chopra said.

Writer: Mary Martialay, [email protected] Source: Gaurav Chopra, [email protected]

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Oncologists' meetings with drug reps don't help cancer patients live longer

Sydney Lupkin

Drug companies often do one-on-one outreach to doctors. A new study finds these meetings with drug reps lead to more prescriptions for cancer patients, but not longer survival. Chris Hondros/Getty Images hide caption

Drug companies often do one-on-one outreach to doctors. A new study finds these meetings with drug reps lead to more prescriptions for cancer patients, but not longer survival.

Pharmaceutical company reps have been visiting doctors for decades to tell them about the latest drugs. But how does the practice affect patients? A group of economists tried to answer that question.

When drug company reps visit doctors, it usually includes lunch or dinner and a conversation about a new drug. These direct-to-physician marketing interactions are tracked as payments in a public database, and a new study shows the meetings work. That is, doctors prescribe about five percent more oncology drugs following a visit from a pharmaceutical representative, according to the new study published by the National Bureau of Economic Research this month.

But the researchers also found that the practice doesn't make cancer patients live longer.

"It does not seem that this payment induces physicians to switch to drugs with a mortality benefit relative to the drug the patient would have gotten otherwise," says study author Colleen Carey , an assistant professor of economics and public policy at Cornell University.

For their research, she and her colleagues used Medicare claims data and the Open Payments database , which tracks drug company payments to doctors.

While the patients being prescribed these new cancer drugs didn't live longer, Carey also points out that they didn't live shorter lives either. It was about equal.

The pharmaceutical industry trade group, which is known as PhRMA, has a code of conduct for how sales reps should interact with doctors. The code was most recently updated in 2022, says Jocelyn Ulrich, the group's vice president of policy and research .

"We're ensuring that there is a constant attention from the industry and ensuring that these are very meaningful and important interactions and that they're compliant," she explains.

The code says that if drug reps are buying doctors a meal, it must be modest and can't be part of an entertainment or recreational event. The goal should be education.

Ulrich also points out that cancer deaths in the U.S. have declined by 33 percent since the 1990s , and new medicines are a part of that.

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Cost of developing new drugs may be far lower than industry claims, trial reveals

Exclusive: MSF calls for transparency after its bill for a trial of TB treatment came to a fraction of the billions claimed by pharmaceutical companies

Doctors have for the first time released details of their spending on a major clinical trial, demonstrating that the true cost of developing a medicine may be far less than the billions of dollars claimed by the pharmaceutical industry.

Médecins Sans Frontières (MSF) is challenging drug companies to be transparent about the cost of trials, which has always been shrouded in secrecy. Its own bill for landmark trials of a four-drug combination treatment for drug-resistant tuberculosis came to €34m (£29m).

Current estimates for research and development of new medicines range from €40m to €3.9bn. The extortionate cost of trials is used to justify high prices of new medicines, but companies do not publish either the topline or a breakdown of their spending. MSF says this opacity should end. It has produced a toolkit for drug trialists, which categorises each item of expenditure and allows the costs to be collated throughout the process, which can last for years.

MSF’s trial, called TB Practecal, has transformed prospects for people with drug-resistant forms of TB, which have high mortality rates and in some countries have been untreatable because of the high price of the few drugs that still work.

Dr Bern-Thomas Nyang’wa, MSF’s medical director and the chief investigator of the trial, said: “We hope that our disclosure of clinical trial costs for identifying an improved regimen for drug-resistant tuberculosis will serve as a clarion call for other public and nonprofit actors to join us and publicly share their clinical trial costs to ensure broader transparency in medical R&D costs.”

He added: “We encourage clinical trial sponsors and implementors to try our Transparency Core toolkit, and to build on it as a guide to facilitate the publication of cost data. While transparency in R&D expenditure remains largely elusive, transparency in clinical trial costs is a transformative step towards exposing what medical innovation actually costs and building a future where access to medicines and medical tools is not hindered by high prices.”

The two antimicrobial drugs that have been the staple treatment for TB for decades, isoniazid and rifampicin, no longer work as well as they did. The outlook for patients with drug-resistant TB has been bleak in middle and low-income countries. Even if alternative drugs were available, they had to be taken regularly for an entire year.

Bedaquiline, a new drug with a different mechanism against drug-resistant TB, was developed by Johnson & Johnson and, in 2012, became the first TB drug to be approved by the Food and Drug Administration in the US in 40 years. But the cost was prohibitive for many of the worst-affected countries . It took a long battle by campaigners to get the price reduced . The cost of R&D was a key factor. Eventually, it was revealed by academics that the drug was developed thanks to public funding, which was five times more than private investment.

MSF trialled the use of a combination of four oral drugs, including bedaquiline, against drug-resistant TB. Its success led to the World Health Organization (WHO) recommending six months’ treatment with the combination for rifampicin-resistant TB. It is now in use in 40 countries.

Roz Scourse, a policy adviser with MSF’s Access Campaign, said: “The global movement that pushed for a significant price reduction of the lifesaving TB drug bedaquiline demonstrated that transparency of R&D costs can lead to increased access to medical tools and help save more lives.

“The unsubstantiated yet dominant narrative that high prices are needed to recoup high R&D costs can no longer remain an evidence-free zone – this information is a critical piece of the policy puzzle that can inform the price of medical products, and who gets access.”

MSF’s paper, presented Thursday at a WHO conference on medicines pricing, showed it was possible to collect good data on spending in trials, Scourse said. She urged public disclosure, so that governments and communities can have the evidence they need to discuss pricing and work towards access for all those who need the medicines.

Although MSF’s trials took place in middle-income countries, the costs were not low, said Scourse, because they had to invest substantial sums to upgrade infrastructure – such as TB clinics – to be able to conduct high-quality research.

The pharmaceutical industry trade body, the International Federation of Pharmaceutical Manufacturers and Traders (IFPMA), said most estimates for the cost of an approved drug ranged from $2.2bn-$3.2bn (£1.7bn-£2.5bn), and pointed to a Deloitte analysis from 2022 which put the average at $2.3bn .

“The pharmaceutical industry invests around $200bn every year on research and development,” said James Anderson, IFPMA’s executive director of global health. “Over the last 10 years alone, companies have developed over 470 medicines to treat diseases such as cancer, cardiovascular diseases and diabetes, as well as vaccines to protect against significant infections from malaria, RSV and Covid-19, among others.

“Medicines should be affordable to healthcare systems, available to patients everywhere, and prices must reflect the value that a medicine delivers to societies in different countries. This can only be achieved by recognising the value of medicines, while engaging in dialogue on how to make innovations more affordable and accessible to all.”

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• Pharmaceuticals industry
• Tuberculosis

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What Are Americans’ Top Foreign Policy Priorities?

Protecting the u.s. from terrorism and reducing the flow of illegal drugs are top issues overall, but democrats and republicans have very different priorities, table of contents.

• Differences by partisanship
• Differences by age
• Acknowledgments
• The American Trends Panel survey methodology

Pew Research Center conducted this analysis to better understand Americans’ long-range foreign policy priorities. For this analysis, we surveyed 3,600 U.S. adults from April 1 to April 7, 2024. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this analysis, along with responses, and its methodology .

Americans have a lot on their plates in 2024, including an important election to determine who will remain or become again president. But the world does not stop for a U.S. election, and multiple conflicts around the world as well as other issues of global prominence continue to concern Americans.

When asked to prioritize the long-range foreign policy goals of the United States, the majority of Americans say preventing terrorist attacks (73%), keeping illegal drugs out of the country (64%) and preventing the spread of weapons of mass destruction (63%) are top priorities. Over half of Americans also see maintaining the U.S. military advantage over other countries (53%) and preventing the spread of infectious diseases (52%) as primary foreign policy responsibilities.

About half of Americans say limiting the power and influence of Russia and China are top priorities. A recent annual threat assessment from the U.S. intelligence community focused heavily on those countries’ strengthening military relationship and their ability to shape the global narrative against U.S. interests.

Fewer than half of Americans say dealing with global climate change (44%) and getting other countries to assume more of the costs of maintaining world order (42%) are top priorities. The partisan gaps on these two issues are quite large:

• 70% of Democrats and Democratic-leaning independents say climate change should be a top priority, while 15% of Republicans and Republican leaners say this.
• 54% of Republicans say getting other countries to assume more of the costs of maintaining world order should be a top priority, compared with 33% of Democrats.

About four-in-ten Americans see limiting the power and influence of North Korea and Iran as top priorities. (The survey was conducted before Iran’s large-scale missile attack on Israel on April 13.) And about a third say the same about the U.S. being a leader in artificial intelligence, a technology that governments around the world are increasingly concerned about .

When it comes to goals that focus on international engagement, like strengthening the United Nations and NATO or finding a solution to the Israeli-Palestinian conflict, fewer than a third of Americans mark these as top foreign policy priorities.

Related: Fewer Americans view the United Nations favorably than in 2023

Only about a quarter of Americans prioritize promoting human rights in other countries, leading other countries in space exploration and reducing military commitments overseas. And similar shares say supporting Ukraine (23%) and Israel (22%) are top issues.

At the bottom of this list of foreign policy priorities are promoting global democracy ( a major policy push from the Biden administration ) and aiding refugees fleeing violence around the world – about two-in-ten Americans describe these as top concerns. These assessments come amid a recent global surge in asylum claims . Still, in Center surveys, democracy promotion has typically been at the bottom of Americans’ list of foreign policy priorities, even dating back to George W. Bush’s and Barack Obama’s administrations .

Overall, a majority of Americans say that all 22 long-range foreign policy goals we asked about should be given at least some priority. Still, about three-in-ten Americans say supporting Israel (31%), promoting democracy (28%) and supporting Ukraine (27%) should be given no priority.

The long-range foreign policy priority questions were also asked in 2018 and 2021, and since then there have been some significant shifts in responses:

• Since 2018, the public has become significantly more likely to say limiting the power and influence of China (+17 percentage points) and finding a solution to the Israeli-Palestinian conflict (+11) are top foreign policy priorities.
• Americans have also increased the emphasis they place on limiting the power and influence of Russia, particularly in the wake of the Russian invasion of Ukraine (+8 points since 2021).
• On the decline since 2018 are strengthening the UN and aiding refugees (-8 points each), reducing foreign military commitments (-6), and promoting and defending human rights in other countries (-5).
• Preventing the spread of infectious diseases is down 19 percentage points since 2021 – during the height of the COVID-19 pandemic – and about back to where it was in 2018.

These are among the findings from a Pew Research Center survey conducted April 1-7, 2024.

The survey of 3,600 U.S. adults shows that foreign policy remains a partisan issue. Republicans prioritize the prevention of terrorism, reducing the flow of illegal drugs into the country, and maintaining a military advantage over other nations. Meanwhile, Democrats prioritize dealing with climate change and preventing the spread of weapons of mass destruction (WMDs), but also preventing terrorist attacks.

There are also stark age differences on many of the policy goals mentioned, but for the most part, young adults are less likely than older Americans to say the issues we asked about are top priorities. The exceptions are dealing with climate change, reducing military commitments overseas, and promoting and defending human rights abroad – on these issues, 18- to 29-year-olds are significantly more likely than older Americans to assign top priority.

Even with these priorities, foreign policy generally takes the backset to domestic policy for most Americans: 83% say it is more important for President Joe Biden to focus on domestic policy, compared with 14% who say he should focus on foreign policy.

Americans are even less likely to prioritize international affairs than they were in 2019, when 74% wanted then-President Donald Trump to focus on domestic policy and 23% said he should focus on foreign policy.

Americans’ foreign policy priorities differ greatly by party. The largest divide, by a significant margin, is the 55 percentage point gap between Democrats and Republicans on dealing with global climate change (70% vs. 15%, respectively, see it as a top priority).

Supporting Ukraine, aiding refugees, reducing the spread of diseases, protecting human rights, and strengthening the UN are also issues on which Democrats are at least 20 points more likely than Republicans to prioritize. For example, 63% of Democrats say reducing the spread of infectious diseases is a top priority, compared with 41% of Republicans.

Republicans prioritize supporting Israel, reducing the flow of illegal drugs and maintaining a military advantage over other countries – among other security and hard power issues – significantly more than Democrats do. For example, more than half of Republicans (54%) say getting other countries to assume more of the costs of maintaining world order should be a top focus in foreign policy. Only a third of Democrats say the same.

The priority assigned to several issues is divided even further by ideology within parties. Take support for Israel and Ukraine as examples. Supporting Israel is generally a higher priority for Republicans than Democrats, but within the Republican Party, 48% of conservatives say it’s a top concern, while 18% of moderates and liberals agree. Previous Center research shows that conservative Republicans are especially likely to favor military aid to Israel .

Supporting Ukraine, something Democrats emphasize more than Republicans, is a top priority particularly for liberal Democrats (47%), while about three-in-ten moderate and conservative Democrats agree (29%). Democrats have also shown more willingness than Republicans to provide aid to Ukraine in its conflict with Russia.

Generally, the partisan differences on the importance of several foreign policy issues have gotten smaller since 2021 , when most of these questions were last fielded. This is especially true for items related to the relative power of major countries, like the U.S. maintaining a military advantage and limiting the power and influence of both Russia and China.

However, finding a solution to the conflict between Israelis and Palestinians – a priority that saw no partisan difference at all when it was last asked about in 2018 – has an emerging partisan gap today. The share of Democrats who call this a top priority has more than doubled, while the share of Republicans has changed little.

Age differences persist on foreign policy issues. Older Americans prioritize most of the issues we asked about at higher rates than those ages 18 t0 29.

On four issues, there is at least a 40 percentage point gap between Americans ages 65 and older and young adults ages 18 to 29. The oldest Americans are more likely to prioritize reducing the flow of illegal drugs, limiting the power and influence of China and Iran, and maintaining a U.S. military advantage.

Those in the oldest age group are also more concerned than their younger counterparts on an additional 11 issues, ranging from support for Israel to U.S. leadership in space exploration.

For their part, young adults are more likely to say dealing with global climate change, reducing U.S. military commitments overseas, and promoting and defending human rights in other countries should be top foreign policy priorities.

Even starker patterns appear when looking at partisanship within two age groups – adults ages 18 to 49 and those 50 and older.

Among Democrats, older adults place particularly high priority on supporting Ukraine, strengthening NATO, and limiting the power and influence of Russia amid its war with Ukraine. Older Democrats are also more likely than younger ones to prioritize preventing the development of WMDs, curbing the spread of diseases, strengthening the UN and promoting democracy around the world, among other issues.

Among Republicans, those ages 50 and older are more likely than those ages 18 to 49 to prioritize supporting Israel, limiting the power and influence of Iran and China, getting other countries to assume more foreign policy costs, reducing the amount of illegal drugs entering the U.S., preventing terrorism, and maintaining a military advantage.

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Drugs, Brains, and Behavior: The Science of Addiction Drug Misuse and Addiction

What is drug addiction.

Addiction is defined as a chronic, relapsing disorder characterized by compulsive drug seeking and use despite adverse consequences. † It is considered a brain disorder, because it involves functional changes to brain circuits involved in reward, stress, and self-control. Those changes may last a long time after a person has stopped taking drugs. 11

Addiction is a lot like other diseases, such as heart disease. Both disrupt the normal, healthy functioning of an organ in the body, both have serious harmful effects, and both are, in many cases, preventable and treatable. If left untreated, they can last a lifetime and may lead to death.

Why do people take drugs?

In general, people take drugs for a few reasons:

• To feel good. Drugs can produce intense feelings of pleasure. This initial euphoria is followed by other effects, which differ with the type of drug used. For example, with stimulants such as cocaine, the high is followed by feelings of power, self-confidence, and increased energy. In contrast, the euphoria caused by opioids such as heroin is followed by feelings of relaxation and satisfaction.
• To feel better. Some people who suffer from social anxiety, stress, and depression start using drugs to try to feel less anxious. Stress can play a major role in starting and continuing drug use as well as relapse (return to drug use) in patients recovering from addiction.
• To do better. Some people feel pressure to improve their focus in school or at work or their abilities in sports. This can play a role in trying or continuing to use drugs, such as prescription stimulants or cocaine.
• Curiosity and social pressure. In this respect, teens are particularly at risk because peer pressure can be very strong. Adolescence is a developmental period during which the presence of risk factors, such as peers who use drugs, may lead to substance use.

If taking drugs makes people feel good or better, what's the problem?

When they first use a drug, people may perceive what seem to be positive effects. They also may believe they can control their use. But drugs can quickly take over a person's life. Over time, if drug use continues, other pleasurable activities become less pleasurable, and the person has to take the drug just to feel “normal.” They have a hard time controlling their need to take drugs even though it causes many problems for themselves and their loved ones. Some people may start to feel the need to take more of a drug or take it more often, even in the early stages of their drug use. These are the signs of an addiction.

Even relatively moderate drug use poses dangers. Consider how a social drinker can become intoxicated, get behind the wheel of a car, and quickly turn a pleasurable activity into a tragedy that affects many lives. Occasional drug use, such as misusing an opioid to get high, can have similarly disastrous effects, including impaired driving and overdose.

Do people choose to keep using drugs?

The initial decision to take drugs is typically voluntary. But with continued use, a person's ability to exert self-control can become seriously impaired. This impairment in self-control is the hallmark of addiction.

Brain imaging studies of people with addiction show physical changes in areas of the brain that are critical to judgment, decision-making, learning and memory, and behavior control. 12 These changes help explain the compulsive nature of addiction.

Why do some people become addicted to drugs, while others do not?

As with other diseases and disorders, the likelihood of developing an addiction differs from person to person, and no single factor determines whether a person will become addicted to drugs. In general, the more risk factors a person has, the greater the chance that taking drugs will lead to drug use and addiction. Protective factors, on the other hand, reduce a person's risk. Risk and protective factors may be either environmental or biological.

What biological factors increase risk of addiction?

Biological factors that can affect a person's risk of addiction include their genes, stage of development, and even gender or ethnicity. Scientists estimate that genes, including the effects environmental factors have on a person's gene expression, called epigenetics, account for between 40 and 60 percent of a person's risk of addiction. 27 Also, teens and people with mental disorders are at greater risk of drug use and addiction than others. 28

What environmental factors increase the risk of addiction?

Environmental factors are those related to the family, school, and neighborhood. Factors that can increase a person's risk include the following:

• Home and Family. The home environment, especially during childhood, is a very important factor. Parents or older family members who use drugs or misuse alcohol, or who break the law, can increase children's risk of future drug problems. 29
• Peer and School. Friends and other peers can have an increasingly strong influence during the teen years. Teens who use drugs can sway even those without risk factors to try drugs for the first time. Struggling in school or having poor social skills can put a child at further risk for using or becoming addicted to drugs. 30

What other factors increase the risk of addiction?

• Early use.  Although taking drugs at any age can lead to addiction, research shows that the earlier people begin to use drugs, the more likely they are to develop serious problems. 31  This may be due to the harmful effect that drugs can have on the developing brain. 32  It also may result from a mix of early social and biological risk factors, including lack of a stable home or family, exposure to physical or sexual abuse, genes, or mental illness. Still, the fact remains that early use is a strong indicator of problems ahead, including addiction.
• How the drug is taken.  Smoking a drug or injecting it into a vein increases its addictive potential. 33,34  Both smoked and injected drugs enter the brain within seconds, producing a powerful rush of pleasure. However, this intense high can fade within a few minutes. Scientists believe this powerful contrast drives some people to repeatedly use drugs to recapture the fleeting pleasurable state.

Images of Brain Development in Healthy Children and Teens (Ages 5-20)

The brain continues to develop into adulthood and undergoes dramatic changes during adolescence.

One of the brain areas still maturing during adolescence is the prefrontal cortex—the part of the brain that allows people to assess situations, make sound decisions, and keep emotions and desires under control. The fact that this critical part of a teen’s brain is still a work in progress puts them at increased risk for trying drugs or continuing to take them. Introducing drugs during this period of development may cause brain changes that have profound and long-lasting consequences.

† The term addiction as used in this booklet is equivalent to a severe substance use disorder as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5, 2013).