Importance: Illicit drug use is among the most common causes of preventable morbidity and mortality in the US.

Objective: To systematically review the literature on screening and interventions for drug use to inform the US Preventive Services Task Force.

Data Sources: MEDLINE, PubMed, PsycINFO, Embase, and Cochrane Central Register of Controlled Trials through September 18, 2018; literature surveillance through September 21, 2019.

Study Selection: Test accuracy studies to detect drug misuse and randomized clinical trials of screening and interventions to reduce drug use.

Data Extraction and Synthesis: Critical appraisal and data abstraction by 2 reviewers and random-effects meta-analyses.

Main Outcomes and Measures: Sensitivity, specificity, drug use and other health, social, and legal outcomes.

Results: Ninety-nine studies (N = 84,206) were included. Twenty-eight studies (n = 65,720) addressed drug screening accuracy. Among adults, sensitivity and specificity of screening tools for detecting unhealthy drug use ranged from 0.71 to 0.94 and 0.87 to 0.97, respectively. Interventions to reduce drug use were evaluated in 52 trials (n = 15,659) of psychosocial interventions, 7 trials (n = 1109) of opioid agonist therapy, and 13 trials (n = 1718) of naltrexone. Psychosocial interventions were associated with increased likelihood of drug use abstinence (15 trials, n = 3636; relative risk [RR], 1.60 [95% CI, 1.24 to 2.13]; absolute risk difference [ARD], 9% [95% CI, 5% to 15%]) and reduced number of drug use days (19 trials, n = 5085; mean difference, –0.49 day in the last 7 days [95% CI, –0.85 to –0.13]) vs no psychosocial intervention at 3- to 4-month follow-up. In treatment-seeking populations, opioid agonist therapy and naltrexone were associated with decreased risk of drug use relapse (4 trials, n = 567; RR, 0.75 [95% CI, 0.59 to 0.82]; ARD, –35% [95% CI, –67% to –3%] and 12 trials, n = 1599; RR, 0.73 [95% CI, 0.62 to 0.85]; ARD, –18% [95% CI, –26% to –10%], respectively) vs placebo or no medication. While evidence on harms was limited, it indicated no increased risk of serious adverse events.

Conclusions and Relevance: Several screening instruments with acceptable sensitivity and specificity are available to screen for drug use, although there is no direct evidence on the benefits or harms of screening. Pharmacotherapy and psychosocial interventions are effective at improving drug use outcomes, but evidence of effectiveness remains primarily derived from trials conducted in treatment-seeking populations.

Illicit drug use is among the most common causes of preventable morbidity and mortality in the US and a leading cause of years lived in disability.^1,2 In 2018, an estimated 11.7% of US residents 12 years or older were current illicit drug users (hereafter “drug use” and generally defined as use of illegal drugs and the nonmedical use of prescription medications).³ This estimate largely represented use of marijuana (10.1%; estimated 27.7 million current users) and nonmedical prescription psychotherapeutic drugs (2.0%; estimated 5.4 million current users), particularly pain relievers (1.0%; estimated 2.9 million current users).³ It was estimated that nearly 84% of those who needed treatment for a drug use disorder did not receive specialty treatment during the past year.³ As such, screening for drug use is important, as it may allow clinicians to counsel patients and, when indicated, refer them to treatment.

In 2008, the US Preventive Services Task Force (USPSTF) concluded that there was insufficient evidence to recommend for or against screening adolescents and adults, including pregnant women, for illicit drug use (I statement).⁴ The objective of this review was to inform an updated recommendation by the USPSTF.

Scope of Review

This is an update of a systematic review⁵ and supplemental report⁶ that served as the basis for the 2008 recommendation. An analytic framework was developed with 7 key questions (KQs) (Figure 1) on the benefits (KQ1) and harms (KQ3) of screening for drug use screening test accuracy (KQ2), benefits (KQ4) and harms (KQ5) of interventions to reduce drug use, and the benefits (KQ6) and harms (KQ7) of preemptively prescribed naloxone in persons with opioid use disorder or misuse. This article summarizes data from 2 reports: one focused on screening for drug use and interventions in screen-detected populations⁷ and the other addressing interventions among patients with known drug use or seeking treatment (“treatment-seeking”).⁸ Both full reports are available at https://uspreventiveservicestaskforce.org/uspstf/recommendation/drug-use-illicit-screening. All results presented in the full reports are also presented in this article; more detailed methods and all forest plots are included in the full reports.

Data Sources and Searches

MEDLINE, PubMed, PsycINFO, the Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Database of Systematic Reviews, and EMBASE were searched for relevant English-language literature. Searches encompassed literature published between January 1, 1998, and June 7, 2018, for KQs 1-3 and from database inception to September 18, 2018, for KQs 4-7. The reference lists of relevant studies and expert suggestions supplemented the electronic searches. ClinicalTrials.gov (https://ClinicalTrials.gov/) and the WHO International Clinical Trials Registry Platform (https://www.who.int/ ictrp) were searched for ongoing trials. Active surveillance was conducted through September 21, 2019, through article alerts, targeted journal searches, and public comment to identify major studies that might affect the conclusions or understanding of the evidence. Four new test accuracy studies were identified to detect drug use disorder among adults and drug use among pregnant women.^9-12 Additionally, 1 new trial¹³ of a psychosocial intervention among adolescents identified through screening was identified. These studies would not substantively change the findings or conclusions of this review and are not included in the results of this study.

Study Selection

At least 2 reviewers independently reviewed all identified titles and abstracts and relevant full-text articles to ensure consistency with predetermined inclusion and exclusion criteria. For all KQs, studies among adolescents (defined as persons aged 12 to 17 years) and adults were included, including pregnant adolescents and adults. Studies screening for any illicit psychoactive or nonmedical pharmaceutical drug use were included, as were interventions targeting use of opioids, stimulants (eg, cocaine, methamphetamines), cannabis, or mixed drug use. For KQ1 and KQ3, randomized clinical trials or nonrandomized controlled intervention studies that compared individuals who received screening with those who received no screening or usual care were included. For KQ2, studies reporting sensitivity and specificity (or data to calculate) of a screening instrument to detect unhealthy drug use (including any drug use and drug use disorders) compared with a structured or semistructured clinical interview or biological samples were included.

Case-control studies were excluded. Eligible screening instruments included brief standardized instruments or a set of questions that screened directly for drug use or drug use risk or those that indirectly screened for drug use with questions regarding alcohol use or other risky behaviors. Studies evaluating the accuracy of biological drug screening tests (eg, urine samples) were not included. Given the variability in target conditions presented across the studies, conditions were collapsed into 3 groups: any use, unhealthy use (variably defined in the studies), or use disorder (Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) [DSM-IV] abuse or dependence, Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) [DSM-5] use disorder). The target condition of “unhealthy use” included conditions such as the full spectrum of unhealthy use (eg, problem use or a use disorder), meeting any DSM criterion for a use disorder, heavy use (eg, using a substance twice or more per day) or negative consequences or problems related to drug use.

For evaluation of drug use interventions (KQs 4-7), eligible trials could enroll screen-detected patients or those seeking substance use treatment or with signs and symptoms of drug use, regardless of drug use severity. Eligible psychosocial interventions used 1 or more of the following techniques: cognitive behavioral therapy (CBT), motivational interventions, contingency management, 12-step facilitation therapy, family interventions, and adaptations of these methods.¹⁴ Interventions could be delivered in-person or using other modalities (eg, telephone, internet, or computer) and were categorized as brief (1 or 2 sessions, each less than 1 hour in duration) or intensive (not brief). Comparators included no intervention, usual care, or a brief intervention.

For pharmacotherapy, inclusion was restricted to US Food and Drug Administration (FDA)–approved medications for drug use disorders. As of September 2018, this included medications for treatment of opioid use disorder: buprenorphine (sublingual, buccal, or extended-release injection or implant), buprenorphine/naloxone (sublingual or buccal),methadone, and naltrexone (oral or extended release injection). While implantable naltrexone is not FDA-approved, it was also included because evidence on injectable naltrexone was limited. Comparators included no intervention, usual care, or placebo. Trials of methadone or buprenorphine detoxification (withdrawal management) were excluded. For KQ6 and KQ7, studies of preemptive naloxone prescribed in clinical settings as a rescue medication for acute overdose events were included.

Outcomes were drug use (ie, abstinence, frequency and/or quantity of drug use, severity of drug use disorder), clinical outcomes (ie, all-cause mortality, drug-related mortality and morbidity, obstetrical/perinatal/neonatal outcomes, quality of life), other drug-related consequences (ie, legal problems, social and family relations, employment, school/educational outcomes), and harms, including serious adverse events such as death and adverse events resulting in hospitalizations or study withdrawal reported at least 3 months after baseline measurement. Retention in substance use treatment was also an outcome for pharmacological therapy.

Data Extraction and Quality Assessment

Two reviewers independently assessed the methodological quality of eligible studies. Disagreements were resolved by consensus and, if needed, consultation with a third reviewer. Each study was assigned a quality rating of “good,” “fair,” or “poor” according to the USPSTF study design–specific criteria.¹⁵ In accordance with the USPSTF Procedure Manual, studies rated as poor quality because of serious methodological shortcomings were excluded.¹⁵ One reviewer abstracted descriptive and outcome data from fair- and good-quality studies into standardized evidence tables and a second checked for accuracy and completeness.

Data Synthesis and Analysis

Summary tables of study, population, screening, and intervention characteristics, as well as outcomes for each KQ, were created according to the type of screening instrument or intervention. The data for screening accuracy did not allow for quantitative pooling given the heterogeneity in instruments, reference conditions, and cutoffs included, so synthesis was qualitative. Screening instruments were categorized as (1) frequency-based (addressing any use, frequency of use, or both), (2) risk assessment (addressing the consequences of drug use, typically indicators of a use disorder and often with drug use frequency), or (3) indirect (did not screen for drug use directly but assessed correlates of drug use, such as alcohol or tobacco use, partner substance use, and other social factors).

For intervention effectiveness, data were analyzed separately for psychosocial interventions, opioid agonists (methadone and buprenorphine), and naltrexone. Meta-analyses were conducted using a random-effects profile likelihood model on abstinence (or relapse), drug use days, retention in treatment, drug use severity, and harms. Results were analyzed separately for outcomes assessed at 3 or 4 months and at 6 to 12 months. Drug use days were standardized to the number of days of drug use during the past 7 days. Drug use severity was analyzed as a standardized mean difference, given heterogeneity in measurement scales. Stratified analyses were conducted according to whether the population was screen-detected or treatment-seeking, the main type of drug measured (cannabis, stimulant, opioid, or mixed drugs), age group (adolescent [12-17 years], young adult [18-25 years], or adult [>25 years]), study quality, and pregnancy or postpartum status. For pharmacotherapies, stratified analyses were also conducted by route of administration, naltrexone dose, timing of outcome assessment, and intensity of the interventions. For psychosocial interventions, analyses were also conducted according to intervention intensity (brief vs intensive) and mode of delivery (face-to-face or other).

Heterogeneity between studies was evaluated by the χ2 test and I² statistics. Analyses were conducted using Stata version 13.1 (StataCorp). All significance testing was 2-sided, and P ≤ 0.05 was considered statistically significant.

The aggregate strength of evidence was assessed for each KQ using the approach described in the Agency for Healthcare Research and Quality methods guidance, based on the number, quality, and size of studies and the consistency and precision of results between studies.¹⁶

A total of 28,012 titles and abstracts and 1398 articles were reviewed for eligibility; of these, 99 studies (N = 84,206) reported in 124 publications were included (Figure 2). Twenty-eight studies (n = 65,720) addressed the accuracy of drug use screening instruments, and 71 trials evaluated psychosocial interventions (52 trials, n = 15,659), opioid agonist therapy (7 trials, n = 1109), or naltrexone (13 trials, n = 1718) to reduce drug use.

Benefits of Screening

Key Question 1. Does primary care screening for drug use in adolescents and adults, including pregnant women, reduce drug use or improve other risky behaviors? Does primary care screening for drug use in adolescents and adults, including pregnant women, reduce morbidity or mortality or improve other health, social, or legal outcomes?

No eligible studies were identified.

Screening Accuracy

Key Question 2. What is the accuracy of drug use screening instruments?

Twenty-eight studies^17-44 (reported in 37 publications^17-52) with 65,720 participants addressed the accuracy of drug use screening instruments. Considerable heterogeneity among studies was present in the populations, screening instruments, substances addressed, reference standards, and target conditions. Specific screening instruments were generally not examined in more than 1 or 2 studies. Eleven studies recruited adolescents, 12 studies recruited adults, and 5 studies recruited pregnant or postpartum people. Twenty-one of 28 studies were conducted in the US, and 17 of 28 recruited patients from primary care. The number screened ranged from 100 to 42,923, with the majority (20/28 studies) screening fewer than 1000 participants.

Most studies used a structured diagnostic interview as the substance use reference standard, sometimes in combination with other screening instruments (eg, ASSIST [Alcohol, Smoking and Substance Involvement Screening Test]), a timeline follow-back method,⁵³ or biologic confirmation. Seventeen of 28 studies were fair quality, with methodological shortcomings including not reporting enough information regarding the order and timing of the reference standard and screening instrument; not clearly reporting whether the researchers had knowledge of the screening instrument results during the administration and interpretation of the reference standard; not presenting a range of screening instrument cutoff values and selecting only the optimal cutoff; and unclear reporting of whether participant recruitment was random or consecutive.

Thirty screening instruments were evaluated. The screening instruments varied in the number of questions (range, 1-31), administration time, administration method (eg, in-person, telephone, electronic), and the substances addressed. Most of the screening instruments addressed the use of any drug (with or without addressing alcohol and tobacco use). Among these, the majority included an assessment of nonmedical use of prescription drugs, either through a specific question or by including it in the definition of drug use in the prescreening instructions.

Among adults, frequency- and risk-based screening tools showed sensitivity for detecting unhealthy use of any drug ranging from 0.71 to 0.94 (95% CI range, 0.62 to 0.97) and specificity ranging from 0.87 to 0.97 (95% CI range, 0.83 to 0.98) (3 studies, n = 1512) (Table 1). For identifying drug use disorders among adults, sensitivity for frequency-based and risk assessment tools ranged from 0.85 to 1.00 (95% CI range, 0.67 to 1.00) and specificity ranged from 0.67 to 0.93 (95% CI, 0.58 to 0.95) (4 studies, n = 1651). In studies that examined unhealthy use of specific drugs, the ranges of sensitivity were lower and less precise for detecting unhealthy use or use disorders for prescription opioids and prescription sedatives (sensitivity ranged from 0.38 to 0.89 [95% CI range, 0.29 to 0.94]), compared with other classes of drugs. Confidence intervals, however, generally overlapped. Specificity for detecting unhealthy use or use disorders due to prescription misuse was comparable and ranged from 0.79 to 0.99 [95% CI range, 0.71 to 0.99]).

Sensitivity and specificity for detecting any prenatal drug use reported by pregnant or postpartum persons were generally lower than the estimates for nonpregnant persons and ranged from 0.37 to 0.76 (95% CI range, 0.24 to 0.86) and 0.68 to 0.83 (95% CI range, 0.55 to 0.91), respectively (3 studies, n = 1456). All studies used hair and urine analyses to validate drug use (Table 1). The 4P’s Plus, an indirect screening instrument, had a sensitivity of 0.87 (95% CI, 0.71 to 0.95) and specificity of 0.76 (95% CI, 0.70 to 0.82) for detecting any prenatal alcohol or drug use when compared with a diagnostic interview (n = 228).

For adolescents, most studies focused on cannabis use. Sensitivity of frequency- and risk-based instruments for any cannabis use or unhealthy cannabis use ranged from 0.68 to 0.98 (95% CI range, 0.64 to 0.99) and specificity ranged from 0.82 to 1.00 (95% CI range, 0.80 to 1.00) (Table 1) (3 studies, n = 2228). Sensitivity and specificity for identifying a cannabis use disorder for frequency-and risk-based instruments ranged from 0.71 to 0.98 (95% CI range, 0.41 to 0.99) and 0.79 to 0.95 (95% CI range, 0.77 to 0.98), respectively (6 studies, n = 5735).

Harms of Screening

Key Question 3. What are the harms of primary care screening for drug use in adolescents and adults, including pregnant women?

No eligible studies were identified.

Benefits of Interventions

Key Question 4. Do interventions to reduce drug use reduce drug use or improve other risky behaviors? Do interventions to reduce drug use reduce morbidity or mortality or improve other health, social, or legal outcomes?

Psychosocial Interventions

Fifty-two trials (reported in 65 publications) evaluated a psychosocial intervention for unhealthy drug use or drug use disorders (n = 15,659).^54-118 Twenty-seven trials enrolled patients identified through screening and 25 trials enrolled patients seeking substance use treatment or with known substance use (“treatment-seeking”). The severity of baseline substance use varied considerably, with only 5 trials (all among treatment-seeking persons)^55,69-72 requiring patients to meet DSM criteria for drug use disorder.

The primary substance used was cannabis in 29 trials, stimulants in 6 trials, opioids in 2 trials, and mixed or multiple drugs in 15 trials. Among the trials reporting mixed or multiple drug use, the proportion of patients reporting opioid use ranged from 5% to 26%. Five trials evaluated interventions in adolescents, 8 in young adults (18-25 years), and 7 trials in mixed populations of adolescents or young adults. Thirty-two trials evaluated adults or mixed populations of adults and adolescents, including 3 trials of postpartum adults and 2 trials of pregnant adults.

Thirty-seven trials evaluated a brief psychosocial intervention and 19 trials evaluated more intensive interventions (number of sessions ranged from 2 to 14, except 1 trial with 57 sessions); some of these trials were multigroup. The most commonly used techniques in the psychosocial intervention trials were motivational interventions and CBT. The mode of delivery was in-person in 37 trials; by computer, internet, or telephone in 12 trials; and by multiple modes of delivery in 3 trials. The control intervention consisted of a minimal intervention in 30 trials, waitlist in 11 trials, and usual care in 11 trials. Minimal intervention controls typically consisted of brief education.

Eight trials were rated good quality and the remainder were rated fair quality. Methodological limitations in the fair-quality trials included high attrition, failure to blind or unclear blinding of outcome assessors, and unclear randomization methods. In these trials, blinding of patients and clinicians was not feasible, given the nature of the interventions. Attrition at 3 to 4 months ranged from 2% to 67% and at 6 to 12 months from 2% to 46%.

Results of the psychosocial trials are presented in Table 2. Psychosocial interventions were associated with increased likelihood of abstinence from drug use vs control conditions at 3 to 4 months (15 trials, n = 3636; risk ratio [RR], 1.60 [95% CI, 1.24 to 2.13]; I² = 61%; absolute risk difference [ARD], 9% [95% CI, 5% to 15%]) and at 6 to 12 months (14 trials, n = 4031; RR, 1.25 [95% CI, 1.11 to 1.52]; I² = 38%; ARD, 6% [95% CI, 2% to 10%]) (Table 2). At 3 to 4 months, psychosocial interventions were also associated with decreased number of days of drug use during the last 7 days vs controls (19 trials, n = 5085; mean difference [MD], –0.49 day [95% CI, –0.85 to –0.13]; I² = 89%) and drug use severity (17 trials, n = 4437; standardized MD, –0.18 [95% CI –0.32 to –0.05]; I² = 73%), but these associations were smaller and not statistically significant at 6 to 12 months for drug use days (15 trials, n = 5095; MD, –0.08 [95% CI, –0.30 to 0.11]; I² = 45%) or severity (13 trials, n = 3798; standardized MD, –0.10 [95% CI, –0.24 to 0.02]; I² = 65%).

At 3 to 4 months, the associations with drug use days were statistically significantly greater among trials of treatment-seeking vs screen-detected populations (10 trials, n = 1664; MD, –0.91 [95% CI, –1.52 to –0.31] vs 9 trials, n = 3421; MD, –0.10 [95% CI, –0.31 to 0.12]; P = 0.02) and for intensive vs brief interventions (10 trials, n = 2364; MD, –0.88 [95% CI, –1.50 to –0.28] vs 9 trials, n = 2721; MD, –0.13 [95% CI, –0.36 to 0.12]; P = 0.03) (Table 2). Otherwise, statistically significant differences were not present in stratified analyses, although effects were generally stronger across outcomes in trials of treatment-seeking vs screen-detected populations, cannabis use vs other types of drug use, intensive vs brief interventions, and (for abstinence) in-person vs other modes of delivery.

Data on effects of psychosocial interventions on other health, social, and legal outcomes were limited. These data, however, generally showed no differences between psychosocial interventions vs control conditions in the likelihood of injection drug use or sexual risk behaviors;^{56-59,98,102,105,119} the risk of emergency department visits or hospital admissions;^107,119 measures related to mental health, quality of life, or function;^{55,56,58,80,81,84,89,107,119} the likelihood of driving after cannabis use;^66,67,85 and risk of incarceration or involvement in criminal activity.^56-58,88,102

Pharmacological Therapies

Opioid Agonist Therapy (Methadone and Buprenorphine). Seven trials (reported in 9 publications) (n = 1109) reported effects of opioid agonist therapy (buprenorphine or methadone) vs placebo or no medication (waitlist or usual care) for opioid use disorder.^120-128 Two trials evaluated oral methadone, with dosing of up to 90mg/d in one trial and averaging 78mg/d in the other trial. The other 5 trials evaluated buprenorphine: sublingual administration in 3 trials (dose, 8-24 mg/d), implant in 1 trial (4 implants, with a total dose of 320 mg), and both sublingual and implant in 2 separate groups in the remaining trial.¹²⁴ The duration of treatment ranged from 3 to 12 months (6 months in 4 trials and 3, 4, or 12 months in 1 trial each). Oral methadone and sublingual buprenorphine were administered daily under direct observation, although some trials allowed take-home doses for weekends and holidays. In 5 of the 7 trials, all patients received some drug use counseling (individual, group, or both). The intensity of counseling ranged from “minimal” (not described) to “standard” counseling for 45 to 60 minutes on a weekly or twice-weekly basis. Two trials of bridging therapy with methadone or buprenorphine did not include a counseling intervention.

In all 7 trials of opioid agonist therapy, the main type of opioid used was heroin; 2 trials reported prescription opioids as the main opioid used by about one-third of patients. Four trials were conducted in the US, 2 trials in Europe, and 1 trial in Malaysia. In all trials, patients were treatment-seeking. Patients were enrolled from inpatient settings in 1 trial, from the community in 1 trial, and from outpatient addiction treatment settings in 5 trials. In all but 1 trial, treatment was administered in outpatient addiction treatment settings.

Study participants were predominantly men (proportion of women ranged from 25%-43%), and mean age ranged from 29 to 43 years. No study was conducted in adolescents, and no trial stratified outcomes by patient sex. In studies that reported the duration of drug use, the mean ranged from 5 to 20 years. Three studies reported the mean number of days of heroin use during the last 30 days, ranging from 19 to 30 days.

Two studies were rated good quality and the remainder were rated fair quality. Methodological shortcomings in the fair-quality trials included unclear randomization or allocation concealment methods and unclear or high attrition. Both methadone trials used an unblinded design—one trial compared methadone vs usual care and the other trial compared methadone vs wait-list control.

Results of trials of methadone and buprenorphine are summarized in Table 3. After 4 to 12 months of treatment, opioid agonist therapy was associated with decreased risk of relapse vs controls (4 trials, n = 567; RR, 0.75 [95% CI, 0.59 to 0.82]; I² = 75%; ARD, –35% [95% CI, –67% to –13%]) and an increased likelihood of treatment retention (7 trials, n = 1099; RR, 2.58 [95% CI, 1.78 to 4.59]; I² = 71%; ARD, 39% [95% CI, 23% to 54%]). There was no significant difference between type of drug (methadone or buprenorphine), buprenorphine administration method (sublingual or by implant), counseling intensity, or trial quality and effects on relapse or retention.

Evidence on health outcomes associated with opioid agonist therapy vs placebo or no opioid agonist was very limited. Only 3 trials reported on a measure of global function or well-being with no clear effect. Mortality was reported in 2 trials of buprenorphine with a total of 4 deaths, all in patients randomized to placebo. No trial reported on the social or legal outcomes of opioid agonist therapy.

Naltrexone. Thirteen trials (in 14 publications) (n = 1718) evaluated naltrexone vs placebo or no naltrexone for opioid use disorder (generally based on meeting DSM-II-R, DSM-III, or DSM-IV criteria).^125,129-141 All patients in the trials received drug use counseling, usually described as individual or group counseling ranging from 3 times per week to biweekly. Details on counseling methods, however, were limited. Eleven trials assessed oral naltrexone, 1 trial injectable naltrexone (300 mg every 4 weeks), and 1 trial had 2 active groups of a naltrexone implant (1000 mg twice a month) and oral naltrexone. The oral naltrexone dose was 50 mg daily in 7 trials, up to 150 mg daily in 2 trials, and 100 or 150 mg 2 or 3 times weekly in 3 trials. Treatment duration was 6 months in 10 trials and 2, 3, or 9 months in the other 3 trials. Outcomes were assessed at the end of treatment in all trials except for 2 trials that evaluated outcomes 6 or 10 months after treatment completion. Five trials were conducted in Russia, 2 in Israel, 2 in the US, 2 in Europe, 1 in Malaysia, and 1 in China. Patients were recruited from inpatient settings, drug treatment settings, or from the criminal justice system (eg, parolees). No study recruited patients from primary care settings. In all cases, naltrexone treatment was administered in outpatient settings.

Where reported, heroin was the primary opioid of use in all or most patients in naltrexone treatment trials. Studies enrolled predominantly men (proportion of women ranged from 0% to 31%), and no trial reported outcomes stratified by patient sex. The mean age ranged from 21 to 29 years, with no trials of adolescents. All trials required patients to be withdrawn from opioids prior to initiation of naltrexone. Four trials described inpatient or residential withdrawal from opioids; details were otherwise not well reported.

Three studies were rated good quality and the remainder were rated fair quality. Methodological shortcomings in the fair-quality trials included unclear randomization or allocation concealment methods and unclear or high attrition. All trials were blinded.

Results of the naltrexone trials are presented in Table 3. In pooled analyses, naltrexone was associated with decreased risk of relapse vs placebo or no naltrexone (12 trials, n = 1599; RR, 0.73 [95% CI, 0.62 to 0.85]; ARD, –18% [95% CI, –26% to –10%]), as well as an increased likelihood of treatment retention (9 trials, n = 1404; RR, 1.71 [95% CI, 1.13 to 2.49]; I² = 67%; ARD, 15% [95% CI, 5% to 22%]). There was no significant difference in the likelihood of relapse or treatment retention based on route of naloxone administration. Results were similar when analyses were restricted to trials of oral naltrexone at a dose of 50 mg/d and to good-quality trials.

Evidence on the effects of naltrexone vs placebo or no naltrexone on health outcomes (eg, global function, quality of life, depression, and anxiety) was limited, with no consistent evidence of a benefit of naltrexone compared with placebo or no naltrexone. Mortality was rare, with a total of 3 deaths (2 in naltrexone groups and 1 in placebo groups) in 5 trials.

Harms of Interventions

Key Question 5. What are the harms of interventions to reduce drug use (including illicit drug use and nonmedical pharmaceutical drug use)?

Psychosocial Interventions

Four trials of psychosocial interventions (n = 1196) reported no adverse events in either intervention or control groups.^94,98,99,142 Harms were otherwise not reported, with no serious adverse events noted.

Pharmacological Therapies

Opioid Agonist Therapy (Buprenorphine or Methadone). Four trials of buprenorphine vs placebo reported harms;^122-125 no trials of methadone reported harms (eTable 13 in the Supplement). There was no significant difference between buprenorphine vs placebo in risk of serious adverse events, which were uncommon (2 trials, n = 450; RR, 0.32 [95% CI, 0.09 to 1.12]; I² = 0%);^123,124 1 trial reported no hospitalizations due to serious medication-related adverse events.¹²⁵ One trial (n = 83) found no significant difference between buprenorphine vs placebo in risk of withdrawal due to adverse events (RR, 0.89 [95% CI, 0.06 to 13.7]),¹²⁵ and 1 trial (n = 287) found no difference in risk of any adverse event (RR, 1.14 [95% CI, 0.90 to 1.43]).¹²⁴ Buprenorphine was also not associated with increased risk of diaphoresis (3 trials, n = 476; RR, 1.15 [95% CI, 0.55 to 2.73]; I² = 44%)^122,124,125 or nausea (3 trials, n = 393; RR, 1.13 [95% CI, 0.41 to 6.07]; I² = 30%).^122,124 Buprenorphine was associated with increased risk of constipation vs placebo, based on 2 trials (n = 246; RR, 2.36 [95% CI, 1.16 to 4.92]; I² = 0%; ARD, 12% [95% CI, –5% to 41%]).^123,125

Naltrexone. Eleven trials of naltrexone vs placebo or no medication reported harms (n = 1645) (eTable 16 in the Supplement).^{125,129-136,139,140} For withdrawal from study due to adverse events, 3 trials found no difference between naltrexone vs placebo or no medication, but the estimate was imprecise (n = 836; RR, 1.54 [95% CI, 0.35 to 8.31]; I² = 0%).^133-135 Three other trials (n = 181) reported no study withdrawals due to adverse events.^125,130,139 Three studies (n = 638) found no differences in serious adverse events, but the estimate was imprecise (RR, 1.24 [95% CI, 0.11 to 10.21]; I² = 59%).^125,134,135 Three trials (n = 163) found no differences between naltrexone and control groups in risk of gastrointestinal adverse events (constipation, diarrhea, and nausea or vomiting).^125,130,140

Benefits of Naloxone Preemptive Prescribing

Key Question 6. Does naloxone reduce morbidity or mortality, or improve other health outcomes, in persons with opioid use disorder or misuse?

No eligible studies were identified.

Harms of Naloxone Preemptive Prescribing

Key Question 7. What are the harms of naloxone in persons with opioid use disorder or misuse?

No eligible studies were identified.

This review updates the 2008 USPSTF review on screening for drug use in adolescents and adults.⁵ A summary of findings, including an assessment of the strength of evidence for each KQ, is presented in Table 4. Consistent with the 2008 review, no studies were identified on the benefits and harms of screening (vs no screening) for drug use in primary care. However, evidence indicates that several screening instruments, including single-item drug frequency questions;^18,20,45,48 the Substance Use Brief Screen;¹⁸ the Tobacco, Alcohol, Prescription Medication,and Other Substance Use tool;^25,49 and the Drug Abuse Screening Test (10 items),²⁰ can detect unhealthy drug use with reasonable accuracy. Both frequency-based and risk assessment screening instruments generally have sensitivity greater than or equal to 0.80 and specificity greater than or equal to 0.85 for identifying unhealthy drug use and drug use disorders among adults when validated against a structured diagnostic interview. Based on the range in test accuracy estimates and a prevalence of drug use among adults of 11%,³ the positive predictive value of screening instruments is approximately 40%. In patients who screen positive, further assessment to define patients’ risk level may help determine the appropriateness for treatment, such as the procedure recommended by the National Institute on Drug Abuse.¹⁴³

Compared with the 2008 review, substantially more evidence is available to support the effectiveness of psychosocial interventions and FDA-approved medications to improve drug use outcomes among persons with unhealthy drug use or a diagnosed drug use disorder. When trials in screen-detected and treatment seeking populations were combined in the meta-analyses, psychosocial interventions were associated with an increased likelihood of drug use abstinence, decreased number of drug use days, and decreased drug use severity at 3 to 4 months. Beneficial effects at 6 to 12 months were only observed for drug use abstinence. Most trials of psychosocial interventions recruited patients with cannabis use or mixed drug use and used CBT or motivational interventions ranging in intensity from 1or 2 sessions to ongoing treatment for months. Based on overall pooled estimates, psychosocial interventions were associated with a number needed to treat of 17 for 1 additional case of drug use abstinence at 6 to 12 months. Effects were generally greater in treatment-seeking populations than in screen-detected populations, stronger for cannabis use than other drug use outcomes, stronger for shorter-term (3- to 4-month) than longer-term (6- to 12-month) outcomes, and stronger for more intensive interventions vs brief interventions. Few trials evaluated psychosocial interventions among adolescents or pregnant persons.

Both opioid agonist therapy (methadone and buprenorphine) and naltrexone were associated with a decreased risk of relapse and increased likelihood of treatment retention among individuals with an opioid use disorder after 4 to 12 months of treatment, compared with no treatment. Trials of pharmacologic treatment were primarily conducted in persons using heroin, and medications were typically administered in conjunction with drug use counseling, in accordance with recommended practice.^14,144 Based on pooled estimates, the number needed to treat to avoid 1 additional case of relapse was 3 for opioid agonists and 6 for naltrexone. There was no evidence that the effectiveness of pharmacologic treatment varied according to type of medication, administration method, intensity of co-occurring counseling, or trial quality.

Evidence on the effects of psychosocial and medications for opioid use disorder on health outcomes (eg, such as global function, quality of life, depression, and anxiety) was very limited and showed no consistent evidence of a benefit of treatment compared with no treatment. While assessment and reporting of harms in trials of pharmacotherapies was suboptimal, it indicated no increase in risk of serious adverse events or study withdrawal due to adverse events vs placebo or pharmacotherapy. Trials of psychosocial interventions generally did not report harms, although serious harms are not anticipated with this type of intervention.

As described in the full report,⁸ evidence on the benefits and harms of preemptive prescribing of naloxone in primary care settings for reducing overdose risk in persons with opioid use disorder or misuse is not available. To date, the effectiveness of naloxone has mainly been demonstrated in the context of evaluations of community opioid overdose prevention and naloxone distribution programs.^145,146

Limitations

This study had several limitations. First, for screening accuracy, despite inclusion criteria designed to result in the selection of studies highly applicable to US primary care, many screening studies were conducted in populations with high prevalence of drug use or high numbers of known drug users, and some of the larger studies were conducted among non–clinic-based samples. As such, the instrument accuracy reported in the included studies may not reflect the accuracy for all US primary care settings.

Second, trials of psychosocial interventions were characterized by marked variability in patient populations, interventions, outcomes, recruitment and treatment settings, and other factors, likely contributing to the substantial statistical heterogeneity observed in pooled analyses. Furthermore, evidence was lacking on the effectiveness of psychosocial treatments among adolescents and pregnant people as well as for treatment of stimulant use. Most trials of medication therapy were among adults with opioid use disorder due to heroin use and not prescription opioid misuse.

Third, trials primarily focused on intermediate outcomes, such as drug use or retention in treatment, and there was little direct evidence on the effects of interventions on mortality or other clinical, social, and legal outcomes.

Several screening instruments with acceptable sensitivity and specificity are available to screen for drug use, although there is no evidence on the benefits or harms of screening. Pharmacotherapy and psychosocial interventions are effective at improving drug use outcomes, but evidence of effectiveness remains primarily derived from trials conducted in treatment-seeking populations.

Source: This article was published online in JAMA on June 9, 2020 (JAMA. 2020;323(22):2310-2328. doi:10.1001/jama.2019.21381).

Conflict of Interest Disclosures: Dr Fu reported receiving grants from Oregon Health & Science University. Dr Chou reported receiving consulting fees from the American Academy of Addiction Psychiatry. No other disclosures were reported.

Funding/Support: This research was funded under contract HHSA-290-2015-00007-I-EPC5, Task Order 2, from the Agency for Healthcare Research and Quality (AHRQ), US Department of Health and Human Services, under a contract to support the US Preventive Services Task Force (USPSTF).

Role of the Funder/Sponsor: Investigators worked with USPSTF members and AHRQ staff to develop the scope, analytic framework, and key questions for this review. AHRQ had no role in study selection, quality assessment, or synthesis. AHRQ staff provided project oversight, reviewed the report to ensure that the analysis met methodological standards, and distributed the draft for peer review. Otherwise, AHRQ had no role in the conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript findings.

Additional Information: A draft version of the full evidence reports underwent external peer review from 11 content experts (Cheryl Arratoon, MSc, Canadian Centre on Substance Abuse; Joan Fleishman, PsyD, Oregon Health & Sciences University; Sharon Levy, MD, MPH, Harvard University; Jennifer McNeely, MD, MS, New York University; Natalie Mercer, PhD, Canadian Centre on Substance Abuse; Yngvild Olsen, MD, MPH, Institutes for Behavior Resources Inc; Steven Ondersma, PhD, MA,Wayne State University; Kevin Sevarion, MP, PhD, Yale University and the University of Connecticut; Brad Stein, MD, PhD, RAND Corporation; Adrienne Stevens, PhD, Ottawa Hospital Research Institute; Matthew Young, PhD, Canadian Centre on Substance Abuse) and 5 federal partners from the Centers for Disease Control and Prevention and National Institutes of Health. Comments were presented to the USPSTF during its deliberation of the evidence and were considered in preparing the final evidence review.

1. Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual causes of death in the United States, 2000. JAMA. 2004;291(10):1238-1245. doi:10.1001/jama.291.10.1238
2. Murray CJ, Lopez AD. Measuring the global burden of disease. N Engl J Med. 2013;369(5):448-457. doi:10.1056/NEJMra1201534
3. Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. Results from the 2018 National Survey on Drug Use and Health: detailed tables. Published August 2019. Accessed May 7, 2020. https://www.samhsa.gov/data/report/2018-nsduh-detailed-tables
4. US Preventive Services Task Force. Final recommendation statement: drug use, illicit: screening. Published 2008. Accessed September 11, 2018. https://www.uspreventiveservicestaskforce.org/Page/Document/Recommendation-Statement-Final/druguse-illicit-screening
5. Polen MR, Whitlock EP, Wisdom JP, Nygren P, Bougatsos C. Screening in Primary Care Settings for Illicit Drug Use: Staged Systematic Review for the U.S. Preventive Services Task Force: Evidence Synthesis No. 58, Part 1. Agency for Healthcare Research and Quality; January 2008. AHRQ publication 08-05108-EF-s.
6. Lanier D, Ko S. Screening in Primary Care Settings for Illicit Drug Use: Assessment of Screening Instruments: A Supplemental Evidence Update for the U.S. Preventive Services Task Force. Agency for Healthcare Research and Quality; 2008. AHRQ publication 08-05108-EF-2.
7. Patnode CD, Perdue LA, Rushkin M, O’Connor EA. Screening for Drug Use in Primary Care in Adolescents and Adults, Including Pregnant Women: An Updated Systematic Review for the U.S. Preventive Services Task Force: Evidence Synthesis No. 186. Agency for Healthcare Research and Quality; 2020. AHRQ publication 19-05255-EF-1.
8. Chou R, Dana T, Blazina I, Grusing S, Bougatsos C. Interventions for Drug Use—Supplemental Report: A Systematic Review for the U.S. Preventive Services Task Force: Evidence Synthesis No. 187. Agency for Healthcare Research and Quality; 2020.
9. Tiet QQ, Leyva YE, Browne K, Moos RH. Screen of drug use: diagnostic accuracy for cannabis use disorder. Addict Behav. 2019;95:184-188. doi:10.1016/j.addbeh.2019.02.010
10. Tiet QQ, Leyva YE, Moos RH. Screen of drug use: diagnostic accuracy for opioid use disorder. Drug Alcohol Depend. 2019;198:176-179. doi:10.1016/j.drugalcdep.2019.01.044
11. Ondersma SJ, Chang G, Blake-Lamb T, et al. Accuracy of five self-report screening instruments for substance use in pregnancy. Addiction. 2019;114(9):1683-1693. doi:10.1111/add.14651
12. Coleman-Cowger VH, Oga EA, Peters EN, Trocin KE, Koszowski B, Mark K. Accuracy of three screening tools for prenatal substance use. Obstet Gynecol. 2019;133(5):952-961. doi:10.1097/AOG.0000000000003230
13. Knight JR, Sherritt L, Gibson EB, et al. Effect of computer-based substance use screening and behavioral counseling vs. usual care for youths in pediatric primary care: a pilot randomized clinical trial. JAMA Netw Open. 2019;2(6):e196258. doi:10.1001/jamanetworkopen.2019.6258
14. United States Department of Veterans Affairs. VA/DoD Clinical Practice Guideline for the Management of Substance Use Disorders. Published 2015. Accessed April 26, 2019. https://www.healthquality.va.gov/guidelines/MH/sud/VADODSUDCPGRevised22216.pdf
15. US Preventive Services Task Force. U.S. Preventive Services Task Force Procedure Manual. Agency for Healthcare Research and Quality; 2015.
16. Berkman ND, Lohr KN, Ansari M, et al. Grading the strength of a body of evidence when assessing health care interventions for the effective health care program of the Agency for Healthcare Research and Quality: an update. In: Agency for Healthcare Research and Quality, ed. Methods Guide for Effectiveness and Comparative Effectiveness Reviews. Agency for Healthcare Research and Quality; 2014:314-349. AHRQ publication 10(14)-EHC063-EF.
17. 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. doi:10.1542/peds.2013-2346
18. McNeely J, Strauss SM, Saitz R, et al. A brief patient self-administered substance use screening tool for primary care: two-site validation study of the Substance Use Brief Screen (SUBS). Am J Med. 2015;128(7):784.e9-784.e19. doi:10.1016/j.amjmed.2015.02.007
19. Tiet QQ, Leyva YE, Moos RH, Frayne SM, Osterberg L, Smith B. Screen of drug use: diagnostic accuracy of a new brief tool for primary care. JAMA Intern Med. 2015;175(8):1371-1377. doi:10.1001/jamainternmed.2015.2438
20. Smith PC, Schmidt SM, Allensworth-Davies D, Saitz R. A single-question screening test for drug use in primary care. Arch Intern Med. 2010;170(13):1155-1160. doi:10.1001/archinternmed.2010.140
21. Knight JR, Sherritt L, Shrier LA, Harris SK, Chang G. Validity of the CRAFFT substance abuse screening test among adolescent clinic patients. Arch Pediatr Adolesc Med. 2002;156(6):607-614. doi:10.1001/archpedi.156.6.607
22. Chasnoff IJ, Wells AM, McGourty RF, Bailey LK. Validation of the 4P’s Plus screen for substance use in pregnancy validation of the 4P’s Plus. J Perinatol. 2007;27(12):744-748. doi:10.1038/sj.jp.7211823
23. Brown RL, Leonard T, Saunders LA, Papasouliotis O. A two-item conjoint screen for alcohol and other drug problems. J Am Board Fam Pract. 2001;14(2):95-106.
24. McCann BS, Simpson TL, Ries R, Roy-Byrne P. Reliability and validity of screening instruments for drug and alcohol abuse in adults seeking evaluation for attention-deficit/hyperactivity disorder. Am J Addict. 2000;9(1):1-9. doi:10.1080/10550490050172173
25. McNeely J, Wu LT, Subramaniam G, et al. Performance of the Tobacco, Alcohol, Prescription Medication, and Other Substance Use (TAPS) tool for substance use screening in primary care patients. Ann Intern Med. 2016;165(10):690-699. doi:10.7326/M16-0317
26. Kumar PC, Cleland CM, Gourevitch MN, et al. Accuracy of the Audio Computer Assisted Self Interview version of the Alcohol, Smoking and Substance Involvement Screening Test (ACASI ASSIST) for identifying unhealthy substance use and substance use disorders in primary care patients. Drug Alcohol Depend. 2016;165:38-44. doi:10.1016/j.drugalcdep.2016.05.030
27. Harris SK, Knight JR Jr, Van Hook S, et al. Adolescent substance use screening in primary care: validity of computer self-administered versus clinician-administered screening. Subst Abus. 2016;37(1):197-203. doi:10.1080/08897077.2015.1014615
28. Lam LP, Leung WC, Ip P, et al. Validation of the Drug Abuse Screening Test (DAST-10): a study on illicit drug use among Chinese pregnant women. Sci Rep. 2015;5:11420. doi:10.1038/srep11420
29. 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. doi:10.1111/add.12767
30. Legleye S, Guignard R, Richard JB, Ludwig K, Pabst A, Beck F. Properties of the Cannabis Abuse Screening Test (CAST) in the general population. Int J Methods Psychiatr Res. 2015;24(2):170-183. doi:10.1002/mpr.1465
31. Mitchell SG, Kelly SM, Gryczynski J, et al. The CRAFFT cut-points and DSM-5 criteria for alcohol and other drugs: a reevaluation and reexamination. Subst Abus. 2014;35(4):376-380. doi:10.1080/08897077.2014.936992
32. Bastiani L, Siciliano V, Curzio O, et al. Optimal scaling of the CAST and of SDS Scale in a national sample of adolescents. Addict Behav. 2013;38(4):2060-2067. doi:10.1016/j.addbeh.2012.12.016
33. Ondersma SJ, Svikis DS, LeBreton JM, et al. Development and preliminary validation of an indirect screener for drug use in the perinatal period. Addiction. 2012;107(12):2099-2106. doi:10.1111/j.1360-0443.2012.03982.x
34. Fernandez-Artamendi S, Fernández-Hermida JR, Muñiz-Fernández J, Secades-Villa R, García-Fernández G. Screening of cannabis-related problems among youth: the CPQ-A-S and CAST questionnaires. Subst Abuse Treat Prev Policy. 2012;7:13. doi:10.1186/1747-597X-7-13
35. Legleye S, Piontek D, Kraus L. Psychometric properties of the Cannabis Abuse Screening Test (CAST) in a French sample of adolescents. Drug Alcohol Depend. 2011;113(2-3):229-235. doi:10.1016/j.drugalcdep.2010.08.011
36. Grekin ER, Svikis DS, Lam P, et al. Drug use during pregnancy: validating the Drug Abuse Screening Test against physiological measures. Psychol Addict Behav. 2010;24(4):719-723. doi:10.1037/a0021741
37. Dawson DA, Compton WM, Grant BF. Frequency of 5+/4+ drinks as a screener for drug use and drug-use disorders. J Stud Alcohol Drugs. 2010;71(5):751-760. doi:10.15288/jsad.2010.71.751
38. Lane WG, Dubowitz H, Feigelman S, et al. Screening for parental substance abuse in pediatric primary care. Ambul Pediatr. 2007;7(6):458-462. doi:10.1016/j.ambp.2007.07.007
39. Harrison PA, Godecker A, Sidebottom A. Validity of the prenatal risk overview for detecting drug use disorders in pregnancy. Public Health Nurs. 2012;29(6):563-573. doi:10.1111/j.1525-1446.2012.01030.x
40. D’Amico EJ, Parast L, Meredith LS, Ewing BA, Shadel WG, Stein BD. Screening in primary care: what is the best way to identify at-risk youth for substance use? Pediatrics. 2016;138(6):e20161717. doi:10.1542/peds.2016-1717
41. Beaudoin FL, Merchant RC, Clark MA. Prevalence and detection of prescription opioid misuse and prescription opioid use disorder among emergency department patients 50 years of age and older: performance of the Prescription Drug Use Questionnaire, Patient Version. Am J Geriatr Psychiatry. 2016;24(8):627-636. doi:10.1016/j.jagp.2016.03.010
42. Chung T, Colby SM, O’Leary TA, Barnett NP, Monti PM. Screening for cannabis use disorders in an adolescent emergency department sample. Drug Alcohol Depend. 2003;70(2):177-186. doi:10.1016/S0376-8716(02)00346-0
43. Rial A, Kim-Harris S, Knight JR, et al. Empirical validation of the CRAFFT abuse screening test in a Spanish sample. Adicciones. 2019;31(2):160-169. doi:10.20882/adicciones.1105
44. Legleye S. The Cannabis Abuse Screening Test and the DSM-5 in the general population: optimal thresholds and underlying common structure using multiple factor analysis. Int J Methods Psychiatr Res. 2018;27(2):e1597. doi:10.1002/mpr.1597
45. McNeely J, Cleland CM, Strauss SM, Palamar JJ, Rotrosen J, Saitz R. Validation of Self-Administered Single-Item Screening Questions (SISQs) for unhealthy alcohol and drug use in primary care patients. J Gen Intern Med. 2015;30(12):1757-1764. doi:10.1007/s11606-015-3391-6
46. Wu LT, McNeely J, Subramaniam GA, Sharma G, VanVeldhuisen P, Schwartz RP. Design of the NIDA clinical trials network validation study of Tobacco, Alcohol, Prescription Medications, and Substance Use/Misuse (TAPS) tool. Contemp Clin Trials. 2016;50:90-97. doi:10.1016/j.cct.2016.07.013
47. Tiet QQ, Leyva Y, Moos RH, Smith B. Diagnostic accuracy of a two-item screen for drug use developed from the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Drug Alcohol Depend. 2016;164:22-27. doi:10.1016/j.drugalcdep.2016.03.029
48. Smith PC, Cheng DM, Allensworth-Davies D, Winter MR, Saitz R. Use of a single alcohol screening question to identify other drug use. Drug Alcohol Depend. 2014;139:178-180. doi:10.1016/j.drugalcdep.2014.03.027
49. Gryczynski J, McNeely J, Wu LT, et al. Validation of the TAPS-1: a four-item screening tool to identify unhealthy substance use in primary care. J Gen Intern Med. 2017;32(9):990-996. doi:10.1007/s11606-017-4079-x
50. Tiet QQ, Leyva YE, Moos RH, Smith B. Diagnostic accuracy of a two-item Drug Abuse Screening Test (DAST-2). Addict Behav. 2017;74:112-117. doi:10.1016/j.addbeh.2017.06.008
51. Kelly SM, O’Grady KE, Gryczynski J, Mitchell SG, Kirk A, Schwartz RP. The concurrent validity of the Problem Oriented Screening Instrument for Teenagers (POSIT) substance use/abuse subscale in adolescent patients in an urban federally qualified health center. Subst Abus. 2017;38(4):382-388. doi:10.1080/08897077.2017.1351413
52. Araujo M, Golpe S, Braña T, Varela J, Rial A. Psychometric validation of the POSIT for screening alcohol and other drugs risk consumption among adolescents. Adicciones. 2018;30(2):130-139. doi: 10.20882/adicciones.958
53. Sobell LC, Sobell MB. Timeline Followback: A Calendar Method for Assessing Alcohol and Drug Use. Addiction Research Foundation; 1996.
54. D’Amico EJ, Parast L, Shadel WG, Meredith LS, Seelam R, Stein BD. Brief motivational interviewing intervention to reduce alcohol and marijuana use for at-risk adolescents in primary care. J Consult Clin Psychol. 2018;86(9):775-786. doi:10.1037/ccp0000332
55. Babor TF, Christiansen K, Donaldson J, Herrel J, Kadden R; Marijuana Treatment Project Research Group. Brief treatments for cannabis dependence: findings from a randomized multisite trial. J Consult Clin Psychol. 2004;72(3):455-466. doi:10.1037/0022-006X.72.3.455
56. Baker A, Boggs TG, Lewin TJ. Randomized controlled trial of brief cognitive-behavioural interventions among regular users of amphetamine. Addiction. 2001;96(9):1279-1287. doi:10.1046/j.1360-0443.2001.96912797.x
57. Baker A, Boggs TG, Lewin TJ. Characteristics of regular amphetamine users and implications for treatment. Drug Alcohol Rev. 2001;20(1):49-56. doi:10.1080/09595230123756
58. Baker A, Lee NK, Claire M, et al. Brief cognitive behavioural interventions for regular amphetamine users: a step in the right direction. Addiction. 2005;100(3):367-378. doi:10.1111/j.1360-0443.2005.01002.x
59. Bonar EE, Walton MA, Barry KL, et al. Sexual HIV risk behavior outcomes of brief interventions for drug use in an inner-city emergency department: secondary outcomes from a randomized controlled trial. Drug Alcohol Depend. 2018;183:217-224. doi:10.1016/j.drugalcdep.2017.10.036
60. Copeland J, Swift W, Rees V. Clinical profile of participants in a brief intervention program for cannabis use disorder. J Subst Abuse Treat. 2001;20(1):45-52. doi:10.1016/S0740-5472(00)00148-3
61. Copeland J, Swift W, Roffman R, Stephens R. A randomized controlled trial of brief cognitive-behavioral interventions for cannabis use disorder. J Subst Abuse Treat. 2001;21(2):55-64. doi:10.1016/S0740-5472(01)00179-9
62. de Dios MA, Herman DS, Britton WB, Hagerty CE, Anderson BJ, Stein MD. Motivational and mindfulness intervention for young adult female marijuana users. J Subst Abuse Treat. 2012;42(1):56-64. doi:10.1016/j.jsat.2011.08.001
63. de Gee EA, Verdurmen JE, Bransen E, de Jonge JM, Schippers GM. A randomized controlled trial of a brief motivational enhancement for non-treatment-seeking adolescent cannabis users. J Subst Abuse Treat. 2014;47(3):181-188. doi:10.1016/j.jsat.2014.05.001
64. Dembo R, Briones-Robinson R, Schmeidler J, et al. Brief intervention impact on truant youths’ marijuana use: eighteen-month follow-up. J Child Adolesc Subst Abuse. 2016;25(1):18-32. doi:10.1080/1067828X.2013.872068
65. Dupont HB, Candel MJ, Kaplan CD, van de Mheen D, de Vries NK. Assessing the efficacy of MOTI-4 for reducing the use of cannabis among youth in the Netherlands: a randomized controlled trial. J Subst Abuse Treat. 2016;65:6-12. doi:10.1016/j.jsat.2015.11.012
66. Fischer B, Dawe M, McGuire F, et al. Feasibility and impact of brief interventions for frequent cannabis users in Canada. J Subst Abuse Treat. 2013;44(1):132-138. doi:10.1016/j.jsat.2012.03.006
67. Fischer B, Jones W, Shuper P, Rehm J. 12-month follow-up of an exploratory “brief intervention” for high-frequency cannabis users among Canadian university students. Subst Abuse Treat Prev Policy. 2012;7:15. doi:10.1186/1747-597X-7-15
68. Gates PJ, Norberg MM, Copeland J, Digiusto E. Randomized controlled trial of a novel cannabis use intervention delivered by telephone. Addiction. 2012;107(12):2149-2158. doi:10.1111/j.1360-0443.2012.03953.x
69. Jones HE, Wong CJ, Tuten M, Stitzer ML. Reinforcement-based therapy: 12-month evaluation of an outpatient drug-free treatment for heroin abusers. Drug Alcohol Depend. 2005;79(2):119-128. doi:10.1016/j.drugalcdep.2005.01.006
70. LittMD, Kadden RM, Kabela-Cormier E, Petry NM. Coping skills training and contingency management treatments for marijuana dependence: exploring mechanisms of behavior change. Addiction. 2008;103(4):638-648. doi:10.1111/j.1360-0443.2008.02137.x
71. LittMD, Kadden RM, Petry NM. Behavioral treatment for marijuana dependence: randomized trial of contingency management and self-efficacy enhancement. Addict Behav. 2013;38(3):1764-1775. doi:10.1016/j.addbeh.2012.08.011
72. LittMD, Kadden RM, Stephens RS; Marijuana Treatment Project Research Group. Coping and self-efficacy in marijuana treatment: results from the Marijuana Treatment Project. J Consult Clin Psychol. 2005;73(6):1015-1025. doi:10.1037/0022-006X.73.6.1015
73. Lozano BE, Stephens RS, Roffman RA. Abstinence and moderate use goals in the treatment of marijuana dependence. Addiction. 2006;101(11):1589-1597. doi:10.1111/j.1360-0443.2006.01609.x
74. Marsden J, Stillwell G, Barlow H, et al. An evaluation of a brief motivational intervention among young ecstasy and cocaine users: no effect on substance and alcohol use outcomes. Addiction. 2006;101(7):1014-1026. doi:10.1111/j.1360-0443.2006.01290.x
75. Martin G, Copeland J. The adolescent cannabis check-up: randomized trial of a brief intervention for young cannabis users. J Subst Abuse Treat. 2008;34(4):407-414. doi:10.1016/j.jsat.2007.07.004
76. McCambridge J, Slym RL, Strang J. Randomized controlled trial of motivational interviewing compared with drug information and advice for early intervention among young cannabis users. Addiction. 2008;103(11):1809-1818. doi:10.1111/j.1360- 0443.2008.02331.x
77. McCambridge J, Strang J. The efficacy of single-session motivational interviewing in reducing drug consumption and perceptions of drug-related risk and harm among young people: results from a multi-site cluster randomized trial. Addiction. 2004;99(1):39-52. doi:10.1111/j.1360-0443.2004.00564.x
78. McCambridge J, Strang J. Deterioration over time in effect of motivational interviewing in reducing drug consumption and related risk among young people. Addiction. 2005;100(4):470-478. doi:10.1111/j.1360-0443.2005.01013.x
79. Rooke S, Copeland J, Norberg M, Hine D, McCambridge J. Effectiveness of a self-guided web-based cannabis treatment program: randomized controlled trial. J Med Internet Res. 2013;15(2):e26. doi:10.2196/jmir.2256
80. Schaub MP, Wenger A, Berg O, et al. A web-based self-help intervention with and without chat counseling to reduce cannabis use in problematic cannabis users: three-arm randomized controlled trial. J Med Internet Res. 2015;17(10):e232. doi:10.2196/jmir.4860
81. Stein MD, Herman DS, Anderson BJ. A motivational intervention trial to reduce cocaine use. J Subst Abuse Treat. 2009;36(1):118-125. doi:10.1016/j.jsat.2008.05.003
82. Stephens RS, Roffman RA, Curtin L. Comparison of extended versus brief treatments for marijuana use. J Consult Clin Psychol. 2000;68(5):898-908. doi:10.1037/0022-006X.68.5.898
83. Stephens RS, Roffman RA, Fearer SA, Williams C, Burke RS. The Marijuana Check-up: promoting change in ambivalent marijuana users. Addiction. 2007;102(6):947-957. doi:10.1111/j.1360-0443.2007.01821.x
84. Tait RJ, McKetin R, Kay-Lambkin F, et al. Six-month outcomes of a web-based intervention for users of amphetamine-type stimulants: randomized controlled trial. J Med Internet Res. 2015;17(4):e105. doi:10.2196/jmir.3778
85. Bernstein E, Edwards E, Dorfman D, Heeren T, Bliss C, Bernstein J. Screening and brief intervention to reduce marijuana use among youth and young adults in a pediatric emergency department. Acad Emerg Med. 2009;16(11):1174-1185. doi:10.1111/j.1553-2712.2009.00490.x
86. Bernstein J, Bernstein E, Tassiopoulos K, Heeren T, Levenson S, Hingson R. Brief motivational intervention at a clinic visit reduces cocaine and heroin use. Drug Alcohol Depend. 2005;77(1):49-59. doi:10.1016/j.drugalcdep.2004.07.006
87. Blow FC, Walton MA, Bohnert ASB, et al. A randomized controlled trial of brief interventions to reduce drug use among adults in a low-income urban emergency department: the HealthiER You study. Addiction. 2017;112(8):1395-1405. doi:10.1111/ add.13773
88. Bogenschutz MP, Donovan DM, Mandler RN, et al. Brief intervention for patients with problematic drug use presenting in emergency departments: a randomized clinical trial [published correction appears in JAMA Intern Med. 2015;175(3):470]. JAMA Intern Med. 2014;174(11):1736-1745. doi:10.1001/jamainternmed.2014.4052
89. Gelberg L, Andersen RM, Afifi AA, et al. Project QUIT (Quit Using Drugs Intervention Trial): a randomized controlled trial of a primary care-based multi-component brief intervention to reduce risky drug use. Addiction. 2015;110(11):1777-1790. doi:10.1111/add.12993
90. Gelberg L, Andersen RM, Rico MW, et al. A pilot replication of QUIT, a randomized controlled trial of a brief intervention for reducing risky drug use, among Latino primary care patients. Drug Alcohol Depend. 2017;179:433-440. doi:10.1016/j.drugalcdep.2017.04.022
91. Gryczynski J, O’Grady KE, Mitchell SG, Ondersma SJ, Schwartz RP. Immediate versus delayed computerized brief intervention for illicit drug misuse. J Addict Med. 2016;10(5):344-351. doi:10.1097/ADM.0000000000000248
92. Humeniuk R, Ali R, Babor T, et al. A randomized controlled trial of a brief intervention for illicit drugs linked to the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) in clients recruited from primary health-care settings in four countries. Addiction. 2012;107(5):957-966. doi:10.1111/j.1360-0443.2011.03740.x
93. Lee BH, Lim SC, Jeon HJ, et al. Acupuncture suppresses reinstatement of morphine-seeking behavior induced by a complex cue in rats. Neurosci Lett. 2013;548:126-131. doi:10.1016/j.neulet.2013.05.026
94. Lee CM, Neighbors C, Kilmer JR, Larimer ME. A brief, web-based personalized feedback selective intervention for college student marijuana use: a randomized clinical trial. Psychol Addict Behav. 2010;24(2):265-273. doi:10.1037/a0018859
95. Martino S, Ondersma SJ, Forray A, et al. A randomized controlled trial of screening and brief interventions for substance misuse in reproductive health. Am J Obstet Gynecol. 2018;218(3):322.e1-322.e12. doi:10.1016/j.ajog.2017.12.005
96. Mason M, Light J, Campbell L, et al. Peer network counseling with urban adolescents: a randomized controlled trial with moderate substance users. J Subst Abuse Treat. 2015;58:16-24. doi:10.1016/j.jsat.2015.06.013
97. Ondersma SJ, Svikis DS, Schuster CR. Computer-based brief intervention a randomized trial with postpartum women [published correction appears in c. 2007;32(6):549]. Am J Prev Med. 2007;32(3):231-238. doi:10.1016/j.amepre.2006.11.003
98. Ondersma SJ, Svikis DS, Thacker C, et al. Computer-delivered indirect screening and brief intervention for drug use in the perinatal period: a randomized trial. Drug Alcohol Depend. 2018;185:271-277. doi:10.1016/j.drugalcdep.2017.12.022
99. Ondersma SJ, Svikis DS, Thacker LR, Beatty JR, Lockhart N. Computer-delivered screening and brief intervention (e-SBI) for postpartum drug use: a randomized trial. J Subst Abuse Treat. 2014;46(1): 52-59. doi:10.1016/j.jsat.2013.07.013
100. Palfai TP, Saitz R, Winter M, et al.Web-based screening and brief intervention for student marijuana use in a university health center: pilot study to examine the implementation of eCHECKUP TO GO in different contexts. Addict Behav. 2014;39(9):1346-1352. doi:10.1016/j.addbeh.2014.04.025
101. Poblete F, Barticevic NA, Zuzulich MS, et al. A randomized controlled trial of a brief intervention for alcohol and drugs linked to the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) in primary health care in Chile. Addiction. 2017;112(8):1462-1469. doi:10.1111/add.13808
102. Roy-Byrne P, Bumgardner K, Krupski A, et al. Brief intervetion for problem drug use in safety-net primary care settings: a randomized clinical trial. JAMA. 2014;312(5):492-501. doi:10.1001/jama.2014.7860
103. Saitz R, Cheng DM, Allensworth-Davies D, Winter MR, Smith PC. The ability of single screening questions for unhealthy alcohol and other drug use to identify substance dependence in primary care. J Stud Alcohol Drugs. 2014;75(1):153-157. doi:10.15288/jsad.2014.75.153
104. Stein MD, Hagerty CE, Herman DS, Phipps MG, Anderson BJ. A brief marijuana intervention for non-treatment-seeking young adult women. J Subst Abuse Treat. 2011;40(2):189-198. doi:10.1016/j.jsat.2010.11.001
105. TzilosWernette G, Plegue M, Kahler CW, Sen A, Zlotnick C. A pilot randomized controlled trial of a computer-delivered brief intervention for substance use and risky sex during pregnancy. J Womens Health (Larchmt). 2018;27(1):83-92. doi:10.1089/jwh.2017.6408
106. Walton MA, Bohnert K, Resko S, et al. Computer and therapist based brief interventions among cannabis-using adolescents presenting to primary care: one year outcomes. Drug Alcohol Depend. 2013;132(3):646-653. doi:10.1016/j.drugalcdep.2013.04.020
107. Watkins KE, Ober AJ, Lamp K, et al. Collaborative care for opioid and alcohol use disorders in primary care: the SUMMIT randomized clinical trial. JAMA Intern Med. 2017;177(10):1480-1488. doi:10.1001/jamainternmed.2017.3947
108. Woolard R, Baird J, Longabaugh R, et al. Project reduce: reducing alcohol and marijuana misuse: effects of a brief intervention in the emergency department. Addict Behav. 2013;38(3):1732-1739. doi:10.1016/j.addbeh.2012.09.006
109. Yonkers KA, Forray A, Howell HB, et al. Motivational enhancement therapy coupled with cognitive behavioral therapy versus brief advice: a randomized trial for treatment of hazardous substance use in pregnancy and after delivery. Gen Hosp Psychiatry. 2012;34(5):439-449. doi:10.1016/j.genhosppsych.2012.06.002
110. Zahradnik A, Otto C, Crackau B, et al. Randomized controlled trial of a brief intervention for problematic prescription drug use in non-treatment-seeking patients. Addiction. 2009;104(1):109-117. doi:10.1111/j.1360-0443.2008.02421.x
111. Baumeister SE, Gelberg L, Leake BD, Yacenda-Murphy J, Vahidi M, Andersen RM. Effect of a primary care based brief intervention trial among risky drug users on health-related quality of life. Drug Alcohol Depend. 2014;142:254-261. doi:10.1016/j.drugalcdep.2014.06.034
112. Bogenschutz MP, Donovan DM, Adinoff B, et al. Design of NIDA CTN Protocol 0047: screening, motivational assessment, referral, and treatment in emergency departments (SMART-ED). Am J Drug Alcohol Abuse. 2011;37(5):417-425. doi:10.3109/00952990.2011.596971
113. Fuster D, Cheng DM, Wang N, et al. Brief intervention for daily marijuana users identified by screening in primary care: a subgroup analysis of the ASPIRE randomized clinical trial. Subst Abus. 2016;37(2):336-342. doi:10.1080/08897077.2015.1075932
114. Kim TW, Bernstein J, Cheng DM, et al. Receipt of addiction treatment as a consequence of a brief intervention for drug use in primary care: a randomized trial. Addiction. 2017;112(5):818-827. doi:10.1111/add.13701
115. Krupski A, Joesch JM, Dunn C, et al. Testing the effects of brief intervention in primary care for problem drug use in a randomized controlled trial: rationale, design, and methods. Addict Sci Clin Pract. 2012;7:27. doi:10.1186/1940-0640-7-27
116. Mason MJ, Sabo R, Zaharakis NM. Peer network counseling as brief treatment for urban adolescent heavy cannabis users. J Stud Alcohol Drugs. 2017;78(1):152-157. doi:10.15288/jsad.2017.78.152
117. Otto C, Crackau B, Löhrmann I, et al. Brief intervention in general hospital for problematic prescription drug use: 12-month outcome. Drug Alcohol Depend. 2009;105(3):221-226. doi:10.1016/j.drugalcdep.2009.07.010
118. Kadden RM, Litt MD, Kabela-Cormier E, Petry NM. Abstinence rates following behavioral treatments for marijuana dependence. Addict Behav. 2007;32(6):1220-1236. doi:10.1016/j.addbeh.2006.08.009
119. Saitz R, Palfai TP, Cheng DM, et al. Screening and brief intervention for drug use in primary care: the ASPIRE randomized clinical trial. JAMA. 2014; 312(5):502-513. doi:10.1001/jama.2014.7862
120. Gruber VA, Delucchi KL, Kielstein A, Batki SL. A randomized trial of 6-month methadone maintenance with standard or minimal counseling versus 21-daymethadone detoxification. Drug Alcohol Depend. 2008;94(1-3):199-206. doi:10.1016/j.drugalcdep.2007.11.021
121. Kakko J, Svanborg KD, Kreek MJ, Heilig M. 1-year retention and social function after buprenorphine-assisted relapse prevention treatment for heroin dependence in Sweden: a randomised, placebo-controlled trial. Lancet. 2003;361(9358):662-668. doi:10.1016/S0140-6736(03)12600-1
122. Krook AL, Brørs O, Dahlberg J, et al. A placebo-controlled study of high dose buprenorphine in opiate dependents waiting for medication-assisted rehabilitation in Oslo, Norway. Addiction. 2002;97(5):533-542. doi:10.1046/j.1360-0443.2002.00090.x
123. LingW, Casadonte P, Bigelow G, et al. Buprenorphine implants for treatment of opioid dependence: a randomized controlled trial. JAMA. 2010;304(14):1576-1583. doi:10.1001/jama.2010.1427
124. Rosenthal RN, Ling W, Casadonte P, et al. Buprenorphine implants for treatment of opioid dependence: randomized comparison to placebo and sublingual buprenorphine/naloxone. Addiction. 2013;108(12):2141-2149. doi:10.1111/add.12315
125. Schottenfeld RS, Chawarski MC, Mazlan M. Maintenance treatment with buprenorphine and naltrexone for heroin dependence in Malaysia: a randomised, double-blind, placebo-controlled trial. Lancet. 2008;371(9631):2192-2200. doi:10.1016/S0140-6736(08)60954-X
126. Schwartz RP, Highfield DA, Jaffe JH, et al. A randomized controlled trial of interim methadone maintenance. Arch Gen Psychiatry. 2006;63(1):102-109. doi:10.1001/archpsyc.63.1.102
127. Schwartz RP, Jaffe JH, Highfield DA, Callaman JM, O’Grady KE. A randomized controlled trial of interim methadone maintenance: 10-month follow-up. Drug Alcohol Depend. 2007;86(1):30-36. doi:10.1016/j.drugalcdep.2006.04.017
128. Schwartz RP, Jaffe JH, O’Grady KE, et al. Interim methadone treatment: impact on arrests. Drug Alcohol Depend. 2009;103(3):148-154. doi:10.1016/j.drugalcdep.2009.03.007
129. Cornish JW, Metzger D, Woody GE, et al. Naltrexone pharmacotherapy for opioid dependent federal probationers. J Subst Abuse Treat. 1997;14(6):529-534. doi:10.1016/S0740-5472(97)00020-2
130. Guo S, Jiang Z, Wu Y. Efficacy of naltrexone hydrochloride for preventing relapse among opiate-dependent patients after detoxification. Hong Kong J Paediatr. 2001;11(4):2-9.
131. Hollister LE. Clinical evaluation of naltrexone treatment of opiate-dependent individuals: report of the National Research Council Committee on Clinical Evaluation of Narcotic Antagonists. Arch Gen Psychiatry. 1978;35(3):335-340. doi:10.1001/archpsyc.1978.01770270085008
132. Krupitsky EM, Zvartau EE, Masalov DV, et al. Naltrexone for heroin dependence treatment in St. Petersburg, Russia. J Subst Abuse Treat. 2004;26(4):285-294. doi:10.1016/j.jsat.2004.02.002
133. Krupitsky EM, Zvartau EE, Masalov DV, et al. Naltrexone with or without fluoxetine for preventing relapse to heroin addiction in St. Petersburg, Russia. J Subst Abuse Treat. 2006;31(4):319-328. doi:10.1016/j.jsat.2006.05.005
134. Krupitsky E, Nunes EV, Ling W, Illeperuma A, Gastfriend DR, Silverman BL. Injectable extended-release naltrexone for opioid dependence: a double-blind, placebo-controlled, multicentre randomised trial. Lancet. 2011;377(9776):1506-1513. doi:10.1016/S0140-6736(11) 60358-9
135. Krupitsky E, Zvartau E, Blokhina E, et al. Randomized trial of long-acting sustained-release naltrexone implant vs oral naltrexone or placebo for preventing relapse to opioid dependence. Arch Gen Psychiatry. 2012;69(9):973-981. doi:10.1001/archgenpsychiatry.2012.1a
136. Krupitsky E, Zvartau E, Blokhina E, et al. Naltrexone with or without guanfacine for preventing relapse to opiate addiction in St. Petersburg, Russia. Drug Alcohol Depend. 2013;132(3):674-680. doi:10.1016/j.drugalcdep.2013.04.021
137. Krupitsky E, Zvartau E, Blokhina E, et al. Anhedonia, depression, anxiety, and craving in opiate dependent patients stabilized on oral naltrexone or an extended release naltrexone implant. Am J Drug Alcohol Abuse. 2016;42(5):614-620. doi:10.1080/00952990.2016.1197231
138. Lerner A, Sigal M, Bacalu A, Shiff R, Burganski I, Gelkopf M. A naltrexone double blind placebo controlled study in Israel. Isr J Psychiatry Relat Sci. 1992;29(1):36-43.
139. San L, Pomarol G, Peri JM, Olle JM, Cami J. Follow-up after a six-month maintenance period on naltrexone versus placebo in heroin addicts. Br J Addict. 1991;86(8):983-990. doi:10.1111/j.1360-0443.1991.tb01859.x
140. Shufman EN, Porat S, Witztum E, Gandacu D, Bar-Hamburger R, Ginath Y. The efficacy of naltrexone in preventing reabuse of heroin after detoxification. Biol Psychiatry. 1994;35(12):935-945. doi:10.1016/0006-3223(94)91240-8
141. Stella L, D’Ambra C, Mazzeo F, et al. Naltrexone plus benzodiazepine aids abstinence in opioid-dependent patients. Life Sci. 2005;77(21):2717-2722. doi:10.1016/j.lfs.2005.05.036
142. Lee CM, Kilmer JR, Neighbors C, et al. Indicated prevention for college student marijuana use: a randomized controlled trial. J Consult Clin Psychol. 2013;81(4):702-709. doi:10.1037/a0033285
143. National Institute on Drug Abuse, National Institutes of Health, US Department of Health and Human Services. Resource guide: screening for drug use in general medical settings. Accessed September 11, 2017. https://www.drugabuse.gov/sites/default/files/resource_guide.pdf
144. American Society of Addiction Medicine. The national practice guideline for the use of medications in the treatment of addiction involving opioid use. Updated 2015. Accessed April 26, 2019. https://www.asam.org/docs/default-source/practice-support/guidelines-and-consensus-docs/asam-national-practice-guideline-supplement.pdf
145. Clark AK, Wilder CM, Winstanley EL. A systematic review of community opioid overdose prevention and naloxone distribution programs. J Addict Med. 2014;8(3):153-163. doi:10.1097/ADM.0000000000000034
146. Giglio RE, Li G, DiMaggio CJ. Effectiveness of bystander naloxone administration and overdose education programs: a meta-analysis. Inj Epidemiol. 2015;2(1):10. doi:10.1186/s40621-015-0041-8

Evidence reviews for the US Preventive Services Task Force (USPSTF) use an analytic framework to visually display the key questions that the review will address to allow the USPSTF to evaluate the effectiveness and safety of a preventive service. The questions are depicted by linkages that relate interventions and outcomes. A dashed line indicates a health outcome that immediately follows an intermediate outcome.
^a Screening refers to screening methods that pose questions about drug use or drug-related risks, not laboratory testing of biologic samples for the presence of drugs.
^b Includes illicit drug use and nonmedical pharmaceutical drug use.

^a Number of citations screened after duplicates removed also reflects studies reviewed for key questions (KQs) 4 and 5 (efficacy and harms of psychosocial interventions in screen-detected populations) in the Screening for Drug Use Report.
^b Counts of full-text articles reviewed are not mutually exclusive; some articles were reviewed for both reports.
^c Reasons for exclusion: Aim: Not applicable/relevant to key question. Setting: Not conducted in a very high Human Development Index country or screening and/or intervention was not conducted in, recruited from, or feasible for primary care. Screener: Assessment for drug use does not include a brief standardized instrument or set of questions conducted in person or via telephone, mail, or electronically. Study design: Not a randomized clinical trial or case-crossover trial (KQs 1, 3, 4, 5); not a large cohort or case-control study (KQ2). Follow-up <3 mo: Less than 3 months’ follow-up after baseline assessment. Outcomes: No measure of drug use reported (KQs 1, 3, 4, 5); no measure related to sensitivity and specificity reported for screening accuracy (KQ2). Population: Children younger than 12 years or populations otherwise out of scope (eg, psychotic disorder, receiving chronic opioid therapy, court-mandated drug treatment, or incarcerated). Comparator: Not an included comparator (eg, screening results given to control clinicians [KQs 1 and 3], no reference standard [KQ2], active intervention [KQs 4 and 5]).  Publication type: Conference abstract, non–English-language publication, main results published prior to review start date (1992).  Quality: Study was poor quality.

^a A single study could use different methodologies for instrument administration or different screening instruments. Although all variations are captured in the ranges (eg, interviewer vs self-administered), the study is counted only once.
^b Excluding Lane et al³⁸ (sensitivity, 0.29; specificity, 0.95). This study used a different outcome (abuse only), the Parental Screening Questionnaire as a screening tool, and is an outlier from the rest of the group.
^c Includes any prescription drug, prescription opioids, and prescription sedatives.
^d Includes cocaine alone and cocaine combined with methamphetamines.

Abbreviations: MD, mean difference; RR, risk ratio; SMD, standardized mean difference.
^a Test of difference not conducted.
^b Standardized to drug use in the past 7 days.

Abbreviation: RR, risk ratio.

Abbreviations: ARD, absolute risk difference; FDA, US Food and Drug Administration; MD, mean difference; NA, not applicable; RR, risk ratio; SES, socioeconomic status; SMD, standardized mean difference.
^a Comparisons are against placebo or no medication for pharmacological interventions and against waitlist, a minimal intervention, or usual care for psychosocial interventions.
^b N includes 1 US-based community sample (n = 42,923) that only evaluated a single-item alcohol question for predicting problematic drug use. Without this study, total n = 22,797.