To measure the prevalence of positive substance use screen results among adolescent primary care patients and to estimate the prevalence of substance-related problems and disorders.
A network of primary care practices in New England.
A consecutive sample of 12- to 18-year-old patients (N = 2133), with a study participation rate of 92.7%.
The CRAFFT substance abuse screening test (a full description of this screen is given in the “Introduction”).
Frequencies of positive screen results were computed for the entire sample, each practice, visit type (well-child care, sick visit, follow-up, or other), and patient status (new vs established). Generalized estimating equation modeling was used to test for difference in proportions. CRAFFT scores, demographic data, and Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) diagnostic data from a previous study were used to estimate the prevalence of problematic substance use, abuse, and dependence.
Overall, 14.8% of adolescents had positive results on the CRAFFT screen. Prevalence rates differed significantly across practices (P < .001) after adjusting for demographic factors. The highest positive rates on the CRAFFT screen were at school-based health centers (29.5%) and the rural family practice (24.2%), the middle rate was at the adolescent clinic (16.6%), and the lowest rates were at the health maintenance organization (14.1%) and pediatric clinic (8.0%). Sick visits had the highest rate (23.2%). Well-child care visits had a significantly lower rate (11.4%, P < .001). Statistical modeling estimated that 11.3% of all patients had problematic use, 7.1% had abuse, and 3.2% had dependence.
Substance abuse screening should occur whenever the opportunity arises, not at well-child care visits only.
According to the National Institute on Drug Abuse,1 addiction is a chronic disease with genetic, environmental, and behavioral factors contributing to its cause, manifestations, and natural history. Recent evidence indicates that addiction treatment response and relapse rates are similar to those of other chronic diseases, such as type 2 diabetes mellitus, hypertension, and asthma.2 As a chronic disease, addiction typically begins during adolescence and early onset of substance use is highly predictive of an addictive disorder later in life.3-5 Substance use by adolescents is, therefore, among the foremost public health problems in the United States.
By senior year in high school, approximately 80% of adolescents have begun to drink and 50% have used an illicit drug.6 Substance use is associated with the leading causes of death among US teenagers: unintentional injuries, homicides, and suicides.7 Substance use is also associated with a wide variety of serious but nonlethal health problems, including depression, conduct disorder, and unplanned sexual activity,8-10 making health care settings ideal venues for universal screening and early intervention programs.11,12
Recognizing this opportunity, the American Medical Association, the American Academy of Pediatrics, and other national organizations recommend that all adolescent patients receive a screening for use of alcohol and other drugs as part of the annual well-child care visit.11,13,14 A number of structured screening tools are available for this purpose, including the Problem Oriented Screening Instrument for Teenagers,15 the Alcohol Use Disorders Identification Test,16 and the CRAFFT questions.17 CRAFFT is a mnemonic acronym of the first letters of key words in the test's 6 questions: (1) “Have you ever ridden in a CAR driven by someone (including yourself) who was ‘high’ or had been using alcohol or drugs?” (2) “Do you ever use alcohol or drugs to RELAX, feel better about yourself, or fit in?” (3) “Do you ever use alcohol or drugs while you are by yourself, ALONE?” (4) “Do you ever FORGET things you did while using alcohol or drugs?” (5) “Do your family or FRIENDS ever tell you that you should cut down on your drinking or drug use?” (6) “Have you ever gotten into TROUBLE while you were using alcohol or drugs?” Each “yes” answer is scored 1 point, and a CRAFFT total score of 2 or more is highly correlated with having a substance-related diagnosis and the need for substance abuse treatment.18
The CRAFFT screen was specifically created to be developmentally appropriate for adolescents, capable of screening for alcohol and other drug use problems, and practical for use in busy medical outpatient settings. The CRAFFT screen has had high test-retest reliability (intraclass correlation coefficient, 0.93 for lifetime use and 0.91 for past year use) and good criterion validity (sensitivity, 0.76; specificity, 0.94; positive predictive value, 0.93; and negative predictive value, 0.91) for identifying substance-related problems and disorders.18,19
Adherence to recommendations for universal substance abuse screening of adolescents is low.20 Primary care providers cite lack of time and training to deal with positive screen results and lack of available treatment for those who have positive screen results to be significant barriers to universal screening.21 In addition, little is known about the screen-positive rates in adolescent primary care settings, the prevalence of substance-related problems and disorders, and the corresponding need for services. This information is crucial to the development of appropriate screening and intervention programs.
The primary objective of this study was to determine the prevalence of positive CRAFFT screen results among adolescents presenting for routine outpatient medical care in a variety of practice types, and to estimate the prevalence of substance-related problematic use, abuse, and dependence among these youth. A secondary objective was to determine the relative value of screening at well-child care visits vs sick visits and other encounters and for screening new vs established patients. The results of this study will assist health care providers (physicians, nurse practitioners, physician assistants, etc) in estimating the resources that will be required to provide level-appropriate prevention and intervention services to adolescents with early signs of a substance-related disorder.
This was a prospective observational study that consisted primarily of a survey. The study was conducted in a primary care research network that included (1) an urban hospital-based pediatric practice, (2) the pediatric department at a large group-model health maintenance organization, (3) an urban hospital-based adolescent clinic, (4) a rural family medicine practice, and (5) 3 school-based health centers (SBHCs) located at urban public high schools. These sites represent the wide variety of types of practices where adolescents receive routine health care and serve youth from urban, suburban, and rural areas, and from diverse racial/ethnic and socioeconomic backgrounds.
Participants were 12- to 18-year-old patients arriving for nonemergency care between March 1, 2003, and August 31, 2005. Recruitment was conducted at all sites simultaneously. We excluded 10 individuals considered medically or emotionally unstable on the day of the medical visit (eg, because of acute illness with fever, recent injury with acute pain, or being upset because of a positive pregnancy test result) and 7 who were unable to read and understand English. During the 28-month recruitment period, 2133 of 2301 invited patients agreed to participate (participation rate, 92.7%). Participation rates were similar across practices (range, 94.6%-99.2%) except one (health maintenance organization vs all others, 84.3% vs 95.5%; P < .001). Reasons cited for refusal included not wanting to be screened (n = 47), not interested in the topic (n = 44), not interested in research (n = 16), accompanied by a parent (n = 16), not enough time (n = 13), not feeling well (n = 4), other (n = 2), and no reason given (n = 26). Of the 168 refusers, 82 gave permission to analyze their demographic data. Compared with participants, these refusers were more likely to be male (43.7% vs 61.3%; P = .003), to be white (47.9% vs 67.1%; P = .001), to live with no parents or in foster care (3.0% vs 8.0%; P = .03), and to come to the clinic for a sick visit (11.8% vs 28.0%; P < .001), but they did not differ significantly with regard to age or parent education.
The survey tool included an 8-item demographic questionnaire, including items on age, sex, race/ethnicity, number of parents living at home, the highest parent education level, reason for the medical visit (well-child care, follow-up, sick visit, or other), patient status (new or established), a lifetime substance use question (“Have you ever used alcohol or drugs?”), the 6-item CRAFFT substance abuse screen, and a 3-item questionnaire on participants' preferences for type and method of completing the CRAFFT (computer vs paper vs verbal administration and administration by a nurse or provider who did or did not know the participant well). Analysis of responses to the preferences questionnaire is the subject of another report.22
A research assistant reviewed the clinic list each day with a nurse to determine eligibility. The research assistant approached eligible patients while they were in the clinic waiting room and moved those who were interested in participating to a private area of the clinic, where she explained the purpose and procedures of the study, obtained informed assent, and administered the study assessment. The research assistant verbally administered the demographic questionnaire and the lifetime substance use question. All participants were then asked the “C” question of the CRAFFT, “Have you ever ridden in a CAR driven by someone (including yourself) who was ‘high’ or had been using alcohol or drugs?” Those who reported ever using alcohol or other drugs were also asked the remaining “RAFFT” questions. The research assistant then supervised adolescents' completion of the preferences questionnaire. A subgroup of participants from all of the study sites (n = 222) completed the CRAFFT screen and preferences questionnaire directly on the computer. All participants were told that their primary care provider would receive a printed report of their responses to the CRAFFT questions. Participants received a $2 bill after completion of the survey as compensation for their time. The Children's Hospital Boston Committee on Clinical Investigations and institutional review boards at each of the participating practices approved a waiver of the requirement for parental consent in accordance with published guidelines for adolescent health research.23
Frequencies were computed for all demographic items, any lifetime use of alcohol or other drugs, any positive response to the “CAR” item on CRAFFT, and a positive substance abuse screen result, which was defined as a CRAFFT total score of 2 or higher (hereafter referred to as “CRAFFT+”).18 Frequencies were computed separately for each practice location and the entire study sample, and by visit type and patient status. Because each SBHC had a small number of participants and similarly high proportions of CRAFFT+ participants (SBHC 1, 7 of 30 participants [23.3%]; SBHC 2, 17 of 65 participants [26.2%]; and SBHC 3, 12 of 27 participants [44.4%]; P = .15), we combined these 3 sites for further analyses. We used computer software (SUDAAN 9; RTI International, Research Triangle Park, North Carolina) to obtain 95% confidence intervals and test statistics adjusted for correlation to practice location. The adjusted χ2 test was used to compare proportions. Generalized estimating equation analysis was used to compare practices and assess the effect of visit type and patient status while controlling for demographic differences of age, sex, race/ethnicity, and socioeconomic status indicators (parent education level and number of parents at home).
We estimated the prevalence of diagnostic categories that were defined in a previous validation study of the CRAFFT18 using a criterion standard psychiatric diagnostic interview.24Problematic use was defined as more than 1 substance-related problem during the past year but no diagnosis of abuse or dependence, and abuse and dependence were defined by the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition).25 For the present study, we developed a predictive model based on the β coefficients from a logistic regression model of the previous study and risk factors common to the 2 study populations (age, sex, race/ethnicity, and CRAFFT screen results) to compute prevalence estimates of problematic use, abuse, and dependence.26 The nonproblematic use estimate was determined as the proportion of the study population who reported substance use but was not predicted to have problematic use, abuse, or dependence. The overall accuracy of the model was high. Sensitivity and specificity were 82.6% and 90.1%, respectively, for problematic use, abuse, or dependence; 67.8% and 92.9%, respectively, for abuse or dependence; and 61.1% and 96.6%, respectively, for dependence. The areas under the receiver operating characteristic curves were 0.93 for problematic use, abuse, or dependence; 0.91 for abuse or dependence; and 0.93 for dependence. We estimated 95% confidence intervals for all prevalence estimates using bootstrap resampling.27
The study sample was 56.3% female and 48.6% non-Hispanic white, and the mean ± SD age was 15.7 ± 1.8 years (Table 1). Distribution of highest parent education level and number of parents at home, proxies for socioeconomic status, indicated a predominance of middle-class and upper-middle-class families. Greater than two-thirds of the medical visits were for routine well-child care and 91.7% were by established patients. However, distribution of all demographic variables differed significantly across practice locations.
Demographic and Substance Use Characteristics by Practice Location for the 2133 Participants
Overall, 43.5% of participants reported any lifetime use of alcohol or other drugs, 24.1% reported impaired driving risk (positive response to the “CAR” item on CRAFFT), and 14.8% screened positive on the CRAFFT (CRAFFT+). Prevalence rates also differed significantly across practices, with the highest CRAFFT+ rates in SBHCs and the rural family practice.
CRAFFT+ status was significantly associated with older age, race or Hispanic ethnicity, and fewer parents at home, but not with sex or lower parent education level (Table 2). Patients coming for well-child care visits had a significantly lower CRAFFT+ rate than those coming for follow-up, sick, and other visits. New patients had a higher CRAFFT+ rate than established patients.
Prevalence of a CRAFFT Screening Test Score of 2 or Higher by Demographic Characteristics in 2133 Patientsa
Some CRAFFT+ rate differences across visit type and patient status were explained by variations in demographic composition and practice location. Compared with well-child care visits, those coming for sick visits had substantially greater odds of being CRAFFT+. After adjusting for demographic differences (age, sex, race/ethnicity, and socioeconomic status) and practice location, however, this difference did not reach statistical significance (Table 3). Compared with the pediatric clinic, differences in demographic mix did not completely explain higher odds of CRAFFT+ status for the health maintenance organization, rural family practice, and SBHCs.
Data for a Positive Result on the CRAFFT by Practice Type, Visit Type, and Patient Status in 2133 Patientsa
Based on frequencies and our predictive modeling, we estimate that across the entire sample, 56.5% of patients were abstinent, 21.9% had nonproblematic use, 11.3% had problematic use, 7.1% met the criteria for a Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) diagnosis of substance abuse, and 3.2% met the criteria for a diagnosis of substance dependence.
This study found that approximately 15% of 12- to 18-year-old patients arriving for routine outpatient care had positive substance abuse screening test results. However, that finding was across all practices, and some practices had much higher rates. Our study did not yield definitive information on why the rural practice and SBHCs had higher rates. Some of the variation can be explained by demographic mix (eg, SBHCs in our study serve an older population and older age is a known risk factor for substance use). However, demographics do not explain all of the variation, and there may be factors inherent in a specific practice location that result in attracting higher-risk patients. Other studies28-31 have found higher rates of alcohol and other drug use in rural areas compared with urban and suburban areas. School-based health centers, because they offer confidential services, such as family planning, and are designed to be more accessible to youth may do a better job at bringing higher-risk youth into care, especially those engaging in early sexual activity.32-34
Our study suggests that sick visits and other non–well-child care visits yield higher screen-positive rates than well-child care visits. This finding, however, was largely a result of differences in demographic mix. Nevertheless, current guidelines recommend an annual screening for substance abuse as part of well-child care, but the implication of our study is that screening should occur at any visit when possible and certainly when the cause of the visit could be related to use of alcohol or other drugs (eg, car crash, other injury, or gastritis). The greatest difficulty with screening at sick visits is that many practices allow short times for these appointments (eg, 10-15 minutes). When this is the case, providers must ask those who screen positive to return for a subsequent visit so an assessment can be completed. The question may arise as to what to tell parents in this situation. Because screening does not yield a diagnosis, we recommend that parents not be informed that substance use is the reason for the return visit. A better approach might be to explain that the provider needs more time to complete a confidential psychosocial history, which is a necessary part of comprehensive adolescent care.
Our study also estimated the prevalence of subdiagnostic “problematic use” at 11.3% and Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition)–defined diagnoses of substance abuse and dependence at 7.1% and 3.3%, respectively. Some of the largest national epidemiological studies of substance abuse and dependence have included only those older than 18 years.4 One exception is the National Household Survey on Drug Abuse, which found that among 12- to 17-year-old individuals, the prevalence of alcohol abuse was 3.5% for males and 3.7% for females and the prevalence of alcohol dependence was 1.6% for males and females alike. The National Household Survey on Drug Abuse did not measure other drug abuse and dependence, and our rates, which were about double those of the National Household Survey on Drug Abuse, likely reflect the fact that we estimated the prevalence of alcohol- and other drug–related disorders together. A recent review35 of prevalence of adolescent alcohol use disorders in community and clinical settings found the range of prevalence of diagnostic orphans (problematic use) was 1.9% to 16.7%, with even wider ranges for the prevalence of abuse and dependence. Our findings are in the middle of these ranges.
A positive screen result does not establish a diagnosis. It should be followed by additional assessment, which is usually accomplished by obtaining a more detailed substance use history from the patient. Given the time pressures on providers in pediatric offices, who are usually allowed no more than 20 minutes for the adolescent annual well-child care visit, this assessment will likely require a return visit. In adolescent clinics and SBHCs, more time is often allowed (eg, 30-60 minutes) for well-child care visits and the assessment might, therefore, be accomplished as part of the initial visit.
In addition to the patient history, assessment sometimes requires history from a parent or other collateral reporter, a focused physical examination, and laboratory testing. These procedures require additional time. While it is partially reassuring that the overall screen-positive rate is only 15%, some practice types, such as rural practices or SBHCs, may require more resources than general pediatric practices to provide screening and follow-up assessments and intervention services and treatment.
The most important implication of the present study relates to treatment. If universal screening for substance use is to be accomplished, practices need to develop a plan to arrange a wide range of services. There is little point in screening for untreatable conditions.36 We found that slightly more than half of adolescents across all practices were abstinent. We recommend that these youth receive anticipatory guidance, praise, and encouragement, which can be delivered on the spot by the primary care provider at no additional cost. Approximately 1 in 5 adolescents had nonproblematic use of alcohol and other drugs. For these youth, the primary care provider should list the health consequences of alcohol and other drug use and advise the patient to stop. Brief physician advice has been effective in reducing drinking among adult medical patients,37,38 and this type of intervention, which should take no more than 5 to 10 minutes, can be delivered at minimal cost. However, providers may need a limited degree of additional training in how to deliver effective brief advice statements.
In our study, the youngest participants had the lowest rate of CRAFFT positivity (3.4%). This should not be taken as a reason to eliminate screening of younger children, because those who screen negative can still benefit from positive reinforcement to encourage continued abstinence. In addition, research indicates that the earlier the age of first drinking, the greater the likelihood of developing alcohol dependence, making it essential that providers identify the young users and provide early intervention.3
Approximately 11% of our patients were estimated to have problematic use, which is a subdiagnostic variant of substance abuse (sometimes referred to as “diagnostic orphans”).39 These youth, along with the 7.1% estimated to have a Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) diagnosis of substance abuse, should be referred for outpatient counseling. There has been a good deal of interest in recent years in brief interventions for substance abuse, which are generally defined as a limited number of counseling sessions (eg, 4-12 visits) over a brief interval (eg, 3-6 months). Structured therapies, such as cognitive-behavioral therapy40 or motivational enhancement therapy,41 are available for this purpose; and several studies42-44 have found these techniques effective in reducing risk behaviors among adolescents. In most settings, brief interventions will not be delivered by primary care providers, but by trained counselors, nurses, or social workers.
Of our sample, 3.2% was estimated to have alcohol or other drug dependence (addiction), and these youth will likely require referral to more intensive treatment. This level of service is, of course, the most expensive, and availability of developmentally appropriate substance abuse treatment for adolescents is limited in many communities. Before the implementation of new screening systems, we suggest that practices identify several providers of residential or day-hospital substance abuse treatment to which primary care providers can refer those patients found to have alcohol or other drug dependence.
This study had a number of strengths. It used a well-validated screen, the CRAFFT. The sample size was moderately large, and we received a waiver of the requirement for parental consent, which minimized the likelihood of self-selection bias. It was conducted in a network representing a wide variety of primary care practice types and locations throughout New England. However, a limitation is that these practices may not be representative of practices in other areas of the country or in different settings. Another potential limitation of the study was that the survey relied on adolescents' self-report. However, previous studies45,46 have shown self-report to be a reliable means of measuring substance use and to compare favorably with other methods of substance use detection, such as laboratory testing. Our study would have been strengthened by an assessment of the percentage of those estimated to meet criteria for abuse or dependence of alcohol alone, marijuana alone, or both substances. This study was also limited in that it did not involve data collection and analysis of tobacco use, another significant health concern for adolescents.
We found that slightly more than 1 in 7 adolescent patients screened positive on the CRAFFT, with significantly higher screen-positive rates in SBHCs and rural practices and among patients arriving for sick visits. We, therefore, recommend that providers consider screening whenever there is an opportunity, not just during annual well-child care visits. We also recommend that providers receive training in how to further assess those who screen positive and to effectively offer brief advice or referral to counseling or treatment for patients who need them. Given the pressures of time on primary care providers, more research is needed on efficient and effective office-based systems for substance abuse screening and therapeutic interventions. Early identification and intervention of adolescent substance use presents the greatest opportunity for reducing the burden of addictive disorders later in life.
Correspondence: John R. Knight, MD, Center for Adolescent Substance Abuse Research, Children's Hospital Boston, 300 Longwood Ave, Boston, MA 02115 (firstname.lastname@example.org).
Accepted for Publication: April 29, 2007.
Author Contributions: Drs Knight and Harris and Mr Sherritt had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Knight, Sherritt, Van Hook, Lawrence, Brooks, Carey, and Kulig. Acquisition of data: Knight, Sherritt, Lawrence, Brooks, Carey, Kossack, and Kulig. Analysis and interpretation of data: Knight, Harris, Sherritt, Van Hook, and Lawrence. Drafting of the manuscript: Knight. Critical revision of the manuscript for important intellectual content: Knight, Harris, Sherritt, Van Hook, Lawrence, Brooks, Carey, Kossack, and Kulig. Statistical analysis: Knight, Harris, and Sherritt. Obtained funding: Knight. Administrative, technical, and material support: Knight, Sherritt, Van Hook, Lawrence, Brooks, Carey, and Kulig. Study supervision: Knight, Sherritt, Van Hook, Brooks, Carey, Kossack, and Kulig.
Financial Disclosure: None reported.
Funding/Support: This study was supported by grant 45222 from the Robert Wood Johnson Foundation; grant K07 AA013280 from the National Institute on Alcohol Abuse and Alcoholism (Dr Knight); and grants 5T20MC000-11-06 (Ms Van Hook and Dr Knight) and 5T71MC00009-12-0 (Dr Harris) from the Maternal and Child Health Bureau.
Role of the Sponsor: The funding bodies had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript.
Additional Contributions: The physicians and staff of The New England Partnership for Substance Abuse Research assisted with study implementation, including Kathleen Kelley, MBA; Jeanne McBride, RN, BSN, MM, Quality Improvement Project Manager, Department of Family Medicine and Community Health, UMass Memorial Health Care; Irene Phelps, RN, BSN; Judy Shaw, RN, MPH, Executive Director, Vermont Child Health Improvement Program; Donald H. Taylor III, MIT; and Colleen Sheppard, RN, BSN, Department of Pediatrics and Adolescent Medicine, Tufts–New England Medical Center.
HD Drug dependence, a chronic medical illness: implications for treatment, insurance, and outcomes evaluation. JAMA
1689- 1695PubMedGoogle ScholarCrossref
MR Age at drinking onset and alcohol dependence: age at onset, duration, and severity. Arch Pediatr Adolesc Med
739- 746PubMedGoogle ScholarCrossref
RP The 12-month prevalence and trends in DSM-IV
alcohol abuse and dependence: United States, 1991-1992 and 2001-2002. Drug Alcohol Depend
223- 234PubMedGoogle ScholarCrossref
et al. Adolescent alcohol use is a risk factor for adult alcohol and drug dependence: evidence from a twin design. Psychol Med
109- 118PubMedGoogle ScholarCrossref
JE Monitoring the Future: National Results on Adolescent Drug Use: Overview of Key Findings, 2005. Bethesda, MD National Institute on Drug Abuse2006.;NIH publication 06-5882
et al. Youth risk behavior surveillance: United States, 2005. MMWR Surveill Summ
1- 108PubMedGoogle Scholar
EJ Effects of age at first substance use and psychiatric comorbidity on the development of substance use disorders. Drug Alcohol Depend
287- 299PubMedGoogle ScholarCrossref
W Cannabis use and mental health in young people: cohort study. BMJ
1195- 1198PubMedGoogle ScholarCrossref
AV Drug use, sexual activity, and suicidal behavior in US high school students. J Sch Health
222- 227PubMedGoogle ScholarCrossref
JW Tobacco, alcohol, and other drugs: the role of the pediatrician in prevention, identification, and management of substance abuse. Pediatrics
816- 821PubMedGoogle ScholarCrossref
JR Office management of substance use. Adolesc Health Update
1- 9Google Scholar
Jed Bright Futures: Guidelines for Health Supervision of Infants, Children, and Adolescents. 2nd ed. Arlington, VA National Center for Education in Maternal and Child Health2000;
Ned AMA Guidelines for Adolescent Preventive Services (GAPS). Baltimore, MD Williams & Wilkins1994;
ERed The Adolescent Assessment/Referral System Manual. Bethesda, MD Alcohol, Drug Abuse, and Mental Health Administration, US Dept of Health and Human Services, Public Health Service1991.;DHHS publication (ADM)91-1735
Tde la Fuente
M AUDIT: The Alcohol Use Disorders Identification Test: Guidelines for Use in Primary Health Care. Geneva, Switzerland World Health Organization1992;
HJ A new brief screen for adolescent substance abuse. Arch Pediatr Adolesc Med
591- 596PubMedGoogle Scholar
G Validity of the CRAFFT substance abuse screening test among adolescent clinic patients. Arch Pediatr Adolesc Med
607- 614PubMedGoogle ScholarCrossref
et al. Test-retest reliability of adolescents' self-report of substance use. Alcohol Clin Exp Res
1236- 1241PubMedGoogle ScholarCrossref
American Academy of Pediatrics, Periodic Survey of Fellows #31: Practices and Attitudes Toward Adolescent Drug Screening. Elk Grove Village, IL Division of Child Health Research, American Academy of Pediatrics1997;
et al. New England Partnership for Substance Abuse Research, The “Six T’s”: barriers to screening teens for substance abuse in primary care. J Adolesc Health
456- 461PubMedGoogle ScholarCrossref
et al. Adolescents' preferences for substance abuse screening in primary care practice. Subst Abus
In pressPubMedGoogle Scholar
G Adolescent Diagnostic Interview (ADI) Manual. Los Angeles, CA Western Psychological Services1993;
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC American Psychiatric Association1994;
DB Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med
361- 387PubMedGoogle ScholarCrossref
J Bootstrap confidence intervals: when, which, what? a practical guide for medical statisticians. Stat Med
1141- 1164PubMedGoogle ScholarCrossref
PD Alcohol, tobacco, and other drug use among rural/small town and urban youth: a secondary analysis of the monitoring the future data set. Am J Public Health
760- 764PubMedGoogle ScholarCrossref
GA Health risk behaviors among adolescents attending rural, suburban, and urban schools: a comparative study. Fam Community Health
53- 64PubMedGoogle ScholarCrossref
LG Problem drinking: rural and urban trends in America, 1995/1997 to 2003. Prev Med
122- 124PubMedGoogle ScholarCrossref
JR Comorbid substance and mental disorders among rural Americans: results from the National Comorbidity Survey. J Affect Disord
265- 271PubMedGoogle ScholarCrossref
J Adolescents' use of school-based health clinics for reproductive health services: data from the National Longitudinal Study of Adolescent Health. J Sch Health
22- 27PubMedGoogle ScholarCrossref
D Use of health and mental health services by adolescents across multiple delivery sites. J Adolesc Health
(suppl)108- 118PubMedGoogle ScholarCrossref
DW Comprehensive school-based health care: high school students' use of medical, mental health, and substance abuse services. Pediatrics
318- 330PubMedGoogle Scholar
EW Prevalence of DSM-IV
alcohol diagnoses and symptoms in adolescent community and clinical samples. J Am Acad Child Adolesc Psychiatry
546- 554PubMedGoogle ScholarCrossref
R Brief physician advice for problem alcohol drinkers: a randomized controlled trial in community-based primary care practices. JAMA
1039- 1045PubMedGoogle ScholarCrossref
KL Brief physician advice for problem drinkers: long-term efficacy and benefit-cost analysis. Alcohol Clin Exp Res
36- 43PubMedGoogle ScholarCrossref
CS Diagnostic orphans: adolescents with alcohol symptoms who do not qualify for DSM-IV
abuse or dependence diagnoses. Am J Psychiatry
897- 901PubMedGoogle Scholar
et al. Cognitive-Behavioral Coping Skills Therapy Manual: A Clinical Research Guide for Therapists Treating Individuals With Alcohol Abuse and Dependence. Rockville, MD National Institute on Alcohol Abuse and Alcoholism1994;
RG Motivational Enhancement Therapy Manual: A Clinical Research Guide for Therapists Treating Individuals With Alcohol Abuse and Dependence. Rockville, MD National Institute on Alcohol Abuse and Alcoholism1994;
G Motivational interviewing for adolescent substance use: a pilot study. J Adolesc Health
167- 169PubMedGoogle ScholarCrossref
P, Colby S, O’Leary T, eds.ed Motivational enhancement for alcohol-involved adolescents. Adolescents, Alcohol, and Substance Abuse: Reaching Teens Through Brief Interventions.
New York, NY Guilford Press2001;145- 182Google Scholar
et al. Brief intervention for harm reduction with alcohol-positive older adolescents in a hospital emergency department. J Consult Clin Psychol
989- 994PubMedGoogle ScholarCrossref
RJ Early detection of harmful alcohol consumption: comparison of clinical, laboratory, and self-report screening procedures. Addict Behav
139- 157PubMedGoogle ScholarCrossref
RH Validity of adolescent self-report of alcohol and other drug involvement. Int J Addict
1379- 1395PubMedGoogle Scholar