Despite their medical vulnerability, youth with chronic medical conditions (YCMCs) drink at levels commensurate with healthy youth. However, information about the prevalence of alcohol use among YCMCs who take alcohol-interactive (AI) medications is scant. To address gaps and inform interventions, we quantified simultaneous exposure to alcohol use and AI medications among YCMCs, hypothesizing that AI exposure would be associated with lower alcohol consumption and mediated by perceptions of alcohol-medication interference. Adolescents with type 1 diabetes, juvenile idiopathic arthritis, moderate persistent asthma, cystic fibrosis, attention-deficit/hyperactivity disorder, or inflammatory bowel disease completed an electronic survey. We measured the prevalence of exposure to AI medications and the associations with past-year alcohol use as well as binge drinking and total consumption volume in the past 3 months using multivariate regression to estimate the odds of alcohol use given AI medication exposure and perceptions of interference. Of 396 youth, 86.4% were on AI medications, of whom, 35.4% reported past-year alcohol use (46.3% among those who were not on AI medications). AI medication use was associated with 43% lower odds of past-year alcohol use (adjusted odds ratio: 0.57; 95% confidence interval: 0.39-0.85) and lower total consumption (β = -.43; SE = 0.11; P < .001). Perceptions of alcohol-medication interference partially mediated the relationship between AI medication exposure and past-year alcohol use (Sobel test P = .05). Many YCMCs reported using alcohol; however, drinking was less likely among those who were taking AI medications. Perceptions about alcohol-medication interference mediated the association between drinking and AI medication exposure, suggesting the potential salience of interventions that emphasize alcohol-related risks.

Objective

Adolescents with attention-deficit/hyperactivity disorder (ADHD) are at increased risk for alcohol and marijuana use. This study's objective is to describe adolescents' ADHD-specific reasons for marijuana use, knowledge of ADHD-specific alcohol risks, and reported subspecialty provider messaging/education regarding alcohol use among adolescents with ADHD.

Methods

Youths with ADHD aged 12 to 18 years completed a survey about alcohol and marijuana use, ADHD-specific reasons for marijuana use, knowledge of ADHD-specific alcohol risks, and reported provider messaging/education regarding alcohol use. We assessed knowledge toward substance use using descriptive statistics. We used χ and t tests to determine whether knowledge or provider messaging/education differed by sociodemographic characteristics.

Results

Of the 96 participants, 61.5% were male, average age was 15.7 years; 31.3% reported past-year alcohol use and 20.8% reported past-year marijuana use. The majority (65.2%) said "no/don't know" to both "Can alcohol make ADHD symptoms worse?" and "Can alcohol interfere or get in the way of the medications you take?" Older participants were more likely to correctly answer the medication question "yes." Despite most (74%) participants reporting that their provider asked about alcohol use, few youth reported that their providers gave specific messages/education that alcohol could make ADHD symptoms worse (9.4%) or interfere with ADHD medications (14.6%); older participants and past-year alcohol users were more likely to have received these alcohol-specific messages.

Conclusion

Many youth with ADHD are unaware of the risks of alcohol use in relation to ADHD and providers are not consistently discussing these risks in the context of clinical ADHD care.

Purpose

We seek to determine how youth with chronic medical conditions experience alcohol screening and counseling.

Methods

Adolescents with type I diabetes, juvenile idiopathic arthritis, moderate persistent asthma, cystic fibrosis, attention deficit hyperactivity disorder, or inflammatory bowel disease were surveyed. Descriptive statistics and regression analysis quantified rates of asking and counseling about alcohol.

Results

Of 390 participants (75.1% white/non-Hispanic, 51.8% female, average age 16.4 years), 70% reported being asked about their alcohol use by a healthcare provider, and 76% reported receiving at least one message regarding alcohol and health. Of past year drinkers, 54% disclosed use to their provider. Only 2.0% of youth reported receiving the message "I should not drink."

Conclusions

Most youth with chronic medical conditions were asked and counseled about alcohol use although few heard unambiguous recommendations to avoid alcohol consumption.

Background

In an effort to reduce barriers to screening for alcohol use in pediatric primary care, the National Institute on Alcoholism and Alcohol Abuse (NIAAA) developed a two-question Youth Alcohol Screening Tool derived from population-based survey data. It is unknown whether this screening tool, designed for use with general populations, accurately identifies risk among youth with chronic medical conditions (YCMC). This growing population, which comprises nearly one in four youth in the US, faces a unique constellation of drinking-related risks.

Method

To validate the NIAAA Youth Alcohol Screening Tool in a population of YCMC, we performed a cross-sectional validation study with a sample of 388 youth ages 9-18 years presenting for routine subspecialty care at a large children's hospital for type 1 diabetes, persistent asthma, cystic fibrosis, inflammatory bowel disease, or juvenile idiopathic arthritis. Participants self-administered the NIAAA Youth Alcohol Screening Tool and the Diagnostic Interview Schedule for Children as a criterion standard measure of alcohol use disorders (AUD). Receiver operating curve analysis was used to determine cut points for identifying youth at moderate and highest risk for an AUD.

Results

Nearly one third of participants (n = 118; 30.4%) reported alcohol use in the past year; 86.4% (106) of past year drinkers did not endorse any AUD criteria, 6.8% (n = 8) of drinkers endorsed a single criterion, and 6.8% of drinkers met criteria for an AUD. Using the NIAAA tool, optimal cut points found to identify youth at moderate and highest risk for an AUD were ≥ 6 and ≥12 drinking days in the past year, respectively.

Conclusions

The NIAAA Youth Alcohol Screening Tool is highly efficient for detecting alcohol use and discriminating disordered use among YCMC. This brief screen appears feasible for use in specialty care to ascertain alcohol-related risk that may impact adversely on health status and disease management.