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* Abbreviations: IU — : instrumental use RU — : recreational use YCMC — : youth with chronic medical conditions We surveyed youth with chronic medical conditions (YCMC) to assess whether marijuana used to address symptoms or side effects (“instrumental use” [IU]) was associated with health characteristics, substance-use behaviors, and beliefs. We analyzed baseline data from 451 participants aged 14 to 18 years receiving care for a chronic medical condition who enrolled in a randomized trial of an intervention to reduce alcohol use. Seventy-three participants reported marijuana use in the past 12 months and were included in these analyses. Youth assent was secured with a waiver of parental consent under the approval of the institutional review board. Participants were asked whether they use marijuana to alleviate disease symptoms or side effects. Marijuana use items included the following: age … Address correspondence to Joe Kossowsky, PhD, MMSc, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children’s Hospital, 333 Longwood Ave, Boston, MA 02115. E-mail: joe.kossowsky{at}childrens.harvard.edu

Background College environments promote high-volume or binge alcohol consumption among youth, which may be especially harmful to those with type 1 diabetes (T1D). Little is known about the acceptability and effectiveness of interventions targeting reduced alcohol use by college students with T1D, and it is unclear whether intervention framing (specifically, the narrator of intervention messages) matters with respect to affecting behavior change. Interventions promoted by peer educators may be highly relatable and socially persuasive, whereas those delivered by clinical providers may be highly credible and motivating. Objective The aim of this study is to determine the acceptability and impacts of an alcohol use psychoeducational intervention delivered asynchronously through web-based channels to college students with T1D. The secondary aim is to compare the impacts of two competing versions of the intervention that differed by narrator (peer vs clinician). Methods We recruited 138 college students (aged 17-25 years) with T1D through web-based channels and delivered a brief intervention to participants randomly assigned to 1 of 2 versions that differed only with respect to the audiovisually recorded narrator. We assessed the impacts of the exposure to the intervention overall and by group, comparing the levels of alcohol- and diabetes-related knowledge, perceptions, and use among baseline, immediately after the intervention, and 2 weeks after intervention delivery. Results Of the 138 enrolled participants, 122 (88.4%) completed all follow-up assessments; the participants were predominantly women (98/122, 80.3%), were White non-Hispanic (102/122, 83.6%), and had consumed alcohol in the past year (101/122, 82.8%). Both arms saw significant postintervention gains in the knowledge of alcohol’s impacts on diabetes-related factors, health-protecting attitudes toward drinking, and concerns about drinking. All participants reported significant decreases in binge drinking 2 weeks after the intervention (21.3%; odds ratio 0.48, 95% CI 0.31-0.75) compared with the 2 weeks before the intervention (43/122, 35.2%). Changes in binge drinking after the intervention were affected by changes in concerns about alcohol use and T1D. Those who viewed the provider narrator were significantly more likely to rate their narrator as knowledgeable and trustworthy; there were no other significant differences in intervention effects by the narrator. Conclusions The intervention model was highly acceptable and effective at reducing self-reported binge drinking at follow-up, offering the potential for broad dissemination and reach given the web-based format and contactless, on-demand content. Both intervention narrators increased knowledge, improved health-protecting attitudes, and increased concerns regarding alcohol use. The participants’ perceptions of expertise and credibility differed by narrator. Trial Registration ClinicalTrials.gov NCT02883829; https://clinicaltrials.gov/ct2/show/NCT02883829 International Registered Report Identifier (IRRID) RR2-10.1177/1932296819839503

Background The Screening to Brief Intervention (S2BI) tool was designed to identify substance use disorders in adolescents. We report the S2BI's sensitivity and specificity for identifying alcohol and cannabis use disorders (AUD and CUD) in adolescents presenting for primary care. Methods Participants aged 14–18 ( N = 517) completed an electronic survey, consisting of the S2BI, the Composite International Diagnostic Interview (CIDI), and anxiety and depression screens. We calculated sensitivity, specificity, and positive and negative predictive value (PPV, NPV) of the S2BI compared to the CIDI criterion standard, using past year “monthly” and “weekly or more” consumption of alcohol or marijuana as a threshold for AUD or CUD. Results Current AUD and CUD were present in 2.9% and 8.3% of the sample, respectively and severe AUD and CUD were present in 0.8% and 3.9%. The S2BI had 53.3% sensitivity and 94.2% specificity for identifying any AUD (PPV = 21.6%; NPV = 98.5%), and 81.4% sensitivity and 92.0% specificity for identifying any CUD (PPV = 47.9%; NPV = 98.2%). The same threshold had 100% sensitivity and 93.6% specificity for identifying moderate/severe AUD, and 90.0% sensitivity and 89.0% specificity for identifying moderate/severe CUD. Conclusions S2BI had excellent sensitivity and specificity for identifying moderate and severe AUD and CUD. Sensitivity decreased when mild AUD and CUD were included.

We sought to quantify the efficiency and acceptability of Internet-based recruitment for engaging an especially hard-to-reach cohort (college-students with type 1 diabetes, T1D) and to describe the approach used for implementing a health-related trial entirely online using off-the-shelf tools inclusive of participant safety and validity concerns.We recruited youth (ages 17-25 years) with T1D via a variety of social media platforms and other outreach channels. We quantified response rate and participant characteristics across channels with engagement metrics tracked via Google Analytics and participant survey data. We developed decision rules to identify invalid (duplicative/false) records (N = 89) and compared them to valid cases (N = 138).Facebook was the highest yield recruitment source; demographics differed by platform. Invalid records were prevalent; invalid records were more likely to be recruited from Twitter or Instagram and differed from valid cases across most demographics. Valid cases closely resembled characteristics obtained from Google Analytics and from prior data on platform user-base. Retention was high, with complete follow-up for 88.4%. There were no safety concerns and participants reported high acceptability for future recruitment via social media.We demonstrate that recruitment of college students with T1D into a longitudinal intervention trial via social media is feasible, efficient, acceptable, and yields a sample representative of the user-base from which they were drawn. Given observed differences in characteristics across recruitment channels, recruiting across multiple platforms is recommended to optimize sample diversity. Trial implementation, engagement tracking, and retention are feasible with off-the-shelf tools using preexisting platforms.

Background Youth with chronic medical conditions (YCMC) use alcohol at levels similar to their healthy peers but face elevated risk for adverse health consequences. As salient reasons to abstain from or limit drinking (RALD) among YCMC are unknown, we sought to identify clusters of RALD and test associations with use behaviors. Methods Eligible YCMC (ages 9-18) recruited from outpatient clinics reported their use behaviors and importance of potential RALD. Cluster analysis was used to discern RALD patterns, which were examined as predictors of alcohol use using multivariate regression. Results Among 398 participants, 30.9% reported past year alcohol use. Concerns about impacts on medications, school, and disease status were the most frequently endorsed RALD; prior negative experiences with alcohol and family history were the least frequently endorsed. Five RALD clusters were identified for all YCMC and 2 for recent drinkers. Compared to the cluster with high endorsement of multiple general and health-related RALD, those predominantly citing concerns about addiction and those not strongly endorsing any RALD consistently reported greater alcohol use. Among recent drinkers, the cluster characterized by low concern across multiple RALD also consistently reported greater alcohol use compared to their counterparts expressing moderate concern. Conclusions For YCMC, RALD are complex but endorsement of multiple general and health-related RALD is associated with less use, and health concerns are especially prevalent. More research is needed to understand how salient RALD can inform tailored interventions that aim to delay and reduce substance use and improve health outcomes for YCMC.

BACKGROUND AND OBJECTIVES: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.