Literature Collection

IMPORTANCE: Little is known about cannabis vaping trajectories across adolescence and young adulthood or the co-occurrence with nicotine vaping. OBJECTIVE: To evaluate nicotine vaping and cannabis vaping trajectories from late adolescence to young adulthood (≥18 years of age) and the extent of polysubstance vaping. DESIGN, SETTING, AND PARTICIPANTS: In this prospective cohort study, 5 surveys (including information on substance vaped) were completed at 10 high schools in the Los Angeles, California, metro area. Students were surveyed at 6-month intervals from fall of 11th grade (October to December 2015; wave 5) through spring of 12th grade (March to June 2017; wave 8) and again approximately 1 to 2 years after high school (October 2018 to October 2019; wave 9). EXPOSURES: Past 30-day nicotine and cannabis vaping frequency across 5 waves. MAIN OUTCOMES AND MEASURES: Self-reported frequency of nicotine vaping and cannabis vaping within the past 30 days across 5 time points from late adolescence to young adulthood. Trajectories were measured with these past 30-day use frequencies at each wave. Parallel growth mixture modeling estimated conditional probabilities of polysubstance vaping. RESULTS: The analytic sample included 3322 participants with at least 1 time point of data (mean [SD] age, 16.50 [0.42] years at baseline; 1777 [53.5%] female; 1573 [47.4%] Hispanic or Latino). Growth mixture modeling identified the 5-trajectory model as optimal for both nicotine vaping and cannabis vaping. Trajectories for nicotine and cannabis vaping were similar (nonusers: 2246 [67.6%] nicotine, 2157 [64.9%] cannabis; infrequent users: 566 [17.0%] nicotine, 608 [18.3%] cannabis; moderate users: 167 [5.0%] nicotine, 233 [7.0%] cannabis; young adult-onset frequent users: 213 [6.4%] nicotine, 190 [5.7%] cannabis; adolescent-onset escalating frequent users: 131 [3.9%] nicotine, 134 [4.0%] cannabis). Males had greater odds of belonging to the adolescent-onset escalating frequent users nicotine (adjusted odds ratio, 2.88; 95% CI, 1.58-5.23; P < .01) and cannabis (adjusted odds ratio, 1.95; 95% CI,1.03-3.66; P < .05) vaping trajectories compared with nonusers. Polysubstance vaping was common, with those in trajectories reflecting more frequent nicotine vaping (adolescent-onset escalating frequent users and young adult-onset frequent users) having a high probability of membership (85% and 93%, respectively) in a cannabis-use trajectory. CONCLUSIONS AND RELEVANCE: In this cohort study, the prevalence and type of nicotine vaping and cannabis vaping developmental trajectories from late adolescence to young adulthood were similar. Polysubstance vaping was common from late adolescence to young adulthood, particularly among those reporting more frequent vaping use. The findings suggest that public health policy and clinical interventions should address polysubstance vaping in both adolescence and young adulthood.

To support effective implementation of these strategies in practices throughout the country--including the identification of barriers and challenges--this case study examines the redesign of the New Mexico Cancer Center (NMCC) as one example of how a group of clinicians can implement change. This case study will focus on the care redesign model and potential payment reform options to sustain improvements at NMCC. With the aim to support the education of a clinical audience regarding how care innovations can be aligned with alternative payment models, this case will answer the following questions: What challenges or problems encouraged the organization to redesign cancer care? How did NMCC redesign care to improve quality, enhance the patient experience, and reduce costs? How can an organization prove they are improving quality and contract with a payer to maintain sustainability? How can alternative payment models sustain a community oncology medical home?