Preferences, use, and perceived access to flavored e-cigarettes among United States adolescents and young adults.

Background: Citing concern over youth use, the Food and Drug Administration announced a prioritized enforcement policy against cartridge-based (reusable pod) e-cigarettes in non-menthol, non-tobacco flavors, effective February 2020. Data are needed regarding youth e-cigarette access and use behaviors following this policy. Methods: This cross-sectional national (USA) online panel survey, conducted March/April 2021, included 2253 participants ages 14-20 who ever used e-cigarettes ≥3 times (73% past 30-day users). Participants reported their flavor preferences, use reasons, and perceived ease of access. Latent class analysis categorized participants according to their preferred e-cigarette flavors, and multinominal logistic regression identified sociodemographic and behavioral correlates of class membership. Results: Most past 30-day e-cigarette users used reusable pod (77%) or modern disposable (68%) devices, ≥1 non-tobacco (92%), sweet (76%), and/or menthol flavors including fruit-ice (70%) (flavor and device categories not mutually exclusive). Most past 30-day users (70%) and non-users (63%) perceived it would be somewhat or very easy to acquire e-cigarettes in flavors they like. Latent class analysis identified four e-cigarette flavor preference classes: mint (34% of sample), no preference (29%), fruit/sweet (28%), and dislikes ≥1 flavor (10%). Relative to no preference, membership in fruit/sweet (RRR: 1.87; 95% CI: 1.37, 2.57) and mint (RRR: 3.85; 95% CI: 2.77, 5.36) classes was associated with using e-cigarettes ≥50 times. Fruit/sweet membership was inversely associated with combustible tobacco use (RRR: 0.50; 95% CI: 0.38, 0.66). Conclusion: Young e-cigarette users maintained ample access to flavored and cartridge-based products. Stronger access restrictions and enforcement are required to reduce youth e-cigarette use.

Cannabis and End-of-Life Care: A Snapshot of Hospice Planning and Experiences Among Illinois Medical Cannabis Patients With A Terminal Diagnosis.

INTRODUCTION: Between 2013 and 2019, Illinois limited cannabis access to certified patients enrolled in the Illinois Medical Cannabis Program (IMCP). In 2016, the state instituted a fast-track pathway for terminal patients. The benefits of medicinal cannabis (MC) have clear implications for patients near end-of-life (EOL). However, little is known about how terminal patients engage medical cannabis relative to supportive care. METHODS: Anonymous cross-sectional survey data were collected from 342 terminal patients who were already enrolled in (n = 19) or planning to enroll (n = 323) in hospice for EOL care. Logistic regression models compare patients in the sample on hospice planning vs. hospice enrollment, use of palliative care vs. hospice care, and use standard care vs non-hospice palliative care. RESULTS: In our sample, cancer patients (OR = 0.21 (0.11), p < .01), and those who used the fast-track application into the IMCP (OR = 0.11 (0.06), p < .001) were less likely to be enrolled in hospice. Compared to patients in palliative care, hospice patients were less likely to report cancer as their qualifying condition (OR = 0.16 (0.11), p < .01), or entered the IMCP via the fast-track (OR = 0.23 (0.15), p < .05). DISCUSSION: Given low hospice enrollment in a fairly large EOL sample, cannabis use may operate as an alternative to supportive forms of care like hospice and palliation. Clinicians should initiate conversations about cannabis use with their patients while also engaging EOL Care planning discussions as an essential part of the general care plan.

Assessing Health-Related Outcomes of Medical Cannabis Use among Older Persons: Findings from Colorado and Illinois.

OBJECTIVES: To assess health-related outcomes associated with medical cannabis use among older patients in Colorado and Illinois enrolled in their home state's medical cannabis program. METHODS: Cross-sectional data from anonymous surveys were collected from 139 persons over the age of 60 using medical cannabis in the past year. We used structural equation modeling (SEM) to confirm the hypothesized four-factor structure that includes health-related quality of life (HRQL), health-care utilization (HCU), symptom effects, and adverse events. We then examined associations between cannabis use and self-reported outcome changes using linear regression. RESULTS: The four-factor model was the best fitting structure (X2(df) = 81.63 (67), p> X2 = 0.108) relative to reduced structures. We also found that using cannabis 1-4 times per week is associated with 3.30 additional points on the HRQL scale (p < .001), 2.72 additional points on the HCU scale (p < .01), and 1.13 points on pain (p < .001). The frequency of use reported at 5-7 times per week is associated with 4.71 additional HRQL score points (p < .001). No significant associations were observed between the frequency of use and adverse events. CONCLUSIONS: We observed how cannabis use outcomes fall into four independent factors, and those using more frequently reported higher values on HRQL, HCU, and pain measures. However, we are cautious about the generalizability of our findings. CLINICAL IMPLICATIONS: Clinicians should consider how older patients using medical cannabis can experience positive and negative outcomes simultaneously or separately and assess these outcomes directly along with considering patient self-reports.

Use of cannabis and opioids for chronic pain by older adults: Distinguishing clinical and contextual influences.

INTRODUCTION AND AIMS: Chronic pain is one of the most common health-related conditions experienced by Americans over the age of 65. In this study, we examine the intersection between pain, opioids and cannabis use among older adults in Colorado and Illinois and examine how medical needs and other variables associated with a persons' background and attitudes influence choices concerning the use of opioids and cannabis to treat pain. DESIGN AND METHODS: Data were collected via a survey about cannabis and opioids use, and questions related to individual need factors (e.g. pain, quality of life) and contextual factors (e.g. sex, finances, personal attitudes, interaction with physicians) were included in this study. We built a logistic regression model to evaluate factors associated with drug use and a multinomial regression model to understand factors that influence drug choices between cannabis and opioids. RESULTS: A total of 436 individuals completed the survey; 62 used opioids only, 71 cannabis only and 72 used both. When comparing drug users to non-drug users, pain was significantly associated with using cannabis and/or opioids when controlling for other covariates. However, when we compared cannabis users to opioid users, pain was no longer a determining factor. Instead, other contextual factors such as sex, personal beliefs and physician attitudes influenced an individual's choice between cannabis or opioids. DISCUSSION AND CONCLUSIONS: This study showed that contextual factors appear to have more influence on an individual's decision to use cannabis as an alternative to opioids than individual need or characteristics.