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Background: Tobacco cannabis co-use is common and becoming more prevalent. Frequent and heavy users of cannabis may struggle to quit smoking. Quitlines offer free cessation treatment in the United States and 25% of quitline callers may also be cannabis users. The present paper describes a randomized pilot study of a tailored intervention for cannabis and cigarette co-users. The intervention combines the quitline smoking cessation treatment with a motivational enhancement therapy-based cannabis intervention. Methods: The randomized pilot study was conducted within four state-funded quitlines with quitline coaches as interventionists. 102 quitline callers who were cannabis and cigarette co-users were randomized to receive treatment as usual (TAU) or the new Quitline Check-Up (QLCU) intervention. Outcomes were collected 90 days post-randomization. Primary outcomes included feasibility and acceptability of delivering the QLCU in the quitline setting. Secondary outcomes included 7-day point prevalence tobacco abstinence, past 30-day cannabis use, and Cannabis Use Disorder Identification Test scores. Results: Study participants were heavy cannabis users, averaging 25 days of use in the past 30; nearly 70% used at a level considered hazardous. Fidelity ratings indicated coaches were successful at delivering the intervention. Treatment engagement was high for both groups (TAU m = 3.4 calls; QLCU m = 3.6 calls) as was treatment satisfaction. Intent-to-treat quit rates (with survey non-responders classified as smokers) were 28.6% for the TAU control group and 24.5% for the QLCU group (P = .45). Discussion: Hazardous cannabis use rates were high in this sample of tobacco cannabis co-users calling quitlines to quit smoking. The intervention for co-users was acceptable and feasible to deliver. No improvements in tobacco cessation outcomes were observed. Pragmatic intervention development within a real-world clinical setting can streamline the intervention development process. More research is needed on tobacco cannabis co-users and who can benefit from a tailored intervention. Registered: ClinicalTrials.gov NCT04737772, February 4, 2021.

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Despite interest in quitting vaping among young adults (YAs), little is known about characteristics of e-cigarette (EC) users seeking treatment. In this study, YAs aged 18-24 living in the United States interested in vaping cessation treatment were recruited to complete an online survey regarding demographics and EC use. Primary eligibility criteria were EC use on at least 20 days per month (no other tobacco use), and interest in quitting in the next month. We report descriptive statistics for those who did and did not complete a mandatory coaching call (n = 981). In this sample, most EC users reported high nicotine dependence, a history of unsuccessful quit attempts (including 29.4% with previous NRT use), along with stress, anxiety, and depression. There were few meaningful differences in demographics, EC use behaviors, or behavioral health factors between those who engaged with a phone coaching call (fully enrolled in study; n = 508), and those who did not (n = 473). YAs demonstrated interest in vaping cessation support, but there were no clear characteristics for the half who did not complete a coaching call. Vaping cessation program designers should consider tailoring for the self-reported behavioral health concerns present in this population.

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Numerous studies have supported the effectiveness and cost-effectiveness of quitlines for cigarette smoking cessation, but how effective they are for vaping cessation has not been established. Our secondary analysis examined quitline data on participants in employer-sponsored quitlines in the US run by Optum, Inc to compare quit rates among callers who were exclusive vapers (n = 1,194) with those who were exclusive smokers (n = 22,845). We examined data from the time of quitline enrollment, January 2017, through October 2020. Before adjusting for differences in demographics, quitline treatment engagement, and unadjusted quit rates, the quit rates for vapers were significantly higher. However, after adjusting for demographic and treatment engagement variables, 6-month quit rates among vapers did not differ significantly from rates among smokers.

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2019 Novel coronavirus (COVID-19) vaccination rates in the United States have plateaued in specific populations, including rural areas. To improve COVID-19 vaccination rates and to encourage early vaccine uptake in future pandemics, this study aimed to examine vaccine attributes associated with early adoption. Data are from an anonymous online survey of adults using targeted Facebook pages of rural southern Indiana towns in January and February 2021 (n = 286). The diffusion of innovation theory states that the rate of adoption of a product in a specific population is explained by five perceived attributes: relative advantage, compatibility, observability, complexity and trialability. Binary logistic regression analyses were used to examine the association of Diffusion of Innovation theory attributes of the COVID-19 vaccine on early adoption. Results indicated that trialability [odds ratio (OR) = 3.307; 95% confidence interval (CI) = 1.964-5.571; P < 0.001], relative advantage (OR = 2.890; 95% CI = 1.789-4.667; P < 0.001) and compatibility (OR = 2.606; 95% CI = 1.476-4.601; P < 0.001) showed significant independent associations with early adoption. Furthermore, age and political ideology were significant moderators of complexity and relative advantage, respectfully. Health education strategies for early vaccine uptake should focus on building trust in vaccine safety, increasing short-term benefits of vaccination and promoting relatability to personal values.

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Purpose: Because older adults are at elevated risk of COVID-19-related adverse health outcomes, and staying at home is an effective strategy to avoid unnecessary exposures, the current formative study used the Reasoned Action Approach (RAA) to identify the beliefs underlying older adults' decision to stay home for the next month. Methods: The participants (weighted n = 206, age 65-94) for the current study were selected from a nationally representative online survey of US adults from April 10-20, 2020. We used multiple linear regression to estimate the relative contribution of the four RAA global constructs (instrumental attitude, injunctive norms, descriptive norms, and self-efficacy) in explaining intention to stay home after controlling for demographic covariates. We also conducted a content analysis to identify beliefs about advantages, disadvantages, and facilitators of staying home. Results: After controlling for demographic characteristics, injunctive norms (b = 0.208; SE = 0.059; B = 0.213, p < 0.01) and self-efficacy (b = 0.532; SE = 0.058; B = 0.537, p < 0.001) showed statistically significant independent associations with intention to stay home. The specific beliefs underlying the decision to stay home spanned across health and wellness dimensions and suggested interpersonal, mental health, and leisure/recreational facilitators. Conclusions: These findings suggest three public health intervention targets. First, self-efficacy building interventions could enhance older adults' perceptions of their ability to stay home to avoid unnecessary exposures. Second, health communication messages to address injunctive norms could emphasize that people important to older adults think they should stay home. Third, for the youngest of the older adults, health communication messages could emphasize the advantages of staying home.

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