Situations and roles of cannabis versus cigarette use: Integrating ecological momentary assessment with qualitative mapping interviews.

Use of both cannabis and tobacco has surpassed use of tobacco alone among young adults in California. To better understand why, we collected data with 32 young adults ages 18-30 in Northern California who regularly used cigarettes and cannabis and had diverse sexual, gender, racial, and ethnic identities. Geographically-explicit ecological momentary assessment (EMA; 30 days) was integrated with qualitative mapping interviews. We found contrasting situations of use for cannabis (e.g., around other people) versus cigarettes (e.g., recent discrimination) and different reasons for why participants chose one substance over the other (e.g., enhancing experiences vs. stepping away). Understanding when and why diverse young adults choose cannabis versus cigarettes as they navigate everyday environments helps explain how cannabis and tobacco retail markets shape substance use disparities over time.

The Reddit cannabis subjective highness rating scale: Applying computational social science to explore psychological and environmental correlates of naturalistic cannabis use.

Social media data provide unprecedented access to discussions of active, naturalistic, and often real-time cannabis use in an era of cannabis policy liberalization. The aim of this study was to explore psychological and environmental correlates of cannabis effects by applying computational social science approaches to a large dataset of unprompted reports of naturalistic cannabis use with corresponding self-reported numerical ratings of subjective highness. Post title text was extracted via the Pushshift dataset from N = 328,865 posts to the r/trees Reddit community, where posters self-assess and disclose how high they feel on a scale from 1 to 10 (M = 6.9, SD = 1.8). Structural topic modelling and Linguistic Inquiry and Word Count (LIWC) dictionary-based approaches were applied to identify (1) frequently discussed topics and (2) text indicative of 5 psychological processes (affective, social, cognitive, perceptual, biological), respectively, as well as to examine relationships between subjective highness and (1) topic prevalence and (2) psychological process word counts. A 40-topic model was selected for interpretation based on semantic coherence and exclusivity. The most discussed topics in a 40-topic model were characterized by references to smoking places, social contexts, positive affect, cognitive states, as well as food and media consumed. In LIWC dictionary analyses, words mentioning affective, social, and cognitive processes were referenced more often than perceptual or body processes. Posters reported greater subjective highness when using language that referred to in-person social environments and lower subjective highness when using language that referred to online social environments and positive affect psychological states. This examination of unprompted online reports of naturalistic cannabis use identified textual content referring to affect and to other people as being associated with perceived effects of cannabis. These affective and social aspects of the cannabis use experience were salient to active posters in this online community and should be integrated into experience sampling methods and behavioral pharmacology research, as well as public health messaging.

Quantifying cigarette and e-cigarette marketing exposure among Chinese adolescents using ecological momentary assessment.

INTRODUCTION: Addressing cigarette and e-cigarette use in China is key to reducing the global tobacco epidemic. Marketing exposure is one causal factor for adolescent smoking and e-cigarette use. Currently, China restricts cigarette and e-cigarette ads in public places and online; however, there may not be full policy compliance. We collected real-time data in the natural environment to estimate how much and where Chinese adolescents - a group susceptible to smoking and e-cigarette use - are exposed to cigarette and e-cigarette marketing to inform policy responses. METHODS: In June 2022, we conducted a seven-day ecological momentary assessment (EMA) study with 15-16-year-olds (n=96) across eight Chinese cities. Participants completed up to 42 EMA surveys (6 per day), sent at random intervals outside of school hours. In each survey, participants reported whether they saw (1) displays and (2) ads in the past hour (none, cigarette, e-cigarette, both) in the past hour. We also captured the source of cigarette/e-cigarette ad exposure. RESULTS: Most participants were exposed to cigarette and/or e-cigarette displays (89.6%) or ads (79.2%) over the seven days. On average, participants reported past-hour exposure to displays 12.7 times and past-hour exposure to ads 10.8 times over the week. The most common sources of cigarette ads were public places (e.g., kiosks, supermarkets); the most common sources of e-cigarette ad exposure were social media/internet or e-cigarette stores. CONCLUSIONS: Findings highlight the need to enhance enforcement of restrictions on cigarette and e-cigarette ads in public places and online in China and extend restrictions to ban displays. IMPLICATIONS: Marketing exposure is a causal factor in youth smoking and e-cigarette use. We used ecological momentary assessments to estimate cigarette and e-cigarette display and ad exposure among Chinese adolescents. On average, participants reported past-hour exposure to cigarette and/or e-cigarette displays 13 times and past-hour exposure to cigarette and/or e-cigarette ads 11 times over one week. Most saw ads in public places and online. Results suggest strengthening implementation of China's ban on cigarette and e-cigarette ads in public places and online and banning product displays. These are policy responses that can contribute to reducing adolescent cigarette and e-cigarette uptake in China.

Quantity of cigarettes smoked when co-used with alcohol and cannabis: Consideration of different definitions of co-use based on daily diary data.

INTRODUCTION: Cigarettes are frequently co-used with alcohol and cannabis. However, definitions of co-use vary and the extent to which cigarette use changes on days with different patterns of co-use is unclear. We compared the number of cigarettes smoked on different days based on co-use patterns of cigarettes and alcohol or cannabis. METHODS: This study analyzed 2408 smoking days collected in a 30-day smartphone-based daily diary study among 146 young adults (aged 18-26) with an oversample from sexual minority groups. Two separate multilevel models were estimated: one for cigarette and alcohol co-use and the other for cigarette and cannabis co-use. Both models examined day-level associations between the number of cigarettes smoked and 3 different types of days (smoking-only days, same-occasion co-use days, different-occasion co-use days), controlling for demographic characteristics. RESULTS: More cigarettes were smoked on same-occasion co-use days compared to cigarette-smoking-only days for both alcohol (b=1.474, SE=0.136, t=10.8, p<.001) and cannabis (b=0.822, SE=0.209, t=3.9, p<.001). There were no significant differences in cigarettes smoked on days with co-use on the same day, but on different occasions, compared to days with smoking only. CONCLUSIONS: Compared to days with cigarette smoking only, more cigarettes are smoked on days when cigarettes are co-used with alcohol or cannabis on the same occasion, while the same is not true for days with co-use on different occasions. Conflating different definitions of co-use may impact findings on associations between co-use and smoking behavior.

Do Smartphone Apps Impact Long-Term Smoking Cessation for Sexual and Gender Minority Adults? Exploratory Results from a 2-Arm Randomized Trial Comparing Acceptance and Commitment Therapy with Standard US Clinical Practice Guidelines.

Sexual and gender minority (SGM) adults face unique challenges in accessing smoking cessation care due to stigma tied to their identities and smoking. While cessation apps show promise in the general population, their efficacy for SGM adults is unclear. This study utilized data from a randomized trial to compare two cessation apps, iCanQuit (Acceptance and Commitment Therapy-based) and QuitGuide (US Clinical Practice Guidelines-based) among 403 SGM adults. The primary outcome was self-reported complete-case 30-day abstinence from cigarette smoking at 12 months. Mediation analyses explored whether interventions operated through acceptance of cues to smoke and app engagement. At 12 months, quit rates did not differ between arms (26% iCanQuit vs. 22% QuitGuide, OR = 1.22; 95% CI: 0.74 to 2.00, p = .43). iCanQuit positively impacted cessation via acceptance of cues to smoke (indirect effect = 0.23; 95% CI: 0.06 to 0.50, p < .001) and demonstrated higher engagement (no. logins, 28.4 vs. 12.1; p < .001) and satisfaction (91% vs. 75%, OR = 4.18; 95% CI: 2.12 to 8.25, p < .001) than QuitGuide. Although quit rates did not differ between arms, acceptance of cues to smoke seemed to play a crucial role in helping SGM adults quit smoking. Future interventions should consider promoting acceptance of cues to smoke in this population.

Designing and Validating a Novel Method for Assessing Delay Discounting Associated With Health Behaviors: Ecological Momentary Assessment Study.

BACKGROUND: Delay discounting quantifies an individual's preference for smaller, short-term rewards over larger, long-term rewards and represents a transdiagnostic factor associated with numerous adverse health outcomes. Rather than a fixed trait, delay discounting may vary over time and place, influenced by individual and contextual factors. Continuous, real-time measurement could inform adaptive interventions for various health conditions. OBJECTIVE: The goals of this paper are 2-fold. First, we present and validate a novel, short, ecological momentary assessment (EMA)-based delay discounting scale we developed. Second, we assess this tool's ability to reproduce known associations between delay discounting and health behaviors (ie, substance use and craving) using a convenience-based sample. METHODS: Participants (N=97) were adults (age range 18-71 years), recruited on social media. In phase 1, data were collected on participant sociodemographic characteristics, and delay discounting was evaluated via the traditional Monetary Choice Questionnaire (MCQ) and our novel method (ie, 7-item time-selection and 7-item monetary-selection scales). During phase 2 (approximately 6 months later), participants completed the MCQ, our novel delay discounting measures, and health outcomes questions. The correlations between our method and the traditional MCQ within and across phases were examined. For scale reduction, a random number of items were iteratively selected, and the correlation between the full and random scales was assessed. We then examined the association between our time- and monetary-selection scales assessed during phase 2 and the percentage of assessments that participants endorsed using or craving alcohol, tobacco, or cannabis. RESULTS: In total, 6 of the 7 individual time-selection items were highly correlated with the full scale (r>0.89). Both time-selection (r=0.71; P<.001) and monetary-selection (r=0.66; P<.001) delay discounting rates had high test-retest reliability across phases 1 and 2. Phase 1 MCQ delay discounting function highly correlated with phase 1 (r=0.76; P<.001) and phase 2 (r=0.45; P<.001) time-selection delay discounting scales. One or more randomly chosen time-selection items were highly correlated with the full scale (r>0.94). Greater delay discounting measured via the time-selection measure (adjusted mean difference=5.89, 95% CI 1.99-9.79), but not the monetary-selection scale (adjusted mean difference=-0.62, 95% CI -3.57 to 2.32), was associated with more past-hour tobacco use endorsement in follow-up surveys. CONCLUSIONS: This study evaluated a novel EMA-based scale's ability to validly and reliably assess delay discounting. By measuring delay discounting with fewer items and in situ via EMA in natural environments, researchers may be better able to identify individuals at risk for poor health outcomes.

A Cross-Sectional Survey on Oral Nicotine Pouches: Characterizing Use-Motives, Topography, Dependence Levels, and Adverse Events.

INTRODUCTION: Oral nicotine pouches (ONPs) contain a crystalized nicotine powder instead of tobacco leaves. ONPs come in a variety of flavors and are often marketed as "tobacco-free," but research on ONP use-motivations and related experiences is limited. AIMS AND METHODS: This cross-sectional web-based survey collected self-report data on ONP use-characteristics (eg, frequency), brands and flavors used, use-motivations, dependence (Fagerström Test for Nicotine Dependence-Smokeless Tobacco [FTND-ST]), and ONP-related adverse events (AEs) experienced. RESULTS: The sample included 118 adults who reported current (past 30-day) ONP use. On average (SD), participants reported ONP use on 13 (6) days during the past month. Most participants (% of the sample) also reported the use of tobacco cigarettes (74%) and/or electronic cigarettes (53%) during the past month. Zyn (27%) and Lucy (19%) were the most currently used ONP brands with mint (23%) and tobacco (16%) as the most currently used flavors. The availability of preferred flavors was the most frequently reported (31%) ONP use-motivation. The sample demonstrated significant dependence levels (FTND-ST = 7, SD = 2). Reported AEs included mouth lesions (48%), upset stomach (39%), sore mouth (37%), sore throat (21%), and nausea (9%). Results should be interpreted in the context of study limitations, including using a relatively small and homogeneous online convenience sample. Acknowledging the limitations, this sample was deemed appropriate to include considering the novelty of the findings, the dearth of related research, and the necessity of examining foundational ONP use-characteristics (eg, topography, AEs); however, future research should consider recruiting larger and more generalizable samples. CONCLUSIONS: The availability of preferred flavors was a key ONP use-motivation in this sample. Mint and tobacco were the most currently used flavors, with Zyn and Lucy being the most currently used ONP brands. Participants reported dependence and a substantial number of ONP-related AEs. Nationally representative surveys should investigate ONP use along with outcomes included in the current study (eg, AEs) to inform ONP surveillance and policy development efforts. IMPLICATIONS: This study is among the first to assess reasons for initiating/maintaining ONP use as well as other relevant use-experiences (eg, AEs, dependence). These results highlight the role of flavors and nicotine dependence in ONP use, which are important considerations for informing ONP regulations.

Temporal associations linking alcohol and cannabis use to cigarette smoking in young adults engaged in a tobacco cessation and relapse monitoring study.

Young adulthood remains a developmental period in which cigarette smoking initiation and progression to dependence and regular use is common. Moreover, co-use of alcohol and/or cannabis with tobacco is common in this age group and may have detrimental effects on tobacco use rates and cessation outcomes. Although young adults are interested in quitting smoking, achieving abstinence remains difficult, even with evidence-based treatment strategies. Understanding proximal associations between other substance use (e.g., alcohol and cannabis) and smoking may have important treatment implications. This exploratory analysis investigated the role of alcohol and/or cannabis use in contributing to smoking events on the same day or next day among young adults engaged in a smoking cessation and relapse monitoring study. We used ecological momentary assessment (EMA) data from 43 young adults (ages 18-25; 932 observations) who smoked cigarettes daily and agreed to participate in a 5-week study that included a 2-day smoking quit attempt and provision of tobacco treatment in the form of nicotine replacement therapy, brief cessation counseling, and financial incentives for abstinence (incentives were provided only during the 2-day quit attempt). We tested multilevel time-series models of daily associations between alcohol use, cannabis use, and smoking. Consistent with hypotheses, days on which participants were more likely to drink alcohol predicted increased likelihood of smoking the next day (OR = 2.27, p =.003). This effect was significant after controlling for both the one-day lagged effect of smoking (i.e., autoregression) and the concurrent (i.e., same day) effects of drinking and cannabis use. Although there was a positive concurrent effect of cannabis use on smoking (OR = 12.86, p =.003), the one-day lagged effect of cannabis use and the concurrent effect of drinking was not significant, contrary to hypotheses. Results indicate that alcohol use presents a potential threat to successful smoking cessation that extends to the following day. This suggests a risk-window in which treatment could be supplemented with just-in-time interventions and extending the focus on co-use to include this lagged impact on cessation outcomes.

Developing a Game (Inner Dragon) Within a Leading Smartphone App for Smoking Cessation: Design and Feasibility Evaluation Study.

BACKGROUND: Several stand-alone smartphone apps have used serious games to provide an engaging approach to quitting smoking. So far, the uptake of these games has been modest, and the evidence base for their efficacy in promoting smoking cessation is still evolving. The feasibility of integrating a game into a popular smoking cessation app is unclear. OBJECTIVE: The aim of this paper was to describe the design and iterative development of the Inner Dragon game within Smoke Free, a smartphone app with proven efficacy, and the results of a single-arm feasibility trial as part of a broad program that seeks to assess the effectiveness of the gamified app for smoking cessation. METHODS: In phase 1, the study team undertook a multistep process to design and develop the game, including web-based focus group discussions with end users (n=15). In phase 2, a single-arm study of Smoke Free users who were trying to quit (n=30) was conducted to assess the feasibility and acceptability of the integrated game and to establish the feasibility of the planned procedures for a randomized pilot trial. RESULTS: Phase 1 led to the final design of Inner Dragon, informed by principles from psychology and behavioral economics and incorporating several game mechanics designed to increase user engagement and retention. Inner Dragon users maintain an evolving pet dragon that serves as a virtual avatar for the users' progress in quitting. The phase-2 study established the feasibility of the study methods. The mean number of app sessions completed per user was 13.8 (SD 13.1; median 8; range 1-46), with a mean duration per session of 5.8 (median 1.1; range 0-81.1) minutes. Overall, three-fourths (18/24, 75%) of the participants entered the Inner Dragon game at least once and had a mean of 2.4 (SD 2.4) sessions of game use. The use of Inner Dragon was positively associated with the total number of app sessions (correlation 0.57). The mean satisfaction score of participants who provided ratings (11/24, 46%) was 4.2 (SD 0.6) on a 5-point scale; however, satisfaction ratings for Inner Dragon were only completed by 13% (3/24) of the participants. CONCLUSIONS: Findings supported further development and evaluation of Inner Dragon as a beneficial feature of Smoke Free. The next step of this study is to conduct a randomized pilot trial to determine whether the gamified version of the app increases user engagement over a standard version of the app.

Review of strategies to investigate low sample return rates in remote tobacco trials: A call to action for more user-centered design research.

Remote collection of biomarkers of tobacco use in clinical trials poses significant challenges. A recent meta-analysis and scoping review of the smoking cessation literature indicated that sample return rates are low and that new methods are needed to investigate the underlying causes of these low rates. In this paper we conducted a narrative review and heuristic analysis of the different human factors approaches reported to evaluate and/or improve sample return rates among 31 smoking cessation studies recently identified in the literature. We created a heuristic metric (with scores from 0 to 4) to evaluate the level of elaboration or complexity of the user-centered design strategy reported by researchers. Our review of the literature identified five types of challenges typically encountered by researchers (in that order): usability and procedural, technical (device related), sample contamination (e.g., polytobacco), psychosocial factors (e.g., digital divide), and motivational factors. Our review of strategies indicated that 35% of the studies employed user-centered design methods with the remaining studies relying on informal methods. Among the studies that employed user-centered design methods, only 6% reached a level of 3 in our user-centered design heuristic metric. None of the studies reached the highest level of complexity (i.e., 4). This review examined these findings in the context of the larger literature, discussed the need to address the role of health equity factors more directly, and concluded with a call to action to increase the application and reporting of user-centered design strategies in biomarkers research.

Using Smartphone Survey and GPS Data to Inform Smoking Cessation Intervention Delivery: Case Study.

BACKGROUND: Interest in quitting smoking is common among young adults who smoke, but it can prove challenging. Although evidence-based smoking cessation interventions exist and are effective, a lack of access to these interventions specifically designed for young adults remains a major barrier for this population to successfully quit smoking. Therefore, researchers have begun to develop modern, smartphone-based interventions to deliver smoking cessation messages at the appropriate place and time for an individual. A promising approach is the delivery of interventions using geofences-spatial buffers around high-risk locations for smoking that trigger intervention messages when an individual's phone enters the perimeter. Despite growth in personalized and ubiquitous smoking cessation interventions, few studies have incorporated spatial methods to optimize intervention delivery using place and time information. OBJECTIVE: This study demonstrates an exploratory method of generating person-specific geofences around high-risk areas for smoking by presenting 4 case studies using a combination of self-reported smartphone-based surveys and passively tracked location data. The study also examines which geofence construction method could inform a subsequent study design that will automate the process of deploying coping messages when young adults enter geofence boundaries. METHODS: Data came from an ecological momentary assessment study with young adult smokers conducted from 2016 to 2017 in the San Francisco Bay area. Participants reported smoking and nonsmoking events through a smartphone app for 30 days, and GPS data was recorded by the app. We sampled 4 cases along ecological momentary assessment compliance quartiles and constructed person-specific geofences around locations with self-reported smoking events for each 3-hour time interval using zones with normalized mean kernel density estimates exceeding 0.7. We assessed the percentage of smoking events captured within geofences constructed for 3 types of zones (census blocks, 500 ft2 fishnet grids, and 1000 ft2 fishnet grids). Descriptive comparisons were made across the 4 cases to better understand the strengths and limitations of each geofence construction method. RESULTS: The number of reported past 30-day smoking events ranged from 12 to 177 for the 4 cases. Each 3-hour geofence for 3 of the 4 cases captured over 50% of smoking events. The 1000 ft2 fishnet grid captured the highest percentage of smoking events compared to census blocks across the 4 cases. Across 3-hour periods except for 3:00 AM-5:59 AM for 1 case, geofences contained an average of 36.4%-100% of smoking events. Findings showed that fishnet grid geofences may capture more smoking events compared to census blocks. CONCLUSIONS: Our findings suggest that this geofence construction method can identify high-risk smoking situations by time and place and has potential for generating individually tailored geofences for smoking cessation intervention delivery. In a subsequent smartphone-based smoking cessation intervention study, we plan to use fishnet grid geofences to inform the delivery of intervention messages.

Effectiveness of Peer-Support Interventions for Smoking Cessation: A Systematic Review and Meta-analysis.

INTRODUCTION: Peer support has been recommended to promote smoking cessation, but results from prior meta-analyses have not established its efficacy. We conducted a systematic review and meta-analysis to assess current evidence and identify potential modifiers of efficacy. METHODS: Randomized controlled trials of peer-support interventions with a smoking cessation outcome were identified in January 2022 from PubMed and references listed in identified studies. The meta-analysis outcome measure was mean risk ratio (RR, 95% confidence interval [CI]) for abstinence at the longest follow-up timepoint between 3 and 9 months from baseline. Potential modifiers tested were peer smoking status (former, current, or unknown), follow-up timepoint, abstinence measure, and cumulative engagement time between peers and smokers ("dose"). Studies were assessed for risk of bias and certainty of evidence. RESULTS: We identified 16 trials, which varied in abstinence effect size (RR 0.61-3.07), sample size (23-2121), dose (41-207 minutes), and follow-up timepoint (<1-15 months). Across 15 trials with follow-up between 3 and 9 months (N = 8573 participants; 4565 intervention, 4008 control), the pooled Mantel-Haenszel RR was 1.34 (95% CI: 1.11-1.62). Effect sizes were greatest among interventions with formerly smoking peers (RR 1.43, 95% CI 1.17-1.74; five trials). We found positive effects for follow-up timepoints ≥3 months but no effect of intervention dose. The overall quality of evidence was deemed "very low." CONCLUSIONS: Peer-support interventions increased smoking abstinence. There remains a lack of consensus about how to define a peer. Intervention features such as peer smoking status appear to have explanatory power. Additional high-quality and more comparable trials are needed. IMPLICATIONS: This study reviewed the latest evidence from randomized controlled trials and found that peer-support interventions enhance smoking cessation. Efficacy varies with key intervention features such as peer smoking status and follow-up timepoint, which may be used to facilitate development of more effective peer-support interventions. Future trials and reviews would benefit from careful consideration and clear reporting of peer smoking status, length of follow-up, abstinence measures, and intervention dose.

Longitudinal associations between age 20 problematic substance use and opioid use disorder incidence at age 30 - findings from an urban cohort.

This study used data from a longitudinal prevention study in an urban cohort to examine associations between nicotine dependence, alcohol, and cannabis use disorder and disorder criteria at age 20, with opioid use disorder (OUD) incidence or criteria onset by age 30. The study sample included 1408 participants (57.5% female, 72.5% African American) drawn from two cohorts of participants in a mid-Atlantic region of the U.S. as part of a series of randomized controlled trials of elementary school-based universal prevention interventions. Lifetime cannabis use disorder (CUD), alcohol use disorder (AUD; both DSM-IV), and current nicotine dependence (Fagerstrom Test for Nicotine Dependence, FTND) assessed at age 20 were used to predict (1) DSM-IV lifetime OUD at age 30, and (2) OUD criteria between ages 20 and 30 in multivariable logistic regression models. Covariates for all analyses included sociodemographics (sex, race, and free/reduced-priced lunch status), community disadvantage, and intervention status. Nicotine dependence (FTND≥3) at age 20 predicted age 30 DSM-IV lifetime OUD (aOR = 2.37; 95% CI 1.02,5.54). The number of CUD criteria (aOR = 1.30; 95% CI 1.09,1.57) and nicotine dependence severity scores (aOR = 1.22; 95% CI = 1.05,1.41) at age 20 predicted any OUD criteria between the ages of 20 and 30. Findings are consistent with previous research on opioid use behavior in young adulthood and suggest that nicotine dependence and CUD criteria among urban young people predict onset of OUD and OUD criteria in young adulthood.

Associations Between Product Type and Intensity of Tobacco and Cannabis Co-use on the Same Day Among Young Adult Smokers: Smartphone-Based Daily-Diary Study.

BACKGROUND: Co-use of tobacco and cannabis is highly prevalent among young US adults. Same-day co-use of tobacco and cannabis (ie, use of both substances on the same day) may increase the extent of use and negative health consequences among young adults. However, much remains unknown about same-day co-use of tobacco and cannabis, in part due to challenges in measuring this complex behavior. Nuanced understanding of tobacco and cannabis co-use in terms of specific products and intensity (ie, quantity of tobacco and cannabis use within a day) is critical to inform prevention and intervention efforts. OBJECTIVE: We used a daily-diary data collection method via smartphone to capture occurrence of tobacco and cannabis co-use within a day. We examined (1) whether the same route of administration would facilitate co-use of 2 substances on the same day and (2) whether participants would use more tobacco on a day when they use more cannabis. METHODS: This smartphone-based study collected 2891 daily assessments from 147 cigarette smokers (aged 18-26 years, n=76, 51.7% female) during 30 consecutive days. Daily assessments measured type (ie, cigarette, cigarillo, or e-cigarette) and intensity (ie, number of cigarettes or cigarillos smoked or number of times vaping e-cigarettes per day) of tobacco use and type (ie, combustible, vaporized, or edible) and intensity (ie, number of times used per day) of cannabis use. We estimated multilevel models to examine day-level associations between types of cannabis use and each type of tobacco use, as well as day-level associations between intensities of using cannabis and tobacco. All models controlled for demographic covariates, day-level alcohol use, and time effects (ie, study day and weekend vs weekday). RESULTS: Same-day co-use was reported in 989 of the total 2891 daily assessments (34.2%). Co-use of cigarettes and combustible cannabis (885 of the 2891 daily assessments; 30.6%) was most commonly reported. Participants had higher odds of using cigarettes (adjusted odds ratio [AOR] 1.92, 95% CI 1.31-2.81) and cigarillos (AOR 244.29, 95% CI 35.51-1680.62) on days when they used combustible cannabis. Notably, participants had higher odds of using e-cigarettes on days when they used vaporized cannabis (AOR 23.21, 95% CI 8.66-62.24). Participants reported a greater intensity of using cigarettes (AOR 1.35, 95% CI 1.23-1.48), cigarillos (AOR 2.04, 95% CI 1.70-2.46), and e-cigarettes (AOR 1.48, 95% CI 1.16-1.88) on days when they used more cannabis. CONCLUSIONS: Types and intensities of tobacco and cannabis use within a day among young adult smokers were positively correlated, including co-use of vaporized products. Prevention and intervention efforts should address co-use and pay attention to all forms of use and timeframes of co-use (eg, within a day or at the same time), including co-use of e-cigarettes and vaporized cannabis, to reduce negative health outcomes.

Association between pain and e-cigarette use stratified by cigarette smoking status: Results from National Health Interview Survey (NHIS) 2019-2020.

INTRODUCTION: Previous studies have shown frequent co-morbidities between pain and tobacco use. However, the investigation in use of e-cigarettes, a relatively new tobacco product, at the intersection of pain and cigarette smoking is still lacking. This study used a US national dataset to examine associations between pain experience (pain lasting 3 months) and e-cigarette use, stratified by cigarette smoking status. METHODS: This study used a pooled dataset of the 2019 and 2020 National Health Interview Survey (NHIS) (N = 63,565). We estimated multivariable binomial logistic regressions predicting current e-cigarette use by pain experience, after controlling for survey year, age, sex, race/ethnicity, sexual orientation, education level, health insurance status, other tobacco use, diagnosis of anxiety and depression, use of pain management methods (e.g., physical therapy, behavioral therapy), and prescribed opioid pain reliever use among the overall population, and stratified by cigarette smoking status - never, former, and current cigarette smoking. RESULTS: After controlling for covariates, past-3-month pain experience was associated with current e-cigarette use (aOR = 1.26; 95 % CI = 1.08, 1.46) in the overall population. When stratified by current cigarette smoking, pain experience was associated with current e-cigarette use among current combustible cigarette smokers (aOR = 1.62, 95 % CI = 1.20, 2.18). However, there was no significant difference in e-cigarette use by pain experience among non-current cigarette smokers (p = 0.103). CONCLUSIONS: We observed a higher likelihood of e-cigarette use among US adults experiencing pain. Future studies are needed to investigate mechanisms linking pain and e-cigarette use to inform smoking/vaping prevention and cessation interventions.

A Scoping Review and Meta-analysis of the Use of Remote Biochemical Verification Methods of Smoking Status in Tobacco Research.

INTRODUCTION: Increasing digital delivery of smoking cessation interventions has resulted in the need to employ novel strategies for remote biochemical verification. AIMS AND METHODS: This scoping review and meta-analysis aimed to investigate best practices for remote biochemical verification of smoking status. The scientific literature was searched for studies that reported remotely obtained (not in-person) biochemical confirmation of smoking status (ie, combustible tobacco). A meta-analysis of proportions was conducted to investigate key outcomes, which included rates of returned biological samples and the ratio of biochemically verified to self-reported abstinence rates. RESULTS: A total of 82 studies were included. The most common samples were expired air (46%) and saliva (40% of studies), the most common biomarkers were carbon monoxide (48%) and cotinine (44%), and the most common verification methods were video confirmation (37%) and mail-in samples for lab analysis (26%). Mean sample return rates determined by random-effects meta-analysis were 70% for smoking cessation intervention studies without contingency management (CM), 77% for CM studies, and 65% for other studies (eg, feasibility and secondary analyses). Among smoking cessation intervention studies without CM, self-reported abstinence rates were 21%, biochemically verified abstinence rates were 10%, and 47% of individuals who self-reported abstinence were also biochemically confirmed as abstinent. CONCLUSIONS: This scoping review suggests that improvements in sample return rates in remote biochemical verification studies of smoking status are needed. Recommendations for reporting standards are provided that may enhance confidence in the validity of reported abstinence rates in remote studies. IMPLICATIONS: This scoping review and meta-analysis included studies using remote biochemical verification to determine smoking status. Challenges exist regarding implementation and ensuring high sample return rates. Higher self-reported compared to biochemically verified abstinence rates suggest the possibility that participants in remote studies may be misreporting abstinence or not returning samples for other reasons (eg, participant burden, inconvenience). Remote biochemical confirmation of self-reported smoking abstinence should be included in smoking cessation studies whenever feasible. However, findings should be considered in the context of challenges to sample return rates. Better reporting guidelines for future studies in this area are needed.

Contextualizing Engagement With Health Information on Facebook: Using the Social Media Content and Context Elicitation Method.

BACKGROUND: Most of what is known regarding health information engagement on social media stems from quantitative methodologies. Public health literature often quantifies engagement by measuring likes, comments, and/or shares of posts within health organizations' Facebook pages. However, this content may not represent the health information (and misinformation) generally available to and consumed by platform users. Furthermore, some individuals may prefer to engage with information without leaving quantifiable digital traces. Mixed methods approaches may provide a way of surpassing the constraints of assessing engagement with health information by using only currently available social media metrics. OBJECTIVE: This study aims to discuss the limitations of current approaches in assessing health information engagement on Facebook and presents the social media content and context elicitation method, a qualitatively driven, mixed methods approach to understanding engagement with health information and how engagement may lead to subsequent actions. METHODS: Data collection, management, and analysis using the social media content and context elicitation method are presented. This method was developed for a broader study exploring how and why US Latinos and Latinas engage with cancer prevention and screening information on Facebook. The study included 20 participants aged between 40 and 75 years without cancer who participated in semistructured, in-depth interviews to discuss their Facebook use and engagement with cancer information on the platform. Participants accessed their Facebook account alongside the researcher, typed cancer in the search bar, and discussed cancer-related posts they engaged with during the previous 12 months. Engagement was defined as liking, commenting, and/or sharing a post; clicking on a post link; reading an article in a post; and/or watching a video within a post. Content engagement prompted questions regarding the reasons for engagement and whether engagement triggered further action. Data were managed using MAXQDA (VERBI GmbH) and analyzed using thematic and content analyses. RESULTS: Data emerging from the social media content and context elicitation method demonstrated that participants mainly engaged with cancer prevention and screening information by viewing and/or reading content (48/66, 73%) without liking, commenting, or sharing it. This method provided rich content regarding how US Latinos and Latinas engage with and act upon cancer prevention and screening information on Facebook. We present 2 emblematic cases from the main study to exemplify the additional information and context elicited from this methodology, which is currently lacking from quantitative approaches. CONCLUSIONS: The social media content and context elicitation method allows a better representation and deeper contextualization of how people engage with and act upon health information and misinformation encountered on social media. This method may be applied to future studies regarding how to best communicate health information on social media, including how these affect assessments of message credibility and accuracy, which can influence health outcomes.

"I got a bunch of weed to help me through the withdrawals": Naturalistic cannabis use reported in online opioid and opioid recovery community discussion forums.

A growing body of research has reported on the potential opioid-sparing effects of cannabis and cannabinoids, but less is known about specific mechanisms. The present research examines cannabis-related posts in two large online communities on the Reddit platform ("subreddits") to compare mentions of naturalistic cannabis use by persons self-identifying as actively using opioids versus persons in recovery. We extracted all posts mentioning cannabis-related keywords (e.g., "weed", "cannabis", "marijuana") from December 2015 through August 2019 from an opioid use subreddit and an opioid recovery subreddit. To investigate how cannabis is discussed at-scale, we identified and compared the most frequent phrases in cannabis-related posts in each subreddit using term-frequency-inverse document frequency (TF-IDF) weighting. To contextualize these findings, we also conducted a qualitative content analysis of 200 random posts (100 from each subreddit). Cannabis-related posts were about twice as prevalent in the recovery subreddit (n = 908; 5.4% of 16,791 posts) than in the active opioid use subreddit (n = 4,224; 2.6% of 159,994 posts, p < .001). The most frequent phrases from the recovery subreddit referred to time without using opioids and the possibility of using cannabis as a "treatment." The most frequent phrases from the opioid subreddit referred to concurrent use of cannabis and opioids. The most common motivations for using cannabis were to manage opioid withdrawal symptoms in the recovery subreddit, often in conjunction with anti-anxiety and GI-distress "comfort meds," and to enhance the "high" when used in combination with opioids in the opioid subreddit. Despite limitations in generalizability from pseudonymous online posts, this examination of reports of naturalistic cannabis use in relation to opioid use identified withdrawal symptom management as a common motivation. Future research is warranted with more structured assessments that examines the role of cannabis and cannabinoids in addressing both somatic and affective symptoms of opioid withdrawal.

Reappraising Choice in Addiction: Novel Conceptualizations and Treatments for Tobacco Use Disorder.

The introduction of alternative nicotine and tobacco products (such as e-cigarettes, heat-not-burn devices, nicotine pouches) warrants an updated framework from which to conceptualize tobacco use disorder (TUD). The following review provides considerations for TUD within the context of novel products. Historically, the tobacco industry falsely claimed that cigarettes were not addictive or harmful and that those who smoked simply chose to do so. This generated an inaccurate lay perception that smoking is a free or informed choice. Research on nicotine pharmacology demonstrates the powerful addictive potential of nicotine, which is shaped by dose, speed of delivery, and other constituents generated. In addition, non-pharmacologic reinforcers motivate and maintain tobacco use behaviors for both traditional cigarettes and novel products. The negative consequences of combustible tobacco use are well known; however, these outcomes may differ for alternative products. Strategies used for combustible product cessation may be adapted for novel products, and treatment recommendations for TUD should be made within the context of a harm reduction framework wherein alternative product use may be the desired outcome. Providers must therefore be willing to modify their perceptions of products and treatment recommendations accordingly. Better public health outcomes are accomplished through promotion of abstinence from combustible smoking. For those who cannot wean from nicotine entirely, switching to less risky modes of delivery might be a secondary goal, with an eventual aim of stopping use of the alternative product. Implications: Given the advent of novel, alternative tobacco products, tobacco use disorder (TUD) must be conceptualized within a contemporary framework that includes harm reduction and alternative outcomes. The unique contributions of nicotine pharmacology, non-pharmacologic reinforcers, and consequences of use can be used to inform treatments for TUD with the ultimate goal of improving the health of individuals who use tobacco.