Agalactosyl IgG induces liver fibrogenesis via Fc gamma receptor 3a on human hepatic stellate cells.

The relevance of aberrant serum IgG N-glycosylation in liver fibrosis has been identified; however, its causal effect remains unclear. Because hepatic stellate cells (HSCs) contribute substantially to liver fibrosis, we investigated whether and through which mechanisms IgG N-glycosylation affects the fibrogenic properties of HSCs. Analysis of serum IgG1 N-glycome from 151 patients with chronic hepatitis B or liver cirrhosis revealed a positive correlation between Ishak fibrosis grading and IgG1 with agalactosyl N-glycoforms on the crystallizable fragment (Fc). Fc gamma receptor (FcγR) IIIa was observed in cultured human HSCs and HSCs in human liver tissues, and levels of FcγRIIIa in HSCs correlated with the severity of liver fibrosis. Additionally, agalactosyl IgG treatment caused HSCs to have a fibroblast-like morphology, enhanced migration and invasion capabilities, and enhanced expression of the FcγRIIIa downstream tyrosine-protein kinase SYK. Furthermore, agalactosyl IgG treatment increased fibrogenic factors in HSCs, including transforming growth factor (TGF)-ß1, total collagen, platelet-derived growth factor subunit B and its receptors, pro-collagen I-α1, α-smooth muscle actin, and matrix metalloproteinase 9. These effects were more pronounced in HSCs that stably expressed FCGR3A and were reduced in FCGR3A knockout cells. Agalactosyl IgG and TGF-ß1 each increased FCGR3A in HSCs. Furthermore, serum TGF-ß1 concentrations in patients were positively correlated with agalactosyl IgG1 levels and liver fibrosis severity, indicating a positive feedback loop involving agalactosyl IgG, HSC-FcγRIIIa, and TGF-ß1. In conclusion, agalactosyl IgG promotes fibrogenic characteristics in HSCs through FcγRIIIa. © 2024 The Pathological Society of Great Britain and Ireland.

Exposure to user-generated e-cigarette content on social media associated with greater vulnerability to e-cigarette use among youth non-users.

INTRODUCTION: Social media are important venues for youth's exposure to e-cigarette content. This study examined how exposure to user-generated e-cigarette content (i.e., content created and shared by individual social media users) is associated with vulnerabilities to e-cigarette use among youth non-users. METHODS: We pooled data from the 2021 and 2022 National Youth Tobacco Survey. Youth who have never used e-cigarettes were included. Weighted linear and logistic regressions were conducted to examine how exposure to user-generated e-cigarette content (from real-life friends, online-only friends, and celebrities/influencers) on social media was associated with e-cigarette use vulnerabilities measured by perceived norms, perceived risk, and susceptibility of use, controlling for demographics, advertising exposure, and mental health conditions. Multiple imputations were performed to account for missing data. RESULTS: Exposure to e-cigarette content on social media posted by real-life friends, online-only friends, and celebrities/influencers were associated with more positive descriptive norm (ßs = 1.56, 0.37, and 0.35, respectively, all ps < .001), more positive injunctive norm (ßs = 0.46, 0.19, and 0.10, respectively, all ps < .001), and higher odds of e-cigarette use susceptibility (ORs = 1.48, 1.50. 1.29, respectively, all ps < .001). Exposure to content posted by real-life and online-only friends were associated with reduced risk perception of e-cigarette use (ß = -0.04, p < 0.05 and ß = -0.07, p < 0.001). CONCLUSIONS: Our study highlighted that friends and celebrities/influencers are important sources on social media that can influence youth non-users' vulnerabilities to e-cigarette use. Interventional messages communicated through friends and influencers on social media may in turn help reduce e-cigarette vulnerability among youth non-users.

E-cigarette use reasons and associated e-cigarette use dependence among college students: A longitudinal examination.

OBJECTIVE: Previous studies have established an understanding of reasons for e-cigarette use and associated e-cigarette use patterns such as use frequency, yet the critical extension to associated e-cigarette dependence outcome remains under-researched. This study used longitudinal data to examine whether the reasons for e-cigarette use predict a higher/lower level of e-cigarette dependence. METHODS: This study recruited college students who were current e-cigarette users from Fall 2019 to Fall 2020 (four semesters) at three public universities in the Midwest and South of the U.S. Those who participated for at least two semesters were included (N = 366). Data were collected using a structured questionnaire. E-cigarette use dependence was assessed using the Penn State Electronic Cigarette Dependence Index. A linear mixed model with a random intercept and a random slope was conducted to examine the longitudinal association between reasons for e-cigarette use and dependence, controlling for demographics and other covariates. RESULTS: Participants who used e-cigarettes for relaxation (ß = 0.63, p < 0.05) and due to their good taste (ß = 0.63, p < 0.05) had a higher level of e-cigarette dependence. Participants using e-cigarettes for experimental purposes had a lower level of e-cigarette dependence (ß = -1.21, p < 0.01). CONCLUSIONS: These findings highlight the importance of addressing e-cigarette use reasons and their relationship to e-cigarette dependence. Prevention and intervention efforts aimed at developing more effective strategies should consider the various e-cigarette use reasons associated with dependence risks, such as enhancing awareness of the use dependence risk related to good taste of e-cigarettes and use for relaxation, as well as incorporating early screenings for use.

Chronic Non-cancer Pain and Associated Risks of Incident Mild Cognitive Impairment and Alzheimer's Disease and Related Dementias in Middle-Aged and Older Adults.

The goal of this study is to investigate the association between chronic non-cancer pain (CNCP) and mild cognitive impairment (MCI)/Alzheimer's disease and related dementias (ADRDs) development among adults aged ≥50 using administrative claims data from a national commercial health insurance company during 2007-2017. To reduce selection bias, propensity-score matching was applied to select comparable CNCP and non-CNCP patients. Time-dependent Cox proportional-hazards regressions were conducted to estimate the hazard ratios (HRs) of incident MCI/ADRDs. Of 170,900 patients with/without CNCP, 0.61% developed MCI and 2.33% had been diagnosed with ADRDs during the follow-up period. Controlling for potential confounders, CNCP patients had a 123% increase in MCI risk (HR = 2.23; 95% CI = 1.92-2.58) and a 44% increase in ADRDs risk (HR = 1.44; 95% CI = 1.34-1.54) relative to non-CNCP patients. CNCP is a risk factor for MCI/ADRDs. Promoting awareness and improving early CNCP diagnosis in middle-aged and older adults should be incorporated into cognitive impairment and dementia prevention.

The mediating roles of mental health problems and racial differences in the linkage between social media use and E-cigarette use among American youth.

OBJECTIVE: Social media use is shown to be linked to youth's e-cigarette use. However, less is known about the underlying mechanisms. This study examined the mediating roles of internalizing and externalizing problems in the association between youth's social media use and e-cigarette use, and the racial differences in the mediation association. METHODS: The study sample included 4913 U.S. youth from the Population Assessment of Tobacco and Health Study Waves 3-5 (2015-2019). Two weighted generalized structural equation models were conducted to examine the mediation pathways between youth's social media use (Wave 3) and past-30-day e-cigarette use (Wave 5) through internalizing and externalizing problems (Wave 4), respectively. Invariance tests were conducted to examine racial group differences. RESULTS: Youth with high social media use frequency were more likely to use e-cigarettes (total effect: OR = 1.20, p < 0.001 in both internalizing and externalizing models). Internalizing and externalizing problems mediated the aforementioned associations (mediation proportions: 5.05% and 5.66%, respectively). The invariance tests indicated a significant difference between White and non-White groups (both ps < 0.001), where a larger proportion of mediation was found in the non-White group (12.22% for internalizing and 11.99% for externalizing) compared to their White counterparts (2.46% for internalizing and 3.17% for externalizing). CONCLUSIONS: Mental health problems following social media use served as a risk factor for e-cigarette use among youth. Interventions aiming to improve youth's mental health could in turn temper e-cigarette use among youth social media users, and implementing tailored interventions in response to racial differences is warranted.

Characterizing Twitter chatter about temporary alcohol abstinence during "Dry January".

With roots as a public health campaign in the United Kingdom, "Dry January" is a temporary alcohol abstinence initiative encouraging participants to abstain from alcohol use during the month of January. Dry January has become a cultural phenomenon, gaining increasing news media attention and social media engagement. Given the utility of capturing naturalistic discussions around health topics on social media, we examined Twitter chatter about Dry January and associated temporary abstinence experiences. Public tweets were collected containing the search terms "dry january" or "dryjanuary" posted between 15 December and 15 February across 3 years (2020-2). A random subsample stratified by year (n = 3145) was pulled for manual content analysis by trained coders. Final codebook accounted for user sentiment toward Dry January, user account type, and themes related to Dry January participation. Engagement metadata (e.g. likes) were also collected. Though user sentiment was mixed, most tweets expressed positive or neutral sentiment toward Dry January (74.7%). Common themes included encouragement and support for Dry January participation (14.1%), experimentation with and promotion of nonalcoholic drinks (14.0%), and benefits derived from Dry January participation (10.4%). While there is promise in the movement to promote positive alcohol-related behavior change, increased efforts to deliver the campaign within a public health context are needed. Health communication campaigns designed to inform participants about evidence-based treatment and recovery support services proven to help people quit or cut down on their drinking are likely to maximize benefits.

Retrospective and Real-time Measures of the Quantity of E-cigarette Use: An Ecological Momentary Assessment Study.

INTRODUCTION: Quantifying e-cigarette use is challenging because of the wide variety of products and the lack of a clear, objective demarcation of a use event. This study aimed to characterize the difference between retrospective and real-time measures of the quantity of e-cigarette use and identify the covariates that may account for discrepancies between the two types of measures. METHODS: This study analyzed data from 401 college student e-cigarette users in Indiana and Texas who responded to a web survey (retrospective) and 7-day ecological momentary assessments (EMA) (real-time) on their e-cigarette use behavior, dependence symptomatology, e-cigarette product characteristics, and use contexts from Fall 2019 to Fall 2021. Generalized linear mixed models were used to model the real-time measures of quantity offset by the retrospective average quantity. RESULTS: Although the number of times using e-cigarettes per day seems to be applicable to both retrospective and real-time measures, the number reported via EMA was 8.5 times the retrospective report. E-cigarette users with higher e-cigarette primary dependence motives tended to report more daily nicotine consumption via EMA than their retrospective reports (ie, perceived average consumption). Other covariates that were associated with discrepancies between real-time and retrospective reports included gender, nicotine concentration, using a menthol- or fruit-flavored product, co-use with alcohol, and being with others when vaping. CONCLUSIONS: The study found extreme under-reporting of e-cigarette consumption on retrospective surveys. Important covariates identified to be associated with higher than average consumption may be considered as potential targets for future vaping interventions. IMPLICATIONS: This is the first study that characterizes the direction and magnitude of the difference between retrospective and real-time measures of the quantity of e-cigarette use among young adults-the population most likely to use e-cigarettes. An average retrospective account of vaping events per day may significantly underestimate e-cigarette use frequency among young adults. The lack of insight into the degree of consumption among users with heavy primary dependence motives illustrates the importance of incorporating self-monitoring into cessation interventions.

An Exploratory Study on Strategies Adopted by Parents Who Use E-Cigarettes to Negotiate Risk Perceptions of Their Children's Secondhand Exposure and Parental Role Modeling.

Existing health messages mainly targeted youth susceptible to vaping or parents who do not have much knowledge about e-cigarettes. This study makes a unique contribution by conducting the first in-depth investigation of e-cigarette-using parents' risk perceptions and parental role modeling and how these two factors affect their vaping behaviors at home or implementation of any strategies to reduce their children's risk. Fifteen parents who used e-cigarettes participated in a semi-structured interview. Interview transcripts were coded and analyzed through a deductive approach of thematic analysis. This study demonstrates the need to develop and disseminate future health messages for e-cigarette-using parents who may have low-risk perceptions of secondhand exposure or who have adopted ineffective strategies to reduce their children's exposure. This study also identifies some possible targets for future intervention efforts through these parents including increasing their knowledge about the health risk of secondhand exposure to e-cigarettes, emphasizing the caregiver role, and effective communications with children about the consequences of vaping.

Racial discrimination, childhood adversity, and depression among Black men: Tests of stress sensitization hypotheses.

Racial discrimination has been linked to depression among Black American men. Racial discrimination, however, does not uniformly confer risk for depression. According to the stress sensitization theory, racial discrimination can be particularly harmful for those with histories of adversity in childhood. Existing research on stress sensitization is limited in that it has conceptualized childhood adversity as a unidimensional construct composed of a broad range of stressful experiences. To fill this gap in the literature, the current study investigated stress sensitization hypotheses, focusing on how different dimensions of adverse childhood experiences moderate the association between racial discrimination and depression. Study sample was 504 young Black men (mean age at baseline = 20.3, SD = 1.08) living in rural counties in South Georgia where childhood adversity is disproportionately high. The association between racial discrimination and increased risk for depressive symptoms varied by the degree of childhood experience of deprivation, but not threat. Our findings suggest that no or low levels of childhood deprivation, which is commonly regarded as a protective factor, can elevate the negative effects of discrimination on depression. This finding emphasizes that clinicians should consider developmental risk and protective factors that are unique to Black American men.

Stressful Life Events and Patterns of Polysubstance Use Among U.S. Late Middle-Aged and Older Adults: A Latent Class Analysis.

The goals of this study were to identify patterns of polysubstance use and their associations with stressful life events among U.S. late middle-aged and older adults and examine whether gender moderates these associations. Adults aged 50 and older (N = 14,738) from the National Epidemiological Survey on Alcohol and Related Conditions-III were included. Latent class analysis was conducted to identify patterns of polysubstance use. Weighted multinomial logistic regression was estimated with a generalized structural equation model. Three different polysubstance use patterns (non-users/low substance users; cannabis and excessive alcohol users; painkiller and sedative/tranquilizer misusers) were identified. Higher levels of stressful life events were associated with patterns of polysubstance use. Gender moderated the association between stressful life events and co-misusing painkillers and sedatives/tranquilizers (p < 0.05). Substance use prevention efforts should consider aging adults' patterns of polysubstance use and associated stressful life events when designing and implementing gender-specific polysubstance use prevention interventions.

An ecological momentary assessment study to examine covariates and effects of concurrent and simultaneous use of electronic cigarettes and marijuana among college students.

INTRODUCTION: The prevalence of concurrent and simultaneous use of e-cigarette and marijuana among college students is high. Yet, the literature was mainly based on cross-sectional surveys with emphasis on the smoking route. This is the first ecological momentary assessment (EMA) study that examined the vaping route of nicotine-marijuana co-use and the associated short-term psychological effects. METHODS: This study recruited 686 college student e-cigarette users to participate in an on-line survey and 7-day EMA. Frequent marijuana users (247) - using marijuana weekly or daily - were compared with infrequent/non-users (439) on academic performance, e-cigarette use patterns, and dependence and respiratory symptoms. EMA data from the frequent users were used to study the association between marijuana vaping and e-cigarette consumption and the short-term psychological effects of e-cigarette and marijuana use. RESULTS: The results show that e-cigarette users who frequently used marijuana tended to have lower academic performance, be involved in higher-risk use patterns, and have higher levels of e-cigarette dependence, marijuana problems, and respiratory symptoms, compared to infrequent/non-users. Marijuana vaping was associated with a higher level of e-cigarette consumption. E-cigarette use and marijuana use were both associated with higher levels of positive affect, physiological sensation, and craving for e-cigarettes. While marijuana use was linked to a lower level of negative affect, e-cigarette use did not have a significant effect. Further, none of the interaction effects between e-cigarette and marijuana use on psychological states were significant. CONCLUSIONS: The results showed additive effects of e-cigarette and marijuana use although the hypothesized synergistic effects were not supported.

Statewide vaping product excise tax policy and use of electronic nicotine delivery systems among US young adults, 2014-2019.

OBJECTIVES: An increasing number of US states have required a tax on electronic nicotine delivery systems (ENDS) in the past few years. This study evaluated the effect of statewide vaping product excise tax policy on ENDS use among young adults. METHODS: We used the two recent waves (2014-2019) of the Tobacco Use Supplement to the Current Population Survey. A total of 17 896 US young adults were analysed. Difference-in-differences approach along with weighted multilevel logistic regressions was used to evaluate the association of vaping product excise tax policy adoption with current ENDS use, accounting for the clustering of respondents within the same states. RESULTS: There was an increase in current ENDS use prevalence from 2014-2015 (3.4%) to 2018-2019 (5.4%). Respondents living in states with vaping product excise tax policy showed significantly lower increase in ENDS use prevalence during the study period (interaction between within-state changes and between-state differences: adjusted OR (AOR)=0.57, 95% CI=0.35 to 0.91), controlling for other state-level policies and sociodemographic characteristics. Additional stratified analysis with state-fixed effects by vaping product excise tax policy implementation status showed consistent findings. CONCLUSIONS: Our findings suggest that adopting a vaping product excise tax policy may help reduce ENDS use and suppress the increase of ENDS use prevalence among young adults. Considering that there are still a number of US states that have not implemented vaping product excise tax policy, wider adoption of such policy across the nation would likely help mitigate ENDS use prevalence.

How Does Online e-cigarette Advertisement Promote Youth's e-cigarettes Use? The Mediating Roles of Social Norm and Risk Perceptions.

The adoption of the internet, social media, and e-cigarettes are on the rise among U.S. youth. Uses of social media and online platforms increase the probability for youth to encounter e-cigarette advertisements. Departing from this line of reasoning, we examine the underlying mechanisms of how online e-cigarettes exposure promotes youth's e-cigarette use. Drawing on insights from the social construction of risk model, this study looks at how perceived social norms and risk perception mediate the link between online e-cigarette advertisement exposure and e-cigarette use. Youth aged 12-17 from the Public Assessment of Tobacco and Health (PATH) Study Waves 2-4 (2014-2018) were included (N = 6,067). Controlling for demographic and other known risk factors for e-cigarette use, respondents who had been exposed to online e-cigarette ads at Wave 2 perceived higher levels of positive social norms of e-cigarette use at Wave 3 (ß = 0.13, p < .001) which was associated with lower e-cigarette risk perception at Wave 3 (ß = -0.22, p < .001). Lower e-cigarette risk perception at Wave 3 resulted in a higher likelihood of e-cigarette use at Wave 4 (AOR = 0.51, p < .001). Online e-cigarettes ads exposure at Wave 2 predicted e-cigarette use at Wave 4 (AOR = 1.87, p < .001). The results indicate that norm perception associated with online e-cigarettes ads may twist youth's e-cigarette risk perception that is associated with subsequent usage. Interventions to curb youth's e-cigarette use can target social norms of e-cigarette use and restrict e-cigarette advertisement exposure to youth.

Stealth vaping and associated attitudes, perceptions, and control beliefs among US college students across four tobacco-free campuses.

OBJECTIVES: Stealth vaping gained popularity among college students in recent years. It may undermine the benefits introduced by tobacco-free policies. Yet, no studies have investigated attitude and belief factors associated with stealth vaping. The objective of the study was to explore the relationship between attitudes toward on-campus tobacco regulations, normative perceptions of stealth vaping behaviors, and control beliefs with on-campus stealth vaping among U.S. college students. METHODS: Participants from four large, public universities with policies prohibiting use of all forms of tobacco (including e-cigarettes) on campus (N = 863) completed an online survey in Fall 2020. On-campus stealth vaping behavior was captured by past 30-day stealth vaping status and frequency. Hurdle models with logistic and negative binomial regressions were conducted, where stealth vaping status was treated as a binary variable based on the non-zero and zero frequency, and stealth vaping frequency was treated as a count variable. Multiple imputation by chained equations was employed to handle the missing data. RESULTS: Participants with more positive attitudes toward regulating on-campus tobacco use were less likely to practice stealth vaping on campus (OR = 1.16, p < 0.01 [predicting zero]). Those with higher perceptions of stealth vaping among other students were more likely to stealth vape more frequently (IRR = 1.03, p < 0.01). CONCLUSION: Our results highlight the need for interventions to address students' attitudes and normative beliefs about stealth vaping. Efforts are needed to educate college students about the risk of e-cigarettes and to enhance enforcement of campus tobacco-free policies.

Using Natural Language Processing to Explore "Dry January" Posts on Twitter: Longitudinal Infodemiology Study.

BACKGROUND: Dry January, a temporary alcohol abstinence campaign, encourages individuals to reflect on their relationship with alcohol by temporarily abstaining from consumption during the month of January. Though Dry January has become a global phenomenon, there has been limited investigation into Dry January participants' experiences. One means through which to gain insights into individuals' Dry January-related experiences is by leveraging large-scale social media data (eg, Twitter chatter) to explore and characterize public discourse concerning Dry January. OBJECTIVE: We sought to answer the following questions: (1) What themes are present within a corpus of tweets about Dry January, and is there consistency in the language used to discuss Dry January across multiple years of tweets (2020-2022)? (2) Do unique themes or patterns emerge in Dry January 2021 tweets after the onset of the COVID-19 pandemic? and (3) What is the association with tweet composition (ie, sentiment and human-authored vs bot-authored) and engagement with Dry January tweets? METHODS: We applied natural language processing techniques to a large sample of tweets (n=222,917) containing the term "dry january" or "dryjanuary" posted from December 15 to February 15 across three separate years of participation (2020-2022). Term frequency inverse document frequency, k-means clustering, and principal component analysis were used for data visualization to identify the optimal number of clusters per year. Once data were visualized, we ran interpretation models to afford within-year (or within-cluster) comparisons. Latent Dirichlet allocation topic modeling was used to examine content within each cluster per given year. Valence Aware Dictionary and Sentiment Reasoner sentiment analysis was used to examine affect per cluster per year. The Botometer automated account check was used to determine average bot score per cluster per year. Last, to assess user engagement with Dry January content, we took the average number of likes and retweets per cluster and ran correlations with other outcome variables of interest. RESULTS: We observed several similar topics per year (eg, Dry January resources, Dry January health benefits, updates related to Dry January progress), suggesting relative consistency in Dry January content over time. Although there was overlap in themes across multiple years of tweets, unique themes related to individuals' experiences with alcohol during the midst of the COVID-19 global pandemic were detected in the corpus of tweets from 2021. Also, tweet composition was associated with engagement, including number of likes, retweets, and quote-tweets per post. Bot-dominant clusters had fewer likes, retweets, or quote tweets compared with human-authored clusters. CONCLUSIONS: The findings underscore the utility for using large-scale social media, such as discussions on Twitter, to study drinking reduction attempts and to monitor the ongoing dynamic needs of persons contemplating, preparing for, or actively pursuing attempts to quit or cut down on their drinking.

Home e-cigarette rules and youth's vulnerability to initiate and sustain e-cigarette use.

Existing studies of the impact of home rules on youth's vulnerability to e-cigarette use were based on cross-sectional data, youth or parent reports alone, as well as youth's perceptions and susceptibility. This study capitalizes on the restricted-use data of the Population Assessment of Tobacco and Health (PATH) Study to examine the longitudinal association between home rules for e-cigarette use and youth's vulnerability including initiation of use and regular use two years later. Secondary analysis was conducted on 1203 parent-youth pairs who participated in both Wave 4 (2016-2018) and Wave 5 (2018-2019) assessment of the PATH Study and while the youth were age 12-16 at Wave 4. Linear and logistic regressions were performed to examine the associations between having a strict home rule for e-cigarette use at Wave 4 and the youth's outcomes including perceived social norms, expectancies, susceptibility, initiation of use, and regular use of e-cigarettes at Wave 5, controlling for parent and youth factors. The results show that having a strict home rule for e-cigarette use was associated with youth's heightened level of perceived injunctive norms (ß = 0.22, p < 0.01), higher expectancy of harmfulness (ß = 0.28, p < 0.01) and lower odds for regular e-cigarette use (OR = 0.36, p < 0.05). In conclusion, the findings of this study support the potential protective effects of implementing a strict home rule for e-cigarette use. Future intervention efforts may promote parents' awareness of the potential protective effects of a strict home e-cigarette rule on youth's normative belief, harm expectancy, and behavior of e-cigarette use.

Organization-Level Factors Associated with Changes in the Delivery of the Five A's for Smoking Cessation following the Implementation of a Comprehensive Tobacco-Free Workplace Program within Substance Use Treatment Centers.

Many adults with a substance use disorder smoke cigarettes. However, tobacco use is not commonly addressed in substance use treatment centers. This study examined how provider beliefs about addressing tobacco use during non-nicotine substance use treatment, provider self-efficacy in delivering tobacco use assessments, and perceived barriers to the routine provision of tobacco care were associated with changes in the delivery of the evidence-based five A's for smoking intervention (asking, advising, assessing, assisting, and arranging) at the organizational level. The data were from 15 substance use treatment centers that implemented a tobacco-free workplace program; data were collected before and after the program's implementation. Linear regression examined how center-level averages of provider factors (1) at pre-implementation and (2) post- minus pre-implementation were associated with changes in the use of the five A's for smoking in substance use treatment patients. The results indicated that centers with providers endorsing less agreement that tobacco use should be addressed in non-nicotine substance use treatment and reporting lower self-efficacy for providing tobacco use assessments at pre-implementation were associated with significant increases in asking patients about smoking, assessing interest in quitting and assisting with a quit attempt by post-implementation. Centers reporting more barriers at pre-implementation and centers that had greater reductions in reported barriers to treatment over time had greater increases in assessing patients' interest in quitting smoking and assisting with a quit attempt by post-implementation. Overall, the centers that had the most to learn regarding addressing patients' tobacco use had greater changes in their use of the five A's compared to centers whose personnel were already better informed and trained. Findings from this study advance implementation science and contribute information relevant to reducing the research-to-practice translational gap in tobacco control for a patient group that suffers tobacco-related health disparities.

Disposable E-Cigarettes and Associated Health Risks: An Experimental Study.

The use of electronic nicotine delivery systems (ENDS), including disposable e-cigarettes, has been prevalent. Existing chemical analyses of ENDS focused on e-liquids rather than aerosols and failed to consider particle sizes and aerosol respiratory deposition fractions, which are key factors for inhalation doses. This study investigated the organic chemical and metal constituents in size-segregated ENDS aerosol and assessed the deposited doses and health risks of these substances. Aerosol chemical analyses were conducted on two popular disposable ENDS products: Puff Bar (Grape) and Air Bar (Watermelon Ice). An ENDS aerosol was generated and delivered into a Micro-Orifice Uniform Deposit Impactor to collect size-segregated aerosol samples, in which organic chemicals and metals were analyzed. Daily and lifetime doses for each chemical were estimated. Cancer and non-cancer risk assessments were conducted based on the deposited doses. We found that e-cigarette aerosol contains certain harmful organic chemicals and metals documented to result in respiratory problems. Estimated respiratory cancer risks corresponding to chromium from both ENDS products and nickel from Air Bar (Watermelon Ice) were substantially above the conventionally acceptable risk. The method, findings, and implications can contribute to the extant literature of ENDS toxicity studies as well as inform tobacco regulation and future large-scale studies.

The situational contexts and subjective effects of co-use of electronic cigarettes and alcohol among college students: An ecological momentary assessment (EMA) study.

INTRODUCTION: Understanding the co-use of e-cigarettes and alcohol, including the situational contexts and subjective effects associated with co-use in real-time is necessary for validating this behavior and informing intervention. Yet, the sparse literature has built upon retrospective data. METHODS: This study recruited 686 college students who were currently using e-cigarettes from three campuses in the Midwest and South of U.S in Fall 2019-Fall 2021. An on-line survey was conducted to measure e-cigarette use patterns, GPA, e-cigarette and alcohol dependence symptoms, and respiratory symptoms. A 7-day ecological momentary assessment was used to collect real-time data on e-cigarette and alcohol use, situational contexts and subjective effects. RESULTS: Frequent drinking e-cigarette users reported more high-risk use behavior including consuming 6 + drinks/occasion and simultaneous use, and reported more e-cigarettes and alcohol related dependence symptoms and respiratory symptoms, compared to infrequent/non-drinker e-cigarette users. Alcohol quantity was positively associated with e-cigarette quantity among the high frequency drinking group. This study identified important use contexts that were associated with higher e-cigarette consumption including use of menthol or fruit flavored e-cigarettes, being in a car, and the presence of others. E-cigarette use and alcohol use both increased the levels of positive affect, physiological sensation, and craving for e-cigarettes, whereas only alcohol use significantly decreased negative affect. No interaction effects between e-cigarette use and alcohol use were found. CONCLUSIONS: The findings highlight the addiction and health risks associated with frequent co-use of e-cigarettes and alcohol, and also call for regulations on nontobacco flavorings in e-cigarette products.

Characteristics of statewide prescription drug monitoring programs and potentially inappropriate opioid prescribing to patients with non-cancer chronic pain: A machine learning application.

Unnecessary/unsafe opioid prescribing has become a major public health concern in the U.S. Statewide prescription drug monitoring programs (PDMPs) with varying characteristics have been implemented to improve safe prescribing practice. Yet, no studies have comprehensively evaluated the effectiveness of PDMP characteristics in reducing opioid-related potentially inappropriate prescribing (PIP) practices. The objective of the study is to apply machine learning methods to evaluate PDMP effectiveness by examining how different PDMP characteristics are associated with opioid-related PIPs for non-cancer chronic pain (NCCP) treatment. This was a retrospective observational study that included 802,926 adult patients who were diagnosed NCCP, obtained opioid prescriptions, and were continuously enrolled in plans of a major U.S. insurer for over a year. Four outcomes of opioid-related PIP practices, including dosage ≥50 MME/day and ≥90 MME/day, days supply ≥7 days, and benzodiazepine-opioid co-prescription were examined. Machine learning models were applied, including logistic regression, least absolute shrinkage and selection operation regression, classification and regression trees, random forests, and gradient boost modeling (GBM). The SHapley Additive exPlanations (SHAP) method was applied to interpret model results. The results show that among 1,886,146 NCCP opioid-related claims, 22.8% had an opioid dosage ≥50 MME/day and 8.9% ≥90 MME/day, 70.3% had days supply ≥7 days, and 10.3% were when benzodiazepine was filled ≤7 days ago. GBM had superior model performance. We identified the most salient PDMP characteristics that predict opioid-related PIPs (e.g., broader access to patient prescription history, monitoring Schedule IV controlled substances), which could be informative to the states considering the redesign of PDMPs.