Trends in Education-Related Smoking Disparities Among U.S. Black or African American and White Adults: Intersections of Race, Sex, and Region

Efficacy of a conversational chatbot for cigarette smoking cessation: Protocol of the QuitBot full-scale randomized controlled trial

Globally, cigarette smoking results in over 8 million premature annual deaths. Addressing this issue requires high-impact, cost-effective population-level interventions for smoking cessation. Conversational chatbots offer a potential solution given the recent advancements in machine learning and large language models. Chatbots can deliver supportive, empathetic behaviors, personalized responses, and timely advice tailored to users' needs that is engaging through therapeutic conversations aimed at creating lasting social-emotional connections. Despite their promise, little is known about the efficacy and underlying mechanisms of chatbots for cigarette smoking cessation. We developed QuitBot, a quit smoking program of two to three-minute conversations covering topics ranging from motivations to quit, setting a quit date, choosing cessation medications, coping with triggers, maintaining abstinence, and recovering from a relapse. QuitBot employs conversational interactions, powered by an expert-curated large language model, allowing users to ask questions and receive personalized guidance on quitting smoking. Here, we report the design and execution of a randomized clinical trial comparing QuitBot (n = 760) against Smokefree TXT (SFT) text messaging program (n = 760), with a 12-month follow-up period. Both interventions include 42-days of content on motivations to quit, skills to cope with triggers, and relapse prevention. The key distinction between QuitBot and SFT is that QuitBot has communication and engagement features. This study aims to determine: whether QuitBot yields higher quit rates than SFT; and whether therapeutic alliance processes and engagement are mechanisms underlying cessation outcomes. Additionally, we will explore whether baseline factors including trust, social support, and demographics, moderate the efficacy of QuitBot. Trial Registration numberClinicalTrials.govNCT04308759.

How "Light" Is "Light Smoking"? On the Cognitive Power of Nicotine Dependence

In recent years, habits related to smoking have been changing. An increasing portion of light/occasional smokers tend to define themselves as non-smokers, leading to an incorrect perception of the risks that smoking even a few cigarettes can entail. In this study, we investigated the nicotine-induced cognitive distortion in young, higher-education students with low/moderate dependence (as indexed by the Fagerstrom questionnaire). The study involved 111 participants (62 female; mean age 24.43 ± 3.77) divided into smokers and non-smokers, who responded to specific questionnaires to evaluate their attachment style, emotion dysregulation, and state anxiety. Their response to smoking-related cues following emotional stimulation was experimentally evaluated, with participants being made to choose between care- or smoking-related images, following the presentation of threatening or neutral stimuli. The results show a cognitive bias in smokers, with participants choosing smoking-related stimuli significantly more often than non-smokers, with a slower reaction time, regardless of emotional cues. Emotion dysregulation and attachment style were also significantly correlated with response choice but not with response latency. Overall, our data indicate that there is no such thing as light use of nicotine and that smoking, even if not continuous, determines cognitive biases that lead to a vision of the environment as a function of substance seeking.

Who uses cigarette price promotions in the U.S.? examining the combined effect of social identities

Introduction

Tobacco industry offers price promotions to promote cigarette smoking. Several social identities (e.g., women, people with low socioeconomic status) are independently associated with exposure and use of these promotions. We examined how combinations of social identities relate to use of cigarette price promotions.

Methods

We analyzed data from adults who reported current cigarette smoking and purchased their own cigarettes in the 1995-2019 U.S. Tobacco Use Supplement to the Current Population Survey (n = 35,749). We applied a statistical-learning boosting algorithm followed by weighted logistic regression models with 3-way interactions to identify combinations of social identities related to cigarette price promotion use.

Results

This analysis revealed that use of cigarette price promotions varied greatly by combinations of social identities. For example, estimated 39.80% of Asian female adults living in the Midwest used these promotions in their last purchase. Meanwhile, estimated 2.80% of Asian male 31-45-year-old adults reported the same behavior. Additionally, American Indian/Alaskan Native peoples were indicated in four of the ten combinations of social identities with highest prevalence of cigarette price promotion use.

Discussion

Our approach allowed for discovery of previously less appreciated social identities (e.g., race/ethnicity) related to high probability of using cigarette price promotions. These findings also revealed how combination of social-identity-related power dynamics may shape use of cigarette price promotions. Adopting this perspective in future surveillance and policy evaluation effort will provide better understanding in commercial tobacco use disparities.

Differences in the Relationship Between Educational Attainment and Health Status Across Racial and Ethnic Groups in a Multi-ethnic United States Older Adult Population: A Cross-Sectional Electronic Health Record-Based Study

Introduction We aimed to describe the relationship of educational attainment with the prevalence of six health outcomes (ever and current smoking, diabetes, hypertension, coronary artery disease, and chronic obstructive pulmonary disease) in an older adult population, including whether education-health relationships differed by health outcome, by racial and ethnic (racial/ethnic) group, and by racial/ethnic group within the same level of education. Methods This cross-sectional study used 2015-2016 electronic health record data for 149,417 non-Hispanic White (White), 15,398 African-American or other Black (Black), 15,319 Hispanic or Latino (Latino), 10,133 Filipino, and 8810 Chinese Northern California health plan members aged 65-79 years whose preferred language was English. For each racial/ethnic group, sex-specific age-standardized prevalence of the six health outcomes was estimated for four levels of education (non-high school graduate, high school graduate, some college, college graduate). Age-adjusted prevalence ratios were used to compare the prevalence between adjacent levels of education and at lower versus college graduate levels within racial/ethnic groups, and the prevalence between White adults and adults in the other racial/ethnic groups, within each level of education and overall. Results The education-health relationship varied across racial/ethnic groups and health outcomes, with gradient relationships more consistently seen for White, Black, and Latino older adults than Filipino and Chinese older adults. Even when a gradient relationship was not observed, the prevalence at the college graduate level was usually significantly lower than the prevalence at the three lower levels of education. The prevalence of current smoking, diabetes, and hypertension was higher among Black than White adults at most levels of education. Controlling for education level minimally affected comparisons of overall prevalence of health outcomes between adults in the White and the other racial/ethnic groups, with the broadest impact seen for Latino-White comparisons. Conclusions The relationship of level of education and health outcomes differs across racial/ethnic groups and by health outcome. This should be taken into consideration when using education as a risk adjustment factor or predictor of health outcomes in multi-ethnic older adult populations.

Reprint of: Smoking and pulmonary health in women: A narrative review and behavioral health perspective

OBJECTIVE

Cigarette smoking prevalence has declined slower among women than men, and smoking-related pulmonary disease (PD) has risen among women. Given these trends, there is a critical need to understand and mitigate PD risk among women who smoke. The purpose of this narrative review and commentary is to highlight important evidence from the literature on smoking and PD among women.

METHODS

This review focuses broadly on examining cigarette smoking and PD among women within six topic areas: (1) demographic characteristics and prevalence of smoking, (2) smoking behavior, (3) lung cancer, (4) obstructive PD, (5) diagnostic and treatment disparities, and (6) gaps in the literature and potential directions for future research and treatment.

RESULTS

Growing evidence indicates that compared to men, women are at increased risk for developing smoking-related PD and poorer PD outcomes. Gender disparities in smoking-related PD may be largely accounted for by genetic differences and sex hormones contributing to PD pathogenesis and presentation, smoking behavior, nicotine dependence, and pathogen/carcinogen clearance. Moreover, gender disparities in smoking-related PD may be exacerbated by important social determinants (e.g., women with less formal education and those from minoritized groups may be at especially high risk for poor PD outcomes due to higher rates of smoking).

CONCLUSION

Rising rates of smoking-related PD among women risk widening diagnostic and treatment disparities. Ongoing research is needed to explore potentially complex relationships between sex, gender, and smoking-related PD processes and outcomes, and to improve smoking-cessation and PD treatment for women.

Smoking and pulmonary health in women: A narrative review and behavioral health perspective

OBJECTIVE

Cigarette smoking prevalence has declined slower among women than men, and smoking-related pulmonary disease (PD) has risen among women. Given these trends, there is a critical need to understand and mitigate PD risk among women who smoke. The purpose of this narrative review and commentary is to highlight important evidence from the literature on smoking and PD among women.

METHODS

This review focuses broadly on examining cigarette smoking and PD among women within six topic areas: (1) demographic characteristics and prevalence of smoking, (2) smoking behavior, (3) lung cancer, (4) obstructive PD, (5) diagnostic and treatment disparities, and (6) gaps in the literature and potential directions for future research and treatment.

RESULTS

Growing evidence indicates that compared to men, women are at increased risk for developing smoking-related PD and poorer PD outcomes. Gender disparities in smoking-related PD may be largely accounted for by genetic differences and sex hormones contributing to PD pathogenesis and presentation, smoking behavior, nicotine dependence, and pathogen/carcinogen clearance. Moreover, gender disparities in smoking-related PD may be exacerbated by important social determinants (e.g., women with less formal education and those from minoritized groups may be at especially high risk for poor PD outcomes due to higher rates of smoking).

CONCLUSION

Rising rates of smoking-related PD among women risk widening diagnostic and treatment disparities. Ongoing research is needed to explore potentially complex relationships between sex, gender, and smoking-related PD processes and outcomes, and to improve smoking-cessation and PD treatment for women.

Conversational Chatbot for Cigarette Smoking Cessation: Results From the 11-Step User-Centered Design Development Process and Randomized Controlled Trial

BACKGROUND

Conversational chatbots are an emerging digital intervention for smoking cessation. No studies have reported on the entire development process of a cessation chatbot.

OBJECTIVE

We aim to report results of the user-centered design development process and randomized controlled trial for a novel and comprehensive quit smoking conversational chatbot called QuitBot.

METHODS

The 4 years of formative research for developing QuitBot followed an 11-step process: (1) specifying a conceptual model; (2) conducting content analysis of existing interventions (63 hours of intervention transcripts); (3) assessing user needs; (4) developing the chat's persona ("personality"); (5) prototyping content and persona; (6) developing full functionality; (7) programming the QuitBot; (8) conducting a diary study; (9) conducting a pilot randomized controlled trial (RCT); (10) reviewing results of the RCT; and (11) adding a free-form question and answer (QnA) function, based on user feedback from pilot RCT results. The process of adding a QnA function itself involved a three-step process: (1) generating QnA pairs, (2) fine-tuning large language models (LLMs) on QnA pairs, and (3) evaluating the LLM outputs.

RESULTS

We developed a quit smoking program spanning 42 days of 2- to 3-minute conversations covering topics ranging from motivations to quit, setting a quit date, choosing Food and Drug Administration-approved cessation medications, coping with triggers, and recovering from lapses and relapses. In a pilot RCT with 96% three-month outcome data retention, QuitBot demonstrated high user engagement and promising cessation rates compared to the National Cancer Institute's SmokefreeTXT text messaging program, particularly among those who viewed all 42 days of program content: 30-day, complete-case, point prevalence abstinence rates at 3-month follow-up were 63% (39/62) for QuitBot versus 38.5% (45/117) for SmokefreeTXT (odds ratio 2.58, 95% CI 1.34-4.99; P=.005). However, Facebook Messenger intermittently blocked participants' access to QuitBot, so we transitioned from Facebook Messenger to a stand-alone smartphone app as the communication channel. Participants' frustration with QuitBot's inability to answer their open-ended questions led to us develop a core conversational feature, enabling users to ask open-ended questions about quitting cigarette smoking and for the QuitBot to respond with accurate and professional answers. To support this functionality, we developed a library of 11,000 QnA pairs on topics associated with quitting cigarette smoking. Model testing results showed that Microsoft's Azure-based QnA maker effectively handled questions that matched our library of 11,000 QnA pairs. A fine-tuned, contextualized GPT-3.5 (OpenAI) responds to questions that are not within our library of QnA pairs.

CONCLUSIONS

The development process yielded the first LLM-based quit smoking program delivered as a conversational chatbot. Iterative testing led to significant enhancements, including improvements to the delivery channel. A pivotal addition was the inclusion of a core LLM-supported conversational feature allowing users to ask open-ended questions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03585231; https://clinicaltrials.gov/study/NCT03585231.

Black Americans' Diminished Return of Educational Attainment on Tobacco Use in Baltimore City

BACKGROUND

Socioeconomic status (SES) indicators such as educational attainment are fundamental factors affecting health. One mechanism through which education affects health is by reducing the likelihood of engaging in high-risk behaviors such as smoking. However, according to the marginalization-related diminished returns (MDRs) theory, the association between education and health may be weaker for marginalized populations such as Black than White, primarily due to racism and discrimination. However, little is known about the racial variations in the differential associations between educational attainment and tobacco use in a local setting.

AIM

This study aimed to investigate the differential association between educational attainment and tobacco use among racial groups in a community sample in Baltimore City.

METHODS

This cross-sectional study used data from a community survey conducted in 2012-2013 in Baltimore City among adults aged 18 years or older. The participants were 3501 adults. Univariate, bivariate, and logistic regression analyses were performed using Stata to investigate the racial difference in the association between education and two outcomes: current smoking status and menthol tobacco product use.

RESULTS

The study found that adults with a graduate degree were less likely to be current smokers (adjusted odds ratio [AOR]: 0.10, 95% confidence interval [CI]: 0.08-0.13) and menthol tobacco users (AOR: 0.10, 95% CI: 0.07-0.14) compared to those with less than high school diploma. The inverse associations between educational attainment and current smoking (AOR: 1.83, 95% CI: 1.05-3.21) and menthol tobacco product use (AOR: 4.73, 95% CI: 2.07-10.80) were weaker for Back individuals than those who were White.

CONCLUSION

Due to MDRs of educational attainment, while highly educated White adults show a low risk of tobacco use, educated Black adults remain at a disproportionately increased risk. The study emphasizes the need for better policies and programs that address minorities' diminished return of education for tobacco use.

Summary and Concluding Remarks: Patterns of Birth Cohort‒Specific Smoking Histories

The Cancer Intervention and Surveillance Modeling Network (CISNET) Lung Working Group age-period-cohort methodology to study smoking patterns can be applied to tackle important issues in tobacco control and public health. This paper summarizes the analyses of smoking patterns in the U.S. by race/ethnicity, educational attainment, and family income and for each of the 50 U.S. states using the CISNET Lung Working Group age-period-cohort approach. We describe how decision makers, policy advocates, and researchers can use the sociodemographic analyses in this supplement to project state smoking trends and develop effective state-level tobacco control strategies. The all-cause mortality RR estimates associated with smoking for U.S. race/ethnicity and education groups are also discussed in the context of research that measures and evaluates health disparities. Finally, the application of the CISNET Lung Working Group age-period-cohort methodology to Brazil is reviewed with a view to how the same types of analyses can be applied to other low- and middle-income countries.