Smoking remains a leading cause of disability and mortality worldwide. Despite declining rates of smoking in developed countries, smoking prevalence remains high, and there is evidence that it has plateaued in recent years. Individuals with a comorbid psychiatric diagnosis represent a disproportionate percentage of those who continue to smoke and are particularly at-risk given they smoke at higher rates and consume more cigarettes compared to those with no diagnosis. Moreover, these individuals are often excluded from clinical trials of smoking cessation, making it difficult to generalize results of previous intervention studies. In the general literature of smoking cessation, smoking cessation self-efficacy, or one’s confidence in their ability to abstain from smoking, is a consistent predictor of positive abstinence outcomes. The overall purpose of this dissertation was to investigate smoking cessation self-efficacy as a predictor of abstinence outcomes in a population of treatment-seeking smokers with and without a history of psychiatric illness. To accomplish this, articles 1 and 2 investigated the psychometric properties of a multi-item measure of cessation self-efficacy. This entailed comparing the measure to other indices of smoking, and conducting a confirmatory factor analysis to ensure factor invariance and equivalence of the measure regardless of psychiatric status. We found a moderate correlation between our multi-item scale to a single-item measure of confidence to quit, as well as support for both the original two-factor model as well as a three-factor model, which explained 79.3% of the variance. Our results also supported the measure as being factor invariant across psychiatric diagnoses. Next, articles 3 and 4 investigated how this measure of cessation self-efficacy predicted several smoking outcomes (10-, 22- and 52-weeks following target-quit date), and whether this relationship was mediated by concurrent smoking and other interpersonal-indices of smoking cessation (nicotine withdrawal, negative affect). In article 3, we found support for a bidirectional and reciprocal relationship between smoking cessation self-efficacy and smoking status. While changes in concurrent behavior (smoking or abstinent) did impact subsequent evaluations of self-efficacy, the inverse was also true. Moreover, both concurrent smoking and cessation self-efficacy predicted outcomes at week 10. Article 4 built on this framework and investigated this relationship at 22- and 52-weeks post-target quit-date. Our results highlight the robust association between cessation self-efficacy and abstinence. Higher cessation self-efficacy was positively associated with better abstinence outcomes, even after controlling for concurrent smoking, withdrawal, and negative affect. Further, there was evidence that cessation self-efficacy partially mediated the impact of withdrawal and negative affect. In our fully adjusted model (adjusting for demographic characteristics, baseline smoking levels, withdrawal and negative affect), cessation self-efficacy along among the interpersonal-determinants predicted abstinence outcomes (Odds ratio = 1.078, 95% confidence interval (1.068 - 1.089). This was true for those with either a current, past, or no lifetime psychiatric diagnosis, and despite the finding that individuals in the lifetime (current or past diagnosis) category experienced overall lower self-efficacy. Overall, our results support the value of cessation self-efficacy as an important indicator of abstinence outcomes, and particularly highlight its potential utility for at-risk populations of comorbid psychiatric smokers.

According to the American Medical Association (AMA), smoking is the greatest cause of preventable illness and death in the United States. In 1997, the Centers for Disease Control and Prevention (CDC) stated that 29% of college students reported current cigarette use. The purpose of this study is to assess students' responses toward administering a smoking cessation program at a state university. This study was conducted at a state university where the researcher surveyed 319 students using a 27-item questionnaire. The survey questions include student demographics; age first smoked; frequency and amount of smoking; places they smoked the most; how soon they smoked after waking up; methods and attempts to quit; and perceptions regarding smoking and their health. Results from the study found statistically significant associations between smoking and the variables: academic classification and attempts to quit. However, there were no significant associations between smoking and age, gender, ethnicity, and residence. Other findings indicated that more than half of student smokers were female and more than half of student smokers were also in the first three years of college. Lack of time and cost were the main factors given as preventing smokers from receiving assistance from the university's smoking cessation program. In addition, student smokers reported shortness of breath, bad breath, stained teeth, decreased sense of smell and taste, increased heart rate, and loss of appetite. Recommendations include assessment, policy development, and assurance. Assessment helps to develop goals and objectives of the smoking cessation program. At the same time, it indicates the strengths and weaknesses of the program. The development of policies must be enforced to reduce or control the number of student smokers, especially in the dormitories. Finally, student smokers willing to receive assistance from the program must be assured that the services provided are free, safe, and efficient.

Abstract available through American Journal of Epidemiology.

Smoking cessation can reduce health risk and prevent millions of tobacco-related deaths. However, cessation rates are low in low-and-middle income countries (LMICs), with only a small proportion of smokers intending to quit. Given the paucity of literature to support tobacco cessation programs in LMICs, this study aimed to: 1) identify factors associated with intention to quit smoking, 2) assess the relationship between health care provider quit advice/tobacco screening and utilization of cessation assistance, and 3) examine the relationship between home smoking rule and smoking intensity across three stages of smoking cessation (precontemplation, contemplation and preparation) in LMICs. Data were obtained from the Global Adult Tobacco Survey, 2009-2012, a nationally representative household survey of noninstitutionalized civilians aged 15 years and older. Weighted multivariable regression analyses were conducted using SAS version 9.4. Adjusted odds ratios (OR), percent change in smoking intensity and associated 95% confidence intervals (CI) were estimated. Home smoking rule and exposure to anti-smoking messages were the important factors associated with contemplation and preparation to quit smoking. Approximately 1%, 7%, 9% and 15% used quitline, medical treatment, counseling/cessation clinic and cessation assistance (all three combined), respectively, in the past year. Quit advice was significantly associated with utilization of counseling/cessation clinic (OR=3.89, 95% CI=2.8–5.5), medical treatment (OR=1.71, 95% CI=1.2–2.4) and cessation assistance (OR=2.60, 95% CI=2.0–3.4). Tobacco screening was associated with utilization of counseling/cessation clinic (OR=2.60, 95% CI=1.1–5.9) and medical treatment (OR=1.71, 95% CI=1.2–2.4). Living in a completely smoke-free home was associated with a 22.5% (95% CI=17.1%–28.0%), an 18.6% (95% CI=9.0%–28.2%), and a 19.4% (95% CI=3.9%–34.9%) significant reduction in smoking intensity among smokers in precontemplation, contemplation and preparation, respectively. In conclusion, the results suggest that smoke-free home, anti-smoking campaigns, and health care provider intervention promote smoking cessation in LMICs. Therefore, comprehensive smoke-free policies, anti-smoking media campaigns and integration of tobacco screening and quit advice into the health care system are important for tobacco cessation in LMICs, suggesting the need for full implementation of the World Health Organization Framework Convention for Tobacco Control Articles 8 and 11 – 13.

While cigarette smoking is a common-knowledge way to stay lean, it has long been known as a risk factor for diabetes and obesity. Here we establish that smoking causes fat gain and metabolic disruption in mice, effects which are exacerbated by a high-fat, high-sugar diet. We found that smoke exposure increases levels of ceramide—the lipid responsible for diet-induced insulin resistance—and that blocking ceramide production with the pharmacological inhibitor myriocin restored insulin sensitivity, stopped weight gain, and rescued mitochondrial respiration in vivo and in vitro.We also sought to assess the impact of the RAGE ligand HMGB1 on skeletal muscle metabolism. We found that respiration between vehicle and HMGB1-injected red gastrocnemius was comparable. In myotubes, adding myriocin treatment to the HMGB1 cells increased respiration above HMGB1 treatment alone. HMGB1 increased oxidative stress in cultured myotubes and increased the transcript levels of Spt2, the enzyme responsible for the rate-limiting step in ceramide synthesis, although transcript levels of markers of mitochondrial fission and fusion leave us unsure of HMGB1's impact on mitochondrial dynamics. HMGB1, even at an exceptionally low dose over only 2 weeks, did cause significant impairment in glucose and insulin tolerance tests. Considering HMGB1's accessibility as a therapeutic target, its involvement in metabolic disruption is worth pursuing further.

Background: Use of electronic cigarettes (EC) has dramatically increased in the United States since 2010 with a forecasted growth of 37% between 2014 and 2019. There is little research on e-liquid nicotine concentration from domestic manufacturers. However, limited research outside of the U.S. found wide inconsistencies between the labeled concentration of nicotine in e-liquids and the actual nicotine concentration. Methods: The seven most popular online manufacturers or distributors were identified. E-liquid samples of the five most popular flavors from each manufacturer were purchased in nicotine concentrations of 0 mg/ml and 18 mg/ml. Of the samples purchased (n=70), all were labeled as produced in the United States of America (USA). The researchers anonymized the samples before sending them to an independent university lab for testing. Results: The 35 e-liquid samples labeled 18 mg/ml nicotine measured between 11.6 and 27.4 mg/ml (M=18.7 SD=3.3) nicotine. The labeled 18 mg/ml samples measured as little as 35% less nicotine and as much as 52% greater nicotine. In the 35 samples labeled 0 mg/ml, nicotine was detected (>0.01 mg/ml) in 91.4% of the samples (Range = 0 to 23.9 mg/ml; M=2.9; SD=7.2). Six samples from two manufacturers labeled as 0 mg/ml were found to contain nicotine in amounts ranging from 5.7 mg/ml to 23.9 mg/ml. Conclusion: This study demonstrates the nicotine labeling inaccuracies present in current e-liquid solutions produced in the U.S. Incorrect labeling poses a significant risk to consumers and supports the recent regulation changes enacted by the FDA. Additional routine testing of nicotine concentrations should be conducted to evaluate the effectiveness of the regulations on future e-liquid production.

Cigarette smoking and depressive symptoms are two problems that affect adolescents’ health. Although it has been well-documented that a relationship exists between these two concerns, most researchers have used self-report methods to study smoking behaviors. While adolescents are typically accurate when reporting depressive symptoms, they tend to be less accurate reporting smoking. Moreover, research supporting the Prototype Willingness Model (PWM) has shown that the social cognitions of willingness to smoke, and the prototypes or images of smokers are predictors of smoking in adolescents. Little is known about the association between social cognitions and depressive symptoms in adolescence. In this study, I examined the relationship between cigarette smoking and depressive symptoms in high school students using a biological measure of cigarette smoking. First, I investigated whether depressive symptoms and cigarette smoking were related in a sample of 440 high school sophomore students from Iowa. Then, using data from 264 of the same participants, I examined whether smoking during or before the sophomore year of high school predicted depressive symptoms a year later when participants were in their junior year of high school. Conversely, I also examined whether depressive symptoms during the sophomore year of high school predicted cigarette smoking in the junior year of high school. Finally, I studied the relationship between social cognitions (i.e., prototypes and willingness) and depressive symptoms. An additional section explored whether the social cognitions predicted cigarette smoking. The findings did not provide evidence supporting a relationship between cigarette smoking and depressive symptoms when smoking was measured by a biological measure. Only self-report of smoking cigarettes significantly predicted depressive symptoms during the sophomore year of high school. Cigarette smoking during or before the sophomore year of high school did not predict depressive symptoms a year later. Similarly, depressive symptoms reported in the sophomore year of high school did not predict cigarette smoking a year later. For the social cognitions, willingness to engage in smoking behaviors and the prototypes or images adolescents have about teenagers who smoke were significantly associated with depressive symptoms. Only willingness to engage in smoking behaviors was a significant predictor of cigarette smoking. These results support the idea that the relationship between depressive symptoms and cigarette smoking varies when using different methodologies to assess smoking status. Also, the finding that social cognitions correlates with depressive symptoms could motivate further investigation. This work can also alert adults about other ways in which elevated depressive symptoms in adolescents may influence their perceptions.

Little is known about how electronic cigarette (EC) users manipulate device parameters, what factors drive their use, and how non-nicotine ingredients influence the stimulus effects of EC aerosols. The ingredients propylene glycol (PG) or vegetable glycerin (VG) serve as the base for virtually all electronic cigarette liquids, and information on how they affect the using experience would provide important groundwork for the study of other ingredients. In this dissertation, results from a survey and laboratory study focused on the stimulus effects of ECs, and the influence of PG and VG, will be discussed. A total of 522 regular EC users completed a survey comprised of an electronic cigarette dependence questionnaire, questions on tobacco and electronic cigarette use, and device and liquid preferences. This was followed by a laboratory study with sixteen electronic cigarette users completing five test days (one practice and four assessment days). In the laboratory study, following one hour of nicotine deprivation, two sampling puffs from liquid formulations containing 100/0, 75/25, 50/50, 25/75, and 0/100% PG/VG concentrations were administered in random order during five assessments, each separated by 20 min. Primary outcome measures were self-reported stimulus characteristics and breakpoint on a multiple-choice procedure. Survey results indicated that ability to change device voltage, and level of resistance, was significantly associated with level of nicotine dependence, as was amount of liquid consumed, nicotine concentration, and milligrams of nicotine used per week. Participants also rated 'good taste' as the most important consideration when purchasing and using liquids, and PG was associated with undesirable effects and VG with desirable effects. Laboratory results indicated that greater VG content was associated with greater reports of visibility of the exhalant (i.e. “cloud”). Liquids with mixtures of PG or VG were associated with conventional cigarette smoking sensations and greater reductions of systolic blood pressure compared to formulations with only PG or VG. There was no significant effect of liquid formulation on the multiple-choice procedure, but puffs were rarely chosen over even the smallest monetary option ($0.05), suggesting minimal reinforcing efficacy. In conclusion, survey data indicate that a wide range device parameter settings and liquid ingredients are preferred by daily e-cigarette users, and that individuals with greater nicotine dependence favor voltage control devices, and lower resistance heating elements. Survey data also indicated that taste is a key factor for EC liquid selection, and relative concentrations of propylene glycol and vegetable glycerin may have a significant impact on the reinforcing effects of liquids. In contrast, laboratory data suggests that PG or VG do not significantly impact the abuse liability of EC liquids, though reinforcing effects of these ingredients was unclear in the laboratory study.

This cross-sectional, mixed-methods study examined the nature of, and association between, causal attributions and current smoking behavior in cervical cancer survivors who were smokers at cancer diagnosis (n=50). As a whole, participants’ beliefs about smoking as a risk factor or cause of cervical cancer in general (i.e., global attribution) and/or their own cervical cancer (i.e., personal attribution) reflected far greater endorsement of global than personal attributions. Data collection involved a quantitative survey and an optional semi-structured interview to assess key variables (i.e., smoking behavior and causal attributions). Data were analyzed via descriptive statistics and inferential tests, all of which illustrated greater endorsement of global smoking-related causal attributions versus personal attributions within the sample. In conclusion, the results of this formative study highlights the potential role of causal attributions in understanding the smoking behavior of cervical cancer survivors, the results of which aids understanding of how cancer survivors think about, and make changes in, their smoking behavior.

The incidence of smoking among mentally ill people is very high. Smokers have a 50%, rate of mental illness diagnosis compared with 23% rate for general population. To address this problem, the purpose of this project was to plan a smoking cessation program for patients in a mental health facility. The theoretical foundation for this project was based on the theory of planned behavior, which identifies the predictive nature of smoking and the benefits that can be derived from implementing a systematic approach for change. The project question examined the effectiveness of smoking cessation program using educational support, pharmacological strategies, and bi-weekly meetings to help patients in a mental health hospital to decrease smoking behavior. The project design was based on use of smoking questionnaires, the Hooked on Nicotine Checklist (HONC), effective pharmacological strategies, educational support, and counseling treatments to evaluate symptoms of dependency. The key results of this project included the creation of a plan that could foster reduction in illness, improved quality of life, and reduced costs related to the onset of major illness in this vulnerable population. This data collection process focused on a qualitative design in which selected professionals were asked to review the materials and answer questions. This project could increase awareness of the issue of smoking; in addition, this project could equip nurses with the tools to deliver evidence based interventions for tobacco dependence that may significantly reduce tobacco use. This project has the implications for positive social change through its potential to improve the health of people with mental illnesses. It also creates a safe and healthy environment in mental health facilities for patients who do not smoke.