New types of nicotine and tobacco products like electronic cigarettes (ECs), heated tobacco products or nicotine pouches have been discussed as less harmful alternatives to combustible cigarettes and other toxic forms of tobacco products. Their harm reduction potential lay in the efficient transition away from smoking to those new products. Numerous studies addressing the cessation efficacy of ECs have been published with contradictory outcomes. Yet, a comprehensive Cochrane review concluded with high certainty on the cessation efficacy of ECs. This prompted us to perform a review to identify weaknesses in common study designs and to summarize best practices for the study design on the potential of new nicotine products as cessation aids. 120 articles retrieved from Medline were found to be eligible. Most of the studies in the field were interventional trials while observational studies played a minor role in the evaluation of smoking cessation. Efficacy was predominantly assessed for ECs in 77% of the reports while heated tobacco (17%) and non-combustible products (11%) were less frequently investigated up to now. Measures to determine the efficacy were questionnaire-based assessments as well as use documentation/prevalence and abstinence rates. Studies varied largely in their duration and sample size with medians of 3 months and 156.5 participants, respectively.With the help of this review, we identified several weaknesses in the common study designs. One major limitation in longitudinal trials was the lack of compliance measures suited to verify the use status over longer time periods, relying solely on self-reports. Moreover, the motivation of the participants to quit was rarely defined and a profound familiarization period was not taken into account for the majority of the studies. To what extent such weaknesses influence the outcome of the studies was beyond the scope of this review. We encourage researchers to consider the recommendations which resulted from this review in order to determine the abuse liability and cessation efficacy of the products in a more robust manner. Finally, we like to call attention to the missing data for low- and middle-income countries which would require quitting strategies most urgently to combat the tobacco smoking epidemic.

UNASSIGNED: Tobacco smoking is a leading cause of preventable death worldwide. The perinatal period provides a unique opportunity for intervention, as many smokers quit smoking during pregnancy but relapse postpartum. Novel relapse prevention interventions that reduce the burden of treatment attendance in this population are needed. Attentional retraining (AR) has been shown to reduce attentional biases toward smoking-related stimuli, a cognitive process implicated in smoking, AR has not been applied to perinatal smokers, and the effect of AR on craving and smoking is not clear. The goal of this study was to evaluate the delivery of AR for smoking cues in perinatal smokers utilizing a mobile intervention.
UNASSIGNED: This pilot study utilized Ecological Momentary Assessment (EMA) methodology delivered on a mobile device to examine the relapse process and evaluate the utility of AR in former smokers attempting to remain abstinent postpartum. AR (or Control Training) was administered to abstinent smokers (N = 17) for up to 2 weeks both before and after delivery.
UNASSIGNED: All 17 participants completed the study. There was evidence that AR reduced attentional bias in the AR group (vs. Controls). There was no evidence that AR reduced craving. An exploratory analysis revealed that there was no evidence that AR reduced smoking during the study period.
UNASSIGNED: AR using EMA methodology via a mobile device is feasible in perinatal smokers. Further research using larger samples is required to evaluate the utility of mobile AR in reducing craving and smoking.

BACKGROUND: Most hospitalized patients who smoke resume after discharge. Associations of tobacco-related disease and health beliefs with post-hospitalization abstinence were examined.
METHODS: This was a cohort study using data from a 2018-2020 multicenter trial of hospitalized adults who smoked and wanted to quit. Tobacco-related disease was defined using primary discharge diagnosis codes. Baseline health beliefs included (1) smoking caused hospitalization, (2) quitting speeds recovery, and (3) quitting prevents future illness. Outcomes included self-reported 7-day point prevalence abstinence 1, 3, and 6 months after discharge. Separate logistic regression models for each of the three health beliefs were constructed. Models stratified by tobacco-related disease explored effect modification. Analysis was performed in 2022-2023.
RESULTS: Of 1,406 participants (mean age 52 years, 56% females, 77% non-Hispanic White), 31% had tobacco-related disease, 42% believed that smoking caused hospitalization, 68% believed that quitting speeds recovery, and 82% believed that quitting prevents future illness. Tobacco-related disease was associated with higher 1-month point prevalence abstinence in each health belief model (AOR=1.55, 95% CI=1.15, 2.10; 1.53, 95% CI=1.14, 2.05; and 1.64, 95% CI=1.24, 2.19, respectively) and higher 6-month point prevalence abstinence in models including health beliefs 2 and 3. Quitting speeds recovery was the only belief associated with higher 1-month point prevalence abstinence (AOR=1.39, 95% CI=1.05, 1.85). Among patients with tobacco-related disease, the belief that quitting prevents future illness was associated with higher 1-month point prevalence abstinence (AOR=2.00, 95% CI=1.06, 3.78).
CONCLUSIONS: Tobacco-related disease predicts abstinence 1 and 6 months after hospitalization independent of health beliefs. Beliefs that quitting speeds recovery and prevents future illness may serve as targets for smoking-cessation interventions.

During quit attempts, smokers must overcome smoking urges triggered by environmental cues and nicotine withdrawal symptoms. This study investigates the psychometric properties of the 12-item Tobacco Urge Management Scale (TUMS), a new measure of smoking urge management behaviors.
We analyzed secondary data (n = 327) from a behavioral smoking cessation intervention trial, Kids Safe and Smokefree (KiSS).
Confirmatory factor analysis of the TUMS indicated that a one-factor model and a correlated two-factor model had similar model fit indices, and a Chi-square difference test supported the one-factor model. Further study of the parsimonious one-factor scale provided evidence of reliability and construct validity. Known group validity was evidenced by significantly higher TUMS scores in the KiSS intervention arm receiving urge management skills training than in the control arm (p < 0.001). Concurrent validity was evidenced by TUMS\'s inverse association with cigarettes smoked per day and positive associations with nonsmoking days, 7-day abstinence, and self-efficacy to control smoking behaviors (p\'s < 0.05).
The TUMS is a reliable, valid measure of smoking urge management behaviors. The measure can support theory-driven research on smoking-specific coping mechanisms, inform clinical practice by identifying coping strategies that might be under-utilized in treatment-seeking smokers, and function as a measure of treatment adherence in cessation trials that target urge management behaviors.

Most mobile cessation studies have found that such interventions have a higher quitting rate than interventions providing minimal smoking cessation support. However, why such interventions are effective has been almost unstudied by researchers.
This paper describes the principles of the personalized mobile cessation intervention-based WeChat app and used generalized estimated equations to assess why a personalized mobile cessation intervention was more likely to promote smokers from the preparation stage to the action stage than a nonpersonalized intervention.
This is a 2-arm, double-blind, randomized controlled trial in five cities in China. The intervention group received a personalized mobile cessation intervention. The control group received a nonpersonalized SMS text message smoking cessation intervention. All information was sent by the WeChat app. The outcomes were the change in protection motivation theory construct scores and the change in transtheoretical model stages.
A total of 722 participants were randomly assigned to the intervention or control group. Compared with those who received the nonpersonalized SMS text message intervention, smokers who received the personalized intervention presented lower intrinsic rewards, extrinsic rewards, and response costs. Intrinsic rewards were determinants of stage change, thus explaining why the intervention group was more likely to promote smokers from the preparation stage to the action stage (odds ratio 2.65, 95% CI 1.41-4.98).
This study identified the psychological determinants at different stages to facilitate smokers moving forward to the next stage of quitting behavior and provides a framework to explore why a smoking cessation intervention is effective.
Chinese Clinical Trial Registry ChiCTR2100041942; https://tinyurl.com/2hhx4m7f.

: Chronic cigarette smoking is a major risk factor for many serious diseases. While complete cessation of smoking is the best option to reduce harm from smoking, adverse impacts of smoking on health could persist for several years after cessation. Therefore, Biomarkers of Potential Harm (BoPH) are useful in interim evaluations of the beneficial effects of smoking cessation or switching to potentially lower-risk tobacco products. A 14-day smoking abstinence study was conducted under clinical confinement conditions and enrolled 70 subjects into younger (24-34 years, n = 33) and older (35-60 years, n = 37) age cohorts. Biomarkers of Exposure (BoE), which indicate exposure to nicotine and other toxicants, were measured at baseline, 7 and 14 days. Several BoPH including previously identified eicosanoids (leukotriene 4 (LTE4) and 2,3-dinor thromboxane 2 (2,3-d-TXB2) and others were evaluated. Significant declines in BoE, LTE4, 2,3-d-TXB2, neutrophils, WBC and select RBC, and arterial blood gas parameters were observed in both age cohorts at Days 7 and 14 compared to baseline, while other BoPH (e.g., FeNO) showed age-related effects. Rapid and reproducible reductions in LTE4, 2,3-d-TXB2 WBC, and neutrophil counts were consistently detected following smoking abstinence, indicating the value of these markers as useful BoPH.

Cross-sectional studies have shown that greater cigarette smoking-related emotion regulation expectancies were associated with retrospectively reported withdrawal during prior quit attempts and greater barriers to cessation. Few studies have investigated the relationship of within-person daily emotion regulation expectancies to factors related to initiating and maintaining a brief quit attempt.
People living in California who smoked cigarettes daily (n = 220, 50 % female; 48.5 % white, 14.6 % Hispanic, 16.7 % Black or African American, 9.6 % Asian, 7.6 % Multi-race, 3.0 % other race; mean age=43.71 years old) completed a practice quit attempt and 28-days of daily diary surveys. In the morning, participants reported non-smoking and smoking emotion regulation expectancies based on the Affective Processing Questionnaire, daily abstinence plan, abstinence self-efficacy, and cigarettes smoked. Successful abstinence plans were calculated as days with an abstinence plan and no cigarettes smoked. Multilevel models investigated whether within-person emotion regulation expectancies were associated with abstinence plan, self-efficacy, and successful abstinence plan.
Greater within-person non-smoking emotion regulation expectancies were associated with increased odds of having an abstinence plan, higher self-efficacy, and a successful abstinence plan on a given day (ps < .05). Greater within-person smoking emotion regulation expectancies were associated with lower odds of having an abstinence plan and lower self-efficacy (ps < .001) but did not significantly associate with a successful abstinence plan.
These findings show that within-person levels of expectations in emotion regulation abilities may contribute to factors relevant to initiating and achieving daily abstinence during a practice attempt.

People experiencing severe mental illness report higher rates of tobacco smoking than the general population, while rates of quitting and sustaining abstinence are considerably lower. This systematic review aimed to identify factors associated with sustained abstinence in people experiencing severe mental illness following a smoking intervention.
Searches were conducted in PubMed, PsycInfo, Scopus, Embase, Emcare, CINAHL and Cochrane Library from the inception of the e-databases until June 2022. Selection criteria included randomised and non-randomised studies of smoking cessation interventions in which most of the participants were experiencing severe mental illness, and reported a follow-up of 3 months or longer. From an initial 1498 unique retrieved records, 26 references were included detailing 17 smoking cessation intervention studies and 3 relapse prevention intervention studies. Risk of bias was assessed using the RoB2 tool for randomised study designs and the ROBINS-I tool for non-randomised designs.
Participation in smoking interventions was associated with higher odds of abstinence in the medium-term, but not long-term follow-ups. There was insufficient evidence that any other factors impact sustained abstinence. Most studies were considered to have some risk of bias, largely due to insufficient availability of analysis plans.
Despite an abundance of studies investigating smoking cessation in smokers experiencing severe mental illness, there is limited knowledge on the factors associated with staying quit. The inclusion of people experiencing severe mental illness in large-scale randomised control trials, in which predictors of sustained abstinence are measured in the medium and long term are needed to address this important question.

BACKGROUND: Gamification in smoking cessation apps has been found to improve cognitive outcomes associated with higher odds of quitting. Although some research has shown that gamification can also positively impact behavioral outcomes such as smoking cessation, studies have largely focused on physical activity and mental health. Only a few studies have explored the effects of gamification on smoking cessation outcomes, of which the majority have adopted qualitative methodologies and/or assessed engagement with apps using self-report.
OBJECTIVE: This study aimed to explore levels of user engagement with gamification features in a smoking cessation app via in-app metrics. Specifically, the objective of this paper was to investigate whether higher engagement with gamification features is associated with the likelihood of quitting in the short term.
METHODS: Data from a larger online study that recruited smokers seeking to quit were analyzed to address the objectives presented in this paper. The study took place between June 2019 and July 2020, and participants were primarily recruited via social media posts. Participants who met the eligibility criteria used 1 of 2 mobile apps for smoking cessation. In-app metrics shared by the developer of one of the smoking cessation apps, called Kwit, were used to assess engagement with gamification features. Out of 58 participants who used the Kwit app, 14 were excluded due to missing data or low engagement with the app (ie, not opening the app once a week). For the remaining 44 participants, mean (SD) values were calculated for engagement with the app using in-app metrics. A logistic regression model was used to investigate the association between engagement with gamification and 7-day smoking abstinence.
RESULTS: In total, data from 44 participants who used the Kwit app were analyzed. The majority of participants were male, married, and employed. Almost 30% (n=13) of participants self-reported successful 7-day abstinence at the end of the study. On average, the Kwit app was opened almost 31 (SD 39) times during the 4-week study period, with the diary feature used the most often (mean 22.8, SD 49.3). Moreover, it was found that each additional level unlocked was associated with approximately 22% higher odds of achieving 7-day abstinence after controlling for other factors such as age and gender (odds ratio 1.22, 95% CI 1.01-1.47).
CONCLUSIONS: This study highlights the likely positive effects of certain gamification elements such as levels and achievements on short-term smoking abstinence. Although more robust research with a larger sample size is needed, this research highlights the important role that gamification features integrated into mobile apps can play in facilitating and supporting health behavior change.

The evidence about the association of smoking with both brain structure and cognitive functions remains inconsistent. Using structural magnetic resonance imaging from the UK Biobank (n = 33,293), we examined the relationships between smoking status, dosage, and abstinence with total and 166 regional brain gray matter volumes (GMV). The relationships between the smoking parameters with cognitive function, and whether this relationship was mediated by brain structure, were then investigated. Smoking was associated with lower total and regional GMV, with the extent depending on the frequency of smoking and on whether smoking had ceased: active regular smokers had the lowest GMV (Cohen\'s d = -0.362), and former light smokers had a slightly smaller GMV (Cohen\'s d = -0.060). The smaller GMV in smokers was most evident in the thalamus. Higher lifetime exposure (i.e., pack-years) was associated with lower total GMV (β = -311.84, p = 8.35 × 10-36). In those who ceased smoking, the duration of abstinence was associated with a larger total GMV (β = 139.57, p = 2.36 × 10-08). It was further found that reduced cognitive function was associated with smoker parameters and that the associations were partially mediated by brain structure. This is the largest scale investigation we know of smoking and brain structure, and these results are likely to be robust. The findings are of associations between brain structure and smoking, and in the future, it will be important to assess whether brain structure influences smoking status, or whether smoking influences brain structure, or both.