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Nicotine & Tobacco Research : Official... May 2019Cognitive control (CC)-the ability to regulate attention and memory-plays an important role in a variety of health behaviors, including smoking behavior. In this... (Review)
Review
UNLABELLED
Cognitive control (CC)-the ability to regulate attention and memory-plays an important role in a variety of health behaviors, including smoking behavior. In this theoretical review of the literature, we propose a CC and smoking behavior framework that includes (1) the positive influence of CC on the self-regulation of smoking, (2) nicotine-induced improvements in CC that may indirectly reinforce smoking (including withdrawal reversal effects), and (3) the long-term effects of smoking on the brain that may result in reduced CC. Integration of these literatures suggests that CC contributes to both self-regulation (ie, brake pedal) and nicotine-related reinforcement (ie, gas pedal) amid the catastrophic effects of long-term smoking, which may reduce self-regulatory control over smoking while also enhancing indirect reinforcement. Supportive evidence and limitations of this approach will be presented, as well as ideas for future research directions that may fully examine this multifaceted modeling of CC in relation to smoking behavior.
IMPLICATIONS
There is substantial evidence that CC contributes to self-regulation (ie, brake pedal) and reinforcement (ie, gas pedal) of smoking behavior as well as evidence that long-term smoking may cause reduced CC. The proposed model delineates how these opposing influences of CC may mask the unique contribution of self-regulation and reinforcement in maintaining smoking behavior. Targeting CC for treating nicotine dependence will require more nuanced approaches that consider the independent and combined effects of self-regulation and reinforcement to improve smoking cessation success rates.
Topics: Cognitive Behavioral Therapy; Humans; Reinforcement, Psychology; Self Efficacy; Smoking; Smoking Cessation; Tobacco Use Disorder
PubMed: 29432572
DOI: 10.1093/ntr/nty029 -
Journal of Medical Internet Research Aug 2022There is little consensus regarding effective digital health interventions for diverse populations, which is due in part to the difficulty of quantifying the impact of... (Review)
Review
BACKGROUND
There is little consensus regarding effective digital health interventions for diverse populations, which is due in part to the difficulty of quantifying the impact of various media and content and the lack of consensus on evaluating dosage and outcomes. In particular, digital smoking behavior change intervention is an area where consistency of measurement has been a challenge because of emerging products and rapid policy changes. This study reviewed the contents and outcomes of digital smoking interventions and the consistency of reporting to inform future research.
OBJECTIVE
This study aims to systematically review digital smoking behavior change interventions and evaluate the consistency in measuring and reporting intervention contents, channels, and dose and response outcomes.
METHODS
PubMed, Embase, Scopus, PsycINFO, and PAIS databases were used to search the literature between January and May 2021. General and journal-based searches were combined. All records were imported into Covidence systematic review software (Veritas Health Innovation) and duplicates were removed. Titles and abstracts were screened by 4 trained reviewers to identify eligible full-text literature. The data synthesis scheme was designed based on the concept that exposure to digital interventions can be divided into intended doses that were planned by the intervention and enacted doses that were completed by participants. The intended dose comprised the frequency and length of the interventions, and the enacted dose was assessed as the engagement. Response measures were assessed for behaviors, intentions, and psychosocial outcomes. Measurements of the dose-response relationship were reviewed for all studies.
RESULTS
A total of 2916 articles were identified through a database search. Of these 2916 articles, the title and abstract review yielded 324 (11.11%) articles for possible eligibility, and 19 (0.65%) articles on digital smoking behavior change interventions were ultimately included for data extraction and synthesis. The analysis revealed a lack of prevention studies (0/19, 0%) and dose-response studies (3/19, 16%). Of the 19 studies, 6 (32%) reported multiple behavioral measures, and 5 (23%) reported multiple psychosocial measures as outcomes. For dosage measures, 37% (7/19) of studies used frequency of exposure, and 21% (4/19) of studies mentioned the length of exposure. The assessment of clarity of reporting revealed that the duration of intervention and data collection tended to be reported vaguely in the literature.
CONCLUSIONS
This review revealed a lack of studies assessing the effects of digital media interventions on smoking outcomes. Data synthesis showed that measurement and reporting were inconsistent across studies, illustrating current challenges in this field. Although most studies focused on reporting outcomes, the measurement of exposure, including intended and enacted doses, was unclear in a large proportion of studies. Clear and consistent reporting of both outcomes and exposures is needed to develop further evidence in intervention research on digital smoking behavior change.
Topics: Humans; Internet; Smoking; Text Messaging; Tobacco Smoking
PubMed: 36006682
DOI: 10.2196/38470 -
Frontiers in Public Health 2022To understand the current status of smoking behavior among emergency physicians in China and to explore its determinants.
OBJECTIVES
To understand the current status of smoking behavior among emergency physicians in China and to explore its determinants.
BACKGROUND
The emergency department is considered a more appropriate setting for tobacco interventions. However, the smoking behavior of emergency physicians can reduce the effectiveness of interventions for patient smoking behavior.
METHODS
From July to August 2018, we conducted a structured online questionnaire among Chinese emergency medicine physicians. We used descriptive analysis with binary logistic regression to analyze the current smoking status of Chinese emergency physicians and its determinants.
RESULTS
A total of 10,457 emergency physicians were included in this study. The prevalence of smoking among physicians was 25.35% (with 34.15 and 1.59% among male and female physicians, respectively). Results of logistic regression showed that postgraduate education (OR = 0.52, 95% CI: 0.41-0.66), chief-level title (OR = 0.79, 95% CI: 0.65-0.97), and regular exercise habits (OR = 0.83, 95% CI: 0.76-0.92) were associated with a lower risk of smoking behavior. However, being over 50 years old (OR = 1.71, 95% CI: 1.29-2.27), being fixed-term (OR = 1.25, 95% CI: 1.10-1.42), and having depressive symptoms (OR = 1.43, 95% CI: 1.28-1.61) were associated with a higher risk of smoking.
CONCLUSION
The prevalence of smoking behavior among emergency physicians in China is high. Hospital management could reduce the incidence of smoking behavior among emergency physicians by strengthening smoking cessation training, paying attention to physicians' psychological health, reducing pressure on physicians in fixed-term positions, and encouraging physicians to develop regular exercise habits.
Topics: Male; Female; Humans; Middle Aged; Cross-Sectional Studies; Prevalence; Smoking; Physicians; Emergency Service, Hospital
PubMed: 36324466
DOI: 10.3389/fpubh.2022.980208 -
Nicotine & Tobacco Research : Official... Dec 2017Although studies have suggested that implicit attitudes may predict smoking-related decisions, evidence that changes in implicit attitudes toward smoking are related to...
INTRODUCTION
Although studies have suggested that implicit attitudes may predict smoking-related decisions, evidence that changes in implicit attitudes toward smoking are related to changes in smoking behavior is lacking. Using data from a trial comparing interventions to induce quit attempts among unmotivated smokers, this study examined whether changes in implicit attitudes were associated with quit attempts and cessation after controlling for explicit motivation.
METHODS
Daily smokers recruited from the community completed measures of implicit attitudes (Implicit Association Test) and explicit measure of motivation to smoke at baseline, mid-intervention (week 12 [W12]) and follow-up (week 26 [W26]). Quit attempts and cessation were assessed at follow-up, and cessation was biochemically verified.
RESULTS
As hypothesized, Implicit Association Test scores became more negative from baseline to W12, a change that was sustained at follow-up. Logistic regression analyses in which implicit attitudes were used to predict smoking outcomes revealed that negative changes in implicit attitudes from baseline to W12 and from baseline to W26 were significantly related to quit attempts (OR = 0.71, 95% CI [0.52, 0.97], p < .05 for both) independent of explicit motivation. Negative changes in implicit attitudes from baseline to W26 were significantly related to cessation (OR = 0.50, 95% CI [0.25, 1.00], p < .05).
CONCLUSIONS
Negative changes in implicit attitudes were associated with positive changes in smoking behavior independent of explicit motivation. This result indicates that smoking cessation interventions may be enhanced by incorporating strategies to change implicit attitudes, and that changes in implicit attitudes are also potentially important intervention outcomes.
IMPLICATIONS
Smoking cessation interventions may be improved by going beyond the current focus on explicit psychological constructs and targeting automatic cognitive processes such as implicit attitudes. The results are encouragement to examine how best to manipulate smokers' implicit attitudes as well as to determine the effect on their smoking behavior.
Topics: Attitude to Health; Female; Humans; Male; Middle Aged; Motivation; Smoking; Smoking Cessation
PubMed: 27679606
DOI: 10.1093/ntr/ntw259 -
Public Health Nursing (Boston, Mass.) Nov 2020The recent COVID-19 pandemic may catalyze smoking behavior modification. The purpose of the study was to examine factors associated with reducing smoking exposure during...
OBJECTIVE
The recent COVID-19 pandemic may catalyze smoking behavior modification. The purpose of the study was to examine factors associated with reducing smoking exposure during the COVID-19 outbreak.
DESIGN
Cross-sectional design using the Health Belief Model to develop an online survey distributed throughout Ohio early during the outbreak.
SAMPLE
810 adults in Ohio (77.9% non-smokers, 22.1% current smokers).
MEASUREMENTS
Sociodemographic factors, smoking and behavior changes since the COVID-19 outbreak, and perceived risk of infection were collected. Logistic regression analyses were conducted to determine factors associated with indoor smoking bans and factors associated with desire to quit smoking since the outbreak.
RESULTS
For the overall sample, the odds of indoor smoking bans were significantly associated with never smoked, college education, single-family residence, not living with smokers, and perceived importance of avoiding public places. For smokers, the desire to quit smoking since the COVID-19 outbreak was associated with diabetes and perceived risk of severe infection.
CONCLUSIONS
Identified factors inform residential smoking exposure reduction through indoor smoking bans. Having an increased perceived risk of severe infection among smokers may motivate cessation. Public health nurses can provide accurate and accessible resources for smoking cessation during the COVID-19 pandemic to promote healthy lifestyle modification.
Topics: Adolescent; Adult; COVID-19; Cross-Sectional Studies; Female; Health Belief Model; Health Knowledge, Attitudes, Practice; Humans; Male; Middle Aged; Ohio; Pandemics; Public Health Nursing; Risk Assessment; Smoking; Smoking Cessation; Surveys and Questionnaires; Young Adult
PubMed: 32981125
DOI: 10.1111/phn.12814 -
Preventive Medicine Sep 2019Cross-sectional data reveal that smoking cigarettes is highly prevalent among those who are food insecure. However, there is limited and conflicting evidence concerning... (Comparative Study)
Comparative Study
Cross-sectional data reveal that smoking cigarettes is highly prevalent among those who are food insecure. However, there is limited and conflicting evidence concerning whether causal factors may influence associations of food insecurity with smoking behavior. Additionally, temporality is a core feature of food insecurity that should be considered when examining linkages between food insecurity and health behaviors like smoking cessation. In 2019, data were extracted from waves 2012 and 2014 of the Health and Retirement Study-a representative sample of U.S. adults ≥50. Analyses were limited to those who smoked cigarettes in 2012 (n = 2197). Food insecurity was assessed in 2012 and 2014 to indicate food insecurity transitions: (1) initially food insecure (food insecure in 2012 only); (2) became food insecure (food insecure in 2014 only); (3) remained food insecure (food insecure in 2012 and 2014), and; (4) not food insecure (reference group). Multivariable logistic regression examined odds of smoking cessation in 2014 due to food insecurity transition. Becoming food insecure was associated with a 2.0 (95% confidence interval = 1.1-3.4) higher odds of smoking cessation. Employment loss or retirement (p < 0.020) and diagnosis of a new chronic condition (p = 0.026) were also associated with higher odds of smoking cessation. In older U.S. adults, smoking cessation was associated with decreased spending power and new health problems. Future studies should examine whether findings of this study may be similar among younger adults and; whether those who quit smoking due to food insecurity are more susceptible to relapse than those who quit due to other factors.
Topics: Aged; Cross-Sectional Studies; Female; Food Supply; Humans; Male; Middle Aged; Smoking; Smoking Cessation; Socioeconomic Factors; United States
PubMed: 31325523
DOI: 10.1016/j.ypmed.2019.105784 -
Addictive Behaviors Aug 2018Ambulatory assessment of smoking behavior has greatly advanced our knowledge of the smoking cessation process. The current article first provides a brief overview of... (Review)
Review
Ambulatory assessment of smoking behavior has greatly advanced our knowledge of the smoking cessation process. The current article first provides a brief overview of ecological momentary assessment for smoking cessation and highlights some of the primary advantages and scientific advancements made from this data collection method. Next, a discussion of how certain data collection tools (i.e., smoking topography and carbon monoxide detection) that have been traditionally used in lab-based settings are now being used to collect data in the real world. The second half of the paper focuses on the use of wearable wireless sensors to collect data during the smoking cessation process. Details regarding how these sensor-based technologies work, their application to newer tobacco products, and their potential to be used as intervention tools are discussed. Specific focus is placed on the opportunity to utilize novel intervention approaches, such as Just-In-Time Adaptive Interventions, to intervene upon smoking behavior. Finally, a discussion of some of the current challenges and limitations related to using sensor-based tools for smoking cessation are presented, along with suggestions for future research in this area.
Topics: Ecological Momentary Assessment; Humans; Monitoring, Ambulatory; Smoking; Smoking Cessation
PubMed: 29398067
DOI: 10.1016/j.addbeh.2018.01.018 -
JMIR MHealth and UHealth Feb 2022There are 1.1 billion smokers worldwide, and each year, more than 8 million die prematurely because of cigarette smoking. More than half of current smokers make a... (Observational Study)
Observational Study
BACKGROUND
There are 1.1 billion smokers worldwide, and each year, more than 8 million die prematurely because of cigarette smoking. More than half of current smokers make a serious quit every year. Nonetheless, 90% of unaided quitters relapse within the first 4 weeks of quitting due to the lack of limited access to cost-effective and efficient smoking cessation tools in their daily lives.
OBJECTIVE
This study aims to enable quantified monitoring of ambulatory smoking behavior 24/7 in real life by using continuous and automatic measurement techniques and identifying and characterizing smoking patterns using longitudinal contextual signals. This work also intends to provide guidance and insights into the design and deployment of technology-enabled smoking cessation applications in naturalistic environments.
METHODS
A 4-week observational study consisting of 46 smokers was conducted in both working and personal life environments. An electric lighter and a smartphone with an experimental app were used to track smoking events and acquire concurrent contextual signals. In addition, the app was used to prompt smoking-contingent ecological momentary assessment (EMA) surveys. The smoking rate was assessed based on the timestamps of smoking and linked statistically to demographics, time, and EMA surveys. A Poisson mixed-effects model to predict smoking rate in 1-hour windows was developed to assess the contribution of each predictor.
RESULTS
In total, 8639 cigarettes and 1839 EMA surveys were tracked over 902 participant days. Most smokers were found to have an inaccurate and often biased estimate of their daily smoking rate compared with the measured smoking rate. Specifically, 74% (34/46) of the smokers made more than one (mean 4.7, SD 4.2 cigarettes per day) wrong estimate, and 70% (32/46) of the smokers overestimated it. On the basis of the timestamp of the tracked smoking events, smoking rates were visualized at different hours and were found to gradually increase and peak at 6 PM in the day. In addition, a 1- to 2-hour shift in smoking patterns was observed between weekdays and weekends. When moderate and heavy smokers were compared with light smokers, their ages (P<.05), Fagerström Test of Nicotine Dependence (P=.01), craving level (P<.001), enjoyment of cigarettes (P<.001), difficulty resisting smoking (P<.001), emotional valence (P<.001), and arousal (P<.001) were all found to be significantly different. In the Poisson mixed-effects model, the number of cigarettes smoked in a 1-hour time window was highly dependent on the smoking status of an individual (P<.001) and was explained by hour (P=.02) and age (P=.005).
CONCLUSIONS
This study reported the high potential and challenges of using an electronic lighter for smoking annotation and smoking-triggered EMAs in an ambulant environment. These results also validate the techniques for smoking behavior monitoring and pave the way for the design and deployment of technology-enabled smoking cessation applications.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)
RR2-10.1136/bmjopen-2018-028284.
Topics: Humans; Smokers; Smoking; Smoking Cessation; Surveys and Questionnaires; Tobacco Use Disorder
PubMed: 35179512
DOI: 10.2196/28159 -
Genes Dec 2022There are several established predictors of smoking, but it is unknown if these predictors operate similarly for young and old smokers. We examined clinical data from...
There are several established predictors of smoking, but it is unknown if these predictors operate similarly for young and old smokers. We examined clinical data from the National Lung Screening Trial (NLST) to determine the predictive ability of gender, body mass index (BMI), marital status, and race on smoking behavior, with emphasis on gender interactions. In addition, we validated the self-report of smoking behaviors for a subgroup that had available epigenetic data in the form of cg05575921 methylation. Participants were N=9572 current or former smokers from the NLST biofluids database, age 55-74, minimum of 30 pack years, and mostly White. A subgroup of N=3084 who had DNA were used for the self-report validation analysis. The predictor analysis was based on the larger group and used penalized logistic regression to predict the self-report of being a former or current smoker at baseline. Cg05575921 methylation showed a moderate ability to discriminate among former and current smokers, AUC = 0.85 (95% confidence interval = [0.83, 0.86]). The final selected variables for the prediction model were BMI, gender, BMI by gender, age, divorced (vs. married), education, and race. The gender by BMI interaction was such that males had a higher probability of current smoking for lower BMI, but this switched to females having higher current smoking for overweight to obese. There is evidence that the self-reported smoking behavior in NLST is moderately accurate. The results of the primary analysis are consistent with the general smoking literature, and our results provide additional specificity regarding the gender by BMI interaction. Body weight issues might play a role in smoking cessation for older established smokers in a similar manner as younger smokers. It could be that women have less success with cessation when their BMI increases.
Topics: Male; Humans; Female; Aged; Middle Aged; Self Report; Smoking; Tobacco Smoking; Smoking Cessation; Epigenesis, Genetic
PubMed: 36672765
DOI: 10.3390/genes14010025 -
International Journal of Environmental... Apr 2022The male smoking rate in China declined moderately through the 1990s and early 2000s, but the decline has since stagnated. It is unclear why the decline stalled and...
INTRODUCTION
The male smoking rate in China declined moderately through the 1990s and early 2000s, but the decline has since stagnated. It is unclear why the decline stalled and whether it stalled uniformly across all social strata. Theories that view socioeconomic status as a fundamental cause of health predict that socioeconomic gaps in smoking may widen, but theories emphasizing the cultural context of health behavior cast doubt on the prediction. We investigated changes in the socioeconomic gaps in smoking during recent decades in China.
METHODS
We applied growth-curve models to examine inter- and intra-cohort changes in socioeconomic gaps in male smoking in China using data from a national longitudinal survey spanning 25 years.
RESULTS
We found diverging trends in smoking in men with different education levels among the post-1980 cohorts; for high-education men, smoking participation consistently declined, but for low-education men, the decline stopped and possibly reversed. The stagnation in the decline in overall smoking rate since 2010 was mostly due to the stalling of the decline of smoking among low-education men in the most recent cohorts. The diverging trends were a continuation of a general trend in expanding educational gaps in smoking that emerged in the cohorts born after 1960. Our analysis also identified widening educational gaps over age within each cohort.
CONCLUSION
We identified a long-term widening in educational gaps in smoking in China. An effective way to reduce smoking, social inequality in smoking and possibly health disparities in China is to target the smoking behavior of vulnerable groups.
Topics: China; Educational Status; Humans; Male; Smoking; Socioeconomic Factors; Tobacco Smoking
PubMed: 35457786
DOI: 10.3390/ijerph19084917