Mindfulness for smoking cessation

Smartband-based smoking detection and real-time brief mindfulness intervention: findings from a feasibility clinical trial

BACKGROUND

Smartbands can be used to detect cigarette smoking and deliver real time smoking interventions. Brief mindfulness interventions have been found to reduce smoking.

OBJECTIVE

This single arm feasibility trial used a smartband to detect smoking and deliver brief mindfulness exercises.

METHODS

Daily smokers who were motivated to reduce their smoking wore a smartband for 60 days. For 21 days, the smartband monitored, detected and notified the user of smoking in real time. After 21 days, a 'mindful smoking' exercise was triggered by detected smoking. After 28 days, a 'RAIN' (recognize, allow, investigate, nonidentify) exercise was delivered to predicted smoking. Participants received mindfulness exercises by text message and online mindfulness training. Feasibility measures included treatment fidelity, adherence and acceptability.

RESULTS

Participants (N=155) were 54% female, 76% white non-Hispanic, and treatment starters (n=115) were analyzed. Treatment fidelity cutoffs were met, including for detecting smoking and delivering mindfulness exercises. Adherence was mixed, including moderate smartband use and low completion of mindfulness exercises. Acceptability was mixed, including high helpfulness ratings and mixed user experiences data. Retention of treatment starters was high (81.9%).

CONCLUSIONS

Findings demonstrate the feasibility of using a smartband to track smoking and deliver quit smoking interventions contingent on smoking.

Combining app-based behavioral therapy with electronic cigarettes for smoking cessation: a study protocol for a single-arm mixed-methods pilot trial

BACKGROUND

Cigarette smoking remains a leading cause of preventable illness and death, underscoring the need for effective evidence-based smoking cessation interventions. Nuumi, a novel smoking cessation program integrating a digital behavioral therapy and an electronic cigarette, may provide a solution.

OBJECTIVE

To investigate the initial efficacy, acceptability and psychological outcomes of an evidence-based smoking cessation intervention comprised of a mobile phone app and an electronic cigarette among adults who smoke and who are motivated to quit.

METHODS

A prospective 6-month single-arm mixed-methods pilot study will be conducted. Seventy adults who smoke and who are motivated to quit will be recruited via web-based advertisements and flyers. Participants receive access to an app and an electronic cigarette with pods containing nicotine for temporary use of at least 3 months. The electronic cigarette is coupled with the app via Bluetooth, allowing for tracking of patterns of use. The behavioral therapy leverages evidence-based content informed by cognitive behavioral therapy and mindfulness-informed principles. Web-based self-report surveys will be conducted at baseline, at 4 weeks, at 8 weeks, at 12 weeks, and at 24 weeks post-baseline. Semi-structured interviews will be conducted at baseline and at 12 weeks post-baseline. Primary outcomes will be self-reported 7-day point prevalence abstinence from smoking at 12 weeks and 24 weeks. Secondary outcomes will include other smoking cessation-related outcomes, psychological outcomes, and acceptability of the nuumi intervention. Descriptive analyses and within-group comparisons will be performed on the quantitative data, and content analyses will be performed on the qualitative data. Recruitment for this study started in October 2023.

DISCUSSION

As tobacco smoking is a leading cause of preventable morbidity and mortality, this research addresses one of the largest health burdens of our time. The results will provide insights into the initial efficacy, acceptability, and psychological outcomes of a novel mobile health intervention for smoking cessation. If successful, this pilot may generate an effective intervention supporting adults who smoke to quit smoking. The results will inform feasibility of a future randomized controlled trial. Trial Registration German Clinical Trials Register DRKS00032652, registered 09/15/2023, https://drks.de/search/de/trial/DRKS00032652 .

Automation of systematic reviews of biomedical literature: a scoping review of studies indexed in PubMed

BACKGROUND

The demand for high-quality systematic literature reviews (SRs) for evidence-based medical decision-making is growing. SRs are costly and require the scarce resource of highly skilled reviewers. Automation technology has been proposed to save workload and expedite the SR workflow. We aimed to provide a comprehensive overview of SR automation studies indexed in PubMed, focusing on the applicability of these technologies in real world practice.

METHODS

In November 2022, we extracted, combined, and ran an integrated PubMed search for SRs on SR automation. Full-text English peer-reviewed articles were included if they reported studies on SR automation methods (SSAM), or automated SRs (ASR). Bibliographic analyses and knowledge-discovery studies were excluded. Record screening was performed by single reviewers, and the selection of full text papers was performed in duplicate. We summarized the publication details, automated review stages, automation goals, applied tools, data sources, methods, results, and Google Scholar citations of SR automation studies.

RESULTS

From 5321 records screened by title and abstract, we included 123 full text articles, of which 108 were SSAM and 15 ASR. Automation was applied for search (19/123, 15.4%), record screening (89/123, 72.4%), full-text selection (6/123, 4.9%), data extraction (13/123, 10.6%), risk of bias assessment (9/123, 7.3%), evidence synthesis (2/123, 1.6%), assessment of evidence quality (2/123, 1.6%), and reporting (2/123, 1.6%). Multiple SR stages were automated by 11 (8.9%) studies. The performance of automated record screening varied largely across SR topics. In published ASR, we found examples of automated search, record screening, full-text selection, and data extraction. In some ASRs, automation fully complemented manual reviews to increase sensitivity rather than to save workload. Reporting of automation details was often incomplete in ASRs.

CONCLUSIONS

Automation techniques are being developed for all SR stages, but with limited real-world adoption. Most SR automation tools target single SR stages, with modest time savings for the entire SR process and varying sensitivity and specificity across studies. Therefore, the real-world benefits of SR automation remain uncertain. Standardizing the terminology, reporting, and metrics of study reports could enhance the adoption of SR automation techniques in real-world practice.

A data extraction template for the behaviour change intervention ontology

Background

The Behaviour Change Intervention Ontology (BCIO) aims to improve the clarity, completeness and consistency of reporting within intervention descriptions and evidence synthesis. However, a recommended method for transparently annotating intervention evaluation reports using the BCIO does not currently exist. This study aimed to develop a data extraction template for annotating using the BCIO.

Methods

The BCIO data extraction template was developed in four stages: i) scoping review of papers citing component ontologies within the BCIO, ii) development of a draft template, iii) piloting and revising the template, and iv) dissemination and maintenance of the template.

Results

A prototype data extraction template using Microsoft Excel was developed based on BCIO annotations from 14 papers. The 'BCIO data extraction template v1' was produced following piloting and revision, incorporating a facility for user feedback.

Discussion

This data extraction template provides a single, accessible resource to extract all necessary characteristics of behaviour change intervention scenarios. It can be used to annotate the presence of BCIO entities for evidence synthesis, including systematic reviews. In the future, we will update this template based on feedback from the community, additions of newly published ontologies within the BCIO, and revisions to existing ontologies.

Effect of a mindfulness training app on a cigarette quit attempt: an investigator-blinded, 58-county randomized controlled trial

BACKGROUND

Cigarette smoking is the leading cause of preventable cancers. A majority of the 34 million people who currently smoke report wanting to quit. Mindfulness training apps offer a guided telehealth intervention to foster individuals' behavioral meditation practice. We present the main outcomes of a parallel-group randomized controlled trial that tested app-based mindfulness training vs attention control on smoking behavior.

METHODS

We enrolled adult residents from across California who smoked daily and were willing to make a quit attempt (N = 213). Participants completed daily sessions in 10-minute segments for 14 consecutive days. Participants then started a quit attempt and reported daily smoking for 28 days following the quit date using the timeline follow-back measure.

RESULTS

Seven-day point-prevalence abstinence for each week during the 4-week quit period ranged from 21.8% to 27.7% for app-based mindfulness training and 17.9% to 19.6% for controls. The intention-to-treat sample revealed that app-based mindfulness training outperformed controls on the proportion of abstinence days during the quit period (odds ratio = 2.00, 95% confidence interval = 1.03 to 3.87, P = .041). Although the 7-day point prevalence abstinence for week 4 favored app-based mindfulness training, significance was not reached (odds ratio = 1.65, 95% confidence interval = 0.84 to 3.23, P = .148). The mean number of cigarettes smoked per day among smokers was 4.95 for app-based mindfulness training vs 5.69 for controls (odds ratio = 0.81, 95% confidence interval = 0.71 to 0.92, P = .002), suggesting harm reduction in continued smokers.

CONCLUSION

A mindfulness training app prescribed for 2 weeks leading up to a quit date showed an advantage over controls for total abstinence days and fewer cigarettes smoked in a diverse sample consisting of urban and rural residents. These findings yield implications for the use of apps to reduce exposure to the carcinogenic properties of cigarette smoke.

Effect of exercise intervention on smoking cessation: a meta-analysis

Background: Exercise has emerged as an effective approach to promote individual health and has shown potential in aiding smoking cessation. However, the specific benefits of exercise in smoking cessation remain unclear, and conflicting findings across studies may be attributed to variations in study populations and intervention characteristics. This study aims to conduct a meta-analysis to evaluate the impact of exercise interventions on tobacco dependence in smokers and assess the effectiveness of exercise in facilitating smoking cessation. Methods: A comprehensive search was performed in databases including PubMed, Web of Science, Embase, The Cochrane Library, and Scopus to identify relevant randomized controlled trials published before 30 October 2022. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines were followed during the review process. The quality of evidence (QoE) was assessed with GRADE (grading of recommendations, assessment, development and evaluations) methodology. Results: Acute exercise was found to significantly reduce smoking cravings [MD = -1.84, 95% CI (-2.92, -0.76), p < 0.001; SMD = -1.64, 95% CI (-2.22, -1.05), p < 0.001] and alleviate most withdrawal symptoms in smokers. However, there was no significant difference in the smoking cessation rate between the exercise group and the control group (p > 0.05). Exercise was associated with increased positive mood [SMD = 0.36, 95% CI (0.14, 0.58), p = 0.001] and reduced negative mood in smokers [SMD = -0.26, 95% CI (-0.39, -0.12), p < 0.001]. Conclusion: Acute exercise interventions effectively reduce cravings and withdrawal symptoms in smokers. However, long-term exercise interventions do not significantly improve the smoking cessation rate. Exercise can help reduce negative mood and enhance positive mood in smokers. Smokers with high levels of tobacco dependence may derive less benefit from exercise. Factors such as literature quality, exercise intervention characteristics, and exercise adherence may influence the effectiveness of interventions. Trial registration: This research protocol was registered in the International Prospective Register for Systematic Reviews (PROSPERO https://www.crd.york.ac.uk/PROSPERO/). Registration number: CRD42022326109.

Attitudes and influencing factors associated with smoking cessation: An online cross-sectional survey in China

INTRODUCTION

Quitting smoking, the critical path to reach the global targets of reducing tobacco use, can bring major and immediate health benefits to smokers. Exploring factors that help individuals to quit smoking is of great importance. The present study explored influencing factors on smoking cessation, in order to provide comprehensive reference for tobacco control policies.

METHODS

Ex-smokers and current smokers were recruited online in this cross-sectional survey, from 1 October to 31 November 2022, in China. The observational data were collected using a questionnaire to collect information with respect to sociodemographic characteristics of smokers, attitudes towards smoking cessation, details of smoking cessation, and different potential factors related to smoking cessation through open-ended questions.

RESULTS

A total of 638 smokers from 30 provinces were recruited as eligible respondents, with a mean age of 37.3 ± 11.7 years and a mean smoking history of 15.9 ± 13.7 years. The percentage of males was 92.3%. Of the 638 respondents, only 3.9% had no intention to stop smoking. Among 155 subjects who had quitted smoking successfully, willpower (55.5%) was considered as the most important contributing factor. Among 365 subjects who tried to quit but failed, lack of willpower (28.2%), tobacco dependence (16.2%), influence of surrounding smokers or smoking environments (15.9%), bad moods (9.9%), stress from work or life (7.9%), habits (7.1%), socialization (4.1%), and easy availability of tobacco (2.7%) were considered as the adverse factors leading to failure in quitting smoking.

CONCLUSIONS

Willpower and support from family members were the vital factors that lead to successful smoking cessation. Future tobacco control policies should also focus on addressing withdrawal symptoms and creating smoke-free environments as well as other factors.