Exploring features of social support in a Chinese online smoking cessation community: A multidimensional content analysis of user interaction data

Development and psychometric assessment of Health Action Process Approach (HAPA) in terms of smoking cessation among Chinese smokers

The Health Action Process Approach (HAPA) is a two-stage (pre-intentional and post-intentional) behavioral change model that distinguishes between motivation and volition in behavior change process. This study aims to develop HAPA-based assessments for smoking cessation among current smokers. The HAPA-based measures were developed and the draft measures included nine constructs, namely, risk perception in smoking-induced cancer, risk perception in smoking-induced systemic disease, positive outcome expectancy, negative outcome expectancy, self-efficacy in quitting smoking, self-efficacy in maintaining, self-efficacy in re-initiating, quitting planning and coping planning in smoking cessation, with a total of 26 items. A cross-sectional survey was conducted in China in 2022. Principal Component Analysis was used for Exploratory Factor Analysis (EFA). Cronbach's α coefficient was calculated to evaluate the internal consistency. Variables such as severity of smoking addiction were selected to evaluate the correlation between the HAPA scale and these variables. Of the 928 participants, 76.4% (709/928) were male and the median age was 35 years. Five factors were extracted by EFA. The factor loadings of each item were all greater than 0.60, and the cumulative variance contribution rate was 90.15%. The Cronbach's α coefficient of each HAPA-based subscales was 0.929-0.986. The HAPA-based measurements are comprehensive, reliable and valid in the assessment of smokers' smoking cessation cognition, which can be used to guide the design and implementation of intervention and the development of theory.

Environment and social support for smoking cessation among community smokers in Beijing, China

INTRODUCTION

This study investigated the relationship between environment support, social support and smoking cessation, to provide suggestions for the construction of environment and social support for tobacco control.

METHODS

This was a secondary analysis based on two cross-sectional surveys of adult smokers who participated in the six-month community smoking cessation intervention projects in Beijing. The study subjects were divided into a successful group (n=159) and an unsuccessful group (n=253). The status of the environment support, community tobacco exposure, and social support were compared between groups. A structural equation model (SEM) was established for Confirmatory Factor Analysis.

RESULTS

The univariate analysis showed that there were differences in smoking cessation outcomes among smokers with different home tobacco regulations, workplace tobacco regulations and number of smokers in the family. Differences in 6-month smoking reduction were also found with different promotion levels of anti-tobacco messaging and the frequency of smoking events at home. The logistic regression analysis indicated that home tobacco regulations (OR=1.30; 95% CI: 1.00-1.69), workplace tobacco regulations (OR=1.27; 95% CI: 1.05- 1.54), and frequency of smoking events at home (OR=1.15; 95% CI: 1.02-1.29), were associated with smoking cessation. The results of the SEM showed that environment support (β=0.39; 95% CI: 0.05-0.73, p=0.026) and social support (β=0.37; 95% CI: 0.05-0.68, p=0.022) had influence on smoking cessation.

CONCLUSIONS

Environment support and social support are related to smoking cessation. Attention should be paid to the smoking regulations at home and workplace, anti-tobacco messaging, and social support by the family.

TRIAL REGISTRATION

The study was registered on the official website of the China Clinical Trial Registration Center. Identifier: ChiCTR1900024991.

Community and Opinion Leadership Effects on Vaping Discourse: A Network Analysis of Online Reddit Threads

Reddit is a popular hub for discussing vaping. A deeper understanding of the factors that influence this online discourse could inform public health messaging efforts targeting this platform. Using a network analysis framework, we sought to investigate the role of opinion leaders and online communities in facilitating vaping discussions on Reddit. We collected Reddit submissions about vaping posted in May 2021 and used these submissions to generate subreddit-level (N=261) and thread-level (N=8,377) data sets. We coded subreddits into four community categories: 1) Vaping, 2) Substance use, 3) Cessation, and 4) Non-specific. We used sociometric in-degree centrality statistics to identify subreddit opinion leaders. We computed non-parametric ANOVAs and negative binomial regressions to test associations between opinion leadership and subreddit community category variables on subreddit network composition (comprised of subreddit-level network nodes and edges) and the number of commenters on Reddit threads about vaping (thread-level). Subreddit network composition was largely dependent on opinion leaders in Non-specific communities, and less so in Vaping and Substance use communities. At the thread-level, the rate of commenters was higher among threads initiated by opinion leaders than non-opinion leaders (adjusted rate ratio [aRR]=4.84). Furthermore, threads posted in Vaping (aRR=1.64), Substance use (aRR=1.92), and Cessation (aRR=1.21) communities had higher commenter rates than those posted in Non-specific communities. Communities and opinion leaders play a key role in the composition and reach of vaping discussions on Reddit. These findings provide a foundation for public health campaigns and interventions targeting Reddit and perhaps other social media platforms.

Cross-Sectional Associations of Self-Reported Social/Emotional Support and Life Satisfaction with Smoking and Vaping Status in Adults

This study aimed to examine the cross-sectional association of self-reported social/emotional support and life satisfaction with smoking/vaping status in US adults. The study included 47,163 adult participants who self-reported social/emotional support, life satisfaction, and smoking/vaping status in the 2016 and 2017 BRFSS national survey data. We used multivariable weighted logistic regression models to measure the cross-sectional association of self-reported social/emotional support and life satisfaction with smoking/vaping status. Compared to never users, dual users and exclusive smokers were more likely to have low life satisfaction, with an adjusted odds ratio (aOR) = 1.770 (95% confidence interval [CI]: 1.135, 2.760) and an aOR = 1.452 (95% CI: 1.121, 1.880) respectively, especially for the age group 18-34. Exclusive cigarette smokers were more likely to have low life satisfaction compared to ex-smokers (aOR = 1.416, 95% CI: 1.095, 1.831). Exclusive cigarette smokers were more likely to have low social/emotional support (aOR = 1.193, 95% CI: 1.030, 1.381) than never users, especially those aged 65 and above. In addition, exclusive cigarette smokers were more likely to have low social/emotional support than ex-smokers, with an aOR = 1.279 (95% CI: 1.097, 1.492), which is more pronounced among the age group 18-34, as well as 65 and above. Our results suggest that life satisfaction and social/emotional support may play important roles in smoking and vaping, which should be incorporated into behavioral interventions to reduce tobacco use.

A Cost-Effectiveness Analysis of Comprehensive Smoking-Cessation Interventions Based on the Community and Hospital Collaboration

Background

The prevalence of cigarette smoking in China is high and the utilization of smoking cessation clinics is very low. Multicomponent smoking cessation interventions involving community and hospital collaboration have the potential to increase the smoking cessation rate. However, the cost-effectiveness of this intervention model is unknown.

Methods

We conducted a smoking cessation intervention trial in 19 community health service centers in Beijing, China. A cost-effectiveness analysis was performed from a societal perspective to compare three strategies of smoking cessation: no intervention (NI), pharmacological intervention (PI), and comprehensive intervention (CI) (PI plus online health promotion). A Markov model, with a time horizon of 20 years, was used to simulate the natural progression of estimated 10,000 male smokers. A cross-sectional survey was conducted to obtain data on costs and quality-adjusted life years (QALYs) by using the five-level EuroQol-5-dimension (EQ-5D-5L) questionnaire. Probabilistic sensitivity analysis was performed to explore parameters of uncertainty in the model.

Results

A total of 680 participants were included in this study, including 283 in the PI group and 397 in the CI group. After 6 months of follow-up, the smoking cessation rate reached 30.0% in the CI group and 21.2% in the PI group. Using the Markov model, compared with the NI group, the intervention strategies of the PI group and the CI group were found to be cost-effective, with an incremental cost-effectiveness ratio (ICER) of $535.62/QALY and $366.19/QALY, respectively. The probabilistic sensitivity analysis indicated that the CI strategy was always the most cost-effective intervention.

Conclusion

CI for smoking cessation, based in hospital and community in China, is more cost-effective than PI alone. Therefore, this smoking cessation model should be considered to be implemented in healthcare settings.

Assessment of Social Support and Quitting Smoking in an Online Community Forum: Study Involving Content Analysis

Background

A key factor in successfully reducing and quitting smoking, as well as preventing smoking relapse is access to and engagement with social support. Recent technological advances have made it possible for smokers to access social support via online community forums. While community forums associated with smoking cessation interventions are now common practice, there is a gap in understanding how and when the different types of social support identified by Cutrona and Suhr (1992) (emotional, esteem, informational, tangible, and network) are exchanged on such forums. Community forums that entail “superusers” (a key marker of a successful forum), like QuitNow, are ripe for exploring and leveraging promising social support exchanges on these platforms.

Objective

The purpose of this study was to characterize the posts made on the QuitNow community forum at different stages in the quit journey, and determine when and how the social support constructs are present within the posts.

Methods

A total of 506 posts (including original and response posts) were collected. Using conventional content analysis, the original posts were coded inductively to generate categories and subcategories, and the responses were coded deductively according to the 5 types of social support. Data were analyzed using Microsoft Excel software.

Results

Overall, individuals were most heavily engaged on the forum during the first month of quitting, which then tapered off in the subsequent months. In relation to the original posts, the majority of them fit into the categories of sharing quit successes, quit struggles, updates, quit strategies, and desires to quit. Asking for advice and describing smoke-free benefits were the least represented categories. In relation to the responses, encouragement (emotional), compliment (esteem), and suggestion/advice (informational) consistently remained the most prominent types of support throughout all quit stages. Companionship (network) maintained a steady downward trajectory over time.

Conclusions

The findings of this study highlight the complexity of how and when different types of social support are exchanged on the QuitNow community forum. These findings provide directions for how social support can be more strategically employed and leveraged in these online contexts to support smoking cessation.

The reception of support in peer-to-peer online networks: Network position, support solicitation, and support provision in an online asthma caregivers group

This study applies social network analysis and quantitative content analysis to messages exchanged within an online support forum of caregivers of children with chronic asthma to examine how peer-to-peer network positions and personal communication styles (seeking and providing support) impact the reception of social support. Content analysis is used to determine rates of giving and receiving informational and emotional support. Network analysis assesses levels of individual betweenness and closeness centrality in the online network. Relationships between network positions, solicitation strategies, and the provision and reception of informational and emotional support are examined. Betweenness and closeness centrality are associated with improved informational and emotional support. The provision of informational support is also improved by providing descriptions of personal experience. Practical implications for the design and use of online support platforms are discussed.

Support-Seeking Strategies and Social Support Provided in Chinese Online Health Communities Related to COVID-19

Online health communities have become one of the most important means for people to seek social support during the coronavirus 2019 disease (COVID-19) pandemic. This study details content analysis of support-seeking strategies and social support offered on the online forum "Baidu COVID-19bar" across different stages of initial stage as well as during the entire initial stage of the COVID-19 pandemic. The results show that asking for support and disclosing directly were the main strategies used across the different stages and during the entire initial stage. Informational support and emotional support were the most common types sought in the first two stages and the entire initial stage, and informational support was the main type during the decline stage. Furthermore, asking for support was more likely to elicit informational support while disclosing directly was more likely to elicit emotional support. Theoretical and practical implications of the findings are discussed.