Young Adult Utilization of a Smoking Cessation Website: An Observational Study Comparing Young and Older Adult Patterns of Use

Prevalence and predictors of waterpipe smoking cessation among young adults in the US: Findings from a population-based study

BACKGROUND

The prevalence of waterpipe tobacco (WPT) smoking is 9.2 % among young adults aged 18-24 years in the United State (US). Adequate understanding of the factors predicting WPT smoking cessation among the young population is essential to tobacco control efforts. This study assessed the prevalence and predictors of WPT smoking cessation among young adults.

METHODS

The population assessment of tobacco and health (PATH) study data (waves 1-5) was used for the study. A total sample of 561 young adults exclusively using WPT (past 30-days) was used for the analysis. The probability of WPT smoking cessation (no use in the past 12 months) was estimated using the Kaplan-Meier survival method, and the predictors were assessed using the Cox proportional hazards regression model.

RESULTS

During the five waves, 25.1 % of the young adult WPT smokers quit smoking. Among them, 58.2 % were females and the remaining 41.8 % were males. The Hispanics (40.2 %) had the highest rate of cessation among the ethnic groups. Regret smoking (adjusted hazard ratio (aHR) = 2.33, 95 % confidence interval (CI) = 1.24-4.36), smoking restriction at home (aHR = 2.86, 95 % CI = 1.41-5.88), and living in Midwest geographical region (aHR = 2.11, 95 % CI = 1.16-3.84) increased the likelihood whereas alcohol use (aHR = 0.62, 95 % CI = 0.41-0.93) decreased the likelihood of cessation among the young adult WPT smokers.

CONCLUSIONS

Communicating the health and economic consequences associated with WPT smoking (e.g., pictorial health warning labels), involving smoker's household members in WPT awareness campaigns, and closing regulatory loopholes related to WPT venues will increase the WPT smoking cessation rate among the young population in the US.

Older adults who smoke: Do they engage with and benefit from web-based smoking cessation interventions?

Quitting smoking at any age increases life expectancy, but older adults face barriers to receiving cessation services. Despite the promise of web-based smoking cessation interventions to help address access barriers, whether older adults who participate in smoking cessation programs engage with and benefit from these tools at the same rate as younger adults remains unknown. In this secondary analysis, we compared engagement and satisfaction with two web-based smoking cessation interventions and quit rates between older, middle-aged, and young adults in the United States enrolled in the WebQuit trial between March 2014 and August 2015. Participants were divided into age groups: older (60 years and older, n = 439/2637), middle-aged (40-59 years, n = 1308/2637), and young adults (18-39 years, n = 890/2637). Treatment engagement and satisfaction, and 12-month quit rates (self-reported complete-case 30-day PPA and missing-as-smoking) were compared between groups. Older adults engaged more with the websites than young adults through multiple indicators of intervention engagement (i.e., number of sessions, unique days of use, and time spent on the site), and older adults spent more time on the site per session than their counterparts. Satisfaction with websites was high (81%) and non-differential between groups. Older and middle-aged adults quit smoking at a similar rate as younger adults (24%, 24%, 27%, respectively, p = 0.905). Older and middle-aged adults who participated in a web-delivered smoking cessation intervention engaged more with the intervention than their younger counterparts and they quit smoking at a similar rate, thereby demonstrating high acceptability and potential of digital interventions to help older adults quit smoking. Trial registration:ClinicalTrials.gov Identifier: NCT1166334.

Subtypes of smokers in a randomized controlled trial of a web-based smoking cessation program and their role in predicting intervention non-usage attrition: Implications for the development of tailored interventions

INTRODUCTION

Web-based smoking interventions hold potential for smoking cessation; however, many of them report low intervention usage (i.e., high levels of non-usage attrition). One strategy to counter this issue is to tailor such interventions to user subtypes if these can be identified and related to non-usage attrition outcomes. The aim of this study was two-fold: (1) to identify and describe a smoker typology in participants of a web-based smoking cessation program and (2) to explore subtypes of smokers who are at a higher risk for non-usage attrition (i.e., early dropout times).

METHODS

We conducted secondary analyses of data from a large randomized controlled trial (RCT) that investigated effects of a web-based Cognitive Bias Modification intervention in adult smokers. First, we conducted a two-step cluster analysis to identify subtypes of smokers based on participants' baseline characteristics (including demographics, psychological and smoking-related variables, N = 749). Next, we conducted a discrete-time survival analysis to investigate the predictive value of the subtypes on time until dropout.

RESULTS

We found three distinct clusters of smokers: Cluster 1 (25.2%, n = 189) was characterized by participants being relatively young, highly educated, unmarried, light-to-moderate smokers, poly-substance users, and relatively high scores on sensation seeking and impulsivity; Cluster 2 (41.0%, n = 307) was characterized by participants being older, with a relatively high socio-economic status (SES), moderate-to-heavy smokers and regular drinkers; Cluster 3 (33.8%, n = 253) contained mostly females of older age, and participants were further characterized by a relatively low SES, heavy smoking, and relatively high scores on hopelessness, anxiety sensitivity, impulsivity, depression, and alcohol use. Additionally, Cluster 1 was more likely to drop out at the early stage of the intervention compared to Cluster 2 (adjusted Hazard Ratio (HR _adjusted) = 1.51, 95% CI = [1.25, 1.83]) and Cluster 3 (HR _adjusted = 1.52, 95% CI = [1.25, 1.86]).

CONCLUSIONS

We identified three clusters of smokers that differed on a broad range of characteristics and on intervention non-usage attrition patterns. This highlights the heterogeneity of participants in a web-based smoking cessation program. Also, it supports the idea that such interventions could be tailored to these subtypes to prevent non-usage attrition. The subtypes of smokers identified in this study need to be replicated in the field of e-health outside the context of RCT; based on the smoker subtypes identified in this study, we provided suggestions for developing tailored web-based smoking cessation intervention programs in future research.

Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement

Background

Motivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Typically, motivational messaging systems have not actively sought feedback on each message, preventing a closer examination of the user-system engagement. This study assessed the granular user-system engagement around a recommender system (a new system that actively sought user feedback on each message to improve message selection) for promoting smoking cessation and the impact of engagement on cessation outcome.

Methods

We prospectively followed a cohort of current smokers enrolled to use the recommender system for 6 months. The system sent participants motivational messages to support smoking cessation every 3 days and used machine learning to incorporate user feedback (i.e., user’s rating on the perceived influence of each message, collected on a 5-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement on perceiving the influence on quitting smoking) to improve the selection of the following message. We assessed user-system engagement by various metrics, including user response rate (i.e., the percent of times a user rated the messages) and the perceived influence of messages. We compared retention rates across different levels of user-system engagement and assessed the association between engagement and the 7-day point prevalence abstinence (missing outcome = smoking) by using multiple logistic regression.

Results

We analyzed data from 731 participants (13% Black; 73% women). The user response rate was 0.24 (SD = 0.34) and user-perceived influence was 3.76 (SD = 0.84). The retention rate positively increased with the user response rate (trend test P < 0.001). Compared with non-response, six-month cessation increased with the levels of response rates: low response rate (odds ratio [OR] = 1.86, 95% confidence interval [CI]: 1.07–3.23), moderate response rate (OR = 2.30, 95% CI: 1.36–3.88), high response rate (OR = 2.69, 95% CI: 1.58–4.58). The association between perceived message influence and the outcome showed a similar pattern.

Conclusions

High user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation.

Trial registration

Registration Identifier: NCT03224520. Registration date: July 21, 2017.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11803-8.

Real-World Utilization and Outcomes of the Veterans Health Administration's Smoking Cessation Text Message Program

INTRODUCTION

Smoking cessation mobile health (mHealth) programs are effective and have been recommended for integration into health care services but have not been evaluated in real-world health care settings. The Veterans Health Administration, a safety net health care provider, provides health care for 9 million US military veterans. Veterans Health Administration implemented the SmokefreeVET text message program in 2013.

METHODS

A retrospective evaluation of 6153 SmokefreeVET subscribers was conducted. The primary outcome was 30-day self-reported abstinence at 6 months. Secondary outcomes included percentage of opt outs, program completers, and 30-day self-reported abstinence at 3 months.

RESULTS

SmokefreeVET subscribers were on average 47.5 years old and 71.4% male. Smoking cessation medication use was reported by 11.5% of subscribers at the start of their quit attempt and subscribers enrolled in the program for an average of 29 days. Subscribers who were younger, female, and heavier smokers were more likely to opt out of the six-week program early. The abstinence rate for the primary outcome, self-reported 30-day abstinence at 6 months among all subscribers was 3.7%.

CONCLUSIONS

SmokefreeVET enrolled a younger and more female population of subscribers than other studies of veterans interested in tobacco treatment. The mHealth program was generally acceptable to veterans, yet strategies to increase retention may improve completion rates and outcomes. In this real-world setting, nearly half of the mHealth program subscribers combined use of the text program with smoking cessation medication. Further study of the optimal combination of mHealth with smoking cessation treatments is needed.

IMPLICATIONS

mHealth smoking cessation programs can be effectively implemented within real-world health care settings, even in those serving disadvantaged populations. Further research to improve mHealth program efficacy and integration into clinical settings will increase the population-level impact of these effective smoking cessation programs.

Engaging People in Tobacco Prevention and Cessation: Reflecting Back Over 20 Years Since the Master Settlement Agreement

Over the past 20 years, tobacco prevention and cessation efforts have evolved to keep pace with the changing tobacco product landscape and the widespread adoption of digital technologies. In 2019, Truth Initiative was awarded the Society of Behavioral Medicine’s Jessie Gruman Award for Health Engagement in recognition of the major role it has played on both fronts since its inception in 1999. This manuscript reviews the challenges and opportunities that have emerged over the past two decades, the evolving tactics deployed by Truth Initiative to engage people in tobacco prevention and cessation efforts, the approaches used to evaluate those efforts, and key achievements. It concludes with a summary of lessons learned and considerations for tobacco control researchers and practitioners to accelerate their impact on public health.

Cold Turkey and Hot Vapes? A National Study of Young Adult Cigarette Cessation Strategies

INTRODUCTION

Young adults have high smoking rates and low utilization of evidence-based smoking cessation strategies. We investigated smoking cessation intentions, strategy use, and socioeconomic predictors of strategy use among young adult smokers (age 18-24) and compared patterns with those of older adults (age 25-64).

METHODS

We used a population-based sample from the Population Assessment of Tobacco and Health (PATH) study of young adult (n = 1,881) and older adult (n = 6,366) established smokers of conventional cigarettes at Wave 1 (2013-2014), who were surveyed at Wave 2 (2014-2015). Simple regression analysis compared intentions to quit between age groups. Among Wave 1 smokers who reported a Wave 2 quit attempt (young adults [YA] n = 748; older adults [OA] n = 2,068), bivariate and multinomial logistic regression estimated differences in use of behavioral support, pharmacotherapy, product substitution, and unassisted quit attempts. Interaction terms estimated age-group differences in relationships between predictors and cessation strategy use.

RESULTS

Young adults planned to quit on a longer time frame, expressed lower interest in quitting, and were more confident they would be successful, compared with older adults. Young adults were significantly less likely to use pharmacotherapy (adjusted odds ratio: 0.15; confidence interval: 0.09, 0.24; reference: quitting unassisted). Both groups reported using product substitution (YA: 31.6%; OA: 28.5%), primarily with e-cigarettes, more than any evidence-based cessation strategy. Socioeconomic predictors of cessation strategy use did not differ between age groups.

CONCLUSIONS

More research on why young adult smokers underutilize evidence-based cessation support is needed, as are innovative efforts to increase intentions to quit and utilization of cessation assistance.

IMPLICATIONS

Young adulthood is a key transition time for tobacco use, and early cessation substantially reduces the risk of morbidity and mortality from smoking. In the context of high e-cigarette and polytobacco use, this study finds young adults have significantly less intention to quit than older adults and are less likely to use evidence-based cessation strategies to help quit. Innovative methods are needed to increase young adult intentions to quit and use of evidence-based cessation assistance.

Technology-Based Substance Use Interventions: Opportunities for Gender-Transformative Health Promotion

Drawing on data from a scoping review on sex, gender and substance use, this narrative review explores the use of gender-informed and technology-based approaches in substance use prevention and health promotion interventions. With an ever-changing landscape of new technological developments, an understanding of how technology-based interventions can address sex, gender, and intersecting equity considerations related to substance use is warranted. Current technology-based approaches to substance use prevention and health promotion are described and assessed for gender-specific and gender transformative outcomes, and limitations are discussed related to inclusivity, access, confidentiality, and a dearth of research on technological approaches that integrate gender-based analysis. A call for action designed to advance technology-based health promotion, prevention and brief interventions that address gender equity simultaneously with substance use is proposed.

Factors Related to Smoking Status Among Young Adults: An Analysis of Younger and Older Young Adults in Korea

Objectives

Young adulthood represents a critical developmental period during which the use of tobacco may begin or cease. Furthermore, differences in smoking behaviors between younger (aged 18-24 years) and older (aged 25-34 years) young adults may exist. This study aimed to characterize patterns related to current smoking in younger and older young adults.

Methods

This study used data acquired from the Sixth Korea National Health and Nutrition Examination Survey conducted from 2013 to 2014. A total of 2069 subjects were categorized as younger (712 subjects) and older (1357 subjects) young adults. The chi-square test was used to assess the relationships between smoking status and socio-demographic, health-related, and smoking-related factors. Multivariable logistic regression models were constructed to assess the factors affecting current smoking in these age groups.

Results

The current smoking prevalence was 18.3% among the younger young adults and 26.0% among the older young adults. Sex, education level, occupation, perceived health status, alcohol consumption, and electronic cigarette use were related to current smoking in both age groups. Secondhand smoke exposure at home and stress levels showed significant relationships with smoking in younger and older young adults, respectively.

Conclusions

Strong correlations were found between the observed variables and smoking behaviors among young adults. Determining the factors affecting smoking and designing interventions based on these factors are essential for smoking cessation in young adults.

Conversation Within a Facebook Smoking Cessation Intervention Trial For Young Adults (Tobacco Status Project): Qualitative Analysis

Background

Smoking cessation interventions delivered through social media have the potential to engage young people in behavior change.

Objective

The aim of this study was to describe participant-posted messages in a Facebook smoking cessation intervention for young adults to discern support for behavior change.

Methods

We qualitatively analyzed data from the treatment arm of a randomized trial testing the efficacy of the Tobacco Status Project Facebook intervention. Young adults (N=138) aged 18-25 years (female: 81/138, 58.7%; white: 101/138, 73.2%; mean age 21 years) were recruited using Facebook and placed into one of the 15 secret Facebook groups based on readiness-to-quit smoking. Messages posted to groups for 90 consecutive days were tailored to readiness-to-quit: Not Ready (46/138, 33.3%), Thinking (66/138, 47.8%), and Getting Ready (26/138, 18.8%). Groups were randomized to receive up to US $90 for posting or no incentive. Two independent coders conducted open coding of user posts. We considered content by readiness-to-quit group and incentive condition.

Results

There were 4 dominant themes across all groups: coping skills, friends and family, motivation to quit, and benefits of quitting. The dominant themes in Not Ready groups were friends and family (incentive) and motivation to quit (no incentive), whereas coping skills was the dominant theme in Thinking and Getting Ready groups. The expression of themes varied by readiness-to-quit group but not by incentive condition.

Conclusions

Intervention messages tailored to readiness-to-quit appear useful in eliciting the desired responses from young adult smokers, with limited influence by monetary incentive.

Trial Registration

ClinicalTrials.gov NCT02207036; https://clinicaltrials.gov/ct2/show/NCT02207036 (Archived by WebCite at http://www.webcitation.org/722XAEAAz)

A randomized controlled evaluation of the tobacco status project, a Facebook intervention for young adults

AIMS

To test the efficacy of the Tobacco Status Project (TSP) Facebook smoking cessation intervention for young adults relative to referral to an on-line program on biochemically verified 7-day abstinence from smoking.

DESIGN

Two-group parallel randomized controlled trial, comparing TSP (n = 251) to on-line control (n = 249) with follow-up to 12 months.

SETTING

On-line, throughout the United States.

PARTICIPANTS

Young adult cigarette smokers (mean age 21 years; 73% white, 55% female, 87% daily smokers).

INTERVENTIONS AND COMPARATOR

TSP provided private Facebook groups tailored to stage of change to quit smoking, daily contacts, weekly live counseling sessions, and for those ready to quit, six cognitive behavioral therapy counseling sessions. Some TSP groups were assigned randomly to receive a monetary incentive for engagement. Control provided referral to the National Cancer Institute Smokefree.gov website.

MEASUREMENTS

PRIMARY OUTCOME: Biochemically verified 7-day abstinence over 12 months.

SECONDARY OUTCOMES

Post-treatment (3-month) abstinence; reported abstinence, quit attempt, reduction in smoking, readiness to quit smoking over 12 months.

FINDINGS

Verified 7-day abstinence was not significantly different for intervention compared with control over 1 year: month 3 (8.3 versus 3.2%), 6 (6.2 versus 6.0%), and 12 (5.9 versus 10.0%); odds ratio (OR) = 1.07; 95% confidence interval (CI) = 0.23, 4.97; retention = 71%. There was an effect at 3 months (OR = 2.52; CI = 1.56, 4.04; P < 0.0001). There were no 12-month treatment effects for reported abstinence (P = 0.746), reduction in smoking by 50% or more (P = 0.533), likelihood of having made a quit attempt (P = 0.387) or stage of change over time (0.968). Participants in TSP engaged more and rated the intervention more favorably than those in the control condition.

CONCLUSIONS

Compared with referral to a smoking cessation website, a novel USA-focused Facebook smoking cessation intervention did not improve abstinence from smoking over 1 year, but increased abstinence at the end of treatment and was engaging to participants.

Addressing engagement in technology-based behavioural HIV interventions through paradata metrics

PURPOSE OF REVIEW

The goal of this review was to examine how often researchers report participants' online engagement using paradata (i.e. intervention usage metrics) when describing the outcomes of online behavioural HIV prevention and care interventions. We also highlight the utility of paradata collection and analysis in future technology-based trials.

RECENT FINDINGS

We focused on studies indexed on PubMed and published between 1 January 2016 and 31 March 2017 that reported the development and testing of online behavioural interventions for HIV prevention and/or care. Of the 705 extracted citations, six met study criteria.

SUMMARY

Only one study reported paradata reflecting participants' engagement with a technology-based intervention. Researchers should systematically collect and analyse paradata to strengthen the evidence base for technology-based interventions (do they work?), advance the use of behaviour change theory across modalities and platforms (how/why do they work?) and inform reach and scale-up efforts (for whom do they work?). Researchers may also rely on paradata to examine dose-response relationships due to user engagement, to identify replicable core components linked to behaviour change outcomes, to allocate resources judiciously and drive down development costs, and to pool these metrics for use in future meta-analyses.

Engagement and attrition in Internet smoking cessation interventions: Insights from a cross-sectional survey of "one-hit-wonders"

INTRODUCTION

Internet interventions can reach large numbers of individuals. However, low levels of engagement and high rates of follow-up attrition are common, presenting major challenges to evaluation. This study investigated why registrants of an Internet smoking cessation intervention did not return after joining ("one hit wonders"), and explored the impact of graduated incentives on survey response rates and responder characteristics.

METHODS

A sample of "one hit wonders" that registered on a free smoking cessation website between 2014 and 2015 were surveyed. The initial invitation contained no incentive. Subsequent invitations were sent to random subsamples of non-responders from each previous wave offering $25 and $50 respectively. Descriptive statistics characterized respondents on demographic characteristics, reasons for not returning, and length of time since last visit. Differences were investigated with Fisher's Exact tests, Kruskal-Wallis, and logistic regression.

RESULTS

Of 8779 users who received the initial invitation, 132 completed the survey (1.5%). Among those subsequently offered a $25 incentive, 127 (3.7%) responded. Among those offered a $50 incentive, 97 responded (5.7%). The most common reasons endorsed for not returning were being unable to quit (51%), not having enough time (33%), having forgotten about the website (28%), and not being ready to quit (21%). Notably, however, 23% reported not returning because they had successfully quit smoking. Paid incentives yielded a higher proportion of individuals who were still smoking than the $0 incentive (72% vs. 61%). Among $0 and $25 responders, likelihood of survey response decreased with time since registration; the $50 incentive removed the negative effect of time-since-registration on probability of response.

CONCLUSIONS

One third of participants that had disengaged from an Internet intervention reported abstinence at follow-up, suggesting that low levels of engagement are not synonymous with treatment failure in all cases. Paid incentives above $25 may be needed to elicit survey responses, especially among those with longer intervals of disengagement from an intervention.