The failure to increase social support: it just might be time to stop intervening (and start rigorously observing)

Effectiveness of a Dyadic Buddy App for Smoking Cessation: Randomized Controlled Trial

Background

Tobacco smoking is one of the biggest public health threats. Smartphone apps offer new promising opportunities for supporting smoking cessation in real time. This randomized controlled trial investigated the effectiveness of an app that encourages individuals to quit smoking with the help of a social network member (buddy) in daily life.

Objective

The objective of this study is to test the effectiveness of the SmokeFree buddy app compared with a control group with self-reported smoking abstinence and carbon monoxide (CO)–verified smoking abstinence as primary outcomes and self-reports of smoked cigarettes per day (CPD) as a secondary outcome.

Methods

A total of 162 adults who smoked participated in this single-blind, two-arm, parallel-group, intensive longitudinal randomized controlled trial. Around a self-set quit date (ie, 7 days before the self-set quit date and 20 days after) and 6 months later, participants of the intervention and control groups reported on daily smoking abstinence and CPD in end-of-day diaries. Daily smoking abstinence was verified via daily exhaled CO assessments. This assessment was administered via an app displaying results of exhaled CO, thus addressing self-monitoring in both groups. In addition, participants in the intervention group used the SmokeFree buddy app, a multicomponent app that facilitates social support from a buddy of choice.

Results

A significant reduction in CPD from baseline to the 6-month follow-up was observed among participants in both groups. Multilevel analyses revealed no significant intervention effect on self-reported and CO-verified daily smoking abstinence at the quit date and 3 weeks later. However, CPD was lower at the quit date and 3 weeks later in the intervention group than in the control group. No significant differences between groups were found for any outcome measures 6 months after the quit date. Overall, low app engagement and low perceived usefulness were observed.

Conclusions

Despite some encouraging short-term findings on the amount of smoking, the SmokeFree buddy app did not have beneficial effects on smoking abstinence over and above the self-monitoring control condition. Future studies should examine whether and what support processes can be effectively stimulated and how app use can be improved to better achieve this goal.

Trial Registration

ISRCTN Registry 11154315; https://www.isrctn.com/ISRCTN11154315

International Registered Report Identifier (IRRID)

RR2-10.1186/s12889-019-7723-z

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.

Optimizing Text Messages to Promote Engagement With Internet Smoking Cessation Treatment: Results From a Factorial Screening Experiment

BACKGROUND

Smoking remains a leading cause of preventable death and illness. Internet interventions for smoking cessation have the potential to significantly impact public health, given their broad reach and proven effectiveness. Given the dose-response association between engagement and behavior change, identifying strategies to promote engagement is a priority across digital health interventions. Text messaging is a proven smoking cessation treatment modality and a powerful strategy to increase intervention engagement in other areas of health, but it has not been tested as an engagement strategy for a digital cessation intervention.

OBJECTIVE

This study examined the impact of 4 experimental text message design factors on adult smokers' engagement with an internet smoking cessation program.

METHODS

We conducted a 2×2×2×2 full factorial screening experiment wherein 864 participants were randomized to 1 of 16 experimental conditions after registering with a free internet smoking cessation program and enrolling in its automated text message program. Experimental factors were personalization (on/off), integration between the web and text message platforms (on/off), dynamic tailoring of intervention content based on user engagement (on/off), and message intensity (tapered vs abrupt drop-off). Primary outcomes were 3-month measures of engagement (ie, page views, time on site, and return visits to the website) as well as use of 6 interactive features of the internet program. All metrics were automatically tracked; there were no missing data.

RESULTS

Main effects were detected for integration and dynamic tailoring. Integration significantly increased interactive feature use by participants, whereas dynamic tailoring increased the number of features used and page views. No main effects were found for message intensity or personalization alone, although several synergistic interactions with other experimental features were observed. Synergistic effects, when all experimental factors were active, resulted in the highest rates of interactive feature use and the greatest proportion of participants at high levels of engagement. Measured in terms of standardized mean differences (SMDs), effects on interactive feature use were highest for Build Support System (SMD 0.56; 95% CI 0.27 to 0.81), Choose Quit Smoking Aid (SMD 0.38; 95% CI 0.10 to 0.66), and Track Smoking Triggers (SMD 0.33; 95% CI 0.05 to 0.61). Among the engagement metrics, the largest effects were on overall feature utilization (SMD 0.33; 95% CI 0.06 to 0.59) and time on site (SMD 0.29; 95% CI 0.01 to 0.57). As no SMD >0.30 was observed for main effects on any outcome, results suggest that for some outcomes, the combined intervention was stronger than individual factors alone.

CONCLUSIONS

This factorial experiment demonstrates the effectiveness of text messaging as a strategy to increase engagement with an internet smoking cessation intervention, resulting in greater overall intervention dose and greater exposure to the core components of tobacco dependence treatment that can promote abstinence.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02585206; https://clinicaltrials.gov/ct2/show/NCT02585206.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2015-010687.

Enhancing partner support to improve smoking cessation

BACKGROUND

While many cessation programmes are available to assist smokers in quitting, research suggests that support from individual partners, family members, or 'buddies' may encourage abstinence.

OBJECTIVES

To determine if an intervention to enhance one-to-one partner support for smokers attempting to quit improves smoking cessation outcomes, compared with cessation interventions lacking a partner-support component.

SEARCH METHODS

We limited the search to the Cochrane Tobacco Addiction Group Specialised Register, which was updated in April 2018. This includes the results of searches of the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE (via OVID); Embase (via OVID); and PsycINFO (via OVID). The search terms used were smoking (prevention, control, therapy), smoking cessation and support (family, marriage, spouse, partner, sexual partner, buddy, friend, cohabitant and co-worker). We also reviewed the bibliographies of all included articles for additional trials.

SELECTION CRITERIA

We included randomised controlled trials recruiting people who smoked. Trials were eligible if they had at least one treatment arm that included a smoking cessation intervention with a partner-support component, compared to a control condition providing behavioural support of similar intensity, without a partner-support component. Trials were also required to report smoking cessation at six months follow-up or more.

DATA COLLECTION AND ANALYSIS

Two review authors independently identified the included studies from the search results, and extracted data using a structured form. A third review author helped resolve discrepancies, in line with standard methodological procedures expected by Cochrane. Smoking abstinence, biochemically verified where possible, was the primary outcome measure and was extracted at two post-treatment intervals where possible: at six to nine months and at 12 months or longer. We used a random-effects model to pool risk ratios from each study and estimate a summary effect.

MAIN RESULTS

Our update search identified 465 citations, which we assessed for eligibility. Three new studies met the criteria for inclusion, giving a total of 14 included studies (n = 3370). The definition of partner varied among the studies. We compared partner support versus control interventions at six- to nine-month follow-up and at 12 or more months follow-up. We also examined outcomes among three subgroups: interventions targeting relatives, friends or coworkers; interventions targeting spouses or cohabiting partners; and interventions targeting fellow cessation programme participants. All studies gave self-reported smoking cessation rates, with limited biochemical verification of abstinence. The pooled risk ratio (RR) for abstinence was 0.97 (95% confidence interval (CI) 0.83 to 1.14; 12 studies; 2818 participants) at six to nine months, and 1.04 (95% CI 0.88 to 1.22; 7 studies; 2573 participants) at 12 months or more post-treatment. Of the 11 studies that measured partner support at follow-up, only two reported a significant increase in partner support in the intervention groups. One of these studies reported a significant increase in partner support in the intervention group, but smokers' reports of partner support received did not differ significantly. We judged one of the included studies to be at high risk of selection bias, but a sensitivity analysis suggests that this did not have an impact on the results. There were also potential issues with detection bias due to a lack of validation of abstinence in five of the 14 studies; however, this is not apparent in the statistically homogeneous results across studies. Using the GRADE system we rated the overall quality of the evidence for the two primary outcomes as low. We downgraded due to the risk of bias, as we judged studies with a high weighting in analyses to be at a high risk of detection bias. In addition, a study in both analyses was insufficiently randomised. We also downgraded the quality of the evidence for indirectness, as very few studies provided any evidence that the interventions tested actually increased the amount of partner support received by participants in the relevant intervention group.

AUTHORS' CONCLUSIONS

Interventions that aim to enhance partner support appear to have no impact on increasing long-term abstinence from smoking. However, most interventions that assessed partner support showed no evidence that the interventions actually achieved their aim and increased support from partners for smoking cessation. Future research should therefore focus on developing behavioural interventions that actually increase partner support, and test this in small-scale studies, before large trials assessing the impact on smoking cessation can be justified.

A prospective examination of online social network dynamics and smoking cessation

Introduction

Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual’s number of social network ties are prospectively related to abstinence in an online social network for cessation. In a network where quitting is normative and is the focus of communications among members, we predicted that an increasing number of ties would be positively associated with abstinence.

Method

Participants were N = 2,657 adult smokers recruited to a randomized cessation treatment trial following enrollment on BecomeAnEX.org, a longstanding Internet cessation program with a large and mature online social network. At 3-months post-randomization, 30-day point prevalence abstinence was assessed and website engagement metrics were extracted. The social network was constructed with clickstream data to capture the flow of information among members. Two network centrality metrics were calculated at weekly intervals over 3 months: 1) in-degree, defined as the number of members whose posts a participant read; and 2) out-degree-aware, defined as the number of members who read a participant’s post and commented, which was subsequently viewed by the participant. Three groups of users were identified based on social network engagement patterns: non-users (N = 1,362), passive users (N = 812), and active users (N = 483). Logistic regression modeled 3-month abstinence by group as a function of baseline variables, website utilization, and network centrality metrics.

Results

Abstinence rates varied by group (non-users = 7.7%, passive users = 10.7%, active users = 20.7%). Significant baseline predictors of abstinence were age, nicotine dependence, confidence to quit, and smoking temptations in social situations among passive users (ps < .05); age and confidence to quit among active users. Among centrality metrics, positive associations with abstinence were observed for in-degree increases from Week 2 to Week 12 among passive and active users, and for out-degree-aware increases from Week 2 to Week 12 among active users (ps < .05).

Conclusions

This study is the first to demonstrate that increased tie formation among members of an online social network for smoking cessation is prospectively associated with abstinence. It also highlights the value of using individuals’ activities in online social networks to predict their offline health behaviors.