Effectiveness and cost-effectiveness of a tailored text-message programme (MiQuit) for smoking cessation in pregnancy: study protocol for a randomised controlled trial (RCT) and meta-analysis

The Effectiveness of Text Support for Stopping Smoking in Pregnancy (MiQuit): Multi-Trial Pooled Analysis Investigating Effect Moderators and Mechanisms of Action

INTRODUCTION

Digital cessation support appeals to pregnant smokers. In two pooled RCTs, MiQuit, a pregnancy-specific tailored text messaging intervention, did not show effectiveness for validated prolonged abstinence. However, secondary outcomes and potential moderators and mediators have not been investigated. We aimed to determine, using pooled RCT data: (1) MiQuit effectiveness on a range of smoking outcomes; (2) whether baseline tobacco dependence or quit motivation moderate effectiveness; (3) whether hypothesized mechanisms of action (quitting determination, self-efficacy, baby harm beliefs, lapse prevention strategies) mediate effectiveness.

METHODS

Pooled data analysis from two procedurally identical RCTs comparing MiQuit (N = 704) to usual care (N = 705). Participants were smokers, <25 weeks pregnant, recruited from 40 English antenatal clinics. Outcomes included self-reported 7-day abstinence at 4 weeks post-baseline and late pregnancy, and prolonged abstinence. Late pregnancy outcomes were also biochemically validated. We used hierarchical regression and structural equation modeling.

RESULTS

MiQuit increased self-reported, 7-day abstinence at 4 weeks (OR = 1.73 [95% CI 1.10-2.74]) and was borderline significant at late pregnancy (OR = 1.34 [0.99-1.82]) but not for prolonged or validated outcomes. Effectiveness was not moderated by baseline dependence (heaviness of smoking "low" vs. "moderate-high") or motivation (planning to quit ≤30 days [high] vs. >30 days [low]), but effects on self-reported outcomes were larger for the high motivation sub-group. MiQuit had a small effect on mean lapse prevention strategies (MiQuit 8.6 [SE 0.17], UC 8.1 [SE 0.17]; P = .030) but not other mechanisms.

CONCLUSIONS

MiQuit increased short-term but not prolonged or validated abstinence and may be most effective for those motivated to quit sooner.

IMPLICATIONS

Digital cessation support appeals to pregnant smokers. MiQuit, a tailored, theory-guided text messaging program for quitting smoking in pregnancy, has not shown effectiveness for validated prolonged abstinence in two previous RCTs but its impact on other smoking outcomes and potential mechanisms of action are unknown. When pooling trial data, MiQuit increased self-reported short-term abstinence, including making a quit attempt and abstinence at 4-week follow-up, but not late pregnancy, sustained, or validated abstinence. MiQuit appeared effective at late pregnancy for participants with high quitting motivation, but its mechanisms of action remain uncertain. Additional support components are likely required to enhance effectiveness.

Technology-based interventions for tobacco smoking prevention and treatment: a 20-year bibliometric analysis (2003-2022)

BACKGROUND

Substance abuse, particularly tobacco smoking, is a significant global public health concern. Efforts have been made to reduce smoking prevalence and promote cessation, but challenges, such as nicotine addiction, marketing tactics by tobacco industry, and cultural acceptability hinder progress. Technology has emerged as a potential tool to address these challenges by providing innovative scalable interventions. The objective of the study was to analyze and map scientific literature on technology-based intervention for tobacco prevention and treatment.

METHODS

A bibliometric methodology was conducted. Scopus database was used to retrieve relevant research articles published between 2003 and 2022. The analysis included publication trends, key contributors, research hotspots, research themes, the most impactful articles, and emerging research topics.

RESULTS

A total of 639 articles were found, with a slow and fluctuating growth pattern observed after 2011. The Journal of Medical Internet Research was the most prominent journal in the field. The United States was the leading country in the field, followed up by the United Kingdom, and the Netherlands. Research hotspots included smoking cessation, randomized controlled trials, and technology-based methods such as internet, mHealth, smartphone apps, text messages, and social media. Four primary research themes were identified: development of smartphone applications, efficacy of text messaging interventions, acceptance and effectiveness of smartphone applications, and interventions targeting young adults and students using mobile phone and social media platforms. The top 10 cited articles demonstrated effectiveness of digital interventions in promoting smoking cessation rates and reducing relapse rates. Emerging research topics included the use of virtual reality interventions, interventions for specific populations through personalized tools, and technology-based interventions in non-Western countries.

CONCLUSIONS

The findings of the current study highlight the potential of technology to address the challenges associated with tobacco smoking. Further future research in this area is warranted to continue advancing the field and developing effective and evidence-based interventions to combat tobacco smoking.

Undertaking Studies Within A Trial to evaluate recruitment and retention strategies for randomised controlled trials: lessons learnt from the PROMETHEUS research programme

Background

Randomised controlled trials ('trials') are susceptible to poor participant recruitment and retention. Studies Within A Trial are the strongest methods for testing the effectiveness of strategies to improve recruitment and retention. However, relatively few of these have been conducted.

Objectives

PROMoting THE Use of Studies Within A Trial aimed to facilitate at least 25 Studies Within A Trial evaluating recruitment or retention strategies. We share our experience of delivering the PROMoting THE Use of Studies Within A Trial programme, and the lessons learnt for undertaking randomised Studies Within A Trial.

Design

A network of 10 Clinical Trials Units and 1 primary care research centre committed to conducting randomised controlled Studies Within A Trial of recruitment and/or retention strategies was established. Promising recruitment and retention strategies were identified from various sources including Cochrane systematic reviews, the Study Within A Trial Repository, and existing prioritisation exercises, which were reviewed by patient and public members to create an initial priority list of seven recruitment and eight retention interventions. Host trial teams could apply for funding and receive support from the PROMoting THE Use of Studies Within A Trial team to undertake Studies Within A Trial. We also tested the feasibility of undertaking co-ordinated Studies Within A Trial, across multiple host trials simultaneously.

Setting

Clinical trials unit-based trials recruiting or following up participants in any setting in the United Kingdom were eligible.

Participants

Clinical trials unit-based teams undertaking trials in any clinical context in the United Kingdom.

Interventions

Funding of up to £5000 and support from the PROMoting THE Use of Studies Within A Trial team to design, implement and report Studies Within A Trial.

Main outcome measures

Number of host trials funded.

Results

Forty-two Studies Within A Trial were funded (31 host trials), across 12 Clinical Trials Units. The mean cost of a Study Within A Trial was £3535. Twelve Studies Within A Trial tested the same strategy across multiple host trials using a co-ordinated Study Within A Trial design, and four used a factorial design. Two recruitment and five retention strategies were evaluated in more than one host trial. PROMoting THE Use of Studies Within A Trial will add 18% more Studies Within A Trial to the Cochrane systematic review of recruitment strategies, and 79% more Studies Within A Trial to the Cochrane review of retention strategies. For retention, we found that pre-notifying participants by card, letter or e-mail before sending questionnaires was effective, as was the use of pens, and sending personalised text messages to improve questionnaire response. We highlight key lessons learnt to guide others planning Studies Within A Trial, including involving patient and public involvement partners; prioritising and selecting strategies to evaluate and elements to consider when designing a Study Within A Trial; obtaining governance approvals; implementing Studies Within A Trial, including individual and co-ordinated Studies Within A Trials; and reporting Study Within A Trials.

Limitations

The COVID-19 pandemic negatively impacted five Studies Within A Trial, being either delayed (n = 2) or prematurely terminated (n = 3).

Conclusions

PROMoting THE Use of Studies Within A Trial significantly increased the evidence base for recruitment and retention strategies. When provided with both funding and practical support, host trial teams successfully implemented Studies Within A Trial.

Future work

Future research should identify and target gaps in the evidence base, including widening Study Within A Trial uptake, undertaking more complex Studies Within A Trial and translating Study Within A Trial evidence into practice.

Study registration

All Studies Within A Trial in the PROMoting THE Use of Studies Within A Trial programme had to be registered with the Northern Ireland Network for Trials Methodology Research Study Within A Trial Repository.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 13/55/80) and is published in full in Health Technology Assessment; Vol. 28, No. 2. See the NIHR Funding and Awards website for further award information.

Helping pregnant smokers quit: a multi-centre randomised controlled trial of electronic cigarettes versus nicotine replacement therapy

Background

Some pregnant smokers try e-cigarettes, but effectiveness and safety of such use are unknown.

Objectives

To compare effectiveness and safety of nicotine patches and e-cigarettes in pregnancy.

Design

A pragmatic multi-centre randomised controlled trial.

Setting

Twenty-three hospitals across England, and a Stop Smoking Service in Scotland.

Participants

One thousand one hundred and forty pregnant daily smokers (12-24 weeks' gestation) motivated to stop smoking, with no strong preference for using nicotine patches or e-cigarettes.

Interventions

Participants in the e-cigarette arm were posted a refillable e-cigarette device with two 10 ml bottles of tobacco-flavoured e-liquid (18 mg nicotine). Participants in the nicotine patches arm were posted a 2-week supply of 15 mg/16-hour nicotine patches. Supplies were provided for up to 8 weeks. Participants sourced further supplies themselves as needed. Participants in both arms received support calls prior to their target quit date, on the quit date, and weekly for the next 4 weeks.

Outcome measures

The primary outcome was validated prolonged abstinence at the end of pregnancy. Participants lost to follow-up or not providing biochemical validation were included as non-abstainers. Secondary outcomes included self-reported abstinence at different time points, treatment adherence and safety outcomes.

Results

Only 55% of self-reported abstainers mailed back useable saliva samples. Due to this, validated sustained abstinence rates were low (6.8% vs. 4.4% in the e-cigarettes and nicotine patches arms, respectively, risk ratio = 1.55, 95% confidence interval 0.95 to 2.53; Bayes factor = 2.7). In a pre-specified sensitivity analysis that excluded abstainers using non-allocated products, the difference became significant (6.8% vs. 3.6%, risk ratio = 1.93, 95% confidence interval 1.14 to 3.26; Bayes factor = 10). Almost a third of the sample did not set a target quit date and the uptake of support calls was low, as was the initial product use. At end of pregnancy, 33.8% versus 5.6% of participants were using their allocated product in the e-cigarettes versus nicotine patches arm (risk ratio = 6.01, 95% confidence interval 4.21 to 8.58). Regular use of e-cigarettes in the nicotine patches arm was more common than use of nicotine replacement products in the e-cigarette arm (17.8% vs. 2.8%). Rates of adverse events and adverse birth outcomes were similar in the two study arms, apart from participants in the e-cigarette arm having fewer infants with low birthweight (<2500 g) (9.6% vs. 14.8%, risk ratio = 0.65, 95% confidence interval 0.47 to 0.90; Bayes factor = 10.3).

Limitations

Low rates of validation reduced the study power. A substantial proportion of participants did not use the support on offer sufficiently to test its benefits. Sample size may have been too small to detect differences in less frequent adverse effects.

Conclusions

E-cigarettes were not significantly more effective than nicotine patches in the primary analysis, but when e-cigarettes use in the nicotine patches arm was accounted for, e-cigarettes were almost twice as effective as patches in all abstinence outcomes. In pregnant smokers seeking help, compared to nicotine patches, e-cigarettes are probably more effective, do not pose more risks to birth outcomes assessed in this study and may reduce the incidence of low birthweight.

Future work

Routine monitoring of smoking cessation and birth outcomes in pregnant women using nicotine patches and e-cigarettes and further studies are needed to confirm these results.

Trial registration

This trial is registered as ISRCTN62025374 and Eudract 2017-001237-65.

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 27, No. 13. See the NIHR Journals Library website for further project information.

A methodological framework allows the identification of personomic markers to consider when designing personalized interventions

OBJECTIVES

To develop a methodological framework to identify and prioritize personomic markers (e.g., psychosocial situation, beliefs…) to consider for personalizing interventions and to test in smoking cessation interventions.

STUDY DESIGN AND SETTING

(1) We identified potential personomic markers considered in protocols of personalized interventions, in reviews of predictors of smoking cessation, and in interviews with general practitioners. (2) Physicians, and patient smokers or former smokers selected the markers they considered most relevant during online paired comparison experiments. Data were analyzed with Bradley Terry Luce models.

RESULTS

Thirty-six personomic markers were identified from research evidence. They were evaluated by 795 physicians (median age: 34, IQR [30-38]; 95% general practitioners) and 793 patients (median age: 54, IQR [42-64], 71.4% former smokers) during 11,963 paired comparisons. Physicians identified patients' motivation for quitting (e.g., Prochaska stages), patients' preferences, and patients' fears and beliefs (e.g., concerns about weight gain) as the most relevant elements to personalize smoking cessation. Patients considered their motivation for quitting, smoking behavior (e.g., smoking at home/at work), and tobacco dependence (e.g., Fagerström Test) as the most relevant elements to consider.

CONCLUSION

We provide a methodological framework to prioritize which personomic markers should be considered when developing smoking cessation interventions.

When we shouldn't borrow information from an existing network of trials for planning a new trial

Introduction: To achieve higher power or increased precision for a new trial, methods based on updating network meta-analysis (NMA) have been proposed by researchers. However, this approach could potentially lead to misinterpreted results and misstated conclusions. This work aims to investigate the potential inflation of type I error risk when a new trial is conducted only when, based on a p-value of the comparison in the existing network, a "promising" difference between two treatments is noticed. Methods: We use simulations to evaluate the scenarios of interest. In particular, a new trial is to be conducted independently or depending on the results from previous NMA in various scenarios. Three analysis methods are applied to each simulation scenario: with the existing network, sequential analysis and without the existing network. Results: For the scenario that the new trial will be conducted only when a promising finding (p-value <5%) is indicated by the existing network, the type I error risk increased dramatically (38.5% in our example data) when analyzed with the existing network and sequential analysis. The type I error is controlled at 5% when analyzing the new trial without the existing network. Conclusion: If the intention is to combine a trial result with an existing network of evidence, or if it is expected that the trial will eventually be included in a network meta-analysis, then the decision that a new trial is performed should not depend on a statistically "promising" finding indicated by the existing network.

Electronic cigarettes versus nicotine patches for smoking cessation in pregnancy: a randomized controlled trial

Nicotine replacement therapy, in the form of nicotine patches, is commonly offered to pregnant women who smoke to help them to stop smoking, but this approach has limited efficacy in this population. Electronic cigarettes (e-cigarettes) are also used by pregnant women who smoke but their safety and efficacy in pregnancy are unknown. Here, we report the results of a randomized controlled trial in 1,140 participants comparing refillable e-cigarettes with nicotine patches. Pregnant women who smoked were randomized to e-cigarettes (n = 569) or nicotine patches (n = 571). In the unadjusted analysis of the primary outcome, validated prolonged quit rates at the end of pregnancy in the two study arms were not significantly different (6.8% versus 4.4% in the e-cigarette and patch arms, respectively; relative risk (RR) = 1.55, 95%CI: 0.95-2.53, P = 0.08). However, some participants in the nicotine patch group also used e-cigarettes during the study. In a pre-specified sensitivity analysis excluding abstinent participants who used non-allocated products, e-cigarettes were more effective than patches (6.8% versus 3.6%; RR = 1.93, 95%CI: 1.14-3.26, P = 0.02). Safety outcomes included adverse events and maternal and birth outcomes. The safety profile was found to be similar for both study products, however, low birthweight (<2,500 g) was less frequent in the e-cigarette arm (14.8% versus 9.6%; RR = 0.65, 95%CI: 0.47-0.90, P = 0.01). Other adverse events and birth outcomes were similar in the two study arms. E-cigarettes might help women who are pregnant to stop smoking, and their safety for use in pregnancy is similar to that of nicotine patches. ISRCTN62025374.

Pre-notification and personalisation of text messages to increase questionnaire completion in a smoking cessation pregnancy RCT: an embedded randomised factorial trial

BACKGROUND

Low completion rates of questionnaires in randomised controlled trials can compromise the reliability of the results, so ways to boost questionnaire completion are often implemented. Although there is evidence to suggest that sending a text message to participants increases completion, there is little evidence around the timing or personalisation of these text messages.  Methods:  A two-by-two factorial SWAT (study within a trial) was embedded within the MiQuit-3 trial, looking at smoking cessation within pregnant smokers. Participants who reached their 36-week gestational follow-up were randomised to receive a personalised or non-personalised text message, either one week or one day prior to their follow-up. Primary outcomes were completion rate of questionnaire via telephone. Secondary outcomes included: completion rate via any method, time to completion, and number of attempts to contact required.  Results  In total 194 participants were randomised into the SWAT to receive a text message that was personalised early(n=50), personalised late (n=47), non-personalised early(n=50), or non-personalised late(n=47). There was no evidence that timing of the text message (early: one week before; or late: one day before) had an effect on any of the outcomes. There was evidence that a personalised text message would result in fewer completions compared with a non-personalised text message when data was collected only via the telephone(adjusted OR 0.44, 95% CI 0.22-0.87, p=0.02). However, these results were not significant when looking at completion via any method (adjusted OR 0.61, 95% CI 0.30-1.24, p=0.17). There was no evidence to show that personalisation or not was better for any of the secondary outcomes.  Conclusion  Timing of the text message does not appear to influence the completion of questionnaires. Personalisation of a text message may be detrimental to questionnaire completion, if data is only collected via the telephone - however, more SWATs should be undertaken in this field.

Pre-notification and personalisation of text-messages to retain participants in a smoking cessation pregnancy RCT: an embedded randomised factorial trial

BACKGROUND

Low response rates in randomised controlled trials can compromise the reliability of the results, so ways to boost retention are often implemented. Although there is evidence to suggest that sending a text message to participants increases retention, there is little evidence around the timing or personalisation of these messages.  Methods:  A two-by-two factorial SWAT (study within a trial) was embedded within the MiQuit-3 trial, looking at smoking cessation within pregnant smokers. Participants who reached their 36-week gestational follow-up were randomised to receive a personalised or non-personalised text message, either one week or one day prior to the telephone follow-up. Primary outcomes were completion rate of questionnaire via telephone. Secondary outcomes included: completion rate via any method, time to completion, and number of reminders required.  Results  In total 194 participants were randomised into the SWAT; 50 to personalised early text, 47 to personalised late text, 50 to non-personalised early text, and 47 to non-personalised late text. There was no evidence that timing of the text message (early: one week before; or late: one day before) had an effect on any of the outcomes. There was evidence that a personalised text would result in fewer completions via telephone compared with a non-personalised text (adjusted OR 0.44, 95% CI 0.22-0.87, p=0.02). However, there was no evidence to show that personalisation or not was better for any of the secondary outcomes.  Conclusion  Timing of the text message does not appear to influence the retention of participants. Personalisation of a text message may be detrimental to retention; however, more SWATs should be undertaken in this field.