Study protocol for a pragmatic randomised controlled trial evaluating efficacy of a smoking cessation e-'Tabac Info Service': ee-TIS trial

[Evaluating population health interventions : The contributions of theory-driven evaluations]

Population health intervention research has been characterized by the deployment of scientific methods designed to produce knowledge on policy and program interventions directly or indirectly involving the health sector, and potentially affecting population health. The proposed solutions encompass a multitude of interventions of variable types, scale, focus and implementation, rendering them particularly complex and difficult to understand. This complexity raises major conceptual and methodological issues because in reality, we assess not an intervention, but rather a set of interventional elements interacting with those specific to the context in which they appear. It is the interactions that produce effects, to the extent that it makes little sense to speak of an intervention, and more sense to consider an interventional system defined by the interactions. To grasp the numerous elements brought into play, it behooves us to amalgamate evaluation paradigms and approaches. In a precise context, theory-driven evaluations are of pronounced interest. This article presents the main principles of this type of evaluation by focusing on its capacity to shed light on the stakes involved in intervention/context interplay, and by putting forward conclusions transferable to population health research.

Understanding the complexity of population health interventions: assessing intervention system theory (ISyT)

Given their inherent complexity, we need a better understanding of what is happening inside the “black box” of population health interventions. The theory-driven intervention/evaluation paradigm is one approach to addressing this question. However, barriers related to semantic or practical issues stand in the way of its complete integration into evaluation designs. In this paper, we attempt to clarify how various theories, models and frameworks can contribute to developing a context-dependent theory, helping us to understand the black box of population health interventions and to acknowledge their complexity. To achieve this goal, we clarify what could be referred to as “theory” in the theory-driven evaluation of the interventional system, distinguishing it from other models, frameworks and classical theories. In order to evaluate the interventional system with a theory-driven paradigm, we put forward the concept of interventional system theory (ISyT), which combines a causal theory and an action model. We suggest that an ISyT could guide evaluation processes, whatever evaluation design is applied, and illustrate this alternative method through different examples of studies. We believe that such a clarification can help to promote the use of theories in complex intervention evaluations, and to identify ways of considering the transferability and scalability of interventions.

Effectiveness of mobile applications to quit smoking: Systematic review and meta-analysis

INTRODUCTION

Tobacco is the leading cause of preventable mortality. The use of mobile phones has grown exponentially, becoming a powerful tool to be used in health care.

METHODS

In order to assess the effectiveness of mobile phones to quit smoking, we have carried out a systematic review and meta-analysis of randomized clinical trials evaluating interventions based on mobile applications for smartphones, that were not a smaller version of the same application, against other types of therapy. To address this, a bibliographic search was carried out in MEDLINE, EMBASE and COCHRANE LIBRARY. To obtain the combined effect, the relative risk and the 95% confidence interval were used. A heterogeneity and sensitivity analysis were also conducted.

RESULTS

A total of nine studies were identified, but five were excluded. Qualitative review was performed with four selected studies, but quantitative analysis was carried out for only three, given the impossibility of calculating the RR in one of the studies. After combining the results, an RR of 0.901 (95% CI: 0.57-1.423) was calculated comparing the effectiveness of mobile applications versus others type of interventions. This measure was robust, as shown by the sensitivity analysis.

CONCLUSIONS

According to the results, it cannot be concluded that apps are effective for quitting tobacco. There are very few clinical trials published evaluating the effectiveness of mobile applications compared to other alternatives. Several clinical trials are still in progress, therefore their results have not been included in the present meta-analysis.

Effectiveness of the e-Tabac Info Service application for smoking cessation: a pragmatic randomised controlled trial

OBJECTIVE

To compare the effectiveness of the mobile e-Tabac Info Service (e-TIS) application (app) for helping adult smokers quit smoking with current practices.

DESIGN

Pragmatic randomised controlled trial with a 1-year follow-up (2017-2018).

SETTING

France, population-wide level.

PARTICIPANTS

2806 adult smokers who wished to quit smoking were recruited via the website of the French National Mandatory Health Insurance fund. Of them, 1400 were randomised to the e-TIS app arm and 1406 were randomised to the current practices arm (control).

INTERVENTION

The app involved personalised interactive contacts that included questionnaires, advice, activities and text messages. All contacts were individually tailored and based on each smoker's progress.In the control group, recommended practices for quitting smoking were described on a non-interactive website.

PRIMARY AND SECONDARY OUTCOMES MEASURES

The primary outcome was 7-day point prevalence abstinence (PPA) at 6 months. The secondary outcomes included continuous abstinence rates at 6 and 12 months, minimum 24-hour point abstinence at 3 months, minimum 30-day point abstinence at 12 months and number and duration of quit attempts.

RESULTS

There was no difference between the e-TIS and control arms for the primary outcome (12.6% vs 13.7% for 7-day PPA at 6 months, p=0.3949, intention-to-treat analysis). However, e-TIS participants with high levels of exposure to the app, which was defined by the completion of at least eight activities or questionnaires, showed higher rates of smoking cessation than the control participants (17.6% vs 12.9% for 7-day PPA at 6 months, p=0.0169, per-protocol analysis).

CONCLUSION

Use of the e-TIS app was not associated with a higher rate of smoking cessation. However, high level of exposure to the e-TIS app may have been more effective than current practices.

TRIAL REGISTRATION NUMBER

NCT02841683.

Mobile phone text messaging and app-based interventions for smoking cessation

BACKGROUND

Mobile phone-based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face-to-face support. In addition, mCessation can be automated and therefore provided affordably even in resource-poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.

OBJECTIVES

To determine whether mobile phone-based smoking cessation interventions increase smoking cessation rates in people who smoke.

SEARCH METHODS

For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.

SELECTION CRITERIA

Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone-based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six-month follow-up.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta-analyses of the most stringent measures of abstinence at six months' follow-up or longer, using a Mantel-Haenszel random-effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.

MAIN RESULTS

This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high-income countries. There was moderate-certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I² = 71%; 13 studies, 14,133 participants). There was also moderate-certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I² = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high- and low-intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I² = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I² = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower-intensity smoking cessation support (either a lower-intensity app or non-app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I² = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that automated text message-based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate-certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.

How do mobile health applications support behaviour changes? A scoping review of mobile health applications relating to physical activity and eating behaviours

OBJECTIVE

The objective of this review was to analyse how researchers conducting studies about mobile health applications (MHApps) effectiveness assess the conditions of this effectiveness.

STUDY DESIGN

A scoping review according to PRIMSA-ScR checklist.

METHODS

We conducted a scoping review of efficacy/effectiveness conditions in high internal validity studies assessing the efficacy of MHApps in changing physical activity behaviours and eating habits. We used the PubMed, Web of Science, SPORTDiscus and PsycINFO databases and processed the review according to the O'Malley and PRISMA-ScR recommendations. We selected studies with high internal validity methodologies (randomised controlled trials, quasi-experimental studies, systematic reviews and meta-analyses), dealing with dietary and/or physical activity behaviours; covering primary, secondary or tertiary prevention and dealing with behaviour change (uptake, maintenance). We excluded articles on MHApps relating to high-level sport and telemedicine. The process for selecting studies followed a set protocol with two authors who independently appraised the studies.

RESULTS

Twenty-two articles were finally selected and analysed. We noted that the mechanisms and techniques to support behaviour changes were poorly reported and studied. There was no explanation of how these MHApps work and how they could be transferred or not. Indeed, the main efficacy conditions reported by authors refer to practical aspects of the tools. Moreover, the issue of social inequalities was essentially reduced to access to the technology (the shrinking access divide), and literacy was poorly studied, even though it is an important consideration in digital prevention. All in all, even when they dealt with behaviours, the evaluations were tool-focused rather than intervention-focused and did not allow a comprehensive assessment of MHApps.

CONCLUSION

To understand the added value of MHApps in supporting behaviour changes, it seems important to draw on the paradigms relating to health technology assessment considering the characteristics of the technologies and on the evaluation of complex interventions considering the characteristics of prevention. This combined approach may help to clarify how these patient-focused MHApps work and is a condition for improved assessment of MHApps in terms of effectiveness, transferability and scalability.

Current challenges in population health intervention research

Population health interventions (PHIs) are generally complex; their results depend on their interaction with the context of their implementation. Moreover, the distinction between intervention and context is arbitrary: we need rather to consider an ‘interventional system’, including both interventional and contextual components. Evaluation must go beyond effectiveness and must include two key research questions: a viability analysis, to verify that the intervention can be routinised in a real-life context; and a theory-based evaluation, to analyse mechanisms and to understand what produces effects among components and their interactions with each other and with the context. PHI research is a question not only of the object but also of perspectives. This means doing research differently, making use of interdisciplinarity and involving stakeholders. Such an approach may contribute to the development, transfer, implementation and scaling-up of innovative interventions.

Mobile Applications for the Treatment of Tobacco Use and Dependence

PURPOSE OF REVIEW

Smoking remains a leading preventable cause of premature death in the world; thus, developing effective and scalable smoking cessation interventions is crucial. This review uses the Obesity-Related Behavioral Intervention Trials (ORBIT) model for early phase development of behavioral interventions to conceptually organize the state of research of mobile applications (apps) for smoking cessation, briefly highlight their technical and theory-based components, and describe available data on efficacy and effectiveness.

RECENT FINDINGS

Our review suggests that there is a need for more programmatic efforts in the development of mobile applications for smoking cessation, though it is promising that more studies are reporting early phase research such as user-centered design. We identified and described the app features used to implement smoking cessation interventions, and found that the majority of the apps studied used a limited number of mechanisms of intervention delivery, though more effort is needed to link specific app features with clinical outcomes. Similar to earlier reviews, we found that few apps have yet been tested in large well-controlled clinical trials, although progress is being made in reporting transparency with protocol papers and clinical trial registration.

SUMMARY

ORBIT is an effective model to summarize and guide research on smartphone apps for smoking cessation. Continued improvements in early phase research and app design should accelerate the progress of research in mobile apps for smoking cessation.

From intervention to interventional system: towards greater theorization in population health intervention research

Background

Population health intervention research raises major conceptual and methodological issues. These require us to clarify what an intervention is and how best to address it.

This paper aims to clarify the concepts of intervention and context and to propose a way to consider their interactions in evaluation studies, especially by addressing the mechanisms and using the theory-driven evaluation methodology.

Main text

This article synthesizes the notions of intervention and context. It suggests that we consider an “interventional system”, defined as a set of interrelated human and non-human contextual agents within spatial and temporal boundaries generating mechanistic configurations – mechanisms – which are prerequisites for change in health. The evaluation focal point is no longer the interventional ingredients taken separately from the context, but rather mechanisms that punctuate the process of change. It encourages a move towards theorization in evaluation designs, in order to analyze the interventional system more effectively. More particularly, it promotes theory-driven evaluation, either alone or combined with experimental designs.

Conclusion

Considering the intervention system, hybridizing paradigms in a process of theorization within evaluation designs, including different scientific disciplines, practitioners and intervention beneficiaries, may allow researchers a better understanding of what is being investigated and enable them to design the most appropriate methods and modalities for characterizing the interventional system. Evaluation methodologies should therefore be repositioned in relation to one another with regard to a new definition of “evidence”, repositioning practitioners’ expertise, qualitative paradigms and experimental questions in order to address the intervention system more profoundly.

[Interventions for smoking cessation in 2018]

Smoking cessation treatments have been proved effective to stop smoking. For pharmacological treatments, nicotine replacement therapies (NRT) as well as bupropion allow to increase 6 month-abstinence rates by more than 80% in comparison with placebo while varenicline prescription doubles success rates in the same conditions. These results mean that for 10 smokers who quit with placebo, 18 are expected to quit with NRT or bupropion and 28 are expected to quit with varenicline. Varenicline is 50% more effective than nicotine patch and 70% more effective than nicotine gum. Nevertheless, a combination including NRT patch and oral nicotine forms is as effective as varenicline, thus leading to encourage the prescription of a combination NRT when NRT are chosen. For these three pharmacological treatments, cardiovascular as well as neuropsychiatric tolerance were not found statistically different from placebo in randomized controlled trials. Yet, bupropion prescription leads to an increasing risk of seizure (1/1000 to 1/1500). For behavioral treatment, motivational interviewing as well as cognitive behavior therapies are been proven to be effective to stop smoking but few smokers have access to this treatment. Smoking cessation mobile application and smartphone application seem to be promising in terms of effectiveness and might be useful to reach more smokers.