Effects of a guided web-based smoking cessation program with telephone counseling: a cluster randomized controlled trial

Efficacy of e-health interventions for smoking cessation management in smokers: a systematic review and meta-analysis

Background

Smoking is one of the major risk factors for shortened lifespan and disability, while smoking cessation is currently the only guaranteed method to reduce the harm caused by smoking. E-health is a field that utilizes information and communication technology to support the health status of its users. The emergence of this digital health approach has provided a new way of smoking cessation support for smokers seeking help, and an increasing number of researchers are attempting to use e-health for a wide range of effective smoking cessation interventions. We conducted a systematic review and meta-analysis of studies that used e-health as a smoking cessation support tool.

Methods

This systematic review and meta-analysis searched the PubMed, Embase, and Cochrane Library databases until December 2022. The included studies were randomized controlled trials (RCTs) comparing the use of e-health interventions and traditional offline smoking cessation care interventions. The primary outcome of the studies was the point smoking cessation rate (7-day and 30-day), and the secondary outcome was sustained smoking cessation rates. Studies were excluded if there was no clear e-health intervention described or if standard-compliant cessation outcomes were not clearly reported. Fixed-effects meta-analysis and meta-regression analyses were performed on the included study data to evaluate the effectiveness of the interventions. The meta-analysis outcome was the risk ratio (RR) and a 95% confidence interval. The study was registered with PROSPERO, CRD42023388667.

Findings

We collectively screened 2408 articles, and ultimately included 39 articles with a total of 17,351 eligible participants, of which 44 studies were included in the meta-analysis. The meta-analysis revealed that compared to traditional smoking cessation interventions, e-health interventions can increase point quit rates (RR 1.86, 95% CI 1.69-2.04) as well as sustained quit rates in the long-term (RR 1.79, 95% CI 1.60-2.00) among smokers. Subgroup analysis showed that text and telephone interventions in e-health significantly improved short-term quit rates for up to 7 days (RR 2.10, 95% CI 1.77-2.48). Website and app interventions also had a positive impact on improving short-term quit rates for up to 7 days (RR 1.74, 95% CI 1.56-1.94). The heterogeneity of the study results was low, demonstrating the significant smoking cessation advantages of e-health interventions.

Interpretation

We have found that personalized e-health interventions can effectively help smokers quit smoking. The diverse remote intervention methods of e-health can provide more convenient options for further customization. Additionally, further follow-up research is needed to evaluate the sustained effectiveness of interventions on smokers' continuous abstinence over a longer period (greater than one year). In the future, e-health can further optimize smoking cessation strategies.

Funding

No funding.

Health Effects of a 12-Week Web-Based Lifestyle Intervention for Physically Inactive and Overweight or Obese Adults: Study Protocol of Two Randomized Controlled Clinical Trials

Web-based lifestyle interventions have attracted considerable research interest. Available evidence on such interventions suggests health-promoting effects, but further research is needed. Therefore, this study aims to investigate short-, medium-, and long-term health effects of a web-based health program ("TK-HealthCoach", TK-HC) offered by a national statutory health insurance fund (Techniker Krankenkasse, TK). The study comprises two randomized controlled clinical trials to evaluate the health goals "Increasing Fitness" (Fclin) and "Losing and Maintaining Weight" (Wclin). A total of n = 186 physically inactive (Fclin) and n = 150 overweight or obese (Wclin) adults will be randomly assigned to a 12-week interactive (TK-HC) or non-interactive web-based health program using permuted block randomization with a 1:1 allocation ratio. Primary outcomes include cardiorespiratory fitness (Fclin) and body weight (Wclin). Secondary outcomes comprise musculoskeletal fitness (Fclin), physical activity and dietary behavior, anthropometry, blood pressure, blood levels, and vascular health (Fclin, Wclin). All outcomes will be measured before and after the 12-week intervention and after a 6- and 12-month follow-up. Additionally, usage behavior data on the health programs will be assessed. Linear mixed models (LMMs) will be used for statistical analysis. Findings of this study will expand the available evidence on web-based lifestyle interventions.

Strategies to improve smoking cessation rates in primary care

BACKGROUND

Primary care is an important setting in which to treat tobacco addiction. However, the rates at which providers address smoking cessation and the success of that support vary. Strategies can be implemented to improve and increase the delivery of smoking cessation support (e.g. through provider training), and to increase the amount and breadth of support given to people who smoke (e.g. through additional counseling or tailored printed materials).

OBJECTIVES

To assess the effectiveness of strategies intended to increase the success of smoking cessation interventions in primary care settings. To assess whether any effect that these interventions have on smoking cessation may be due to increased implementation by healthcare providers.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and trial registries to 10 September 2020.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) and cluster-RCTs (cRCTs) carried out in primary care, including non-pregnant adults. Studies investigated a strategy or strategies to improve the implementation or success of smoking cessation treatment in primary care. These strategies could include interventions designed to increase or enhance the quality of existing support, or smoking cessation interventions offered in addition to standard care (adjunctive interventions). Intervention strategies had to be tested in addition to and in comparison with standard care, or in addition to other active intervention strategies if the effect of an individual strategy could be isolated. Standard care typically incorporates physician-delivered brief behavioral support, and an offer of smoking cessation medication, but differs across studies. Studies had to measure smoking abstinence at six months' follow-up or longer.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. Our primary outcome - smoking abstinence - was measured using the most rigorous intention-to-treat definition available. We also extracted outcome data for quit attempts, and the following markers of healthcare provider performance: asking about smoking status; advising on cessation; assessment of participant readiness to quit; assisting with cessation; arranging follow-up for smoking participants. Where more than one study investigated the same strategy or set of strategies, and measured the same outcome, we conducted meta-analyses using Mantel-Haenszel random-effects methods to generate pooled risk ratios (RRs) and 95% confidence intervals (CIs).

MAIN RESULTS

We included 81 RCTs and cRCTs, involving 112,159 participants. Fourteen were rated at low risk of bias, 44 at high risk, and the remainder at unclear risk. We identified moderate-certainty evidence, limited by inconsistency, that the provision of adjunctive counseling by a health professional other than the physician (RR 1.31, 95% CI 1.10 to 1.55; I2 = 44%; 22 studies, 18,150 participants), and provision of cost-free medications (RR 1.36, 95% CI 1.05 to 1.76; I2 = 63%; 10 studies,7560 participants) increased smoking quit rates in primary care. There was also moderate-certainty evidence, limited by risk of bias, that the addition of tailored print materials to standard smoking cessation treatment increased the number of people who had successfully stopped smoking at six months' follow-up or more (RR 1.29, 95% CI 1.04 to 1.59; I2 = 37%; 6 studies, 15,978 participants). There was no clear evidence that providing participants who smoked with biomedical risk feedback increased their likelihood of quitting (RR 1.07, 95% CI 0.81 to 1.41; I2 = 40%; 7 studies, 3491 participants), or that provider smoking cessation training (RR 1.10, 95% CI 0.85 to 1.41; I2 = 66%; 7 studies, 13,685 participants) or provider incentives (RR 1.14, 95% CI 0.97 to 1.34; I2 = 0%; 2 studies, 2454 participants) increased smoking abstinence rates. However, in assessing the former two strategies we judged the evidence to be of low certainty and in assessing the latter strategies it was of very low certainty. We downgraded the evidence due to imprecision, inconsistency and risk of bias across these comparisons. There was some indication that provider training increased the delivery of smoking cessation support, along with the provision of adjunctive counseling and cost-free medications. However, our secondary outcomes were not measured consistently, and in many cases analyses were subject to substantial statistical heterogeneity, imprecision, or both, making it difficult to draw conclusions. Thirty-four studies investigated multicomponent interventions to improve smoking cessation rates. There was substantial variation in the combinations of strategies tested, and the resulting individual study effect estimates, precluding meta-analyses in most cases. Meta-analyses provided some evidence that adjunctive counseling combined with either cost-free medications or provider training enhanced quit rates when compared with standard care alone. However, analyses were limited by small numbers of events, high statistical heterogeneity, and studies at high risk of bias. Analyses looking at the effects of combining provider training with flow sheets to aid physician decision-making, and with outreach facilitation, found no clear evidence that these combinations increased quit rates; however, analyses were limited by imprecision, and there was some indication that these approaches did improve some forms of provider implementation.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that providing adjunctive counseling by an allied health professional, cost-free smoking cessation medications, and tailored printed materials as part of smoking cessation support in primary care can increase the number of people who achieve smoking cessation. There is no clear evidence that providing participants with biomedical risk feedback, or primary care providers with training or incentives to provide smoking cessation support enhance quit rates. However, we rated this evidence as of low or very low certainty, and so conclusions are likely to change as further evidence becomes available. Most of the studies in this review evaluated smoking cessation interventions that had already been extensively tested in the general population. Further studies should assess strategies designed to optimize the delivery of those interventions already known to be effective within the primary care setting. Such studies should be cluster-randomized to account for the implications of implementation in this particular setting. Due to substantial variation between studies in this review, identifying optimal characteristics of multicomponent interventions to improve the delivery of smoking cessation treatment was challenging. Future research could use component network meta-analysis to investigate this further.

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.

[The prevalence of strategies for cessation of tobacco use in primary health care: an integrative review]

The habit of tobacco use/smoking, which is a major concern of Primary Health Care (PHC), is a serious public health problem and the main avoidable cause of death in the world. The relevance of actions, whose focus is to facilitate the cessation of this habit, motivates the discussion of studies that have different approaches to tackle this issue by seeking to train PHC professionals accordingly. A search was conducted in the Lilacs, MEDLINE and Web of Science databases for recent scientific publications (2010-2015). The key words were combined with Boolean operators and, after analysis of the articles found, 75 are discussed in this article since they have strategies with a higher prevalence in PHC. The conclusion drawn is that the brief or intense individual approach using the 5A method (Transtheoretical Model) is the most widely adopted, as well as bupropion and nicotine replacement patches. The increasing use of hard technology requires new studies that examine their impact on the treatment of smokers. It was clearly revealed that there is a need for health professionals to be better prepared to address the issue with the users, in addition to a lack of stimulus and proper conditions to work in the PHC team directly reflecting scientific advances in clinical practice.

Which eHealth interventions are most effective for smoking cessation? A systematic review

PURPOSE

To synthesize evidence of the effects and potential effect modifiers of different electronic health (eHealth) interventions to help people quit smoking.

METHODS

Four databases (MEDLINE, PsycINFO, Embase, and The Cochrane Library) were searched in March 2017 using terms that included "smoking cessation", "eHealth/mHealth" and "electronic technology" to find relevant studies. Meta-analysis and meta-regression analyses were performed using Mantel-Haenszel test for fixed-effect risk ratio (RR) and restricted maximum-likelihood technique, respectively. Protocol Registration Number: CRD42017072560.

RESULTS

The review included 108 studies and 110,372 participants. Compared to nonactive control groups (eg, usual care), smoking cessation interventions using web-based and mobile health (mHealth) platform resulted in significantly greater smoking abstinence, RR 2.03 (95% CI 1.7-2.03), and RR 1.71 (95% CI 1.35-2.16), respectively. Similarly, smoking cessation trials using tailored text messages (RR 1.80, 95% CI 1.54-2.10) and web-based information and conjunctive nicotine replacement therapy (RR 1.29, 95% CI 1.17-1.43) may also increase cessation. In contrast, little or no benefit for smoking abstinence was found for computer-assisted interventions (RR 1.31, 95% CI 1.11-1.53). The magnitude of effect sizes from mHealth smoking cessation interventions was likely to be greater if the trial was conducted in the USA or Europe and when the intervention included individually tailored text messages. In contrast, high frequency of texts (daily) was less effective than weekly texts.

CONCLUSIONS

There was consistent evidence that web-based and mHealth smoking cessation interventions may increase abstinence moderately. Methodologic quality of trials and the intervention characteristics (tailored vs untailored) are critical effect modifiers among eHealth smoking cessation interventions, especially for web-based and text messaging trials. Future smoking cessation intervention should take advantages of web-based and mHealth engagement to improve prolonged abstinence.

Internet-based interventions for smoking cessation

BACKGROUND

Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide, making the Internet a potential platform to help people quit smoking.

OBJECTIVES

To determine the effectiveness of Internet-based interventions for smoking cessation, whether intervention effectiveness is altered by tailoring or interactive features, and if there is a difference in effectiveness between adolescents, young adults, and adults.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, which included searches of MEDLINE, Embase and PsycINFO (through OVID). There were no restrictions placed on language, publication status or publication date. The most recent search was conducted in August 2016.

SELECTION CRITERIA

We included randomised controlled trials (RCTs). Participants were people who smoked, with no exclusions based on age, gender, ethnicity, language or health status. Any type of Internet intervention was eligible. The comparison condition could be a no-intervention control, a different Internet intervention, or a non-Internet intervention. To be included, studies must have measured smoking cessation at four weeks or longer.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed and extracted data. We extracted and, where appropriate, pooled smoking cessation outcomes of six-month follow-up or more, reporting short-term outcomes narratively where longer-term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI).We grouped studies according to whether they (1) compared an Internet intervention with a non-active control arm (e.g. printed self-help guides), (2) compared an Internet intervention with an active control arm (e.g. face-to-face counselling), (3) evaluated the addition of behavioural support to an Internet programme, or (4) compared one Internet intervention with another. Where appropriate we grouped studies by age.

MAIN RESULTS

We identified 67 RCTs, including data from over 110,000 participants. We pooled data from 35,969 participants.There were only four RCTs conducted in adolescence or young adults that were eligible for meta-analysis.Results for trials in adults: Eight trials compared a tailored and interactive Internet intervention to a non-active control. Pooled results demonstrated an effect in favour of the intervention (RR 1.15, 95% CI 1.01 to 1.30, n = 6786). However, statistical heterogeneity was high (I2 = 58%) and was unexplained, and the overall quality of evidence was low according to GRADE. Five trials compared an Internet intervention to an active control. The pooled effect estimate favoured the control group, but crossed the null (RR 0.92, 95% CI 0.78 to 1.09, n = 3806, I2 = 0%); GRADE quality rating was moderate. Five studies evaluated an Internet programme plus behavioural support compared to a non-active control (n = 2334). Pooled, these studies indicated a positive effect of the intervention (RR 1.69, 95% CI 1.30 to 2.18). Although statistical heterogeneity was substantial (I2 = 60%) and was unexplained, the GRADE rating was moderate. Four studies evaluated the Internet plus behavioural support compared to active control. None of the studies detected a difference between trial arms (RR 1.00, 95% CI 0.84 to 1.18, n = 2769, I2 = 0%); GRADE rating was moderate. Seven studies compared an interactive or tailored Internet intervention, or both, to an Internet intervention that was not tailored/interactive. Pooled results favoured the interactive or tailored programme, but the estimate crossed the null (RR 1.10, 95% CI 0.99 to 1.22, n = 14,623, I2 = 0%); GRADE rating was moderate. Three studies compared tailored with non-tailored Internet-based messages, compared to non-tailored messages. The tailored messages produced higher cessation rates compared to control, but the estimate was not precise (RR 1.17, 95% CI 0.97 to 1.41, n = 4040), and there was evidence of unexplained substantial statistical heterogeneity (I2 = 57%); GRADE rating was low.Results should be interpreted with caution as we judged some of the included studies to be at high risk of bias.

AUTHORS' CONCLUSIONS

The evidence from trials in adults suggests that interactive and tailored Internet-based interventions with or without additional behavioural support are moderately more effective than non-active controls at six months or longer, but there was no evidence that these interventions were better than other active smoking treatments. However some of the studies were at high risk of bias, and there was evidence of substantial statistical heterogeneity. Treatment effectiveness in younger people is unknown.

Feasibility and Acceptability of a Text Message-Based Smoking Cessation Program for Young Adults in Lima, Peru: Pilot Study

BACKGROUND

In Peru's urban communities, tobacco smoking generally starts during adolescence and smoking prevalence is highest among young adults. Each year, many attempt to quit, but access to smoking cessation programs is limited. Evidence-based text messaging smoking cessation programs are an alternative that has been successfully implemented in high-income countries, but not yet in middle- and low-income countries with limited tobacco control policies.

OBJECTIVE

The objective was to assess the feasibility and acceptability of an short message service (SMS) text message-based cognitive behavioral smoking cessation program for young adults in Lima, Peru.

METHODS

Recruitment included using flyers and social media ads to direct young adults interested in quitting smoking to a website where interested participants completed a Google Drive survey. Inclusion criteria were being between ages 18 and 25 years, smoking at least four cigarettes per day at least 6 days per week, willing to quit in the next 30 days, owning a mobile phone, using SMS text messaging at least once in past year, and residing in Lima. Participants joined one of three phases: (1) focus groups and in-depth interviews whose feedback was used to develop the SMS text messages, (2) validating the SMS text messages, and (3) a pilot of the SMS text message-based smoking cessation program to test its feasibility and acceptability among young adults in Lima. The outcome measures included adherence to the SMS text message-based program, acceptability of content, and smoking abstinence self-report on days 2, 7, and 30 after quitting.

RESULTS

Of 639 participants who completed initial online surveys, 42 met the inclusion criteria and 35 agreed to participate (focus groups and interviews: n=12; validate SMS text messages: n=8; program pilot: n=15). Common quit practices and beliefs emerged from participants in the focus groups and interviews informed the content, tone, and delivery schedule of the messages used in the SMS text message smoking cessation program. A small randomized controlled pilot trial was performed to test the program's feasibility and acceptability; nine smokers were assigned to the SMS text message smoking cessation program and six to a SMS text message nutrition program. Participant retention was high: 93% (14/15) remained until day 30 after quit day. In all, 56% of participants (5/9) in the SMS text message smoking cessation program reported remaining smoke-free until day 30 after quit day and 17% of participants (1/6) in the SMS text message nutrition program reported remaining smoke-free during the entire program. The 14 participants who completed the pilot reported that they received valuable health information and approved the delivery schedule of the SMS text messages.

CONCLUSIONS

This study provides initial evidence that a SMS text message smoking cessation program is feasible and acceptable for young adults residing in Lima.

The effectiveness of telephone counselling and internet- and text-message-based support for smoking cessation: results from a randomized controlled trial

AIM

To compare the effectiveness of proactive telephone counselling, reactive telephone counselling and an internet- and text-message-based intervention with a self-help booklet for smoking cessation.

DESIGN

A randomized controlled trial with equal allocation to four conditions: (1) proactive telephone counselling (n = 452), (2) reactive telephone counselling (n = 453), (3) internet- and text-message-based intervention (n = 453) and (4) self-help booklet (control) (n = 452).

SETTING

Denmark.

PARTICIPANTS

Smokers who had participated previously in two national health surveys were invited. Eligibility criteria were daily cigarette smoking, age ≥ 16 years, having a mobile phone and e-mail address.

MEASUREMENTS

Primary outcome was prolonged abstinence to 12 months from the end of the intervention period.

FINDINGS

At 12-month follow-up, higher prolonged abstinence was found in the proactive telephone counselling group compared with the booklet group [7.3 versus 3.6%, odds ratio (OR) = 2.2, 95% confidence interval (CI) = 1.2-4.0]. There was no clear evidence of a difference in prolonged abstinence between the reactive telephone counselling group or the internet-based smoking cessation program and the booklet group: 1.8 versus 3.6%, OR = 0.8, 95% CI = 0.6-1.2 and 5.3 versus 3.6%, OR = 1.6, 95% CI = 0.8-3.0, respectively. In the proactive telephone counselling group, the cost per additional 12-month quitter compared with the booklet group was £644.

CONCLUSIONS

Proactive telephone counselling was more effective than a self-help booklet in achieving prolonged abstinence for 12 months. No clear evidence of an effect of reactive telephone counselling or the internet- and text-message-based intervention was found compared with the self-help booklet.

Systematic review and meta-analysis of Internet interventions for smoking cessation among adults

BACKGROUND

The aim of this systematic review was to determine the effectiveness of Internet interventions in promoting smoking cessation among adult tobacco users relative to other forms of intervention recommended in treatment guidelines.

METHODS

This review followed Cochrane Collaboration guidelines for systematic reviews. Combinations of "Internet," "web-based," and "smoking cessation intervention" and related keywords were used in both automated and manual searches. We included randomized trials published from January 1990 through to April 2015. A modified version of the Cochrane risk of bias assessment tool was used. We calculated risk ratios (RRs) for each study. Meta-analysis was conducted using random-effects method to pool RRs. Presentation of results follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

Forty randomized trials involving 98,530 participants were included. Most trials had a low risk of bias in most domains. Pooled results comparing Internet interventions to assessment-only/waitlist control were significant (RR 1.60, 95% confidence interval [CI] 1.15-2.21, I (2)=51.7%; four studies). Pooled results of largely static Internet interventions compared to print materials were not significant (RR 0.83, 95% CI 0.63-1.10, I (2)=0%; two studies), whereas comparisons of interactive Internet interventions to print materials were significant (RR 2.10, 95% CI 1.25-3.52, I (2)=41.6%; two studies). No significant effects were observed in pooled results of Internet interventions compared to face-to-face counseling (RR 1.35, 95% CI 0.97-1.87, I (2)=0%; four studies) or to telephone counseling (RR 0.95, 95% CI 0.79-1.13, I (2)=0%; two studies). The majority of trials compared different Internet interventions; pooled results from 15 such trials (24 comparisons) found a significant effect in favor of experimental Internet interventions (RR 1.16, 95% CI 1.03-1.31, I (2)=76.7%).

CONCLUSION

Internet interventions are superior to other broad reach cessation interventions (ie, print materials), equivalent to other currently recommended treatment modes (telephone and in-person counseling), and they have an important role to play in the arsenal of tobacco-dependence treatments.

Mobile phone-based interventions for smoking cessation

BACKGROUND

Access to mobile phones continues to increase exponentially globally, outstripping access to fixed telephone lines, fixed computers and the Internet. Mobile phones are an appropriate and effective option for the delivery of smoking cessation support in some contexts. This review updates the evidence on the effectiveness of mobile phone-based smoking cessation interventions.

OBJECTIVES

To determine whether mobile phone-based smoking cessation interventions increase smoking cessation in people who smoke and want to quit.

SEARCH METHODS

For the most recent update, we searched the Cochrane Tobacco Addiction Group Specialised Register in April 2015. We also searched the UK Clinical Research Network Portfolio for current projects in the UK, and the ClinicalTrials.gov register for ongoing or recently completed studies. We searched through the reference lists of identified studies and attempted to contact the authors of ongoing studies. We applied no restrictions on language or publication date.

SELECTION CRITERIA

We included randomised or quasi-randomised trials. Participants were smokers of any age who wanted to quit. Studies were those examining any type of mobile phone-based intervention for smoking cessation. This included any intervention aimed at mobile phone users, based around delivery via mobile phone, and using any functions or applications that can be used or sent via a mobile phone.

DATA COLLECTION AND ANALYSIS

Review authors extracted information on risk of bias and methodological details using a standardised form. We considered participants who dropped out of the trials or were lost to follow-up to be smoking. We calculated risk ratios (RR) and 95% confidence intervals (CI) for each included study. Meta-analysis of the included studies used the Mantel-Haenszel fixed-effect method. Where meta-analysis was not possible, we presented a narrative summary and descriptive statistics.

MAIN RESULTS

This updated search identified 12 studies with six-month smoking cessation outcomes, including seven studies completed since the previous review. The interventions were predominantly text messaging-based, although several paired text messaging with in-person visits or initial assessments. Two studies gave pre-paid mobile phones to low-income human immunodeficiency virus (HIV)-positive populations - one solely for phone counselling, the other also included text messaging. One study used text messages to link to video messages. Control programmes varied widely. Studies were pooled according to outcomes - some providing measures of continuous abstinence or repeated measures of point prevalence; others only providing 7-day point prevalence abstinence. All 12 studies pooled using their most rigorous 26-week measures of abstinence provided an RR of 1.67 (95% CI 1.46 to 1.90; I(2) = 59%). Six studies verified quitting biochemically at six months (RR 1.83; 95% CI 1.54 to 2.19).

AUTHORS' CONCLUSIONS

The current evidence supports a beneficial impact of mobile phone-based smoking cessation interventions on six-month cessation outcomes. While all studies were good quality, the fact that those studies with biochemical verification of quitting status demonstrated an even higher chance of quitting further supports the positive findings. However, it should be noted that most included studies were of text message interventions in high-income countries with good tobacco control policies. Therefore, caution should be taken in generalising these results outside of this type of intervention and context.