Summary of findings
In much of the developed world, the prevalence of smoking amongst young people has been falling over the last 20 years. Recent figures from the UK show that for 11 to 15 year olds, 25% had tried smoking at least once, the lowest figure since 1982, when the figure was 53%. Currently, around 5% of 11 to 15 year olds are smoking regularly (one cigarette per week or more), roughly half the proportion doing so in 2001 (NHSIC 2011). A similar decline has been noted in the United States, although the rate of decline has levelled off in recent years, attributed to the withdrawal of funding for programmes; in 2011, 25% of high school males and 17% of females smoked tobacco (MMWR 2012). In developing economies the picture is less clear cut, with wide variation and often higher rates of smoking in young people (Eriksen 2012). The incidence of the initiation of smoking first becomes measurable in the 10 to 12 year age range (ONS 2000), and most adult smokers acquired the habit in teenage years (NHSIC 2012). However, there is evidence that within a short time of commencing many teenage smokers want to quit (Burt 1998; Hu 1998; Sussman 1998; Stanton 2001; MMWR 2009). Frequent quit attempts are reported in this population (Stanton 2001; MMWR 2009).
Although the major burden of disease caused by smoking falls on the adult population, there are several reasons why those charged with promoting child health should be active in tobacco control at an appropriate level. Firstly, the vast majority of smokers acquire the habit in childhood and young smokers suffer impairment of lung function and lung growth (NHSIC 2012). There is evidence that those who start earliest have greatest difficulty in quitting, and that they may be more susceptible to disease in adulthood. There is also growing evidence that addiction to nicotine can develop very rapidly in young smokers, making quitting difficult (DiFranza 2008). The tobacco industry have long been aware of the need to replace adult smokers with new young recruits, and there is now strong evidence of the effect that all advertising, including that at point of sale, has on encouraging young people to smoke (CPHTP 2012).
An additional cause for concern is that smoking may be a particular problem in young people with mental health or behavioural problems. In the UK, smoking rates among 11 to 15 year olds were 30% in those with conduct disorder, 19% in those with emotional disorder, and 15% in those with attention deficit hyperactivity disorder (ADHD) compared to 5% in those without such disorders (Green 2004; Geeta 2012).There is now strong evidence that the relationship is causal with respect to depression (Boden 2010), whilst for ADHD molecular genetics would seem to play a role.
There is now a large literature on smoking cessation services for adults. This is reflected in a number of Cochrane reviews examining several aspects of the subject in detail. Many countries have developed appropriate services for adults. However, whilst some have suggested that similar services, suitably modified, should be considered for young people (Raw 1998), this assertion is open to challenge in view of the difference in smoking pattern, lifestyle and attitudes to services in this age group (TAG 2000). Previous reviews of adolescent smoking cessation have been published (Sussman 1999; Sussman 2002; McDonald 2003; Sussman 2006; Patnode 2013); this is the second update of the first Cochrane review to focus on smoking cessation in young people under 20 years. A further systematic review has looked at strategies for smoking cessation for university age smokers (Villanti 2010). The paucity of high quality research evidence to answer important clinical questions is a recurrent theme of reviews in this area.
Other Cochrane reviews of interventions relevant to tobacco addiction amongst young people have mainly focused on primary prevention. These include a review of school-based prevention programmes (Thomas 2012), and reviews of mass media interventions (Brinn 2010), community interventions (Carson 2011), interventions for reducing access by preventing illegal sale of tobacco (Stead 2005), prevention in indigenous youth (Carson 2012), and school smoking policies (Coppo 2012). This review looks at strategies for smoking cessation in young people and more specifically at the context in which the interventions are offered, and how young people are enrolled into quit attempts.
To evaluate the effectiveness of strategies that help young people to stop smoking tobacco.
Criteria for considering studies for this review
Types of studies
Eligible study designs include:
a) Randomized controlled trials (RCTs)
Studies in which individuals, classes, schools, units or groups were randomized to either the intervention or the control arm of the experiment, or randomized to receive different interventions.
b) Cluster-randomized controlled trials (C-RCTs)
Trials that have as the unit of allocation a school or organization level, or where clusters of professionals or groups of professionals are implementing interventions.
c) Controlled trials
We include trials that allocate individuals or units to intervention and control conditions without formal randomization if baseline characteristics were assessed and were comparable. We have assessed the sensitivity of our conclusions to the inclusion of evidence from non-randomized studies.
Types of participants
Participants are young people, aged less than 20, who are regular tobacco smokers. As there is evidence that some young people have an irregular pattern of smoking, for example smoking only at weekends (Grimshaw 2003) or weekly (O'Loughlin 2003), we define a regular smoker in this review as a young person who smokes an average of at least one cigarette a week, and has done so for at least six months. Trials which target young people who smoke less than this were excluded.
If a study included participants beyond our top threshold of 20
The intervention may also be aimed at the organization to which the young person is attached. If so, the study design must demonstrate suitable control for differences in the two groups. Only studies with an outcome related to the individual smoker are included.
We exclude from this review Interventions specifically targeting young women in pregnancy, since this topic is covered by the Pregnancy and Childbirth Group (Coleman 2012; Lumley 2009). We also exclude any programme aimed primarily at the adult population, and have contacted investigators where there was a lack of clarity on this issue.
Types of interventions
Interventions could be specifically designed to meet the needs of young people aged under 20 years, or could also be applicable to adults. Interventions could range from simple ones such as pharmacotherapy, targeting individual young people, through strategic programmes targeting people or organizations associated with young people (for example, their families or schools), to complex programmes targeting the community in which young people study or live. We differentiated between these in the analyses.
To be included, all interventions had to be aimed at helping young people to stop smoking tobacco. We included cessation programmes or strategies that also targeted relapse. We included programmes or strategies that targeted psycho-social determinants (for example, enhancing self efficacy for refusing tobacco), or that focused on developing life skills in order to stay abstinent, if the study design was appropriate. No restrictions were placed on the setting in which the intervention was offered (for example, school, hospital, doctor's surgery, or dentist).
Smoking prevention programmes were excluded, even if they reported cessation data, as they have been the subject of previous reviews (Brinn 2010; Carson 2011; Thomas 2012). Within large-scale community primary prevention interventions, health education programmes/curricula or mass media campaigns that target young people, we only considered for inclusion the cessation component of those programmes where the following three criteria were met: that part of the intervention had been specifically designed to target cessation; that the interventions could be separately assessed; and that the interventions explicitly met the criteria of this review for study design and recruitment.
Interventions in the control arm of the study could be one of the following:
- no intervention;
- delayed intervention beyond the last date of data acquisition including follow-up;
- information on stopping smoking either delivered to individuals in control groups or as literature (indicated in Characteristics of included studies as “Brief Intervention”);
- general tobacco education given to all participants in trial.
Studies that compared two different cessation interventions or combinations of interventions were also included.
We have not included primary prevention strategies that identify and follow up baseline tobacco users, or programmes aimed solely at relapse prevention.
Types of outcome measures
Measures of quitting
The primary outcome of interest was change in smoking behaviour, i.e. being a smoker at baseline and becoming an ex-smoker at post-test for all participants who received the intervention. The primary outcome was smoking status at six months follow-up or longer. Trials with follow-up of less than six months have been excluded. We have not included relapse rates in the review.
We have reported the definition of cessation used in each trial, for example abstinence during a particular period, such as in the past 7 or 30 days (point prevalence), abstinence from the start of the programme (continuous abstinence), or abstinence following occasional relapse in the two weeks post-treatment grace period (prolonged abstinence) (Hughes 2003). If studies reported cessation using more than one definition of abstinence we used the most rigorous outcome. Biochemical confirmation of self-reported non-smoking is generally taken to be the gold standard for reporting of quit rates (West 2005). This tests for the presence of smoking-related substances in exhaled breath, saliva, urine or blood, and is the preferred verification method for reported outcomes where this is available. It should be noted that biochemical validation may not be a very sensitive measure of change in smoking status for irregular smokers; it is possible that some studies may have recruited participants who would not be identified as smokers at baseline.
We analysed data on an intention-to-treat basis, i.e. with all participants analysed in the groups to which they were randomized, and including all the randomized participants. Where necessary we have contacted authors for discrete data if it could not be imputed from the published reports. We have reported enrolment to studies according to type, as revealed in the study designs; e.g. personal invitation, entry through mass media campaigns, non-voluntary interviews in schools, etc. Randomization may be at the level of individual or organization. We have noted whether randomization took place after enrolment into the intervention.
Participation and retention in intervention
Since one might postulate that there is educational benefit from participation in a cessation programme, we report data on losses to follow-up. We have counted drop-outs and losses to follow-up as continuing smokers.
We extracted data on adverse events as a secondary outcome.
Search methods for identification of studies
We used the Cochrane Tobacco Addiction Review Group search strategies to identify randomized controlled trials (RCTs), cluster-randomized controlled trials (C-RCTs), and controlled trials of smoking cessation and prevention interventions. Trials relevant to the review were identified using the free text and keywords 'Child' or 'adolescent*' or 'adolescence'. We searched the Cochrane Tobacco Addiction Group Specialized Register in February 2013. At the time of the search the Register included the results of searches of the Cochrane Central Register of Controlled Trials (CENTRAL), issue 12, 2012; MEDLINE (via OVID) to update 20130104; EMBASE (via OVID) to week 201252; and PsycINFO (via OVID) to update 20121231. See the Tobacco Addiction Group Module in the Cochrane Library for full search strategies and a list of other resources searched. We have also searched the 'grey literature' (unpublished resources and conference proceedings) and the reference lists of identified studies and contacted manufacturers of smoking cessation products.
Where necessary, we have contacted the authors of existing trials and other experts for ongoing trials, and for unpublished results pertaining to completed trials, subject to the availability of peer review.
We also contacted smoking cessation e-networks with a list of the references to extracted studies, to request verification and any additional information.
Data collection and analysis
Selection of studies
We drew up a prospective list of eligibility criteria with two levels of priority: essential and desirable. Two authors (GG and AS) assessed the retrieved abstracts against this list for possible inclusion, to measure the feasibility of each criterion. We assessed levels of agreement by kappa score.
After piloting, we applied the agreed criteria to the abstracts of all studies extracted from the databases. We then categorized studies into three groups:
- Both authors agree on inclusion based on the abstract;
- One author suggests inclusion based on the abstract;
- Both authors agree on exclusion based on the abstract.
We retrieved full text articles for groups (1) and (2). The processes outlined here and later were used for all updates.
Two authors independently assessed each full article, using the agreed inclusion criteria. For studies where there was disagreement, the editorial base was consulted to reach a consensus. Where there was ambiguity in trial reporting or lack of data, we contacted investigators for clarification where possible. If we could not retrieve missing data, a study may have been excluded on that basis.
Data extraction and management
We extracted and reported the following information, where it was available, concerning each study:
- Country and study setting
- Theoretical framework (including a brief description of the intervention)
- Focus of the intervention
- Type of intervention, its duration, intensity, delivery format, gatekeeper
- Length of follow-up
- Size of eligible population
- Recruitment rate
- Number of participants or number of clusters and participants
- Definition of the study population
- Age range, grade, gender and ethnicity of participants
- Definition of smoking status used at baseline
- Definition of abstinence
- Biochemical validation
- Adverse effects of intervention
We report any threats to validity or other limitations described by the studies and report where authors have been contacted for discrete data in the 'notes' section (see Characteristics of included studies).
We have maintained a full list of excluded studies (see the Characteristics of excluded studies).
Assessment of risk of bias in included studies
We rated each included study as being at low, unclear, or high risk of bias in five domains:
- Random sequence generation
- Concealment of allocation. For cluster-randomized controlled trials which recruited after allocation to intervention or control status, we took account of whether individuals may have been selectively recruited or may have differentially refused to participate in the light of the known allocation, where this could be ascertained (Campbell 2004a; Campbell 2004b; Hahn 2005).
- Performance bias (blinding of participants and personnel, if applicable)
- Detection bias (blinding of outcome assessment, biochemical validation)
We also recorded any other risks of bias that did not fit in the above categories.
Measures of treatment effect
We summarised an effect size for each individual study as a risk ratio (RR) with 95% confidence intervals, and these are displayed in Analysis 1.1 for descriptive purposes. The risk ratio is calculated as (number quit in intervention group/ number randomized to intervention) / (number quit in control group/ number randomized to control), with participants randomized but lost to follow-up regarded as non-abstinent.
Unit of analysis issues
For cluster randomized trials, we checked whether the analysis used the same unit as randomization, or if other methods were used to account for cluster effects, such as multi-level modelling. We either included data that had been corrected or considered whether it was possible to adjust odds ratios. Unadjusted results are reported as such.
We have pooled groups of studies that we consider to be sufficiently similar in their interventions, comparison groups, setting, and participants, provided that there was no evidence of substantial statistical heterogeneity as assessed by the I² statistic (Higgins 2003). We estimated a pooled risk ratio using the Mantel-Haenszel fixed-effect model, based on the quit rates at longest follow-up. Where meta-analysis was not appropriate, we present summary and descriptive statistics.
Description of studies
Results of the search
For this update 64 references were identified, and four new trials were added to the included studies. These include one trial previously awaiting classification, which tested two different interventions so is treated as two trials in the analyses (Joffe 2009; NoT MD 2009). Figure 1 displays the numbers of records screened and studies included in previous versions of the review. The 90 excluded trials are listed in the Characteristics of excluded studies table with reasons for their exclusion, and the characteristics of two ongoing studies can be found in the Characteristics of ongoing studies table. One previously ongoing study was published in full after the date of search so is in the Characteristics of studies awaiting classification table.
|Figure 1. Study flow diagram|
Full details of the included studies are given in the Characteristics of included studies table where new trials are identified in the notes as "New for 2013 update". Trials are identified by the first author and the publication year of the main report, except for a group of studies reporting the Not on Tobacco (NoT) programme and the Project X programme, which are identified by programme type, trial location, and publication year of the main report.
Theoretical basis of intervention
It was difficult to stratify studies into categories with respect to the nature of the intervention. One intervention, conducted in 1978, used the health promotion strategies of that period (Greenberg 1978). Another used personal health risk management (Chan 1988). However, many interventions were complex and used combinations of psycho-social theories (see Sheppard 2009 for discussion of management of reviews of complex interventions). Constructs relating to motivational enhancement and strategies for resisting cultural and social pressures were the most common. Studies of this type included those using Motivational Interviewing, such as Colby 2005, Peterson 2009 and Horn 2007, sometimes combined with some form of relapse prevention advice and ongoing support (Brown 2003; Robinson 2003; Lipkus 2004). Other studies tested interventions based on the Transtheoretical Model of Change for adolescents (Prochaska 2000), either alone (Aveyard 2001) or in combination with other modalities, including brief advice and motivational enhancement (Hollis 2005) and cognitive behavioural therapy (CBT) (Lipkus 2004). Myers 2005 used an intervention based on CBT and motivational enhancement, while two other studies (Project EX-1 2001 and Project EX Russia 2013) used a more eclectic mix which included yoga and meditation. Studies of NoT used social cognitive theory (NoT FL 2001; NoT NC 2002; NoT WV 2004; NoT AL 2008; NoT MD 2009; NoT WV 2011). Three further studies have been undertaken based, at least in part, on social cognitive learning models (Patten 2006; Woodruff 2007; Peterson 2009). Three were primarily Information and Communication Technology (ICT) based interventions (Aveyard 2001; Patten 2006; Woodruff 2007). Finally, three studies have explored pharmacological support for quitting (Killen 2004; Moolchan 2005; Muramoto 2007).
Recruitment and settings
As can be expected from a cohort where most are still associated with some form of formal education, recruitment for studies was mainly within an educational setting (Greenberg 1978; Chan 1988; Aveyard 2001; NoT FL 2001; Project EX-1 2001; NoT NC 2002; Robinson 2003; Killen 2004; NoT WV 2004; Kelly 2006; Woodruff 2007; Hoffman 2008; NoT AL 2008; Joffe 2009; NoT MD 2009; NoT WV 2011). Educational settings have the advantage of easier recruitment and minimization of contamination. Six studies recruited from the healthcare environment (Brown 2003; Colby 2005; Hollis 2005; Moolchan 2005; Myers 2005; Horn 2007). Two studies (Lipkus 2004; Patten 2006) recruited directly from the community. Typically, where school or college was the base, the trials were clustered and the intervention was delivered to all students in one school, with matched schools used for control (Aveyard 2001; NoT studies; Project X studies; Woodruff 2007). All trials but two (Aveyard 2001 in the UK and Kelly 2006 in Australia) were based in North America. The rate of recruitment was commented on by several trialists. Where schools were recruited and matched or randomized (Greenberg 1978; Aveyard 2001; NoT studies; Project EX-1 2001; Project EX Russia 2013) and attendance in the programme was not compulsory, typically fewer than half of the students who smoked showed interest in enrolling. It should be noted, however, that for many of these studies parental permission was a requirement. Inducements to enrol and to remain in the study were also a feature of these trials (Greenberg 1978; Project EX-1 2001; Killen 2004; Lipkus 2004; Colby 2005; Moolchan 2005; Myers 2005; Woodruff 2007; NoT AL 2008). In three trials some element of compulsion was present (Brown 2003; Robinson 2003; Myers 2005), either with attendance as a consequence of a smoking policy violation (Robinson 2003) or as a controlled regimen in a hospital setting (Brown 2003; Myers 2005). One trial used a hospital emergency room to identify higher risk teens (Horn 2007).
Definition of smoking
One of the crucial issues for smoking cessation research for young people is how smoking is defined, and how cessation is defined and verified. The cessation issues are dealt with in the Risk of bias in included studies section and in the Discussion section. There was diversity among the included studies concerning the definition of smoking status, with most studies relying on self-reported smoking status at recruitment.
In general at least one cigarette per week (cpw) was used as a definition of being a smoker. Many studies used different definitions (e.g. one cigarette per day at recruitment). Where there was doubt we assured compatibility with our criterion through discussion with authors. Hollis 2005 differentiated between smokers and 'experimenters', but no studies explicitly took account of the episodic nature of adolescent smoking (Corby 2000; Grimshaw 2003). Many studies estimated nicotine dependence using some form of scale, most commonly the modified Fagerstrom Questionnaire (Prokhorov 2000; NoT FL 2001; Project EX-1 2001; NoT NC 2002; Brown 2003; NoT WV 2004; Killen 2004; Lipkus 2004; Moolchan 2005; Myers 2005).
Measurement of outcomes
The primary outcome of all interventions was smoking cessation for each individual. Just as a wide variety of definitions of smoking were used so there were several definitions of cessation.
The gold standard outcome of continuous abstinence (West 2005) was used by two authors (Lipkus 2004; Peterson 2009). Other continuous measures included 90-day abstinence (Myers 2005) and "prolonged abstinence" (Moolchan 2005).
Point prevalence measures were in the majority and these ranged from cessation for longer than one day (NoT FL 2001; NoT NC 2002; NoT WV 2004; Hoffman 2008) to 30 day cessation (Chan 1988; Aveyard 2001; Project EX-1 2001; Hollis 2005; Kelly 2006; Project EX Russia 2013). The most common outcome measure was seven-day point prevalence (Aveyard 2001; Brown 2003; Robinson 2003; Killen 2004; Lipkus 2004; Colby 2005; Moolchan 2005; Myers 2005; Muramoto 2007; NoT AL 2008). One study defined cessation as two sequential reports of seven-day point prevalence at four months and eight months from the start of the intervention (Lipkus 2004).
Verification of smoking status
Of the 28 studies which satisfied the inclusion criteria for this review, only 14 used or attempted some form of biochemical verification of self reports of smoking status for the whole cohort or for the full duration of follow-up (West 2005). Five trials used more than one method of biochemical verification (Brown 2003; Killen 2004; Colby 2005; Moolchan 2005; Myers 2005). Carbon monoxide levels were measured in eleven trials (NoT FL 2001; NoT NC 2002; Brown 2003; Killen 2004; Colby 2005; Moolchan 2005; Myers 2005; Patten 2006; Horn 2007; Muramoto 2007; NoT WV 2011), and salivary cotinine in ten trials (Brown 2003; Killen 2004; Lipkus 2004; Colby 2005; Moolchan 2005; Myers 2005; Hoffman 2008; NoT AL 2008; Joffe 2009; NoT MD 2009). In Chan 1988 and Myers 2005, smoking status was confirmed by report of another individual, and Peterson 2009 used internal verification within questionnaires.
Risk of bias in included studies
Figure 2 summarises review authors' judgements across each risk of bias domain. The majority of studies were judged to be at unclear or high risk of bias in at least one domain.
|Figure 2. Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.|
Of the 28 studies included studies, 12 allocated groups or institutions to conditions (Chan 1988; Aveyard 2001; NoT FL 2001; Project EX-1 2001; NoT NC 2002; NoT WV 2004; Woodruff 2007; NoT AL 2008; Hoffman 2008; Peterson 2009; NoT WV 2011; Project EX Russia 2013) and 16 allocated individuals (Greenberg 1978; Brown 2003; Robinson 2003; Killen 2004; Lipkus 2004; Colby 2005; Hollis 2005; Moolchan 2005; Myers 2005; Sherbot 2005; Kelly 2006; Patten 2006; Horn 2007; Muramoto 2007; Joffe 2009; NoT MD 2009). Of the cluster-randomized trials, seven were judged to be at high risk of selection bias either because groups or institutions were not randomly allocated or because of the way in which students within clusters were recruited (Chan 1988; NoT FL 2001; NoT NC 2002; NoT WV 2004; Woodruff 2007; NoT AL 2008; NoT WV 2011). Four of the individual studies were rated at high risk of selection bias because of the method of allocation or concealment (Greenberg 1978; Brown 2003; Myers 2005; Sherbot 2005). Fifteen studies did not provide sufficient detail on randomization and allocation, and hence were judged to be at unclear risk of selection bias.
The majority of studies were judged to be at unclear risk of performance bias, as it was not clear if blinding had taken place and, in the case of behavioural interventions, was not clear if participants in control groups were aware of the programme the intervention arms were receiving. Nine studies that involved face-to-face contact in the intervention group did not employ any form of biochemical validation, and were hence judged to be at high risk of detection bias due to possible differential misreport.
Incomplete outcome data
One marked feature of all included studies was the effort required to follow-up cases. Losses to follow-up ranged from less than 10% to more than 50% of the cohort. Three studies were judged to be at high risk of attrition bias as over half of the participants were missing data at follow-up (NoT FL 2001; Horn 2007; NoT AL 2008). A further three studies were judged to be at unclear risk as attrition rates were not reported in sufficient detail with which to judge (NoT NC 2002; Robinson 2003; NoT WV 2004). All other studies were judged to be at low risk of attrition bias.
It is a frequent feature of analysis of smoking cessation studies that cases lost to follow-up are assumed to be still smoking. Several authors attempt to discuss this issue and make adjustments in analysis (NoT FL 2001; NoT NC 2002; NoT WV 2004; Hollis 2005; Joffe 2009). As these studies cover those aged 20 or less, it can be assumed that, amongst other issues, this is a mobile population, changing or leaving school, moving on to college, etc. Paradoxically, there may be real pressures to conceal quit attempts from social groups. Several trials analysed their data on an intention-to-treat basis, i.e. including all participants in the groups to which they were originally randomized, and classifying those lost to follow-up as continuing smokers. One other feature of reporting was a tendency to report outcomes as percentages, sometimes without any particular clarity as to the denominator. Some of the results of our analysis have been imputed from percentage data, and in all cases authors have been contacted to ask for verification of the calculations (Chan 1988; NoT FL 2001; Project EX-1 2001; NoT NC 2002; NoT WV 2004; Brown 2003; Killen 2004; Lipkus 2004; Colby 2005).
Other potential sources of bias
We also evaluated studies for any other potential sources of bias. Three studies were judged to be at unclear or high risk of other bias due to possible or confirmed issues with treatment fidelity and contamination (Chan 1988; Aveyard 2001; Robinson 2003). One study was judged to be at high risk of other bias due to significant between group differences at baseline (Sherbot 2005). Finally, one further study was judged to be at high risk of other bias due to a doubling of the control group quit rate between 6 and 15 month follow-ups, which the authors speculate may represent confounding due to the influx of prevention initiatives delivered statewide during that period as a result of funds from the Master Settlement Agreement (NoT WV 2004).
Effects of interventions
See: Summary of findings for the main comparison Transtheoretical Model of Change (TTM) for smoking cessation in young people; Summary of findings 2 Interventions including motivational enhancement for smoking cessation in young people; Summary of findings 3 Not on Tobacco (NoT) programmes for smoking cessation in young people
Details of individual study outcomes are given in Analysis 1.1, in subgroups by the definition of abstinence used. Studies that reported more than one definition appear in each applicable subgroup. Four trials reported sustained or prolonged abstinence for at least six months, eight trials reported 30 day point prevalence abstinence and six trials used seven day point prevalence abstinence (PPA) as the strictest outcome. Eight other trials reported cessation that could be based on an even shorter period, or were unclear about the definition. One study is not displayed because we were unable to establish the denominator and the study report was published before follow-up was complete (Robinson 2003). Analysis 1.2 displays the results of trials added for the 2013 update. The wide confidence intervals for individual studies reflect the lack of power due to the small size and low quit rates in many trials. In total, around 6000 young people participated in the included studies.
Studies including Transtheoretical Model of Change (TTM)
Four studies were based on interventions targeting the stage of change of individual participants using TTM. A school-based intervention using a TTM computer expert system (Aveyard 2001) had a risk ratio (RR) for 30 day PPA of 1.45 (95% confidence interval [CI] 1.01 to 2.08) at 12 months, and 1.14 (0.78 to 1.66) after 24 months. By contrast the 'Teen Reach' study (Hollis 2005) included a brief clinical message and motivational counselling and booster sessions as well as using a TTM-based computer expert system recruiting from family practices and paediatric departments. The 'Teen Reach' intervention was effective for smokers (a subgroup of those recruited), with an RR of 1.80 (1.19 to 2.71) at 12 months and the intervention effect persisted with an RR of 1.71 (95% CI 1.06 to 2.76) at 24 months. Hoffman 2008 used a programme of Cognitive Behavioural Therapy (CBT) tailored to stage of change. The measures of quitting on this programme were defined as no smoking during 24 hours prior to interview and verification was attempted although administration proved problematic. The results from this trial do need consideration alongside the known nature of episodic smoking reported by teens.
Pooled results from these three trials show a significant effect in favour of the intervention (at 12 months, RR 1.56, 95% CI 1.21 to 2.01, Analysis 2.1, Summary of findings for the main comparison), yielding a number needed to treat of 17.5 at the end of the first year after the beginning of the intervention. In the two trials with follow-up at two years, the direction of the effect remained consistent but results were no longer statistically significant, with a pooled RR of 1.33 (95% CI 0.99 to 1.79, Analysis 2.2) and a doubling of the number needed to treat.
Lipkus 2004 used a TTM-based intervention that also included motivational enhancement via telephone and cognitive behavioural therapy (CBT) for young people recruited in the community (shopping malls and an amusement park). At eight month follow-up, the hypothesis that telephone counselling as an adjunct to self-help material would be effective was not supported (RR 1.10, 95% CI 0.74 to 1.62) for seven-day PPA. As this trial was testing mode of delivery rather than stage of change, we have not included it in the pooled analysis with the other TTM-based trials. It should be noted that this study was one of the few included in this review which attempted to measure sustained quitting between two points of data collection (four months and eight months).
Twelve studies used some form of motivational enhancement for young people within their intervention (Figure 3, Analysis 3.1, Summary of findings 2). Point estimates of effect ranged from 0.85 (in a trial with just two quitters, Horn 2007) to 6.00 (Greenberg 1978). Confidence intervals were wide and many trials were small, with only half enrolling more than 50 participants per trial arm (Project EX-1 2001; Brown 2003; Lipkus 2004; Hollis 2005; Peterson 2009; Project EX Russia 2013). Only Hollis 2005 detected a significant effect. Pooled results detected a significant effect in favour of the intervention (RR 1.60, 95% CI 1.28 to 2.01, n = 2667, Analysis 3.1). Two of these studies (Lipkus 2004; Myers 2005) met Russell standards (West 2005) and these have been analysed as an additional subgroup ( Analysis 9.1); pooled results were not statistically significant (RR 1.18, 95% CI 0.80 to 1.72). Six studies within the motivational enhancement group used complex interventions that included motivational interviewing as one of their theoretical frameworks. Brown 2003 was based in an inpatient psychiatric facility, Colby 2005 was based in a hospital outpatients and emergency room, Sherbot 2005 recruited from a pool of teenagers identified as having substance misuse issues, Project EX-1 2001 and Peterson 2009 were school based, and Project EX Russia 2013 was based in a youth camp. Although when pooled the six interventions that included Motivational Interviewing as one component of the intervention had a significant effect (RR 1.88, 95% CI 1.30 to 2.72, Analysis 3.2), it would be unwise to draw any inferences from this finding, as not all trials studied Motivational Interviewing alone.
|Figure 3. Analysis 3.1 Motivational enhancement versus brief interventions, cessation at 6 months or longer.|
Thirteen studies included cognitive behavioural techniques ( Analysis 4.1). This analysis is included as a record of where CBT has been included in trials. It is not possible to pool data from trials using CBT as, in general, CBT was only one component of a multicomponent intervention and the impact of the CBT element is impossible to disaggregate. This impact of this specific technique would, however, be interesting to explore as one study using a combination of CBT and motivational techniques delivered over four sessions with telephone follow-up did not detect any effect on cessation (Robinson 2003). A brief summary of the range of complex interventions is shown in Analysis 5.1.
Greenberg 1978 explored three educational approaches: fact-based, scare-based and attitudinal (values and affective strategies), but differences between the small groups were not statistically significant. Health Risk Assessment (HRA) was trialled by Chan 1988 amongst university students. This study recruited only 40 smokers to the group contributing to this review and did not detect a difference between HRA with feedback and HRA without feedback (RR 4.43, 95% CI 0.59 to 33.50 at nine months).
In some studies there was a degree of externally applied motivation to quit smoking. In Brown 2003, the inpatient adolescents were prohibited from smoking during hospital admission. The Myers 2005 cohort were obliged to attend group quit sessions, although they could decline to be followed up. The Robinson 2003 cohort were referred because of a violation of a local no smoking policy, and reduced punitive sanctions were offered if they attended groups in addition to monetary inducements.
Not on Tobacco (NoT) interventions
The Not on Tobacco intervention (NoT) has been tested in five localities with 1420 smokers in 148 schools (NoT FL 2001; NoT NC 2002; NoT WV 2004; NoT AL 2008; NoT MD 2009; NoT WV 2011). The RRs of the individual trials and overall effectiveness are summarized in Analysis 6.1 (see Figure 4 and Summary of findings 3). Individually, none of the six trials of the NoT intervention demonstrated a statistically significant effect at six months follow-up using an intention-to-treat analysis (raw data supplied by the authors). This may be related to the low power of the individual trials; when the trials are pooled, the result shows a statistically significant effect (RR 1.31, 95% CI 1.01 to 1.71), though the confidence interval is close to the line of no effect. Two new trials of the NoT intervention have been added in the 2013 update (NoT MD 2009; NoT WV 2011). These new trials use outcome measures designed to show persistence of intervention effect beyond measures in previous trials, thereby correcting for one of the difficulties of estimating effectiveness from previous reports, given the episodic pattern of teen smoking. Recent NoT trials have broadly confirmed previous results and it should be noted that length of abstinence measured has been extended in recent work to be in line with Russell Standards (NoT MD 2009; NoT WV 2011).
|Figure 4. Forest plot of comparison: 5 NoT (Not on Tobacco), outcome: 5.1 Cessation at 6 months or longer.|
In addition to comparing the standard NoT intervention to control, NoT WV 2011 involved a third arm in which the NoT programme was augmented with a physical activity component (NoT+Fit). At six months, the NoT+Fit arm had significantly higher quit rates when compared with control (RR 1.97, 95% CI 1.02 and 3.79, Analysis 6.2) but the result was not significant when compared with NoT alone (RR 1.48, 95% CI 0.88 to 2.48, Analysis 6.3).
Interventions using ICTs
In settings where all teens have equal access to the Internet and/or computers it has been possible to design studies that include this medium. Four studies utilise ICTs to deliver part of the intervention. Aveyard 2001 and Hollis 2005 used programmes specifically tailored to stage of change, Patten 2006 tested a home-based internet programme based on Social Learning Theory, and Woodruff 2007 used the internet to disseminate a smoking educational package based in a virtual reality. No study relied solely on ICTs. Aveyard 2001 and Hollis 2005 detected significant evidence of an effect, whereas the other two studies did not detect a significant difference between intervention and control arms (see Analysis 7.1; Analysis 7.2; Analysis 7.3).
This review contains three studies exploring different pharmacological interventions, which we have not pooled. Effect sizes are displayed in Analysis 8.1. All studies were relatively small and abstinence rates were low, hence confidence intervals are wide. One study investigated the effectiveness of nicotine replacement therapy (NRT) in supporting cessation (Moolchan 2005), one tested bupropion as an adjunct to NRT (Killen 2004) and one tested bupropion alone at two strengths: the standard daily dose of 300 mg or a single daily dose of 150 mg (Muramoto 2007). Comparing NRT patches and gum with placebo (Moolchan 2005), results at six months were not statistically significant in this underpowered study, with an RR of 4.12 (95% CI 0.92 to 18.52) for patches and an RR of 1.74 (95% CI 0.34 to 9.00) for gum versus placebo using biochemically verified seven-day PPA. Results using prolonged abstinence also did not detect a significant effect of either type of NRT. Muramoto 2007 did not detect evidence for a benefit of standard dose bupropion (RR 1.49 95% CI 0.55 to 4.02) or a lower 150 mg dose (RR 0.33 95% CI 0.07 to 1.58). Killen 2004 also failed to detect an effect for bupropion used as an adjunct to NRT patches (RR 1.05 95% CI 0.41 to 2.69). The evidence regarding the effectiveness of the use of bupropion alone in adolescence from the single study conducted so far appears to suggest that this intervention does not have a persistent effect (six months or longer) for either of the doses tested.
No adverse effects were reported in any of the psycho-social trials. In the trial of bupropion as an adjunct to nicotine patch (Killen 2004), although young people reported a total of 47 self-rated 'severe' complaints with nausea the most common, none of these were judged to be severe by the lead study physician. In the trial of nicotine patch versus nicotine gum (Moolchan 2005), active medication was associated with a statistically significant (P > 0.01) increase in four symptom categories, including sore throat, erythema, pruritus and shoulder/arm pain. In the trial of bupropion alone (Muramoto 2007), four percent of participants reported adverse effects and eight subjects discontinued treatment because of adverse events. Two serious adverse events resulting in hospitalisation occurred in this trial: one participant was admitted for anticholinergic crisis after ingesting Datura innoxia and one participant intentionally overdosed on study medication and other substances.
For the purpose of this review, we have taken a clinical focus on young smokers. In public health terms, the line between young smokers, experimenters and 'potential' smokers is blurred. Some interventions are therefore aimed at the population level, attempting to combine prevention and cessation. Individual clinicians, however, face a different problem: what advice should they give and what works for the young person who has started smoking and expresses a wish to stop? For this review, therefore, we drew what might otherwise be seen as an arbitrary line and developed a protocol which would include those prevention studies that had a cessation intervention component and discrete results for smokers (Chan 1988; Aveyard 2001; Hollis 2005).
Ideally, we would wish to know outcomes in terms of true smoking cessation, i.e. quitting smoking and not returning to the habit, although an absolute measure of cessation in these terms is in practice impossible, as it would require life-long follow-up of subjects. It is necessary therefore to consider just how well what are effectively proxy measures correspond to the desired outcome. Clearly, longer periods of follow-up will be of greater value. We therefore limited our review to studies with six months follow-up, as recommended elsewhere (Mermelstein 2002; West 2005). There is clear evidence in some of the included studies that have done repeated measures of a waning effect over this period (e.g. Myers 2005 and Brown 2003). Early relapse is an obvious danger, especially for young people who have been shown to make many quit attempts (MMWR 2009). In order to standardize comparisons, we took the six month period as beginning from baseline measurement. It should be noted however, that studies may not set a quit date until some weeks into the programme (e.g. Project EX) and this may be a source of bias when comparing outcomes.
A more substantial weakness in the evidence base springs from the definitions of quitting used in studies. These vary from self-reported quitting longer than one day (NoT FL 2001; NoT NC 2002; NoT WV 2004) through to seven-day or 30-day point prevalence abstinence (PPA) at the point of ascertainment, to longer or continuous periods (see Effects of interventions and forest plots). With respect to the shorter PPAs, a negative result is useful in demonstrating evidence of a lack of effect where the study size is adequate but care should be taken with the shorter quit lengths such as 24 hours. The irregularity and instability of the smoking habit in its early stages (for example, weekend smoking is commonly reported) and the low number of cigarettes smoked at baseline by some subjects, call into question the prognostic value of short-term PPA measurements of less than 30 days. Several trials recognize this pattern of smoking and use a 30 day measure of abstinence but continuous abstinence remains the important and recommended outcome (West 2005). It is tempting to conclude that encouraging an increased number of what are effectively short-lived (e.g. seven-day) quit attempts allows young people to 'practice' quitting, and therefore may help to achieve prolonged cessation in the long run. Prolonged quit attempts might also have a health benefit of their own, or interrupt the progression to more regular or heavy smoking. However, we have no data for young people against which we can test these assumptions.
For our results, we have used an intention-to-treat analysis, i.e. all those randomized included in their original groups, whether or not they received the full intervention. We counted all those with missing data as continuing smokers. We requested information from authors where necessary to facilitate these calculations. Although this is standard practice in adult cessation studies, our review demonstrates that the reasons for young people dropping out from follow-up are diverse, and by no means always related to risk of continued smoking (NoT FL 2001; NoT NC 2002; NoT WV 2004; Hollis 2005). We accept, therefore, that this assumption leads to a conservative analysis, and that it may bias our results towards the null. Unfortunately, there does not seem to be any other way of reliably imputing missing data across all situations, so this problem would seem to be intractable.
Several studies clearly demonstrate the importance of biochemical verification (Robinson 2003; Killen 2004; Colby 2005) as substantial numbers of subjects have given false information regarding quit attempts. This raises possible doubts about the validity of those studies which showed positive results but did not use verification, e.g. Hollis 2005. In Project EX-1 2001, verification was incomplete and a weighting factor was added to results. For NoT WV 2011, verification was added to the intervention but only done at three months. There is a continued need for further studies where smoking status has been verified, but the experience of Kohler (NoT AL 2008) and Hoffman (Hoffman 2008) underline the challenges that face researchers in this area. Muramoto warns that exhaled CO has a short half life and may be an insensitive measure given the episodic nature of teen smoking. She reports cotinine confirmed rates 50 to 65% lower than CO rates.
With regard to the limitations of the pharmacotherapy trials (Killen 2004; Moolchan 2005; Muramoto 2007), the existing evidence base gives us no reason to believe that the neuropharmacological efficacy, effectiveness and safety of pharmacotherapies for smoking cessation would be different for adolescents than for any other group of smokers. However, the context and meaning of smoking in adolescence is very different from that for adult smokers (Amos 2006), and there is currently insufficient evidence to determine whether NRT aids quitting in adolescents. The evidence on bupropion however appears to suggest this is not effective alone and varenicline is not currently licensed for under 18 years old in UK.
Several of the studies we reviewed appear underpowered as demonstrated by wide confidence intervals (e.g. Greenberg 1978; Chan 1988; Colby 2005; Sherbot 2005; Myers 2005; Horn 2007; Project EX Russia 2013), whilst Moolchan 2005 was powered for smoking reduction outcomes rather than cessation. Overall, the total number of young people currently contributing to this review is around 6000, a very small number considering the low quit rates and the range of interventions under investigation.
It should be noted that where recruitment was by inclusion from self reports it is likely that those volunteering, and in some trials obtaining parental consent, could be perceived as a subset of all smokers - those willing to quit. Some authors comment on this aspect of recruitment (Kealey 2009b).
The results of this review are consistent with other reviews in this area, though other reviews are very different from ours (Sussman 1998; Sussman 2002; McDonald 2003; Sussman 2006; Gervais 2007). Wherease other reviews had a much wider focus and included non-experimental studies, our review has aimed to evaluate where possible the experimental evidence for effectiveness rather than the more discursive evaluation of current approaches undertaken by other authors. Our results are also consistent with Riemsma 2003, whose review found results similar to Aveyard 2001. A recent review by Patnode et al was limited to interventions relevant to primary care and did not find any evidence of effectiveness (Patnode 2013).
With the exception of two very small trials (Greenberg 1978 and Chan 1988), all the included studies have been published within the last twelve years, suggesting an increase in both activity and quality. We are aware there is a growing interest in this topic and we intend to continue regular updates of this review. Over the period we have been extracting data, teen prevalence figures have shown some improvement in those countries using global public health campaigns, such as bans on smoking in public places, suggesting global measures may have had an impact on smoking initiation. In some developing countries, however, the prevalence is rising and concern for teens remains.
Implications for practice
There is currently little evidence on effectiveness of pharmacotherapies or incorporation of NRT into psycho-social programmes in this age group. The evidence does not support the use of bupropion either alone or as an adjunct to NRT. Evidence from one study suggests a mandatory intervention for those caught in violation of school smoking cessation policies is ineffective.
The evidence of outcomes on the Not on Tobacco (NoT) programme is improving and there is better evidence of the effectiveness of this programme in terms of length of abstinence. The meaningfulness of the definition of cessation (one day or more) used for many of the older NoT trials must be challenged when compared to the episodic nature of patterns of smoking of young people but newer studies are encouraging.
Those interventions with positive outcomes, in terms of their own protocols, are complex and are designed to respond to the many issues that characterise young persons' smoking. In particular, complex approaches show promise and show some persistence of abstinence (30 days point prevalence or longer) and recent publications add weight to interventions combining motivational enhancement and support with approaches based on social cognitive theory. A recent trial demonstrates that attention to recruitment and the mode of delivery and follow-up may be as important as the construct for the intervention. However, complex interventions often contain components requiring one-to-one (or one-to-few) input from trained staff, raising the cost of delivery, and means of communication other than face-to-face may be more cost effective. Within the context of a clinical trial, great attention is paid to quality management of the intervention. The challenge for services is to maintain these levels of clinical effectiveness. In view of the paucity of the current evidence, services should recognize the need to maintain rigorous evaluation in terms of outcomes; many of the issues researchers encountered did not arise simply from research protocols but from the practicalities of working with organisations and young people (Grimshaw 2003; Kishnuck 2004; NoT WV 2011). There is not as yet sufficient evidence to recommend widespread implementation of any one model.
Implications for research
Research is developing and increasingly studies are measuring verified, sustained quitting. This trend is to be encouraged for all new trials for teen smoking. The evidence is developing for complex psycho-social interventions but needs to be replicated and tested in different settings. The role of motivation to quit and other variables in predicting cessation need to be further explored as do the most appropriate ways of combining readiness to quit into complex programmes. Trials of brief interventions or self-help materials would be useful, particularly as these are often used as control conditions for more complex interventions. Further studies of appropriate ways to use pharmacotherapy in adolescent populations are needed (adequately powered for cessation).
In the six years since this review was first published, few trials have been able to implement suggested standards (Mermelstein 2002; West 2005). Funders of future trials must give priority to proposals which conform to these standards. Futhermore, given the evidence now available about effect sizes there is no reason why future studies should not be adequately powered. The theoretical basis of all interventions should be explicit, and reporting using CONSORT standards should be the norm (e.g. Hollis 2005).
Likely losses to follow-up for this age group must also be considered in the research design and the assumption that losses to follow-up are non-quitters (whilst representing the current "gold standard”) needs testing. Every effort should be made to keep the latter as small as possible, so that intention-to-treat analysis with missing subjects treated as continuing smokers can be carried out without excessive bias towards the null. Brown 2003 and Peterson 2009 demonstrate good practice in this respect. Subsidiary analysis of data with other imputed data is acceptable but should not represent the main result.
Biochemical verification remains the gold standard (West 2005). If this is used, note should be made of comments on the limitations of exhaled CO given the episodic nature of smoking in this population. However, although it is recognized that self reports in this cohort are not necessarily reliable, use of verification can affect recruitment and retention and a pragmatic decision needs to be taken in study design, balancing these factors.
Few of our studies complied with Russell Standards ( Analysis 9.1). Six months follow-up should be a minimum requirement, and research now needs to move on to using outcomes based on sustained, continuous quitting in line with the Russell Standards (West 2005). Longer interventions, perhaps with relapse prevention as a feature, need to be further explored. As a complementary measure, long-term prospective studies of the natural smoking history of those making quit attempts in adolescence are needed. Finally, as the field matures, direct comparisons of effective treatments should become possible and should support full economic analyses.
We would like to thank Paul Aveyard and Cathy Backinger for reading and commenting on drafts of the initial review. Our gratitude goes to Review Group Co-ordinators and staff, who have been untiring in their support, especially with searches and with software applications, and to all the trialists who supplied additional data or information for this review. We would particularly like to thank Steve Sussman for sharing with us the bibliography of his systematic reviews. These have provided invaluable secondary checks of our search and quality assessment strategies. No additional studies were identified from these bibliographies as meeting the criteria for inclusion in this Cochrane Review.
Data and analyses
- Top of page
- Summary of findings [Explanations]
- Authors' conclusions
- Data and analyses
- What's new
- Contributions of authors
- Declarations of interest
- Index terms
Last assessed as up-to-date: 31 July 2013.
Protocol first published: Issue 3, 2005
Review first published: Issue 4, 2006
Contributions of authors
Both authors conceived the review, and both selected and extracted data. GG and AS wrote the review in collaboration.
Declarations of interest
Medical Subject Headings (MeSH)
MeSH check words
Adolescent; Humans; Young Adult
* Indicates the major publication for the study