Stage-based interventions for smoking cessation

Stage-based interventions for smoking cessation (Review)

Cahill K, Lancaster T, Green N

This is a reprint of a Cochrane review, prepared and maintained by The Cochrane Collaboration and published in The Cochrane Library2010, Issue 11

http://www.thecochranelibrary.com

Stage-based interventions for smoking cessation (Review)

Copyright © 2010 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.

http://www.thecochranelibrary.com

T A B L E O F C O N T E N T S

1HEADER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2PLAIN LANGUAGE SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2BACKGROUND . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3OBJECTIVES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3METHODS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

12DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

14AUTHORS’ CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

14ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

14REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25CHARACTERISTICS OF STUDIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

68DATA AND ANALYSES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Analysis 1.1. Comparison 1 Optimal trial comparisons, Outcome 1 Stage-based vs standard SH materials. . . . . 71

Analysis 1.2. Comparison 1 Optimal trial comparisons, Outcome 2 Stage-based counselling vs standard advice. . . 72

Analysis 2.1. Comparison 2 Abstinence by intervention and comparison, Outcome 1 Expert systems. . . . . . . 72

Analysis 2.2. Comparison 2 Abstinence by intervention and comparison, Outcome 2 Individual counselling. . . . 74

Analysis 2.3. Comparison 2 Abstinence by intervention and comparison, Outcome 3 Interactive computer programme. 75

Analysis 2.4. Comparison 2 Abstinence by intervention and comparison, Outcome 4 Phone quit lines. . . . . . 76

Analysis 2.5. Comparison 2 Abstinence by intervention and comparison, Outcome 5 Training doctors. . . . . . 76

Analysis 2.6. Comparison 2 Abstinence by intervention and comparison, Outcome 6 Training lay supporters. . . . 77

Analysis 2.7. Comparison 2 Abstinence by intervention and comparison, Outcome 7 Staged SH materials. . . . . 77

Analysis 3.1. Comparison 3 Validated abstinence, Outcome 1 Biochemically validated abstinence. . . . . . . . 78

Analysis 3.2. Comparison 3 Validated abstinence, Outcome 2 Self-reported abstinence. . . . . . . . . . . . 79

Analysis 3.3. Comparison 3 Validated abstinence, Outcome 3 ’Bogus pipeline’. . . . . . . . . . . . . . 80

Analysis 4.1. Comparison 4 Missing data testing, Outcome 1 Intervention ITT versus control per protocol. . . . 81

Analysis 4.2. Comparison 4 Missing data testing, Outcome 2 Intervention ITT versus control ITT. . . . . . . 82

Analysis 5.1. Comparison 5 Any stage-based intervention vs control, Outcome 1 Abstinence at longest follow up. . 83

Analysis 5.2. Comparison 5 Any stage-based intervention vs control, Outcome 2 Abstinence by comparison condition. 85

Analysis 6.1. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 1 Expert systems. . . . 87

Analysis 6.2. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 2 Individual counselling. . 88

Analysis 6.3. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 3 Interactive computer

programme. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

Analysis 6.4. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 4 Phone quit lines. . . . 91

Analysis 6.5. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 5 Training doctors. . . . 92

Analysis 6.6. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 6 Training lay supporters. . 92

Analysis 6.7. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 7 Staged SH materials. . . 93

Analysis 7.1. Comparison 7 Per protocol analyses, Outcome 1 Expert systems. . . . . . . . . . . . . . . 93

Analysis 7.2. Comparison 7 Per protocol analyses, Outcome 2 Individual counselling. . . . . . . . . . . . 95

Analysis 7.3. Comparison 7 Per protocol analyses, Outcome 3 Interactive computer programme. . . . . . . . 96

Analysis 7.4. Comparison 7 Per protocol analyses, Outcome 4 Phone quit lines. . . . . . . . . . . . . . 97

Analysis 7.5. Comparison 7 Per protocol analyses, Outcome 5 Training doctors. . . . . . . . . . . . . . 98

Analysis 7.6. Comparison 7 Per protocol analyses, Outcome 6 Training lay supporters. . . . . . . . . . . . 98

Analysis 7.7. Comparison 7 Per protocol analyses, Outcome 7 Staged SH materials. . . . . . . . . . . . . 99

Analysis 8.1. Comparison 8 Cluster randomized trials, Outcome 1 Individual counselling. . . . . . . . . . 99

Analysis 8.2. Comparison 8 Cluster randomized trials, Outcome 2 Interactive computer programme. . . . . . . 101

Analysis 8.3. Comparison 8 Cluster randomized trials, Outcome 3 Training doctors. . . . . . . . . . . . 102

102ADDITIONAL TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

103APPENDICES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

105HISTORY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

iStage-based interventions for smoking cessation (Review)


105CONTRIBUTIONS OF AUTHORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

106DECLARATIONS OF INTEREST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

106SOURCES OF SUPPORT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

106DIFFERENCES BETWEEN PROTOCOL AND REVIEW . . . . . . . . . . . . . . . . . . . . .

106INDEX TERMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

iiStage-based interventions for smoking cessation (Review)


[Intervention Review]

Stage-based interventions for smoking cessation

Kate Cahill1, Tim Lancaster1 , Natasha Green2

1Department of Primary Health Care, University of Oxford, Oxford, UK. 2London, UK

Contact address: Kate Cahill, Department of Primary Health Care, University of Oxford, Rosemary Rue Building, Old Road Campus,

Oxford, OX3 7LF, UK. [email protected].

Editorial group: Cochrane Tobacco Addiction Group.

Publication status and date: New, published in Issue 11, 2010.

Review content assessed as up-to-date: 27 August 2010.

Citation: Cahill K, Lancaster T, Green N. Stage-based interventions for smoking cessation. Cochrane Database of Systematic Reviews2010, Issue 11. Art. No.: CD004492. DOI: 10.1002/14651858.CD004492.pub4.


A B S T R A C T

Background

The transtheoretical model is the most widely known of several stage-based theories of behaviour. It proposes that smokers move through

a discrete series of motivational stages before they quit successfully. These are precontemplation (no thoughts of quitting), contemplation(thinking about quitting), preparation (planning to quit in the next 30 days), action (quitting successfully for up to six months), and

maintenance (no smoking for more than six months). According to this influential model, interventions which help people to stop

smoking should be tailored to their stage of readiness to quit, and are designed to move them forward through subsequent stages

to eventual success. People in the preparation and action stages of quitting would require different types of support from those in

precontemplation or contemplation.

Objectives

Our primary objective was to test the effectiveness of stage-based interventions in helping smokers to quit.

Search methods

We searched the Cochrane Tobacco Addiction Group’s specialised register for trials, using the terms (’stage* of change’, ’transtheoretical

model*’, ’trans-theoretical model*, ’precaution adoption model*’, ’health action model’, ’processes of change questionnaire*’, ’readiness

to change’, ’tailor*’) and ’smoking’ in the title or abstract, or as keywords. The latest search was in August 2010.

Selection criteria

We included randomized controlled trials, which compared stage-based interventions with non-stage-based controls, with ’usual care’

or with assessment only. We excluded trials which did not report a minimum follow-up period of six months from start of treatment,

and those which measured stage of change but did not modify their intervention in the light of it.

Data collection and analysis

We extracted data in duplicate on the participants, the dose and duration of intervention, the outcome measures, the randomization

procedure, concealment of allocation, and completeness of follow up.

The main outcome was abstinence from smoking for at least six months. We used the most rigorous definition of abstinence, and

preferred biochemically validated rates where reported. Where appropriate we performed meta-analysis to estimate a pooled risk ratio,

using the Mantel-Haenszel fixed-effect model.

1Stage-based interventions for smoking cessation (Review)


mailto:[email protected]

Main results

We found 41 trials (>33,000 participants) which met our inclusion criteria. Four trials, which directly compared the same intervention in

stage-based and standard versions, found no clear advantage for the staging component. Stage-based versus standard self-help materials

(two trials) gave a relative risk (RR) of 0.93 (95% CI 0.62 to 1.39). Stage-based versus standard counselling (two trials) gave a relative

risk of 1.00 (95% CI 0.82 to 1.22). Six trials of stage-based self-help systems versus any standard self-help support demonstrated a

benefit for the staged groups, with an RR of 1.27 (95% CI 1.01 to 1.59). Twelve trials comparing stage-based self help with ’usual care’

or assessment-only gave an RR of 1.32 (95% CI 1.17 to 1.48). Thirteen trials of stage-based individual counselling versus any control

condition gave an RR of 1.24 (95% CI 1.08 to 1.42). These findings are consistent with the proven effectiveness of these interventions

in their non-stage-based versions. The evidence was unclear for telephone counselling, interactive computer programmes or training

of doctors or lay supporters. This uncertainty may be due in part to smaller numbers of trials.

Authors’ conclusions

Based on four trials using direct comparisons, stage-based self-help interventions (expert systems and/or tailored materials) and individual

counselling were neither more nor less effective than their non-stage-based equivalents. Thirty-one trials of stage-based self help or

counselling interventions versus any control condition demonstrated levels of effectiveness which were comparable with their non-

stage-based counterparts. Providing these forms of practical support to those trying to quit appears to be more productive than not

intervening. However, the additional value of adapting the intervention to the smoker’s stage of change is uncertain. The evidence is

not clear for other types of staged intervention, including telephone counselling, interactive computer programmes and training of

physicians or lay supporters. The evidence does not support the restriction of quitting advice and encouragement only to those smokers

perceived to be in the preparation and action stages.

P L A I N L A N G U A G E S U M M A R Y

Are stage-based interventions more effective than non-stage-based ones in helping smokers to quit?

The transtheoretical model is one of several stage-based theories of behaviour change. It suggests that smokers move through a series of

motivational stages before they manage to stop smoking. These are precontemplation (no thoughts of quitting), contemplation (thinking

about quitting), preparation (planning to quit in the next 30 days), action (quitting successfully for up to six months), and maintenance(no smoking for more than six months). According to this widely-known theory, programmes which help people to stop smoking

should be matched to their stage of readiness to quit. They are designed to move them forward through the stages to eventual success.

In this review, we have compared stage-based programmes of smoking cessation with standard (unstaged) programmes, or with ’usual

care’, or with assessment only. We found 41 stage-based trials, covering more than 33,000 smokers, which measured quit rates at least

six months after treatment. Only four of the 41 trials directly compared the same intervention in a standard and a stage-based version.

This showed that the stage-based version was neither more nor less effective than the standard one. Eighteen trials which compared

stage-based self-help programmes with any control condition showed better success rates for the intervention groups. Thirteen trials

of stage-based individual counselling versus any control condition showed a similar benefit for the intervention groups. These findings

confirm the known effectiveness of these interventions, whether staged or unstaged. The evidence was less clear on the effects of stage-

based telephone counselling, interactive computer programmes or training of doctors and helpers. This uncertainty may be due in part

to smaller numbers of trials. We find on the evidence from this review that providing self-help or counselling support to smokers trying

to quit is more effective than ’usual care’ or simple observation. However, the extra value of fitting that support to the smoker’s stage

of change is currently unclear.

B A C K G R O U N D

Almost five million people worldwide die prematurely from smok-

ing each year. If current trends continue, this will rise to 10 mil-

lion within 10 years, with 70% of those deaths occurring within

the developing world (WHO FCTC 2000). It has been estimated

that between 1950 and 2000, 60 million people have died from

tobacco-related diseases (Peto 1994). In the USA alone, smoking

now kills around 512,000 people a year. These premature deaths



from smoking on average amount to each individual losing 23

years of life (CTSU 2006).

Smokers are also at increased risk of a number of non-lethal ill-

nesses, including cataracts, Crohn’s disease, depression, diabetes

Type 2, impotence, visual impairment, osteoporosis and tuber-

culosis (ACSH 2003). They suffer increased fertility problems,

and aggravated symptoms of asthma, chronic rhinitis, diabetic

retinopathy, Graves’ disease, multiple sclerosis and optic neuri-

tis (ACSH 2003). However, stopping smoking before middle age

avoids more than 90% of the risk attributable to smoking (Peto

2000).

There are a number of established aids to smoking cessation,

including a range of pharmacotherapies (nicotine replacement

therapy (Stead 2008), bupropion (Hughes 2007), varenicline

(Cahill 2008)) and behavioural approaches (group or individ-

ual counselling (Stead 2005; Lancaster 2005a), self-help mate-

rials (Lancaster 2005b)). One widely-used behavioural approach

is the ’stages of change’ or transtheoretical model (TTM), pro-

pounded by Prochaska and colleagues (Prochaska 1985; Prochaska

1991; Prochaska 1997). This approach assumes that smokers pass

through a discrete series of motivational stages (Prochaska 2001):

Precontemplation: the individual does not perceive their smoking

to be a problem and has no intention of quitting in the foreseeable

future (typically over the next six months).

Contemplation: the individual is aware that their smoking is a prob-

lem, and is thinking seriously about overcoming it but has not

committed to a course of action. Contemplators may state that

they are seriously considering changing their behaviour within the

next six months.

Preparation: Individuals intend to take action within the next

month, and have unsuccessfully taken action in the past year (there

is some debate over the appropriateness of previous failure as a

defining feature of this phase; West 2005a).

Action: the person makes overt behavioural changes to stop smok-

ing, and has successfully altered their behaviour for a period of

anything from one day to six months.

Maintenance: the now ex-smoker works to prevent relapse and to

consolidate their abstinence for more than six months.

Termination (not always an explicit component of the model): the

individual has completed the process of change; they have a high

level of confidence across all high-risk situations and no temptation

to relapse.

The model proposes that individuals move sequentially through

the stages, but may revert to earlier stages before finally achieving

complete abstinence. The authors also identify 10 strategies or

’processes of change’, which help an individual to move through

the quitting process, and which vary from stage to stage (Prochaska

1988). Other component variables of the model include decisional

balance (weighing the pros and cons of maintaining current be-

haviour), situational temptations (managing scenarios in which

one might lapse), and self-efficacy (the belief that one will be able

to change one’s behaviour). The theory assumes that an individ-

ual’s stage of change can be accurately defined, so that the ap-

propriate intervention can be offered, and that the stage will fre-

quently be re-assessed and the intervention tailored accordingly. It

also propounds that incremental moves through the stages, inde-

pendently of an active quit attempt, predict higher eventual levels

of abstinence (Prochaska 2004).

The stages of change model has been deployed for a number

of therapeutic purposes. Its application to alcohol abuse (Project

MATCH 1997; Project MATCH 1998), to physical activity

(Blissmer 2002) and to radon testing (Weinstein 1998) have all

been explored elsewhere. Similar models of behaviour change were

hypothesised concurrently with the development of the TTM, in-

cluding the Precaution Adoption model (Weinstein 1988), and the

Health Action model (Tones 1987). The stages of change model

has remained influential in the development of current guide-

lines for clinical practice. It remains standard practice to set a quit

date during supported cessation attempts, on the assumption that

abrupt or spontaneous quit attempts are less likely to succeed (cf.

Larabie 2005; West 2005a; West 2006). However, the conceptual

validity and the practical usefulness of the stages of change model

for smoking cessation have been challenged over recent years, and a

number of systematic reviews of trials based on the model have pro-

duced inconsistent or negative findings (Froelicher 2002; Littell

2002; Spencer 2002; Riemsma 2003; van Sluijs 2004; Bridle 2005;

Webb 2006; Herzog 2008; Herzog 2010). Our review is intended

to contribute to this process of testing the application and value

of the model for smoking cessation.

O B J E C T I V E S

To evaluate the effectiveness of interventions using a stage-based

approach to achieve abstinence from smoking, compared with:

• no intervention (assessment only or usual care)

• a non-stage-based intervention of lower intensity

• a non-stage-based intervention of equal intensity

M E T H O D S

Criteria for considering studies for this review

Types of studies



Randomized or quasi-randomized controlled trials.

Types of participants

Smokers, of any age, race or gender.

Types of interventions

Any intervention using a stage-based design to influence a change

in smoking behaviour. We have attempted to distinguish where

possible, between those studies which substantively modify the

intervention to fit the estimated state of change, and those which

simply assess participants’ stage of change or use the stage-based

model to frame the approach without greatly affecting the content

of the intervention. The latter group have not been treated as

included studies.

The intervention may be compared with a non-stage-based control

(lower or equal intensity), or with a no-intervention control or

usual care group.

Types of outcome measures

The primary outcome is smoking cessation at least six months

after the start of the intervention, and longer wherever the data are

reported. Many of the studies in this review are cessation induction

studies, i.e. aiming to persuade mostly reluctant quitters to try

and stop, and often supporting them as they make a quit attempt.

Assessment of abstinence is therefore made after the period of

cessation induction, where that distinction is reported.

Secondary outcomes include any adverse effects of the interven-

tions. We have not included movement through stages of change

as an outcome of interest, since the primary concern of this re-

view and of the included studies is achievement and maintenance

of smoking cessation (Prochaska 2006). However, we consider

movement through stages of change in the Discussion section, as

a marker of the validity of the model for smoking cessation.

Search methods for identification of studies

We searched the Cochrane Tobacco Addiction Review Group

Specialized Register for trials. This register has been developed

from electronic searching of CENTRAL, MEDLINE, EMBASE

and PsycINFO, together with handsearching of specialist jour-

nals, conference proceedings and reference lists of previous trials

and overviews. We identified potentially relevant records from the

Register by searching for the following phrases in the title, abstract

or keywords; ’stage* of change’, ’transtheoretical model*’, ’trans-

theoretical model*, ’precaution adoption model*’, ’health action

model*’, ’health action process*’, ’health action approach*’ ’pro-

cesses of change’, ’readiness to change’, ’motivational interviewing’

or ’rubicon’). The most recent search of the register was in Au-

gust 2010. See the Tobacco Addiction Group module for Register

search strategies for all databases and dates of searches.

We have also checked the bibliographies of retrieved references

for further relevant publications, and have contacted authors and

experts in the field where necessary. There were no restrictions on

language or publication date.

Data collection and analysis

Two authors (KC and NG) independently assessed the retrieved ti-

tles and abstracts, and obtained full text copies of relevant articles.

They assessed them for possible inclusion against the pre-deter-

mined selection criteria . Each author independently extracted the

relevant data from trials meeting the selection criteria, and then

compared their extraction forms. Any disagreements were resolved

by discussion with the third author, and with the editorial base.

We have recorded the following trial characteristics, where they

were reported:

• Country

• Setting (e.g. community/ hospital/ outpatient clinic/

workplace/school)

• Stage of Change model used (Transtheoretical Model

[TTM]/ Health Action Process/ Precaution Adoption Process/

Rubicon process)

• Method of randomization and allocation concealment (if

used)

• Participant characteristics: number, age, sex, baseline

smoking, stage distribution

• Intervention: method of stage assessment, number and

timing of contacts, total duration

• Comparison group(s)

• Statistical techniques

• Outcomes: Follow-up period (from start of intervention),

definition of quitting (primary outcome), definition of stage of

change. Biochemical validation of self-report (if used)

• Implementation issues, attrition rates, withdrawals/losses to

follow up. Any differential loss to follow up by treatment group

or by stage of change at baseline will be noted.

The primary outcome was the number of quitters at the longest

follow up, and at least six months from the start of the interven-

tion. We preferred, but did not require, biochemically validated

quitting over self report, and measures of continuous or prolonged

abstinence over point prevalence. We treated participants lost to

follow up as continuing to smoke, and included them in an in-

tention-to-treat analysis where possible. However, since many of

the studies were population- rather than clinic-based, we also con-

ducted sensitivity analyses to test different assumptions about the

smoking status of those lost to follow up.

We describe and display results graphically as a risk ratio (RR:

[number of quitters/total number of participants in intervention

group] divided by [number of quitters/total number of partici-

pants in control group]) with 95% confidence intervals.



http://onlinelibrary.wiley.com/o/cochrane/clabout/articles/TOBACCO/frame.html




Analyses which included cluster-randomized trials have been con-

ducted with and without adjustment for clustering. Adjustment

for clustering generally delivered slightly wider confidence inter-

vals. Where applicable both versions are reported in the Results

section. The data, the interclass correlation and the design effects

used for these trials are displayed in Additional Table 1.

We have included a brief discussion of secondary outcomes, in-

cluding movement through stages of change.

We have assessed each included trial for methodological quality

and for the quality of the implementation of the intervention,

using the following questions:

• Was the method of randomization (sequence generation)

reported and acceptable?

• Was the method of allocation concealment reported and

acceptable?

• Were the intervention and control groups comparable at

baseline? If not, were analyses adequately adjusted?

• Were rates of attrition (during treatment) and loss to

follow-up (post-treatment) at acceptable levels, and did they

differ between groups ?

• Did all groups get the same treatment apart from the

intervention being tested?

• Was stage of change assessed at baseline?

• Was the stage of change instrument validated?

• Was the intervention tailored to individual stage of change?

• Was the quality and fidelity of the implementation

reported?

• Were the statistical methods appropriate?

• Were details of the training of educators given, where

applicable?

We have performed meta-analysis using the Mantel-Haenszel risk

ratio and fixed-effect method, provided that there was no signifi-

cant heterogeneity between the trials in their interventions, pop-

ulations and design. We assess statistical heterogeneity between

trials using the I² statistic, which describes the percentage of total

variation between studies that is due to heterogeneity rather than

to chance (Higgins 2003). Values over 50% suggest moderate het-

erogeneity, and values over 75% substantial heterogeneity.

We have performed sub-group analyses based primarily on types

of intervention, where such groupings can be made, with pooling

of trials that use the same format for intervention.

We include in this review the Tobacco Addiction Group glossary

of tobacco-specific terms (Appendix 1).

R E S U L T S

Description of studies

See: Characteristics of included studies; Characteristics of excluded

studies; Characteristics of ongoing studies.

We identified 41 trials for inclusion in our review. Full details

of each trial are given in the Characteristics of included studies

table. A further 58 trials did not meet the inclusion criteria for this

review, and are briefly described in the Characteristics of excluded

studies table, with reasons for their exclusion. Seven additional

trials could not be confirmed as meeting our inclusion criteria, and

are listed as excluded because of insufficient information (Hughes

2000; Borrelli 2002; Jones 2003; McDonald 2003; Chan 2005;

Tsoh 2005; Skewes 2007). One included study (Velicer 1999)

did not incorporate a non-stage-based control condition, and has

therefore not contributed to the meta-analyses. Two trials (Cabezas

2009; Prokhorov 2010) have not yet reported their findings, and

are described in the Characteristics of ongoing studies table.

Fifteen of the included studies had more than one intervention

arm. In two cases (Lawrence 2005; Meyer 2008) we have meta-

analysed the data under more than one category, where this could

be done without pooling. For the remainder we have either com-

bined intervention arms versus control or have selected the most

informative comparison for this review. In each case, the selected

comparisons are described in the ’Notes’ field of the Included Stud-

ies table.

The transtheoretical or stages of change model is often used in

conjunction with motivational interviewing (MI). In this review

we have included studies which primarily test stage-based inter-

ventions for smoking cessation, whether or not they deployed

MI techniques. Twelve of the included studies explicitly used

some form of MI-based counselling in the delivery of their stage-

based or control interventions (Lennox 1998; McBride 1999;

Stotts 2002; Mermelstein 2003; Manfredi 2004; Patten 2004;

Hennrikus 2005; Hollis 2005; Prochaska 2008; Prokhorov 2008;

Young 2008; Hannöver 2009). Our review of motivational in-

terviewing for smoking cessation (Lai 2010) covers studies which

concentrate on those interventions. Hennrikus 2005 is an included

study for both reviews; Manfredi 2004 is included in this review

but excluded from the motivational interviewing review, as the

impact of the MI counselling could not be isolated from other

intervention components.

Settings

Twenty-one of the included studies were conducted in the USA.

Five were in the UK, three each in Australia, the Netherlands and

Germany, and one each in Belgium, Canada, Finland, Switzerland,

Taiwan and Japan.

Eleven of the included studies were population-based. Nine were

set in clinics or in out-patient departments, three in antenatal clin-

ics and three on hospital wards. Five were set in family practices.

Six were education-based, including three set in secondary schools,

two in colleges and one accessing the parents of school children.

Two trials were conducted through telephone quitlines, and two

were set in worksites.



Interventions

We have grouped the included studies under six intervention types.

Within these broad categories we have then examined them by the

comparison condition, i.e. generic self-help, ’usual care’, or assess-

ment only. Additionally, four trials which used a non-smoking-

related healthcare intervention as their comparator are treated for

our purposes as assessment only.

1: Tailored, computer-generated or ’expert system’ letters (18 trials):

(Prochaska 1993; Curry 1995; Dijkstra 1998; Dijkstra 1999;

McBride 1999; Velicer 1999; Lennox 2001; Prochaska 2001a;

Stotts 2002; Aveyard 2003; Borland 2003; Borland 2004; Etter

2004; Prochaska 2004; Hollis 2005; Prochaska 2005; Schumann

2006; Meyer 2008 [Int 1]).

These are personalised reports or letters, usually produced elec-

tronically in response to baseline and follow-up questionnaires or

interviews. They are matched to the participant’s perceived stage of

change, and may include self-help materials (tailored or standard)

and/or follow-up phone calls. Stotts 2002 combined individual

MI-based counselling with an expert system letter, but is included

within this group for our review. Five of the studies were struc-

tured incrementally, i.e. augmenting the intervention components

across a number of arms, compared with a non-staged control

group (Prochaska 1993; Curry 1995; Velicer 1999; Aveyard 2003;

Borland 2003). This group of studies is discussed separately in the

’Effects of the Interventions’ section below. Velicer 1999 is not

included in the meta-analyses, as it did not include a non-staged

control group.

2. Individual counselling or brief advice (13 trials):

(Bobo 1998; Pieterse 2001;Mermelstein 2003; Manfredi 2004;

Nakamura 2004; Chouinard 2005; Davies 2005; Hennrikus

2005; Lawrence 2005 [Arm B]; Meyer 2008 [Int 2]; Prokhorov

2008; Hannöver 2009; Meysman 2010). This is usually delivered

by a physician or other healthcare worker, or by a trained counsel-

lor, and often includes one or more follow-up phone calls or letters,

to check progress and to reinforce the advice. The counselling is

tailored to the participant’s perceived stage of change. Mermelstein

2003 gave all participants a seven-week course of group coun-

selling for smoking cessation, and then tested the addition of tai-

lored versus generic phone counselling. Lawrence 2005 compared

usual care (advice from a midwife) with stage-based manuals and

counselling (Arm B), and with the same material presented as an

interactive computer programme (Arm C). We have included each

arm as a separate comparison. Similarly, Meyer 2008 compared

assessment-only controls with stage-based tailored letters (Int 1)

and with stage-based brief advice (Int 2). Each comparison is in-

cluded in the relevant meta-analysis. One trial (Prokhorov 2008)

combined individual counselling with biofeedback (lung function

testing and measurement of exhaled carbon monoxide).

3. Interactive computer programmes (5 trials):

(Aveyard 1999; O’Neill 2000; Escoffery 2004; Lawrence 2005

[Arm C]; Prochaska 2008).

These programmes are usually made available within a fixed time

frame, and are often conducted at the participant’s own pace. They

may be supervised sessions, and generally provide oral or written

feedback. Lawrence 2005 also delivered the material as a stage-

based counselling intervention, and this is treated as a separate

comparison (see Individual Counselling above).

4. Telephone counselling (2 trials):

(Thompson 1993; Young 2008).

Assessments and counselling are conducted entirely by phone, with

advice tailored to the caller’s stage of change.

5. Training in the stages of change model for smoking cessation (3

trials):(Wang 1994; Lennox 1998; Patten 2004).

These trials use rates of abstinence as surrogate markers for the

effectiveness of the training.

(a) Physicians:Two trials tested the training of physicians to deliver smoking ces-

sation advice based on the stages of change model. Other out-

comes included patient movement through stages of change and

number of quit attempts (Lennox 1998), and reduction in daily

cigarette consumption (Wang 1994).

(b) Supporters:Patten 2004 tested stages of change skills training for lay support-

ers of smokers trying to quit. Other outcomes included measures

of supportive behaviour, acceptability of the programme and re-

ceptivity of the smoker to the supporter’s attempts to help.

6. Stage-based self-help materials (1 trial):

Pallonen 1994 provided a manual to participants at six-month

intervals, matched to their stage of change. Many of the trials also

supplied generic or tailored self-help materials to their participants

as part of the intervention programme, or as part of the control

condition.

Comparison

The control or comparison conditions for the trials included

generic self-help materials or services (12 trials), ’usual care’ (13

trials), and assessment only (12 trials). Four trials used a non-

smoking-related healthcare intervention as the control condition.

These were dietary advice (Hollis 2005), advice on diet, hyperten-

sion or stress management (O’Neill 2000), a health risk assessment

(Prochaska 2008), and advice on hypertension or hypercholestero-

laemia (Nakamura 2004). For our analyses, we have combined the

assessment only and the non-smoking-related healthcare interven-

tion groups.

Follow-up assessment

All the included studies followed up their participants for at least

six months. Nine trials followed up for a maximum of 12 months,

nine for between 13 and 18 months, and ten for two years. We

have used the longest available follow-up measurement for our

analyses.



Validation of abstinence

The majority of the trials relied upon self-reported abstinence

rates. Five studies validated their outcomes by salivary cotinine

samples (Bobo 1998; McBride 1999; Lennox 2001; Aveyard 2003;

Hennrikus 2005), one by expired carbon monoxide (Nakamura

2004), and two by combining carbon monoxide with cotinine

testing (Mermelstein 2003; Chouinard 2005). Two further studies

achieved partially validated results, with Curry 1995 and Lawrence

2005 testing at intermediate but not at longest follow ups. Four

trials (Prochaska 1993; Thompson 1993; Dijkstra 1998; Pieterse

2001) used the ’bogus pipeline’ method, i.e. collecting biological

samples for validation but not testing them, and two of these cross-

checked self-report against the testimony of family or friends.

Stages of Change model

The generic five-stage transtheoretical model, with its associated

processes of change, decisional balance and temptation/self-effi-

cacy, is fully described elsewhere (Velicer 1996; Prochaska 1997;

CPRC 1998). This model has been variously applied and adapted

in the studies covered by this review. Although the stages are gen-

erally expressed as discrete steps, the process has also been de-

picted as a spiral (Prochaska 1992; Chouinard 2005), as cyclical

(switching between quitting and relapse; Nakamura 2004), or as a

contemplation ladder (Biener 1991; Patten 2004), to indicate the

likelihood of progression and relapse before achieving behavioural

change.

The concept has been reconfigured as ’perspectives on change’

(Borland 2004), representing the stages as: ’disengaged’ (precon-

templation and contemplation); ’engaged’ (preparation, with a

quit date between 15 and 30 days away); ’committed’ (preparation,

with a quit date set within the next 14 days); ’implementation’ (ac-

tion, during the first one or two weeks of quitting); ’consolidation’

(maintenance, from end of implementation to decline of urges

to smoke or concurrent nicotine replacement therapy (NRT));

’synthesis’ (maintenance or termination, less than daily urges to

smoke and no NRT). Thompson 1993 loosened the parameter

definitions to ’Not even thinking of quitting’ (precontemplation);

’thinking of quitting some time in the near future’ (contempla-

tion); ’set a quit date or made a quit attempt’ (action); ’success-

fully remained smokefree for an extended period (maintenance).

Pieterse 2001 reclassified the stages as low, moderately or highly

motivated to make a quit attempt. Stotts 2002 mapped the stages

to patterns of smoking cessation among pregnant women. Many

of the studies modified the individual stages, while preserving the

conceptual model.

Precontemplation:

The transtheoretical definition for this stage is ’Not thinking about

quitting in the next six months’.

Dijkstra 1998c and Nakamura 2004 both favoured an additional

category, ’immotives’, for those smokers not interested in quitting

or not planning to quit in the foreseeable future. Lennox 1998

subdivided the precontemplators into three groups, based on de-

cisional balance (the pros and cons of change), while Manfredi

2004 subgrouped them as never planning to quit, or planning to

reduce but not quit, or thinking of quitting but not in the next

six months. Meyer 2008 classified the precontemplators into four

groups, based on decisional balance and levels of self-efficacy.

Contemplation:The transtheoretical definition for this stage is ’thinking about

quitting within the next six months, but not in the next month’.

Lennox 2001 subdivided this group, based on positive versus

mixed or negative decisional balance.

Preparation:The transtheoretical definition of this stage is ’having made a 24-

hour quit attempt in the past year and planning to stop within the

next thirty days’.

A number of trials did not require a 24-hour quit attempt as a defin-

ing characteristic of this stage (Curry 1995; Etter 2004). Lennox

2001 subdivided this group on decisional balance. Thompson

1993 did not identify preparation as a separate stage, and de-

fined action as setting a quit date or making a quit attempt. An

earlier transtheoretical model had dropped the preparation stage

(Prochaska 1982; Prochaska 1992), but later reinstated it as an

integral part of the concept.

Risk of bias in included studies

There was considerable variation among the included trials’ at-

tempts to control for risk of bias. Assessment of the quality markers

for the risk of bias in each trial are reported in the Characteristics

of included studies tables, and are displayed in summary form in

Figure 1. A funnel plot (not shown) for all the included studies

did not suggest any significant risk of publication bias.

Randomization procedures, defined as sequence generation and

allocation concealment, were performed and reported adequately

in six trials, and included such techniques as computer-generated

tables of random numbers, minimization, and allocation by sealed

opaque envelopes. Five trials reported methods of sequence gen-

eration or allocation concealment which would be considered in-

adequate, including shuffling of questionnaires (Borland 2003),

assignment by an office assistant (Pieterse 2001), alternate order of

assignment (Escoffery 2004), and ’topping up’ recruitment arms

by extending catchment (Lawrence 2005). Meyer 2008 assigned

participants to study arm by which week they attended over a

three-week recruitment period. Frequent attenders were therefore

more likely to be allocated to the assessment only (control) arm,

or to the tailored letter arm.

The remaining trials either did not report their methods of ran-

domization, or did not describe them in sufficient detail to be as-

sessed.

Blinding of participants to study arm was reported in three trials

(Stotts 2002; Borland 2003; Borland 2004). Blinding of random-

ization staff was reported by one trial (Chouinard 2005), of inter-



viewers or counsellors by three trials (Mermelstein 2003; Manfredi

2004; Prochaska 2005), of assessors by three trials ( Manfredi

2004; Hollis 2005; Hannöver 2009), and of all study personnel

by Meyer 2008.

Sensitivity analyses excluding trials rated as inadequately random-

ized, allocated or blinded did not demonstrate any significant

change in the point estimates, although the confidence intervals

had widened.

Other events which might have introduced bias included mixing

up questionnaires between the recruitment waves (Aveyard 2003);

an intervention response insufficient to make the three- and six-

month data usable (Borland 2004); a low rate (55%) of inter-

vention delivery (Stotts 2002); disparate drop-out rates between

intervention and control groups (24% vs 8%) (Etter 2004); and

physicians choosing to deliver the intervention to some members

of the control group (Pieterse 2001), with consequent exclusion of

their data from the trial analysis. Four trials which aimed to match

self-help manuals to participants’ stage of change supplied the ap-

propriate manual plus all subsequent manuals in a single delivery,

which may have weakened the specificity of the targeted interven-

tion (Prochaska 1993; Velicer 1999; Prochaska 2001a; Prochaska

2001b). A similar limitation may apply to Curry 1995 (supplying

a composite manual of eight stage-based units) and to Lawrence

2005 (supplying the complete course of six manuals). The degree

of bias introduced in such cases would depend on the accompa-

nying instructions, and on the participants’ level of compliance.

Sensitivity analyses removing these trials made little difference to

the findings.

Figure 1



Figure 1. Risk of bias summary: review authors’ judgements about each risk of bias item for each included

study.



Effects of interventions

Studies varied in the type of staged intervention that they tested,

in the intensity of the intervention, and in the comparison condi-

tions that they used. We have therefore grouped them into their

categories (described above), and then subgrouped each category

by the comparison condition. We have preferred the most rig-

orous definition of abstinence for each trial, and have taken the

longest reported follow-up period. We also analysed the trials for

point prevalence abstinence (PPA) rates where reported, at 6- or12-

month follow up, but found no important differences between the

two sets of analyses.

The most informative comparison for this review is between a

generic or non-stage-based intervention and a similar stage-based

version of comparable intensity. Very few of the included stud-

ies offered such data. For trials of self-help materials (expert sys-

tems, manuals, interactive computer programmes), two studies

(Prochaska 1993; Lennox 2001) included this comparison. The

relative risk (RR) was 0.93 (95% confidence interval (CI) 0.62

to 1.39); analysis 1.1). For trials testing counselling (individual,

with or without supplementary self-help materials), two studies

(Thompson 1993; Mermelstein 2003) contributed to the compar-

ison, returning an RR of 1.00 (95% CI 0.82 to 1.22; analysis 1.2).

These findings demonstrate neither a beneficial nor a detrimental

effect of stage-based over standard approaches.

Type of intervention:

1. Tailored, computer-generated or ’expert system’ letters:Eighteen trials tested stage-based expert systems or tailored self-

help materials against any non-stage-based control group. Velicer

1999 was not included in this analysis, since it did not have a non-

stage-based comparison group, and shared one of its experimen-

tal groups with Prochaska 2001b. We subgrouped these trials on

the comparison condition. The relative risk for stage-based versus

any standard self-help materials was 1.27 (95% CI 1.01 to 1.59;

analysis 2.1.1; PPA at 6 or 12 months: 1.07, 95% CI 0.91 to 1.25;

six trials). This estimate was influenced by the positive findings of

Borland 2004, which had a RR of 1.78 (95% CI 1.20 to 2.63),

and a weighting of 28% in the meta-analysis. A sensitivity analysis

removing this trial returned a RR of 1.07 (095% CI .79 to 1.41)

and reduced the I2 value (estimating heterogeneity) from 28% to

0%. For the ’usual care’ controls the RR was 0.94 (95% CI 0.56

to 1.57; analysis 2.1.2), and for the assessment only controls 1.35

(95% CI 1.19 to 1.52; analysis 2.1.3). Early success for the inter-

vention arm in Etter 2004, the largest trial in analysis 2.1.3, was

not sustained beyond the seven-month assessment; by 24 months

the four-week point prevalence abstinence rates in both groups

were similar (11.1% for the intervention group and 10.5% for the

controls; P = 0.6).

Incremental tailored interventions:Five of the 18 trials compared a non-staged control group with

increasing levels of staged intervention (Prochaska 1993; Curry

1995; Velicer 1999; Aveyard 2003; Borland 2003). A comparison

of the cumulative effects of adding, for example, a counselling

intervention to an expert system to stage-based manuals showed

no clear trend in favour of the additional components, with only

Curry 1995 demonstrating an incremental benefit across the in-

tervention groups (RRs increasing from 0.43 to 1.87, but con-

fidence intervals including 1 in each case [analyses not shown]).

There were no substantive differences between any arms com-

pared with control in Aveyard 2003 or in Borland 2003. Prochaska

1993 demonstrated a benefit at 18 months for the individualized

feedback intervention over standard self-help manuals (RR 2.49,

95% CI 1.18 to 5.24; analysis not shown), but no clear advantage

for stage-based manuals or for additional phone counselling. Al-

though Velicer 1999 is not included in the meta-analyses because

it lacked a non-staged control group, we conducted a separate anal-

ysis of this trial, to assess the effect of adding expert system letters

to stage-based self-help manuals. The RR of 1.33 (95% CI 0.97

to 1.82) favoured the expert system component, while increasing

the number of contacts conferred no additional benefit (analysesnot shown).2. Individual counselling or brief advice:Thirteen trials compared individual counselling (face-to-face or by

phone) with any non-staged control condition. When this group

of studies was subgrouped by comparison condition, only one

of the findings demonstrated a modest advantage for the staged

interventions. The RR for the standard self-help comparator group

(three trials) was 1.33 (95% CI 1.00 to 1.78; analysis 2.2.1), for

the ’usual care’ comparator group (seven trials) 1.19 (95% CI 0.99

to 1.42; analysis 2.2.2), and for the assessment only comparator

group (three trials) 1.28 (95% CI 0.95 to 1.73; analysis 2.2.3).Six of the 13 trials in this group were cluster-randomized, and

the analysis was redone using the generic inverse variance method.

Relative risks on this basis were 1.20 (95% CI 0.92 to 1.55) for

standard self help, 1.24 (95% CI 0.99 to 1.56) for ’usual care’,

and 1.43 (95% CI 0.94 to 2.17) for assessment only (analysis 8).

Key data for the cluster randomized trials are given in Table 1.

3. Interactive computer programmes:Five trials tested stage-based interactive computer programmes, al-

though none used standard interactive programmes as a compara-

tor. Subgrouping by comparison condition detected no conclusive

benefit of this approach versus ’usual care’ (RR 1.14, 95% CI 0.81

to 1.59; analysis 2.3.1 ), and versus assessment only (RR 1.36,

95% CI 0.78 to 2.36; analysis 2.3.2). Two of the five trials were

cluster-randomized, and the analysis was redone using the generic

inverse variance method. The corresponding RRs were 1.14 (95%

CI 0.79 to 1.63) for ’usual care’, and 1.32 (95% CI 0.76 to 2.28)

for assessment only.

4. Telephone counselling:



Two trials comparing staged telephone counselling with a control

condition found no clear benefit for the staged intervention versus

standard self help (RR 1.04, 95% CI 0.59 to 1.82; analysis 2.4.1),

or versus ’usual care’ (RR 1.27, 95% CI 0.56 to 2.89; analysis2.4.2).

5. Training in the stages of change model for smoking cessation:(a) Physicians:Two trials which tested the training of physicians to deliver stage-

based smoking cessation advice against ’usual care’ found no ad-

vantage for the intervention (RR 0.99, 95% CI 0.65 to 1.50; anal-ysis 2.5.1). Lennox 1998 was cluster-randomized, and the data

were reanalysed using the generic inverse variance method. This

returned an adjusted RR of 1.33 (95% CI 0.67 to 2.63), the differ-

ence being mainly attributable to the redistribution of weighting

associated with this statistical method.

(b) Supporters:Patten 2004, testing stages of change skills training for lay sup-

porters of smokers trying to quit, detected a possible benefit of

the training (RR 1.50, 95% CI 0.27 to 8.34; analysis 2.6), but the

small numbers of participants and events (five quitters from 60

participants) meant that chance could not be ruled out.

6. Stage-based self-help materials:Pallonen 1994, testing the provision of staged self-help materials

versus assessment only, found a possible benefit of the interven-

tion (RR 1.31, 95% CI 0.55 to 3.13; analysis 2.7), but could not

exclude the likelihood of this being a chance finding.

Validated outcomes

Relative risks were similar between the studies which relied on self-

reported abstinence (RR 1.25; 95% CI 1.14 to 1.37) and those

which biochemically validated claims of abstinence (RR 1.19; 95%

CI 1.02 to 1.39; analysis 3). However, the quit rates for the vali-

dated studies were predictably lower compared with studies giving

self-reported rates. The median control quit rate in the eight vali-

dated studies, and in the four ’bogus pipeline’ trials, was four per

cent, giving a median intervention quit rate (based on relative risk)

of five per cent. The corresponding rates for the 29 self-reporting

studies were medians of seven per cent for the controls and nine

per cent for the intervention groups.

Use of pharmacotherapy

We excluded five studies which supplied or prescribed NRT, where

appropriate, as part of the intervention (Morgan 1996a; Cornuz

2002a; Pisinger 2005a; Hall 2006; Wilson 2008) .

Seven of the included studies (Mermelstein 2003; Borland 2004;

Chouinard 2005; Davies 2005; Hennrikus 2005; Young 2008;

Meysman 2010) either recommended NRT to all participants or

included a control condition (self-help or usual care) which was

likely to advise the use of pharmacotherapies where appropriate.

Four of the seven trials reported usage: Mermelstein 2003 and

Hennrikus 2005 found no difference in uptake between interven-

tion and control, while Chouinard 2005 and Meysman 2010 both

reported lower usage by controls (6/56 participants and 4/14 quit-

ters respectively) compared with intervention smokers (35/112

participants and 9/28 quitters respectively). Manfredi 2004 left

it to the discretion of each physician whether or not to prescribe

NRT, and reported that fewer than 1% of participants used it.

Pieterse 2001 advised intervention participants to use NRT where

appropriate but left it to control participants to raise it for dis-

cussion with their physician. In that trial, nicotine gum was used

by 9.4% of participants, with no significant differences in usage

between the groups. Etter 2004 reported that, although controls

received no smoking cessation advice, 24.9% of intervention par-

ticipants and 20.8% of controls (P = 0.008) reported having used

NRT by the two-year follow up.

Dose-response effects

Although we have not included Velicer 1999 in the meta-analyses

for this review, it offers evidence that a single staged intervention

can be as effective as two, three or six such contacts, and does

not support a dose-response effect. Borland 2004 found a positive

relationship between quitting and the number of tailored letters

received. Among those smoking at baseline, 6% of the recipients

of one or two letters achieved six-month sustained abstinence,

compared with 45% of those who received seven to ten letters, and

36% of those who received eleven or more letters (P < 0.001). Etter

2004 also observed a linear trend for rates of 4-week abstinence

increasing with the number of counselling letters, from two per

cent for no letter read to 32% for four or more letters read (P =

0.002). However, these observations may be instances of selection

bias, and are examined further in the Discussion section below.

Match-mismatch studies

A few smoking cessation studies have sought to test the robustness

of the transtheoretical model (TTM) by deliberately mismatching

the intervention to the participants’ stage of change.The assump-

tion underpinning this approach is that standard interventions

target people who are ready to make a quit attempt, i.e. those in

preparation or action stages, while contemplators and precontem-

plators need different kinds of support, to move them through the

stages towards action (Prochaska 1997). On this basis, precontem-

plators and contemplators would not be expected to benefit from

standard interventions.

To explore this hypothesis, Aveyard 2009a and Parsons 2009 re-

analysed the Aveyard 2003 data, to compare the efficacy of the

TTM versus standard materials in moving people from one stage

to the next. They found that the combined TTM study arms were

slightly but not significantly more likely to progress through the

stages than the control arm. However, contrary to the TTM hy-

pothesis, those in preparation were slightly more likely to make a

positive change with the TTM interventions than with the stan-

dard materials, and the likelihood of quitting in the TTM arms

compared with the control arm was higher for those in contem-

plation and precontemplation than for those in preparation, al-

though none of these finding reached statistical significance. To

account for these disparities, the authors mapped the content of

the standard materials to the processes of change described by the

TTM, and suggested that the standard manuals were “largely stage



appropriate”.

The same study group (Lawrence 2005) tested the TTM in an

intervention for smoking cessation in pregnant women, and re-

ported comparable findings. The relative benefits of the stage-

based interventions were not greater for women in precontempla-

tion or contemplation, but proved particularly effective for those

in preparation, for whom they would be considered a mismatch.

This study confirmed that the TTM intervention increased ces-

sation rates, but did not support the appropriateness of the stage-

matched materials to the predicted groups.

Quinlan 2000 (an excluded study) randomized 92 young adult

smokers to receive stage-matched manuals, stage mismatched

manuals or assessment only, and found that the mismatched group

performed better than the other two groups for every outcome.

Fifty-four per cent of the mismatched group progressed through at

least one stage, compared with 30% of the stage-matched group,

and 35% of the assessment only control group. Fourteen per cent

of the mismatched group were abstinent at one month follow up,

compared with three per cent of the matched group, and none in

the assessment-only group. Although the results of this small trial

failed to reach statistical significance, they do not endorse the prac-

tical application of the TTM to smoking cessation programmes.

Two studies by Dijkstra have also tested the plausibility of the

stage-based model. Dijkstra 1998 randomized participants to re-

ceive (i) pros-of-quitting material appropriate to ’immotives’ (i.e.

those with no interest in quitting), or (ii) self-efficacy material ap-

propriate to those preparing to quit, or (iii) both types of material,

suitable for those in precontemplation or contemplation, or (iv)

no intervention (the control group). The group that received both

types of material had significantly more sustained quitters at 14

months than the control group (OR 3.74), leading the authors to

conclude that smokers with varying readiness to quit can benefit

from a combination of information on outcomes of quitting and

of self-efficacy enhancement.

Dijkstra 2006 tested the Social Cognitive Stage Model, which is

inspired by and similar to the transtheoretical model, with forward

stage transition as the primary outcome. Participants were ran-

domized to (i) pros of quitting material (deemed appropriate for

precontemplators), or (ii) reducing the cons of quitting (for con-

templators), or self-efficacy materials (for preparers and ex-smok-

ers). The study confirmed the highest percentage of transitions

in the expected groups for precontemplators, contemplators and

ex-smokers, but not for preparers, for whom the pros and cons

materials proved a better match than the self-efficacy materials.

Overall, matched materials accounted for 44.7% of movement,

and mis-matched for 25.8% (OR 2.78, 95% CI 1.85 to 4.35).

Other trials have reported findings which are inconsistent with

the stages of change model. Curry 1995 reported that 5% of pre-

contemplators in the Phone group had achieved continuous ab-

stinence at 21 months, compared with 2% of the contemplators.

The groups in Prochaska 1993 behaved predictably, apart from

the precontemplator controls (standard manuals), who achieved a

higher quit rate than the contemplators in the same group.

Movement through stages

Movement through the stages of change, without reference to

quitting, was not a primary outcome of interest for this review.

However, we briefly consider it here for the included studies, as a

marker for the validity of the model for behaviour change (Martin

1996). The evidence from the studies in this review was incon-

clusive. Seven studies (O’Neill 2000; Lennox 2001; Stotts 2002;

Patten 2004; Chouinard 2005; Davies 2005; Prokhorov 2008)

confirmed the predicted transitions, although three of them as-

sessed forward movement only. A further five studies did not con-

firm the expected movement through the stages Thompson 1993;

Curry 1995; Aveyard 1999; Schumann 2006; Young 2008). All

five included regression to earlier stages as part of their assessments,

with all except Curry 1995 employing a mean change scoring sys-

tem. Four additional studies detected contradictory or inconsis-

tent patterns of movement through the stages (Pallonen 1994;

Dijkstra 1999; Borland 2004; Lawrence 2005).

D I S C U S S I O N

The most rigorous comparisons that we offer in this review suggest

that stage-based self-help materials (relative risk (RR) 0.93, 95%

confidence interval (CI) 0.62 to 1.39) and stage-based individual

counselling (RR 1.00, 95% CI 0.82 to 1.22) are no more nor less

effective than their generic or non-stage-based equivalents pro-

vided at a similar intensity. These findings are based on four trials

which construct direct comparisons between the two approaches,

involving 3255 participants.

We have also explored other included trials, which test stage-

based interventions against a range of control conditions. Six trials

(5947 participants) of stage-based self-help interventions, includ-

ing manuals and expert systems, compared with generic self-help

materials, demonstrated a modest benefit, with a RR of 1.27 (95%

CI 1.01 to 1.59). Twelve trials (14,446 participants) of stage-based

self-help interventions versus ’usual care’ or assessment only found

a RR of 1.32 (95% CI 1.17 to 1.48; analysis not shown). These esti-

mates are compatible with the Cochrane review of self-help inter-

ventions for smoking cessation (Lancaster 2005b), which demon-

strates a RR of 1.24 (95% CI 1.11 to 1.39) for 19 trials of self-help

materials versus minimal or no self help, and without supportive

contact. However, such comparisons are indirect, and although

they may be suggestive, their significance should not be overstated.

Three trials of stage-based individual counselling (2035 partici-

pants), compared with generic self-help, conferred a marginal ben-

efit, with a RR of 1.33 (95% CI 1.00 to 1.78). Pooling all 13

individual counselling studies, regardless of the control condition,

produced a RR of 1.24 (95% CI 1.08 to 1.42; analysis not shown),

which is somewhat lower than the RR of 1.44 (95% CI 1.25 to

1.65) for 18 trials of counselling versus any control in the Cochrane



review of individual behavioural counselling (Lancaster 2005a).

Included studies testing stage-based telephone counselling, inter-

active computer programmes or training of physicians and lay sup-

porters were too few to offer meaningful comparisons with the rel-

evant Cochrane reviews. Our findings suggest that established ces-

sation interventions, including self-help materials, both tailored

and standard, and individual counselling, work at the expected

levels of effectiveness when delivered as stage-based interventions.

Evidence for a dose-response effect is currently unclear. Two stud-

ies (Borland 2004 and Etter 2004) support the increased effective-

ness of multiple contacts, while the large study Velicer 1999 found

no differences in outcome between single and multiple contacts.

Etter 2004 cautions against a simplistic interpretation of the ’more

is better’ approach, pointing out that the association between quit-

ting and the number of counselling letters in his trial could be

an instance of selection bias rather than a dose-response effect,

since those with higher motivation to quit were more likely to re-

quest the letters. This may also be true for Borland 2004, since the

provision of the advisory letters was triggered by the participants’

progress through the perspectives on change. The Etter trial also

suffered from differential rates of attrition, with losses of 24% in

the intervention group at six months, compared with 8% of the

controls. Feedback indicated that intervention participants may

have wearied of successive mailings, leading to higher attrition and

potentially to an inverse dose-response effect.

The five studies which cumulated two or three stage-based com-

ponents of increasing intensity to the baseline control condition

did not demonstrate a clear dose-response trend. The first addi-

tional component increased the quit rates compared with controls

in all cases except for Curry 1995, but subsequent increments gen-

erally failed to establish the trend predicted by the model, and in

some cases may have precipitated higher rates of drop-outs than

the less intensive arms (Prochaska 1993; Aveyard 2003; Borland

2003). The evidence from our review lends little support for the

increased effort and resources implicit in this stepped intervention

approach.

The analyses in this review have been conducted on an intention-

to-treat (ITT) basis, wherever the data were available, i.e. includ-

ing all participants randomized in their original groups. We ex-

cluded deaths where reported, but counted drop-outs and those

lost to follow up as continuing smokers. While this approach may

be appropriate for clinic- and counsellor-based intervention trials,

and is recommended by the Russell Standard (West 2005b), its

applicability to population-based studies has been debated (Velicer

1992; Prochaska 1993; Borland 2004). For the 11 population-

based studies eligible for meta-analysis and the two telephone quit-

line studies, we conducted a sensitivity analysis to test the most

conservative assumptions about the smoking status of those with

missing data or lost to follow up. The ITT-based relative risk for

the 13 studies was 1.21 (95% CI 1.09 to 1.36). We then tested the

effect of including all randomized participants in the treatment

groups (ITT analysis) versus only those who had follow-up data

in the control groups (per protocol analysis). This has the effect of

maintaining a conservative quit rate in the treatment group, but a

more optimistic one in the control group. The analysis on this ba-

sis found little difference between the groups, with an RR of 0.88

(95% CI 0.79 to 0.98), marginally favouring the control groups.

It should be emphasised that this approach makes relatively ex-

treme assumptions about differential distribution of missing data

in treatment and control groups, which inevitably reduce the rel-

ative risk.

To further test assumptions about missing data, we repeated all

analyses on a per protocol basis, i.e. including data (where reported)

only for those participants who complete the study. Relative risks

remained similar; stage-based self-help interventions (18 trials, any

control condition) returned a per protocol RR of 1.36 (95% CI 1.23

to 1.51; analysis 7.1), compared with the ITT-based RR of 1.31

(95% CI 1.18 to 1.45). For stage-based individual counselling (13

trials, any control condition), the per protocol RR was 1.26 (95%

CI 1.10 to 1.44; analysis 7.2), compared with the ITT-based RR

of 1.24 (95% CI 1.08 to 1.42).

Although movement through the stages was not a primary out-

come of interest for our review, it is a useful test of the valid-

ity of the transtheoretical model for behaviour change. To judge

the value of the concept solely on numbers achieving abstinence

would misrepresent the process and risk underestimating its ef-

fects. Evidence from the included studies in this review was un-

clear, and depended to some degree on what measures were used

and whether regression to earlier stages was included in the calcu-

lation. Mean change scores were more sensitive to transition than

percentages measured at different points in the study process, and

took account of movement in both directions. The five studies

which used this approach found little evidence for the predictive

strength of the model, and our findings on this question remain

speculative. However, it should be emphasised that the studies in-

cluded in this review were selected for their relevance to smoking

cessation outcomes, and not to test transition between stages.

Disparities noted in the match-mismatch studies are difficult to

square with the theoretical model. Aveyard and colleagues have

speculated that standard self-help materials may be more broadly

applicable than the stages of change model assumes. They also

question the stability of the baseline staging assessments, pointing

out that in their trial (Aveyard 2003; Aveyard 2009a) 24% of the

precontemplators (i.e. with no wish to quit within the next six

months) actually made a quit attempt within three months. They

conclude from their own studies (Aveyard 2003; Lawrence 2005)

that the intensity of the intervention for those ready to try and

change may be more predictive of success than their baseline stage

of change.

The logic of the transtheoretical model is that smokers should be

assessed for their stage of change, and that interventions should



then be tailored to their stage of readiness to quit. Forward tran-

sition is the primary goal rather than smoking cessation, and mis-

matched interventions are assumed to be a waste of resources and

potentially counterproductive. The evidence from this review does

not unequivocally support this modular and linear view of the

quitting process, with trials frequently showing ’staged’ smokers

behaving unpredictably. A British Marketing Research Bureau sur-

vey in 2005 (West 2006) reported that almost half of the most

recent quit attempts among smokers and ex-smokers had involved

no previous planning. Furthermore, the odds of unplanned quit

attempts being more likely to succeed for at least six months than

planned ones were 2.6 times greater (95% CI 1.9 to 3.6) for at-

tempts made during the previous five years. While the findings

of retrospective surveys may not be wholly reliable, spontaneous

quit attempts such as these, by ’immotives’ or ’precontemplators’,

are at odds with the assumptions underpinning the staged model,

and may raise further questions about its validity and application.

Such discrepancies, together with the findings of the match-mis-

match studies and the movement through stages, may be at-

tributable to a number of factors. These include a flawed be-

havioural model, selective recall by survey participants, inaccurate

stage assessments, or underestimation of the flexibility and fit of

the standard comparators.

A U T H O R S ’ C O N C L U S I O N S

Implications for practice• Direct comparisons between the same intervention in a

standard format or modified by stage of change, with each

intervention delivered at a similar intensity, demonstrate neither

a beneficial nor a detrimental effect of the staged approach.

However, the current evidence base is underpowered, and

precludes robust conclusions.

• Offering practical support to smokers trying to quit delivers

higher success rates than ’usual care’ or assessing their smoking

status, but the additional value of adapting the intervention to

the smoker’s stage of change is unclear.

• Expert systems, tailored self-help materials and individual

counselling, appear to be as effective in a stage-based

intervention as they are in a non-stage-based form.

• The evidence is inconclusive for other types of stage-based

intervention, including telephone counselling, interactive

computer programmes and training of physicians or lay

supporters.

• The evidence does not support the restriction of quitting

advice and encouragement only to those smokers assessed as

being in the preparation and action stages.

Implications for research• Additional trials to test the value of modifying an

intervention by stage of change are unlikely to alter the

conclusions of this review.

• Trials testing the use of the transtheoretical model in stage-

matched self-help manuals should provide only those materials

which match to the participant’s current stage of change.

A C K N O W L E D G E M E N T S

We would like to thank Paul Aveyard, Arie Dijkstra, Rob Riemsma

and Robert West for reading and commenting on drafts of this

review, and Shirley Manknell for consumer input. Thanks also to

Cam Escoffery for additional data. Lindsay Stead (Cochrane To-

bacco Addiction Group) performed literature searches, and Monaz

Mehta (Cochrane Tobacco Addiction Group) double-checked all

data extraction. Rafael Perera gave statistical support.

R E F E R E N C E S

References to studies included in this review

Aveyard 1999 {published data only}

Aveyard P, Cheng KK, Almond J, Sherratt E, Lancashire

R, Lawrence T, et al.Cluster-randomized controlled trial

of expert system based on the transtheoretical (“stages of

change”) model for smoking prevention and cessation in

schools. BMJ 1999;319(7215):948–53.

Aveyard P, Markham WA, Almond J, Lancashire E, Cheng

KK. The risk of smoking in relation to engagement with a

school-based smoking intervention. Social Science Medicine

2003;56(4):869–82.∗ Aveyard P, Sherratt E, Almond J, Lawrence T, Lancashire

R, Griffin C, et al.The change-in-stage and updated

smoking status results from a cluster-randomized trial of

smoking prevention and cessation using the transtheoretical

model among British adolescents. Preventive Medicine

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balance and temptation predict stage movement? Evidence

from smoking cessation in adolescents. Addiction 2009;



104:828–38.

Guo B, Aveyard P, Fielding A, Sutton S. The factor structure

and factorial invariance for the decisional balance scale for

adolescent smoking. International Journal of Behavioral

Medicine 2009;16(2):158–63.

Aveyard 2003 {published data only}∗ Aveyard P, Griffin C, Lawrence T, Cheng KK. A controlled

trial of an expert system and self-help manual intervention

based on the stages of change versus standard self-help

materials in smoking cessation. Addiction 2003;98(3):

345–54.

Aveyard P, Massey L, Parsons A, Manaseki S, Griffin C.

The effect of Transtheoretical Model based interventions on

smoking cessation. Social Science and Medicine 2009;68(2):

397–403.

Parsons A, Aveyard P. What is transtheoretical therapy? A

response to Prochaska. Social Science and Medicine 2009;

68:407–9.

Prochaska JO. Flaws in the theory or flaws in the study:

a commentary on “The effect of Transtheoretical Model

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and Medicine 2009;68:404–6.

Bobo 1998 {published data only}

Bobo JK, McIlvain HE, Lando HA, Walker RD, Leed

Kelly A. Effect of smoking cessation counseling on recovery

from alcoholism: findings from a randomized community

intervention trial. Addiction 1998;93:877–87.

Borland 2003 {published data only}

Borland R, Balmford J, Segan C, Livingston P, Owen

N. The effectiveness of personalized smoking cessation

strategies for callers to a Quitline service. Addiction 2003;

98(6):837–46.

Borland 2004 {published data only}∗ Borland R, Balmford J, Hunt D. The effectiveness of

personally tailored computer-generated advice letters for

smoking cessation. Addiction 2004;99:369–77.

Borland R, Hunt D, Balmford J. A randomized trial of

a program of computer-generated personalized advice

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Chouinard MC, Robichaud-Ekstrand S. Predictive value

of the transtheoretical model to smoking cessation in

hospitalized patients with cardiovascular disease. European

Journal of Cardiovascular Prevention and Rehabilitation

2007;14:51–8.∗ Chouinard MC, Robichaud-Ekstrand S. The effectiveness

of a nursing inpatient smoking cessation program in

individuals with cardiovascular disease. Nursing Research

2005;54(4):243–54.

Curry 1995 {published data only}

Britt J, Curry SJ, McBride CM, Grothaus L, Louie D.

Implementation and acceptance of outreach telephone

counselling for smoking cessation with non-volunteer

smokers. Health Education Quarterly 1994;21:55–68.∗ Curry SJ, McBride C, Grothaus LC, Louie D, Wagner

EH. A randomized trial of self-help materials, personalized

feedback, and telephone counseling with nonvolunteer

smokers. Journal of Consulting and Clinical Psychology 1995;

63(6):1005–114.

Davies 2005 {published data only}

Davies SL, Kohler CL, Fish L, Taylor BE, Foster GE,

Annang L. Evaluation of an intervention for hospitalized

African American smokers. American Journal of Health

Behavior 2005;29(3):228–39.

Dijkstra 1998 {published data only}∗ Dijkstra A, De Vries H, Roijackers J. Long-term

effectiveness of computer-generated tailored feedback in

smoking cessation. Health Education Research 1998;13:

207–14.

Dijkstra A, De Vries H, Roijackers J, van Breukelen G.

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Journal of Consulting and Clinical Psychology 1998;66(3):

549–57.

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Gedrag and Gezondheid: Tijdschrift voor Psychologie and

Gezondheid 1996;24:314–22.

Dijkstra 1999 {published data only}∗ Dijkstra A, Devries H, Roijackers J. Targeting smokers

with low readiness to change with tailored and nontailored

self-help materials. Preventive Medicine 1999;28:203–11.

Escoffery 2004 {published data only}

Escoffery C, McCormick L, Bateman K. Development

and process evaluation of a web-based smoking cessation

program for college smokers: innovative tool for education.

Patient Education & Counseling 2004;53(2):217–25.

Etter 2004 {published data only}

Etter JF, Perneger TV. A comparison of cigarette smokers

recruited through the internet or by mail. International

Journal of Epidemiology 2001;30(3):521–5.∗ Etter JF, Perneger TV. Effectiveness of a computer-tailored

smoking cessation program: a randomized trial. Archives of

Internal Medicine 2001;161(21):2596–601.

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computer tailored smoking cessation programme. Journal of

Epidemiology and Community Health 2004;58(10):849–51.

Hannöver 2009 {published data only}

Hannöver W, Kelbsch J, Röske K, Thyrian JR, John U,

Hapke U. Smoking cessation and relapse prevention in

women postpartum: Results from a randomized controlled

trial. In: Velicer WF, Keller S editor(s). Research on the

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H-J, John U, et al.Smoking cessation and relapse prevention

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controlled trial at 6, 12, 18 and 24 months. Addictive

Behaviors 2009;34(1):1–8.

Röske K, Schumann A, Hannöver, Grempler J, Thyrian JR,

Rumpf H-J, et al.Postpartum smoking cessation and relapse

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Thyrian JR, Freyer-Adam J, Hannöver W, Röske K,

Mentzel F, Kufeld C, Bischof G, et al.Population-based

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John U. smoking cessation and relapse prevention among

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Thyrian JR, Hannöver W, Röske K, Rumpf H-J, John

U, Hapke U. Postpartum return to smoking: identifying

different groups to tailor interventions. Addictive Behaviors

2006;31(10):1785–96.

Hennrikus 2005 {published data only}

Hennrikus DJ, Lando HA, McCarty MC, Klevan D, Holtan

N, Huebsch JAet al. The TEAM project: the effectiveness

of smoking cessation interventions with hospital patients.

Preventive Medicine 2005;40:249–58.

Hollis 2005 {published data only}

Hollis JF, Polen MR, Whitlock EP, Lichtenstein E,

Mullooly JP, Velicer WF, et al.Teen Reach: outcomes from a

randomized controlled trial of a tobacco reduction program

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Lawrence 2005 {published data only}

Aveyard P, Lawrence T, Cheng KK, Griffin C, Croghan

E, Johnson C. A randomized controlled trial of smoking

cessation for pregnant women to test the effect of a

transtheoretical model-based intervention on movement in

stage and interaction with baseline stage. British Journal of

Health Psychology 2006;11(2):263–78.

Aveyard P, Lawrence T, Evans O, Cheng KK. The influence

of in-pregnancy smoking cessation programmes on partner

quitting and women’s social support mobilization: a

randomized controlled trial [ISRCTN89131885]. BMC

Public Health 2005;5:80.∗ Lawrence T, Aveyard P, Cheng KK, Griffin C, Johnson C,

Croghan E. Does stage-based smoking advice in pregnancy

result in long-term quitters? 18-month postpartum follow-

up of a randomized controlled trial. Addiction 2005;100:

107–16.

Lawrence T, Aveyard P, Evans O, Cheng KK. A cluster

randomised controlled trial of smoking cessation in

pregnant women comparing interventions based on the

transtheoretical (stages of change) model to standard care.

Tobacco Control 2003;12(2):168–77.

Lennox 1998 {published data only}

Lennox AS, Bain N, Taylor RJ, McKie L, Donnan PT,

Groves J. Stages of Change training for opportunistic

smoking intervention by the primary health care team.

Part I: randomised controlled trial of the effect of training

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1998;57(2):140–9.

Lennox 2001 {published data only}

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McCann Iet al. Cost effectiveness of computer tailored and

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Manfredi 2004 {published data only}

Manfredi C, Crittenden KS, Cho YI, Engler J, Warnecke

R. The effect of a structured smoking cessation program,

independent of exposure to existing interventions. American

Journal of Public Health 2000;90(5):751–6.∗ Manfredi C, Crittenden KS, Cho YI, Gao S. Long-term

effects (up to 18 months) of a smoking cessation program

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Medicine 2004;38:10–19.

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McBride 1999 {published data only}

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E, Albright J. Evaluation of a minimal self-help smoking

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Mermelstein 2003 {published data only}

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counseling for smoking cessation: does content matter?

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Schorr G, Ulbricht S, Schmidt CO, Baumeister S, Rüge

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Pallonen 1994 {published data only}

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based health promotion programs. Palo Alto, CA: Mayfield

Publishers, 2001:453–77.∗ Stotts AL, DiClemente CC, Dolan-Mullen P. One-to-one:

a motivational intervention for resistant pregnant smokers.


Thompson 1993 {published data only}

Kinne S, Thompson B, Wooldridge JA. Response to a

telephone smoking information line. American Journal of

Public Health 1991;5:410–3.∗ Thompson B, Kinne S, Lewis FM, Woolridge JA.

Randomized telephone smoking-intervention trial initially

directed at blue-collar workers. Monographs / National

Cancer Institute 1993;14:105–12.

Velicer 1999 {published data only}




Velicer WF, Cumming G, Fava JL, Rossi JS, Prochaska JO,

Johnson J. Theory testing using quantitative predictions

of effect size. Applied Psychology: an International Review

2008;57(4):589–608.

Velicer WF, Fava JL, Prochaska JO, Rossi JS, Laforge

RG. Selecting an appropriate missing data procedure in

proactively recruited clinical trials. Annual Meeting of the

Society for Multivariate Experimental Psychology, Phoenix

AZ. 1997.



smoking cessation. Addictive Behaviors 1993;18:269–90.

Velicer WF, Prochaska JO, Fava JL, Laforge RG, Rossi JS.

Interactive versus noninteractive interventions and dose-



response relationships for stage-matched smoking cessation

programs in a managed care setting. Health Psychology 1999;

18:21–8.




Velicer WF, Rossi JS, Ruggiero L, Prochaska JO. Minimal

interventions appropriate for an entire population of

smokers. In: Richmond, R editor(s). Interventions for

smokers: an international perspective. Baltimore: Williams &

Wilkins, 1994:69–92.

Wang 1994 {published data only}

Wang WD. Feasibility and effectiveness of a stages-of-

change model in cigarette smoking cessation counseling.

Journal of the Formosan Medical Association 1994;93(9):

752–7.

Young 2008 {published data only}

Young JM, Girgis S, Bruce TA, Hobbs M, Ward JE.

Acceptability and effectiveness of opportunistic referral

of smokers to telephone cessation advice from a nurse:

a randomised tiral in Australian general practice. BMC

Family Practice 2008;9:16.

References to studies excluded from this review

Abdullah 2005 {published data only}

Abdullah ASM, Mak YW, Loke AY, Lam TH. Smoking

cessation intervention in parents of young children: a

randomised controlled trial. Addiction 2005;100(11):

1731–40.

Ahluwalia 2007 {published data only}

Ahluwalia JS, Nollen N, Kaur H, James AS, Mayo MS,

Resnicow K. Pathways to health: cluster-randomized trial

to increase fruit and vegetable consumption among smokers

in public housing. Health Psychology 2007;26(2):214–21.

Andersen 2006 {published data only}

Andersen S. Adding addiction to the transtheoretical

model for smoking cessation. Addictive Behaviors 2007;32:

1099–104.

Armitage 2008 {published data only}

Armitage CJ, Arden MA. How useful are the stages of

change for targeting interventions? Randomized test of a

brief intervention. Health Psychology 2008;27:789–98.

Baker 2006 {published data only}

Baker A, Richmond R, Haile M, Lewin TJ, Carr VJ,

Taylor RL, et al.A randomized controlled trial of a smoking

cessation intervention among people with a psychotic

disorder. American Journal of Psychiatry 2006;163(11):

1934–42.

Becona 2001 {published data only}

Becona E, Vazquez FL. Effectiveness of personalized written

feedback through a mail intervention for smoking cessation:

a randomized-controlled trial in Spanish smokers. Journal

of Consulting and Clinical Psychology 2001;69(1):33–40.

Berman 1995 {published data only}

Berman BA, Gritz ER, Braxton Owens H, Nisenbaum R.

Targeting adult smokers through a multi-ethnic public

school system. Journal of Cancer Education 1995;10:

91–101.

Borrelli 2002 {published data only}

Borrelli B, McQuaid EL, Becker B, Hammond K,

Papandonatos G, Fritz G, et al.Motivating parents of kids

with asthma to quit smoking: the PAQS project. Health

Education Research 2002;17(5):659–69.

Campbell 2004 {published data only}

Campbell ANC, Fisher DS, Picciano JF, Orlando MJ,

Stephens RS, Roffman RA. Marketing effectiveness in

reaching the nontreatment-seeking marijuana smoker.

Journal of Social Work Practice in the Addictions 2004;4(1):

39–59.

Carlson 2003 {published data only}

Carlson LE, Taenzer P, Koopmans J, Casebeer A. Predictive

value of aspects of the Transtheoretical Model on smoking

cessation in a community-based, large-group cognitive

behavioral program. Addictive Behaviors 2003;28(4):

725–40.

Chan 2005 {published data only}∗ Chan SC, Lam TH, Lau C-P. The effectiveness of a

nurse-delivered smoking cessation intervention for cardiac

patients: a randomised controlled trial. Nicotine & Tobacco

Research 2005;7(4):692.

Chan SSC, Chan SC, Lam TH, Lau C-P. The effectiveness

of a stage-matched smoking cessation intervention to cardiac

patients: Preliminary results of a randomised controlled trial

[POS3-97]. Society for Research on Nicotine and Tobacco

9th Annual Meeting, February 19th-22nd, New Orleans,

LA. 2003.

Cornuz 2002 {published data only}

Cornuz J, Humair JP, Seematter L, Stoianov R, van Melle

G, Stalder Het al. Efficacy of resident training in smoking

cessation: a randomized, controlled trial of a program

based on application of behavioral theory and practice

with standardized patients.[summary for patients in Ann

Intern Med. 2002 Mar 19;136(6):I31 ]. Annals of Internal

Medicine 2002;136(6):429–37.

Humair JP, Cornuz J. Training physicians in smoking

cessation: Research and education serving public health.

Médecine & Hygiène 2003;61(2451):1809–15.

Humair J-P, Cornuz J. A new curriculum using active

learning methods and standardized patients to train

residents in smoking cessation. Journal of General Internal

Medicine 2003;18:1023–7.

Humair J-P, Cornuz J. Continuing and postgraduate

training of doctors in smoking cessation: description of an

effective programme [Formation postgraduée et continue

des médecins à la désaccoutumance au tabac: description

d’un programme efficace]. Médecine & Hygiène 2003;2451:

1809–15.

Dijkstra 1998b {published data only}

Dijkstra A, Devries H, Roijackers J. Computerized tailored

feedback to change cognitive determinants of smoking: a

Dutch field experiment. Health Education and Research

1998;13:197–206.



Dijkstra 1998c {published data only}

Dijkstra A, De Vries H, Roijackers J, van Breukelen G.

Tailoring information to enhance quitting in smokers with

low motivation to quit: three basic efficacy questions.


Dijkstra 2006 {published data only}

Dijkstra A, Conijn B, de Vries H. A field experiment

on stages of change for smoking cessation: the effects

of matched and mismatched information. Psychologie &

Gezonheid 2007;35:5–16.∗ Dijkstra A, Conijn B, de Vries H. A match-mismatch test

of a stage model of behaviour change in tobacco smoking.

Addiction 2006;101(7):1035–43.

Drevenhorn 2007 {published data only}

Drevenhorn E, Bengtson A, Allen, JK, Säljö R, Kjellgren K.

Counselling on lifestyle factors in hypertension care after

training on the stages of change model. European Journal of

Cardiovascular Nursing 2007;6(1):46–53.

Erol 2008 {published data only}

Erol S, Erdogan S. Application of a stage based motivational

interviewing approach to adolescent smoking cessation: the

transtheoretical model-based study. Patient Education and

Counseling 2008;72:42–8.

Ershoff 1999 {published data only}

Ershoff DH, Quinn VP, Boyd NR, Stern J, Gregory M,

Wirtschafter D. The Kaiser Permanente prenatal smoking-

cessation trial. When more isn’t better, what is enough?.

American Journal of Preventive Medicine 1999;17(3):161–8.


Etter JF. Comparing the efficacy of two Internet-based,

computer-tailored smoking cessation programs: a

randomized trial. Journal of Medical Internet Research 2005;

7(1):e2.


Etter J-F. Comparing computer-tailored, internet-based

smoking cessation counseling reports with generic,

untailored reports: a randomized trial. Journal of Health

Communication 2009;14(7):646–57.

Fang 2006 {published data only}

Fang CY, Ma GX, Miller SM, Tan Y, Su X, Shive S. A brief

smoking cessation intervention for Chinese and Korean

American smokers. Preventive Medicine 2006;43(4):321–4.

Fritz 2008 {published data only}

Fritz DJ, Hardin SB, Gore PA Jr, Bram D. A computerised

smoking cessation intervention for high school smokers.

Pediatric Nursing 2008;34:13–17.

Gritz 1993 {published data only}

Gritz ER, Carr CR, Rapkin D, Abemayor E, Chang LJ,

Wong WKet al. Predictors of long-term smoking cessation

in head and neck cancer patients. Cancer Epidemiology,

Biomarkers & Prevention 1993;2(3):261–70.

Hall 2006 {published data only}

Hall SM, Tsoh JY, Prochaska JJ, Eisendrath S, Rossi JS,

Redding CAet al. Treatment for cigarette smoking among

depressed mental health outpatients: A randomized clinical

trial. American Journal of Public Health 2006;96(10):

1808–14.

Haug 2009 {published data only}

Haug S, Meyer C, Schorr G, Bauer S, John U. Continuous

individual support of smoking cessation using text

messaging: a pilot experimental study. Nicotine & Tobacco

Research 2009;11(8):915–23.

Hoving 2007 {published data only}

Hoving EF. The feasibility of a smoking cessation computer

tailored expert system in Dutch general practice and

community pharmacy setting. http://arno.unimaas.nl/

show.cgi?fid=9388 2007.

Hoving EF, Mudde AN, de Vries H. Smoking and the Ø

pattern; predictors of transitions through the stages of

change. Health Education Research 2006;21(3):305–14.

Smit ES, Hoving C, de Vries H. Does a typical contemplator

exist? Three clusters of smokers in contemplation. Health

Education Research 2010;25(1):61–73.

Huang 2005 {published data only}

Huang M, Hollis J, Polen M, Lapidus J, Austin D. Stages

of smoking acquisition versus susceptibility as predictors of

smoking initiation in adolescents in primary care. Addictive

Behaviors 2005;30(6):1183–94.

Hughes 2000 {published data only}

Hughes EG, Lamont DA, Beecroff ML, Wilson DMC,

Brennan BG, Rice SC. Randomized trial of a “stage-of-

change” oriented smoking cessation intervention in infertile

and pregnant women. Fertility and Sterility 2000;74(3):

498–503.

Hughes 2005 {published data only}

Hughes JR, Keely JP, Fagerstrom KO, Callas PW. Intentions

to quit smoking change over short periods of time. Addictive

Behaviors 2005;30(4):653–62.

Hyman 2007 {published data only}

Hyman DJ, Pavlik VN, Taylor WC. Simultaneous vs

sequential counseling for multiple behaviour change.

Archives of Internal Medicine 2007;167:1152–8.

Jennings 2007 {published data only}

Jennings EG. A randomized clinical trial in a child health

care setting comparing two brief interventions to reduce

environmental tobacco smoke exposure. Dissertation

Abstracts International 2007;Part B: The Sciences and

Engineering(67):pp–B.

Johs 2003 {published data only}

Johs Artisensi JL. The effect of web-based support as

an adjunct to a self-help smoking cessation program.

Dissertation Abstracts International: Section B: The Sciences

and Engineering 2003;63(9-B):4138.

Jones 2003 {published data only}

Jones H, Edwards L, Vallis TM, Ruggiero L, Rossi SR,

Rossi JS, et al.Changes in diabetes self-care behaviors make

a difference in glycemic control: the Diabetes Stages of

Change (DiSC) Study. Diabetes Care 2003;26(3):732–7.

Jones H, Ruggiero L, Edwards L, Vallis TM, Rossi S, Rossi

JS, et al.Diabetes Stages of Change (DiSC): methodlogy



and study design. Canadian Journal of Diabetes Care 2001;

25:97–107.

Keller 2000 {published data only}

Keller S, Donnerbanzhoff N, Kaluza G, Baum E, Basler

HD. Improving physician-delivered counseling in a primary

care setting: Lessons from a failed attempt. Education for

Health 2000;13(3):387–97.

Kim 2004 {published data only}

Kim S, Nam KA, Seo M, Lee HH. Effectiveness of a

smoking cessation program for adolescents. Taehan Kanho

Hakhoe Chi 2004;34(4):646–54.

Kim 2009 {published data only}

Kim YH, Kim JS, Kim MS. Effectiveness of public health

center smoking cessation counseling program using the

transtheoretical model [Korean]. Journal of Korean Academy

of Nursing 2009;39(4):469–79.

Kohler 2008 {published data only}

Kohler CL, Schoenberger YM, Tseng TS, Ross L. Correlates

of transitions in stage of change for quitting among

adolescent smokers. Addictive Behaviors 2008;33:1615–8.

Lipkus 1999 {published data only}

Lipkus IM, Lyna PR, Rimer BK. Using tailored

interventions to enhance smoking cessation among African-

Americans at a community health center. Nicotine &

Tobacco Research 1999;1(1):77–85.

Rimer BK, Glassman B. Tailored communications for

primary care settings. Methods of Information in Medicine

1998;37:171–8.

Ma 2005 {published data only}

Ma GX, Fang C, Shive SE, Su X, Toubbeh JI, Miller S, et

al.A culturally enhanced smoking cessation study among

Chinese and Korean smokers. International Electronic

Journal of Health Education 2005;8(1):1–10.

McDonald 2003 {unpublished data only}

McDonald PW, Jessup L, Brown KS, Ahmed R, Filsinger

S. Are cessation interventions based on stage of change

really more effective? [POS4-27]. Society for Research on

Nicotine and Tobacco, 9th Annual Meeting, February 19th-

22nd, New Orleanss, LA. 2003:88.

Morgan 1996 {published data only}

Morgan GD, Noll EL, Orleans CT, Rimer BK, Amfoh K,

Bonney G. Reaching midlife and older smokers - tailored

interventions for routine medical care. Preventive Medicine

1996;25:346–54.

Osinubi 2003 {published data only}

Osinubi OY, Moline J, Rovner E, Sinha S, Perez-Lugo

M, Demissie Ket al. A pilot study of telephone-based

smoking cessation intervention in asbestos workers. Journal

of Occupational and Environmental Medicine 2003;45(5):

569–74.

Pallonen 1998 {published data only}

Pallonen UE, Velicer WF, Prochaska JO, Rossi JS, Bellis

JM, Tsoh JYet al. Computer-based smoking cessation

interventions in adolescents: Description, feasibility, and

six-month follow-up findings. Substance Use and Misuse

1998;33(4):935–65.

Pisinger 2005 {published data only}

Jørgensen T, Borch-Johnsen K, Thomsen TF, Ibsen H,

Glümer C, Pisinger C. A randomized non-pharmacological

intervention study for prevention of ischaem,ic heart disease:

baseline results Inter99 (1). Cardiovascular Prevention and

Rehabilitation 2003;10:377–86.

Pisinger C. Smoking cessation and smoking reduction in

a general population. The Inter99 study. A randomised

population-based intervention study. Nordic Journal of

Psychiatry 2006;60(1):67.

Pisinger C, Glümer C, Toft U, von Huth Smith L, Aadahl

M, Borch-Johnsen K, et al.High risk strategy in smoking

cessation is feasible on a population-based level. The

inter99 study. Preventive Medicine 2008;46:579–84.

Pisinger C, Vestbo J, Borch-Johnsen K, Jorgensen T. It is

possible to help smokers in early motivational stages to quit.

The Inter99 study. Preventive Medicine 2005;40(3):278–84.

Pisinger C, Vestbo J, Borch-Johnsen K, Jorgensen T.

Smoking cessation intervention in a large randomised

population-based study. The Inter99 study. Preventive

Medicine 2005;40(3):285–92.

Pisinger C, Vestbo J, Borch-Johnsen K, Thomsen T,

Jørgensen T. Acceptance of the smoking cessation

intervention in a large population-based study: The Inter99

study. Scandinavain Journal of Public Health 2005;33:

138–45.

Pletsch 2002 {published data only}

Pletsch PK. Reduction of primary and secondary smoke

exposure for low-income black pregnant women. Nursing

Clinics of North America 2002;37(2):315-29, viii.

Quinlan 2000 {published data only}

Quinlan KB, McCaul KD. Matched and mismatched

interventions with young adult smokers: Testing a stage

theory. Health Psychology 2000;19(2):165–71.

Reeve 2000 {published data only}

Reeve K, Calabro K, Adams-McNeill J. Tobacco cessation

intervention in a nurse practitioner managed clinic. Journal

of the American Academy of Nurse Practitioners 2000;12(5):

163–9.

Reid 2003 {published data only}

Reid R, Pipe A, Higginson L, Johnson K, D’Angelo MS,

Cooke Det al. Stepped care approach to smoking cessation

in patients hospitalized for coronary artery disease. Journal

of Cardiopulmonary Rehabilitation 2003;23(3):176–82.

Resnicow 1997 {published data only}

Resnicow K, Royce J, Vaughan R, Orlandi MA, Smith M.

Analysis of a multicomponent smoking cessation project:

What worked and why. Preventive Medicine 1997;26:

373–81.

Rissel 2000 {published data only}

Rissel C, Salmon A, Hughes AM. Evaluation of a (pilot)

stage-tailored brief smoking cessation intervention among

hospital patients presenting to a hospital pre-admission

clinic. Australian Health Review 2000;23(3):83–93.



Schneider 1990 {published data only}

Schneider SJ, Walter R, O’Donnell R. Computerised

communication as a medium for behavioral smoking

cessation treatment: Controlled evaluation. Computers in

Human Behavior 1990;6:141–51.

Simon 2003 {published data only}

Simon JA, Carmody TP, Hudes ES, Snyder E, Murray J.

Intensive smoking cessation counseling versus minimal

counseling among hospitalized smokers treated with

transdermal nicotine replacement: a randomized trial.

American Journal of Medicine 2003;114(7):555–62.

Sinclair 1998 {published data only}

Sinclair H, Bond C, Lennox AS, Silcock J, Winfield A. An

evaluation of a training workshop for pharmacists based on

the Stages of Change model of smoking cessation. Health

Education Journal 1997;56:296–312.

Sinclair HK, Bond CM, Lennox AS. The long-term

learning effect of training in stage pf change for smoking

cessation: a three-year follow up of community pharmacy

staff ’s knowledge and attitudes. International Journal of

Pharmacy Practice 1999;7:1–11.∗ Sinclair HK, Bond CM, Lennox AS, Silcock J, Winfield

AJ, Donnan PT. Training pharmacists and pharmcay

assistants in the stage-of-change model of smoking cessation:

a randomised controlled trial in Scotland. Tobacco Control

1998;7:253–61.

Sinclair HK, Silcock J, Bond CM, Lennox AS, Winfield

AJ. The cost-effectiveness of intensive pharmaceutical

intervention in assisting people to stop smoking. Internation

Journal of Pharmacy Practice 1999;7:107–12.

Skewes 2007 {unpublished data only}

Skewes MC. Utep women kick butt! development,

implementation and evaluation of a web-based smoking

cessation intervention targeted to Hispanic female college

students (Texas). Dissertation Abstracts International 2007;

Vol. 67, issue 11–B.

Swanson 2003 {published data only}

Swanson NA, Burroughs CC, Long MA, Lee RW.

Controlled trial for smoking cessation in a Navy shipboard

population using nicotine patch, sustained-release

buproprion, or both. Military Medicine 2003;168(10):

830–4.

Tanaka 2006 {published data only}

Tanaka H, Yamato H, Tanaka T, Kadowaki T, Okamura T,

Nakamura M, et al.Effectiveness of a low-intensity intra-

worksite intervention on smoking cessation in Japanese

employees: a three-year intervention trial. Journal of

Occupational Health 2006;48:175–82.

Tappin 2000 {published data only}

Tappin DM, Lumsden MA, McIntyre D, Mckay C,

Gilmour WH, Webber Ret al. A pilot study to establish

a randomized trial methodology to test the efficacy of a

behavioural intervention. Health Education Research 2000;

15(4):491–502.

Tsoh 2005 {unpublished data only}

Tsoh J, Delucchi K, Benowitz N, Hall S. Cigarette reduction

predicts 12-month smoking cessation in Chinese smokers.

Society for Research on Nicotine and Tobacco, 11th Annual

Meeting, 20th-23rd March, Prague, Czech Republic. 2005.

Valanis 2001 {published data only}

Valanis B, Lichtenstein E, Mullooly JP, Labuhn K, Brody K,

Severson HH, et al.Maternal smoking cessation and relapse

prevention during health care visits. American Journal of


Webb 2005 {published data only}

Webb MS, Simmons VN, Brandon TH. Tailored

interventions for motivating smoking cessation: using

placebo tailoring to examine the influence of expectancies

and personalization. Health Psychol 2005;24(2):179–88.

Wiggers 2005 {published data only}

Wiggers LC, Stalmeier PF, Oort FJ, Smets EM, Legemate

DA, de Haes JC. Do patients’ preferences predict smoking

cessation?. Preventive Medicine 2005;41(2):667–75.

Williams 2006 {published data only}

Williams GC, McGregor HA, Sharp D, Levesque C,

Kouides RW, Ryan RMet al. Testing a Self-Determination

Theory Intervention for Motivating Tobacco Cessation:

Supporting Autonomy and Competence in a Clinical Trial.


Wilson 2008 {published data only}

Wilson JS, Fitzsimons D, Bradbury I, Elborn JS. Does

additional support by nurses enahnce the effect of a brief

smoking cessation intervention in people with moderate to

severe chronic obstructive pulmonary disease? a randomised

controlled trial. International Journal of Nursing Studies

2008;45:508–17.

Wu 2009 {published data only}

Wu D, Ma GX, Zhou K, Zhou D, Liu A, Poon AN. The

effect of a culturally tailored smoking cessation for Chinese

American smokers. Nicoitne & Tobacco Research 2009;11

(12):1448–57.

Young 2002 {published data only}

Young JM, Ward J. Can distance learning improve smoking

cessation advice in family practice? A randomized trial.

Journal of Continuing Education in the Health Professions

2002;22(2):84–93.

References to ongoing studies

Cabezas 2009 {published data only}

Cabezas C, Martin C, Granollers S, Morera C, Ballve

JL, Zarza E, et al.Effectiveness of a stepped primary care

smoking cessation intervention (ISTAPS study): design of a

cluster randomised trial. BMC Public Health 2009;9:48–59.

[: clinicaltrials ID: NCT00125905]

Prokhorov 2010 {published data only}

Prokhorov AV, Kelder SH, Shegog R, Conroy JL, Murray N,

Peters R, et al.Project ASPIRE: an interactive, multimedia

smoking prevention and cessation curriculum for culturally



diverse high school students. Substance Use & Misuse 2010;

45:983–1006.

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Blissmer B, McAuley E. Testing the requirements of

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C H A R A C T E R I S T I C S O F S T U D I E S

Characteristics of included studies [ordered by study ID]

Aveyard 1999

Methods Setting: 52 schools, West Midlands, UK.

Study Design: Cluster-randomized controlled trial

Recruitment: Year 9 classes of students; 52 schools agreed / 89 schools approached

SoC model: Standard TTM (10 processes of change, decisional balance, self-efficacy,

temptations to smoke)

Participants Students aged 13-14; Int (4125), controls (4227). Ethnicity 86% W; gender 50% M.

Smoking prevalence: Int: 13.3% current (547), 7.6% ex, 26.5% tried, 51.8% never.

Control: 12.8% current (543), 8.5% ex, 23.2% tried, 54.8% never.

Only children smoking at baseline included in the analysis

Interventions Intervention: 1 computer session and 1 class lesson per term (=6 sessions). Computer

sessions were interactive expert system, questionnaire + visual and oral feedback. 2nd

and 3rd sessions included feedback from previous sessions; included tailored video clips

of other students.

Lesson was 1hr with their own teacher, to explore SoC and pros and cons of smoking

Control: Usual care, i.e. standard English curriculum on smoking i.e. smoking quizzes

and advice on persuading people to quit

Outcomes Prevalence of weekly and daily smoking at 1yr and 2yrs.

Biochem validation: None

2 year 30-day PPA supplied by author.

Notes Type of intervention: Interactive computer expert system

Interclass correlation of 0.008.

Funded by West Midlands Health Authorities (NHS)

Risk of bias

Item Authors’ judgement Description

Adequate sequence generation? Yes Computer-generated block randomiza-

tion, balanced by class size

Allocation concealment? Yes Computerised and anonymised

Blinding?

All outcomes

Unclear N/A

Incomplete outcome data addressed?

All outcomes

Yes Analyses tested all models of losses to follow

up (Table 3)



Aveyard 1999 (Continued)

Free of other bias? Unclear Fidelity of implementation for controls un-

clear

Aveyard 2003

Methods Setting: 65 general practices, West Midlands, UK

Study design: Randomized controlled trial

Recruitment: Inviting randomly selected smokers within practices to participate; 3 waves

of recruitment, with 3rd wave practices non-randomly selected.

SoC Model: TTM, Pro-Change programme

Participants Manual Group (683), Phone Group (685), Nurse Group (413), Controls (690). Gender

42% M; ethnicity 96% W; mean CPD 20;

Motivation to quit not required.

Interventions Int 1. Manual: TTM-based Pro-Change programme for a healthier lifestyle + 6-8 pp expert

system letter based on Q responses; Qs at 3m and 6m, to generate 2 more tailored letters.

Int 2. Phone: As 1, + phone calls at baseline, 3m and 6m, structured as reminders rather

than motivational.

Int 3. Nurse: As 1, + nurse appointment to explain and motivate.

Control: (i) Stopping smoking made easier booklet

(ii) The Quit guide to stopping smoking manual

(iii) ’Credit card’ with bulleted quit tips

(iv) ’credit card’ with pros and cons of smoking.

(i) - (iii) all included quitline phone number

Outcomes PPA and sustained abstinence at 12m.

Biochem validation: Salivary cotinine, face-to-face or postal sample. >14.2ng/ml=smok-

ing

Notes Type of intervention: Tailored self help; expert system; telephone counselling; individual

counselling.

We have compared Int 1 (TTM manuals) with Control (standard SH manuals) for our

MAs in this review.

Uptake on nurse arm very low, so abandoned for wave 3 recruitment. Analyses performed

as 3-way and 4-way comparisons.

Funded by West Midlands Health Authorities (NHS)

Risk of bias


Adequate sequence generation? Yes Minimization, balancing SoC, FTND and

SES; Qs read optically into ACCESS

database

Allocation concealment? Yes Computerised



Aveyard 2003 (Continued)

Blinding?

All outcomes

Unclear Not reported


All outcomes

Yes Complete case and ITT analyses per-

formed. Control lost 24%, Int 1 31%, Int

2 31%, Int 3 29%

Free of other bias? No Wave 3 practices were targeted, not ran-

domly selected; some practices mixed Qs

between waves 1 and 2, leading to some

oversampling in wave 1

Bobo 1998

Methods Setting: 12 alcohol drug treatment centres, Iowa, Kansas and Nebraska, USA.

Study design: Cluster-randomized controlled trial, six matched pairs, each pair 50+ miles

apart

Recruitment: By study staff, with scripts and a/v aids, enrolled 50 per site. All smokers

eligible.

SoC Model: TTM;

Participants Int (288), Control (287); 67% M, mean age 33, 33% “ethnic minority”. Mean CPD

20.

Motivation to quit not required, but conts encouraged to think about quitting.

Interventions All completed baseline and follow-up Qs.

Int: 1 x face-to-face session in treatment centre, delivered by centre staff, + 3 follow-

up phone calls, at 8w, 12w and 16w. All sessions 10-15 mins. Follow up delivered by

counsellors trained in psychology, health education or social work.

Control: ’usual care with respect to tobacco use’.

Outcomes 7-day PPA at 1, 6 and 12m.

Validation: 70% of quitters supplied saliva cotinine; also by collateral informants for

30% of respondents

Notes Type of intervention: individual counselling, follow-up telephone support.

Supported by National Institute on Alcohol Abuse and Alcoholism

Risk of bias


Adequate sequence generation? Yes “randomly determined by coin toss”

Allocation concealment? Unclear Not reported



Bobo 1998 (Continued)

Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes Response rates at 1m 86%, 6m 82%, 12m

78%

Free of other bias? Unclear Not stated

Borland 2003

Methods Setting: smokers calling a quitline in Victoria, Australia

Study Design: Randomized controlled trial

Recruitment: Invited to participate after consent and baseline assessment.

SoC Model: TTM, adapted for Australian users; all received stage-based support, but int

groups were interactive and tailored

Participants Int 1: Tailored letters (523); Int 2: Callback (528); Int 3: Control (527). Gender 46%

M; mean CPD 23; No sig diffs in baseline SoC between groups. 56% had made quit

attempt in previous 12m.

Motivation to quit implicit in contact call, but not required

Interventions Control: Quit pack: 30pp Can Quit Book, using SoC; leaflets promoting callback service

and Fresh Start smoking cessation courses; ’business card’ with strategies for craving

reduction. [Callers who requested callback were excluded]

Int 1: As control, + 2-3pp computer-generated letters based on responses at baseline, 3m

and 6m. Feedback and tailored advice on cons of smoking, up to 6 processes of change

and temptations to smoke

Int 2: As Int 1, + callback, i.e. a series of CBT-based stage-based calls around quit attempts

or relative to letters; calls lasted 10-15 mins

Outcomes 9m sustained at 12m, 3m sustained at 6m, 12m PPA.

Biochem validation: None

Notes Type of intervention: self help; expert system; telephone counselling.

We have compared Int 1 (SH manuals + ES letters) with Control (SH manuals) for our

MAs in this review.

Funded by NHMRC, The Cancer Council Victoria, and Quit Victoria

Risk of bias


Adequate sequence generation? No “by shuffling questionnaires”

Allocation concealment? Unclear “no opportunity for interviewers to influ-

ence the choice of condition”



Borland 2003 (Continued)

Blinding?

All outcomes

Yes Pts only informed of their assigned condi-

tion, not of other options


All outcomes

Yes Complete case and ITT analyses; 23.4%

dropped out by 12m, with a trend for

higher losses in more intensive int groups

Free of other bias? Unclear Of 528 callback pts, only 358 received any

calls (129 refused, 41 not reached)

Borland 2004

Methods Setting: Telephone quitline in Victoria, Australia

Study Design: Randomized controlled trial

Recruitment: Invited adult smokers or recent quitters calling quitline and requesting S-

H materials only.

SoC Model: Modified TTM, adapted to ’perspectives on change’, i.e. six levels. ’Steps to

Stop’ programme

Participants Int 521, Control 537, mix of current and former smokers. Int smokers refusing tailored

advice (34) remained in Int group and followed up.

Baseline smokers only are included in our analyses (Int 382, Control 390).

46% M, mean age 47, mean CPD 19. 27% already quit at baseline.

Motivation to quit implicit in contact call, but not required

Interventions Int: Series of assessments followed by computerised letter, tailored to SoC, quitting

history, level of addiction, need for NRT, lapses, age, gender. Also standard S-H info

sent as needed. Schedule varied by progress. Mean 5.7 letters received

Control: Standard ’quit pack’, i.e. A5 SoC booklet, details of callback service and group-

based counselling

Outcomes Assessments at 3, 6 and 12m

Self-reported 6m sustained abstinence at 12m

PPA at 12m

Validation: None

Notes Type of intervention: Written S-H materials; tailored advice letters.

Funded by NHMRC.

Risk of bias


Adequate sequence generation? Yes “computer-generated ID numbers, with

even numbers allocated to the intervention

group”



Borland 2004 (Continued)

Allocation concealment? Unclear Not stated

Blinding?

All outcomes

Yes “participants in each condition [did] not

know about the other condition unless they

specifically asked ... (none did)”


All outcomes

No 3m and 6m assessments sig lower for Int

groups (3.8% vs 2.0% controls; P<0.001);

No sig diffs at 12m

Free of other bias? No Low response rates at 3m and 6m in Int

group, so only 12m comparison data used

Chouinard 2005

Methods Setting: Regional tertiary hospital, Quebec, Canada

Study Design: Cluster-randomized controlled trial

Recruitment: CVD inpatients

SoC Model: Modified TTM, conceived as a ’spiral’ rather than a linear progression

Participants Int 1 (56), Int 2 (56), Control (56), plus 57 non-pts. 73% M, mean age 56, CPD not

reported.


Interventions All pts encouraged to use NRT or bupropion if wished

Int 1: Individual I/P counselling session, mean duration 40 mins, + 6 follow-up phone

calls over 2m.

Int 2: I/P counselling session only.

Control: Usual care, i.e. general advice on SC, + pharma if wished.

Outcomes 7-day PPA and CA at 6m

Validation: urinary metabolites, or expired CO

Notes Type of intervention: Nurse-delivered individual counselling telephone follow up.

We have combined Ints 1 and 2 (stage-based counselling phone calls) vs Control for

our MAs in this review.

Funding not specified.

Risk of bias


Adequate sequence generation? Unclear Not stated

Allocation concealment? Yes Sealed envelopes



Chouinard 2005 (Continued)

Blinding?

All outcomes

Yes “Individuals not familiar with the study

were in charge of the randomization pro-

cedure”


All outcomes

Yes At 6m, Ints 1 and 2 each lost 3, and controls

lost 1. 25% of Int 1 pts did not receive all

6 calls


Curry 1995

Methods Setting: HMO in Puget Sound, WA, USA

Study Design: randomized controlled trial

Recruitment: non-volunteer population-based sample of HMO members

SoC Model: Modified TTM; no previous quit attempt required for conts

Participants Int 1 (330), Int 2 (329), Int 3 (150), Control (328). 47% M, mean age 41, mean CPD

17.


Interventions Incremental programmes:

Int 1: Manual: Breaking Away S-H programme booklet, 8 units covering all stages of

change.

Int 2: as 1, + personalized feedback: computer-generated from baseline Q data, tailored

to SoC.

Int 3: as 2, + phone calls tailored to SoC at 2w, 6w, 10w.

Control: No materials or intervention

Outcomes 24-hr quit; 7-day PPA; CA between follow-up points.

Validation: Salivary cotinine at 12m only

Notes Type of intervention: S-H, tailored feedback, phone support

Resources limited number randomized to phone intervention.

We have compared Int 2 (TTM manual + feedback) vs Control (assessment) for our

MAs in this review.

Funded by National Institute on Drug Abuse

Risk of bias


Adequate sequence generation? Unclear Not stated


Blinding?

All outcomes

Unclear Not stated



Curry 1995 (Continued)


All outcomes

Yes 24% dropped out by 21m; 88% provided

data at 3m and 12m, 67% at 3m, 12m and

21m

Free of other bias? Unclear S-H manual included all stages, so not truly

tailored.

Davies 2005

Methods Setting: Public indigent-care hospital, Birmingham, AL, USA

Study Design: randomized pretest post-test trial

Recruitment: low-income African-American in-patient smokers

Study: HOPE intervention

SoC Model: Transtheoretical Model of Change (TCM)

Participants Int (127), Control (121); 67% M, mean age 47, mean CPD 16. Ns not reported but

extrapolated from results section.

Motivation to quit not required

Interventions Int: (i) brief stage-matched physician advice, recommending NRT if appropriate; (ii)

1x 20-30 min tailored, stage-matched counselling session; (iii) S-H manual Pathways toFreedom (iv) post-discharge phone call at 2w; same counsellor.

Control: usual care

Outcomes PPA at 6m

Validation: None

Notes Significant losses to follow up (114/248 completed at 6m post-discharge); only used

follow-up data collected 6-9m after intervention; Int 50, Control 46.

Type of intervention: Physician advice, individual counselling, S-H, follow-up phone

support.

Funded by National Cancer Institute.

Risk of bias


Adequate sequence generation? Unclear randomization by hospital room


Blinding?

All outcomes

Unclear Not stated


All outcomes

Unclear Major losses to follow up (152/248), but

no significant differences between lost and

retained, other than mean age (43 vs 47)



Davies 2005 (Continued)

Free of other bias? Unclear Not stated; population was difficult to re-

cruit and to retain

Dijkstra 1998

Methods Setting: Population-based, Netherlands


Recruitment: any cigarette smokers

SoC Model: modified TTM, with new category ’immotives’, i.e. no plans for any change

at any time

Participants 1540 Qs returned from 1733 registrants. Int 1: OC (384), Int 2: SE (385), Int 3: BO

(386), Control (385). 41% M, mean age 40, mean CPD 20.


Interventions Int 1. OC: computer-generated tailored letter on outcomes of smoking and quitting.

Int 2. SE: computer-generated tailored letter on self-efficacy, active skills to quit, boosting

confidence, coping skills.

Int 3. BO: computer-generated tailored letter stressing both types of info.

Control: Letter confirming no S-H info would be sent

Outcomes 7-day PPA at 10w and 14m

Validation: None; ’bogus pipeline’ used.

Notes Type of intervention: computer-generated tailored mailed S-H materials.

We have compared Ints 1+2+3 (stage-based letters) vs Control (assessment only) for our

MAs in this review.

Study funded by the Dutch Cancer Society

Risk of bias


Adequate sequence generation? Unclear “smokers were randomly assigned”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes 36% at 14m; no diffs between groups re-

ported. Analyses repeated with ITT [not

quite sure what the 36% is, isn’t it 61% lost

to follow up - 152/248?]




Dijkstra 1999

Methods Setting: Population-based, Netherlands


Recruitment: nation-wide local newspaper advertising

SoC Model: modified TTM, with new category ’immotives’, i.e. no plans for any change

at any time

Participants 843, assigned to Int 1: MT (214), Int 2: ST (206), Int 3: SHG (215), Control (208).

63% F, mean age 42, mean CPD 21.5

Pts selected for low or no motivation to quit

Interventions Int 1: MT: 3 computer-generated tailored letters, at 2wks, 7wks and 12wks; 2nd and

3rd modified by 10 min phone interviews.

Int 2: ST: single computer-generated tailored letter at 2wks.

Int 3: SHG: 46pp S-H Guide

Control: CO: no materials sent

Outcomes 7-day PPA at 6m

Validation: None

Notes Type of intervention: computer-generated tailored letter(s), S-H manual.

We have compared Ints 1+ 2 (stage-based letters) vs Int 3 (SH Guide) for our MAs in

this review.

Study supported by the Dutch Cancer Society

Risk of bias


Adequate sequence generation? Unclear “smokers were randomly assigned”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes 11% at 6m (MT 12.6%, ST 12.2% [I get

12.6%], SHG 6.9% [6.5%], CO 12.5%).

Analyses repeated as ITT




Escoffery 2004

Methods Setting: College, Atlanta, GA, USA


Recruitment: ads, fliers, posters, mailings; recruitment incentives

Study: Kick It! Programme

SoC Model: TTM

Participants 70 college student smokers, Int (35), Control (35). Int: 43% M, mean age 21, mean

CPD 9.


Interventions Int: 4 x web-based sessions, 2-7 screens of SC information, tailored and interactive, over

2wks. Stage assessment, stage-matched messages, approaches to managing temptation,

alternatives to smoking. Feedback online and by email, + links to related websites.

Control: No intervention, assessment only

Outcomes PPA at 6m

Validation: None

Notes Type of intervention: Interactive web-based S-H

Additional data supplied by the author.

Funded by National Institute of Drug Abuse

Risk of bias


Adequate sequence generation? No “simple randomization through drawings

and alternate assignment”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes 46% lost at post-test, 35% at 6m


Etter 2004

Methods Setting: Population-based, francophone Switzerland


Recruitment: 20,000 invitations to random addresses in population register.

SoC Model: TTM, (no previous quit attempt required for conts), + theory of planned

behaviour, theories of RP and tobacco dependence, AHCP recommendations



Etter 2004 (Continued)

Participants Daily smokers, randomized to Int (1467), Control (1467). 48% M, mean age 36, mean

CPD 20.


Interventions Int: Computer-generated tailored counselling letters (baseline, 2m and 4m), with car-

toons and graphs, + 2 stage-matched booklets (current and next SoC).

Control: no intervention, assessment only

Outcomes 4-wk PPA and 7-day PPA (not even a puff ) at 6m, 24m.

Validation: None

Notes Type of intervention: Tailored S-H materials.

Funded by Swiss National Science Foundation, Swiss Cancer League, Swiss Federal

Office of Public Health, Geneva Health Authority

Risk of bias


Adequate sequence generation? Yes “randomly assigned ... using a list of ran-

dom numbers”


Blinding?

All outcomes

Unclear Unclear; “...members of the control group

received a letter indicating that they had

been attributed to that group...”


All outcomes

Yes Higher drop-out rates among intervention

group (24%) than controls (8%); feedback

suggested that Int members became “tired

of successive mailings”.

All pts included in analyses

Free of other bias? No Not stated

Hannöver 2009

Methods Setting: Six hospitals in Mecklenberg-West Pomerania, Germany


Recruitment: Invited postpartum mothers, with raffle incentives

Study: part of the EARLINT programme

SoC Model: TTM

Participants 299 women (151 baseline smokers) treated in Int group, 345 (187 baseline smokers)

treated in controls; mean age 26, mean FTND 2.08, mean CPD 11



Hannöver 2009 (Continued)

Interventions Int: Home-based MI + RP counselling session, + 2 booster phone calls at 4 and 12wks.

Covered harms, ETS, decisional balance, self-efficacy, temptations to smoke, RP strate-

gies.

Control: Usual care, + 2 x S-H brochures, targeting women smokers and partners’ ETS

Outcomes 4-wk PPA, sustained abstinence at 6, 12, 18 and 24m.

Validation: None

Notes Type of intervention: MI, follow-up phone calls, S-H booklets.

Funded by German Federal Ministry of Education and Research, the Social Ministry

of the Federal State of Mecklenburg-West Pomerania, and the Krupp von Bohlen and

Halbach Foundation

Risk of bias


Adequate sequence generation? Unclear “allocating women... alternating in the or-

der on the screening forms. Whether the al-

location sequence would begin with treat-

ment or control condition was decided ad

hoc”


Blinding?

All outcomes

Yes “impossible”, but assessors “were blind to

the women’s group membership”


All outcomes

Yes 12% at 6m, 18% at 12m, 24% at 18m,

25% at 24m


Hennrikus 2005

Methods Setting: Four hospitals, MN, USA


Recruitment: Newly admitted eligible patients invited by research staff

Study: the TEAM [Teachable Moment] Project

SoC Model: TTM

Participants Inpatients, smoked 1+ cigs in wk before admission, assigned to Int 1: Advice (703), Int

2; Advice + Counselling (696) or Control: Usual care (696). 47% M, mean age 47, 78%

W, mean CPD not stated.


Interventions Control: Usual care: 2 x SC manuals + directory of local SC services

Int 1: A: As Control, + brief (60-sec) advice from nurse or physician, and post-discharge



Hennrikus 2005 (Continued)

letter + pamphlets confirming SC benefits.

Int 2: A+C: As 1, + longer bedside MI and RP counselling, post-discharge letter, + 3-6

post-discharge phone calls over 6m.

NRT/bupropion encouraged but not supplied.


Validation: saliva cotinine at 12m

Notes Type of intervention: MI counselling, brief advice, S-H materials.

We have compared Int 2 (stage-based counselling + phone calls) vs Control (UC SH

materials) + Int 1 (brief advice + UC) for our MAs in this review.

Funded by National Institutes of Health

Risk of bias


Adequate sequence generation? Yes “the next available group assignment on a

list on which the three conditions were ran-

domly ordered within blocks of 30 assign-

ments”

Allocation concealment? Yes As above

Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes Losses at 12m: UC 21%, A 23%, A+C

28%; losses not significantly related to

study condition


Hollis 2005

Methods Setting: Seven HMO medical centres in OR and WA, USA


Recruitment: Invited during routine visits

Study: the Teen Reach Study

SoC Model: Pathways to Change (included TTM)

Participants Teenagers (14-17), smokers and non-smokers, randomized to Int (1254) or Control

(1270). 41% M, 78% W, smoking prevalence 22.4% in both groups.

Baseline smokers or exsmokers: Int: 281, Control 284 (from SoC in Table 1)

Interventions Int: (i) Written prompt to clinician to give 30-60s message against smoking, and advice

to consult health counsellor (ii) 10-12 min computer session, to assess SoC and give

tailored feedback.

(iii) 3-5 min MI counselling. Also tailored S-H material + quit kits.



Hollis 2005 (Continued)

2 booster sessions over 11m, face-to-face or by phone.

Control: 3-5 mins dietary advice (5-a-day fruit and veg).

Outcomes 30-day no-smoking status at 1 and 2yr follow up.

Validation: None

Notes Type of intervention: Expert system, tailored S-H materials, MI counselling, brief advice,

quit kits.

Only baseline smokers and exsmokers (448) used for this review. Denominators taken

from Grimshaw 2006.

Funded by National Cancer Institute

Risk of bias


Adequate sequence generation? Yes “blocked over time and stratified accord-

ing to medical center and 30-day cigarette

smoking status”

Allocation concealment? Yes Assignment printed on index cards in

sealed envelopes

Blinding?

All outcomes

Yes Assessor blinded


All outcomes

Yes Six types of analyses to model missing data.


Lawrence 2005

Methods Setting: 100 general practices in W Midlands, UK

Study design: Cluster-randomized controlled trial

Recruitment: by midwives in routine antenatal appointments

SoC Model: TTM, Pro-Change system

Participants 918 pregnant smokers, allocated to Arm A (control: 289), Arm B (305) or Arm C (324)

. Mean age 26, 89% W, CPD 70% 5-20.


Interventions Control: Arm A: standard care, i.e. advice + leaflet Thinking about StoppingInt 1: Arm B: 6 x 30pp stage-based manuals (1 per stage + RP) Pro-Change programmefor a healthy pregnancy. Assessed and guided (15 mins) at <20wks, 23-25 wks, 28-30wks,

by midwife

Int 2: Arm C: As B, + computer session at each assessment, with audio and on-screen

feedback on SoC, progress, decisional balance, temptations, processes of change. Feed-



Lawrence 2005 (Continued)

back print-out supplied after each visit

Outcomes 24hr PPA and sustained abstinence (10 wks+) at 28-30 wks, 10 days post-natal and

18m.

Validation: Urinary cotinine≤1.5µg/l at 10-day post-natal only

Notes Type of interventions: S-H materials, nurse counselling, expert system.

We have compared (a) Int 1 (stage-based counselling) and (b) Int 2 (interactive computer)

vs Control (advice/SH Guide) for our MAs in this review.

Funded by the West Midlands Regional Levies Board

Risk of bias


Adequate sequence generation? Yes “computerised minimisation programme”

allocating practices, minimising by

Townsend score, urban/rural, birth rate

Allocation concealment? No 17 top-up practices added to Arm A af-

ter 9m slow recruitment, + 12 midwives to

Arm B

Blinding?

All outcomes

Unclear Midwives aware of allocation


All outcomes

Yes Higher losses to follow up in SArm A (36%)

than B (28%) or C (23%) at 10 days p/n.

At 18m, 41% lost from A, 43% from B and

47% from C


Lennox 1998

Methods Setting: 16 general practices in Aberdeen, UK


Recruitment: invited by post, with 2 reminders

SoC Model: TTM

Participants 2588 smokers, 1381 in 8 Int practices and 1207 in 8 control practices. ”No significant

difference ... in age, sex, addiction score,or readiness to change.


Interventions Int: All or most GPs and all practice nurses and health visitors workshop-trained to

deliver stage-based SC advice, MI-based techniques

Control: no special training



Lennox 1998 (Continued)

Outcomes 24hr PPA at 8 and 14m; CA from 8 to 14m

Validation: none used

Notes Type of intervention: Practitioner training in SC

Funded by Chief Scientist Office, Scottish Office Department of Health

Risk of bias


Adequate sequence generation? Yes “pair-matched by list size, staff numbers

and social deprivation and randomly and

blindly allocated”

+ computer-generated random sample of

1 in 6 patients using Community Health

Index number, done centrally by Grampian

Health Board


Blinding?

All outcomes

Unclear “blindly allocated to control or interven-

tion”


All outcomes

Yes Losses similar across groups: 8m: Int 32%,

Control 28%; 14m: Int 35%, Control

34%. Analyses per protocol


Lennox 2001

Methods Setting: 6 general practices in Aberdeen, UK


Recruitment: invited by post, with 2 reminders

SoC Model: modified TTM, with preconts subdivided into 3 groups, conts into 2 groups,

preps into 2 groups

Participants 2553 smokers, randomized to Int 1 (870), Int 2 (869) or control (871). No demographic

info reported, but % of heavy smokers significantly higher in Int 1 (tailored letter) group

than in Int 2 (standard letter) group.


Interventions Int 1: TL: computer-generated letter, tailored for SoC, age and sex.

Int 2: SL: computer-generated standard letter

Control: NL: letter of thanks and promise to send SC material at study end


Validation: salivary cotinine



Lennox 2001 (Continued)

Notes Type of intervention: tailored letter, S-H materials

Analysis did not control for general practice.

We have compared Int 1 (stage-based letter) vs Int 2 (standard letter) for our MAs in

this review.

Funded by Chief Scientist Office, Scottish Executive Health Department, and Engineer-

ing and Physical Sciences Research Council

Risk of bias


Adequate sequence generation? Yes “computer generated random numbers”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes Withdrawals at 6m were 13 (TL), 23 (SL)

, 21 (C), excluded from analyses; dropouts

included as continuing smokers (200; 213;

145)


Manfredi 2004

Methods Setting: 12 clinics, pre-natal, family planning and paediatric, Ill, USA


Recruitment: by invitation at clinic

Study: The ’IT’S TIME’ Programme

SoC Model: modified TTM, i.e. 6 ’stages of readiness’

Participants 1063 women smokers allocated to Int (516), Control (547); mean age 29, mean CPD

11; more Afro-Americans in Int than control (86% vs 70%).


Interventions Int: At clinic: video, posters, brief advice, S-H booklet, agreement form to set quit date.

After clinic: reminder letter from provider, 15min MI phone call if wished.

Control: Measurement only.

Outcomes PPA at 2, 6, 12 and 18m.

Validation: None

Notes Type of intervention: Videos, posters, MI, brief advice, S-H materials, NRT if wished

(<1%).

Denominators inconsistent between reports.

Funded by National Cancer Institute and Centers for Disease Control



Manfredi 2004 (Continued)

Risk of bias


Adequate sequence generation? Unclear clinics “randomly assigned within pairs

to intervention and control conditions”,

matched on clinic type, location, ethnic

mix


Blinding?

All outcomes

Yes assessed by non-clinic staff; interviews con-

ducted by market researchers


All outcomes

Yes Losses at 6m 24% (I), 14% (C); at 12m

43% (I), 34% (C); at 18m 56% (I), 48%

(C); Prenatal smokers under-represented,

and well-child smoking mothers over-rep-

resented


McBride 1999

Methods Setting: HMO in Puget Sound, WA, USA


Recruitment: 15% sample of all cervical screening clinic results; all class 3 & 4 + random

sample of normal and class 2 invited.

SoC Model: TTM

Participants 580 women smokers, allocated to Int (288) or Control (292). Mean age 36, 84% W,

mean CPD 13.


Interventions Int: SC kit, i.e. personalised computer-generated cover letter, S-H guide Clearing the

Air, cervical cancer info card, tea bags, bath salts. MI counselling phone calls at 2wks,

6wks, 10wks.

Control: Usual care

Outcomes PPA at 6 and 15m

Validation: saliva cotinine at 15m

Notes Type of intervention: S-H, telephone counselling

Funded by National Cancer Insititute, and National Heart, Lung and Blood Institute

Risk of bias




McBride 1999 (Continued)

Adequate sequence generation? Unclear “stratified on Pap test ... and randomized

to one of two groups”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Unclear 12% lost at 6m, 19% at 15m.


Mermelstein 2003

Methods Setting: USA


Recruitment: paid ads, media coverage, fliers, referrals

SoC Model: TTM

Participants 771 smokers completing group SC programme, allocated to Int (381) or control (375).

34% M, mean age 43, 63% W, mean CPD 22.


Interventions All pts completed 7wk group SC programme. Then 6 x 15-min counsellor calls over

10wks.

Int: Enhanced: If still smoking at end of group programme, given a video, Yes you can.If relapsed, given a video, It’s Time. Calls tailored to pt’s smoking status, following MI

principles. Mood management skills,self-efficacy, S-H manual.

Control: Basic: 5-20 mins per call. Generic encouragement, no specific guidance, “sup-

portive but nonspecific”

Outcomes 7-day PPA at 3, 6, 9, 12 and 15m

Validation: CO≤8ppm or cotinine <10ng/ml

Notes Type of intervention: telephone counselling, S-H manuals, videos.

Funded by National Cancer Institute, and National Heart, Lung and Blood Institute

Risk of bias


Adequate sequence generation? Unclear “Groups were randomly assigned to condi-

tion”




Mermelstein 2003 (Continued)

Blinding?

All outcomes

Yes “Counselors were kept blind to condition

until the last group meeting”


All outcomes

Yes 4% lost to follow up; “Attrition was min-

imal during the follow-up, and there were

no

differences in attrition by condition.”


Meyer 2008

Methods Setting: 34 family practices in Vorpommern, Germany


Recruitment: all smokers invited by practice during routine visits

Study: part of the Pro GP project

SoC Model: modified TTM

Participants 1499 pts, randomized by week of attendance to Control (609), Int 1(488) or Int 2 (402)

; 52% M, mean age 34, mean CPD 16.


Interventions Int 1: Letters: 3 computer-generated letters, tailored to SoC, scores on decisional balance,

self-efficacy, processes of change. Letters went at 1 wk, 3m and 6m from baseline visit.

Pts also given relevant S-H manuals

Int 2: Brief advice (10 mins), tailored to SoC, plus same manuals as Int 1.

Control: Assessment only, no intervention

Outcomes 24hr and 7-day PPA at 6, 12, 18 and 24 m.

6m PA at 6, 12, 18 and 24m.

18m PA at 24m.

Validation: None

Notes Type of intervention: Expert system, brief advice, S-H manuals.

We have compared (a) Int 1 (ES) and (b) Int 2 (brief counselling) vs Control in our MAs

for this review.

Funded by German Ministry of Research and Education, the Social Ministry of Meck-

lenburg-Vorpommern, and the German Research Foundation

Risk of bias


Adequate sequence generation? No (i) “44 of 149 practices were selected ran-

domly”

(ii) All pts in 1st week allocated to assess-

ment only, 2nd week letters, 3rd week brief

advice



Meyer 2008 (Continued)


Blinding?

All outcomes

Yes Practice team, practitioner and follow-up

interviewers all blinded


All outcomes

Yes 8.8% lost at 6m, 3.7% at 24m.

Free of other bias? No “patients attending the practice frequently

... had a lower probability of inclusion in

the later study groups”

Meysman 2010

Methods Setting: Surgical wards in 4 Flemish hospitals


Recruitment: inpatient smokers


Participants 358 adult smokers admitted for surgery; randomized to experimental (178) or control

(180) groups. 63% M, mean age 43.2, 39% smoked >20 CPD, 61% 10-20 CPD.


Interventions Int: Brief nurse-led counselling session; SoC assessed, and appropriate advice given, i.e.

precontemplators got risks of smoking and health gains after cessation, contemplators got

barriers and pitfalls to quitting, + raising self-efficacy, and preparers were either referred

to a SC counsellor of agreed a SC plan with the nurse.

Control: a standard booklet on smoking cessation.

Outcomes Self-reported continuous abstinence on discharge and at 6m post-discharge.

Validation: None

Notes Type of intervention: Brief counselling from a nurse.

Funded by a grant from Pfizer.

Risk of bias


Adequate sequence generation? Yes “a web-base stage of change calculation was

done and patients were randomised to two

treatment groups”


Blinding?

All outcomes

Unclear Not stated



Meysman 2010 (Continued)


All outcomes

Unclear Losses at 6m not reported

Nakamura 2004

Methods Setting: 72 sites (26 communities and 46 worksites), Osaka, Japan

Study design: Multisite randomized controlled trial

Recruitment: 20 subjects with two risk factors from each site by health care providers,

Study: HISLIM Study

SoC Model: modified TTM: includes immotives

Participants 977 smokers (from 1386 pts); 332 in smoking/hypertension (SHT) group, 645 in smok-

ing/hypercholesterolaemia (SHC) group. SHT group allocated Int: 173, Control 159;

SHC allocated to Int 327, Control 318. 98% M, mean age 44, mean CPD 25.


Interventions Int: 1 x 40-min individual counselling session + 4 x 20-30 min follow-up sessions at 1,

2, 4 and 6m. If quit date set, 1 extra phone session or letter. S-H guide. Counsellors were

nurses, physicians, nutritionists, medical technologists.

Control: Interventions for hypertension or hypercholesterolaemia

Outcomes PPA at 6m, CA at 2 and 6m, and at 1, 2, 4 and 6m.

Validation: CO≤8ppm

Notes Type of intervention: Physician advice, S-H materials.

Funded by Japanese Ministry of Health and Welfare

Risk of bias


Adequate sequence generation? Unclear “stratified by study site and randomly as-

signed”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes Losses at 6m 4.8% (I) and 6.3% (C).




O’Neill 2000

Methods Setting: North Dakota State University, ND, USA


Recruitment: invitation to all lower-level psychology undergraduates

SoC Model: TTM

Participants 65 undergraduate daily smokers, allocated to int (31), Control (34). 37% M, mean age

19, 48% smoked 10-20 CPD.


Interventions Int: 4 x computer sessions over 6wks, adapted from Smoke Mall programme. 6 x modules

tailored to SoC.

Control: 3 x computer modules related to other health behaviours, i.e. diet, hypertension,

stress management

Outcomes Primary outcome was movement through SoC, not cessation.

PPA and CA at 7m

Validation: None

Notes Type of intervention: computerized experts system.

Funding not reported.

Possible conflict of interest: the intervention being tested was developed by one of the

authors

Risk of bias


Adequate sequence generation? Unclear “randomly assigned to a condition”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes 6% lost at 3m, 14% at 7m


Pallonen 1994

Methods Setting: Eastern Finland

Study design: Randomized controlled trial within longitudinal CV risk factor study

Recruitment: Invited as part of ongoing surveillance study

SoC Model: TTM

Participants 482 male moderate smokers (10+ CPD) assigned 2:1 to intervention or control. Prepar-

ers in intervention group were offered SC course (62 accepted). Precontemplators, con-

templators and preparers refusing SC (N=263) received stage-matched manual. Control



Pallonen 1994 (Continued)

group (N=157) received ’usual care’. Mean age 52, mean CPD 19

Interventions Only Manuals intervention group and controls used in this review: Baseline info for 233

Int, 142 controls.

Int: Appropriate 10-20pp manual for SoC sent every 6m. If no SoC movement between

assessments, no new manual sent. Pts could contact or visit research staff if wished (“very

few” did so).

Control: usual care, measurement only.

Outcomes PPA at 6, 12, 18, 24m for Int group, 12 and 24m for controls.

Validation: None

Notes Type of intervention: S-H stage-matched manuals

This study only compared (2) S-H manuals with (3) usual care, and used only those

assessed at baseline, 1yr and 2yrs. We have used baseline measures as our denominators.

Funded by Academy of Finland, the Finnish National Board of Health and the national

Cancer Institute

Risk of bias


Adequate sequence generation? Unclear Classified by stage, then “two-thirds were

randomly allocated to a treatment condi-

tion and one-third to a usual care condi-

tion”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Unclear 30 in Int and 15 in controls gave no or in-

sufficient data at baseline, reducing groups

to 233 and 142. 29% of these lost at yr

2; usable cohort, present at all three time-

points, was 149 for Int 2 and 116 for con-

trols


Patten 2004

Methods Setting: Mayo Clinic and community, MN, USA


Recruitment: Support volunteers, by TV ad, + fliers in clinic and community




Patten 2004 (Continued)

Participants 60 volunteers willing to help a smoker to quit. Mean age 47, 100% W, 50% married/

living with smoking spouse/partner

Interventions Int: (i) S-H manual Because you care: information for those wanting to help someone stopsmoking. Stressed MI techniques, tailoring to SoC; (ii) 5 x weekly 90 min group sessions,

average 4 people, to support volunteers.

Control: One-page leaflet of generic support strategies


Validation: None

Notes Type of intervention: S-H materials + group support sessions (training supporters, not

smokers).

Funded by Mayo Clinic Cancer Center and National Cancer Institute

Risk of bias


Adequate sequence generation? Unclear “people were randomized”


Blinding?

All outcomes

Yes “Study assistants who were not involved in

the intervention conducted all follow-up

assessments”


All outcomes

Yes 10% lost in each group at 6m


Pieterse 2001

Methods Setting: 18 general practices, Netherlands


Recruitment: poster in waiting room, proactive invitations by practice assistants

SoC Model: modified TTM, i.e. low, moderate or high motivation to quit

Participants 530 smokers, allocated to Int (269) and Control (261). 40% M, mean age 35, 70% (Int) and 68%

(Control) smoked 11-24 CPD.

Motivation to quit not required, but some GPs felt it a waste of time to counsel unmotivated

smokers

Interventions Int: Brief physician advice, mean 10 mins, tailored to SoC, S-H manual, NRT gum recommended

if appropriate.

Control: usual care (smoking discussed only if raised by patient).



Pieterse 2001 (Continued)

Outcomes PPA and CA at 6 and 12m

Validation: None; ’bogus pipeline’ at 1m

Notes Type of intervention: Brief physician advice, S-H materials

Funded by Dutch Cancer Society

Risk of bias


Adequate sequence generation? No “subjects were assigned ... by the office assistant”,

but GPs were allowed to give the intervention to

some control patients, who were later excluded

from analyses

Allocation concealment? Yes Prestructured allocation lists.

Blinding?

All outcomes

Unclear Not stated

Free of other bias? No Disparities in baseline characteristics in CPD

and motivation to quit suggest selection bias.

Follow up period ’contaminated’ by intensive

mass media anti-smoking campaign

Prochaska 1993

Methods Setting: Houston, TX, and Rhode Island, USA


Recruitment: Mass media ads + incentives

SoC Model: TTM

Participants 1466 smokers randomized by SoC: Preconts: 166 [93 in RI] (not seriously considering

quitting within next 6m); Conts 794 [435 in RI] (seriously considering quitting in next

6m, but not in next 30 days and/or had not made a 24-hr quit attempt in previous yr)

; Preps 506 [228 in RI] (planning to quit in next 30 days and had made previous 24-hr

quit attempt).

37% M, mean age 42, 86% W (TX), 98% W (RI), mean CPD 27.


Interventions Int 1: TTT manuals, matched to current SoC + all subsequent manuals.

Int 2: As 1, + computerised feedback tailored to baseline, post-test and 6m Qs.

Int 3: As 2, + 4 personalised stage-matched counsellor phone calls (≃ 15 mins) at pretest,

1, 3 and 6m.

Control: 3 standardized ALA manuals + cover letter advising on best fit for each stage.

Reactive hot line available to all pts, but hardly used.



Prochaska 1993 (Continued)

Outcomes Pts from both sites assessed at baseline, 1m, 6m, but only RI pts at 12 and 18m

24-hr PPA and PA (abstinent at 2 points).

Validation: None, but ’bogus pipeline’ of confirmation by ’significant other’

Notes Type of intervention: S-H, expert system, phone counselling.

We have compared Int 1 (stage-based manuals) with Controls (standard S-H manuals)

for our MAs.

RI cohort used for our analyses; denominators by treatment groups not reported.


Risk of bias


Adequate sequence generation? Unclear “randomly assigned, stratified by stage”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Unclear Not stated

Free of other bias? No Pts received stage-matched manual + all

subsequent manuals in one delivery

Prochaska 2001a

Methods Setting: Houston, Rhode Island, USA


Recruitment: Random digit dialling

SoC Model: TTM

Participants 4144 smokers assigned to Int (1358) or control (2786). 44% M, mean age 41, ethnicity

96% W, mean CPD 20.


Interventions Int: Expert System (ES): Baseline feedback report + stage-matched S-H manuals; Qs at

3 and 6m, with computerised tailored feedback.

Control: Assessment Only (AS): proactively assessed at 6m intervals

Outcomes 24-hr PPA and 30 day and 6m PA at 6, 12, 18 and 24m.

Validation: None

Notes Type of intervention: S-H manuals, expert system.




Prochaska 2001a (Continued)

Risk of bias


Adequate sequence generation? Unclear “Subjects were randomly assigned”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes By 24m 39.8% Int group and 35.6% Cont

group lost or refused.



Prochaska 2001b

Methods Setting: SE Massachusetts and Rhode Island, USA


Recruitment: Smokers identified and invited from managed care system

SoC Model: TTM

Participants 1452 smokers randomized to ES (368), ES+CO (359), ES+SC (366) and AS (359).

Shares the ES group with Velicer 1999, but denominator discrepant by 6.

44% M, mean age 38, mean CPD 20.


Interventions Int 1: Expert System (ES): S-H manual, matched to SoC + all subsequent manuals +

computerised tailored feedback reports.

Int 2: ES + Counselling (ES+CO): As 1, + 3 proactive tailored counselling calls at baseline,

3 and 6m.

Int 3: ES+Stimulus Control (ES+SC): As 1, + Conts and preps were sent Lifesign hand-

held computer (nicotine fading) + materials. Preconts who moved to Cont within dura-

tion of trial were sent the computer.

Control: Assessment only (AS):

Outcomes 24-hr, 7-day PPA and 30-day and 6m PA at 6, 12 and 18m

Validation: None

Notes Type of intervention: S-H materials, expert system, nicotine fading.

Study reports 1447 randomized, but group totals come to 1452.

We have compared Int 1 (ES letters + manuals) vs Control (Assessment) for our MAs in

this review.


Risk of bias



Prochaska 2001b (Continued)


Adequate sequence generation? Unclear “random assignment was employed”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes Five models of “missingness” tested



Prochaska 2004

Methods Setting: Rhode Island schools, USA


Recruitment: Parents of 9th grade teenagers

SoC Model: TTM

Participants 711 smokers, from 2460 parents with at least 1 risk factor (sun, smoking, high fat).

Randomized to Int (349) or Control (362). Across whole cohort, 25% M, mean age 42,

mean CPD 18.


Interventions Int: Expert System (ES): S-H materials, + 3 computer-generated tailored reports at

baseline, 6 and 12m, based on phone follow up.

Control: Assessment only at 6 and 12m

Outcomes 24-hr and 7-day PPA, + 6m PA at 12 and 24m.

Notes Type of intervention: S-H manuals, expert system

4 died before assessment, but distribution NK.


Risk of bias


Adequate sequence generation? Unclear “subjects were randomly assigned”


Blinding?

All outcomes

Unclear Not stated



Prochaska 2004 (Continued)


All outcomes

Yes At 12m 36% and at 24m 42% of smokers

were lost or refused.


Prochaska 2005

Methods Setting: 79 primary care practices within an HMO, USA


Recruitment: by phone, for pts registered with the practices

SoC Model: TTM

Participants 1211 smokers, from 5407 pts with at least 1 cancer risk factor (smoking, diet, sun

exposure, mammography). Smoker allocation to int and control not reported. 30% M,

mean age 45, mean CPD 17

Interventions Int: Home-based ES: 3 x computer reports at baseline, 6 and 12m.

Control: assessment only at 12 and 24m.

Outcomes 24-hr and 7-day PPA at 6m (int only), 12 and 24m, + 6m PA at 12 and 24m

Validation: None

Notes Type of intervention: expert system

ITT denominators not known.


Risk of bias


Adequate sequence generation? Unclear “patients were randomly assigned”


Blinding?

All outcomes

Yes “Telephone surveyors were blind to assign-

ment”


All outcomes

Unclear By 24m, 35% of smokers were lost to follow

up or refused (distribution not stated)




Prochaska 2008

Methods Setting: Medical University, OR, USA


Recruitment: Randomized to mail/email only, mail/email + incentive, or mail + incentive + phone

prompt.

SoC Model: TTM

Participants 1400 employees, randomized to health risk assessment intervention (HRI: 464; 48 smokers), HRI +

MI counselling (433; 40 smokers) or HRI + interactive TTM programme (TTM: 503; 48 smokers)

. Study targeted 4 risk-reduction programmes: stress, exercise, weight control and smoking. 11%

M, mean age 41, mean CPD N/S

Interventions Control: Health risk assessment (HRA) only. SoC assessed for each risk, and identified single best

step to remedy.

Int 1: MI: HRA + 3 x phone or face-to-face MI sessions, to move along SoC and reduce risky

behaviour.

Int 2: TTM: HRA + online TTM programme (Pro-Change Lifestyle Management Program); 4

programmes over 6m; recommended 3 sessions of each course

Outcomes ’Reaching criterion’ at 6m, i.e. PPA (no longer at risk) for smokers.

We have compared Int 2 (TTM computer programme) vs Control (HRA) for our MAs in this

review.

Validation: None

Notes Denominators by group not reported for 6m follow up, but 35/136 did not supply 6m follow-up

data. We have applied 6m % quit rates to baseline denominators for our MAs in this review.

Funded by US Centers for Disease Control and Prevention

Risk of bias


Adequate sequence generation? Unclear “randomly assigned”


Blinding?

All outcomes

Unclear Not stated


Prokhorov 2008

Methods Setting: 15 Community colleges, Houston, TX, USA


Recruitment: by instructors, newspapers, newsletters, fliers, sign-up booths, promo items

Study: “Look At Your Health”

SoC Model: TTM + Health Belief Model



Prokhorov 2008 (Continued)

Participants 426 students, assigned by college to Int (219) or control (207). 46% M (SC), 27% M

(LAYH); mean age 23; mean CPD 13.


Interventions Int: Look At Your Health: MI counselling + lung function and CO test feedback; Coun-

selling modified by expert system software, tailoring for nicotine dependence, decisional

balance, temptations to smoke, SoC. Each pt given a brief individualised newsletter of

their data.

Control: Standard Care: brief MI counselling + S-H manual Clearing the Air.Follow ups at 2, 4 and 10m, to support, answer questions, assess

Outcomes 7-day PPA at 10m.

Validation: salivary cotinine ≤5 g/mL at baseline and 10m.

Notes Type of intervention: expert system, biofeedback, S-H manuals.

“phenomenal” discrepancies between self-reported and validated quit rates: LAYH: 28.

5 vs 16.6; SC 24.4 vs 10.1.


Risk of bias


Adequate sequence generation? Unclear “campuses were pair-matched by size and

then randomly assigned”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Unclear By 10m, SC had lost 19%, LAYH 28%

Free of other bias? Unclear 1 campus dropped out and was replaced

Schumann 2006

Methods Setting: 3 cities in W Pomerania, Germany


Recruitment: Identified smokers invited to take part.

Study: SHIP study

SoC Model: TTM

Participants 485 daily smokers, assigned to Int (240) or control (245). 52% M, mean age 44, mean

CPD 15.




Schumann 2006 (Continued)

Interventions Int: 3 x computer-generated expert system letters + tailored S-H materials.

Control: Assessment only

Outcomes PPA at 3m (int only), 6, 12, 18 and 24m

Validation: None

Notes Type of intervention: expert system, S-H material

2008 data includes ex-smokers in denominator, but our comparison uses baseline smok-

ers only.

Funded by German Federal Ministry of Education and Research, and Social Ministry of

mecklenburg-West Pomerania

Risk of bias


Adequate sequence generation? Yes “Each subject was assigned a unique com-

puter-generated random number”

Allocation concealment? Yes “subject data file was sorted by ascending

random numbers, and then subjects were

consecutively assigned to the three study

conditions”

Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes At 12m 27.4% and at 24m 30.5% lost or

refused


Stotts 2002

Methods Setting: 21 satellite locations of 3 large clinics in Houston and Dallas, TX, USA

Study design: Pilot randomized controlled trial

Recruitment: phone invitation at 28 wks

Study: One-to-One Study


Participants 269 late-pregnancy smokers (28 wks+) who had already tried and failed to quit, allocated

to Int (134) or control (135). Mean age 28, 79% W, mean CPD not stated

Interventions Int: 1 x 20-30 min tailored counselling call, SoC-based personalised letter + follow-up

phone call, + postpartum newsletters and video

Control: Usual care, i.e. brief counselling and S-H booklets, received by all participants



Stotts 2002 (Continued)

Outcomes PPA or ’not smoking most of the time’ at 6m postpartum

Validation: 175 anonymized cotinine samples at 34 wks (41% of Int, 39% of control)

Notes Type of intervention: Tailored expert system letter, phone-based MI counselling, video.


Risk of bias


Adequate sequence generation? Yes “computer-generated random number list”


Blinding?

All outcomes

Yes Pts blinded to purpose of follow-up survey


All outcomes

Yes 45% of Int group did not receive full inter-

vention

Free of other bias? No Only 55% of Int group received full inter-

vention

Thompson 1993

Methods Setting: Free Cancer Information Service hotline throughout USA


Recruitment: Invitation to callers, + ads, posters, fliers


Participants 4 worksites + “other sources”, i.e. callers to a free SC hotline. 382 callers allocated to Int

(197) or control (185). Int 43% M, Control 35% M, mean age 40, mean CPD 22

Interventions Callers to ’hotline’ did not include any in precontemplation.

Int: Tailored responses, to move caller along cessation continuum; Mean duration of call

34 mins

Control: Reactive ’general information’ + standard S-H materials. Mean duration of call

20 mins

Outcomes PPA at 6 and 12m (subset)

Validation: mailed saliva samples as ’bogus pipeline’; surrogates contacted

Notes Study targeted blue-collar workers, but recruited only 24% in cohort.

Type of intervention: telephone counselling.


Risk of bias



Thompson 1993 (Continued)


Adequate sequence generation? Unclear “randomly assigned”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Unclear 17% lost at 6m, 24.2% at 12m

Free of other bias? Unclear 41 Pts were non-smokers at baseline, but

included in the analyses; slow recruitment

meant that only 207/382 were in the study

for 12m

Velicer 1999

Methods Setting: SE Massachusetts and Rhode Island, USA


Recruitment: Smokers identified and invited from managed care system

SoC Model: TTM

Participants 2882 smokers randomized to ES (1429) or Manuals (1453).

Shares the ESX3 group with Prochaska 2001b, but denominator discrepant by 6.

44% M, mean age 38, mean CPD 20.


Interventions 1. Non-interactive SH manuals: Pts received the manual matched to their current SoC

+ all subsequent manuals.

2. Interactive tailored feedback reports, + manuals as (1).

No non-staged control group.

Both groups’ interventions were delivered in one of four doses, i.e. 1, 2, 3 or 6 mailings,

to test dose-response effects. In multiple contact subgroups, a different manual was sent

on each occasion. Participants in the ESx2 and ESx3 contact groups received a phone

contact at 3m; those in ESx6 contact group received phone contacts at 3, 9 and 15m

Outcomes 24-hr and 7-day PPA and PA at 6, 12 and 18m.

Validation: None

Notes Type of intervention: Stage-based SH manuals, expert system, phone contacts

Not included in MAs, as no non-staged control group, and overlap with Prochaska

2001b.


Risk of bias



Velicer 1999 (Continued)


Adequate sequence generation? Unclear “2882 were randomly assigned”


Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes Full details of attrition and refusals

Free of other bias? Unclear Pts received relevant + all subsequent stage

manuals.

Wang 1994

Methods Setting: Outpatient clinics in Taiwanese Hospital


Recruitment: Physicians within Dept Family Medicine


Participants 93 smoker patients of physicians allocated to SoC training (39 pts), to reminder (26 pts)

or to usual care (28 pts). 95% M

Interventions Int 1: 2 x lessons on SoC model and counselling for SC

Int 2: Reminder poster placed in clinic room to encourage standard SC advice.

Control: Usual care (may or may not include reference to SC)

Outcomes PPA at 6m

Validation: None

Notes Type of intervention: training physicians in SoC SC techniques.

We have compared Int 1 (stage-based physician advice) vs Int 2+Control (minimal or

usual care) for our MAs in this review.

Supported by Taiwanese Department of Health

Risk of bias


Adequate sequence generation? Unclear “All physicians were numbered and ran-

domly assigned to one of three groups by

number of years in practice”




Wang 1994 (Continued)

Blinding?

All outcomes

Unclear Not stated


All outcomes

Yes 12% at 6m


Young 2008

Methods Setting: 30 general practices, Sydney, Australia


Recruitment: All patients assessed over 3wk period, and smokers invited

SoC Model: TTM

Participants 318 smokers, randomized to Int (169) or control (149); 46% M, mean age 38; 73%

smoked ≥20 CPD

Interventions Int: 4 x counselling phone calls, delivered by trained nurse, based on 5As, MI, 5Rs.

Those not ready to make a quit attempt received a motivational intervention to move

them through the stages. Quit-attempters were sent quit pack, encouraged to use NRT;

Calls made on TQD, +1wk and +3wks.

Control: Usual care, including free quit kits

Outcomes PPA at 6, 12m

Validation: None

Notes Type of intervention: telephone counselling.

Only 76 of 169 intervention smokers agreed to participate in the counselling phase.

Funded by National Heart Foundation of Australia

Risk of bias


Adequate sequence generation? Yes “prerandomized questionnaires”

Allocation concealment? Yes Before consultation

Blinding?

All outcomes

Unclear phone follow-up “blind to ... group alloca-

tion”


All outcomes

Yes 21% (I) and 26% (C) lost at 6m; 31% (I)

and 41% (C) at 12m

Free of other bias? Unclear 5 control pts received intervention in error;

analysed as controls (ITT).

Only 55 smokers completed all 4 calls.



4As: Ask-Advise-Assist-Arrange follow up

a/v: audio-visual

AHCP: Agency for Health Care Policy

APA: American Psychiatric Association

CA: continuous abstinence

CO: carbon monoxide

Cont: contemplator

CPD: cigarettes per day

FTND: Fagerström Test for Nicotine Dependence

M: male

m: month(s)

MA: meta-analysis

MI: motivational interviewing

PA: prolonged abstinence

PPA: point prevalence abstinence

Precont: precontemplators

Prep: in preparation

Pt: participant

Q: questionnaire

SC: smoking cessation

SES: socio-economic status

SoC: stage of change

TTM: Transtheoretical Model

W: white

Characteristics of excluded studies [ordered by study ID]

Study Reason for exclusion

Abdullah 2005 Both groups received staged materials; tested intervention was additional telephone counselling

Ahluwalia 2007 Main outcome was fruit and vegetable consumption among smokers; smoking behaviour was not a reported

outcome

Andersen 2006 Outcomes were effect of support on smoking and movement through stages; Only 5 weeks follow up

Armitage 2008 Only 2 months follow up.

Baker 2006 Intervention was mainly MI and CBT; Stage of change was measured but not used in intervention

Becona 2001 Participants were classified by stage of change, but it did not modify the intervention

Berman 1995 Stage of change was measured but not integrated into the intervention

Borrelli 2002 PAQS Study: Insufficient information to treat as an included study (results not reported)

Campbell 2004 Report of recruitment; participants were marijuana users.



(Continued)

Carlson 2003 Uncontrolled cohort study, follow up only to 3 months.

Chan 2005 Insufficient information to treat as an included study (details of intervention not available)

Cornuz 2002 Prescribed NRT as part of the intervention where appropriate

Dijkstra 1998b Outcomes were attitudes and movement through stages, not smoking behaviour change

Dijkstra 1998c Only 4 months follow up.

Dijkstra 2006 Outcome was movement through the stages of change, not smoking cessation

Drevenhorn 2007 Outcome was consultation skills, not smoking behaviour change

Erol 2008 Main outcome was movement through stages of change, and main intervention was MI. Smoking rates were

reported as an incidental outcome

Ershoff 1999 All pts received SoC-based interventions. Study tested addition of phone counselling and MI

Etter 2005 Only 10 weeks follow up.

Etter 2009 Short-term (48-hour) effects of tailored vs generic advice to quit

Fang 2006 Only 3 months follow up.

Fritz 2008 Only 1 month follow up.

Gritz 1993 Stage of change was recorded, but not used in tailoring the intervention

Hall 2006 Supplied NRT or bupropion as appropriate as part of the intervention

Haug 2009 Three group trial of text messaging support. Final assessment was at 3m

Hoving 2007 Stage of change was measured to determine eligibility, but did not significantly modify the intervention

Huang 2005 Outcome was prevention rather than cessation.

Hughes 2000 Insufficient information to treat as an included study (quit rates for intervention and control groups not reported

separately)

Hughes 2005 Outcome was intention to quit over 30 days, not cessation.

Hyman 2007 Stage of change was reported, but intervention was timing.

Jennings 2007 Stage of change was measured but not integrated with intervention



(Continued)

Johs 2003 Only 3 months follow up.

Jones 2003 Insufficient information to treat as an included study (disparities in denominators for intervention and control

groups)

Keller 2000 Movement through stages of change was main outcome, not cessation

Kim 2004 Intervention was not tailored to stage of change.

Kim 2009 Non-randomized study. Outcomes included movement through stages and scores on processes of change, but

not abstinence achieved

Kohler 2008 Motivation and movement through stages were main outcomes; only 10 weeks follow up

Lipkus 1999 All participants received stage-based support, and heavier smokers were given a coupon for free NRT, which

could have confounded the results

Ma 2005 Follow up was to 3m.

McDonald 2003 Insufficient information to treat as an included study (results and denominators not available)

Morgan 1996 Provided NRT gum where appropriate as part of the intervention

Osinubi 2003 Stage of change was measured but did not modify intervention

Pallonen 1998 Quit rates for each group not reported separately.

Pisinger 2005 Both intervention arms were given free samples of NRT if wished

Pletsch 2002 Outcome was movement through stages of change, not cessation

Quinlan 2000 Only 1 month follow up.

Reeve 2000 Only 3 months follow up.

Reid 2003 Stage of change was measured, but not integrated into intervention

Resnicow 1997 Stage of change advice not separable from other components.

Rissel 2000 Only 3 months follow up.

Schneider 1990 Tailored intervention not modified by stage of change.

Simon 2003 Impact of stage of change could not be isolated from other components

Sinclair 1998 Tailoring was not modified by stage of change.



(Continued)

Skewes 2007 Insufficient information to treat as an included study

Swanson 2003 Main outcome was comparison of NRT and/or bupropion versus counselling. Stage of change was measured

but did not modify the intervention

Tanaka 2006 Intervention was not modified by stage of change.

Tappin 2000 Quit rates were assessed at 14 weeks and in late pregnancy; intervention was more MI than stage of change

Tsoh 2005 Insufficient information to treat as an included study (18m results not yet available)

Valanis 2001 Quasi-experimental prospective cohort study, not randomized, with historical and interim controls

Webb 2005 Changes in smoking behaviour were not an outcome of interest

Wiggers 2005 Only 8 weeks follow up.

Williams 2006 Main theoretical model was self-determination theory, not stages of change

Wilson 2008 Both intervention groups were given free NRT if wished.

Wu 2009 Stage of change measured, but primarily a trial of MI techniques + NRT

Young 2002 Outcome was changes in competencies among family doctors using distance learning, not smoking cessation

CBT: cognitive behavioural therapy

MI: motivational interviewing

Characteristics of ongoing studies [ordered by study ID]

Cabezas 2009

Trial name or title ISTAPS Study

Methods Cluster-randomized trial, in 82 primary care centres (PCCs) in Spain

Participants 3024 teenage and adult smokers attending PCC

Interventions MI counselling, brief advice, NRT, vs usual care

Outcomes PPA at 6m, 1 yr,2 yrs, CO-validated.

Starting date 2003



Cabezas 2009 (Continued)

Contact information [email protected]

Notes Supported by grants from Carlos III Health Institute

Prokhorov 2010

Trial name or title Project ASPIRE

Methods Nested-cohort group-randomized trial of students from 16 schools in Houston, Texas

Participants school students, smoking and non-smoking

Interventions CD-ROM-based interactive programme of five sessions + 2 booster sessions

Outcomes Rates of uptake among baseline non-smokers, and cessation among baseline smokers

Starting date

Contact information [email protected]

Notes Supported by a grant from National Cancer institute



D A T A A N D A N A L Y S E S

Comparison 1. Optimal trial comparisons

Outcome or subgroup titleNo. of

studies

No. of

participants Statistical method Effect size

1 Stage-based vs standard SH

materials

2 2117 Risk Ratio (M-H, Fixed, 95% CI) 0.93 [0.62, 1.39]

2 Stage-based counselling vs

standard advice


Comparison 2. Abstinence by intervention and comparison


studies

No. of


1 Expert systems 18 Risk Ratio (M-H, Fixed, 95% CI) Subtotals only

1.1 Standard self help 6 5947 Risk Ratio (M-H, Fixed, 95% CI) 1.27 [1.01, 1.59]

1.2 Usual care 2 849 Risk Ratio (M-H, Fixed, 95% CI) 0.94 [0.56, 1.57]

1.3 Assessment only 10 13597 Risk Ratio (M-H, Fixed, 95% CI) 1.35 [1.19, 1.52]

2 Individual counselling 13 Risk Ratio (M-H, Fixed, 95% CI) Subtotals only




3 Interactive computer programme 5 Risk Ratio (M-H, Fixed, 95% CI) Subtotals only



4 Phone quit lines 2 Risk Ratio (M-H, Fixed, 95% CI) Subtotals only



5 Training doctors 2 Risk Ratio (M-H, Fixed, 95% CI) Subtotals only


6 Training lay supporters 1 Risk Ratio (M-H, Fixed, 95% CI) Subtotals only


7 Staged SH materials 1 Risk Ratio (M-H, Fixed, 95% CI) Subtotals only




Comparison 3. Validated abstinence


studies

No. of


1 Biochemically validated

abstinence


2 Self-reported abstinence 28 23334 Risk Ratio (M-H, Fixed, 95% CI) 1.25 [1.14, 1.37]

3 ’Bogus pipeline’ 4 3033 Risk Ratio (M-H, Fixed, 95% CI) 1.72 [1.20, 2.46]

Comparison 4. Missing data testing


studies

No. of


1 Intervention ITT versus control

per protocol


2 Intervention ITT versus control

ITT


Comparison 5. Any stage-based intervention vs control


studies

No. of


1 Abstinence at longest follow up 40 33446 Risk Ratio (M-H, Fixed, 95% CI) 1.25 [1.16, 1.35]

2 Abstinence by comparison

condition

40 Risk Ratio (M-H, Fixed, 95% CI) Subtotals only

2.1 Standard self-help

materials




Comparison 6. PPA at 6 or 12 m by intervention and comparison


studies

No. of


1 Expert systems 18 20472 Risk Ratio (M-H, Fixed, 95% CI) 1.14 [1.05, 1.24]




2 Individual counselling 12 8026 Risk Ratio (M-H, Fixed, 95% CI) 1.33 [1.18, 1.51]






3 Interactive computer programme 5 1933 Risk Ratio (M-H, Fixed, 95% CI) 1.24 [0.96, 1.59]



4 Phone quit lines 2 525 Risk Ratio (M-H, Fixed, 95% CI) 1.12 [0.70, 1.78]



5 Training doctors 2 2681 Risk Ratio (M-H, Fixed, 95% CI) 1.03 [0.79, 1.34]


6 Training lay supporters 1 60 Risk Ratio (M-H, Fixed, 95% CI) 1.5 [0.27, 8.34]


7 Staged SH materials 1 375 Risk Ratio (M-H, Fixed, 95% CI) 1.45 [0.65, 3.22]


Comparison 7. Per protocol analyses


studies

No. of


1 Expert systems 18 15504 Risk Ratio (M-H, Fixed, 95% CI) 1.36 [1.23, 1.51]




2 Individual counselling 13 6329 Risk Ratio (M-H, Fixed, 95% CI) 1.29 [1.13, 1.48]




3 Interactive computer programme 5 1554 Risk Ratio (M-H, Fixed, 95% CI) 1.21 [0.91, 1.61]



4 Phone quit lines 2 412 Risk Ratio (M-H, Fixed, 95% CI) 1.05 [0.66, 1.67]



5 Training doctors 2 1738 Risk Ratio (M-H, Fixed, 95% CI) 1.00 [0.66, 1.51]


6 Training lay supporters 1 54 Risk Ratio (M-H, Fixed, 95% CI) 1.5 [0.27, 8.28]


7 Staged SH materials 1 265 Risk Ratio (M-H, Fixed, 95% CI) 1.67 [0.70, 3.96]




Comparison 8. Cluster randomized trials


studies

No. of


1 Individual counselling 13 Risk Ratio (Fixed, 95% CI) 1.25 [1.07, 1.46]

1.1 Standard Self help 3 Risk Ratio (Fixed, 95% CI) 1.20 [0.92, 1.55]

1.2 Usual care 7 Risk Ratio (Fixed, 95% CI) 1.24 [0.99, 1.56]

1.3 Assessment only 3 Risk Ratio (Fixed, 95% CI) 1.43 [0.94, 2.17]

2 Interactive computer programme 5 Risk Ratio (Fixed, 95% CI) 1.19 [0.88, 1.61]


2.2 Assessment only 3 Risk Ratio (Fixed, 95% CI) 1.32 [0.76, 2.28]

3 Training doctors 2 Risk Ratio (Fixed, 95% CI) 1.33 [0.67, 2.63]


Analysis 1.1. Comparison 1 Optimal trial comparisons, Outcome 1 Stage-based vs standard SH materials.

Review: Stage-based interventions for smoking cessation

Comparison: 1 Optimal trial comparisons

Outcome: 1 Stage-based vs standard SH materials

Study or subgroup Experimental Control Risk Ratio Weight Risk Ratio

n/N n/N M-H,Fixed,95% CI M-H,Fixed,95% CI

Lennox 2001 30/870 37/869 80.2 % 0.81 [ 0.51, 1.30 ]

Prochaska 1993 13/192 9/186 19.8 % 1.40 [ 0.61, 3.20 ]

Total (95% CI) 1062 1055 100.0 % 0.93 [ 0.62, 1.39 ]

Total events: 43 (Experimental), 46 (Control)

Heterogeneity: Chi?? = 1.27, df = 1 (P = 0.26); I?? =21%

Test for overall effect: Z = 0.37 (P = 0.71)

Test for subgroup differences: Not applicable

0.01 0.1 1 10 100

Favours control Favours intervention



Analysis 1.2. Comparison 1 Optimal trial comparisons, Outcome 2 Stage-based counselling vs standard

advice.


Comparison: 1 Optimal trial comparisons

Outcome: 2 Stage-based counselling vs standard advice



Mermelstein 2003 106/381 108/375 75.6 % 0.97 [ 0.77, 1.21 ]

Thompson 1993 40/197 34/185 24.4 % 1.10 [ 0.73, 1.67 ]

Total (95% CI) 578 560 100.0 % 1.00 [ 0.82, 1.22 ]


Heterogeneity: Chi?? = 0.32, df = 1 (P = 0.57); I?? =0.0%



0.01 0.1 1 10 100


Analysis 2.1. Comparison 2 Abstinence by intervention and comparison, Outcome 1 Expert systems.


Comparison: 2 Abstinence by intervention and comparison

Outcome: 1 Expert systems

Study or subgroup Expert system Control Risk Ratio Weight Risk Ratio


1 Standard self help

Aveyard 2003 15/683 10/690 8.2 % 1.52 [ 0.69, 3.35 ]

Borland 2003 24/523 21/527 17.3 % 1.15 [ 0.65, 2.04 ]

Borland 2004 61/382 35/390 28.6 % 1.78 [ 1.20, 2.63 ]

Dijkstra 1999 14/420 7/215 7.7 % 1.02 [ 0.42, 2.50 ]

Lennox 2001 30/870 37/869 30.6 % 0.81 [ 0.51, 1.30 ]

Prochaska 1993 13/192 9/186 7.6 % 1.40 [ 0.61, 3.20 ]

Subtotal (95% CI) 3070 2877 100.0 % 1.27 [ 1.01, 1.59 ]

0.1 0.2 0.5 1 2 5 10


(Continued . . . )



(. . . Continued)Study or subgroup Expert system Control Risk Ratio Weight Risk Ratio


Total events: 157 (Expert system), 119 (Control)



2 Usual care

McBride 1999 16/288 14/292 49.9 % 1.16 [ 0.58, 2.33 ]

Stotts 2002 10/134 14/135 50.1 % 0.72 [ 0.33, 1.56 ]

Subtotal (95% CI) 422 427 100.0 % 0.94 [ 0.56, 1.57 ]




3 Assessment only

Curry 1995 7/329 7/328 1.7 % 1.00 [ 0.35, 2.81 ]

Dijkstra 1998 26/1155 4/385 1.5 % 2.17 [ 0.76, 6.17 ]

Etter 2004 163/1467 154/1467 37.8 % 1.06 [ 0.86, 1.30 ]

Hollis 2005 54/281 25/284 6.1 % 2.18 [ 1.40, 3.41 ]

Meyer 2008 14/488 5/609 1.1 % 3.49 [ 1.27, 9.63 ]

Prochaska 2001a 96/1346 136/2761 21.9 % 1.45 [ 1.12, 1.86 ]

Prochaska 2001b 28/362 16/350 4.0 % 1.69 [ 0.93, 3.07 ]

Prochaska 2004 29/349 18/362 4.3 % 1.67 [ 0.95, 2.95 ]

Prochaska 2005 85/352 81/437 17.7 % 1.30 [ 0.99, 1.71 ]

Schumann 2006 15/240 16/245 3.9 % 0.96 [ 0.48, 1.89 ]

Subtotal (95% CI) 6369 7228 100.0 % 1.35 [ 1.19, 1.52 ]



Test for overall effect: Z = 4.83 (P < 0.00001)

0.1 0.2 0.5 1 2 5 10




Analysis 2.2. Comparison 2 Abstinence by intervention and comparison, Outcome 2 Individual counselling.



Outcome: 2 Individual counselling




Hann??ver 2009 2/151 0/187 0.6 % 6.18 [ 0.30, 127.85 ]

Hennrikus 2005 66/666 59/673 80.3 % 1.13 [ 0.81, 1.58 ]

Meysman 2010 28/178 14/180 19.1 % 2.02 [ 1.10, 3.71 ]

Subtotal (95% CI) 995 1040 100.0 % 1.33 [ 1.00, 1.78 ]




2 Usual care

Bobo 1998 20/288 16/287 8.9 % 1.25 [ 0.66, 2.35 ]

Chouinard 2005 26/108 7/56 5.1 % 1.93 [ 0.89, 4.16 ]

Davies 2005 10/127 7/121 4.0 % 1.36 [ 0.54, 3.46 ]

Lawrence 2005 14/305 12/289 6.9 % 1.11 [ 0.52, 2.35 ]

Mermelstein 2003 106/381 108/375 60.7 % 0.97 [ 0.77, 1.21 ]

Pieterse 2001 22/269 8/261 4.5 % 2.67 [ 1.21, 5.89 ]

Prokhorov 2008 26/219 17/207 9.8 % 1.45 [ 0.81, 2.58 ]

Subtotal (95% CI) 1697 1596 100.0 % 1.19 [ 0.99, 1.42 ]




3 Assessment only

Manfredi 2004 57/527 61/541 88.2 % 0.96 [ 0.68, 1.35 ]

Meyer 2008 10/402 5/609 5.8 % 3.03 [ 1.04, 8.80 ]

Nakamura 2004 18/500 4/477 6.0 % 4.29 [ 1.46, 12.59 ]

Subtotal (95% CI) 1429 1627 100.0 % 1.28 [ 0.95, 1.73 ]




0.5 0.7 1 1.5 2




Analysis 2.3. Comparison 2 Abstinence by intervention and comparison, Outcome 3 Interactive computer

programme.



Outcome: 3 Interactive computer programme

Study or subgroup Programme Control Risk Ratio Weight Risk Ratio


1 Usual care

Aveyard 1999 53/547 46/542 78.5 % 1.14 [ 0.78, 1.66 ]

Lawrence 2005 15/324 12/289 21.5 % 1.11 [ 0.53, 2.34 ]

Subtotal (95% CI) 871 831 100.0 % 1.14 [ 0.81, 1.59 ]

Total events: 68 (Programme), 58 (Control)



2 Assessment only

Escoffery 2004 9/35 6/35 33.7 % 1.50 [ 0.60, 3.77 ]

O’Neill 2000 5/31 4/34 21.4 % 1.37 [ 0.40, 4.65 ]

Prochaska 2008 10/48 8/48 44.9 % 1.25 [ 0.54, 2.89 ]

Subtotal (95% CI) 114 117 100.0 % 1.36 [ 0.78, 2.36 ]




0.01 0.1 1 10 100




Analysis 2.4. Comparison 2 Abstinence by intervention and comparison, Outcome 4 Phone quit lines.



Outcome: 4 Phone quit lines

Study or subgroup Phone Control Risk Ratio Weight Risk Ratio



Thompson 1993 19/99 20/108 100.0 % 1.04 [ 0.59, 1.82 ]

Subtotal (95% CI) 99 108 100.0 % 1.04 [ 0.59, 1.82 ]

Total events: 19 (Phone), 20 (Control)

Heterogeneity: not applicable


2 Usual care

Young 2008 13/169 9/149 100.0 % 1.27 [ 0.56, 2.89 ]

Subtotal (95% CI) 169 149 100.0 % 1.27 [ 0.56, 2.89 ]




0.01 0.1 1 10 100


Analysis 2.5. Comparison 2 Abstinence by intervention and comparison, Outcome 5 Training doctors.



Outcome: 5 Training doctors

Study or subgroup Training Control Risk Ratio Weight Risk Ratio


1 Usual care

Lennox 1998 32/1381 37/1207 94.0 % 0.76 [ 0.47, 1.21 ]

Wang 1994 10/39 3/54 6.0 % 4.62 [ 1.36, 15.68 ]

Subtotal (95% CI) 1420 1261 100.0 % 0.99 [ 0.65, 1.50 ]

Total events: 42 (Training), 40 (Control)



0.01 0.1 1 10 100




Analysis 2.6. Comparison 2 Abstinence by intervention and comparison, Outcome 6 Training lay supporters.



Outcome: 6 Training lay supporters

Study or subgroup training Control Risk Ratio Weight Risk Ratio



Patten 2004 3/30 2/30 100.0 % 1.50 [ 0.27, 8.34 ]

Subtotal (95% CI) 30 30 100.0 % 1.50 [ 0.27, 8.34 ]

Total events: 3 (training), 2 (Control)



0.01 0.1 1 10 100


Analysis 2.7. Comparison 2 Abstinence by intervention and comparison, Outcome 7 Staged SH materials.



Outcome: 7 Staged SH materials

Study or subgroup SH materials Control Risk Ratio Weight Risk Ratio


1 Assessment only

Pallonen 1994 15/233 7/142 100.0 % 1.31 [ 0.55, 3.13 ]

Subtotal (95% CI) 233 142 100.0 % 1.31 [ 0.55, 3.13 ]

Total events: 15 (SH materials), 7 (Control)



0.01 0.1 1 10 100




Analysis 3.1. Comparison 3 Validated abstinence, Outcome 1 Biochemically validated abstinence.


Comparison: 3 Validated abstinence

Outcome: 1 Biochemically validated abstinence

Study or subgroup Intervention Control Risk Ratio Weight Risk Ratio


Aveyard 2003 15/683 10/690 3.9 % 1.52 [ 0.69, 3.35 ]

Bobo 1998 20/288 16/287 6.3 % 1.25 [ 0.66, 2.35 ]

Chouinard 2005 26/108 7/156 2.3 % 5.37 [ 2.42, 11.91 ]

Hennrikus 2005 66/666 59/673 23.2 % 1.13 [ 0.81, 1.58 ]

Lennox 2001 30/870 37/869 14.6 % 0.81 [ 0.51, 1.30 ]

McBride 1999 16/288 13/292 5.1 % 1.25 [ 0.61, 2.55 ]

Mermelstein 2003 106/381 108/375 43.0 % 0.97 [ 0.77, 1.21 ]

Nakamura 2004 18/500 4/477 1.6 % 4.29 [ 1.46, 12.59 ]

Total (95% CI) 3784 3819 100.0 % 1.19 [ 1.02, 1.39 ]

Total events: 297 (Intervention), 254 (Control)




0.01 0.1 1 10 100

Favours controll Favours intervention



Analysis 3.2. Comparison 3 Validated abstinence, Outcome 2 Self-reported abstinence.



Outcome: 2 Self-reported abstinence



Aveyard 1999 53/683 46/452 7.5 % 0.76 [ 0.52, 1.11 ]

Borland 2003 24/523 21/527 2.8 % 1.15 [ 0.65, 2.04 ]

Borland 2004 61/382 35/390 4.7 % 1.78 [ 1.20, 2.63 ]

Curry 1995 7/329 7/328 1.0 % 1.00 [ 0.35, 2.81 ]

Davies 2005 10/127 7/121 1.0 % 1.36 [ 0.54, 3.46 ]

Dijkstra 1999 14/420 10/208 1.8 % 0.69 [ 0.31, 1.53 ]

Escoffery 2004 9/35 6/35 0.8 % 1.50 [ 0.60, 3.77 ]

Etter 2004 163/1467 154/1467 20.9 % 1.06 [ 0.86, 1.30 ]

Hann??ver 2009 2/151 0/187 0.1 % 6.18 [ 0.30, 127.85 ]

Hollis 2005 54/281 25/284 3.4 % 2.18 [ 1.40, 3.41 ]

Lawrence 2005 29/629 12/289 2.2 % 1.11 [ 0.57, 2.14 ]

Lennox 1998 32/1381 37/1207 5.4 % 0.76 [ 0.47, 1.21 ]

Manfredi 2004 57/527 61/541 8.2 % 0.96 [ 0.68, 1.35 ]

Meyer 2008 24/890 5/609 0.8 % 3.28 [ 1.26, 8.56 ]

Meysman 2010 28/178 14/180 1.9 % 2.02 [ 1.10, 3.71 ]

O’Neill 2000 5/31 4/34 0.5 % 1.37 [ 0.40, 4.65 ]

Pallonen 1994 15/233 7/142 1.2 % 1.31 [ 0.55, 3.13 ]

Patten 2004 3/30 2/30 0.3 % 1.50 [ 0.27, 8.34 ]

Prochaska 2001a 96/1346 136/2761 12.1 % 1.45 [ 1.12, 1.86 ]

Prochaska 2001b 28/362 16/350 2.2 % 1.69 [ 0.93, 3.07 ]

Prochaska 2004 29/349 18/362 2.4 % 1.67 [ 0.95, 2.95 ]

Prochaska 2005 85/352 81/437 9.8 % 1.30 [ 0.99, 1.71 ]

Prochaska 2008 10/48 8/48 1.1 % 1.25 [ 0.54, 2.89 ]

Prokhorov 2008 26/219 17/207 2.4 % 1.45 [ 0.81, 2.58 ]

Schumann 2006 15/240 16/245 2.1 % 0.96 [ 0.48, 1.89 ]

Stotts 2002 10/134 14/135 1.9 % 0.72 [ 0.33, 1.56 ]

0.01 0.1 1 10 100


(Continued . . . )



(. . . Continued)Study or subgroup Intervention Control Risk Ratio Weight Risk Ratio


Wang 1994 10/39 3/54 0.3 % 4.62 [ 1.36, 15.68 ]

Young 2008 13/169 9/149 1.3 % 1.27 [ 0.56, 2.89 ]

Total (95% CI) 11555 11779 100.0 % 1.25 [ 1.14, 1.37 ]





0.01 0.1 1 10 100


Analysis 3.3. Comparison 3 Validated abstinence, Outcome 3 ’Bogus pipeline’.



Outcome: 3 ’Bogus pipeline’



Dijkstra 1998 26/1155 4/385 12.8 % 2.17 [ 0.76, 6.17 ]

Pieterse 2001 22/269 8/261 17.3 % 2.67 [ 1.21, 5.89 ]

Prochaska 1993 53/570 9/186 29.0 % 1.92 [ 0.97, 3.82 ]

Thompson 1993 19/99 20/108 40.9 % 1.04 [ 0.59, 1.82 ]

Total (95% CI) 2093 940 100.0 % 1.72 [ 1.20, 2.46 ]




0.01 0.1 1 10 100




Analysis 4.1. Comparison 4 Missing data testing, Outcome 1 Intervention ITT versus control per protocol.


Comparison: 4 Missing data testing

Outcome: 1 Intervention ITT versus control per protocol



Borland 2003 24/523 21/416 3.9 % 0.91 [ 0.51, 1.61 ]

Borland 2004 61/382 83/278 16.1 % 0.53 [ 0.40, 0.72 ]

Curry 1995 7/329 7/324 1.2 % 0.98 [ 0.35, 2.78 ]

Dijkstra 1998 26/1155 4/250 1.1 % 1.41 [ 0.50, 4.00 ]

Dijkstra 1999 14/420 10/182 2.3 % 0.61 [ 0.27, 1.34 ]

Etter 2004 163/1467 154/1346 27.0 % 0.97 [ 0.79, 1.20 ]

Mermelstein 2003 106/381 108/354 18.8 % 0.91 [ 0.73, 1.14 ]

Pallonen 1994 15/233 7/116 1.6 % 1.07 [ 0.45, 2.54 ]

Patten 2004 3/30 2/27 0.4 % 1.35 [ 0.24, 7.48 ]

Prochaska 1993 13/192 9/166 1.6 % 1.25 [ 0.55, 2.85 ]

Prochaska 2001a 96/1346 136/1769 19.7 % 0.93 [ 0.72, 1.19 ]

Prochaska 2001b 28/362 16/252 3.2 % 1.22 [ 0.67, 2.20 ]

Schumann 2006 15/240 16/175 3.1 % 0.68 [ 0.35, 1.35 ]

Total (95% CI) 7060 5655 100.0 % 0.88 [ 0.79, 0.98 ]





0.01 0.1 1 10 100




Analysis 4.2. Comparison 4 Missing data testing, Outcome 2 Intervention ITT versus control ITT.


Comparison: 4 Missing data testing

Outcome: 2 Intervention ITT versus control ITT



Borland 2003 24/523 21/527 4.3 % 1.15 [ 0.65, 2.04 ]

Borland 2004 61/382 35/390 7.1 % 1.78 [ 1.20, 2.63 ]

Curry 1995 7/329 7/328 1.4 % 1.00 [ 0.35, 2.81 ]

Dijkstra 1998 26/1155 4/385 1.2 % 2.17 [ 0.76, 6.17 ]

Dijkstra 1999 14/420 10/208 2.7 % 0.69 [ 0.31, 1.53 ]

Etter 2004 163/1467 154/1467 31.4 % 1.06 [ 0.86, 1.30 ]

Mermelstein 2003 106/381 108/375 22.2 % 0.97 [ 0.77, 1.21 ]

Pallonen 1994 15/233 7/142 1.8 % 1.31 [ 0.55, 3.13 ]

Patten 2004 3/30 2/30 0.4 % 1.50 [ 0.27, 8.34 ]

Prochaska 1993 53/570 9/186 2.8 % 1.92 [ 0.97, 3.82 ]

Prochaska 2001a 96/1346 136/2761 18.2 % 1.45 [ 1.12, 1.86 ]

Prochaska 2001b 28/362 16/350 3.3 % 1.69 [ 0.93, 3.07 ]

Schumann 2006 15/240 16/245 3.2 % 0.96 [ 0.48, 1.89 ]

Total (95% CI) 7438 7394 100.0 % 1.21 [ 1.09, 1.36 ]





0.01 0.1 1 10 100




Analysis 5.1. Comparison 5 Any stage-based intervention vs control, Outcome 1 Abstinence at longest

follow up.


Comparison: 5 Any stage-based intervention vs control

Outcome: 1 Abstinence at longest follow up



Aveyard 1999 53/547 46/542 4.5 % 1.14 [ 0.78, 1.66 ]

Aveyard 2003 15/683 10/690 1.0 % 1.52 [ 0.69, 3.35 ]

Bobo 1998 20/288 16/287 1.6 % 1.25 [ 0.66, 2.35 ]

Borland 2003 24/523 21/527 2.0 % 1.15 [ 0.65, 2.04 ]

Borland 2004 61/382 35/390 3.4 % 1.78 [ 1.20, 2.63 ]

Chouinard 2005 26/108 7/56 0.9 % 1.93 [ 0.89, 4.16 ]

Curry 1995 7/329 7/328 0.7 % 1.00 [ 0.35, 2.81 ]

Davies 2005 10/127 7/121 0.7 % 1.36 [ 0.54, 3.46 ]

Dijkstra 1998 26/1155 4/385 0.6 % 2.17 [ 0.76, 6.17 ]

Dijkstra 1999 14/420 10/208 1.3 % 0.69 [ 0.31, 1.53 ]

Escoffery 2004 9/35 6/35 0.6 % 1.50 [ 0.60, 3.77 ]

Etter 2004 163/1467 154/1467 15.0 % 1.06 [ 0.86, 1.30 ]

Hann??ver 2009 2/151 0/187 0.0 % 6.18 [ 0.30, 127.85 ]

Hennrikus 2005 66/666 59/673 5.7 % 1.13 [ 0.81, 1.58 ]

Hollis 2005 54/281 25/284 2.4 % 2.18 [ 1.40, 3.41 ]

Lawrence 2005 29/629 12/289 1.6 % 1.11 [ 0.57, 2.14 ]

Lennox 1998 32/1381 37/1207 3.8 % 0.76 [ 0.47, 1.21 ]

Lennox 2001 30/870 37/869 3.6 % 0.81 [ 0.51, 1.30 ]

Manfredi 2004 57/527 61/541 5.9 % 0.96 [ 0.68, 1.35 ]

McBride 1999 16/288 13/292 1.3 % 1.25 [ 0.61, 2.55 ]

Mermelstein 2003 106/381 108/375 10.6 % 0.97 [ 0.77, 1.21 ]

Meyer 2008 24/890 5/609 0.6 % 3.28 [ 1.26, 8.56 ]

Meysman 2010 28/178 14/180 1.4 % 2.02 [ 1.10, 3.71 ]

Nakamura 2004 18/500 4/477 0.4 % 4.29 [ 1.46, 12.59 ]

O’Neill 2000 5/31 4/34 0.4 % 1.37 [ 0.40, 4.65 ]

0.01 0.1 1 10 100


(Continued . . . )



(. . . Continued)Study or subgroup Intervention Control Risk Ratio Weight Risk Ratio


Pallonen 1994 15/233 7/142 0.8 % 1.31 [ 0.55, 3.13 ]

Patten 2004 3/30 2/30 0.2 % 1.50 [ 0.27, 8.34 ]

Pieterse 2001 22/269 8/261 0.8 % 2.67 [ 1.21, 5.89 ]

Prochaska 1993 13/192 9/186 0.9 % 1.40 [ 0.61, 3.20 ]

Prochaska 2001a 96/1346 136/2761 8.7 % 1.45 [ 1.12, 1.86 ]

Prochaska 2001b 28/362 16/350 1.6 % 1.69 [ 0.93, 3.07 ]

Prochaska 2004 29/349 18/362 1.7 % 1.67 [ 0.95, 2.95 ]

Prochaska 2005 85/352 81/437 7.0 % 1.30 [ 0.99, 1.71 ]

Prochaska 2008 10/48 8/48 0.8 % 1.25 [ 0.54, 2.89 ]

Prokhorov 2008 26/219 17/207 1.7 % 1.45 [ 0.81, 2.58 ]

Schumann 2006 15/240 16/245 1.5 % 0.96 [ 0.48, 1.89 ]

Stotts 2002 10/134 14/135 1.4 % 0.72 [ 0.33, 1.56 ]

Thompson 1993 19/99 20/108 1.9 % 1.04 [ 0.59, 1.82 ]

Wang 1994 10/39 3/54 0.2 % 4.62 [ 1.36, 15.68 ]

Young 2008 13/169 9/149 0.9 % 1.27 [ 0.56, 2.89 ]

Total (95% CI) 16918 16528 100.0 % 1.25 [ 1.16, 1.35 ]





0.01 0.1 1 10 100




Analysis 5.2. Comparison 5 Any stage-based intervention vs control, Outcome 2 Abstinence by comparison

condition.


Comparison: 5 Any stage-based intervention vs control

Outcome: 2 Abstinence by comparison condition

Study or subgroup Intervention Control Risk Ratio Risk Ratio


1 Standard self-help materials

Aveyard 2003 15/683 10/690 1.52 [ 0.69, 3.35 ]

Borland 2003 24/523 21/527 1.15 [ 0.65, 2.04 ]

Borland 2004 61/382 35/390 1.78 [ 1.20, 2.63 ]

Dijkstra 1999 14/420 7/215 1.02 [ 0.42, 2.50 ]

Hann??ver 2009 2/151 0/187 6.18 [ 0.30, 127.85 ]

Hennrikus 2005 66/666 59/673 1.13 [ 0.81, 1.58 ]

Lennox 2001 30/870 37/869 0.81 [ 0.51, 1.30 ]

Mermelstein 2003 106/381 108/375 0.97 [ 0.77, 1.21 ]

Meysman 2010 28/178 14/180 2.02 [ 1.10, 3.71 ]

Patten 2004 3/30 2/30 1.50 [ 0.27, 8.34 ]

Prochaska 1993 53/570 9/186 1.92 [ 0.97, 3.82 ]

Thompson 1993 19/99 20/108 1.04 [ 0.59, 1.82 ]

Subtotal (95% CI) 4953 4430 1.19 [ 1.04, 1.37 ]




2 Usual care

Aveyard 1999 53/547 46/542 1.14 [ 0.78, 1.66 ]

Bobo 1998 20/288 16/287 1.25 [ 0.66, 2.35 ]

Chouinard 2005 26/108 7/56 1.93 [ 0.89, 4.16 ]

Davies 2005 10/127 7/121 1.36 [ 0.54, 3.46 ]

Lawrence 2005 29/629 12/289 1.11 [ 0.57, 2.14 ]

Lennox 1998 32/1381 37/1207 0.76 [ 0.47, 1.21 ]

McBride 1999 16/288 13/292 1.25 [ 0.61, 2.55 ]

Pieterse 2001 22/269 8/261 2.67 [ 1.21, 5.89 ]

Prokhorov 2008 26/219 17/207 1.45 [ 0.81, 2.58 ]

0.01 0.1 1 10 100


(Continued . . . )



(. . . Continued)Study or subgroup Intervention Control Risk Ratio Risk Ratio


Stotts 2002 10/134 14/135 0.72 [ 0.33, 1.56 ]

Wang 1994 10/39 3/54 4.62 [ 1.36, 15.68 ]

Young 2008 0/55 0/34 0.0 [ 0.0, 0.0 ]

Subtotal (95% CI) 4084 3485 1.23 [ 1.02, 1.48 ]




3 Assessment only

Curry 1995 7/329 7/328 1.00 [ 0.35, 2.81 ]

Dijkstra 1998 26/1155 4/385 2.17 [ 0.76, 6.17 ]

Escoffery 2004 9/35 6/35 1.50 [ 0.60, 3.77 ]

Etter 2004 163/1467 154/1467 1.06 [ 0.86, 1.30 ]

Hollis 2005 54/281 25/284 2.18 [ 1.40, 3.41 ]

Manfredi 2004 57/527 61/541 0.96 [ 0.68, 1.35 ]

Meyer 2008 24/890 5/609 3.28 [ 1.26, 8.56 ]

Nakamura 2004 18/500 4/477 4.29 [ 1.46, 12.59 ]

O’Neill 2000 5/31 4/34 1.37 [ 0.40, 4.65 ]

Pallonen 1994 15/233 7/142 1.31 [ 0.55, 3.13 ]

Prochaska 2001a 96/1346 136/2761 1.45 [ 1.12, 1.86 ]

Prochaska 2001b 28/362 16/350 1.69 [ 0.93, 3.07 ]

Prochaska 2004 29/349 18/362 1.67 [ 0.95, 2.95 ]

Prochaska 2005 85/352 81/437 1.30 [ 0.99, 1.71 ]

Prochaska 2008 10/48 8/48 1.25 [ 0.54, 2.89 ]

Schumann 2006 15/240 16/245 0.96 [ 0.48, 1.89 ]

Subtotal (95% CI) 8145 8505 1.33 [ 1.19, 1.48 ]




0.01 0.1 1 10 100




Analysis 6.1. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 1 Expert systems.


Comparison: 6 PPA at 6 or 12 m by intervention and comparison





Aveyard 2003 23/683 15/690 1.6 % 1.55 [ 0.82, 2.94 ]

Borland 2003 91/523 92/527 10.1 % 1.00 [ 0.77, 1.30 ]

Borland 2004 84/382 82/390 8.9 % 1.05 [ 0.80, 1.37 ]

Dijkstra 1999 14/420 7/215 1.0 % 1.02 [ 0.42, 2.50 ]

Lennox 2001 30/870 37/869 4.1 % 0.81 [ 0.51, 1.30 ]

Prochaska 1993 31/192 18/186 2.0 % 1.67 [ 0.97, 2.88 ]

Subtotal (95% CI) 3070 2877 27.8 % 1.07 [ 0.91, 1.25 ]




2 Usual care

McBride 1999 30/288 40/292 4.4 % 0.76 [ 0.49, 1.19 ]

Stotts 2002 10/134 14/135 1.5 % 0.72 [ 0.33, 1.56 ]

Subtotal (95% CI) 422 427 5.9 % 0.75 [ 0.51, 1.10 ]




3 Assessment only

Curry 1995 30/329 36/328 4.0 % 0.83 [ 0.52, 1.32 ]

Dijkstra 1998 77/1155 28/385 4.6 % 0.92 [ 0.60, 1.39 ]

Etter 2004 163/1467 154/1467 17.0 % 1.06 [ 0.86, 1.30 ]

Hollis 2005 64/281 31/284 3.4 % 2.09 [ 1.40, 3.10 ]

Meyer 2008 44/488 38/609 3.7 % 1.44 [ 0.95, 2.19 ]

Prochaska 2001a 154/1349 284/2774 20.5 % 1.12 [ 0.93, 1.34 ]

Prochaska 2001b 55/362 37/350 4.1 % 1.44 [ 0.97, 2.12 ]

Prochaska 2004 31/349 22/362 2.4 % 1.46 [ 0.86, 2.47 ]

Prochaska 2005 64/379 51/473 5.0 % 1.57 [ 1.11, 2.21 ]

Schumann 2006 16/240 15/245 1.6 % 1.09 [ 0.55, 2.15 ]

0.1 0.2 0.5 1 2 5 10


(Continued . . . )





Subtotal (95% CI) 6399 7277 66.3 % 1.20 [ 1.09, 1.33 ]




Total (95% CI) 9891 10581 100.0 % 1.14 [ 1.05, 1.24 ]




0.1 0.2 0.5 1 2 5 10


Analysis 6.2. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 2 Individual

counselling.







Hann??ver 2009 13/151 8/187 1.9 % 2.01 [ 0.86, 4.73 ]

Hennrikus 2005 66/666 59/673 15.9 % 1.13 [ 0.81, 1.58 ]

Subtotal (95% CI) 817 860 17.8 % 1.23 [ 0.90, 1.67 ]




2 Usual care

Bobo 1998 20/288 16/287 4.3 % 1.25 [ 0.66, 2.35 ]

Chouinard 2005 38/108 11/56 3.9 % 1.79 [ 0.99, 3.23 ]

Davies 2005 10/127 7/121 1.9 % 1.36 [ 0.54, 3.46 ]

Lawrence 2005 14/305 10/289 2.8 % 1.33 [ 0.60, 2.94 ]

Mermelstein 2003 112/381 117/375 31.9 % 0.94 [ 0.76, 1.17 ]

0.005 0.1 1 10 200


(Continued . . . )



(. . . Continued)Study or subgroup Experimental Control Risk Ratio Weight Risk Ratio


Pieterse 2001 36/269 19/261 5.2 % 1.84 [ 1.08, 3.12 ]

Prokhorov 2008 26/219 17/207 4.7 % 1.45 [ 0.81, 2.58 ]

Subtotal (95% CI) 1697 1596 54.9 % 1.19 [ 1.01, 1.41 ]




3 Assessment only

Manfredi 2004 59/527 59/541 15.8 % 1.03 [ 0.73, 1.44 ]

Meyer 2008 37/402 38/609 8.2 % 1.48 [ 0.95, 2.28 ]

Nakamura 2004 68/500 12/477 3.3 % 5.41 [ 2.96, 9.86 ]

Subtotal (95% CI) 1429 1627 27.3 % 1.70 [ 1.34, 2.14 ]


Heterogeneity: Chi?? = 23.05, df = 2 (P<0.00001); I?? =91%


Total (95% CI) 3943 4083 100.0 % 1.33 [ 1.18, 1.51 ]




Test for subgroup differences: Chi?? = 0.0, df = 2 (P = 0.0), I?? =0.0%

0.005 0.1 1 10 200




Analysis 6.3. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 3 Interactive

computer programme.






1 Usual care

Aveyard 1999 76/547 59/542 62.7 % 1.28 [ 0.93, 1.76 ]

Lawrence 2005 15/324 12/289 13.4 % 1.11 [ 0.53, 2.34 ]

Subtotal (95% CI) 871 831 76.1 % 1.25 [ 0.93, 1.67 ]




2 Assessment only

Escoffery 2004 9/35 6/35 6.3 % 1.50 [ 0.60, 3.77 ]

O’Neill 2000 8/31 9/34 9.1 % 0.97 [ 0.43, 2.21 ]

Prochaska 2008 10/48 8/48 8.5 % 1.25 [ 0.54, 2.89 ]

Subtotal (95% CI) 114 117 23.9 % 1.21 [ 0.74, 1.98 ]




Total (95% CI) 985 948 100.0 % 1.24 [ 0.96, 1.59 ]





0.01 0.1 1 10 100




Analysis 6.4. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 4 Phone quit lines.







Thompson 1993 19/99 20/108 66.7 % 1.04 [ 0.59, 1.82 ]

Subtotal (95% CI) 99 108 66.7 % 1.04 [ 0.59, 1.82 ]




2 Usual care

Young 2008 13/169 9/149 33.3 % 1.27 [ 0.56, 2.89 ]

Subtotal (95% CI) 169 149 33.3 % 1.27 [ 0.56, 2.89 ]




Total (95% CI) 268 257 100.0 % 1.12 [ 0.70, 1.78 ]





0.01 0.1 1 10 100




Analysis 6.5. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 5 Training doctors.






1 Usual care

Lennox 1998 100/1381 93/1207 97.5 % 0.94 [ 0.72, 1.23 ]

Wang 1994 10/39 3/54 2.5 % 4.62 [ 1.36, 15.68 ]

Total (95% CI) 1420 1261 100.0 % 1.03 [ 0.79, 1.34 ]





0.01 0.1 1 10 100


Analysis 6.6. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 6 Training lay

supporters.







Patten 2004 3/30 2/30 100.0 % 1.50 [ 0.27, 8.34 ]

Total (95% CI) 30 30 100.0 % 1.50 [ 0.27, 8.34 ]





0.01 0.1 1 10 100




Analysis 6.7. Comparison 6 PPA at 6 or 12 m by intervention and comparison, Outcome 7 Staged SH

materials.






1 Assessment only

Pallonen 1994 19/233 8/142 100.0 % 1.45 [ 0.65, 3.22 ]

Total (95% CI) 233 142 100.0 % 1.45 [ 0.65, 3.22 ]





0.01 0.1 1 10 100


Analysis 7.1. Comparison 7 Per protocol analyses, Outcome 1 Expert systems.


Comparison: 7 Per protocol analyses





Aveyard 2003 15/471 10/524 1.7 % 1.67 [ 0.76, 3.68 ]

Borland 2003 24/402 21/416 3.8 % 1.18 [ 0.67, 2.09 ]

Borland 2004 61/244 33/278 5.7 % 2.11 [ 1.43, 3.10 ]

Dijkstra 1999 14/367 7/201 1.7 % 1.10 [ 0.45, 2.67 ]

Lennox 2001 30/857 37/846 6.8 % 0.80 [ 0.50, 1.28 ]

Prochaska 1993 13/175 9/166 1.7 % 1.37 [ 0.60, 3.12 ]

Subtotal (95% CI) 2516 2431 21.4 % 1.35 [ 1.08, 1.70 ]

0.1 0.2 0.5 1 2 5 10


(Continued . . . )








2 Usual care

McBride 1999 16/283 14/277 2.6 % 1.12 [ 0.56, 2.25 ]

Stotts 2002 10/82 14/82 2.6 % 0.71 [ 0.34, 1.51 ]

Subtotal (95% CI) 365 359 5.2 % 0.92 [ 0.55, 1.53 ]




3 Assessment only

Curry 1995 7/323 7/328 1.3 % 1.02 [ 0.36, 2.86 ]

Dijkstra 1998 26/740 4/250 1.1 % 2.20 [ 0.77, 6.23 ]

Etter 2004 163/1261 154/1310 27.8 % 1.10 [ 0.89, 1.35 ]

Hollis 2005 54/226 25/222 4.6 % 2.12 [ 1.37, 3.28 ]

Meyer 2008 14/232 5/341 0.7 % 4.12 [ 1.50, 11.27 ]

Prochaska 2001a 96/802 136/1769 15.6 % 1.56 [ 1.22, 1.99 ]

Prochaska 2001b 28/251 16/252 2.9 % 1.76 [ 0.98, 3.17 ]

Prochaska 2004 29/191 18/218 3.1 % 1.84 [ 1.06, 3.20 ]

Prochaska 2005 85/352 81/437 13.3 % 1.30 [ 0.99, 1.71 ]

Schumann 2006 16/175 15/153 2.9 % 0.93 [ 0.48, 1.82 ]

Subtotal (95% CI) 4553 5280 73.4 % 1.39 [ 1.24, 1.57 ]




Total (95% CI) 7434 8070 100.0 % 1.36 [ 1.23, 1.51 ]




0.1 0.2 0.5 1 2 5 10




Analysis 7.2. Comparison 7 Per protocol analyses, Outcome 2 Individual counselling.







Hann??ver 2009 2/151 0/187 0.1 % 6.18 [ 0.30, 127.85 ]

Hennrikus 2005 66/501 59/551 17.7 % 1.23 [ 0.88, 1.71 ]

Meysman 2010 28/178 14/180 4.4 % 2.02 [ 1.10, 3.71 ]

Subtotal (95% CI) 830 918 22.2 % 1.42 [ 1.07, 1.89 ]




2 Usual care

Bobo 1998 20/218 16/226 4.9 % 1.30 [ 0.69, 2.43 ]

Chouinard 2005 26/106 7/55 2.9 % 1.93 [ 0.89, 4.16 ]

Davies 2005 10/50 7/46 2.3 % 1.31 [ 0.55, 3.17 ]

Lawrence 2005 14/139 12/127 3.9 % 1.07 [ 0.51, 2.22 ]

Mermelstein 2003 106/372 108/354 34.8 % 0.93 [ 0.75, 1.17 ]

Pieterse 2001 22/144 8/151 2.5 % 2.88 [ 1.33, 6.27 ]

Prokhorov 2008 26/158 17/168 5.2 % 1.63 [ 0.92, 2.88 ]

Subtotal (95% CI) 1187 1127 56.5 % 1.19 [ 1.00, 1.42 ]




3 Assessment only

Manfredi 2004 59/226 69/285 19.2 % 1.08 [ 0.80, 1.46 ]

Meyer 2008 10/224 5/609 0.8 % 5.44 [ 1.88, 15.73 ]

Nakamura 2004 18/476 4/447 1.3 % 4.23 [ 1.44, 12.39 ]

Subtotal (95% CI) 926 1341 21.3 % 1.44 [ 1.10, 1.89 ]




Total (95% CI) 2943 3386 100.0 % 1.29 [ 1.13, 1.48 ]





0.005 0.1 1 10 200




Analysis 7.3. Comparison 7 Per protocol analyses, Outcome 3 Interactive computer programme.






1 Usual care

Aveyard 1999 53/547 46/542 60.9 % 1.14 [ 0.78, 1.66 ]

Lawrence 2005 15/131 12/127 16.0 % 1.21 [ 0.59, 2.49 ]

Subtotal (95% CI) 678 669 76.9 % 1.16 [ 0.83, 1.61 ]




2 Assessment only

Escoffery 2004 9/26 6/29 7.5 % 1.67 [ 0.69, 4.06 ]

O’Neill 2000 5/27 4/29 5.1 % 1.34 [ 0.40, 4.48 ]

Prochaska 2008 10/48 8/48 10.5 % 1.25 [ 0.54, 2.89 ]

Subtotal (95% CI) 101 106 23.1 % 1.41 [ 0.82, 2.42 ]




Total (95% CI) 779 775 100.0 % 1.21 [ 0.91, 1.61 ]





0.01 0.1 1 10 100




Analysis 7.4. Comparison 7 Per protocol analyses, Outcome 4 Phone quit lines.







Thompson 1993 19/99 20/108 65.1 % 1.04 [ 0.59, 1.82 ]

Subtotal (95% CI) 99 108 65.1 % 1.04 [ 0.59, 1.82 ]




2 Usual care

Young 2008 13/117 9/88 34.9 % 1.09 [ 0.49, 2.43 ]

Subtotal (95% CI) 117 88 34.9 % 1.09 [ 0.49, 2.43 ]




Total (95% CI) 216 196 100.0 % 1.05 [ 0.66, 1.67 ]





0.01 0.1 1 10 100




Analysis 7.5. Comparison 7 Per protocol analyses, Outcome 5 Training doctors.






1 Usual care

Lennox 1998 32/877 37/779 93.9 % 0.77 [ 0.48, 1.22 ]

Wang 1994 10/35 3/47 6.1 % 4.48 [ 1.33, 15.07 ]

Total (95% CI) 912 826 100.0 % 1.00 [ 0.66, 1.51 ]





0.01 0.1 1 10 100


Analysis 7.6. Comparison 7 Per protocol analyses, Outcome 6 Training lay supporters.







Patten 2004 3/27 2/27 100.0 % 1.50 [ 0.27, 8.28 ]

Total (95% CI) 27 27 100.0 % 1.50 [ 0.27, 8.28 ]





0.01 0.1 1 10 100




Analysis 7.7. Comparison 7 Per protocol analyses, Outcome 7 Staged SH materials.






1 Assessment only

Pallonen 1994 15/149 7/116 100.0 % 1.67 [ 0.70, 3.96 ]

Total (95% CI) 149 116 100.0 % 1.67 [ 0.70, 3.96 ]





0.01 0.1 1 10 100


Analysis 8.1. Comparison 8 Cluster randomized trials, Outcome 1 Individual counselling.


Comparison: 8 Cluster randomized trials


Study or subgroup log [Risk Ratio] Risk Ratio Weight Risk Ratio

(SE) IV,Fixed,95% CI IV,Fixed,95% CI

1 Standard Self help

Hann??ver 2009 1.821318 (1.5446) 0.3 % 6.18 [ 0.30, 127.57 ]

Hennrikus 2005 0.04879 (0.145968) 30.5 % 1.05 [ 0.79, 1.40 ]

Meysman 2010 0.703098 (0.310133) 6.8 % 2.02 [ 1.10, 3.71 ]

Subtotal (95% CI) 37.5 % 1.20 [ 0.92, 1.55 ]



2 Usual care

Bobo 1998 0.219665 (0.344366) 5.5 % 1.25 [ 0.63, 2.45 ]

Chouinard 2005 0.655407 (0.416246) 3.8 % 1.93 [ 0.85, 4.35 ]

0.01 0.1 1 10 100

Favours experimental Favours control

(Continued . . . )



(. . . Continued)Study or subgroup log [Risk Ratio] Risk Ratio Weight Risk Ratio


Davies 2005 0.307485 (0.47384) 2.9 % 1.36 [ 0.54, 3.44 ]

Lawrence 2005 0.100266 (0.401153) 4.0 % 1.11 [ 0.50, 2.43 ]

Mermelstein 2003 -0.03457 (0.172319) 21.9 % 0.97 [ 0.69, 1.35 ]

Pieterse 2001 0.982078 (0.403734) 4.0 % 2.67 [ 1.21, 5.89 ]

Prokhorov 2008 0.36853 (0.32769) 6.1 % 1.45 [ 0.76, 2.75 ]

Subtotal (95% CI) 48.1 % 1.24 [ 0.99, 1.56 ]



3 Assessment only

Manfredi 2004 -0.0416 (0.254389) 10.0 % 0.96 [ 0.58, 1.58 ]

Meyer 2008 1.108563 (0.544778) 2.2 % 3.03 [ 1.04, 8.81 ]

Nakamura 2004 1.456287 (0.549609) 2.2 % 4.29 [ 1.46, 12.60 ]

Subtotal (95% CI) 14.4 % 1.43 [ 0.94, 2.17 ]



Total (95% CI) 100.0 % 1.25 [ 1.07, 1.46 ]




0.01 0.1 1 10 100




Analysis 8.2. Comparison 8 Cluster randomized trials, Outcome 2 Interactive computer programme.






1 Usual care

Aveyard 1999 0.132468 (0.20694) 55.3 % 1.14 [ 0.76, 1.71 ]

Lawrence 2005 0.108827 (0.400688) 14.8 % 1.11 [ 0.51, 2.45 ]

Subtotal (95% CI) 70.1 % 1.14 [ 0.79, 1.63 ]



2 Assessment only

Escoffery 2004 0.405465 (0.468852) 10.8 % 1.50 [ 0.60, 3.76 ]

O’Neill 2000 0.157004 (0.616954) 6.2 % 1.17 [ 0.35, 3.92 ]

Prochaska 2008 0.223144 (0.427919) 12.9 % 1.25 [ 0.54, 2.89 ]

Subtotal (95% CI) 29.9 % 1.32 [ 0.76, 2.28 ]



Total (95% CI) 100.0 % 1.19 [ 0.88, 1.61 ]




0.01 0.1 1 10 100




Analysis 8.3. Comparison 8 Cluster randomized trials, Outcome 3 Training doctors.






1 Usual care

Lennox 1998 -0.27985 (0.419376) 68.9 % 0.76 [ 0.33, 1.72 ]

Wang 1994 1.530395 (0.623699) 31.1 % 4.62 [ 1.36, 15.69 ]

Total (95% CI) 100.0 % 1.33 [ 0.67, 2.63 ]




0.01 0.1 1 10 100


A D D I T I O N A L T A B L E S

Table 1. Cluster randomized trials data

Study Events (I) N (I) Clusters (I) Events (C) N (C) Clusters (C) ICC Design effect (I) Design effect (C)

Bobo 1998 20 288 6 16 287 6 1.123595506 1.123595506

Chouinard

2005

26 108 18 7 56 9.33333 1.123595506 1.123595506

Lawrence

2005

(Coun-

selling)

14 305 36 12 289 41 0.013 1.097138889 1.078634146

Lawrence

2005

(Com-

puter)

15 324 23 12 289 41 0.013 1.170130435 1.078634146

Lennox

1998

32 1381 8 37 1207 8 0.013 3.231125 2.948375

Manfredi

2004

57 527 6 61 541 6 0.013 2.128833333 2.159166667



Table 1. Cluster randomized trials data (Continued)

Prokhorov

2008

26 219 8 17 207 7 0.008 1.211 1.228571429

Aveyard

1999

53 547 26 46 542 26 0.008 1.160307692 1.158769231

Mermel-

stein 2003

106 381 4 108 375 4 0.013 2.22525 2.20575

A P P E N D I C E S

Appendix 1. Glossary of tobacco-related terms

Term Definition

Abstinence A period of being quit, i.e. stopping the use of cigarettes or other tobacco products,

May be defined in various ways; see also:

point prevalence abstinence; prolonged abstinence; continuous/sustained abstinence

Biochemical verification Also called ’biochemical validation’ or ’biochemical confirmation’:

A procedure for checking a tobacco user’s report that he or she has not smoked or used

tobacco. It can be measured by testing levels of nicotine or cotinine or other chemicals

in blood, urine, or saliva, or by measuring levels of carbon monoxide in exhaled breath

or in blood

Bupropion A pharmaceutical drug originally developed as an antidepressant, but now also licensed

for smoking cessation; trade names Zyban, Wellbutrin (when prescribed as an antide-

pressant)

Carbon monoxide (CO) A colourless, odourless highly poisonous gas found in tobacco smoke and in the lungs

of people who have recently smoked, or (in smaller amounts) in people who have been

exposed to tobacco smoke. May be used for biochemical verification of abstinence

Cessation Also called ’quitting’

The goal of treatment to help people achieve abstinence from smoking or other tobacco

use, also used to describe the process of changing the behaviour

Continuous abstinence Also called ’sustained abstinence’

A measure of cessation often used in clinical trials involving avoidance of all tobacco

use since the quit day until the time the assessment is made. The definition occasionally

allows for lapses. This is the most rigorous measure of abstinence



(Continued)

’Cold Turkey’ Quitting abruptly, and/or quitting without behavioural or pharmaceutical support

Craving A very intense urge or desire [to smoke].

See: Shiffman et al ’Recommendations for the assessment of tobacco craving and with-

drawal in smoking cessation trials’

Nicotine & Tobacco Research 2004: 6(4): 599-614

Dopamine A neurotransmitter in the brain which regulates mood, attention, pleasure, reward,

motivation and movement

Efficacy Also called ’treatment effect’ or ’effect size’:

The difference in outcome between the experimental and control groups

Harm reduction Strategies to reduce harm caused by continued tobacco/nicotine use, such as reducing

the number of cigarettes smoked, or switching to different brands or products, e.g.

potentially reduced exposure products (PREPs), smokeless tobacco

Lapse/slip Terms sometimes used for a return to tobacco use after a period of abstinence. A

lapse or slip might be defined as a puff or two on a cigarette. This may proceed to

relapse, or abstinence may be regained. Some definitions of continuous, sustained or

prolonged abstinence require complete abstinence, but some allow for a limited number

or duration of slips. People who lapse are very likely to relapse, but some treatments

may have their effect by helping people recover from a lapse

nAChR [neural nicotinic acetylcholine receptors]: Areas in the brain which are thought to

respond to nicotine, forming the basis of nicotine addiction by stimulating the overflow

of dopamine

Nicotine An alkaloid derived from tobacco, responsible for the psychoactive and addictive effects

of smoking

Nicotine Replacement Therapy (NRT) A smoking cessation treatment in which nicotine from tobacco is replaced for a limited

period by pharmaceutical nicotine. This reduces the craving and withdrawal experi-

enced during the initial period of abstinence while users are learning to be tobacco-free

The nicotine dose can be taken through the skin, using patches, by inhaling a spray, or

by mouth using gum or lozenges

Outcome Often used to describe the result being measured in trials that is of relevance to the

review. For example smoking cessation is the outcome used in reviews of ways to help

smokers quit. The exact outcome in terms of the definition of abstinence and the length

of time that has elapsed since the quit attempt was made may vary from trial to trial

Pharmacotherapy A treatment using pharmaceutical drugs, e.g. NRT, bupropion

Point prevalence abstinence (PPA) A measure of cessation based on behaviour at a particular point in time, or during a

relatively brief specified period, e.g. 24 hours, 7 days. It may include a mixture of recent

and long-term quitters. cf. prolonged abstinence, continuous abstinence



(Continued)

Prolonged abstinence A measure of cessation which typically allows a ’grace period’ following the quit date

(usually of about two weeks), to allow for slips/lapses during the first few days when

the effect of treatment may still be emerging.

See: Hughes et al ’Measures of abstinence in clinical trials: issues and recommendations’;

Nicotine & Tobacco Research, 2003: 5 (1); 13-25

Relapse A return to regular smoking after a period of abstinence

Secondhand smoke Also called passive smoking or environmental tobacco smoke [ETS]

A mixture of smoke exhaled by smokers and smoke released from smouldering

cigarettes, cigars, pipes, bidis, etc. The smoke mixture contains gases and particulates,

including nicotine, carcinogens and toxins

Self-efficacy The belief that one will be able to change one’s behaviour, e.g. to quit smoking

SPC [Summary of Product Characteristics] Advice from the manufacturers of a drug, agreed with the relevant licensing authority,

to enable health professionals to prescribe and use the treatment safely and effectively

Tapering A gradual decrease in dose at the end of treatment, as an alternative to abruptly stopping

treatment

Titration A technique of dosing at low levels at the beginning of treatment, and gradually in-

creasing to full dose over a few days, to allow the body to get used to the drug. It is

designed to limit side effects

Withdrawal A variety of behavioural, affective, cognitive and physiological symptoms, usually tran-

sient, which occur after use of an addictive drug is reduced or stopped.

See: Shiffman et al ’Recommendations for the assessment of tobacco craving and with-

drawal in smoking cessation trials’

Nicotine & Tobacco Research 2004: 6(4): 599-614

H I S T O R Y

Protocol first published: Issue 3, 2007

Review first published: Issue 11, 2010



C O N T R I B U T I O N S O F A U T H O R S

KC and NG selected studies and extracted data. TL checked data extraction. KC wrote the review, with contributions from all authors.

D E C L A R A T I O N S O F I N T E R E S T

None known

S O U R C E S O F S U P P O R T

Internal sources

• Department of Primary Health Care, Oxford University, UK.

External sources

• No sources of support supplied

D I F F E R E N C E S B E T W E E N P R O T O C O L A N D R E V I E W

We have added sections on matched-mismatched studies and on movement through stages of change, to test the robustness and validity

of the transtheoretical model.

I N D E X T E R M S

Medical Subject Headings (MeSH)

∗Motivation; Program Evaluation; Randomized Controlled Trials as Topic; Smoking [∗psychology; therapy]; Smoking Cessation

[∗methods; psychology]

MeSH check words

Humans



Documents

Stage-based interventions for smoking cessation