Abstract

Implementation intentions are a goal-setting technique in which an individual commits to perform a particular behavior when a specific context arises. Recently, researchers have begun studying how implementation intention (II) interventions can facilitate antismoking efforts. The current systematic review synthesized results of experimental studies that tested the effect of an II intervention on smoking cognitions and behavior. Of 29 reviewed articles, 11 studies met inclusion criteria. Nine studies (81.8%) tested an II intervention as a cessation tool for current smokers, whereas two tested II interventions as a tool to prevent smoking among predominantly nonsmoking adolescents. A majority of the studies (66.7%) testing II interventions as a cessation tool reported a positive effect on cessation at long-term follow-up. Of the two studies testing II interventions as a tool for prevention, one study found a positive effect on long-term follow-up. Methodology varied between the studies, highlighting the discrepancies between what researchers consider “implementation intentions” to be. II interventions are a promising tool for antismoking efforts, but more research is necessary to determine the best methodology and the populations for whom this intervention will be most effective.

Implications

Brief, free, and easily scalable, II interventions to prevent smoking are highly attractive for antismoking efforts. This review outlines the circumstances under which II interventions have demonstrated effectiveness in helping people resist smoking cigarettes. We illuminate gaps in the existing literature, limitations, methodological discrepancies between studies, and areas for future study.

Introduction

Smoking combustible cigarettes is associated with a myriad of deadly diseases, including lung cancer, coronary heart disease, chronic obstructive pulmonary disease, and type II diabetes.1 In 2016, smoking was responsible for 6.3 million deaths, making it the leading cause of preventable death worldwide.2 Fortunately, a recent survey found that almost 70% of current smokers want to quit, and over half of them made a quit attempt in the past year.3 Although many who smoke intend to stop, the highly addictive nature of nicotine makes quitting extremely difficult.4 Smokers go through an average of 30 quit attempts before they are successful at abandoning smoking altogether,5 highlighting a discrepancy between intention and quitting behavior. Because the discrepancy between intention and actual quitting behavior is so large,6 researchers have sought to identify strategies that help smokers’ intentions more successfully translate into cessation. One potentially useful approach involves having those who are preparing to quit form implementation intentions.

Implementation Intentions

Implementation intentions are highly specific plans that serve a larger goal.7 Implementation intentions supplement goal attainment by specifying the exact behaviors that will lead to this attainment.7 To set an implementation intention, an individual commits to perform a particular behavior if or when a specific situation is encountered. The standard format is as follows: “If/when situation X occurs, then I will do Y.”  7 For instance, a person who hopes to lose weight could set the implementation intention that if they are offered dessert at a restaurant, then they will decline. Implementation intentions work, in part, because they promote strong mental associations between the context cue (ie, being offered dessert) and the targeted behavior (ie, turning it down). As a result, the individual knows exactly how to respond the moment the context cue is encountered.8

Experimental manipulations of implementation intentions vary in the extent to which they are experimenter generated versus participant generated. For instance, some manipulations present a list of context cues and potential responses. Participants are then instructed to form implementation intentions by making connections between the two lists and deciding on a specific behavioral response for each context. Other manipulations require participants to generate both the context and the intended response on their own, creating the entire “if…then…” statement to implement the plan.9 Still other manipulations provide participants with potentially triggering contexts but ask them to generate their own unique intended responses for each situation.10

Implementation intentions are one of the best-validated tools for translating intentions into behavior.6 For example, in a meta-analysis of 94 independent studies, implementation intentions were found to enhance the likelihood of goal achievement by promoting initiation of goal striving and increasing the individual’s awareness of opportunities for goal pursuit.11 This exercise is effective for translating intentions into action for several reasons. First, implementation intentions help generate more specific goals (ie, more clearly defined), and such goals are more easily achieved than those that are more vague.12 Another reason implementation intentions are effective is that they increase the salience and accessibility of the specified cues. By identifying the context cues that are most relevant to them in advance, individuals better detect their prompt to act.13 This detection seems to operate at least partially without conscious awareness, as implementation intentions help individuals achieve goals even in contexts where cognitive load is high (ie, individuals are distracted by other tasks).14,15

Implementation Intentions and Smoking

Throughout the past decade, researchers have tested the potential of implementation intentions to prevent smoking initiation and help current smokers quit.16–18 Implementation intention (II) interventions allow smokers to create a plan for how to resist a cigarette if or when they feel an urge to use. Implementation intentions are a good fit for smoking cessation because smokers often report specific “triggers” of their cravings (eg, experiencing stress at work),19 which can serve as the contextual cues for the intended action to prevent smoking. For instance, a person who hopes to quit smoking could set the implementation intention that if they experience stress at work, then they will take a walk instead of having a cigarette. This way, implementation intentions can prepare the individual to effectively manage the encountered trigger.

Whereas the work described above utilized II interventions to reduce smoking, some studies have also examined how II interventions can prevent smoking initiation. In these studies, adolescents were asked to identify behavioral responses they could use to resist a cigarette when they felt pressured to smoke.20,21 Although a number of studies show promising effects of II interventions on smoking outcomes,18,22 others show no or minimal effect.20,23

Understanding the utility of implementation intentions is important for both large-scale and individual antismoking efforts. Although several interventions have demonstrated effectiveness for smoking cessation, including nicotine replacement therapy, individual counseling, and group behavior therapy,24 many of these methods are time consuming and costly. Implementation intentions offer a promising opportunity for an inexpensive (or even free), brief intervention. Importantly, setting implementation intentions can serve as an intervention itself or can be incorporated into larger cessation programs such as self-help materials or counseling,25,26 as well as preventive programs for adolescents. Given the potential of implementation intentions for both prevention and cessation efforts, it is important to synthesize the existing literature to clarify when and for whom these interventions will be effective.

Current Study

The objective of the present study was to synthesize research that has tested the effectiveness of II interventions and report critical differences between II interventions with respect to (1) the smoking status of the sample and (2) methods used to establish implementation intentions. This objective was met by conducting a systematic literature review. To date, two meta-analyses have examined the effects of smoking cessation interventions that involve implementation intentions, and both concluded that this intervention has a small, positive effect on promoting smoking cessation.27,28 However, these meta-analyses excluded several relevant studies that examine smoking outcomes other than cessation (eg, continued abstinence among nonsmokers, smoking behavior during a small window of time)27,28 or that did not meet the authors’ criteria for the protocol of an II intervention.28 The current review synthesizes experimental studies that test the effect of an II intervention on smoking outcomes including initiation, cessation, and other smoking cognitions or behaviors. We include all studies that refer to their intervention as an II intervention, regardless of the protocol, and provide commentary on the different methodologies across studies. However, we only include articles that isolate the effect of implementation intentions on smoking outcomes. In doing so, the review will elucidate the circumstances under which implementation intentions are effective tools to reduce smoking, which can be used to inform future interventions.

Methods

A systematic literature review that followed PRISMA guidelines was conducted.29 The electronic databases PsychInfo, PsychArticles, Medline, Medline Complete, and CINAHL Complete were searched on in July 2023 using three separate steps. First, the terms “smok*,” “ciga*,” and “tobacco” were entered as search terms combined with the operator “or.” Then “implementation intentions” and “volitional help” were entered as search terms combined with the operator “or.” The last step combined these two searches using the operator “and.” On the same day, a Pubmed search was conducted using the same search terms in a single step: “((smok*) OR (ciga*) OR (tobacco)) AND ((‘implementation intentions’) OR (‘volitional help’)).”

Searches did not include date restrictions, as implementation intentions are a relatively new intervention, but were limited to peer-reviewed articles written in English. The term “tobacco” and “volitional help” were included to ensure that the searches included all of the existing relevant literature. We included tobacco, a broader term than smoking or cigarettes, to help ensure that relevant studies were captured. Volitional help sheets are a specific method for conducting an implementation intentions intervention,16 so it was important to capture any studies that used this phrase to describe the same intervention.

Inclusion and Exclusion Criteria

Inclusion criteria specified that articles must be peer-reviewed, experimental studies using random assignment. Furthermore, only studies in which the primary outcome variables were cigarette smoking-related behaviors (eg, cessation, reduction) and/or cognitions (eg, craving, attitude) were included. Studies were required to use a design that isolates the effect of the II intervention. If experimental conditions used implementation intentions alongside other treatment methods (eg, an antismoking message), the comparison group needed to include the other treatment methods, so that the only difference between the two groups was the II intervention piece. This helps us avoid misattributing the effects of a larger intervention to implementation intentions alone.

The search process is shown in Figure 1. The initial search from the databases yielded a total of 64 articles. After removing duplicates, 29 unique articles remained. Titles and abstracts of the 29 articles were independently screened by two authors (RH and CH) for relevance. The agreement rate was 79% and discrepancies were resolved through discussion. After this review, 13 articles remained. Manual checks of the references of these 13 articles were also completed to identify any additional relevant studies, and 2 were found, leaving a total of 15 studies. Upon full-text review, three studies were eliminated for not meeting the inclusion criteria (ie, the studies did not completely isolate the effect of the II intervention). As a result, a total of 12 studies were included in the review.

Figure 1.

Flow diagram of search process.

Open in new tabDownload slide Data Extraction

Three authors (CH, RH, SV) independently completed an equal portion of the full-text search and data extraction. To ascertain agreement, a second author assessed and edited another’s contribution to the data extraction chart. Extracted data included the sample, study duration, intervention and control condition methods, main outcome measures, and results for all studies. The data extraction sheet is shown in Table 1. The samples and outcome measures varied among the selected studies, which precluded the possibility of statistically combining quantitative results. Therefore, the findings are presented as a systematic review rather than a meta-analysis.

Table 1. Open in new tab

Data Extraction

Reference . Sample . Experimental groups . Implementation intentions intervention(s) . Primary findings . Armitage3090 smokers (ages 18–85)Randomly assigned to II intervention vs control conditionGiven 3 blank lines; instructed to create implementation intentions to help them quit smoking in the next 2 mo.II intervention group more likely to report having quit at 2-mo follow-up.Armitage16193 smokers (ages 16–78)Randomly assigned to an II intervention or to one of three comparison conditionsGiven 20 potentially triggering contexts and 20 responses to avoid smoking; asked to link context to response by drawing a line between the two.II intervention group were more likely to report having quit at 1-mo follow-up than those in all other conditions.Armitage22168 smokers (ages 18–75)Randomly assigned to intervention (II intervention vs control) × certainty condition (“if” vs “when” stems)Linked a column of 20 potentially triggering contexts with 20 responses to avoid smoking by drawing a line between the two. Contexts were preceded by “if” or “when.”Intervention groups more likely to report having quit at 1-mo follow-up than those in the control conditions. No differences found between certainty conditions.Armitage and Arden31350 smokersRandomly assigned to an II intervention or one of two comparison conditionsAsked to write down a detailed plan to help them quit in 1 mo. Told to pay attention to the situations in which they would implement the plans.II intervention group were more likely to have quit at 2-mo follow-up than comparison groups.Brown et al.18159 smokers in cessation program (ages 18–83)Randomly assigned to weekly self-incentivizing II intervention, monthly incentivizing II intervention, or comparison groupAsked to choose 1 of 20 self-incentives as a reward for not smoking for a full week (or for full month).Intervention groups (vs comparison) more likely to have quit at 3- and 6-mo follow-up. No differences between the weekly and monthly groups.Conner and Higgins211551 adolescents (ages 11–12 at baseline)Randomly assigned to II intervention or 1 of 3 comparison conditions. Completed every 4 mo for 2 yrSelected 1 of 5 possible responses to decline a cigarette, or wrote in own response. Also indicated where and when they would not smoke by checking boxes.II intervention group less likely to be smokers (self-report and objective measure) at 48-mo follow-up when compared to the comparison conditions.DeStasio et al.3262 smokers (ages 25–66)Randomly assigned to II intervention + self-authored motivational text messages for 30 days, self-authored text messages only, or active control groupInstructed to identify an obstacle (“if”) and pair it with a specific plan (“then”) to help them quit smoking. Examples were provided.No between-group differences in change in cigarettes/day after intervention (~30 days post-baseline). Participants in self-authorship + II condition had larger reduction in CO2 than those in the active control condition.Higgins and Conner20347 children (ages 11–12)Randomly assigned to II intervention or control conditionSelected 1 of 5 possible responses to decline a cigarette, or wrote in own response. Indicated where and when they would not smoke by checking boxes.No differences in cessation at 8-week follow-up.Matcham et al.17160 smokers newly referred to cessation program (ages 19–80)Randomly assigned to 1 of 4 groups: standard care alone, standard care + effectiveness booklet, standard care + II, or standard care + effectiveness booklet and IIInstructed to read the following statement three times and repeat it silently one time: “As soon as I start to doubt about attending my appointments with the NHS SSSs, I will ignore that feeling and tell myself that this is perfectly normal to feel that way!”No differences in cessation at 4-week follow-up.Moody et al.3336 smokers (ages 18 and 65)All completed 4 different interventions during 4 different sessions (order randomly assigned): control task, II intervention; monetary incentives; II intervention + monetary incentivesGiven 7 context cues and 11 responses to avoid smoking and linked the two. Picked three of the pairs and wrote the full sentences word-for-word.II intervention had no effect on amount of time smokers resisted smoking during a 2-h period.Van Osch et al.231,566 smokers in cessation program (ages 18–81)Randomly assigned to II intervention or control conditionChose 3 context cues from a list of 14; wrote in their plan to avoid smoking in that situation. Full intentions were flashed on the screen.No significant differences in smoking abstinence at 1- or 7-mo follow-up.Webb et al.,34 Study 2172 high school smokers (ages 17–21)Randomly assigned: II intervention or control conditionGiven four risk situations; asked to write down how they would avoid smoking in each situation.II group reported fewer cigarettes per day at 1-mo follow-up, but only among participants with weak/moderate (not strong) habit strength.Reference . Sample . Experimental groups . Implementation intentions intervention(s) . Primary findings . Armitage3090 smokers (ages 18–85)Randomly assigned to II intervention vs control conditionGiven 3 blank lines; instructed to create implementation intentions to help them quit smoking in the next 2 mo.II intervention group more likely to report having quit at 2-mo follow-up.Armitage16193 smokers (ages 16–78)Randomly assigned to an II intervention or to one of three comparison conditionsGiven 20 potentially triggering contexts and 20 responses to avoid smoking; asked to link context to response by drawing a line between the two.II intervention group were more likely to report having quit at 1-mo follow-up than those in all other conditions.Armitage22168 smokers (ages 18–75)Randomly assigned to intervention (II intervention vs control) × certainty condition (“if” vs “when” stems)Linked a column of 20 potentially triggering contexts with 20 responses to avoid smoking by drawing a line between the two. Contexts were preceded by “if” or “when.”Intervention groups more likely to report having quit at 1-mo follow-up than those in the control conditions. No differences found between certainty conditions.Armitage and Arden31350 smokersRandomly assigned to an II intervention or one of two comparison conditionsAsked to write down a detailed plan to help them quit in 1 mo. Told to pay attention to the situations in which they would implement the plans.II intervention group were more likely to have quit at 2-mo follow-up than comparison groups.Brown et al.18159 smokers in cessation program (ages 18–83)Randomly assigned to weekly self-incentivizing II intervention, monthly incentivizing II intervention, or comparison groupAsked to choose 1 of 20 self-incentives as a reward for not smoking for a full week (or for full month).Intervention groups (vs comparison) more likely to have quit at 3- and 6-mo follow-up. No differences between the weekly and monthly groups.Conner and Higgins211551 adolescents (ages 11–12 at baseline)Randomly assigned to II intervention or 1 of 3 comparison conditions. Completed every 4 mo for 2 yrSelected 1 of 5 possible responses to decline a cigarette, or wrote in own response. Also indicated where and when they would not smoke by checking boxes.II intervention group less likely to be smokers (self-report and objective measure) at 48-mo follow-up when compared to the comparison conditions.DeStasio et al.3262 smokers (ages 25–66)Randomly assigned to II intervention + self-authored motivational text messages for 30 days, self-authored text messages only, or active control groupInstructed to identify an obstacle (“if”) and pair it with a specific plan (“then”) to help them quit smoking. Examples were provided.No between-group differences in change in cigarettes/day after intervention (~30 days post-baseline). Participants in self-authorship + II condition had larger reduction in CO2 than those in the active control condition.Higgins and Conner20347 children (ages 11–12)Randomly assigned to II intervention or control conditionSelected 1 of 5 possible responses to decline a cigarette, or wrote in own response. Indicated where and when they would not smoke by checking boxes.No differences in cessation at 8-week follow-up.Matcham et al.17160 smokers newly referred to cessation program (ages 19–80)Randomly assigned to 1 of 4 groups: standard care alone, standard care + effectiveness booklet, standard care + II, or standard care + effectiveness booklet and IIInstructed to read the following statement three times and repeat it silently one time: “As soon as I start to doubt about attending my appointments with the NHS SSSs, I will ignore that feeling and tell myself that this is perfectly normal to feel that way!”No differences in cessation at 4-week follow-up.Moody et al.3336 smokers (ages 18 and 65)All completed 4 different interventions during 4 different sessions (order randomly assigned): control task, II intervention; monetary incentives; II intervention + monetary incentivesGiven 7 context cues and 11 responses to avoid smoking and linked the two. Picked three of the pairs and wrote the full sentences word-for-word.II intervention had no effect on amount of time smokers resisted smoking during a 2-h period.Van Osch et al.231,566 smokers in cessation program (ages 18–81)Randomly assigned to II intervention or control conditionChose 3 context cues from a list of 14; wrote in their plan to avoid smoking in that situation. Full intentions were flashed on the screen.No significant differences in smoking abstinence at 1- or 7-mo follow-up.Webb et al.,34 Study 2172 high school smokers (ages 17–21)Randomly assigned: II intervention or control conditionGiven four risk situations; asked to write down how they would avoid smoking in each situation.II group reported fewer cigarettes per day at 1-mo follow-up, but only among participants with weak/moderate (not strong) habit strength.

II = implementation intention.

Table 1. Open in new tab

Data Extraction

Reference . Sample . Experimental groups . Implementation intentions intervention(s) . Primary findings . Armitage3090 smokers (ages 18–85)Randomly assigned to II intervention vs control conditionGiven 3 blank lines; instructed to create implementation intentions to help them quit smoking in the next 2 mo.II intervention group more likely to report having quit at 2-mo follow-up.Armitage16193 smokers (ages 16–78)Randomly assigned to an II intervention or to one of three comparison conditionsGiven 20 potentially triggering contexts and 20 responses to avoid smoking; asked to link context to response by drawing a line between the two.II intervention group were more likely to report having quit at 1-mo follow-up than those in all other conditions.Armitage22168 smokers (ages 18–75)Randomly assigned to intervention (II intervention vs control) × certainty condition (“if” vs “when” stems)Linked a column of 20 potentially triggering contexts with 20 responses to avoid smoking by drawing a line between the two. Contexts were preceded by “if” or “when.”Intervention groups more likely to report having quit at 1-mo follow-up than those in the control conditions. No differences found between certainty conditions.Armitage and Arden31350 smokersRandomly assigned to an II intervention or one of two comparison conditionsAsked to write down a detailed plan to help them quit in 1 mo. Told to pay attention to the situations in which they would implement the plans.II intervention group were more likely to have quit at 2-mo follow-up than comparison groups.Brown et al.18159 smokers in cessation program (ages 18–83)Randomly assigned to weekly self-incentivizing II intervention, monthly incentivizing II intervention, or comparison groupAsked to choose 1 of 20 self-incentives as a reward for not smoking for a full week (or for full month).Intervention groups (vs comparison) more likely to have quit at 3- and 6-mo follow-up. No differences between the weekly and monthly groups.Conner and Higgins211551 adolescents (ages 11–12 at baseline)Randomly assigned to II intervention or 1 of 3 comparison conditions. Completed every 4 mo for 2 yrSelected 1 of 5 possible responses to decline a cigarette, or wrote in own response. Also indicated where and when they would not smoke by checking boxes.II intervention group less likely to be smokers (self-report and objective measure) at 48-mo follow-up when compared to the comparison conditions.DeStasio et al.3262 smokers (ages 25–66)Randomly assigned to II intervention + self-authored motivational text messages for 30 days, self-authored text messages only, or active control groupInstructed to identify an obstacle (“if”) and pair it with a specific plan (“then”) to help them quit smoking. Examples were provided.No between-group differences in change in cigarettes/day after intervention (~30 days post-baseline). Participants in self-authorship + II condition had larger reduction in CO2 than those in the active control condition.Higgins and Conner20347 children (ages 11–12)Randomly assigned to II intervention or control conditionSelected 1 of 5 possible responses to decline a cigarette, or wrote in own response. Indicated where and when they would not smoke by checking boxes.No differences in cessation at 8-week follow-up.Matcham et al.17160 smokers newly referred to cessation program (ages 19–80)Randomly assigned to 1 of 4 groups: standard care alone, standard care + effectiveness booklet, standard care + II, or standard care + effectiveness booklet and IIInstructed to read the following statement three times and repeat it silently one time: “As soon as I start to doubt about attending my appointments with the NHS SSSs, I will ignore that feeling and tell myself that this is perfectly normal to feel that way!”No differences in cessation at 4-week follow-up.Moody et al.3336 smokers (ages 18 and 65)All completed 4 different interventions during 4 different sessions (order randomly assigned): control task, II intervention; monetary incentives; II intervention + monetary incentivesGiven 7 context cues and 11 responses to avoid smoking and linked the two. Picked three of the pairs and wrote the full sentences word-for-word.II intervention had no effect on amount of time smokers resisted smoking during a 2-h period.Van Osch et al.231,566 smokers in cessation program (ages 18–81)Randomly assigned to II intervention or control conditionChose 3 context cues from a list of 14; wrote in their plan to avoid smoking in that situation. Full intentions were flashed on the screen.No significant differences in smoking abstinence at 1- or 7-mo follow-up.Webb et al.,34 Study 2172 high school smokers (ages 17–21)Randomly assigned: II intervention or control conditionGiven four risk situations; asked to write down how they would avoid smoking in each situation.II group reported fewer cigarettes per day at 1-mo follow-up, but only among participants with weak/moderate (not strong) habit strength.Reference . Sample . Experimental groups . Implementation intentions intervention(s) . Primary findings . Armitage3090 smokers (ages 18–85)Randomly assigned to II intervention vs control conditionGiven 3 blank lines; instructed to create implementation intentions to help them quit smoking in the next 2 mo.II intervention group more likely to report having quit at 2-mo follow-up.Armitage16193 smokers (ages 16–78)Randomly assigned to an II intervention or to one of three comparison conditionsGiven 20 potentially triggering contexts and 20 responses to avoid smoking; asked to link context to response by drawing a line between the two.II intervention group were more likely to report having quit at 1-mo follow-up than those in all other conditions.Armitage22168 smokers (ages 18–75)Randomly assigned to intervention (II intervention vs control) × certainty condition (“if” vs “when” stems)Linked a column of 20 potentially triggering contexts with 20 responses to avoid smoking by drawing a line between the two. Contexts were preceded by “if” or “when.”Intervention groups more likely to report having quit at 1-mo follow-up than those in the control conditions. No differences found between certainty conditions.Armitage and Arden31350 smokersRandomly assigned to an II intervention or one of two comparison conditionsAsked to write down a detailed plan to help them quit in 1 mo. Told to pay attention to the situations in which they would implement the plans.II intervention group were more likely to have quit at 2-mo follow-up than comparison groups.Brown et al.18159 smokers in cessation program (ages 18–83)Randomly assigned to weekly self-incentivizing II intervention, monthly incentivizing II intervention, or comparison groupAsked to choose 1 of 20 self-incentives as a reward for not smoking for a full week (or for full month).Intervention groups (vs comparison) more likely to have quit at 3- and 6-mo follow-up. No differences between the weekly and monthly groups.Conner and Higgins211551 adolescents (ages 11–12 at baseline)Randomly assigned to II intervention or 1 of 3 comparison conditions. Completed every 4 mo for 2 yrSelected 1 of 5 possible responses to decline a cigarette, or wrote in own response. Also indicated where and when they would not smoke by checking boxes.II intervention group less likely to be smokers (self-report and objective measure) at 48-mo follow-up when compared to the comparison conditions.DeStasio et al.3262 smokers (ages 25–66)Randomly assigned to II intervention + self-authored motivational text messages for 30 days, self-authored text messages only, or active control groupInstructed to identify an obstacle (“if”) and pair it with a specific plan (“then”) to help them quit smoking. Examples were provided.No between-group differences in change in cigarettes/day after intervention (~30 days post-baseline). Participants in self-authorship + II condition had larger reduction in CO2 than those in the active control condition.Higgins and Conner20347 children (ages 11–12)Randomly assigned to II intervention or control conditionSelected 1 of 5 possible responses to decline a cigarette, or wrote in own response. Indicated where and when they would not smoke by checking boxes.No differences in cessation at 8-week follow-up.Matcham et al.17160 smokers newly referred to cessation program (ages 19–80)Randomly assigned to 1 of 4 groups: standard care alone, standard care + effectiveness booklet, standard care + II, or standard care + effectiveness booklet and IIInstructed to read the following statement three times and repeat it silently one time: “As soon as I start to doubt about attending my appointments with the NHS SSSs, I will ignore that feeling and tell myself that this is perfectly normal to feel that way!”No differences in cessation at 4-week follow-up.Moody et al.3336 smokers (ages 18 and 65)All completed 4 different interventions during 4 different sessions (order randomly assigned): control task, II intervention; monetary incentives; II intervention + monetary incentivesGiven 7 context cues and 11 responses to avoid smoking and linked the two. Picked three of the pairs and wrote the full sentences word-for-word.II intervention had no effect on amount of time smokers resisted smoking during a 2-h period.Van Osch et al.231,566 smokers in cessation program (ages 18–81)Randomly assigned to II intervention or control conditionChose 3 context cues from a list of 14; wrote in their plan to avoid smoking in that situation. Full intentions were flashed on the screen.No significant differences in smoking abstinence at 1- or 7-mo follow-up.Webb et al.,34 Study 2172 high school smokers (ages 17–21)Randomly assigned: II intervention or control conditionGiven four risk situations; asked to write down how they would avoid smoking in each situation.II group reported fewer cigarettes per day at 1-mo follow-up, but only among participants with weak/moderate (not strong) habit strength.

II = implementation intention.

Bias Assessment

Cochrane Review criteria was used to assess the risk of bias in experiments.35 Studies were rated on six evidence-based domains: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, and selective reporting.35 Random sequence allocation refers to the process used to assign participants to intervention versus control groups, and allocation concealment occurs when the study personnel does not know the randomization sequence before participants are accrued. Blinding of participants and personnel refers to whether the participants or personnel could have known the condition to which participants had been assigned. Blinding of outcome assessment reflects whether outcome measurement could have been affected by the knowledge of the intervention that was received. Incomplete outcome data occur when analyses do not account for participant attrition. Selective reporting refers to the omittance of results that were not statistically significant. We chose not to report on a seventh domain, “other bias,” as we did not find important biases that did not fall under the other six categories. For each study, each of these components was rated as either “low risk,” “high risk,” or “unclear” if the manuscript did not provide sufficient information for making a decision. Similar to the process used for data extraction, at least two of the three authors assessed each article for bias. Then authors met to compare and discuss assessments. Overall agreement across the six domains for the 12 studies was 87.5%, and discrepancies were resolved through discussion.

Results Study Characteristics

Of the 12 randomized controlled trials included in the review, eight were conducted in the United Kingdom, two in the United States, one in the Netherlands, and one study did not specify the location. All studies but one18 were longitudinal. Those that were longitudinal tested the effect of implementation intentions at least 1 month after the intervention was administered. Seven of the 12 studies (58.3%) reported a beneficial effect of an II intervention on smoking outcomes, and five studies (41.7%) reported null results. No studies reported a negative effect of II intervention. See Table 1 for data extraction and Supplementary Material for a more detailed version.

Ten studies (83.3%) tested II interventions as a cessation tool. That is, these studies focused on reducing or eliminating smoking in a population of current smokers. Two of the studies20,21 (16.7%) tested the effect of II interventions as a tool to prevent smoking in a population of nonsmoking adolescents. Although the goal for all interventions was abstention from cigarettes, this goal is decidedly more difficult for current smokers. Unlike nonsmokers, who may smoke only socially or in response to peer pressure (as may be the case with adolescents), current smokers must override their current habits and fight physiological addiction to resist a cigarette. Because the difficulty of the intended behavior is so different for these two populations, studies assessing the effectiveness of II interventions as a cessation tool and II interventions as a prevention tool are presented separately.

Bias Assessment

Table 2 summarizes the risk of bias for the articles included in this review. Studies showed relatively low risk of bias across the six criteria. However, many studies did not include enough information to make informed judgments on all criteria.

Table 2. Open in new tab

Quality Assessment

Source . Random sequence allocation . Allocation concealment . Blinding of participants and personnel . Blinding of outcome assessment . Complete outcome data . Avoidance of selective reporting . Armitage30✔?✔✔✔?Armitage16✔?✔✔✔?Armitage22✔?✔✔✔?Armitage and Arden31✔?✔✔✔✔Brown et al.18✔?✔✔✔?Conner and Higgins21??✕✔✔✔DeStasio et al.32???✔✕?Higgins and Conner20???✔✔?Matcham et al.17✕✕✕✔✔?Moody et al.33???✔✔?Van Osch et al.23✕✕✕✕✔?Webb et al.,34 Study 2✔?✔✔✔?Source . Random sequence allocation . Allocation concealment . Blinding of participants and personnel . Blinding of outcome assessment . Complete outcome data . Avoidance of selective reporting . Armitage30✔?✔✔✔?Armitage16✔?✔✔✔?Armitage22✔?✔✔✔?Armitage and Arden31✔?✔✔✔✔Brown et al.18✔?✔✔✔?Conner and Higgins21??✕✔✔✔DeStasio et al.32???✔✕?Higgins and Conner20???✔✔?Matcham et al.17✕✕✕✔✔?Moody et al.33???✔✔?Van Osch et al.23✕✕✕✕✔?Webb et al.,34 Study 2✔?✔✔✔?

A check-mark indicates “low risk,” an X-mark indicates “high risk,” and a question mark indicates “unclear.”

Table 2. Open in new tab

Quality Assessment

Source . Random sequence allocation . Allocation concealment . Blinding of participants and personnel . Blinding of outcome assessment . Complete outcome data . Avoidance of selective reporting . Armitage30✔?✔✔✔?Armitage16✔?✔✔✔?Armitage22✔?✔✔✔?Armitage and Arden31✔?✔✔✔✔Brown et al.18✔?✔✔✔?Conner and Higgins21??✕✔✔✔DeStasio et al.32???✔✕?Higgins and Conner20???✔✔?Matcham et al.17✕✕✕✔✔?Moody et al.33???✔✔?Van Osch et al.23✕✕✕✕✔?Webb et al.,34 Study 2✔?✔✔✔?Source . Random sequence allocation . Allocation concealment . Blinding of participants and personnel . Blinding of outcome assessment . Complete outcome data . Avoidance of selective reporting . Armitage30✔?✔✔✔?Armitage16✔?✔✔✔?Armitage22✔?✔✔✔?Armitage and Arden31✔?✔✔✔✔Brown et al.18✔?✔✔✔?Conner and Higgins21??✕✔✔✔DeStasio et al.32???✔✕?Higgins and Conner20???✔✔?Matcham et al.17✕✕✕✔✔?Moody et al.33???✔✔?Van Osch et al.23✕✕✕✕✔?Webb et al.,34 Study 2✔?✔✔✔?

A check-mark indicates “low risk,” an X-mark indicates “high risk,” and a question mark indicates “unclear.”

Implementation Intentions as a Cessation Tool

Of the 10 studies that tested an II intervention as a smoking cessation tool, five studies16,18,22,30,31 (50%) reported a positive effect of the intervention on cessation at long-term follow-up (ie, at least 1 month). An additional study (Webb et al.34; 10%) found a positive effect of the intervention on cessation at 1-month follow-up among only a subset of participants (ie, those who scored lower on nicotine dependence).

Four of the 10 studies (40%) failed to find a beneficial effect of the intervention. Matcham et al.17 and DeStasio et al.32 reported no effect of the intervention on cessation at 1-month follow-up. Van Osch et al.23 similarly found no effect of the intervention at 1- or 7-month follow-up using intention-to-treat analysis; however, the intervention group was more likely to have quit at 7-month follow-up in respondents-only analysis. The fourth study by Moody et al.33 tested smoking abstention during a 2-hour lab session, rather than long-term cessation, and found no effect of an II intervention on smokers’ ability to avoid smoking during this 2-hour period.

II Intervention Methodology

Methods of the II interventions for cessation varied widely among studies, and this variability may have influenced the effectiveness of the intervention. The following describes the methods used in the II interventions for smoking cessation and reports effectiveness as a function of methodology used.

Most (80%) of the II interventions for smoking cessation explicitly asked participants to pair a context in which they might be tempted to smoke with a response that would help them avoid smoking. The studies varied in whether the contexts and/or intended responses were provided by the experimenter or generated by the participant.

In three studies,16,22,33 experimenters provided a list of possible contexts and a list of intended responses, asking participants to form implementation intentions by drawing lines between the two. Although two of these studies16,22 reported that participants who completed this intervention were more likely to quit at long-term follow-up, one study33 failed to find an effect of this intervention on abstention from cigarettes during a 2-hour session.

Two of the studies23,34 testing effects of II interventions as a smoking cessation tool (20%) provided participants with a list of possible contexts in which they would be tempted to smoke, but asked them to generate their own unique intended response for each one. Webb et al. found that this intervention effectively reduced the number of cigarettes smoked per day among adolescent smokers at 1-month follow-up. However, Van Osch et al.23 failed to find an effect of this intervention on smokers’ long-term abstinence.

Three studies30–32 (30%) asked participants to generate both their own context cue and their intended response to avoid a cigarette. Armitage and Arden31 gave particularly vague instructions, only asking participants to create a stop-smoking plan and to “pay attention to the situations” in which they would implement it. Both studies by Armitage et al. were effective in reducing smoking at follow-up, but the intervention in DeStasio et al.32 was not.

The interventions of these final two cessation studies (2/10, 20%) differed from the others in that the intended responses were not strategies to avoid a cigarette. Instead, Brown et al.18 provided participants with the cue “if I am able to refrain from smoking” and asked them to choose among 20 self-incentives they could use as rewards for not smoking. The intervention had significant effects on follow-up abstinence.18 Matcham et al.17 asked participants to set implementation intentions to remain in the program when they felt like leaving. Smokers were given a complete implementation intention that they were asked to read and say aloud: “As soon as I start to doubt about attending my appointments with the NHS SSSs, I will ignore that feeling and tell myself that this is perfectly normal to feel that way!” The intervention had no effect on 1-month abstinence rates.17

The Role of Baseline Smoking Characteristics

Smokers vary in level of addiction (eg, habit strength or cigarettes per day) and their motivation to quit smoking. These factors often determine whether a cessation intervention will be effective.36,37 For instance, some interventions may successfully facilitate cessation among those who are preparing to quit, but have no impact on those who lack interest in quitting. Only 3 of the 10 studies (30%) that examined II intentions as a cessation tool tested whether baseline smoking characteristics (ie, baseline level of addiction or readiness to quit) influenced the effectiveness of the intervention.

One study34 reported that baseline habit strength (operationalized by a combined measure of the Fagerström Test for Nicotine Dependence,38 number of months as a smoker, and number of attempts to quit smoking) moderated the impact of the II intervention on smoking cessation. The II intervention was successful for smokers with low and moderate, but not high, habit strength. No other studies tested whether smoking behaviors (cigarettes per day, habit strength, etc.) moderated the impact of the II intervention.

Two studies considered readiness to quit at baseline. Armitage and Arden31 tested whether baseline readiness to quit moderated the impact of the II intervention. There was a statistically significant three-way interaction (experimental group × time × stage of change), such that the II intervention was more strongly related to quitting at follow-up (2 months later) for participants who were in the preparation stage (ie, planning to quit vs contemplation stage) at baseline. Armitage30 used a different strategy to test the importance of readiness to quit at baseline. In this study, a MANCOVA was used to compare the baseline smoking characteristics of participants in the II intervention who quit smoking during the study to those in the same condition who did not quit. Participants who had quit smoking at follow-up reported greater baseline intentions to quit, fewer temptations to smoke, less nicotine dependence, greater perceived control, and stronger subjective norms than those who had not quit.30 The remaining studies that used II interventions as a cessation tool did not assess smokers’ readiness to quit at baseline.16–18,22,23,33,34 However, two studies used only smokers who had self-enrolled in a stop-smoking program, suggesting some initiative to quit,18,23 and one study only used smokers who reported being ready to quit.32 Of these three, Brown et al.18 found an effect of the intervention, but Van Osch et al.23 and DeStasio et al.32 found no effect of the intervention using intention-to-treat analysis.

The Role of Intervention Adherence

To evaluate the effectiveness of the interventions, it is important to consider the extent to which participants adhered to the instructions. Two of the 10 (20%) studies that tested the effectiveness of II interventions as a cessation tool examined the role of intervention adherence. Van Osch et al.23 conducted a “per-protocol” analysis to test the influence of implementation intentions using only those participants in the intervention group who completed the intervention properly (ie, formulated three coping plans with responses that were both viable and could facilitate smoking cessation). Whereas van Osch et al.’s23 initial intention-to-treat analysis reported no effect of the II intervention on smoking cessation, the per-protocol analysis showed that participants who correctly completed the intervention were more likely to have reported continuous abstinence at 7-month follow-up than those in the control condition.

In the other study that considered adherence, Armitage30 noted that all participants in the II intervention condition who quit at long-term follow-up wrote their intentions down, whereas 6 (15.8%) of the 38 nonquitters in the same condition did not write anything down (ie, did not adhere to the intervention). However, removing the six smokers who failed to adhere to the intervention did not change the strength of the already significant difference between the II intervention group and the control group.30 No other studies reported intervention adherence or whether it affected the results.

Implementation Intentions as a Prevention Tool

Two of the 12 studies (16.7%) tested II interventions as a tool to prevent smoking among youth.20,21 Both studies tested whether an II intervention could prevent smoking initiation (or continued smoking) among a group of primarily nonsmoking adolescents (ie, no participants were smoking at least once a week). Conner and Higgins21 found lower rates of smoking initiation in the II intervention group 4 years later, whereas Higgins and Conner20 reported no effect of the intervention on the likelihood of smoking initiation at the 2-month follow-up.

Both studies used a task that was slightly different from traditional II interventions, as they were not formed by linking a single “if” statement with a single “then” statement. Participants were asked to indicate what they planned to say if they were offered a cigarette or if they felt tempted to smoke by checking off options from a list of predetermined responses or by writing in their own response. They were then asked to check off the places where they would resist smoking (eg, at school) and were asked to sign a statement saying that they could resist smoking for an entire year.20,21 Conner and Higgins’ protocol had participants in the II intention group repeat this intervention six additional times over the course of the next 2 years. Neither of these studies assessed adherence to the intervention. Furthermore, because the sample was primarily nonsmoking, neither tested whether baseline smoking behavior or cognitions impacted the results.

Discussion

This systematic review synthesizes the literature that has tested the effectiveness of II interventions to prevent smoking. Taken together, the 10 experiments testing this intervention as a cessation tool suggest that it may be an effective strategy to help current smokers quit. About half of the studies demonstrated that smokers who completed the intervention had reduced smoking behavior at least 1 month later. These effects are impressive considering the brevity of the exercise. Although the methodology of the intervention varied, taken together, these studies demonstrate that probing individuals to consider triggering contexts and creating plans to avoid smoking can help facilitate cessation goals.

Only two studies examined II interventions as a prevention tool, so one avenue for future research is to test further whether these interventions will be useful for efforts to prevent smoking initiation among youth. A recent study by Conner et al. reported the results of a brief, biannual II intervention for smoking prevention among adolescents, but did not meet inclusion criteria for the current review. The study did not isolate the effect of the II intervention, instead pairing it with an antismoking message, which led to greater smoking abstinence at 4-year follow-up (vs control condition).39 The same intervention weakened the influence between e-cigarette smoking and later cigarette smoking,40 an important finding to highlight given the recent rise in e-cigarette use.41 Antismoking messages may be critical to the effectiveness of II prevention interventions for youth. In general, II interventions tend to be more effective when goal motivation is stronger,42 and adolescents may not have the same level of motivation to avoid cigarettes that most current smokers do.3 Future research should consider testing whether II interventions for smoking prevention are more effective (or only effective) when paired with antismoking or other motivational messages.

Importance of Baseline Smoking Characteristics

Surprisingly few studies examined baseline characteristics as a potential moderator of intervention effects. However, this review suggests that II cessation interventions are more likely to facilitate abstinence among smokers who are less addicted to nicotine34 and more ready to quit,30,31 underlining the importance of goal motivation for II interventions.42 These findings are consistent with evidence that other cessation interventions (eg, counseling) are more effective for those preparing to quit in the next 6 months (vs not ready to quit)43 and for lighter smokers (vs heavier).44 If, as the preliminary evidence in this review suggests, II interventions are more beneficial when smokers are more ready to quit and less dependent on nicotine, then II interventions may be most aptly incorporated into later stages of the quitting process, when participants have already made some progress in their cessation efforts.

One important point to note in the review of II cessation interventions is that all five studies that reported a positive effect of the intervention for the entire sample (ie, a positive main effect) were conducted by the same group of colleagues (ie, Armitage et al.). It is unlikely that the effectiveness of these studies was due to unique methodology used in that lab, as the intervention procedure varied across their studies. Given the preliminary evidence that the intervention is only beneficial for smokers who are more ready quit, perhaps this research lab is drawing from population of smokers who are more amenable to quitting than other labs are. Indeed, the only other group of researchers who reported a positive effect of this intervention on smoking cessation found this effect exclusively among participants with lower nicotine dependence.34

Lack of Consensus Regarding Methodology

This review illuminates the lack of consensus among researchers as to what constitutes an II intervention. Several of the intervention methodologies did not follow the traditional definition of an II intention, in which individuals prepare a response for when they encounter a specific environment or experience a specific internal state (eg, have a certain thought).45 Three studies17,20,21 administered an II intervention did not incorporate the hallmark of an implementation intention: the process of actively linking a single cue with an intended response. This active linkage of a specific cue with a single behavior is what distinguishes implementation intentions from other highly specific plans.46 Furthermore, the intervention by Brown et al.18 asked participants to set an intention to reward themselves if/when they did not smoke a cigarette. This strategy differs slightly from the traditional definition of implementation intentions, which serve a larger goal by facilitating goal-congruent behavior,45 not by administering a reward for this behavior.

Overall, the review indicates that one way to advance the field is to come to a clearer consensus on what methodology warrants a label of an “implementation intentions intervention.” It would be helpful for future research to identify the specific features necessary for such interventions to be successful. However, despite the methodological discrepancies, these interventions do show promise. At this point, it appears that any intervention that encourages smokers to anticipate triggering contexts and identify preventive responses to such contexts will be useful.

Future Directions

In the future, experimental studies testing an II cessation intervention should examine how baseline smoking characteristics such as nicotine dependence, readiness to quit, and number of years smoked may influence intervention effectiveness. Researchers may also consider testing whether smokers who are less ready to quit create lower quality implementation intentions and whether this can explain (ie, mediate) the relatively weaker effect of II interventions within this population. For example, these smokers may be less capable of identifying effective strategies to resist cravings or of anticipating triggering contexts. Future studies testing II interventions for youth smoking prevention should examine whether previous smoking initiation alters the effectiveness of the intervention. Neither of the two studies in this review tested past smoking initiation as a moderator. However, the intervention was effective in Conner and Higgins’  21 sample, in which 4.0% of adolescents had initiated smoking, but not in Higgins and Conner’s20 sample, in which 23.9% of participants had initiated smoking. With only two studies, we cannot draw meaningful conclusions, but it is possible that II interventions are more effective for adolescents who have never smoked before.

The extent to which other participant characteristics influence the effectiveness of the intervention is also important to consider. For instance, smokers with higher levels of psychological distress may benefit less from tobacco treatment programs.47 Trials testing II interventions for smoking prevention should also consider the importance of participant characteristics. Previous reviews have shown that the effectiveness of youth smoking prevention programs depends on the psychological distress and cultural background of the population.48

Another next step for future research is to compare the effectiveness of implementation intentions that are experimenter generated versus participant generated.45 The current review included both types of interventions, but there were too few studies to draw meaningful conclusions about the relative effectiveness of these strategies. Asking smokers to generate their own intentions is appealing because it allows them to personalize the intention and prepare responses to their unique triggers. They can also draw on strategies that have been helpful to them in the past or upon the unique resources they have available (eg, call a friend who has also recently quit smoking). However, studies of II interventions in other domains show that participants struggle to form quality (ie, specific) implementation intentions, and that poorer quality implementation intentions are less likely to be enacted.45,49 Indeed, Van Osch et al.,23 which found a null effect of the intervention, also reported that over 20% of the sample failed to complete the self-generated II intervention properly. Per-protocol analysis revealed the intervention was effective for the roughly 80% of participants who created quality implementation intentions.

Whereas most studies in this review tested the influence of a single-dose II intervention, future research should test whether multiple doses (ie, repeated) of the interventions provide added benefit, allowing researchers to detect the presence of a potential dose–response relationship. Conner and Higgins (the only intervention with multiple sessions) performed post hoc analyses to determine whether the number of II interventions attended was associated with smoking behavior, but found no significant relationship.21 Last, randomized controlled trials for smoking cessation should test the effect of combining II interventions with other evidence-based cessation strategies, such as group counseling or pharmacological interventions like nicotine replacement therapy. II interventions are simple, adaptable, and cost-effective enough to be paired with almost any treatment program.

Recommendations for Antismoking Efforts

Findings from this systematic review show that II intentions may be an effective approach to aid smoking cessation efforts, especially among those with some readiness to quit. More research is needed to ascertain the specific populations for whom II interventions will be most effective at achieving abstinence and the optimal method for developing implementation intentions. However, it is evident that anticipating cues or triggers to smoke when establishing strategies to avoid smoking can facilitate a larger goal of cessation. Because II interventions are brief and essentially free, incorporating them into larger programs presents low cost with potentially high reward.

Supplementary Material

A Contributorship Form detailing each author’s specific involvement with this content, as well as any supplementary data, are available online at https://academic.oup.com/ntr.

Funding

None declared.

Declaration of Interests

None declared.

References1.

Centers for Disease Control and Prevention. Health Effects of Cigarette Smoking. 2018. https://www.cdc.gov/tobacco/data_statistics/fact_sheets/health_effects/effects_cig_smoking/index.htm.2.

American Cancer Society. Deaths. 2018. https://tobaccoatlas.org/topic/deaths.3.

Centers for Disease Control and Prevention. Morbidity and Mortality Weekly Report: Quitting Smoking Among Adults: United States, 2001–2010. 2011. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6044a2.htm?s_cid=mm6044a2_w.4.

Pontieri FE, Tanda G, Orzi F, Di Chiara G.

Effects of nicotine on the nucleus accumbens and similarity to those of addictive drugs. Nature. 1996;382(6588):255–257.

Google Scholar

CrossrefSearch ADS

WorldCat

 5.

Chaiton M, Diemert L, Cohen JE, et al. 

Estimating the number of quit attempts it takes to quit smoking successfully in a longitudinal cohort of smokers. BMJ Open. 2016;6(6):e011045.

Google Scholar

CrossrefSearch ADS

WorldCat

 6.

Sheeran P, Webb TL.

The intention-behavior gap. Soc Personal Psychol Compass. 2016;10(9):503–518.

Google Scholar

CrossrefSearch ADS

WorldCat

 7.

Gollwitzer PM.

Implementation intentions: strong effects of simple plans. Am Psychol. 1999;54(7):493–503.

Google Scholar

CrossrefSearch ADS

WorldCat

 8.

Webb TL, Sheeran P.

Mechanisms of implementation intention effects: the role of goal intentions, self-efficacy, and accessibility of plan components. Br J Soc Psychol. 2008;47(Pt 3):373–395.

Google Scholar

OpenURL Placeholder Text

WorldCat

 9.

Chapman J, Armitage CJ, Norman P.

Comparing implementation intention interventions in relation to young adults’ intake of fruit and vegetables. Psychol Health. 2009;24(3):317–332.

Google Scholar

CrossrefSearch ADS

WorldCat

 10.

Adriaanse MA, de Ridder DT, de Wit JB.

Finding the critical cue: implementation intentions to change one’s diet work best when tailored to personally relevant reasons for unhealthy eating. Pers Soc Psychol Bull. 2009;35(1):60–71.

Google Scholar

CrossrefSearch ADS

WorldCat

 11.

Gollwitzer PM, Sheeran P.

Implementation intentions and goal achievement: a meta-analysis of effects and processes. Adv Exp Soc Psychol. 2006;38(2006):69–119.

Google Scholar

OpenURL Placeholder Text

WorldCat

 12.

Locke EA, Latham GP.

New directions in goal-setting theory new directions in goal-setting theory. Curr Dir Psychol Sci. 2006;15(5):265–268.

Google Scholar

CrossrefSearch ADS

WorldCat

 13.

Gollwitzer PM, Fujita K, Oettingen G.

Planning and the implementation of goals. In: Baumesiter RF, ed. Handbook of Self-regulation: Research, Theory, and Applications. New York: Guilford Press; 2004:211–228.

Google Scholar

Google Preview

OpenURL Placeholder Text

WorldCat

COPAC 14.

Brandstätter V, Lengfelder A, Gollwitzer PM.

Implementation intentions and efficient action initiation. J Pers Soc Psychol. 2001;81(5):946–960.

Google Scholar

CrossrefSearch ADS

WorldCat

 15.

Cohen AL, Gollwitzer PM.

The cost of remembering to remember: cognitive load and implementation intentions influence ongoing task performance. In: Kliegel M, ed. Prospective Memory: Cognitive, Neuroscience, Developmental, and Applied Perspectives. New York: Erlbaum; 2008:367–390.

Google Scholar

Google Preview

OpenURL Placeholder Text

WorldCat

COPAC 16.

Armitage CJ.

A Volitional help sheet to encourage smoking cessation: a randomized exploratory trial. Heal Psychol. 2008;27(5):557–566.

Google Scholar

CrossrefSearch ADS

WorldCat

 17.

Matcham F, McNally L, Vogt F.

A pilot randomized controlled trial to increase smoking cessation by maintaining National Health Service Stop Smoking Service attendance. Br J Health Psychol. 2014;19(4):795–809.

Google Scholar

CrossrefSearch ADS

WorldCat

 18.

Brown EM, Smith DM, Armitage CJ.

Self-incentives uniquely boost cessation in community-based stop smoking programs: randomized controlled trial. Ann Behav Med. 2018;53(5):442–452.

Google Scholar

CrossrefSearch ADS

WorldCat

 19.

Krukowski RA, Solomon LJ, Naud S.

Triggers of heavier and lighter cigarette smoking in college students. J Behav Med. 2005;28(4):335–345.

Google Scholar

CrossrefSearch ADS

WorldCat

 20.

Higgins A, Conner M.

Understanding adolescent smoking: the role of the theory of planned behaviour and implementation intentions. Psychol Health Med. 2003;8(2):173–186.

Google Scholar

CrossrefSearch ADS

WorldCat

 21.

Conner M, Higgins AR.

Long-term effects of implementation intentions on prevention of smoking uptake among adolescents: a cluster randomized controlled trial. Health Psychol. 2010;29(5):529–538.

Google Scholar

CrossrefSearch ADS

WorldCat

 22.

Armitage CJ.

Evidence that implementation intentions can overcome the effects of smoking habits. Health Psychol. 2016;35(9):935–943.

Google Scholar

CrossrefSearch ADS

WorldCat

 23.

Van Osch L, Lechner L, Reubsaet A, Wigger S, de Vries H.

Relapse prevention in a national smoking cessation contest: effects of coping planning. Br J Health Psychol. 2008;13(Pt 3):525–535.

Google Scholar

OpenURL Placeholder Text

WorldCat

 24.

Valery L, Anke O, Inge KK, Johannes B.

Effectiveness of smoking cessation interventions among adults: a systematic review of reviews. Eur J Cancer Prev. 2008;17(6):535–544.

Google Scholar

OpenURL Placeholder Text

WorldCat

 25.

Smit ES, de Vries H, Hoving C.

Effectiveness of a Web-based multiple tailored smoking cessation program: a randomized controlled trial among Dutch adult smokers. J Med Internet Res. 2012;14(3):e82.

Google Scholar

CrossrefSearch ADS

WorldCat

 26.

Brendryen H, Drozd F, Kraft P.

A digital smoking cessation program delivered through internet and cell phone without nicotine replacement (happy ending): randomized controlled trial. J Med Internet Res. 2008;10(5):e51.

Google Scholar

CrossrefSearch ADS

WorldCat

 27.

McWilliams L, Bellhouse S, Yorke J, Lloyd K, Armitage CJ.

Beyond “planning”: a meta-analysis of implementation intentions to support smoking cessation. Health Psychol. 2023;38(12):1059–1068.

Google Scholar

CrossrefSearch ADS

WorldCat

 28.

Malaguti A, Ciocanel O, Sani F, Dillon JF, Eriksen A, Power K.

Effectiveness of the use of implementation intentions on reduction of substance use: a meta-analysis. Drug Alcohol Depend. 2023;214:108120.

Google Scholar

CrossrefSearch ADS

WorldCat

 29.

Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group.

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151(4):264–249, W64.

Google Scholar

CrossrefSearch ADS

WorldCat

 30.

Armitage CJ.

Efficacy of a brief worksite intervention to reduce smoking: the roles of behavioral and implementation intentions. J Occup Health Psychol. 2007;12(4):376–390.

Google Scholar

CrossrefSearch ADS

WorldCat

 31.

Armitage CJ, Arden MA.

How useful are the stages of change for targeting interventions? Randomized test of a brief intervention to reduce smoking. Health Psychol. 2008;27(6):789–798.

Google Scholar

CrossrefSearch ADS

WorldCat

 32.

DeStasio KL, Hill AP, Berkman ET.

Efficacy of an SMS-based smoking intervention using message self-authorship: a pilot study. J Smok Cessat. 2018;13(1):55–58.

Google Scholar

CrossrefSearch ADS

WorldCat

 33.

Moody LN, Poe LM, Bickel WK.

Toward a laboratory model for psychotherapeutic treatment screening: implementation intentions and incentives for abstinence in an analog of smoking relapse. Exp Clin Psychopharmacol. 2017;25(5):373–379.

Google Scholar

CrossrefSearch ADS

WorldCat

 34.

Webb TL, Sheeran P, Luszczynska A.

Planning to break unwanted habits: habit strength moderates implementation intention effects on behaviour change. Br J Soc Psychol. 2009;48(Pt 3):507–523.

Google Scholar

OpenURL Placeholder Text

WorldCat

 35.

The Cochrane Collaboration. Cochrane Risk of Bias Tools for Randomized Trials. 2011. https://methods.cochrane.org/bias/resources/cochrane-risk-bias-tool.36.

Dino G, Kamal K, Horn K, Kalsekar I, Fernandes A.

Stage of change and smoking cessation outcomes among adolescents. Addict Behav. 2004;29(5):935–940.

Google Scholar

CrossrefSearch ADS

WorldCat

 37.

Hettema JE, Hendricks PS.

Motivational interviewing for smoking cessation: a meta-analytic review. J Consult Clin Psychol. 2010;78(6):868–884.

Google Scholar

CrossrefSearch ADS

WorldCat

 38.

Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO.

The Fagerström Test for Nicotine Dependence: a revision of the Fagerström Tolerance Questionnaire. Br J Addict. 1991;86(9):1119–1127.

Google Scholar

CrossrefSearch ADS

WorldCat

 39.

Conner M, Grogan S, West R, et al. 

Effectiveness and cost-effectiveness of repeated implementation intention formation on adolescent smoking initiation: a cluster randomized controlled trial. J Consult Clin Psychol. 2023;87(5):422–432.

Google Scholar

CrossrefSearch ADS

WorldCat

 40.

Conner M, Grogan S, Simms-Ellis R, et al. 

Evidence that an intervention weakens the relationship between adolescent electronic cigarette use and tobacco smoking: a 24-month prospective study. Tob Control. 2023;29(4):425–431.

Google Scholar

OpenURL Placeholder Text

WorldCat

 41.

Fadus MC, Smith TT, Squeglia LM.

The rise of e-cigarettes, pod mod devices, and JUUL among youth: factors influencing use, health implications, and downstream effects. Drug Alcohol Depend. 2023;201:85–93.

Google Scholar

CrossrefSearch ADS

WorldCat

 42.

Prestwich A, Kellar I.

How can the impact of implementation intentions as a behaviour change intervention be improved? Eur J Appl Psychol. 2014;64(1):35–41.

Google Scholar

CrossrefSearch ADS

WorldCat

 43.

Ali A, Kaplan CM, Derefinko KJ, Klesges RC.

Smoking cessation for smokers not ready to quit: meta-analysis and cost-effectiveness analysis. Am J Prev Med. 2018;55(2):253–262.

Google Scholar

CrossrefSearch ADS

WorldCat

 44.

Gariti P, Lynch K, Alterman A, Kampman K, Xie H, Varillo K.

Comparing smoking treatment programs for lighter smokers with and without a history of heavier smoking. J Subst Abuse Treat. 2009;37(3):247–255.

Google Scholar

CrossrefSearch ADS

WorldCat

 45.

Prestwich A, Sheeran P, Webb TL, Gollwitzer PM.

Implementation intentions. Predict Heal Behav. 2015;3:321–357.

Google Scholar

OpenURL Placeholder Text

WorldCat

 46.

Webb TL, Sheeran P.

How do implementation intentions promote goal attainment? A test of component processes. J Exp Soc Psychol. 2007;43(2):295–302.

Google Scholar

CrossrefSearch ADS

WorldCat

 47.

Lawrence D, Williams JM.

Trends in smoking rates by level of psychological distress – time series analysis of US National Health Interview Survey Data 1997–2014. Nicotine Tob Res. 2015;18(6):1463–1470.

Google Scholar

CrossrefSearch ADS

WorldCat

 48.

Johnson CA, Cen S, Gallaher P, et al. 

Why smoking prevention programs sometimes fail. Does effectiveness depend on sociocultural context and individual characteristics? Cancer Epidemiol Biomarkers Prev. 2007;16(6):1043–1049.

Google Scholar

CrossrefSearch ADS

WorldCat

 49.

De Vet E, Oenema A, Brug J.

More or better: do the number and specificity of implementation intentions matter in increasing physical activity? Psychol Sport Exerc. 2011;12(4):471–477.

Google Scholar

CrossrefSearch ADS

WorldCat

  © The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)