Abstract
Background:
Research has suggested that smokers who quit smoking and continue to identify themselves as a smoker versus a non-smoker are at greater risk of relapse. This study examines the relationship between post-quit smoker identities and relapse risk of former smokers in Australia and the UK comparing those who still identified as a smoker with firm choice to no longer smoke versus those not expressing a firm choice. Cross-country differences were examined.
Methods:
Data analysed came from 544 former smokers (quit 1 month or more) who participated in the Australian and UK Waves 9 (2013) and 10 (2014) of the International Tobacco Control (ITC) surveys. Post-quit smoker identities were assessed at baseline and smoking relapse at follow-up.
Results:
Baseline self-reported smoker identity independently predicted smoking relapse at 12-month follow-up (p<.01). Compared with the subgroup who identified themselves as smokers trying to quit, those who identified themselves as smokers who had chosen to no longer smoke (OR=.01, 95% CI=.01-.25, p<.001), ex-smokers (OR=.05, CI=.01-.25, p<.001) or non-smokers (OR=.07, CI=.02-.37, p<.001) were less likely to relapse at follow-up. No cross-country differences were found.
Conclusions:
Following quitting, smokers who maintained a smoker identity with a firm choice to no longer smoke or adopted a non-smoker or ex-smoker identity were less likely to relapse than those who failed to do so, suggesting that a clear rule/commitment to not smoke and/or a shift to a non-smoking identity may be protective of relapse.
Keywords: Smoker Identity, Ex-Smokers, Relapse, Smoking Cessation, Tobacco Smoking
INTRODUCTION
Most quit attempts by smokers end in relapse back to smoking. Relapse rates for unaided and aided attempts to quit smoking are high, particularly within the first few weeks of abstinence (1). Of smokers who reach 4-week abstinence, approximately 70% relapse within a year (2, 3). Additionally, upwards of thirty quit attempts required before a smoker successfully quits smoking (4). By identifying the challenges and supporting factors for successful abstinence, the rate of long-term abstinence may be improved (5). One key factor that has been hypothesized as contributing to smoking persistence is smoking identity (6). Understanding how smoker identity can contribute to the success/failure of behaviour change during a quit attempt could help improve interventions to prevent relapse during this vulnerable period (7).
Comprehensive theories of health behaviour change such as PRIME theory (8) and CEOS theory (9) both postulate an important role for self-identity in influencing behaviour. PRIME theory defines identity as the mental representations that we form of ourselves and the thoughts and feelings we attach to these (8). Identity is an important source of our motives, providing us with the ability for self-regulation, boundaries and stability of behaviour. Identity is composed of labels (i.e., the categories we use to define ourselves), attributes (i.e., the characteristics that arise from labels) and rules (i.e., the behaviours we permit ourselves). According to Tombor et al. (10), it is through these elements that a person’s identity directs behaviour and generates motives that may override an impulse.
CEOS theory focuses more on the role of self-identity as a manifestation of people’s values and expectations and it is this which influences the value we give specific behaviours (9). Both theories predict that changing an established identity to one where the act of smoking and its associated experiences are less valued should reduce the desire to return to an old behaviour and thus provide a valuable focus for behaviour change intervention (8, 9). Research has supported the influential role a person’s identity plays in their actions and attitudes towards smoking. A positive image of oneself as a smoker predicts continuation of smoking and reduces susceptibility to take on evidence of health risks for smoking behaviour (11, 12). Cessation attempts are less desirable and less likely to have occurred in smokers who maintain a positive smoker identity (13, 14). Research has shown that a non-smoker identity is strongly associated with smoking cessation (15).
During smoking cessation, there can be a shift from a smoker identity to a non-smoker identity (12, 16). Where this happens, both theories predict that the adoption of a ‘non-smoker’ identity should provide an important protection against smoking relapse. Identifying as a non-smoker would allow for a revision of one’s values (9) along with motives and evaluation (8) allowing for rules to be generated to override motives associated with smoking behaviour.
Failure to adopt a non-smoker identity has been linked to relapse. Following a quit attempt, many smokers report developing a sense of lost social identity (17). This disparity between current behaviour and identity as a ‘smoker’ has been highlighted as resulting in relapse in order to realign identity with behavioural outcomes. Further, research has indicated that in the short-term, smokers who continue to retain smoking behaviour as an important part of their identity are less likely to remain abstinent after three months than those who adopt an abstainer self-concept (18).
Despite the pivotal role that identity plays in smoking behaviour, only a handful of studies have explored the potential long-term protective benefits for relapse prevention that the adoption of a non-smoker identity could provide (10, 19). Research reviewing the effectiveness of behaviour change techniques (BCT) in English stop smoking services (19) found that BCT focused on strengthening an ex-smoker identity were associated with higher quit rates at 1-month post treatment. Another English study examined non-smoker identity beyond 1-month post-quitting and relationship to smoking abstinence and found that majority of participants who had quit smoking identified themselves as non-smokers at the 3-month and 6-month follow up assessments, and those who did so were more likely to have remained abstinent (10). Taken together, both of these studies provide some support for the role of identity in promoting continued and sustained positive behaviour change, with strong suggestion that non-smoker identity can have a protective effect against smoking relapse.
A major challenge of interpreting the findings of past research is the lack of a consistent definition and/or operationalization of identity construct. It is unclear whether an ex-smoker identity differs from a non-smoker identity as the terms are often used interchangeably. Our research aimed to address this shortcoming to further understand the relationship between post-quit smoker identities and subsequent risk of relapse. The sample was taken from a non-treatment seeking smoker population who participated in a longitudinal cohort-based survey allowing for assessment of relapse past the initial stage of cessation and ensuring results will be generalizable to a larger population. Unlike past research, the survey question used four instead of two categories to assess smoking identity, allowing a more nuanced measurement of identity transition. Whilst research supports a post-quit transition of a smoker identity to non-smoker identity (16), a significant minority of long-term ex-smokers have been found to retain both a smoker identity and residual attraction towards smoking (7). Research has found smokers who retained a residual attraction to smoking could be more at risk of relapse (20, 21). Meijer, Vangeli, Gebhardt and van Laar (22) conducted a qualitative, longitudinal investigation that found those who identified as a ‘smoker who does not smoke’ found abstinence from smoking more challenging to maintain than those who identified as a non-smoker. Continued residual attraction to smoking and maintenance of a smoker identity in some former smokers suggests it is not a straightforward shift in identity from a smoker to non-smoker, but a more nuanced shift of attraction and identification throughout the abstinence process (23). To account for this, smoker identity was distinguished into those who saw themselves as smokers trying to quit smoking with no clear rule versus those who had set a clear rule for stopping smoking. A distinction between non-smoker versus ex-smoker identity was also made, the latter being those who still held some residual image of themselves as a smoker versus the former who did not want to be associated with past smoking identity and saw themselves now completely as a non-smoker.
Past research has established abstinence self-efficacy, post-quit urges to smoke, enjoyment of smoking and perceived importance of smoking as strong key predictors of both attempts at quitting and relapse to smoking in the short-term (21, 24, 25). Our study included these variables in analysis to further examine whether the predictive effect of post-quit smoker identities is over and above that of these other predictors of relapse.
Based on the theories, existing research in this area and our conceptualisation of smoking-related identity post quitting, it was hypothesised that following smoking cessation, smokers who perceived themselves as either a smoker who had chosen to no longer smoke, an ex-smoker or a non-smoker would be less likely to relapse than those who perceived themselves as a smoker trying to quit. Further, it was hypothesized that smokers who adopted a non-smoker identity following smoking cessation would be less likely to relapse compared to both those who saw themselves as smokers who had chosen to no longer smoke and as ex-smokers. No prediction was made for the latter two groups. As a secondary aim, differences in identity-abstinence relationships were explored across UK and Australia.
METHODS
Sample and Data Collection Procedures
Data come from the International Tobacco Control Four Country (ITC 4C) Survey, a longitudinal cohort study of around 2000 adult smokers each from Australia, the US, the UK, and Canada who were followed up approximately annually that aimed to systematically evaluate the key policies from the WHO Framework Convention on Tobacco Control. Details of the study methodology have been reported elsewhere (26). Briefly, eligible participants were those aged 18+, had smoked over 100 cigarettes in their lifetime and smoked at least once in the past 30 days. Those who had quit smoking were retained in the study for subsequent waves and those lost to attrition were replaced using a replenishment sample to maintain sample size. Survey responses were collected via web or phone questionnaires.
Probability sampling methods were used to recruit participants into the ITC surveys. Each country was stratified by geographic region and random digit dialling methods were used to select eligible households. For households where more than one respondent met eligibility criteria, the next birthday method was used for participant selection.
Participants completed an initial 10-minute recruitment survey to establish consent and eligibility. Those who agreed to complete a 35-minute survey were provided with a small financial compensation.
For our study purposes, the analytic sample consisted of ex-smokers who participated in the 2013 Australian and UK ITC survey (Wave 9) and provided outcome data in the 2014 survey (Wave 10). The US and Canada cohorts were excluded from analysis because the 2014 survey was not conducted in these two countries to provide outcome data.
Ethics approval was obtained from the Office of Research Ethics at the University of Waterloo, and ethics committees in the UK (King’s College London) and Australia (Cancer Council Victoria and Deakin University).
Measures
Smoker identity:
Assessed in 2013 (Wave 9) using the question ‘How would you describe yourself now’ with response options ‘A smoker trying to quit’, ‘A smoker who has chosen to no longer smoke’, ‘A non-smoker’ or an ‘ex-smoker’. This question was only asked of ex-smokers who reported quitting for at least 1 month based on the expectation that any identity shift would have been more stable at this point (27).
Relapse:
Ex-smokers at the 2013 survey were asked at follow-up survey in 2014 about their smoking status using the question ‘Are you back smoking cigarettes or are you still stopped?’ with response options ‘Back smoking’ indicating had relapsed (Relapse=Yes) or ‘Still stopped’ indicating had not relapsed (Relapse=No).
Control variables assessed at the 2013 survey included sociodemographic such as gender, age, education, and income, along with quit duration (1–6 months, 7–12 months, >12 months) and other smoking-related variables known to predict relapse such as post-quit urges to smoke (How often do you get strong urges to smoke? 1. Never, 2. Less than daily, 3. Daily, 4. Several times a day, 5. Hourly or more often), abstinence self-efficacy (How likely are you that you will succeed in quitting smoking for good at this attempt? 1. Not at all sure, 2. Slightly sure, 3. Moderately sure, 4. Very sure, 5. Extremely sure), enjoyment of smoking (You enjoyed smoking) and perceived importance of smoking to one’s life (Smoking is an important part of your life), both rated on a 5-point agree-disagree scale. Education and income were recoded into low, medium and high to equate them across countries. Data on survey mode (phone or internet) and wave participants were recruited into the study were collected.
Data Analysis
The data were analysed using SPSS version 26. Pearson’s χ2 was used to assess the association between categorical variables and to test for differences in baseline sociodemographic and smoking related characteristics by country between participants retained in the sample at follow-up versus those lost to attrition. Binomial logistic regression analyses were conducted, first bivariately (Model 1) to assess the unadjusted association between the independent variable post-quit smoker identity and the dependent variable relapse status (Yes/No) at follow-up, then multivariately to control for potential confounders (Model 2) such as sociodemographic characteristics and survey response characteristics and finally, to determine whether the effect of smoker identity was over and above that of a set of smoking-related variables known to predict relapse (Model 3). Odds ratio (OR) and 95% confidence intervals (CI) were computed for each association. To determine whether the identity-relapse relationship differed by country, an identity by country interaction term was tested in the logistic regression model.
RESULTS
Sample Characteristics
Table 1 shows sociodemographic characteristics of the sample at baseline for Australia (n=304) and UK (n=240). Overall the pattern of sociodemographic variables was comparable across countries with the majority of participants being over 40-years old (70.8%), of low education (52.5%) and survey completion via the internet (72.4%).
Table 1.
Baseline sample Characteristics by Country for those retained vs those lost to attrition.
| Australia | UK | All | Test of country difference in retained sample - chi-square value (p-value) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Variables | Retain (n=304) | Lost (n=58) | p | Retain (n=240) | Lost (n=46) | p | Retain (n=544) | Lost (n=104) | p | |
| Gender(%) | .908 | .466 | .568 | 0.13 (.717) | ||||||
| Female | 54.3 | 53.4 | 55.8 | 50.0 | 55.0 | 51.9 | ||||
| Male | 45.7 | 46.6 | 44.2 | 50.0 | 45.0 | 48.1 | ||||
| Age (%) | .189 | .322 | .070 | 8.86 (.031) | ||||||
| 18-24 | 6.9 | 5.2 | 2.9 | 4.3 | 5.1 | 4.8 | ||||
| 25-39 | 25.3 | 36.2 | 22.5 | 23.9 | 24.1 | 30.8 | ||||
| 40-54 | 44.4 | 31.0 | 42.1 | 28.3 | 43.4 | 29.8 | ||||
| 55+ | 23.4 | 27.6 | 32.5 | 43.5 | 27.4 | 34.6 | ||||
| Income (%) | .182 | .110 | .225 | 12.27 (.007) | ||||||
| Low | 19.7 | 24.1 | 29.2 | 21.7 | 23.9 | 23.1 | ||||
| Moderate | 23.7 | 34.5 | 28.3 | 30.4 | 25.7 | 32.7 | ||||
| High | 48.0 | 36.2 | 34.2 | 28.3 | 41.9 | 32.7 | ||||
| No answer | 8.6 | 5.2 | 8.3 | 19.6 | 8.5 | 11.5 | ||||
| Education (%) | .730 | .050 | .109 | 0.78 (.676) | ||||||
| Low | 53.0 | 58.6 | 51.9 | 73.9 | 52.5 | 65.4 | ||||
| Moderate | 23.7 | 20.7 | 26.8 | 15.2 | 25.0 | 18.3 | ||||
| High | 23.4 | 20.7 | 21.3 | 10.9 | 22.5 | 16.3 | ||||
| Quit Duration (%) | .000 | .278 | .011 | 1.01 (.604) | ||||||
| 1-6 months | 11.8 | 29.3 | 13.8 | 15.2 | 12.7 | 23.1 | ||||
| 7-12 months | 7.6 | 17.2 | 9.2 | 2.2 | 8.3 | 10.6 | ||||
| >12 month | 80.6 | 53.4 | 77.1 | 82.6 | 79.0 | 66.3 | ||||
| Smoker-Identity (%) | .965 | .717 | .813 | 3.09 (.377) | ||||||
| A smoker trying to quit | 2.3 | 3.4 | 2.9 | 4.3 | 2.6 | 3.8 | ||||
| A smoker who has chosen to no longer smoke | 25.0 | 24.1 | 22.1 | 23.9 | 23.7 | 24.0 | ||||
| A non-smoker | 29.6 | 29.3 | 25.0 | 30.4 | 27.6 | 29.8 | ||||
| An ex-smoker | 43.1 | 43.1 | 50.0 | 41.3 | 46.1 | 42.3 | ||||
| Wave 9 Survey Mode (%) | .000 | .000 | .000 | 6.14 (.013) | ||||||
| Telephone | 23.4 | 55.2 | 32.9 | 60.9 | 27.6 | 57.7 | ||||
| Internet | 76.6 | 44.8 | 67.1 | 39.1 | 72.4 | 42.3 | ||||
| Wave Recruited into the study (%) | .041 | .158 | .096 | 42.84 (.000) | ||||||
| Wave 1 (2002) | 34.5 | 24.1 | 36.7 | 39.1 | 35.5 | 30.8 | ||||
| Wave 2 (2003) | 4.6 | 8.6 | 3.3 | 4.3 | 4.0 | 6.7 | ||||
| Wave 3 (2004) | 11.2 | 8.6 | 15.8 | 4.3 | 13.2 | 6.7 | ||||
| Wave 4 (2006) | 6.9 | 8.6 | 8.3 | 10.9 | 7.5 | 9.6 | ||||
| Wave 5 (2007) | 18.4 | 8.6 | 12.1 | 17.4 | 15.6 | 12.5 | ||||
| Wave 6 (2008) | 12.8 | 13.8 | 13.8 | 21.7 | 13.2 | 17.3 | ||||
| Wave 7 (2009) | 2.3 | 6.9 | 10.0 | 2.2 | 5.7 | 4.8 | ||||
| Wave 8 (2011) | 6.3 | 12.1 | 0.0 | 0.0 | 3.5 | 6.7 | ||||
| Wave 8.5 (2012) | 3.0 | 8.6 | -^ | - | 1.7 | 4.8 | ||||
Note:
No UK survey conducted in 2012
At a country level the distribution of gender and education did not significantly differ across Australia and the UK. However, there were small cross-country differences with more participants from Australia than the UK aged under 40 (32.2% vs 25.4% in the UK), of a higher income (48% vs 34.2% in the UK) and survey completion via the internet (76.6% vs 67.1% in the UK).
Sample Retained versus Lost to Attrition
Table 1 also presents characteristics of participants lost to attrition from Wave 9 (2012) to Wave 10 (2013) by country and overall (n=104). In Australia only, individuals quit for 1-6 months (p<.001) recruited more recently into the study (p<.05) were more likely to have been lost to attrition than retained. In both Australia and the UK, participants who completed the survey via telephone were more likely to be lost to attrition than those completed via the internet (p<.001). Gender, age, income, education and smoker-identity did not differ between those lost to attrition versus those retained for Australia and the UK.
Association between Smoker Identity and Relapse status
Table 2 reports results of the binomial logistic regression analyses of bivariate and multivariate associations between reported smoker identity and relapse status (Yes/No). Participants who described themselves as ‘A smoker trying to quit’ at baseline (Wave 9) had the highest rates of relapse (71.4%) at follow-up survey (Wave 10), followed by those who labelled themselves as smoker who has chosen to no longer smoke (12.4%), non-smokers (8%) and the lowest among those who labelled themselves as ex-smokers (7.2%). The bivariate model (Model 1) revealed that smoker identity was a significant predictor of smoking relapse (p<.001).
Table 2.
Logistic regression analyses for prospective association between Smoker Identity at Wave 9 and relapse to smoking (Yes vs. No) at Wave 10 for Australia and the United Kingdom.
| Predictors | n | % Relapse | Model 1 OR (95% CI) |
Model 2 OR (95% CI) |
Model 3 OR (95% CI) |
|---|---|---|---|---|---|
| Smoker-identity | |||||
| A smoker trying to quit | 14 | 71.4 | ref | ref | ref |
| Smoker who has chosen to no longer smoke | 126 | 12.4 | .05 (.02-.19)*** | 0.05 (.01-.25)*** | 0.08 (.02-.41)** |
| Non-Smoker | 150 | 8.0 | .04 (.01-.13)*** | 0.07 (.02-.37)*** | 0.14 (.03-.76)* |
| Ex-Smoker | 251 | 7.2 | .03 (.01-.11)*** | 0.05 (.01-.25)*** | 0.08 (.02-.43)** |
| Country | |||||
| Australia | 302 | 10.8 | 1.02 (.50-2.05) | 0.98(.48-2.02) | |
| United Kingdom | 239 | 8.8 | ref | ref | |
| Gender | |||||
| Female | 297 | 10.4 | ref | ref | |
| Male | 244 | 10.2 | 0.74 (.36-1.50) | 0.89 (.42-1.89) | |
| Age | |||||
| 18-24 | 28 | 10.7 | ref | ref | |
| 25-39 | 130 | 13.0 | 1.45 (.28-7.63) | 1.78 (.34-9.21) | |
| 40-54 | 234 | 11.4 | 1.45 (.29-7.32) | 1.38 (.27-6.97) | |
| 55+ | 149 | 6.0 | 0.58 (.09-3.67) | 0.60 (.10-3.82) | |
| Income | |||||
| Low | 130 | 7.7 | ref | ref | |
| Moderate | 140 | 12.1 | 1.27 (.45-3.55) | 1.32 (.46-3.80) | |
| High | 225 | 10.5 | 2.08 (.27-2.18) | 0.70 (.24-2.00) | |
| No Answer | 46 | 10.9 | 2.08 (.52-8.30) | 2.32 (.50-10.9) | |
| Education | |||||
| Low | 285 | 9.1 | ref | ref | |
| Moderate | 135 | 11.0 | 0.80 (.34-1.87) | 0.76 (.31-1.88) | |
| High | 121 | 12.3 | 1.23 (.49-3.11) | 1.22 (.48-3.11) | |
| Quit Duration | |||||
| Quit 1-6 months | 69 | 6.7 | ref | ref | |
| Quit 7-12 months | 44 | 35.6 | 0.89 (.37-2.15) | 1.40 (.54-3.58) | |
| Quit > 12 months | 428 | 3.3 | 0.07 (.03-0.16)*** | 0.09 (.04-0.23)*** | |
| Survey Mode | |||||
| Telephone | 150 | 6.7 | ref | ref | |
| Internet | 391 | 11.7 | 1.96 (.79-4.88) | 2.59 (.95-7.06) | |
| Wave of recruitment | 541 | 10.3 | 1.15 (.99-1.33) | 1.13 (.97-1.31) | |
| Post-quit urges to smoke | 530 | - | 1.30 (.84-2.00) | ||
| Abstinence Self-efficacy | 530 | - | 0.69 (.48-1.01)* | ||
| Enjoyment of smoking | 530 | - | 0.57 (.17-1.92) | ||
| Perceived importance of smoking to one’s life | 530 | - | 0.56 (.25-1.26) |
Note: OR= odds ratio; CI=confidence interval; ref= reference group; Model 1 unadjusted OR vs Model 2 OR adjusted for sociodemographic, quit duration, survey mode and wave of recruitment vs Model 3 OR also adjusted for other predictors of relapse;
p< .05
p<.01
p<.001
The multivariate model (Model 2) revealed that after adjusting for potential confounders, smoker identity remained a significant predictor of subsequent smoking relapse (p<.002). Compared to the group who labelled themselves as smokers trying to quit smoking, those who identified themselves as a smoker who has chosen to no longer smoke (OR=.01, 95% CI .01-.25, p<.001), a non-smoker (OR=.07, 95% CI= .02-.37, p<.001) and an ex-smoker (OR=.05, 95% CI .01-.25, p<.001) were all less likely to subsequently relapse back to smoking. No other covariates were significant predictors of relapse except for quit duration at baseline (p<.001). Further, the effect of smoker identity (p<.05) remained significant over and above that of several known predictors of relapse (Model 3); post-quit urges to smoke (p=.209), self-efficacy (p=.041), enjoyment of smoking (p=.864) and importance of smoking to life (p=.634)
Post-hoc Pairwise Comparison
Table 3 displays the results of post-hoc analyses conducted to compare differences in relapse rate between all smoker identity categories. Each category was modelled as the reference group. Relapse rate of the group describing themselves as smokers trying to quit (p<.001) differed significantly from the other three groups but the latter 3 groups did not differ significantly from each other in relapse rate.
Table 3.
Pairwise comparisons of smoker-identity subgroups
| Predictors | n | % Relapse | Group 2 as reference OR (95% CI) |
Group 3 as reference OR (95% CI) |
Group 4 as reference OR (95% CI) |
|---|---|---|---|---|---|
| Smoker-identity | |||||
| Group 1:A smoker trying to quit | 14 | 71.4 | 19.49 (4.04-93.95)*** | 13.46 (2.73-66.39)*** | 18.37 (4.01-84.27)*** |
| Group 2:A smoker who has chosen to no longer smoke | 126 | 12.4 | ref | .69 (.26-1.85) | .94 (.39-2.24) |
| Group 3:A non-Smoker | 150 | 8.0 | 1.45 (.54-3.87) | ref | 1.37 (.57-3.27) |
| Group 4:An ex-Smoker | 251 | 7.2 | 1.06 (.45-2.52) | .73 (.31-1.76) | ref |
Note: OR = odds ratio adjusted for other variables in the model; CI = confidence interval;
p<.001; ref = reference group
Country Differences
Finally, no significant country differences were found for the association between post-quit smoker identity and relapse (p=.090).
DISCUSSION
The present study examined the association between smoker identity and risk of relapse among adult ex-smokers in Australia and the UK. Confirming our hypothesis, smoker identity significantly predicted smoking relapse, even after controlling for sociodemographic variables, quit duration, survey mode and year of recruitment. Former smokers who identified themselves as a smoker who was trying to quit had the highest rates of relapse and were significantly more likely to relapse when compared to those who identified as either a smoker who had chosen to no longer smoke, a non-smoker or an ex-smoker.
Contrary to the hypothesis, risk of relapse was not significantly different between subgroups identifying as either a smoker who had chosen to no longer smoke, a non-smoker or an ex-smoker although the percent relapsed among the smoker subgroup was somewhat higher than that of the non-smoker and ex-smoker subgroups. Also, of note is that the identity of a smoker was the most influential predictor of relapse, over and above other known predictors, such as abstinence self-efficacy which was also found to be significantly associated with relapse risk. The predictive relationship between smoker identity and risk of relapse did not significantly differ by country.
Consistent with past research (10, 18), results show that smoker identity is significantly associated with outcome of a quit attempt. This extends on findings from Tombor et al. (14) that the establishment of a non-smoker identity following a recent quit attempt was associated with successful smoking abstinence. While reasons for this association were not explored, it is consistent with the theorized proposal that formation of a smoker identity no longer associated with smoking provides a basis for long-term behaviour change through establishment of absolute non-smoking rules (8, 9). Extending on research which found an association between smoker identity and relapse in the early periods of quitting (10), our results suggest that post-quit smoker identity continues to play an important role for long-term relapse (i.e., beyond 12 months). However, it may have been the implicit commitment to not smoking again that is more important given the low relapse rate in the group who still identified as smokers but were committed to not smoking again. This suggestion is supported by research highlighting the commitment to quit smoking as a key predictor of smoking relapse (28, 29). The absence of direct measurement of level of commitment limits the conclusions that can be drawn, but future research could seek to further understand commitment as a function of identity and the potential relapse protection it offers.
Smoker identity has been recognised as more complex than a binary smoker vs. non-smoker construct (6) and this study attempted to expand on previous research by capturing smoker identity in more detail. A key finding was that those who were not as committed to a non-smoker identity, labelling themselves as a smoker trying to quit, were most likely to relapse. Tombor et al (6) suggested the degree to which a specific smoker identity is internalised drives motivation to engage or refrain from smoking. The label of ‘a smoker who is trying to quit’ acknowledges that the individual is a smoker refraining from a behaviour to which they still closely identify. The degree of commitment to quitting smoking does not reflect that of an individual who labels themselves as a non-smoker, dissociating from smoking behaviour completely.
The results suggest the way former smokers define their identity can impact the success of quit attempts. PRIME theory encapsulates this as rules undertaken by a smoker (8) and resulting motives that drive behaviour. Rules defined by attempting not to smoke may not provide high enough motivation levels to resist smoking in all circumstances. However, those with rules that define no smoking behaviour at all, boundaries are clearly established and power to prevent smoking relapse is motivated. Identification as a smoker trying to quit may form a label that is less committed to cessation and an absence of rules providing motivation to prevent relapse.
Past research has found that individuals who identify as a ‘smoker who does not smoke’ find quitting to be challenging and that some element of non-smoking needs to be incorporated into identity to reach stable abstinence (30). However, our finding seems to contradict this given the low relapse rate observed among former smokers who described themselves as a smoker but committed to not smoking again which suggests that identity label is less important than level of commitment to a non-smoking lifestyle and having the non-smoking rules established in maintaining abstinence. Nevertheless, the important role of identity self-label cannot be entirely ruled out since an alternative explanation might be that this subgroup of former smokers who still described themselves as smokers represented mainly those in the early stages of quitting who would eventually transition to an ‘ex-’ or ‘non-smoker’ identity after further months of abstinence which would lower their relapse risk. This possibility appears to be supported by the association found of shorter quit duration at baseline for the two ‘smoker’ groups compared to the ‘ex-’ and ‘non-smoker’ groups (see Appendix Table 1A).
Quit duration was identified as an additional independent predictor of relapse in the analysis, supporting research that has established this as a key predictor in success of long-term quit attempts (10, 31). Studies have found that a non-smoker identity is more prevalent and identification with smoking decreases amongst quitters after longer abstinence length (32). Transition from a smoker to a non-smoker identity, and formation of rules that provide motive to successfully abstain from smoking occurs over time (12, 16) and high relapse rates before successful abstinence may be due to these not yet being established. Many determinants of relapse change as a function of length of abstinence (21, 33). Future research should seek to more clearly define how smoker identity changes as a function of length of abstinence and the resulting impact on success of a quit attempt. It may also be useful to explore how self-identity changes in the early days of a quit attempt, we only asked those quit for at least 1 month.
In addition, abstinence self-efficacy was identified as an independent predictor of relapse supporting research which has found individuals with higher confidence in their ability to quit smoking are more likely to achieve a successful quit attempt (21, 34). This could be linked with the conceptualisation of an individual’s post-quit identity and the rules that were established. The commitment an individual has towards the quit attempt and the rules that are established as a result could be directly influenced by their confidence in the success of their quit attempt. Future research should look at how these predictors interact and influence the success of a quit attempt.
The lack of country differences in the predictive relationship between smoker identity and relapse risk could be limited to the two countries studied. It would be interesting to explore it in countries with quite different cultural and tobacco control traditions.
Strengths and Limitations
The strengths of this study include a multi-country comparison, a relatively large sample size and longitudinal cohort design. It is one of the few studies to begin to capture a more nuanced smoking-related identity. Future research should continue to address the complexity of post-quit smoker identity labels and the rules, motivation and commitment that they represent to help gain further insight into their specific contribution in promoting continued and sustained abstinence from smoking. Moreover, such insight may also help inform the development of effective interventions to promote and strengthen identity shift to prevent long-term relapse.
Our study did have several limitations beyond those already mentioned. First, the number of participants who identified as a smoker trying to quit was small, resulting in estimates with a wide confidence interval and also the findings based on odds ratios are only suggestive of the hypothesized associations, thus the findings require replication to confirm the effect is real and not due to something unusual in this small group.
Second, reliance on self-report measures for smoking behaviour may raise concerns about possible bias. However, research has shown that there is generally little bias in self-report of smoking status for large scale population-based survey studies and even intervention studies with no face to face contact (35).
Third, individuals who declined to be surveyed and those lost to attrition may pose a threat to the generalisability of results. The sensitivity analysis conducted found very few baseline differences between those retained and those lost, and these were controlled for in the multivariate analyses.
Conclusion
This study found that smokers who had managed to quit for at least a month rarely describe themselves as a smoker trying to quit. The minority who did so appears to be more at risk of smoking relapse compared to their counterparts who identified themselves as either a smoker who had chosen to no longer smoke, a non-smoker or an ex-smoker. This finding suggests possible value of establishing a post-cessation identity that sets clear rules, reflecting a commitment to non-smoking and/or a shift to a non-smoker identity as ways to protect against relapse. While randomized trials would be required to demonstrate actual causality, there would appear to be no downside of encouraging such identity shifts.
Post-cessation identity as a smoker has been proposed to increase relapse risk
Former smokers who still describe themselves as a smoker trying to quit are rare
Post-cessation identity as a non- or ex-smoker appears to protect against relapse
Rules or commitments to not smoke again appear to also reduce relapse risk
Funding acknowledgements:
The ITC Four Country Survey is supported by multiple grants including R01 CA 100362, P01 CA138389 and P01 CA200512 all funded by the National Cancer Institute of the United States, Canadian Institutes of Health Research (MOP-115016), National Health and Medical Research Council of Australia (APP1005922; APP1106451). GTF was supported by a Senior Investigator Award from the Ontario Institute for Cancer Research (IA-004).
Role of Funding:
The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit for publication.
Appendix
Table 1A.
Association between identity self-labels and quit duration
| Quit duration | |||
|---|---|---|---|
| Quit 1-6m | Quit 7-12m | Quit 12m+ | |
| Identity self-labels: | |||
| A smoker trying to quit (n=14) | 57.1% | 21.4% | 21.4% |
| A smoker who has chosen to no longer smoke (n=129) | 17.8% | 14.7% | 67.4% |
| An ex-smoker (n=150) | 10.0% | 7.2% | 82.9% |
| A non-smoker (n=251) | 8.7% | 3.3% | 88.0% |
Note: Pearson Chi-square (6, N=544)=52.17, p=.000
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Ethics approval: The survey protocols and all materials, including the survey questionnaires, were approved by the Office of Research Ethics at the University of Waterloo, Ontario, Canada (ORE#17469); Research Ethics Office, King’s College London, United Kingdom (IRB PNM/13/14-151); Human Research Ethics, the Cancer Council Victoria, Australia (HREC 0211); and Deakin University, Australia (DUHREC2018-346).
Conflict of Interest
KMC has received payment as a consultant to Pfizer, Inc., for service on an external advisory panel to assess ways to improve smoking cessation delivery in health care settings. KMC also has served as a paid expert witness in litigation filed against cigarette manufacturers. GTF has served as an expert witness on behalf of governments in litigation involving the tobacco industry. All other authors have no conflicts of interest to declare.
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