scholarly journals Predictive Power of Dependence Measures for Quitting Smoking. Findings From the 2016 to 2018 ITC Four Country Smoking and Vaping Surveys

2020 ◽  
Author(s):  
Michael Le Grande ◽  
Ron Borland ◽  
Hua-Hie Yong ◽  
K Michael Cummings ◽  
Ann McNeill ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Explanatory Power ◽  
Short Term ◽  
Logistic Regression Models ◽  
Quit Attempt ◽  
Dependence Measure ◽  
Quit Attempts ◽  
Quitting Smoking ◽  
Dependence Measures ◽  
Variance Explained

Abstract Introduction To test whether urges to smoke and perceived addiction to smoking have independent predictive value for quit attempts and short-term quit success over and above the Heaviness of Smoking Index (HSI). Aims and Methods Data were from the International Tobacco Control Four Country Smoking and Vaping Wave 1 (2016) and Wave 2 (2018) surveys. About 3661 daily smokers (daily vapers excluded) provided data in both waves. A series of multivariable logistic regression models assessed the association of each dependence measure on odds of making a quit attempt and at least 1-month smoking abstinence. Results Of the 3661 participants, 1594 (43.5%) reported a quit attempt. Of those who reported a quit attempt, 546 (34.9%) reported short-term quit success. Fully adjusted models showed that making quit attempts was associated with lower HSI (adjusted odds ratio [aOR] = 0.81, 95% confidence interval [CI] = 0.73 to 0.90, p < .001), stronger urges to smoke (aOR = 1.08, 95% CI = 1.04 to 1.20, p = .002), and higher perceived addiction to smoking (aOR = 0.52, 95% CI = 0.32 to 0.84, p = .008). Lower HSI (aOR = 0.57, 95% CI = 0.40 to 0.87, p < .001), weaker urges to smoke (aOR = 0.85, 95% CI = 0.76 to 0.95, p = .006), and lower perceived addiction to smoking (aOR = 0.55, 95% CI = 0.32 to 0.91, p = .021) were associated with greater odds of short-term quit success. In both cases, overall R2 was around 0.5. Conclusions The two additional dependence measures were complementary to HSI adding explanatory power to smoking cessation models, but variance explained remains small. Implications Strength of urges to smoke and perceived addiction to smoking may significantly improve prediction of cessation attempts and short-term quit success over and above routinely assessed demographic variables and the HSI. Stratification of analyses by age group is recommended because the relationship between dependence measures and outcomes differs significantly for younger (aged 18–39) compared to older (aged older than 40) participants. Even with the addition of these extra measures of dependence, the overall variance explained in predicting smoking cessation outcomes remains very low. These measures can only be thought of as assessing some aspects of dependence. Current understanding of the factors that ultimately determine quit success remains limited.

scholarly journals Assessment of a Personal Interactive Carbon Monoxide Breath Sensor in People Who Smoke Cigarettes: Single-Arm Cohort Study (Preprint)

2020 ◽  
Author(s):  
Jennifer D Marler ◽  
Craig A Fujii ◽  
Kristine S Wong ◽  
Joseph A Galanko ◽  
Daniel J Balbierz ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Smoking Cessation ◽  
Smoking Behavior ◽  
Exhaled Breath ◽  
Disease States ◽  
Quit Attempt ◽  
Quit Attempts ◽  
Motivation To Quit ◽  
Quitting Smoking ◽  
Evidence Based Treatments

BACKGROUND Tobacco use is the leading cause of preventable morbidity and mortality. Existing evidence-based treatments are underutilized and have seen little recent innovation. The success of personal biofeedback interventions in other disease states portends a similar opportunity in smoking cessation. The Pivot Breath Sensor is a personal interactive FDA-cleared (over-the-counter) device that measures carbon monoxide (CO) in exhaled breath, enabling users to link their smoking behavior and CO values, and track their progress in reducing or quitting smoking. OBJECTIVE The objective of this study is to assess the Pivot Breath Sensor in people who smoke cigarettes, evaluating changes in attitudes toward quitting smoking, changes in smoking behavior, and use experience. METHODS US adults (18-80 years of age, ≥10 cigarettes per day [CPD]) were recruited online for this remote 12-week study. Participants completed a screening call, informed consent, and baseline questionnaire, and then were mailed their sensor. Participants were asked to submit 4 or more breath samples per day and complete questionnaires at 1-4, 8, and 12 weeks. Outcomes included attitudes toward quitting smoking (Stage of Change, success to quit, and perceived difficulty of quitting), smoking behavior (quit attempts, CPD reduction, and 7-, 30-day point prevalence abstinence [PPA]), and use experience (impact and learning). RESULTS Participants comprised 234 smokers, mean age 39.9 (SD 11.3) years, 52.6% (123/234) female, mean CPD 20.3 (SD 8.0). The 4- and 12-week questionnaires were completed by 92.3% (216/234) and 91.9% (215/234) of participants, respectively. Concerning attitude outcomes, at baseline, 15.4% (36/234) were seriously thinking of quitting in the next 30 days, increasing to 38.9% (84/216) at 4 weeks and 47.9% (103/215) at 12 weeks (both <i>P</i>&lt;.001). At 12 weeks, motivation to quit was increased in 39.1% (84/215), unchanged in 54.9% (118/215), and decreased in 6.0% (13/215; <i>P</i>&lt;.001). Additional attitudes toward quitting improved from baseline to 12 weeks: success to quit 3.3 versus 5.0 (<i>P</i>&lt;.001) and difficulty of quitting 2.8 versus 4.3 (<i>P</i>&lt;.001). Regarding smoking behavior, at 4 weeks, 28.2% (66/234) had made 1 or more quit attempts (≥1 day of abstinence), increasing to 48.3% (113/234) at 12 weeks. At 4 weeks, 23.1% (54/234) had reduced CPD by 50% or more, increasing to 38.5% (90/234) at 12 weeks. At 12 weeks, CPD decreased by 41.1% from baseline (<i>P</i>&lt;.001), and 7- and 30-day PPA were 12.0% (28/234) and 6.0% (14/234), respectively. Concerning use experience, 75.3% (171/227) reported the sensor increased their motivation to quit. More than 90% (&gt;196/214) indicated the sensor taught them about their CO levels and smoking behavior, and 73.1% (166/227) reported that seeing their CO values made them want to quit smoking. CONCLUSIONS Use of the Pivot Breath Sensor resulted in a significant increase in motivation to quit, a reduction in CPD, and favorable quit attempt rates. These outcomes confer increased likelihood of quitting smoking. Accordingly, the results support a role for biofeedback via personal CO breath sampling in smoking cessation. CLINICALTRIAL ClinicalTrials.gov NCT04133064; https://clinicaltrials.gov/ct2/show/NCT04133064

scholarly journals Does free or lower cost smoking cessation medication stimulate quitting? Findings from the International Tobacco Control (ITC) Netherlands and UK Surveys

2018 ◽  
Vol 28 (Suppl 1) ◽  
pp. s61-s67 ◽  
Author(s):  
Floor A van den Brand ◽  
Gera E Nagelhout ◽  
Karin Hummel ◽  
Marc C Willemsen ◽  
Ann McNeill ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
The Netherlands ◽  
Tobacco Control ◽  
Lower Cost ◽  
Regression Analyses ◽  
Quit Attempt ◽  
Quit Attempts ◽  
Quitting Smoking ◽  
The Uk ◽  
Education Groups

ObjectiveTo investigate whether mentioning free or lower cost smoking cessation medication as a trigger for thinking about quitting is related to higher medication use, more quit attempts and quit success, and whether these associations are modified by education and income.MethodsData were derived from the 2013 and 2014 surveys of the International Tobacco Control Netherlands (n=1164) and UK (n=768) cohort. Logistic regression analyses were used to assess associations between mentioning in 2013 that free/lower cost smoking cessation medication was a trigger for thinking about quitting smoking and the use of medication, quit attempts and smoking cessation in 2014.Results37.0% of smokers in the UK and 24.9% of smokers in the Netherlands mentioned free/lower cost medication as a trigger for thinking about quitting. Smokers who mentioned this trigger were more likely to have used cessation medication during a quit attempt both in the UK (OR=4.19, p<0.001) and in the Netherlands (OR=2.14, p=0.033). The association between mentioning free/lower cost medication as a trigger for thinking about quitting and actual quit attempts was significant in the UK (OR=1.45, p=0.030), but not in the Netherlands (OR=1.10, p=0.587). There was no significant association with quit success. Associations did not differ across income and education groups.ConclusionFree/lower cost smoking cessation medication may increase the use of cessation medication and stimulate quit attempts among smokers with low, moderate and high education and income.

scholarly journals Assessment of a Personal Interactive Carbon Monoxide Breath Sensor in People Who Smoke Cigarettes: Single-Arm Cohort Study

10.2196/22811 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e22811
Author(s):  
Jennifer D Marler ◽  
Craig A Fujii ◽  
Kristine S Wong ◽  
Joseph A Galanko ◽  
Daniel J Balbierz ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Smoking Cessation ◽  
Smoking Behavior ◽  
Exhaled Breath ◽  
Disease States ◽  
Quit Attempt ◽  
Quit Attempts ◽  
Motivation To Quit ◽  
Quitting Smoking ◽  
Evidence Based Treatments

Background Tobacco use is the leading cause of preventable morbidity and mortality. Existing evidence-based treatments are underutilized and have seen little recent innovation. The success of personal biofeedback interventions in other disease states portends a similar opportunity in smoking cessation. The Pivot Breath Sensor is a personal interactive FDA-cleared (over-the-counter) device that measures carbon monoxide (CO) in exhaled breath, enabling users to link their smoking behavior and CO values, and track their progress in reducing or quitting smoking. Objective The objective of this study is to assess the Pivot Breath Sensor in people who smoke cigarettes, evaluating changes in attitudes toward quitting smoking, changes in smoking behavior, and use experience. Methods US adults (18-80 years of age, ≥10 cigarettes per day [CPD]) were recruited online for this remote 12-week study. Participants completed a screening call, informed consent, and baseline questionnaire, and then were mailed their sensor. Participants were asked to submit 4 or more breath samples per day and complete questionnaires at 1-4, 8, and 12 weeks. Outcomes included attitudes toward quitting smoking (Stage of Change, success to quit, and perceived difficulty of quitting), smoking behavior (quit attempts, CPD reduction, and 7-, 30-day point prevalence abstinence [PPA]), and use experience (impact and learning). Results Participants comprised 234 smokers, mean age 39.9 (SD 11.3) years, 52.6% (123/234) female, mean CPD 20.3 (SD 8.0). The 4- and 12-week questionnaires were completed by 92.3% (216/234) and 91.9% (215/234) of participants, respectively. Concerning attitude outcomes, at baseline, 15.4% (36/234) were seriously thinking of quitting in the next 30 days, increasing to 38.9% (84/216) at 4 weeks and 47.9% (103/215) at 12 weeks (both P<.001). At 12 weeks, motivation to quit was increased in 39.1% (84/215), unchanged in 54.9% (118/215), and decreased in 6.0% (13/215; P<.001). Additional attitudes toward quitting improved from baseline to 12 weeks: success to quit 3.3 versus 5.0 (P<.001) and difficulty of quitting 2.8 versus 4.3 (P<.001). Regarding smoking behavior, at 4 weeks, 28.2% (66/234) had made 1 or more quit attempts (≥1 day of abstinence), increasing to 48.3% (113/234) at 12 weeks. At 4 weeks, 23.1% (54/234) had reduced CPD by 50% or more, increasing to 38.5% (90/234) at 12 weeks. At 12 weeks, CPD decreased by 41.1% from baseline (P<.001), and 7- and 30-day PPA were 12.0% (28/234) and 6.0% (14/234), respectively. Concerning use experience, 75.3% (171/227) reported the sensor increased their motivation to quit. More than 90% (>196/214) indicated the sensor taught them about their CO levels and smoking behavior, and 73.1% (166/227) reported that seeing their CO values made them want to quit smoking. Conclusions Use of the Pivot Breath Sensor resulted in a significant increase in motivation to quit, a reduction in CPD, and favorable quit attempt rates. These outcomes confer increased likelihood of quitting smoking. Accordingly, the results support a role for biofeedback via personal CO breath sampling in smoking cessation. Trial Registration ClinicalTrials.gov NCT04133064; https://clinicaltrials.gov/ct2/show/NCT04133064

Facebook Chat Application to Prompt and Assist Smoking Cessation Among Spanish-Speaking Young Adults in South Texas

2021 ◽  
pp. 152483992110262
Author(s):  
Patricia Chalela ◽  
Alfred L. McAlister ◽  
David Akopian ◽  
Edgar Munoz ◽  
Cliff Despres ◽  
...  
Keyword(s):  
Social Media ◽  
Smoking Cessation ◽  
Young Adults ◽  
South Texas ◽  
Spanish Speaking ◽  
Quit Attempt ◽  
Quit Attempts ◽  
Facebook Advertising

Given how smart phones, internet services, and social media have shown great potential for assisting smoking cessation, we constructed a Facebook chat application based on our previous work with SMS texting services. This report summarizes findings from 2,364 Spanish-speaking young adults recruited through Facebook advertising in South Texas during the 2020 New Year holiday season. Among these service users, 926 (39%) were ready to make a quit attempt, and 26 (3.1%) of those users reported that they were tobacco free 1 month later. There were no responses to a chat question survey 72 days after the dates selected for quitting. Although more research with longer follow up is needed, these findings show that social media chat applications may be helpful for at least prompting quit attempts and short-term cessation among young adult Spanish-speaking smokers. There is no evidence of an impact on long-term cessation, and more research is clearly needed.

Balancing Consideration of the Risks and Benefits of E-Cigarettes

2021 ◽  
pp. e1-e12
Author(s):  
David J. K. Balfour ◽  
Neal L. Benowitz ◽  
Suzanne M. Colby ◽  
Dorothy K. Hatsukami ◽  
Harry A. Lando ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Media Coverage ◽  
Attributable Mortality ◽  
Cigarette Use ◽  
The Public ◽  
Health Community ◽  
Smoking Policies ◽  
Quit Attempts ◽  
Quitting Smoking ◽  
Potential Benefits

The topic of e-cigarettes is controversial. Opponents focus on e-cigarettes’ risks for young people, while supporters emphasize the potential for e-cigarettes to assist smokers in quitting smoking. Most US health organizations, media coverage, and policymakers have focused primarily on risks to youths. Because of their messaging, much of the public—including most smokers—now consider e-cigarette use as dangerous as or more dangerous than smoking. By contrast, the National Academies of Science, Engineering, and Medicine concluded that e-cigarette use is likely far less hazardous than smoking. Policies intended to reduce adolescent vaping may also reduce adult smokers’ use of e-cigarettes in quit attempts. Because evidence indicates that e-cigarette use can increase the odds of quitting smoking, many scientists, including this essay’s authors, encourage the health community, media, and policymakers to more carefully weigh vaping’s potential to reduce adult smoking-attributable mortality. We review the health risks of e-cigarette use, the likelihood that vaping increases smoking cessation, concerns about youth vaping, and the need to balance valid concerns about risks to youths with the potential benefits of increasing adult smoking cessation. (Am J Public Health. Published online ahead of print August 19, 2021: e1–e12. https://doi.org/10.2105/AJPH.2021.306416 )

scholarly journals Understanding the Association Between Spontaneous Quit Attempts and Improved Smoking Cessation Success Rates: A Population Survey in England With 6-Month Follow-up

2019 ◽  
Vol 22 (9) ◽  
pp. 1460-1467 ◽  
Author(s):  
Claire Garnett ◽  
Lion Shahab ◽  
Tobias Raupach ◽  
Robert West ◽  
Jamie Brown
Keyword(s):  
Regression Models ◽  
Population Survey ◽  
Adult Population ◽  
Success Rates ◽  
Logistic Regression Models ◽  
The Past ◽  
Quit Attempt ◽  
Quit Attempts ◽  
Adjusted Model

Abstract Introduction Almost half of smoking quit attempts are “spontaneous” (initiated as soon as the decision to quit has been made) and are associated with increased success rates. This study aimed to assess to what extent other factors may account for this association. Methods Data were used from respondents to a survey representative of the adult population in England from 2006 to 2016. We included 2018 respondents who were current smokers at baseline and had attempted to quit between baseline and 6-month follow-up. Logistic regression models assessed the association between quit success and spontaneous quit attempts while adjusting for smoking, sociodemographic, and quit attempt characteristics. Results Spontaneous quit attempts were associated with greater odds of quit success (OR = 1.31, 95% CI = 1.07 to 1.60) but the association was not significant in the fully adjusted model (ORadj = 1.19, 95% CI = 0.95 to 1.49). In this adjusted model, those who attempted to quit without cutting down first (ORadj = 3.08, 95% CI = 2.46 to 3.88) and were male (ORadj = 1.44, 95% CI = 1.16 to 1.80) had greater odds of success; although a greater number of attempts in the past 6 months, stronger urges to smoke (strong vs. none), higher daily cigarette consumption, and lower social grade (E vs. AB) were associated with lower odds of success (ORadj range = 0.32–0.98, p &lt; .030). Quit attempts made without cutting down first were correlated with spontaneous quit attempts (r = .150, p &lt; .001) and appeared to account for the diminished association between spontaneous quitting and success (ORadj = 1.18, 95% CI = 0.96 to 1.46). Conclusions The increased success rate of spontaneous quit attempts appears to be because spontaneous quit attempts are more likely to be made without cutting down first. Implications The apparent benefit of spontaneous over planned quit attempts may be attributable to the former being more likely to involve quitting without cutting down first (ie, abrupt cessation) than cutting down first (ie, gradual cessation) and so this may be a more useful target for advice to improve the chances of successful quitting.

scholarly journals History and Correlates of Smoking Cessation Behaviors Among Smokers With Serious Mental Illness

2019 ◽  
Vol 22 (9) ◽  
pp. 1492-1499 ◽  
Author(s):  
Su Fen Lubitz ◽  
Alex Flitter ◽  
E Paul Wileyto ◽  
Douglas Ziedonis ◽  
Nathaniel Stevens ◽  
...  
Keyword(s):  
Mental Illness ◽  
Carbon Monoxide ◽  
Smoking Cessation ◽  
General Population ◽  
Serious Mental Illness ◽  
Smoking Cessation Counseling ◽  
Smoking Cessation Advice ◽  
Smoking Cessation Treatment ◽  
Quit Attempt ◽  
Quit Attempts

Abstract Introduction Individuals with serious mental illness (SMI) smoke at rates two to three times greater than the general population but are less likely to receive treatment. Increasing our understanding of correlates of smoking cessation behaviors in this group can guide intervention development. Aims and Methods Baseline data from an ongoing trial involving smokers with SMI (N = 482) were used to describe smoking cessation behaviors (ie, quit attempts, quit motivation, and smoking cessation treatment) and correlates of these behaviors (ie, demographics, attitudinal and systems-related variables). Results Forty-three percent of the sample did not report making a quit attempt in the last year, but 44% reported making one to six quit attempts; 43% and 20%, respectively, reported wanting to quit within the next 6 months or the next 30 days. Sixty-one percent used a smoking cessation medication during their quit attempt, while 13% utilized counseling. More quit attempts were associated with lower nicotine dependence and carbon monoxide and greater beliefs about the harms of smoking. Greater quit motivation was associated with lower carbon monoxide, minority race, benefits of cessation counseling, and importance of counseling within the clinic. A greater likelihood of using smoking cessation medications was associated with being female, smoking more cigarettes, and receiving smoking cessation advice. A greater likelihood of using smoking cessation counseling was associated with being male, greater academic achievement, and receiving smoking cessation advice. Conclusions Many smokers with SMI are engaged in efforts to quit smoking. Measures of smoking cessation behavior are associated with tobacco use indicators, beliefs about smoking, race and gender, and receiving cessation advice. Implications Consideration of factors related to cessation behaviors among smokers with SMI continues to be warranted, due to their high smoking rates compared to the general population. Increasing our understanding of these predictive characteristics can help promote higher engagement in evidence-based smoking cessation treatments among this subpopulation.

scholarly journals Impact of the “Stoptober” Smoking Cessation Campaign in England From 2012 to 2017: A Quasiexperimental Repeat Cross-Sectional Study

2019 ◽  
Vol 22 (9) ◽  
pp. 1453-1459 ◽  
Author(s):  
Mirte A G Kuipers ◽  
Robert West ◽  
Emma V Beard ◽  
Jamie Brown
Keyword(s):  
Smoking Cessation ◽  
Cross Sectional Study ◽  
Vulnerable Groups ◽  
Future Research ◽  
Cross Sectional ◽  
Quit Attempt ◽  
Quit Attempts ◽  
The Difference ◽  
Adjusted Logistic Regression

Abstract Introduction Since 2012, England has an annual “Stoptober” campaign for collective smoking cessation. Our aim was to assess (1) overall impact of the Stoptober campaign on quit attempts over its first 6 years, (2) consistency of impact over the campaign years, and (3) the role of the campaign budget. Methods We used data of 51 399 adult smokers and ex-smokers in 132 repeat cross-sectional monthly surveys in England, 2007–2017. In a quasiexperimental design, adjusted logistic regression analyses compared past-month quit attempt rate between (1) October and other months in the year, between 2007–2011 and 2012–2017; (2) October and other months, across years 2012–2017; and (3) October and other months, between high-budget (2012–2015) and low-budget Stoptober campaigns (2016–2017). Bayes factors (BF) differentiated insensitive data and absence of an effect. Results (1) In 2012–2017, quit attempts were more prevalent in October versus other months (odds ratio [OR]: 1.24, 95% confidence interval [CI]: 1.00 to 1.53), whereas similar in 2007–2011 (OR: 0.95, 95% CI: 0.76 to 1.18; BF = 0.2); data were somewhat insensitive but supported this difference (OR: 1.30, 95% CI: 0.97 to 1.75; BF = 2.1). (2) In 2012–2017, quit attempt prevalence ranged from 3.1% to 8.5% in October and 5.0% to 7.3% in other months. The difference between October and other months was large in 2012 (absolute unadjusted difference of 3.3%; OR: 1.92, 95% CI: 1.23 to 2.98) and 2015 (3.1%; OR: 1.84, 95% CI: 1.14 to 2.95), but small in 2013–2014 and 2016–2017 (0.36 &lt; BF &lt; 1.02). (3) Data were somewhat insensitive but supported interaction with campaign budget (OR: 1.50, 95% CI: 0.92 to 2.44; BF = 2.2). Discussion In 2012–2017, there appears to have been an increase in past-month quit attempts during October in England. The increase was inconsistent across Stoptober campaigns and appears to have been greater when the campaign budget was higher. Implications Over the first 6 years of Stoptober campaigns, there appears to have been an overall increase in past-month quit attempts during October in England, and the data imply that a sufficiently high budget contributes to greater impact of the Stoptober campaign. These findings encourage the further spread of the Stoptober campaign to other countries. Future research should clarify how increased quit attempts as a consequence of Stoptober translate into quit success and which of Stoptober’s ingredients were most important in increasing quit attempts, especially among vulnerable groups.

scholarly journals Quitting Without Reporting Having Tried: Findings From a National Survey

2014 ◽  
Vol 10 (2) ◽  
pp. 141-145 ◽  
Author(s):  
Jamie Brown ◽  
Eleni Vangeli ◽  
Jennifer A. Fidler ◽  
Tobias Raupach ◽  
Robert West
Keyword(s):  
National Survey ◽  
Common Reason ◽  
Household Surveys ◽  
The Past ◽  
Quit Attempt ◽  
Quit Attempts ◽  
The Future ◽  
Quitting Smoking ◽  
Nationally Representative ◽  
Do So

Background: It is assumed that smokers rarely quit without ‘attempting’ to do so but the assumption does not appear to have been adequately tested. This study assessed the prevalence of reporting having stopped without reporting a quit attempt and the reasons given for this discrepancy.Methods: Data were collected from ex-smokers who said they had quit within the last 12 months during nationally representative household surveys conducted monthly between 2006–12.Results: Of the 1,892 ex-smokers who said that they had quit within the last 12 months, 13.9% (95%CI = 12.4%–15.5%) reported having made no serious quit attempts in that period. In a sub-group of 24 smokers who were asked why they had reported stopping without also reporting an attempt, nine cited inconsistency over timing; three reported stopping without attempting to do so; four did not consider it an ‘attempt’ because they had succeeded; and six had not ruled out the occasional cigarette in the future.Conclusions: A substantial minority of people who report having stopped in the past year may fail to report a corresponding quit attempt. However, quitting smoking without considering that one has tried appears to be rare. Instead, the most common reason for the discrepancy is inconsistent reporting of the timing of quit attempts.

scholarly journals Difficulties Quitting for Smokers with and without a Respiratory Disease and Use of a Tailored Intervention for Smoking Cessation – A Qualitative Study

2017 ◽  
Vol 13 (2) ◽  
pp. 63-71 ◽  
Author(s):  
Camille Alexis-Garsee ◽  
Hazel Gilbert ◽  
Martha Burton ◽  
Olga van den Akker
Keyword(s):  
Smoking Cessation ◽  
Respiratory Diseases ◽  
Tailored Intervention ◽  
Structured Interviews ◽  
Quit Attempts ◽  
Quitting Smoking ◽  
Impaired Lung Function ◽  
Personal Approach ◽  
Tailored Approach

Introduction: Smokers with respiratory diseases are less likely to quit than those without impaired lung function, yet few studies have investigated the effectiveness of smoking cessation interventions with this population, and none have used a computer-tailored approach.Aims: This paper aims to fill this gap in the literature by exploring smokers’ experiences when trying to quit and their perceptions of a computer-tailored intervention.Methods: Semi-structured interviews were conducted with 26 smokers recruited from six general practises in North London. Thematic analysis was conducted to examine participants’ previous experiences of quitting and their perceptions of receiving personal tailored feedback reports to aid smoking cessation.Results: Participants discussed how their positive smoking experiences coupled with their negative cessation experiences led to conflicts with quitting smoking. Although the computer-tailored intervention was key in prompting quit attempts and participants valued its personal approach; it was not sufficient as a stand-alone intervention.Conclusions: The results highlight the difficulties that smokers experience when quitting and the need for a more personalised stop smoking service in smokers with respiratory diseases. The study also demonstrates the application and potential for computer-tailored intervention as part of a wider programme of long-term smoking cessation.

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