Decrease in resting heart rate measured using smartphone apps to verify abstinence from smoking: an exploratory study

INTRODUCTION: Verifying self-reports of smoking abstinence is challenging in studies that involve remote data collection. Resting heart rate (HR) decreases during smoking abstinence. This study assessed whether a decrease in resting HR measured using freely available smartphone apps could potentially be used to verify smoking abstinence. METHODS: This study involved a repeated measures experimental design, with data collection in natural setting. Participants were 18 adult, daily smokers. They recorded resting HR in beats per minute (bpm) using freely available smartphone apps during five time points (two in the morning and three post-noon) on each of three days. The outcome measure was the mean of the post-noon HR recordings. The experimental condition for each of the three days (counterbalanced order) was: 1) smoking as usual, 2) not smoking without nicotine replacement therapy (NRT), or 3) not smoking but using NRT. Abstinence was verified using expired-air carbon monoxide (CO) concentration. RESULTS: Compared with the smoking as usual condition, mean HR was 13.4 bpm lower (95%CI=5.4-21.4,p=0.001) in the not smoking without NRT condition and 10.4 bpm lower (95%CI=3.1-17.8, p=0.004) in the not smoking with NRT condition. There was no statistically significant difference in HR between the two not smoking conditions (p=0.39). Abstinence during not smoking days without and with NRT was CO-verified in 18/18 and in 16/18 cases, respectively. CONCLUSIONS: Self-recording of resting heart rate in natural setting using smartphone apps shows a reliable decrease in response to smoking abstinence and may provide a basis for remote verification in smoking cessation studies. IMPLICATIONS: Remote verification of self-reported abstinence in smoking cessation studies remains challenging. Smoking abstinence has been shown to decrease resting heart rate under laboratory conditions. This study demonstrated that self-recording using freely available smartphone apps shows reliable decreases in resting heart rate during smoking abstinence and may provide a basis for inexpensive remote verification of smoking abstinence

Changes in Cigarette Smoking and Vaping in Response to the COVID-19 Pandemic in the UK: Findings from Baseline and 12-Month Follow up of HEBECO Study

This study investigated UK adults’ changes in cigarette smoking and vaping during the COVID-19 pandemic and factors associated with any changes. Data were from an online longitudinal study. A self-selected sample (n = 332) of 228 smokers and 155 vapers (51 participants were both smokers and vapers) completed 5 surveys between April 2020 and June 2021. Participants self-reported data on sociodemographics, COVID-19-related, and smoking/vaping characteristics. During the 12 months of observations, among smokers, 45% self-reported a quit attempt (27.5% due to COVID-19-related reasons) since the onset of COVID-19 pandemic and the quit rate was 17.5%. At 12 months, 35.1% of continuing smokers (n = 174) reported smoking less and 37.9% the same, while 27.0% reported an increase in the number of cigarettes smoked/day. Among vapers, 25.0% self-reported a quit attempt (16.1% due to COVID-19-related reasons) and the quit rate was 18.1%. At 12 months, 47.7% of continuing vapers (n = 109) reported no change in the frequency of vaping/hour, while a similar proportion reported vaping less (27.5%) and more (24.8%). Motivation to quit smoking and being younger were associated with making a smoking quit attempt and smoking cessation. Being a cigarette smoker was associated with vaping cessation. Among a self-selected sample, COVID-19 stimulated more interest in reducing or quitting cigarette smoking than vaping

Associations between vaping and Covid-19: Cross-sectional findings from the HEBECO study

AIMS: To explore i) associations between vaping and self-reported diagnosed/suspected Covid-19; ii) changes in vaping since Covid-19 and factors associated with these changes; iii) whether Covid-19 motivated current or recent ex-vapers to quit. METHODS: Cross-sectional online survey of 2791 UK adults recruited 30/04/2020-14/06/2020. Participants self-reported data on sociodemographic characteristics, diagnosed/suspected Covid-19, vaping status, changes in vaping and motivation to quit vaping since Covid-19. RESULTS: There were no differences in diagnosed/suspected Covid-19 between never, current and ex-vapers. Bayes factors indicated there was sufficient evidence to rule out small negative (protective) associations between vaping status and diagnosed/suspected Covid-19. Among current vapers (n = 397), 9.7 % (95 % CI 6.8-12.6 %) self-reported vaping less than usual since Covid-19, 42.0 % (37.2-46.9 %) self-reported vaping more, and 48.3 % (43.4-53.2 %) self-reported no change. In adjusted analyses, vaping less was associated with being female (aOR = 3.40, 95 % CI 1.73-6.71), not living with children (aOR = 4.93, 1.15-21.08) and concurrent smoking (aOR = 8.77, 3.04-25.64), while vaping more was associated with being younger (aOR = 5.26, 1.37-20.0), living alone (aOR = 2.08, 1.14-3.85), and diagnosed/suspected Covid-19 (aOR = 4.72, 2.60-8.62). Of current vapers, 32.2 % (95 % CI 27.5-36.8 %) were motivated to quit vaping since Covid-19, partly motivated by Covid-19, and 21.0 %, (10.5-31.4 %) of recent ex-vapers quit vaping due to Covid-19. CONCLUSIONS: Among UK adults, self-reported diagnosed/suspected Covid-19 was not associated with vaping status. Half of current vapers changed their vaping consumption since Covid-19, with the majority reporting an increase, and a minority was motivated to quit due to Covid-19. REGISTRATION: The analysis plan was pre-registered, and it is available at https://osf.io/6j8z3/

Does addition of craving management tools in a stop smoking app improve quit rates among adult smokers? Results from BupaQuit pragmatic pilot randomised controlled trial

Objectives: Delivery of craving management tools via smartphone applications (apps) may improve smoking cessation rates, but research on such programmes remains limited, especially in real-world settings. This study evaluated the effectiveness of adding craving management tools in a cessation app (BupaQuit). Methods: The study was a two-arm pragmatic pilot parallel randomised controlled trial, comparing a fully-automated BupaQuit app with craving management tool with a control app version without craving management tool. A total of 425 adult UK-based daily smokers were enrolled through open online recruitment (February 2015–March 2016), with no researcher involvement, and individually randomised within the app to the intervention (n = 208) or control (n = 217). The primary outcome was self-reported 14-day continuous abstinence assessed at 4-week follow-up. Secondary outcomes included 6-month point-prevalence and sustained abstinence, and app usage. The primary outcome was assessed with Fisher's exact test using intent to treat with those lost to follow-up counted as smoking. Participants were not reimbursed. Results: Re-contact rates were 50.4% at 4 weeks and 40.2% at 6 months. There was no significant difference between intervention and control arms on the primary outcome (13.5% vs 15.7%; p = 0.58; relative risk = 0.86, 95% confidence interval = 0.54–1.36) or secondary cessation outcomes (6-month point prevalence: 14.4% vs 17.1%, p = 0.51; relative risk = 0.85, 95% confidence interval = 0.54–1.32; 6-month sustained: 11.1% vs 13.4%, p = 0.55; relative risk = 0.83, 95% confidence interval = 0.50–1.38). Bayes factors supported the null hypothesis (B[0, 0, 1.0986] = 0.20). Usage was similar across the conditions (mean/median logins: 9.6/4 vs 10.5/5; time spent: 401.8/202 s vs 325.8/209 s). Conclusions: The addition of craving management tools did not affect cessation, and the limited engagement with the app may have contributed to this

Does addition of craving management tools in a stop smoking app improve quit rates among adult smokers? Results from BupaQuit pragmatic pilot randomised controlled trial

Introduction: Delivery of craving management tools (CMTs) via smartphone applications (apps) may improve smoking cessation rates, but research on such programmes remains limited, especially in real-world settings. This study evaluated the effectiveness of adding CMTs in a cessation app (BupaQuit). / Methods: The study was a two-arm pragmatic pilot parallel randomised controlled trial, comparing a fully-automated BupaQuit app with CMT with a control app version without CMT. A total of 425 adult UK-based daily smokers were enrolled through open online recruitment (February 2015-March 2016), with no researcher involvement, and individually randomised within the app to the intervention (n=208) or control (n=217). The primary outcome was self-reported 14-day continuous abstinence assessed at 4-week follow-up. Secondary outcomes included 6-month point-prevalence and sustained abstinence, and app usage. The primary outcome was assessed with Fisher’s exact test using intent to treat with those lost to follow-up counted as smoking. Participants were not reimbursed. / Results: Re-contact rates were 50.4% at 4 weeks and 40.2% at 6 months. There was no significant difference between intervention and control arms on the primary outcome (13.5% vs 15.7%; p=0.58;RR=0.86, 95% Confidence Interval (CI)=0.54-1.36) or secondary cessation outcomes (6-month point prevalence: 14.4% vs. 17.1%, p=0.51;RR=0.85, 95%CI=0.54-1.32; 6-month sustained: 11.1% vs 13.4%, p=0.55,RR=0.83,95%CI=0.50-1.38). Bayes factors supported the null hypothesis (B[0, 0,1.0986]=.20). Usage was similar across the conditions (mean/median logins: 9.6/4 vs. 10.5/5; time spent: 401.8/202s vs. 325.8/209s). / Conclusions: The addition of craving management tools did not affect cessation, and the limited engagement with the app may have contributed to this

Tobacco dependence treatment for special populations: challenges and opportunities

Although smoking rates have declined in most of the countries in the world, there are population groups within these countries whose smoking rates remain significantly higher than the general population. These ‘‘forgotten groups’’ who have not been receiving the needed attention in tobacco control policies and tobacco cessation efforts include people with serious mental illness, substance use disorders, tuberculosis, people living with human immunodeficiency virus (HIV), lesbian-gaybisexual-transgender-queer people, and pregnant women. A number of steps are needed at the national level in countries where these disparities exist, including modifications to national smoking cessation treatment guidelines that address the special needs of these populations, as well as targeted smoking cessation research, since these populations are often not included in clinical trials. Because of the higher smoking prevalence in these populations, as well as their lower smoking cessation treatment success rates than the general population, more resources are needed if we are to reduce health disparities in these vulnerable populations. Additionally, we believe that more effort should be focused on integrating smoking cessation treatment in the specialized care settings frequented by these subpopulations

Perceived risk factors for severe Covid-19 symptoms and their association with health behaviours: Findings from the HEBECO study

Risk perceptions are important influences on health behaviours. We used descriptive statistics and multivariable logistic regression models to assess cross-sectionally risk perceptions for severe Covid-19 symptoms and their health behaviour correlates among 2206 UK adults from the HEBECO study. The great majority (89-99%) classified age 70+, having comorbidities, being a key worker, overweight, and from an ethnic minority as increasing the risk. People were less sure about alcohol drinking, vaping, and nicotine replacement therapy use (17.4-29.5% responding 'don't know'). Relative to those who did not, those who engaged in the following behaviours had higher odds of classifying these behaviours as (i) decreasing the risk: smoking cigarettes (adjusted odds ratios, aORs, 95% CI = 2.26, 1.39-3.37), and using e-cigarettes (aORs = 5.80, 3.25-10.34); (ii) having no impact: smoking cigarettes (1.98; 1.42-2.76), using e-cigarettes (aORs = 2.63, 1.96-3.50), drinking alcohol (aORs = 1.75, 1.31-2.33); and lower odds of classifying these as increasing the risk: smoking cigarettes (aORs: 0.43, 0.32-0.56), using e-cigarettes (aORs = 0.25, 0.18-0.35). Similarly, eating more fruit and vegetables was associated with classifying unhealthy diet as 'increasing risk' (aOR = 1.37, 1.12-1.69), and exercising more with classifying regular physical activity as 'decreasing risk' (aOR = 2.42, 1.75-3.34). Risk perceptions for severe Covid-19 among UK adults were lower for their own health behaviours, evidencing optimism bias. These risk perceptions may form barriers to changing people's own unhealthy behaviours, make them less responsive to interventions that refer to the risk of Covid-19 as a motivating factor, and exacerbate inequalities in health behaviours and outcomes

"If I'd Known ..." - a Theory-Informed Systematic Analysis of Missed Opportunities in Optimising Use of Nicotine Replacement Therapy and Accessing Relevant Support: a Qualitative Study

PURPOSE: Nicotine replacement therapy (NRT) is often used suboptimally by smokers. Previous research has focused on cognitions and attitudes as potential reasons. This study drew on theoretical frameworks of behaviour to comprehensively explore smokers' NRT use to identify new intervention targets. METHODS: Semi-structured face-to-face interviews were conducted with 16 adult UK-based smokers and ex-smokers who used NRT in recent quit attempts (mean (SD) age = 34.9(10.3); 82.3% women). The COM-B (capability, opportunity, motivation, behaviour) model and the theoretical domains framework informed the interviews and analyses. Data were analysed in NVivo 11. RESULTS: Two related behaviours were identified relevant to NRT use: use of NRT per se and engaging with information and support with NRT use. A meta-theme of "missed opportunity" identified instances when smokers did not or could not engage in these behaviours. For use of NRT per se, these included limited knowledge, poor technique of use, low motivation to optimise use, and lack of role models. For engaging with information and support, they included low awareness of optimal use techniques, selective information-seeking, low expectations, limited exposure to guidelines, deficient advice from healthcare professionals, and suboptimal product display. Prior suboptimal experience tended to negatively affect subsequent use and views. Participants were interested in accessible and comprehensive guidelines on NRT and its use. CONCLUSIONS: There appear to be important missed opportunities for optimal use of NRT both in terms of use itself and engagement with information on optimal use. These missed opportunities arise from a range of capability, motivational, and opportunity-related factors

Perceived risk factors for severe Covid-19 symptoms and their association with health behaviours: Findings from the HEBECO study

Background: There remains uncertainty about Covid-19 risk factors. We examined UK adults’ risk perceptions for severe Covid-19 symptoms and whether engaging in concurrent health behaviours is associated with risk perceptions. / Methods: Cross-sectional analysis of data from the HEBECO study where 2206 UK adults classified potential factors (age 70+, ethnic minority, medical comorbidities, vaping, smoking cigarettes, alcohol drinking, regular physical activity, being overweight, eating unhealthy foods, using nicotine replacement therapy – NRT, lower income, poor housing, being a keyworker) as either increasing, decreasing, or having no impact on severe Covid-19 symptoms. Logistic regressions examined whether engaging in health behaviours was associated with risk perceptions after adjusting for socio-demographic characteristics, health conditions and other behaviours. / Results: The great majority (89-99%) of adults classified age 70+, having comorbidities, being a key worker, overweight, and from an ethnic minority as increasing the risk. People were less sure about alcohol drinking, vaping, and nicotine replacement therapy use (17.4-29.5% responding ‘don’t know’). Relative to those who did not, those who smoked tobacco, vaped and consumed alcohol had significantly (all p<0.015) higher odds (aORs=1.58 to 5.80) for classifying these behaviours as ‘no impact’ or ‘decreasing risk’, and lower odds (aORs=.25 to .72) for classifying as ‘increasing risk’. Similarly, eating more fruit and vegetables was associated with classifying unhealthy diet as ‘increasing risk’ (aOR=1.37,1.12-1.69), and exercising more with classifying regular physical activity as ‘decreasing risk’ (aOR=2.42,1.75-3.34). / Conclusions: Risk perceptions for severe Covid-19 symptoms were lower for adults’ own health behaviours, evidencing optimism bias. / Implications: These risk perceptions may form barriers to changing one’s own unhealthy behaviours or make one less responsive to interventions that refer to the risk of Covid-19 as a motivating factor. Thus, in some cases risk perceptions could help sustain unhealthy behaviours and exacerbate inequalities in health behaviours and outcomes

Smoker Identity and Its Potential Role in Young Adults' Smoking Behavior: A Meta-ethnography

OBJECTIVE: Identity is an important influence on behavior. To identify potential targets for smoking cessation interventions in young adults, we synthesized findings from qualitative studies on smoker identity and potential influences on smoking and smoking cessation. METHODS: A systematic search of 4 electronic databases up to September 19, 2013, was conducted to identify qualitative studies on smoker identity in smokers and ex-smokers aged 16-34. Key concepts were extracted from individual studies and synthesized into higher-order interpretations by following the principles of meta-ethnography. RESULTS: Seventeen relevant papers were identified. At the highest level of interpretation, we identified 4 types of findings: (a) contributory factors to identity, (b) identity in relation to smoking, (c) contextual and temporal patterning, and (d) behavior in relation to smoking. Contributory factors included the desire to establish aspirational individual and social identities, enact a smoker identity appropriate to the momentary social context, and alter personal nonsmoking rules when consuming alcohol. Smoker identity was multifaceted and incorporated individuals' defensive rationalizations, and both positive and negative feelings attached to it. Smoker identities took time to develop, were subject to change, and were context dependent. Identity was found to play a role in quit attempts. CONCLUSIONS: Qualitative research into the identity of young adult smokers has established it as a multifaceted phenomenon serving important functions but also involving conflict and defensive rationalizations. It develops over time and contextual factors influence its expression. The nature of a smoker's identity can play an important role in smoking cessation