Promoting engagement with a Stop Smoking Service via pro-active telephone calls

Accessing National Health Service Stop Smoking Services in the UK: a COM-B analysis of barriers and facilitators perceived by smokers, ex-smokers and stop smoking advisors

OBJECTIVE

Smokers who access free National Health Service (NHS) Stop Smoking Services (SSS) in the UK are four times more likely to stop smoking, yet uptake of the services has been in decline in recent years. Evidence was collated to explore the beliefs of smokers, ex-smokers and Stop Smoking Advisors (SSAs) about SSS and the barriers and facilitators to access.

STUDY DESIGN

Mixed-methods design including i) a search of the literature; ii) a cross-sectional online questionnaire completed by 38 smokers and ex-smokers; and iii) semistructured interviews with 5 SSAs.

METHODS

PubMed, Web of Science, Scopus, Prospero and the NIHR Portfolio were searched in October 2017 to identify relevant studies. Smokers and ex-smokers were recruited to the online questionnaire via Public Health websites and social media in Warwickshire. SSAs identified via Public Health Warwickshire were invited to take part in an interview conducted over the telephone. Findings were collated and analysed using the COM-B ('Capability', 'Opportunity', 'Motivation' and 'Behaviour') model framework.

RESULTS

A range of practical and psychological or belief-based barriers and facilitators to accessing SSS were identified within all the components of the COM-B model, aside from physical capability, for example; 'Psychological capability', such as lack of understanding about what the service offers; 'Reflective motivation', such as lack of confidence in service efficacy; and 'Social opportunity', such as recommendations from healthcare professionals to attend. Suggestions and consideration on how future tobacco control intervention and public health messages can address these components are reported.

CONCLUSIONS

Public health interventions and campaigns may benefit from focussing on addressing the well-known perceived barriers and facilitators smokers experience, in particular focussing on the components of the COM-B that have been identified as being important to increase the uptake of SSS.

Smoking cessation interventions for patients with coronary heart disease and comorbidities: an observational cross-sectional study in primary care

BACKGROUND

Little is known about how smoking cessation practices in primary care differ for patients with coronary heart disease (CHD) who have different comorbidities.

AIM

To determine the association between different patterns of comorbidity and smoking rates and smoking cessation interventions in primary care for patients with CHD.

DESIGN AND SETTING

Cross-sectional study of 81 456 adults with CHD in primary care in Scotland.

METHOD

Details of eight concordant physical comorbidities, 23 discordant physical comorbidities, and eight mental health comorbidities were extracted from electronic health records between April 2006 and March 2007. Multilevel binary logistic regression models were constructed to determine the association between these patterns of comorbidity and smoking status, smoking cessation advice, and smoking cessation medication (nicotine replacement therapy) prescribed.

RESULTS

The most deprived quintile had nearly three times higher odds of being current smokers than the least deprived (odds ratio [OR] 2.76; 95% confidence interval [CI] = 2.49 to 3.05). People with CHD and two or more mental health comorbidities had more than twice the odds of being current smokers than those with no mental health conditions (OR 2.11; 95% CI = 1.99 to 2.24). Despite this, those with two or more mental health comorbidities (OR 0.77; 95% CI = 0.61 to 0.98) were less likely to receive smoking cessation advice, but absolute differences were small.

CONCLUSION

Patterns of comorbidity are associated with variation in smoking status and the delivery of smoking cessation advice among people with CHD in primary care. Those from the most deprived areas and those with mental health problems are considerably more likely to be current smokers and require additional smoking cessation support.

StopApp: Using the Behaviour Change Wheel to Develop an App to Increase Uptake and Attendance at NHS Stop Smoking Services

Smokers who attend NHS Stop Smoking Services (SSS) are four times more likely to stop smoking; however, uptake has been in decline. We report the development of an intervention designed to increase uptake of SSS, from a more motivated self-selected sample of smokers. In Phase 1 we collected data to explore the barriers and facilitators to people using SSS. In Phase 2, data from extant literature and Phase 1 were subject to behavioural analysis, as outlined by the Behaviour Change Wheel (BCW) framework. Relevant Behaviour Change Techniques (BCTs) were identified in order to address these, informing the content of the StopApp intervention. In Phase 3 we assessed the acceptability of the StopApp. Smokers and ex-smokers identified a number of barriers to attending SSS, including a lack of knowledge about what happens at SSS (Capability); the belief that SSS is not easy to access (Opportunity); that there would be ’scare tactics’ or ‘nagging’; and not knowing anyone who had been and successfully quit (Motivation). The ‘StopApp’ is in development and will link in with the commissioned SSS booking system. Examples of the content and functionality of the app are outlined. The next phase will involve a full trial to test effectiveness.

Factors predicting recruitment to a UK wide primary care smoking cessation study (the ESCAPE trial)

BACKGROUND

Recruiting smokers to smoking cessation trials is challenging and participation rates are often low. Consequently, the interventions evaluated may fail to reach a broad spectrum of the target population, thus compromising the generalizability of the findings. Brief interventions, using proactive recruitment, are likely to attract a broader and more representative proportion of the population.

OBJECTIVE

We explored the factors that influenced recruitment into a trial evaluating computer-tailored feedback reports that aimed to help smokers to quit [the ESCAPE (Effectiveness of computer-tailored Smoking Cessation Advice in Primary Care) study] in order to investigate the possibilities for increasing recruitment into smoking cessation trials.

METHODS

Current cigarette smokers, identified from GP records, were invited to participate in the study. The main outcome measure was the recruitment rate, i.e. the proportion of participants who responded and were randomized to one of the intervention groups. Predictor variables included geographical region, level of deprivation, practice characteristics and the number and timing of mailings of questionnaires.

RESULTS

The recruitment rate varied by practice (2.5-19.8%) and differed significantly between regions (from 16.3% in Scotland to 8.4% in London, P < 0.001). Recruitment decreased significantly by 1.1% between the lowest and highest quintiles of deprivation (P = 0.012), measured by Index of Multiple Deprivation scores, and decreased by 1.33% for every extra 10% smokers identified within a practice population (P = 0.010). Sending reminders increased recruitment by 7.5% (P < 0.001). Multivariable analysis showed region and length of time between mailings were the main predictors of recruitment.

CONCLUSIONS

Proactive recruitment methods can increase participation in smoking cessation trials and weighting the target sample in favour of more deprived areas will recruit a more representative sample. The number and timing of mailings to potential participants can also increase recruitment.