Category Archives: Discussion

Do Smokers Consist of a Single Group?

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When you think of a smoker, it is likely that you are imagining someone who goes through a pack of cigarettes per day and can often be found running to the nearest store to maintain their supply. Perhaps you amuse yourself watching your friend conspicuously leaving work to stand outside and huddle around their cigarette in the rain. Your assumption would often be correct as the majority of smokers are dependent on nicotine and smoke throughout the day. These daily smokers account for approximately 89% of current smokers in the UK (Herbec, Brown and West 2014), and between 67%-75% of smokers in the USA (Coggins, Murrelle and Carchman 2009). However, what about this missing proportion of smokers?

This consists of non-daily smokers, a sub-group of smokers who only consume a few cigarettes per day and can often engage in voluntary days of abstinence without experiencing the effects of withdrawal (Shiffman, Ferguson and Dunbar 2012b). What makes these smokers interesting is that although they do not appear to be dependent on nicotine, 82% of them relapse within 90 days of attempting to quit (Tindle and Shiffman 2011). Compared to 87% of daily smokers, these figures are remarkably close. Similar results were found in a UK sample as 92% of daily smokers and 83% of non-daily smokers failed to remain abstinent beyond six months (Herbec et al. 2014). Despite this difficulty, smoking cessation therapies lack efficacy in non-daily smokers due to a reliance on nicotine replacement therapy (Jimenéz-Ruiz and Fagerström 2010). This is not surprising as clinical trials commonly exclude light smokers (Shiffman 2009), and they rarely experience withdrawal symptoms due to a lack of nicotine dependence.

As smoking restrictions become more and more stringent, the proportion of light smokers is predicted to increase (Coggins et al. 2009; Shiffman 2009). Although light smoking is often perceived as being less harmful, it is associated with the same increased risk of developing cardiovascular disease, lung and other types of cancer as heavy smoking. For example, one prospective study found that male and female light smokers had a significantly increased risk of ischaemic heart disease and lung cancer in comparison to non-smokers (Bjartveit and Tverdal 2005). Furthermore, a systematic review found that light smokers show an intermediate risk between non-smokers and heavy smokers, but interestingly they share the same risk for heart disease as heavy smokers (Schane, Ling and Glantz 2009). Considering this, it is important to understand what the differences are between the groups, and how we can identify them.    

What are the differences in smoking patterns?

Table 1 shows the number of cigarettes smoked per day by light and heavy smokers in a small range of studies that include figures for both groups. Although there is some fluctuation, smoking rates are approximately 15 and 4 cigarettes per day for heavy and light smokers respectively. Additionally, it is interesting that light smokers often engage in voluntary days of abstinence. Compared to heavy smokers who consistently use cigarettes every day, one study found that light smokers only tend to use cigarettes on only four days per week (Shiffman, Tindle and Li 2013). This suggests that light smokers are relatively free of nicotine dependence as the half-life of nicotine in the body is approximately two hours (Advokat, Comaty and Julien 2014). This is usually the time heavy smokers start to crave their next cigarette, but it appears that light smokers are comfortable without smoking for hours and even days after all of the nicotine has been metabolised and left the body.

Table 1

Mean Number of Cigarettes Smoked Per Day in Light and Heavy smokers

Study Smoking Group Cigarettes Per Day
Herbec et al. (2014) Daily

Non-Daily

13.90

5.20

Shiffman et al. (2012a) Daily

Intermittent

15.00

4.50

Shiffman, Dunbar and Benowitz (2014a) Daily

Intermittent

15.98

3.24

Shiffman et al. (2014b) Daily

Intermittent

15.01

4.45

Scheuermann et al. (2015) Moderate Daily

Light Daily

Converted Non-Daily

Native Non-Daily

20.60

7.41

5.78

4.25

Note: Smoking group names are reproduced with those used within each study

The early dismissal of non-daily smokers was based on the belief that they only consisted of adolescents who were in a transitioning state on the way to being a heavy smoker (Shiffman 2009). Whilst this does not provide a full explanation, non-daily smoking as a young adult is indeed an important risk factor for becoming a daily smoker later in life. One cohort study found that non-daily smoking at age 21 was associated with an odds ratio of 3.60 to becoming a daily smoker at age 38 upon follow-up (Robertson, Losua and McGee 2015). In terms of public health, this highlights the need for research to focus on non-daily adolescent smokers as they could be the target of interventions before they progress into heavier, daily smoking. However, it is not only a transient state on the road to becoming a heavy smoker. The non-daily smokers in Shiffman et al. (2012b) had been smoking for an average of 18 years, and those in Shiffman et al. (2013) had smoked an estimated 42,000 cigarettes. This suggests that light, non-daily smoking can also be a consistent behaviour pattern that can last throughout adulthood.

What are the reasons people report for smoking?

Non-daily smokers appear to show markedly different smoking habits, but they also show large differences in their reported reasons for smoking. The dominant paradigm of addictive behaviour for smokers centred around continuing to use cigarettes to avoid experiencing the aversive effects of withdrawal (Shiffman 2009). This motive appears to be consistent with heavy smokers as they cite cravings, tolerance, and a loss of control over cigarette availability as influences to smoke (Shiffman et al. 2012a). This is also consistent in young heavy smokers as higher scores of nicotine dependence was associated with smoking due to craving and habit in a sample of college students (Piasecki, Richardson and Smith 2007).

On the other hand, non-daily smokers report to smoke for radically different reasons. For example, exposure to smoking cues, weight control, sensory experiences of smoking, and positive reinforcement have been cited as motives for non-daily smokers (Shiffman et al. 2012a). This is inconsistent with daily smokers as rather than avoiding the negative experiences of smoking, they appear to smoke for the positive experiences. This has led non-daily smokers to be labelled as ‘indulgent’, as they tend to smoke to enhance the experience of situations that are already positive such as drinking alcohol in a bar with friends (Shiffman, Dunbar and Li 2014). As well as showing different habits and smoking patterns, non-daily smokers report being motivated to smoke by substantially different reasons to those normally proposed in daily smokers.

 

How can you measure cigarette consumption?

Definitions of light and heavy smoking

You may have noticed that a few different terms have been used such as: light smoker; non-daily smoker; occasional smokers. This is mainly because no one can agree on a consistent definition, and several have been used across the studies investigating this group. Firstly, light and heavy smoking has been used to highlight the contrast between consumption levels. However, this classification is associated with the largest range of criteria between studies (Husten 2009) Secondly, daily and non-daily (or intermittent) smoking is associated with a much more consistent pattern of use in contrast to light and heavy smoking (Shiffman et al. 2012a; 2012b; 2014). This is due to the number of cigarettes per day fluctuating, but smoking less than daily is a key indicator of this consumption pattern. Finally, there is a dichotomy between low and high nicotine dependence. This also appears to be a valid characterisation as non-daily/light smokers consistently exhibit significantly less nicotine dependence on every common measure (Shiffman 2012b). However, it is important to note that in reality, dependence and smoking behaviour exists along a continuum. Even within different dichotomies, there is a large amount of variation across the supposedly homogeneous sub-groups.

Measuring light and heavy smokers

On a final note of measurement, it is crucial to ask the right questions when assessing light smokers. Many questionnaires simply ask ‘are you a smoker?’ which may not detect non-daily smokers as they commonly do not identify with being a smoker (Schane et al. 2009). For example, in one study approximately 50% of light smokers said they might not admit to being a smoker (Shiffman et al. 2013). This suggests simply asking whether people smoke or not might not be the best strategy, as they may just get ‘no’ as an answer. Clearly, more nuanced approaches are necessary to detect the low number of cigarettes consumed by this group. Fortunately, there are some additional measures of cigarette consumption that can provide a more sensitive answer:

  • A diary measure of the number of cigarettes smoked over a period of time
  • Breath Carbon Monoxide (CO) in a single session
  • Average CO over a number of sessions
  • Hair cotinine (a metabolite of nicotine) or nicotine levels

However, what are the best measures to use? An intensive diary account is considered to be the most accurate but it is the most time consuming for smokers which may deter some participants (Wray, Gass and Miller 2015). When comparing this to the less motivationally intensive measures, it appears that a single daily report of cigarettes across a number of days is the measure most strongly correlated with the intensive diary. Furthermore, when the level of exhaled CO is averaged across multiple testing session, this provides a valid biomarker for measuring cigarette consumption in light smokers (Wray et al. 2015). As well as these accuracy benefits, using a handheld CO monitor is cheap and does not require the expertise associated with analysing hair cotinine and nicotine levels. Due to the heterogeneous nature of smokers, it is crucial that the complexities in identifying light smokers are fully appreciated.

Conclusion

In summary, there is a clear distinction between different types of smoker but it is often neglected in research. Despite an apparent lack of nicotine dependence, both types of smoker find it difficult to remain abstinent with only a small difference between the cessation failure rates (Tindle and Shiffman 2011; Herbec et al. 2014). This is important for public health as although they form a minority of smokers, they share the same risk factor for heart disease as heavy smokers, and have an elevated risk of lung cancer (Bjartveit and Tverdal 2005; Schane et al. 2009). Considering the number of light smokers is predicted to increase as smoking restrictions tighten (Coggins et al. 2009; Shiffman 2009), it is crucial that this group is understood better. Research should focus on the individual differences in the determinants of smoking behaviour to better understand what is motivating light and heavy smokers. This knowledge will hopefully translate into more effective smoking cessation treatments that cater to the individual needs of each smoker.

 

Reading List

Health implications: Schane, R. E., Ling, P. M., Glantz, S. A. (2010) ‘Health Effect of Light and Intermittent Smoking: A Review’. Circulation 121, 1518-1522

Smoking Patterns: Shiffman, S., Tindle, H., Li, X., Scholl, S., Dunbar, M. and Mitchell-Miland, C. (2013) ‘Characteristics and Smoking Patterns of Intermittent Smokers’. Experimental and Clinical Psychopharmacology 20(4), 264-277

Smoking Motives: Shiffman, S., Dunbar, M. S., Scholl, S. M. and Tindle, H. A. (2012a) ‘Smoking Motives of Daily and Non-Daily Smokers: A Profile Analysis’. Drug and Alcohol Dependence 126, 362-368

Definitions: Husten, C. G. (2009) ‘How Should we Define Light or Intermittent Smoking? Does it Matter?’. Nicotine and Tobacco Research 11(2), 111-121

Measurement: Wray, J. M., Gass, J. C., Miller, E. I., Wilkins, D. G., Rollins, D. E. and Tiffany, S. T. (2015) ‘A Comparative Evaluation of Self-Report and Biological Measures of Cigarette Use in Non-Daily Smokers’. Psychological Assessment [online] available from http://www.ncbi.nlm.nih.gov/pubmed/26479132  [12/07/2016]

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A Psychologist’s Guide to Reading a Neuroimaging Paper

Psychological research is benefiting from advances in neuroimaging techniques. This has been achieved through the validation and falsification of established hypothesis in psychological science (Cacioppo, Berntson, & Nusbaum, 2008). It has also helped nurture links with neuroscience, leading to more comprehensive explanations of established theories. Positron Emission Tomography (PET), functional MRI (fMRI), structural MRI (sMRI), electroencephalography (EEG), diffusion tensor imaging (DTI) and numerous other lesser-known neuroimaging techniques can provide information complimentary to behavioural data (Wager, 2006). With these modalities of research becoming more prevalent, ranging from investigating the neural effects of mindfulness training to neuro-degeneration, it is worth taking a moment to highlight some points to help discern what may be good or poor research. Like any other methodology, neuroimaging is a great tool that can be used poorly. As with all areas of science, one must exercise a good degree of caution when reading neuroimaging papers. Continue reading

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Bayesian Statistics: What is it and Why do we Need it?

prlipohellThere is a revolution in statistics happening: The Bayesian revolution. Psychology students who are interested in research methods (which I hope everyone is!) should know what this revolution is about. Gaining this knowledge now instead of later might spare you lots of misconceptions about statistics as it is usually instructed in psychology, and it might help you gain a deeper understanding of the foundations of statistics. To make sure that you can try out everything you learn immediately, I conducted analysis in the free statistics software R (www.r-project.org; click HERE for a tutorial how to get started with R, and install RStudio for an enhanced R-experience) and I provide the syntax for the analysis directly in the article so you can easily try them out. So let’s jump in: What is “Bayesian Statistics”, and why do we need it? Continue reading

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Engaging in a Research Project with an International Team – Opportunities and Problems

ID-100160549Doing science is great, but doing it together with people you can learn from and who share your research interests – that’s fantastic! Add the cross-cultural dimension to the project and it grows even better! Why doesn’t everyone do that? Regrettably the projects involving collaborative work with other young scientists and/or students who love research can often be hard to begin and even tougher to maintain. Although undeniably rewarding, working in a traditional team already has a number of difficulties, while doing it with people who you can’t communicate with face-to-face adds a whole new pile of concerns. Let’s face it – even with a great concept writing a paper doesn’t always go smoothly and it can turn into tough, uninspiring work; keeping up with an international team and all the things that come with being part of one (things we often don’t even have to think of when working alone, such as communication problems, file storage, different ethics procedures than these in our academic institution, other people’s needs, skills and motivation, etc.) can quickly turn our initial enthusiasm into disillusionment.  Well, thanks to the advances in technology and some good old tips and ideas – it doesn’t have to be so bleak and discouraging! Read on for some useful strategies, ideas and tools to help start off your collaboration efforts, keep your team together, your productivity high and your experiences positive while conducting cross-cultural research with peers from abroad!  Continue reading

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Why Would Researchers Skip Peer-Review? Media Reports of Unpublished Findings

‘You love your iPhone. Literally.’ ‘This is your brain on politics.’ ‘Overclock your brain using transcranial Direct Current Stimulation (tDCS).’ There are many other claims in psychology which have been publicised by the media, yet remain unchecked by academic experts. Peer-reviewed publications – papers which have been checked by researchers of similar expertise to the authors – are produced very slowly and only occasionally make instant impacts outside the walls of academia. In contrast, media publications are produced very quickly and provoke immediate reactions from the general public. Continue reading

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Twitter in The University: How Using Twitter Can Benefit Students and Early Career Researchers

Twitter is stereotypically portrayed as a website for following celebrities and posting mundane tidbits. Recently, I realized that Twitter could be used as an academic tool – to share and receive ideas and information in an educational context. Indeed, students and early career researchers should be capitalizing on Twitter to learn new information, connect with others, and share interesting thoughts. Continue reading

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What Do Whigs Have To Do With History of Psychology?

The 2013 December issue of the journal Theory & Psychology saw a forceful exchange between Kurt Danziger and Daniel N. Robinson on the nature of psychology’s disciplinary history. For those unfamiliar with the names, both are eminent scholars in (among other things) history of psychology. The exchange boils down to Danziger accusing Robinson of creating a romanticized history of psychology, tying the discipline down to Ancient Greek philosophies.  What Danziger cannot forgive in such a way of writing history of science is the idea of a concept that stays the same throughout history, and then finds its way into psychology. For example (Danziger, 2013, p. 835): “This understanding of psychology’s history has always relied on the belief that the concept of ‘human nature’ represents some historically unchanging essence guaranteeing continuity, no matter how great the gulf that appears to separate the present from the remote past.” Robinson, in turn, answers with two articles in the same issue defending his position with insinuations that Danziger and his supporters are not familiar enough with Aristotle’s body of work to mount such a criticism. His repartees, sans the scholastic posturing, can be summed up well with the sentence (Robinson, 2013a, p. 820): “It is worth noting in order to make clear that the past can be highly instructive without being causally efficacious.” Continue reading

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Collaborating With Researchers in Other Fields

collaboration As students and young professionals by now we have come to realize how working with other people is essential for the completion of  many goals in the pursuit of scientific relevance. Sometimes it is through the insight, know-how and/or dedication of others that we can push forward a project that was stuck at a roadblock. So how do scientists in the field of psychology collaborate with other scientists and what strengths  and disadvantages they may have in a team of researchers with diverse backgrounds? The following piece attempts to outline some such possible opportunities and hurdles.

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Enunciation on Open Access: The practitioners’ perspective

A continually  growing body of student organizations, as well as scientists, have been advocating for an Open Access to scientific publications. The European Federation of Psychology Students Associations (EFPSA) has been part of this effort for a long time and this blog hosts an extensive cover of the numerous aspects of the Open Access initiative. Checking the Open Access tag, here at the bulletin, will give you a comprehensive list of the already covered topics by the JEPS editors and their associates.

To begin, in working for advocating and raising awareness, the collaboration of many organizations and institutions has already produced results and we have seen governmental and intergovernmental bodies already taking steps to favour open publication policies. For instance, the United Kingdom’s Research Councils’ policy on Open Access and EU Commission’s inclusion of Open Access as a general principle in the Horizon 2020 projects are high level decisions that will ensure extended access to scientific knowledge and awareness of the issues amongst researchers.

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How to Collect Data Effectively? An Overview of the Best Online Survey Providers

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This post will talk about the pros and cons of a few selected providers of online survey services and may help you find the best survey service provider for your research purposes. With the information given in this post, your future data collections will become much easier due to the overview of survey providers for quantitative research you will receive. After giving you an insight into the diversity of survey tools and the general features they provide, four of the best featured and most frequently used survey tool providers will be presented in greater detail.

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