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Home > The contribution of cognitive biases to the development and maintenance of smoking-related addiction in adolescents and adults.

Hopper, Louise (2013) The contribution of cognitive biases to the development and maintenance of smoking-related addiction in adolescents and adults. PhD thesis, Trinity College Dublin.

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Anomalies between self-reported smoking intentions and actual smoking behaviour are common, yet few studies investigate both the explicit and implicit measurement of smoking cognitions within the same sample. Nor do many studies consider implicit adolescent smoking cognitions, despite the knowledge that smoking onset typically occurs during this pe... riod. The aim of this thesis was to examine the role that cognitive biases play in the initiation and maintenance of tobacco smoking. Within the context of cognitive and socio-cognitive models of nicotine addiction, the three studies that comprise this research investigated age-related changes in cognitive beliefs and the implications that these have for smoking behaviour.


Participants in each study were grouped by age into adolescent (15-18), young adult (19-25), and older adult (26+) groups, and then categorised by smoking status; a non-smoking group served as the control in each case.


Chapter 1 reviewed the prevalence and the developmental context of tobacco smoking. Affect-based, psychobiological, cognitive, and socio-cognitive theories of addiction were then evaluated. Smoking-related memory, attention, prevalence estimation, and optimistic risk biases were discussed, and the explicit and implicit measurement of these biases was then considered.


Chapter 2 aimed to investigate whether explicit and implicit measurement of smoking expectancies would reveal differences in the types and sequence of outcomes endorsed by smokers and non-smokers of different ages (N = 231), and if these differences could successfully predict current smoking behaviour. Results demonstrated that although positive and negative smoking expectancies were available to all groups, smokers, and in particular adolescent smokers, exhibited a positive memory bias for smoking-related information.


Chapter 3 then sought to identify how smokers and non-smokers in each age group (N = 182) managed positive and negative smoking-related information. Implicit reactions to positive and negative smoking words and images, relative to general positive, general negative, and to neutral stimuli were examined using lexical decision, modified-Stroop, and visual dot-probe tasks. A suppression effect was found for smoking negative words, while attentional biases to smoking images and to negative images were found for all participants.


Chapter 4 aimed to develop and validate a revised explicit smoking expectancy measure for use in diverse age and smoking experience groups. It first explored the psychometric properties of the revised scale used in the first study. It subsequently validated this scale using data from a larger sample of adolescent and adult smokers and non-smokers (N = 1046).


Chapter 5 aimed to replicate earlier smoking expectancy findings, and to extend false consensus (FCE) and optimistic risk research by examining potential age- and experience-related influences on peer prevalence and risk perceptions of smoking (N = 1011). Different patterns of bias were found across smoking status and age groups, which suggests that they may facilitate the maintenance and potential escalation of smoking behaviour. As a result,


Chapter 6 sought to develop an extended theory of planned behaviour model of smoking intentions and current smoking behaviour, which incorporated measures of smoking-related cognitive biases. Smoking expectancy positivity bias, clear overestimation of peer smoking norms, moral norms, group identity, and relative risk perceptions were found to increase the explanatory power of the extended model in each age group.


Chapter 7 summarised the main findings from the empirical studies. Taken together, they emphasised the importance of considering the influence of smoking-related cognitive biases when attempting to explain smoking behaviour. Key models of addiction were reviewed in terms of their ability to explain smoking-related cognitive biases, and conclusions regarding the affective, cognitive, and social learning influences on smoking were drawn.


Finally, the discussion addressed general methodological limitations and suggestions for future research.

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