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Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking
Published on: August 6, 2013
The Austrian multicentre study on smoking: subgroups of nicotine dependence and their craving
Otto Michael Lesch1, Alexander Dvorak, Ines Hertling
1Department of Psychiatry, University of Vienna, Vienna, Austria. otto.m.lesch@akh-wien.ac.at
Background:
The misconception of tobacco smoking as a 'bad habit' has been replaced by a diagnosis of addiction. Although help to quit is offered by nicotine replacement, antidepressants and psychotherapeutic support, there is no cure yet. One cause of impediment might be psychiatric comorbidity. Therefore, we searched for smoker subgroups, needing different treatments.
Aim Of The Study:
The study aimed at subtyping smokers in an attempt to better understand the phenomenon of resistant smokers and provide more information that could potentially become useful to treatment centres assuming the subtypes correlate directly with outcomes of different smoking cessation treatments, tailor-made according to subtypes.
Methods:
330 out of 430 recruited smokers were classified as nicotine dependent (ICD-10) and tobacco dependent (DSM-IV) and remained in the study. They were investigated with different diagnostic assessments: Fagerström Test (FT), Lübeck Craving Risk Relapse Questionnaire and Lesch Typology Questionnaire (the last two being modified for smoking).
Results:
Dependence severity degree is reflected by the FT. FT scores >/=5 indicated higher conspicuousness. Four clusters for nicotine craving were found: (1) 'depressed', (2) 'stimulated', (3) 'relaxed mood state' and (4) 'socially triggered tensed mood'. In contrast to alcoholism, 'stimulation' was one of the major craving conditions in smokers. The decision tree, consisting of the FT and the Lesch Typology Questionnaire, distinguishes four subgroups of nicotine-dependent persons.
Conclusion:
The subgroups reflect different reinforcement and psychosocial disturbances. They match treatment and can be applied as outcome predictors in controlled treatment and relapse prevention studies.
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