PubMed · 6907540
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K J Redican. 1980. "All or None" evaluation: is it valid?. https://doi.org/10.1111/j.1746-1561.1980.tb03141.x
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To advance the science of tobacco control, an enhanced understanding of the bio-behavioral basis of nicotine addiction is needed. In this study, we provide an overview of data from investigations of genetic factors in smoking behavior, discuss potential bio-behavioral mechanisms and effect modifiers, and suggest avenues for pharmacogenetics research in the area of smoking cessation treatment. The evidence to date is very consistent with respect to the significance of genetic contributions to smoking behavior. However, attempts to elucidate the role of specific genetic variants have met with mixed success. Explanations for the lack of consistency in the results of genetic association studies include biases in ascertainment, ethnic admixture, lack of attention to co-variates or modifiers of genetic risk, and the need for more refined phenotypes. As the field of genetics and smoking research progresses, increasing attention is being devoted to gene-environment interactions, with particular attention to the identification of genetic variants that may modify the effects of pharmacological treatment for smoking. With advances in molecular biology and genomics technology, individualized tailoring of smoking cessation therapy to genotype is within our grasp. Such research has the potential to improve treatment outcome, thereby reducing morbidity and mortality from smoking-related disease.
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Behaviour modification is often delivered to teaching subgroups. For example, experimental and control smoking cessation programmes may be given to 15 classes (subgroups) with 10 (otherwise independent) individuals. We present general statistical tests and power estimates to compare continuous outcomes from two interventions in settings where the magnitude of teaching subgroup heterogeneity, number of subgroups and subgroup size can differ between intervention arms. An application is made to data from a trial to reduce disease-transmitting sexual behaviour. The statistical impact of teaching subgroup heterogeneity effect increases as the (a) number of participants in a subgroup increases, and (b) ratio of 'averaged experimental and control subgroup effect variance' to study subject variance increases. If plausible levels of subgroup teaching effect heterogeneity are ignored, the true sizes of tests with nominal 0.05 two-sided type I errors range from 0.055 to 0.47, while when planning studies, estimated sample sizes are only 11.1-95.2 per cent of the true requirements.