A Close Look at the Nomology of Support for National Smoking Bans amongst Hospitality Industry Managers: An application of Growth Mixture Modeling
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosophy
Politicians and social marketers considering whether, and how, to implement a national smoking ban in their countries require sound evidence regarding what the causes of support are amongst key stakeholders, how this support will develop over the short to medium term in which they seek to be re-elected, and how support relates to critical outcomes like enforcement. In response to this need, I use structural equation models to develop a model of the antecedents of support, based on theories of self interest and common sense justice, amongst hospitality industry managers. I show that support is determined more by fairness related constructs than self interest constructs, that support for national smoking bans increases consistently over time, and that the initial level of support, and the rate at which support increases, is positively related to subsequent enforcement behaviour by bar managers, in the year after implementation of such a ban, in New Zealand. I use growth mixture modeling to identify two subgroups of bar managers whose support changes at different rates. First, a class of bar managers with a high proportion of smokers who reported fewer instances of respiratory related health problems, showed low initial support, and whose support for the legislation slowly decreased. And second, a class of bar managers comprised of fewer smokers, but reporting more instances of respiratory related health problems. This class began with a high degree support, and steadily increased in support for the national smoking ban. I discuss the implications of these findings for social marketers, health educationalists, and politicians interested in introducing a similar ban in other countries.