Social influence, intention to smoke, and adolescent smoking behaviour longitudinal relations.

OBJECTIVES: There is a debate on the determinants of smoking behaviour, their relative impact, and how impacts are exerted. This longitudinal study is on the relations among social influence, intention to smoke, and smoking behaviour, controlling for attitude and self-efficacy. DESIGN AND METHODS: A model combining parents and peers with subjective and descriptive norms, resulting in four factors, was used to assess social influence. Data were collected at the beginning of the 7th(-T1), 8th(-T2), and 9th(-T3) school years, concerning 578 students (M(age) = 13.04 at T1). Structural Equation Modelling was used to test longitudinal effects. RESULTS: Variances explained by the model were high: R(2) (intention-T2) = .65, R(2) (behaviour-T2) = .67, and R(2) (behaviour-T3) = .76. Longitudinal analyses confirmed the effects of social influence on intention and behaviour. These effects on behaviour were direct and indirect (peers' and parents' descriptive norms in both cases). Descriptive norms had a stronger effect on behaviour than subjective norms. Peers' effect on behaviour was stronger than parents', but peers' effect was exerted only through descriptive norms while parents' effect was exerted through both norms. The intention effect on behaviour was not as detached as expected and its role of full mediator between other variables' effects on behaviour was not confirmed, since descriptive norms and self-efficacy had also a mediation role. CONCLUSIONS: Results show direct and indirect effects of social influence on behaviour. Descriptive norms are an important variable to operationalize social influence. Peers and parents exert influence on adolescents' intention and behaviour through different processes. The impact of intention on behaviour is not as important as expected.

Connections Between Graphical Gaussian Models and Factor Analysis.

Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations for the single-factor graphical Gaussian model are facilitated by expressing the manifest partial correlations as functions of the factor partial correlations. The power of selecting a graphical Gaussian model with an association structure between manifest variables compatible with a single-factor model is investigated. The results are illustrated using 2 examples: the 1st is a hypothetical factor model with parallel measures. The 2nd uses data from the British Household Panel Survey on job satisfaction.

The impact of social influence on adolescent intention to smoke: combining types and referents of influence.

OBJECTIVES: Theory and research suggest that the intention to smoke is the main determinant of smoking initiation and emphasizes the role of cognitive and social factors on the prediction of the intention to smoke. However, extended models such as the I-Change and results from published studies reveal inconsistencies regarding the impact of social influence on the intention to smoke. Possible explanations for this may be the definition and measurement of the constructs that have been used. DESIGN AND METHODS: The current study was designed with two main goals: (i) to test a measurement model for social influence, combining different types of social influence (subjective norms, perceived behaviour, and direct pressure) with various referents of influence (parents, siblings, peers, and teachers); (ii) to investigate the impact of social influence on adolescent intention to smoke, controlling for smoking behaviour. LISREL was used to test these models. The sample includes 3,064 Portuguese adolescents, with a mean age of 13.5 years, at the beginning of the seventh school grade. RESULTS: The hypothesized measurement model of social influence was supported by results and explained 29% of the variance of the intention to smoke. A more extended model, including attitude and self-efficacy, explained 55% of the variance of the intention to smoke. Perceived behaviour of peers, parental norms, and perceived behaviour of parents were the social influence factors with impact on adolescent intention to smoke. CONCLUSIONS: Results suggest that different referents exert their influence through distinct types of social influence and recommend further work on the definition and measurement of social influence.