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How well do cognitive and environmental variables predict active commuting?

Lemieux M, Godin G - Int J Behav Nutr Phys Act (2009)

Bottom Line: The significant determinants were intention, habit and age.The results showed that cognitive variables play a more important role than environmental variables in predicting and explaining active commuting.When environmental variables were significant, they were mediated by cognitive variables.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Social and Preventive Medicine, Division of Kinesiology, Laval University, Québec, Canada. Gaston.Godin@fsi.ulaval.ca.

ABSTRACT

Background: In recent years, there has been growing interest in theoretical studies integrating cognitions and environmental variables in the prediction of behaviour related to the obesity epidemic. This is the approach adopted in the present study in reference to the theory of planned behaviour. More precisely, the aim of this study was to determine the contribution of cognitive and environmental variables in the prediction of active commuting to get to and from work or school.

Methods: A prospective study was carried out with 130 undergraduate and graduate students (93 females; 37 males). Environmental, cognitive and socio-demographic variables were evaluated at baseline by questionnaire. Two weeks later, active commuting (walking/bicycling) to get to and from work or school was self-reported by questionnaire. Hierarchical multiple regression analyses were performed to predict intention and behaviour.

Results: The model predicting behaviour based on cognitive variables explained more variance than the model based on environmental variables (37.4% versus 26.8%; Z = 3.86, p < 0.001). Combining cognitive and environmental variables with socio-demographic variables to predict behaviour yielded a final model explaining 41.1% (p < 0.001) of the variance. The significant determinants were intention, habit and age. Concerning intention, the same procedure yielded a final model explaining 78.2% (p < 0.001) of the variance, with perceived behavioural control, attitude and habit being the significant determinants.

Conclusion: The results showed that cognitive variables play a more important role than environmental variables in predicting and explaining active commuting. When environmental variables were significant, they were mediated by cognitive variables. Therefore, individual cognitions should remain one of the main focuses of interventions promoting active commuting among undergraduate and graduate students.

No MeSH data available.


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Observed model for the prediction of active commuting. Only significant associations are illustrated.
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Figure 1: Observed model for the prediction of active commuting. Only significant associations are illustrated.

Mentions: Mediation tests were performed to identify how environmental factors contribute to the formation of intention and prediction of behaviour. Five environmental variables met Baron and Kenny's (1986) criteria and were tested for mediation by intention in the prediction of active commuting, controlling for age and habit. None of these factors reached significance: detached single-family residence (CI95%: -0.52, 0.17); apartments (CI95%: -0.14, 0.41); time to access services (CI95%: -0.04, 0.05); time to get to work or school (CI95%: -0.06, 0.002); and car accessibility (CI95%: -0.93, 0.02). In fact, mediation analyses indicated that environmental variables were mediated by the determinants of intention. Time to get to work or school was mediated by PBC (CI95%: -0.03, -0.0008; covariate: habit) and habit (CI95%: -0.13, -0.06), whereas detached single-family residence (CI95%: -0.65, -0.13), apartments (CI95%: 0.12, 0.67), time to access services (CI95%: -0.13, -0.06) and car accessibility (CI95%: -1.51, -0.80) were mediated by PBC. No other significant relation was found. Figure 1 illustrates the interrelationship between cognitions and environmental variables in explaining intention and predicting behaviour.


How well do cognitive and environmental variables predict active commuting?

Lemieux M, Godin G - Int J Behav Nutr Phys Act (2009)

Observed model for the prediction of active commuting. Only significant associations are illustrated.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2667470&req=5

Figure 1: Observed model for the prediction of active commuting. Only significant associations are illustrated.
Mentions: Mediation tests were performed to identify how environmental factors contribute to the formation of intention and prediction of behaviour. Five environmental variables met Baron and Kenny's (1986) criteria and were tested for mediation by intention in the prediction of active commuting, controlling for age and habit. None of these factors reached significance: detached single-family residence (CI95%: -0.52, 0.17); apartments (CI95%: -0.14, 0.41); time to access services (CI95%: -0.04, 0.05); time to get to work or school (CI95%: -0.06, 0.002); and car accessibility (CI95%: -0.93, 0.02). In fact, mediation analyses indicated that environmental variables were mediated by the determinants of intention. Time to get to work or school was mediated by PBC (CI95%: -0.03, -0.0008; covariate: habit) and habit (CI95%: -0.13, -0.06), whereas detached single-family residence (CI95%: -0.65, -0.13), apartments (CI95%: 0.12, 0.67), time to access services (CI95%: -0.13, -0.06) and car accessibility (CI95%: -1.51, -0.80) were mediated by PBC. No other significant relation was found. Figure 1 illustrates the interrelationship between cognitions and environmental variables in explaining intention and predicting behaviour.

Bottom Line: The significant determinants were intention, habit and age.The results showed that cognitive variables play a more important role than environmental variables in predicting and explaining active commuting.When environmental variables were significant, they were mediated by cognitive variables.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Social and Preventive Medicine, Division of Kinesiology, Laval University, Québec, Canada. Gaston.Godin@fsi.ulaval.ca.

ABSTRACT

Background: In recent years, there has been growing interest in theoretical studies integrating cognitions and environmental variables in the prediction of behaviour related to the obesity epidemic. This is the approach adopted in the present study in reference to the theory of planned behaviour. More precisely, the aim of this study was to determine the contribution of cognitive and environmental variables in the prediction of active commuting to get to and from work or school.

Methods: A prospective study was carried out with 130 undergraduate and graduate students (93 females; 37 males). Environmental, cognitive and socio-demographic variables were evaluated at baseline by questionnaire. Two weeks later, active commuting (walking/bicycling) to get to and from work or school was self-reported by questionnaire. Hierarchical multiple regression analyses were performed to predict intention and behaviour.

Results: The model predicting behaviour based on cognitive variables explained more variance than the model based on environmental variables (37.4% versus 26.8%; Z = 3.86, p < 0.001). Combining cognitive and environmental variables with socio-demographic variables to predict behaviour yielded a final model explaining 41.1% (p < 0.001) of the variance. The significant determinants were intention, habit and age. Concerning intention, the same procedure yielded a final model explaining 78.2% (p < 0.001) of the variance, with perceived behavioural control, attitude and habit being the significant determinants.

Conclusion: The results showed that cognitive variables play a more important role than environmental variables in predicting and explaining active commuting. When environmental variables were significant, they were mediated by cognitive variables. Therefore, individual cognitions should remain one of the main focuses of interventions promoting active commuting among undergraduate and graduate students.

No MeSH data available.


Related in: MedlinePlus