Active transportation prediction using Theory of Planned Behavior among college students
type: CreativeWork
description: Rates of physical inactivity have been on the rise in America among all groups of people, including college students. Physical inactivity poses serious health risks. Active transportation (AT) is commuting under one’s own power. Examples of AT include bicycling and walking. This mode of transportation may be a helpful tool promoting physical activity. The purpose of this study was to describe predictors of active transportation behavior among University of Cincinnati students. Students were selected through the UC Registrar’s office and were emailed the survey instrument. Significant differences for all Theory of Planned Behavior constructs were seen between AT users and non-AT users except the distal construct, perceived behavioral control and its corresponding proximal constructs. A regression model predicting AT use with only Theory of Planned behavior constructs accounted for 11% of explained variation in AT use. However, when other variables were added to the regression model, 51% explanation was achieved. The final model included subjective norms, age, perceived behavioral control, and transportation type and destination. This research provides useful insight to explaining AT behavior that heretofore has not been done. Applications for this knowledge may include promoting physical activity, safety for AT users or general understanding of AT use.
abstract: Rates of physical inactivity have been on the rise in America among all groups of people, including college students. Physical inactivity poses serious health risks. Active transportation (AT) is commuting under one’s own power. Examples of AT include bicycling and walking. This mode of transportation may be a helpful tool promoting physical activity. The purpose of this study was to describe predictors of active transportation behavior among University of Cincinnati students. Students were selected through the UC Registrar’s office and were emailed the survey instrument. Significant differences for all Theory of Planned Behavior constructs were seen between AT users and non-AT users except the distal construct, perceived behavioral control and its corresponding proximal constructs. A regression model predicting AT use with only Theory of Planned behavior constructs accounted for 11% of explained variation in AT use. However, when other variables were added to the regression model, 51% explanation was achieved. The final model included subjective norms, age, perceived behavioral control, and transportation type and destination. This research provides useful insight to explaining AT behavior that heretofore has not been done. Applications for this knowledge may include promoting physical activity, safety for AT users or general understanding of AT use.
author: Chaney, Robert A.
language: English
keywords: Health Education, Active transportation, biking, walking, theory of planned behavior, physical activity, non-motorized transportation
date published: 2012
date modified: 2026-07-24T03:36:39Z
provider: OhioLINK
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cincinnati