Predicting adolescent breakfast consumption in the UK and Australia using an extended theory of planned behaviour

Mullan, Barbara; Wong, Cara; Kothe, Emily

doi:10.1016/j.appet.2012.11.021

Cited by 41 publications

(38 citation statements)

References 31 publications

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“…In fact, the wide intention-behavior gap can be attributed to other internal and external factors contributing to the behavior as well as individuals' failure to act based on their intentions (17,18). (8,21). Our findings also showed that TPB constructs explained 53.8% of the total variance of behavioral intention and 30% of the total variance of eating behaviors.…”

Section: Discussionsupporting

confidence: 65%

“…Hazavehei et al (2009) also found that 90% of their participating students had poor eating behaviors (14). An explanation for this finding is the fact that large increases in behavioral intention may be associated with moderate-level changes in behavior (8). In fact, the wide intention-behavior gap can be attributed to other internal and external factors contributing to the behavior as well as individuals' failure to act based on their intentions (17,18).…”

Section: Discussionmentioning

confidence: 99%

“…Our findings also showed that TPB constructs explained 53.8% of the total variance of behavioral intention and 30% of the total variance of eating behaviors. Similarly, most studies on eating behaviors have reported that TPB successfully predicts behavioral intention and eating behaviors (8,22).…”

Section: Discussionmentioning

confidence: 99%

“…It is among the most important theories in the area of food choice, the predictive power of which has been assessed and confirmed in many sociological and behavioral studies (3). For instance, Mullan et al (2013) found that the constructs of TPB predicted 42.2% and 57% of the variances of intention and behavior, respectively (8).…”

Section: Introductionmentioning

confidence: 99%

“…perceived social pressure for a behavior), and perceived behavioral control (i.e. perceived easiness or difficulty of showing desired behaviors) (8).…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Eating Behaviors Among High-School Students Based on the Constructs of Theory of Planned Behavior

et al. 2016

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Background and Aim: Adolescence is among the most critical periods of growth and development. In this period, the quality of nutrition goes down with age. Thus, it is really important to pay special attention to adolescents' nutritional status. This study aimed at identifying the predictors of eating behaviors among high-school students based on the theory of planned behavior. Methods: This descriptive-analytic study was conducted in 2013 -2014 in Birjand, Iran, on 457 female students. Participants were selected through two-stage cluster random sampling. A three-part instrument was used for data collection. The instrument contained items on participants' demographic characteristics, TPB constructs (namely attitude, subjective norms, perceived behavioral control, and behavioral intention), and eating behaviors. The data were analyzed by employing SPSS software (v. 16) and through conducting Pearson correlation and multiple linear regression analyses at the significance level of less than 0.05. Results:The constructs of the Theory of Planned Behavior predicted 53.8% and 30% of the variances of behavioral intention and eating behaviors, respectively. The strongest and the weakest predictors of behavioral intention were perceived behavioral control

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Section: Discussionsupporting

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…perceived social pressure for a behavior), and perceived behavioral control (i.e. perceived easiness or difficulty of showing desired behaviors) (8).…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Eating Behaviors Among High-School Students Based on the Constructs of Theory of Planned Behavior

et al. 2016

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Green Travel Behavior in Urban China: Influencing Factors and their Effects

Han

2017

Sustainable Development

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With the ever-increasing number of family cars in China, pollution and traffic jams seriously affect residents' daily lives. Motivating residents to select green travel modes is becoming a major issue. Based on the theory of planned behavior, a framework is developed to identify influencing factors and then examine how these factors affect residential green travel behavior (GTB). An empirical study with 332 valid questionnaires finds that personal factors mediate the relationship between soft environmental factors and green travel intentions (GTIs), whereas hard environmental factors could help GTIs transform into GTB. Such results indicate that the Chinese government needs to improve GTIs by developing related policies and transport systems to motivate people to select green travel modes. GTIs are improved directly by addressing personal factors and indirectly by perfecting green travel policies and campaigns.

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