Predicting sugar consumption : Application of an integrated dual-process, dual-phase model
Hagger, M., Trost, N., Keech, J., Chan, D. K. C., & Hamilton, K. (2017). Predicting sugar consumption : Application of an integrated dual-process, dual-phase model. Appetite, 116, 147-156. doi:10.1016/j.appet.2017.04.032
© 2017 Elsevier Ltd. This is a final draft version of an article whose final and definitive form has been published by Elsevier. Published in this repository with the kind permission of the publisher.
Excess consumption of added dietary sugars is related to multiple metabolic problems and adverse health conditions. Identifying the modifiable social cognitive and motivational constructs that predict sugar consumption is important to inform behavioral interventions aimed at reducing sugar intake. We tested the efficacy of an integrated dual-process, dual-phase model derived from multiple theories to predict sugar consumption. Using a prospective design, university students (N = 90) completed initial measures of the reflective (autonomous and controlled motivation, intentions, attitudes, subjective norm, perceived behavioral control), impulsive (implicit attitudes), volitional (action and coping planning), and behavioral (past sugar consumption) components of the proposed model. Self-reported sugar consumption was measured two weeks later. A structural equation model revealed that intentions, implicit attitudes, and, indirectly, autonomous motivation to reduce sugar consumption had small, significant effects on sugar consumption. Attitudes, subjective norm, and, indirectly, autonomous motivation to reduce sugar consumption predicted intentions. There were no effects of the planning constructs. Model effects were independent of the effects of past sugar consumption. The model identified the relative contribution of reflective and impulsive components in predicting sugar consumption. Given the prominent role of the impulsive component, interventions that assist individuals in managing cues-to-action and behavioral monitoring are likely to be effective in regulating sugar consumption. ...
MetadataShow full item record
- Liikuntatieteiden tiedekunta 
Showing items with similar title or keywords.
Hamilton, Kyra; Gibbs, Isabelle; Keech, Jacob J.; Hagger, Martin S. (The British Psychological Society; John Wiley & Sons, 2020)Objectives: University students commonly engage in heavy episodic drinking (HED), which contributes to injury risk, deleterious educational outcomes, and economic costs. Identification of the determinants of this risky ...
Predicting fruit and vegetable consumption in long-haul heavy goods vehicle drivers : application of a multi-theory, dual-phase model and the contribution of past behaviour Brown, D.J.; Hagger, Martin; Morrissey, S.; Hamilton, K. (Elsevier BV, 2018)Fruit and vegetable intake is insufficient in industrialized nations and long-haul heavy goods vehicle (HGV) drivers are considered a particularly at-risk group. The aim of the current study was to test the effectiveness ...
The trans-contextual model of motivation : an integrated multi-theory model to explain the processes of motivational transfer across context Hagger, Martin (University of Jyväskylä, 2014)
Phipps, Daniel J.; Hagger, Martin S.; Hamilton, Kyra (Elsevier, 2020)Excess intake of ‘free sugars’ is a key predictor of chronic disease, obesity, and dental ill health. Given the importance of determining modifiable predictors of free sugar-related dietary behaviors, we applied the ...
Predicting physical activity change in cancer survivors : an application of the Health Action Process Approach Hardcastle, Sarah J.; Maxwell-Smith, Chloe; Hagger, Martin S. (Springer, 2021)Purpose Previous research has not examined the utility of the Health Action Process Approach (HAPA) to predict physical activity (PA) change in cancer survivors. The aim of the study was to investigate the efficacy of a ...