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Predicting fruit consumption

Authors :
Sander Matthijs Eggers
Liesbeth van Osch
Maartje M. van Stralen
Hein de Vries
Lilian Lechner
Public and occupational health
EMGO - Lifestyle, overweight and diabetes
Academic Field Psychology
Health promotion
RS: CAPHRI School for Public Health and Primary Care
RS: CAPHRI - Health Promotion and Health Communication
EMGO+ - Lifestyle, Overweight and Diabetes
Source :
de Vries, H, Eggers, S M, Lechner, L, van Osch, L & van Stralen, M M 2014, ' Predicting fruit consumption: the role of habits, previous behavior and mediation effects ', BMC Public Health, vol. 14, 730 . https://doi.org/10.1186/1471-2458-14-730, de Vries, H, Eggers, S M, Lechner, L, van Osch, L & van Stralen, M M 2014, ' Predicting fruit consumption : the role of habits, previous behavior and mediation effects ', BMC Public Health, vol. 14, 730 . https://doi.org/10.1186/1471-2458-14-730, BMC Public Health, 14:730. BioMed Central, BMC Public Health, 14:730. BioMed Central Ltd., BMC Public Health, 14:730. BioMed Central Ltd, BMC Public Health
Publication Year :
2014

Abstract

Background: This study assessed the role of habits and previous behavior in predicting fruit consumption as well as their additional predictive contribution besides socio-demographic and motivational factors. In the literature, habits are proposed as a stable construct that needs to be controlled for in longitudinal analyses that predict behavior. The aim of this study is to provide empirical evidence for the inclusion of either previous behavior or habits. Methods. A random sample of 806 Dutch adults (>18 years) was invited by an online survey panel of a private research company to participate in an online study on fruit consumption. A longitudinal design (N = 574) was used with assessments at baseline and after one (T2) and two months (T3). Multivariate linear regression analysis was used to assess the differential value of habit and previous behavior in the prediction of fruit consumption. Results: Eighty percent of habit strength could be explained by habit strength one month earlier, and 64% of fruit consumption could be explained by fruit consumption one month earlier. Regression analyses revealed that the model with motivational constructs explained 41% of the behavioral variance at T2 and 38% at T3. The addition of previous behavior and habit increased the explained variance up to 66% at T2 and to 59% at T3. Inclusion of these factors resulted in non-significant contributions of the motivational constructs. Furthermore, our findings showed that the effect of habit strength on future behavior was to a large extent mediated by previous behavior. Conclusions: Both habit and previous behavior are important as predictors of future behavior, and as educational objectives for behavior change programs. Our results revealed less stability for the constructs over time than expected. Habit strength was to a large extent mediated by previous behavior and our results do not strongly suggest a need for the inclusion of both constructs. Future research needs to assess the conditions that determine direct influences of both previous behavior and habit, since these influences may differ per type of health behavior, per context stability in which the behavior is performed, and per time frame used for predicting future behavior. © 2014 de Vries et al.; licensee BioMed Central Ltd.

Details

Language :
English
ISSN :
14712458
Volume :
14
Database :
OpenAIRE
Journal :
BMC Public Health
Accession number :
edsair.doi.dedup.....300a528e45193a53c1209779e86a1749