Using the Integrative Model of Behavioral Prediction to Predict Vegetable Subgroup Consumption among College Students

Abstract

ABSTRACTBackground: The United States Department of Agriculture (USDA) currently recommends that young adults consume 2.5–3 cups of vegetables daily, while also providing weekly recommendations for 5 vegetable subgroups: dark green, red and orange, beans and peas, starchy, and other. Purpose: The purpose of this study was to explore theory-based determinants of consumption for 5 USDA vegetable subgroups among college students. Methods: Operationalizing the integrative model of behavioral prediction (IMB), a survey was developed and distributed online to college students (n = 386). Linear regression models were used to predict behavioral intentions of each subgroup with attitudes, perceived norms, and perceived behavioral control (PBC), and logistic regression models predicted whether students met (or did not meet) recommendations, with intentions and PBC. Results: Collectively, IBM constructs accounted for 40.5%–54.6% of the variance of intentions and 14.2%–44.3% of the variance of each subgroup. Discussion: Research exploring determinants of vegetable subgroups is rarely done. This study demonstrated that young adults hold different beliefs about subgroups, and theory-based determinants of subgroups vary. Translation to Health Education Practice: Vegetable consumption is associated with many health benefits, and understanding significant theory-based determinants of each subgroup can help future practitioners develop targeted and tailored programs that promote vegetable quantity and variety.