USING THE INTEGRATIVE MODEL TO PREDICT VEGETABLE SUBGROUP CONSUMPTION AMONG COLLEGE STUDENTS
dc.contributor.advisor | Branscum, Paul | |
dc.contributor.author | Senkowski, Valerie | |
dc.contributor.committeeMember | Maness, Sarah | |
dc.contributor.committeeMember | Larson, Daniel | |
dc.date.accessioned | 2016-05-13T20:03:22Z | |
dc.date.available | 2016-05-13T20:03:22Z | |
dc.date.issued | 2016 | |
dc.date.manuscript | 2016 | |
dc.description.abstract | Although eating the recommended amount of vegetables is associated with many health benefits, vegetable consumption is low among college students in the United States. “Vegetable consumption” is a behavioral category, consisting of consuming a wide range of foods, which the United State Department of Agriculture (USDA) has further divided into 5 vegetable subgroups: dark green vegetables, red and orange vegetables, beans and peas, starchy vegetables, and other vegetables. While vegetable consumption is typically studied as a single behavior, understanding the behavioral determinants for consuming defined vegetable subgroups, such as those developed by the USDA, may be more beneficial, as it would provide targeted information about these foods, from which theory based interventions can be developed. Therefore, this purpose of this study was to utilize the Integrative Model (IM) to predict the intentions and behaviors of consuming each vegetable subgroup among college students. | en_US |
dc.identifier.uri | http://hdl.handle.net/11244/34685 | |
dc.language | en_US | en_US |
dc.subject | subgroup | en_US |
dc.subject | Integrative Model | en_US |
dc.subject | vegetable | en_US |
dc.subject | college | en_US |
dc.thesis.degree | Master of Science | en_US |
dc.title | USING THE INTEGRATIVE MODEL TO PREDICT VEGETABLE SUBGROUP CONSUMPTION AMONG COLLEGE STUDENTS | en_US |
ou.group | College of Arts and Sciences::Department of Health and Exercise Science | en_US |
Files
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 1.72 KB
- Format:
- Item-specific license agreed upon to submission
- Description: