Measuring stage of change for assessing readiness to increase fruit and vegetable intake among 18- to 24-year-olds.
OBJECTIVE
To examine the appropriateness of the five-stage schema developed for addictive behaviors when applied to nonaddictive behaviors such as fruit and vegetable consumption.


METHODS
A cross-sectional mail survey was conducted.


METHODS
Self-administered questionnaires were mailed to the home addresses of respondents recruited in 10 states and returned upon completion.


METHODS
In all, 116 male and 185 female young adults (response rate = 70%) completed the questionnaires. Most respondents were Caucasian (74.4%) and college students (62.2%).


METHODS
Statistical analyses included analysis of variance with Scheffe's test, Pearson correlation and Cronbach's alpha coefficients, factor analysis, and cluster analysis.


RESULTS
Staging algorithms for fruits and vegetables were developed according to the five-stage schema, and their construct validity was verified by the incremental trend of food intakes. The algorithms identified more than 80% of the subjects as precontemplators, preparers, or maintainers for both food groups. This distribution pattern agreed well with the three-factor solution generated from the stages of change questionnaire, for which internal reliability and validity were confirmed. Seven cluster profiles of the respondents were derived based on the three generated factors and appeared to represent stage subgroupings of those factors. The two food groups shared marked similarities regarding the profiling of the clusters, which was validated by comparing food intake. The results, however, cannot be generalized because of limitations involved in the current sample.


CONCLUSIONS
The original five stages of change and traditional staging measures may need to be adapted and/or extended for dietary change.
Ma
J
J
University of Nebraska-Lincoln, Department of Nutritional Science and Dietetics, 202 Ruth Leverton Hall, Lincoln, NE 68583-0806, USA.
Betts
N M
NM
Horacek
T
T
D000293:Adolescent; D000328:Adult; D000465:Algorithms; D003430:Cross-Sectional Studies; D005247:Feeding Behavior / Q000523:psychology*; D005260:Female; D005638:Fruit; D006293:Health Promotion / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D020377:Self Efficacy; D011795:Surveys and Questionnaires; D014481:United States; D014675:Vegetables