Developing Nutrition Label Reading Skills: A Web-Based Practice Approach

BACKGROUND: Nutrition labels offer the information needed to follow Dietary Guidelines for Americans, yet many individuals use labels infrequently or ineffectively due to limited comprehension and the effort required to use them. OBJECTIVE: The objective of our study was to develop and test a Web-based label-reading training tool to improve individuals’ ability to use labels to select more healthful foods. We were particularly interested in determining whether practice can lead to increased accuracy using labels as well as decreased effort, together reflecting greater efficiency. We compared a basic and an enhanced, prior-knowledge version of the tool that contained an additional component, a brief nutrition tutorial. METHODS: Participants were 140 college students with an average age of 20.7 (SD 2.1) years and education 14.6 (SD 1.2) years, who completed 3 sets of practice that were designed to teach them, through repetition and feedback, how to use nutrition labels to select more healthful products. Prior to training, participants in the prior-knowledge group viewed a multimedia nutrition presentation, which those in the basic group did not receive. Mixed-effects models tested for improvement in accuracy and speed with practice, and whether improvements varied by group. RESULTS: The training led to significant increases in average accuracy across the 3 practice sets (averaging 79% [19/24 questions], 92% [22/24], 96% [23/24] respectively, P<.001), as well as decreases in time to complete with mean (SD) values of 8.7 (2.8), 4.6 (1.8), and 4.1 (1.7) seconds, respectively. In block 3, the odds of a correct answer for the prior-knowledge group were 79% higher (odds ratio, OR=1.79, 95% CI 1.1-2.9) than those for the basic group (P=.02). There was no significant difference between the groups in block 2 (P=.89). CONCLUSIONS: Practice led to improvements in nutrition label reading skills that are indicative of early stages of automatic processing. To the extent that automatic processes are at the core of healthy habit change, this may be an efficient way to improve dietary decision-making.