Alarming reports suggest rates of obesity in children have tripled in recent decades, and many do not meet the USDA’s daily dietary recommendations (Centers for Disease Control, 2008). Other research cites that many students lack nutritious food choices in their schools and communities (Larson, Story & Nelson, 2009; Zenk et al., 2011). Some studies have investigated mobile technologies to support learning in schools (Bausell, 2008; Watterson, 2012), yet little research examines how technologies influence health-related behaviors. The purpose of this pilot study was to examine how a mobile health application ("app") designed using self-determination theory and nutrition education lessons influenced students’ nutrition confidence.
Method:
Participants included 61 first- and second-grade students in a metropolitan elementary school in the southeastern U.S. Students were randomly assigned to an experimental or control group. Parental consent and student assent were obtained before collecting data. Students’ confidence of fruit/vegetable intake was measured before and after intervention using a modified Patient-Centered Assessment and Counseling for Exercise (PACE, 2001) instrument. Participants logged food intake (breakfast and lunch) using the AFIT application twice per week for eight weeks. Students in the experimental group participated in two 30-minute lessons covering content about fruits, vegetables, portions and serving sizes. Classroom teachers were provided the lessons at study completion.
Analysis/Results:
We used the 2 (treatment-control) by 2 (pre-post) analysis of variance (ANOVA) with repeated measures to examine the main effect of the treatment, time, and the interactions between the two factors. The repeated-measures ANOVA revealed a non-significant main effect for the treatment conditions, F (1, 59) = .395, p = .5321, η2p = .007. The test of within-subjects effects also suggested a non-significant effect for time, F (1, 59) = .348, p = .558, η2p = .006. In addition, the results also showed a non-significant effect of interaction between time and treatment, F (1, 59) = .415, p = .522, η2p = .007. Overall, the results indicate that there is no significant difference between students’ pre- and post-tests regardless of the experimental conditions.
Conclusions:
This study compared the influence of the AFIT app on nutrition confidence with supplemental lessons with students only using the app. Lack of statistical significance suggests the app may be sufficient for introducing content and measuring students’ confidence for fruit and vegetable intake. Further research should investigate additional psychosocial factors regarding nutrition behaviors, and best practices when using mobile technology to promote healthy behaviors during childhood.