Mobile telephones with an integrated camera can provide a unique mechanism for collecting dietary information that reduces burden on record keepers. Objectives for this study were: (1) to test whether participant's proficiency with the mobile telephone food record (mpFR) improved after training and repeated use, and (2) to measure changes in perceptions regarding use of the mpFR after training and repeated use. Seventy-eight adolescents (26 males, 52 females) ages 11–18 y were recruited to use the mpFR for one or two meals. Proficiency with the mpFR was defined as capturing a useful image for image analysis and self-reported ease of use. Positive changes in perceptions regarding use of the mpFR were assumed to equate to potentially improved proficiency with the mpFR. Participants received instruction for using the mpFR prior to their first meal, and captured an image of their meals before and after eating. Following the first meal, participants took part in an interactive session where they received additional training on capturing images in various snacking situations and responded to questions about user preferences. Changes in the participants' abilities to capture useful images and perceptions about the usability of the mpFR were examined using McNemar, Wilcoxon rank-sum test, and paired t-test. After using the mpFR, the majority of participants (79%) agreed that the software was easy to use. Eleven percent of participants agreed taking images before snacking would be easy. After additional training, the percent increased significantly to 32% (p<.0001). For taking images after snacking, there was also improvement (21% before training and 43% after, p<.0001). Adolescents readily adopt new technologies; however the mpFR design needs to accommodate the lifestyles of its users to ensure useful images and continuous use. Further, these results suggest that additional training in using a new technology may improve the accuracy among users.
Objective: To evaluate adolescents' abilities to identify foods and estimate the portion size of foods consumed in order to inform development of the mobile telephone food record (mpFR). Design: Data were collected from two samples of adolescents (11-18 years). Adolescents in sample 1 participated in one lunch (n 63) and fifty-five of the sixtythree adolescents (87 %) returned for breakfast the next morning. Sample 2 volunteers received all meals and snacks for a 24 h period. At mealtime, sample 1 participants were asked to write down the names of the foods. Sample 2 participants identified foods in an image of their meal 10-14 h postprandial. Adolescents in sample 2 also estimated portion sizes of their breakfast foods and snacks. Results: Sample 1 identified thirty of the thirty-eight food items correctly, and of the misidentified foods all were identified within the correct major food group. For sample 2, eleven of the thirteen food items were identified correctly 100 % of the time. Half of the breakfast and snack foods had at least one portion size estimate within 10 % of the true amount using a variety of measurement descriptors. Conclusions:The results provide evidence that adolescents can correctly identify familiar foods and they can look at an image of their meal and identify the foods in the image up to 14?5 h postprandial. The results of the present study not only inform the development of the mpFR but also provide strong evidence of the use of digital images of eating occasions in research and clinical settings.
The development of a mobile telephone food record (mpFR) in which image analysis and volume estimation data can be indexed with the Food and Nutrient Database for Dietary Studies (FNDDS) has the potential to improve the accuracy of dietary assessment. To validate the mpFR for use with adolescents, a convenience sample of adolescents, aged 11–18 years, was recruited to eat all meals and snacks in a controlled feeding environment over a 24-hour period. Each food item matched a food code in the FNDDS 3.0. The objective of this analysis was to compare the measured energy and protein content of foods to the published values in the FNDDS. Duplicate plates of all meals and snacks were prepared, and samples of 20 foods were individually weighed, homogenized, freeze dried, and analyzed for energy with a bomb calorimeter and for protein with a Dumas nitrogen analyzer. Eleven of the twenty food items had energy values in the FNDDS within ±10% of the measured energy value. The measured energy and protein values from all foods correlated significantly with the energy (r=0.981, P<0.01) and protein (r= 0.911, P<0.01) values in the FNDDS. These results support the use of the FNDDS with the mpFR.
The mobile phone Food Record (mpFR) is a novel diet assessment tool (Six, 2010; Zhu 2009). Zepeda (2008) suggested that use of image‐based food records leads to reduced food intake. However, no quantitative analysis comparing self‐reported energy to expected energy intake (EEI) was reported. Our objective was to investigate the influence of mpFR use on EEI for meals and 24‐hr dietary intake. Distribution of energy intake (breakfast 16%, lunch 27%, dinner 33%, snacks 24%) was derived from results among 8th graders (Dwyer, 2001) and used to determine EEI as a percent of estimated energy requirement (EER). In a controlled setting, 26 boys and 51 girls aged 11–18 y used the mpFR to record meals eaten to satiation. Adolescents ate breakfast (n=70), lunch (n=78), and dinner and snacks (n=15). There was no significant difference between the EER and known energy consumed over 24‐hr (n=15, p = 0.352). Boys consumed significantly less energy from snacks than expected (mean difference 324 kcal, SE 111, p = 0.014). Girls consumed significantly more energy at dinner than expected (mean difference 196 kcal, SE 43, p = 0.044). Those with a BMI for age in the 85–95th percentile ate significantly less energy at lunch than expected (p = 0.047, mean difference 88 kcal). These results suggest that mpFR use does not mitigate behavior change in adolescents. The mpFR holds promise to accurately assess daily energy intake in adolescents.NCI, NIDDK
Mobile telephones with an integrated camera can provide a unique mechanism for collecting dietary information that reduces burden on record keepers. The purpose of this study was to receive feedback from users during the interaction design of a mobile phone food record (mpFR) for adolescents that will eventually translate to an accurate account of daily food and nutrient intakes. A total of 78 adolescents (26 males, 51 females) ages 11‐18 y were recruited to participate in breakfast and lunch meal sessions and provide feedback about the mpFR. Prior to their first meal, all participants received instruction for using the mpFR. Volunteers captured an image of their meals (or snacks) before and after eating using the mpFR. After using the mpFR, the majority of participants (79%) agreed that the software was easy to use. Also, the students participated in a training activity where they received additional instruction on capturing images in various snacking situations. As a result of the additional training, significantly more participants agreed that taking images before snacking would be easy (10% vs 28%, p=0.01), as well as, after snacking (19% vs 38%, p<0.001). Though adolescents readily adopt new technologies, formative evaluation is needed to tailor technology. Further, these results suggest that additional training in using a new technology may improve the accuracy among users.Grant Funding SourceNIH‐NIDDK
Mobile telephones are widely used throughout the world and can provide a unique mechanism for collecting dietary information that reduces burden on record keepers. Our belief is that allowing the user to interact with the mobile phone Food Record (mpFR) after the eating occasion removes one layer of burden while maintaining accuracy for nutrient analysis. The purpose of this study is to investigate adolescents' ability to correctly identify foods up to fourteen hours postprandial when prompted with an image of their meals. Fifteen adolescents (ages 11‐18 y) were provided lunch and dinner meals. The participants were asked to identify each food (fifteen foods total) in the image up to fourteen hours after the respective meal. One hundred percent of participants exactly identified five of the fifteen foods, i.e., milk, spaghetti, peaches, ketchup, and french fries. The other foods were identified within their same respective major food groups. For example, 80% of participants identified lettuce as salad and 33% labeled Coke as soda, pop, or cola. Further probing programmed into the mpFR would lead to an accurate identification of these food items. The results provide evidence that it is feasible to delay user interaction with the mpFR and still obtain accurate food identification.Grant Funding SourceNIH‐NIDDK & NCI
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