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      Online dietary intake assessment using a graphical food frequency app (eNutri): Usability metrics from the EatWellUK study

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          Abstract

          Background

          With widespread use of the internet, lifestyle and dietary data collection can now be facilitated using online questionnaires as opposed to paper versions. We have developed a graphical food frequency assessment app (eNutri), which is able to assess dietary intake using a validated food frequency questionnaire (FFQ) and provide personalised nutrition advice. FFQ user acceptance and evaluation have not been investigated extensively and only a few studies involving user acceptance of nutrition assessment and advice apps by older adults are published.

          Methods

          A formative study with 20 participants (including n = 10 ≥60 years) assessed the suitability of this app for adults and investigated improvements to its usability. The outcomes of this formative study were applied to the final version of the application, which was deployed in an online study (EatWellUK) with 324 participants (including n = 53 ≥60 years) in the UK, using different devices (smartphones, tablets and laptops/desktops). Completion times were based on browser timestamps and usability was measured using the System Usability Scale (SUS), scoring between 0 and 100. Products with a SUS score higher than 70 are considered to be good.

          Results

          In the EatWellUK study, SUS score median (n = 322) was 77.5 (IQR 15.0). Out of the 322 SUS questionnaire completions, 321 device screen sizes were detected by the app. Grouped by device screen size, small (n = 92), medium (n = 38) and large (n = 191) screens received median SUS scores of 77.5 (IQR 15.0), 75.0 (IQR 19.4) and 77.5 (IQR 16.25), respectively. The median SUS scores from younger (n = 268) and older participants (n = 53) were the same. The FFQ contained 157 food items, and the mean completion time was 13.1 minutes (95% CI 12.6–13.7 minutes). Small, medium and large screen devices resulted in completion times of 11.7 minutes (95% CI 10.9–12.6 minutes), 14.4 minutes (95% CI 12.9–15.9 minutes) and 13.6 minutes (95% CI 12.8–14.3 minutes), respectively.

          Conclusions

          The overall median SUS score of 77.5 and overall mean completion time of 13.3 minutes indicate good overall usability, and equally, comparable SUS scores and completion times across small, medium and large screen sizes indicates good usability across devices. This work is a step toward the promotion of wider uptake of online apps that can provide online dietary intake assessment at-scale, with the aim of addressing pressing epidemiological challenges.

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          Most cited references18

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          Online Dietary Intake Estimation: Reproducibility and Validity of the Food4Me Food Frequency Questionnaire Against a 4-Day Weighed Food Record

          Background Advances in nutritional assessment are continuing to embrace developments in computer technology. The online Food4Me food frequency questionnaire (FFQ) was created as an electronic system for the collection of nutrient intake data. To ensure its accuracy in assessing both nutrient and food group intake, further validation against data obtained using a reliable, but independent, instrument and assessment of its reproducibility are required. Objective The aim was to assess the reproducibility and validity of the Food4Me FFQ against a 4-day weighed food record (WFR). Methods Reproducibility of the Food4Me FFQ was assessed using test-retest methodology by asking participants to complete the FFQ on 2 occasions 4 weeks apart. To assess the validity of the Food4Me FFQ against the 4-day WFR, half the participants were also asked to complete a 4-day WFR 1 week after the first administration of the Food4Me FFQ. Level of agreement between nutrient and food group intakes estimated by the repeated Food4Me FFQ and the Food4Me FFQ and 4-day WFR were evaluated using Bland-Altman methodology and classification into quartiles of daily intake. Crude unadjusted correlation coefficients were also calculated for nutrient and food group intakes. Results In total, 100 people participated in the assessment of reproducibility (mean age 32, SD 12 years), and 49 of these (mean age 27, SD 8 years) also took part in the assessment of validity. Crude unadjusted correlations for repeated Food4Me FFQ ranged from .65 (vitamin D) to .90 (alcohol). The mean cross-classification into “exact agreement plus adjacent” was 92% for both nutrient and food group intakes, and Bland-Altman plots showed good agreement for energy-adjusted macronutrient intakes. Agreement between the Food4Me FFQ and 4-day WFR varied, with crude unadjusted correlations ranging from .23 (vitamin D) to .65 (protein, % total energy) for nutrient intakes and .11 (soups, sauces and miscellaneous foods) to .73 (yogurts) for food group intake. The mean cross-classification into “exact agreement plus adjacent” was 80% and 78% for nutrient and food group intake, respectively. There were no significant differences between energy intakes estimated using the Food4Me FFQ and 4-day WFR, and Bland-Altman plots showed good agreement for both energy and energy-controlled nutrient intakes. Conclusions The results demonstrate that the online Food4Me FFQ is reproducible for assessing nutrient and food group intake and has moderate agreement with the 4-day WFR for assessing energy and energy-adjusted nutrient intakes. The Food4Me FFQ is a suitable online tool for assessing dietary intake in healthy adults.
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            Validity and reproducibility of a web-based, self-administered food frequency questionnaire.

            To assess the validity and the reproducibility of a newly developed web-based, self-administered food frequency questionnaire (web-FFQ). A total of 74 healthy subjects (34 men and 40 women) from the Québec City metropolitan area were asked to complete, in random order, the web-FFQ, a validated interviewer-administered FFQ (IA-FFQ) and a 3-day food record (3-day FR). Mean intakes of 17/22 nutrients assessed between the web-FFQ and the 3-day FR were not significantly different (differences <10%, P≥0.11). Sex and energy-adjusted de-attenuated Pearson correlation coefficients for each nutrient varied from 0.12-0.98 (mean R=0.55, 95% confidence interval 0.46; 0.63) between the web-FFQ and the 3-day FR. All correlations were significant (P≤0.01) and above 0.34 (mean R=0.59, 95% confidence interval 0.54; 0.65) between the web-FFQ and the IA-FFQ, except for sodium (R=0.17, P=0.14). Cross-classification analysis revealed that on average, 77% of subjects were classified in the same or adjacent quartile of nutrient intake between the web-FFQ and the 3-day FR. Correlation coefficients for reproducibility of the web-FFQ tested 4-6 weeks apart in the same individuals were all equal or above 0.48 (P≤0.0001; mean R=0.72, 95% confidence interval 0.68; 0.76). More than 90% of the subjects were classified in the same or adjacent quartile between the two administrations of the web-FFQ, while only 0.8% was misclassified. These data demonstrate that the newly developed web-based FFQ appears to have reasonable validity and good reproducibility for assessing nutrient intakes at the group and individual levels in a population of healthy adults.
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              Evaluation of web-based, self-administered, graphical food frequency questionnaire.

              Computer-administered food frequency questionnaires (FFQs) can address limitations inherent in paper questionnaires by allowing very complex skip patterns, portion size estimation based on food pictures, and real-time error checking. We evaluated a web-based FFQ, the Graphical Food Frequency System (GraFFS). Participants completed the GraFFS, six telephone-administered 24-hour dietary recalls over the next 12 weeks, followed by a second GraFFS. Participants were 40 men and 34 women, aged 18 to 69 years, living in the Columbus, OH, area. Intakes of energy, macronutrients, and 17 micronutrients/food components were estimated from the GraFFS and the mean of all recalls. Bias (second GraFFS minus recalls) was -9%, -5%, +4%, and -4% for energy and percentages of energy from fat, carbohydrate, and protein, respectively. De-attenuated, energy-adjusted correlations (intermethod reliability) between the recalls and the second GraFFS for fat, carbohydrate, protein, and alcohol were 0.82, 0.79, 0.67, and 0.90, respectively; for micronutrients/food components the median was 0.61 and ranged from 0.40 for zinc to 0.92 for beta carotene. The correlations between the two administrations of the GraFFS (test-retest reliability) for fat, carbohydrate, protein, and alcohol were 0.60, 0.63, 0.73, and 0.87, respectively; among micronutrients/food components the median was 0.67 and ranged from 0.49 for vitamin B-12 to 0.82 for fiber. The measurement characteristics of the GraFFS were at least as good as those reported for most paper FFQs, and its high intermethod reliability suggests that further development of computer-administered FFQs is warranted.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                10 August 2018
                2018
                : 13
                : 8
                : e0202006
                Affiliations
                [1 ] Biomedical Engineering Section, School of Biological Sciences, University of Reading, Reading, United Kingdom
                [2 ] Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, United Kingdom
                McMaster University, CANADA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-1998-4367
                Article
                PONE-D-18-00314
                10.1371/journal.pone.0202006
                6086444
                30096211
                3389e12a-daf9-4ac5-870a-11028a6009be
                © 2018 Zenun Franco et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 4 January 2018
                : 25 July 2018
                Page count
                Figures: 3, Tables: 2, Pages: 13
                Funding
                Funded by: National Council of Technological and Scientific Development (CNPq)
                Award Recipient :
                Rodrigo Zenun Franco is sponsored by the National Council of Technological and Scientific Development (CNPq) from the Brazilian government, via the Science without Borders program. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Computer and Information Sciences
                Computer Software
                Apps
                Research and Analysis Methods
                Research Design
                Survey Research
                Questionnaires
                Computer and Information Sciences
                Computer Networks
                Internet
                Biology and Life Sciences
                Nutrition
                Medicine and Health Sciences
                Nutrition
                People and Places
                Population Groupings
                Age Groups
                Elderly
                Engineering and Technology
                Electronics
                Consumer Electronics
                Engineering and Technology
                Equipment
                Communication Equipment
                Cell Phones
                Medicine and Health Sciences
                Public and Occupational Health
                Physical Activity
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. eNutri app source code is publicly available (MIT License) in http://github.com/rodrigozenun/enutri.

                Uncategorized
                Uncategorized

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