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Franco RZ, Alawadhi B, Fallaize R, et al. A Web-Based Graphical Food Frequency Assessment System: Design, Development and Usability Metrics. JMIR Hum Factors. 2017;4(2):e13doi: 10.2196/humanfactors.7287.
Franco, R. Z., Alawadhi, B., Fallaize, R., Lovegrove, J. A., & Hwang, F. (2017). A Web-Based Graphical Food Frequency Assessment System: Design, Development and Usability Metrics. JMIR human factors, 4(2), e13. https://doi.org/10.2196/humanfactors.7287
Franco, Rodrigo Zenun, et al. "A Web-Based Graphical Food Frequency Assessment System: Design, Development and Usability Metrics." JMIR human factors vol. 4,2 (2017): e13. doi: https://doi.org/10.2196/humanfactors.7287
Franco RZ, Alawadhi B, Fallaize R, Lovegrove JA, Hwang F. A Web-Based Graphical Food Frequency Assessment System: Design, Development and Usability Metrics. JMIR Hum Factors. 2017 May 08;4(2):e13. doi: 10.2196/humanfactors.7287. PMID: 28483746; PMCID: PMC5440732.
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JMIR Hum Factors. 2017 May 08;4(2):e13. doi: 10.2196/humanfactors.7287.

A Web-Based Graphical Food Frequency Assessment System: Design, Development and Usability Metrics.

JMIR human factors

Rodrigo Zenun Franco, Balqees Alawadhi, Rosalind Fallaize, Julie A Lovegrove, Faustina Hwang

Affiliations

  1. Biomedical Engineering, School of Biological Sciences, University of Reading, Reading, United Kingdom.
  2. Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Sciences, University of Reading, Reading, United Kingdom.

PMID: 28483746 PMCID: PMC5440732 DOI: 10.2196/humanfactors.7287

Abstract

BACKGROUND: Food frequency questionnaires (FFQs) are well established in the nutrition field, but there remain important questions around how to develop online tools in a way that can facilitate wider uptake. Also, FFQ user acceptance and evaluation have not been investigated extensively.

OBJECTIVE: This paper presents a Web-based graphical food frequency assessment system that addresses challenges of reproducibility, scalability, mobile friendliness, security, and usability and also presents the utilization metrics and user feedback from a deployment study.

METHODS: The application design employs a single-page application Web architecture with back-end services (database, authentication, and authorization) provided by Google Firebase's free plan. Its design and responsiveness take advantage of the Bootstrap framework. The FFQ was deployed in Kuwait as part of the EatWellQ8 study during 2016. The EatWellQ8 FFQ contains 146 food items (including drinks). Participants were recruited in Kuwait without financial incentive. Completion time was based on browser timestamps and usability was measured using the System Usability Scale (SUS), scoring between 0 and 100. Products with a SUS higher than 70 are considered to be good.

RESULTS: A total of 235 participants created accounts in the system, and 163 completed the FFQ. Of those 163 participants, 142 reported their gender (93 female, 49 male) and 144 reported their date of birth (mean age of 35 years, range from 18-65 years). The mean completion time for all FFQs (n=163), excluding periods of interruption, was 14.2 minutes (95% CI 13.3-15.1 minutes). Female participants (n=93) completed in 14.1 minutes (95% CI 12.9-15.3 minutes) and male participants (n=49) completed in 14.3 minutes (95% CI 12.6-15.9 minutes). Participants using laptops or desktops (n=69) completed the FFQ in an average of 13.9 minutes (95% CI 12.6-15.1 minutes) and participants using smartphones or tablets (n=91) completed in an average of 14.5 minutes (95% CI 13.2-15.8 minutes). The median SUS score (n=141) was 75.0 (interquartile range [IQR] 12.5), and 84% of the participants who completed the SUS classified the system either "good" (n=50) or "excellent" (n=69). Considering only participants using smartphones or tablets (n=80), the median score was 72.5 (IQR 12.5), slightly below the SUS median for desktops and laptops (n=58), which was 75.0 (IQR 12.5). No significant differences were found between genders or age groups (below and above the median) for the SUS or completion time.

CONCLUSIONS: Taking into account all the requirements, the deployment used professional cloud computing at no cost, and the resulting system had good user acceptance. The results for smartphones/tablets were comparable with desktops/laptops. This work has potential to promote wider uptake of online tools that can assess dietary intake at scale.

©Rodrigo Zenun Franco, Balqees Alawadhi, Rosalind Fallaize, Julie A Lovegrove, Faustina Hwang. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 08.05.2017.

Keywords: FFQ; SUS; dietary intake; food frequency questionnaire; nutrition assessment; nutrition informatics; personalized nutrition; usability

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