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Importance of user interaction with automated dietary assessment methods

European Journal of Clinical Nutrition volume 66, page 648 (2012)Cite this article

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The utility of using images, as described by Arab et al.,1 which uses automated image-capture to aid completion of a web-based dietary recall to enhance recall of food and beverage intakes, is indeed promising. We have verified that individuals can correctly identify foods and beverages using an image up to 14 h after an eating occasion.2 However, we do want to clarify an incorrect description of our system described on page 1157 in Arab et al.1 The system in Boushey et al.3 and Six et al.4 referred to as the Mobile Phone Food Record (mpFR) is automated with image upload followed by ‘decoding of images by automation’. In addition, the system also includes a user confirmation step, which Arab et al.1 implied was not a part of the mpFR. The user provides the final confirmation of foods and beverages identified by the automated system; thus, the images are used directly by the participant. This step is clearly illustrated in the mpFR diagram4 and in the process diagram.2 This step is important because an automated system would need a method to identify new foods (whether new to the system or new to market), as well as correct foods that are misclassified. In addition to the advantages of soliciting contextual help from the user as described by Arab et al.,1 this step provides a novel approach for selecting foods to add to an existing food composition database.

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References

  1. Arab L, Estrin D, Kim DH, Burke J, Goldman J . Feasibility test of an automated image-capture method to aid dietary recall. Eur J Clin Nutr 2011; 65, 1156–1162.

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  2. Schap TE, Six BL, Delp EJ, Ebert DS, Kerr DA, Boushey CJ . Adolescents in the United States can identify familiar foods at the time of consumption and when prompted with an image 14 h postprandial, but poorly estimate portions. Public Health Nutr 2011; 14, 1184–1191.

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  3. Boushey CJ, Kerr DA, Wright J, Lutes KD, Ebert DS, Delp EJ . Use of technology in children's dietary assessment. Eur J Clin Nutr 2009; 63, S50–S57.

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  4. Six BL, Schap TE, Zhu FM, Mariappan A, Bosch M, Delp EJ et al. Evidence-based development of a mobile telephone food record. J Am Diet Assoc 2010; 110, 74–79.

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Authors and Affiliations

  1. Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA

    C J Boushey

  2. School of Public Health, Curtin University of Technology, Perth, Western Australia, Australia

    D A Kerr

  3. Department of Nutrition Science, Purdue University, West Lafayette, IN, USA

    T E Schap

  4. Health and Human Sciences Extension Educator, Lawrence County Extension Office, Purdue University, West Lafayette, IN, USA

    B L Daugherty

Authors
  1. C J Boushey
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  2. D A Kerr
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  3. T E Schap
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  4. B L Daugherty
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Corresponding author

Correspondence to C J Boushey.

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The authors declare no conflict of interest.

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Boushey, C., Kerr, D., Schap, T. et al. Importance of user interaction with automated dietary assessment methods. Eur J Clin Nutr 66, 648 (2012). https://doi.org/10.1038/ejcn.2012.14

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  • DOI: https://doi.org/10.1038/ejcn.2012.14

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