Literature DB >> 17524721

Formative research of a quick list for an automated self-administered 24-hour dietary recall.

Amy F Subar1, Frances E Thompson, Nancy Potischman, Barbara H Forsyth, Richard Buday, Debbie Richards, Suzanne McNutt, Stephen G Hull, Patricia M Guenther, Arthur Schatzkin, Tom Baranowski.   

Abstract

Twenty-four-hour dietary recalls are used to collect high-quality dietary data. Because they require highly trained interviewers, recalls are expensive and impractical for large-scale nutrition research, leading to the use of food frequency questionnaires. We are developing a computer-based, self-administered 24-hour dietary recall for use by adults. Our goal is an easy-to-use, low-cost, publicly available, Web-enabled instrument that will include elements of the Automated Multiple Pass Method developed by the US Department of Agriculture, which uses five passes to enhance recall. The initial pass is called the "quick list" and allows respondents to report foods consumed the previous day freely, in any order, and without detail. Using a crossover design, we conducted initial formative pilot testing among 18 adults in a self-administered computer environment. We tested two versions of a "quick list" (the first Automated Multiple Pass Method pass) for remembering foods consumed the previous day: "unstructured" and "meal-based." Respondents showed a strong preference for the meal-based version (13 of 18), although positive features of both were identified. Chronological reporting was most common, although many foods were sporadically reported out of order. Versions did not appreciably differ in number of foods reported, moved, or deleted. Usability issues and preferences were also identified. If these developmental efforts prove successful, the use of affordable automated recalls could be valuable in clarifying diet-disease associations in observational epidemiologic studies and measuring dietary compliance in clinical trials. This pilot work illustrates the usefulness of formative cognitive and usability testing for questionnaire and software development.

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Year:  2007        PMID: 17524721     DOI: 10.1016/j.jada.2007.03.007

Source DB:  PubMed          Journal:  J Am Diet Assoc        ISSN: 0002-8223


  49 in total

1.  Stable nitrogen and carbon isotope ratios indicate traditional and market food intake in an indigenous circumpolar population.

Authors:  Sarah H Nash; Andrea Bersamin; Alan R Kristal; Scarlett E Hopkins; Rebecca S Church; Renee L Pasker; Bret R Luick; Gerald V Mohatt; Bert B Boyer; Diane M O'Brien
Journal:  J Nutr       Date:  2011-12-07       Impact factor: 4.798

2.  Taking advantage of the strengths of 2 different dietary assessment instruments to improve intake estimates for nutritional epidemiology.

Authors:  Raymond J Carroll; Douglas Midthune; Amy F Subar; Marina Shumakovich; Laurence S Freedman; Frances E Thompson; Victor Kipnis
Journal:  Am J Epidemiol       Date:  2012-01-24       Impact factor: 4.897

3.  Web-enabled and improved software tools and data are needed to measure nutrient intakes and physical activity for personalized health research.

Authors:  Phyllis J Stumbo; Rick Weiss; John W Newman; Jean A Pennington; Katherine L Tucker; Paddy L Wiesenfeld; Anne-Kathrin Illner; David M Klurfeld; Jim Kaput
Journal:  J Nutr       Date:  2010-10-27       Impact factor: 4.798

4.  Reliability of 24-Hour Dietary Recalls as a Measure of Diet in African-American Youth.

Authors:  Sara M St George; M Lee Van Horn; Hannah G Lawman; Dawn K Wilson
Journal:  J Acad Nutr Diet       Date:  2016-07-06       Impact factor: 4.910

5.  Evaluating the feasibility of utilizing the Automated Self-administered 24-hour (ASA24) dietary recall in a sample of multiethnic older adults.

Authors:  Reynolette Ettienne-Gittens; Carol J Boushey; Donna Au; Suzanne P Murphy; Unhee Lim; Lynne Wilkens
Journal:  Procedia Food Sci       Date:  2013-05-29

Review 6.  Biomarkers in nutritional epidemiology: applications, needs and new horizons.

Authors:  Mazda Jenab; Nadia Slimani; Magda Bictash; Pietro Ferrari; Sheila A Bingham
Journal:  Hum Genet       Date:  2009-04-09       Impact factor: 4.132

7.  Design and implementation of a randomized controlled social and mobile weight loss trial for young adults (project SMART).

Authors:  K Patrick; S J Marshall; E P Davila; J K Kolodziejczyk; J H Fowler; K J Calfas; J S Huang; C L Rock; W G Griswold; A Gupta; G Merchant; G J Norman; F Raab; M C Donohue; B J Fogg; T N Robinson
Journal:  Contemp Clin Trials       Date:  2013-11-09       Impact factor: 2.226

8.  Grains are similarly categorized by 8- to 13-year-old children.

Authors:  Alicia Beltran; Karina Knight Sepulveda; Kathy Watson; Tom Baranowski; Janice Baranowski; Noemi Islam; Mariam Missaghian
Journal:  J Am Diet Assoc       Date:  2008-11

9.  Diverse food items are similarly categorized by 8- to 13-year-old children.

Authors:  Alicia Beltran; Karina Knight Sepulveda; Kathy Watson; Tom Baranowski; Janice Baranowski; Noemi Islam; Mariam Missaghian
Journal:  J Nutr Educ Behav       Date:  2008 May-Jun       Impact factor: 3.045

10.  Fruit and vegetables are similarly categorised by 8-13-year-old children.

Authors:  Karina Knight Sepulveda; Alicia Beltran; Kathy Watson; Tom Baranowski; Janice Baranowski; Noemi Islam; Mariam Missaghian
Journal:  Public Health Nutr       Date:  2008-06-19       Impact factor: 4.022

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