Conventional analyses of data from dietary validation studies may misestimate reporting accuracy: illustration from a study of the effect of interview modality on children's reporting accuracy
Related Experiment Video
Updated: Jul 16, 2026

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
Published on: May 3, 2016
Albert F Smith1, Suzanne Domel Baxter, James W Hardin
1Department of Psychology, Cleveland State University, 2121 Euclid Avenue, Cleveland, OH 44115, USA. a.f.smith@csuohio.edu
Objective:
To compare two approaches to analysing energy- and nutrient-converted data from dietary validation (and relative validation) studies - conventional analyses, in which the accuracy of reported items is not ascertained, and reporting-error-sensitive analyses, in which reported items are classified as matches (items actually eaten) or intrusions (items not actually eaten), and reported amounts are classified as corresponding or overreported.
Design:
Subjects were observed eating school breakfast and lunch, and interviewed that evening about that day's intake. For conventional analyses, reference and reported information were converted to energy and macronutrients; then t-tests, correlation coefficients and report rates (reported/reference) were calculated. For reporting error-sensitive analyses, reported items were classified as matches or intrusions, reported amounts were classified as corresponding or overreported, and correspondence rates (corresponding amount/reference amount) and inflation ratios (overreported amount/reference amount) were calculated.
Subjects:
Sixty-nine fourth-grade children (35 girls) from 10 elementary schools in Georgia (USA).
Results:
For energy and each macronutrient, conventional analyses found that reported amounts were significantly less than reference amounts (every P < 0.021; paired t-tests); correlations between reported and reference amounts exceeded 0.52 (every P < 0.001); and median report rates ranged from 76% to 95%. Analyses sensitive to reporting errors found median correspondence rates between 67% and 79%, and that median inflation ratios, which ranged from 7% to 17%, differed significantly from 0 (every P < 0.0001; sign tests).
Conclusions:
Conventional analyses of energy and nutrient data from dietary reporting validation (and relative validation) studies may overestimate accuracy and mask the complexity of dietary reporting error.
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