Trial reportPloS one2019
Evaluation of the dietary intake data coding process in a clinical setting: Implications for research practice.
Trial report in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- A standardized framework for dietary intake data: implementation and monitoring of the 24-hour dietary recalls in the PROVEN-DIA trial.Frontiers in nutrition · 2026Article
- Efficacy and Safety of Ginseng Berry Extract (SIRTBERRY™) in Treating Andropause Symptoms: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial.The world journal of men's health · 2026Article
- A Novel Mobile App for Personalized Dietary Advice Leveraging Persuasive Technology, Computer Vision, and Cloud Computing: Development and Usability Study.JMIR formative research · 2023Article
- Identifying usual food choices with avocados in a clinical trial cohort of overweight and obese adults in Australia.PloS one · 2023Article
- Article
- Characterisation, procedures and heritability of acute dietary intake in the Twins UK cohort: an observational study.Nutrition journal · 2022Observational
- Perspectives of Dietary Assessment in Human Health and Disease.Nutrients · 2022Article
- Standardised Outcome Reporting for the Nutrition Management of Complex Chronic Disease: A Rapid Review.Nutrients · 2021Review
- Parental and Child Self-Efficacy Explaining Food Intake through Self-Regulation: A Dyadic Prospective Study.Applied psychology. Health and well-being · 2021Article
- Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.Nutrients · 2020Review
- Identifying Usual Food Choice Combinations With Walnuts: Analysis of a 2005-2015 Clinical Trial Cohort of Overweight and Obese Adults.Frontiers in nutrition · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHigh quality dietary intake data is required to support evidence of diet-disease relationships exposed in clinical research. Source data verification may be a useful quality assurance method in this setting. The present pilot study aimed to apply source data verification to evaluate the quality of the data coding process for dietary intake in a clinical trial and to explore potential barriers to data quality in this setting.
methodsUsing a sample of 20 cases from a clinical trial, source data verification was conducted between three sets of data derived documents: transcripts of audio-recorded diet history interviews, matched paper-based diet history forms and outputs from nutrition analysis software. The number of cases and rates of discrepancies between documents were calculated. A total of five in-depth interviews with dietitians collecting and coding dietary data were thematically analysed.
resultsSome 2024 discrepancies were identified. The highest discrepancy rate was 57.49%, and occurred between diet history interviews and nutrition analysis software outputs. Sources of the discrepancies included both quantities and frequencies of food intake. The highest discrepancy rate was for the food group "vegetable products and dishes". In-depth interviews implicated recall bias of trial participants as a cause of discrepancies, but dietitians also acknowledged a possible subconscious influence of having to code reported foods into nutrition analysis software programs.
conclusionThe accuracy of dietary intake data appeared to depend on the level of detailed food data required. More support for participants on reporting consumption, and incorporating supportive tools to guide estimates of food quantities may facilitate a more consistent coding process and improve data quality. This pilot study offers a novel method and an overview of dietary intake data coding measurement errors. These findings may warrant further investigation in a larger sample.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.