Predictors for Reporting of Dietary Assessment Methods in Food-based Randomized Controlled Trials over a Ten-year Period

Probst, Yasmine; Zammit, Gail

doi:10.1080/10408398.2013.816653

Cited by 10 publications

(8 citation statements)

References 282 publications

(203 reference statements)

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“…Relatively few studies were found and included in this review, limiting the conclusions that can be drawn between dietary intakes and symptoms. The lack of a standardised approach to dietary assessment methods with respect to those included studies in which primary outcome measures related to food measurement limited any comparison between studies, and this issue has been identified previously in the dietary methodology literature, even in relation to food‐based randomised trials . However, the present review used a standardised approach, which included a published methodology, searching a variety of online databases, assessed study quality using recognised tools and was completed in accordance with the PRISMA statement .…”

Section: Limitationsmentioning

confidence: 99%

Food and functional dyspepsia: a systematic review

Duncanson

Talley

Walker

et al. 2017

J Human Nutrition Diet

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Wheat and dietary fats may play key roles in the generation of FD symptoms and reduction or withdrawal eased symptoms. Randomised trials investigating the roles of gluten, FODMAPs (fermentable oligosaccharide, disaccharide, monosaccharide and polyols) and high fat ingestion and naturally occurring food chemicals in the generation of functional dyspepsia symptoms are warranted and further investigation of the mechanisms is now required.

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Section: Limitationsmentioning

confidence: 99%

Food and functional dyspepsia: a systematic review

Duncanson

Talley

Walker

et al. 2017

J Human Nutrition Diet

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“…Being able to complete the app-based task at home on a smartphone possibly offset the impact of participants wanting to provide socially desirable responses during the interviews. The increasing use of this methodology in food-based research studies reflects the shift toward patient-oriented data capture, as daily diaries may help monitor changes in eating behaviors over time [ 24 ].…”

Section: Discussionmentioning

confidence: 99%

Perceptions and Experiences of People with Obesity and Type 2 Diabetes Around Appetite and Eating Behaviors: A Qualitative Study

Poon,

OHara,

Kendal

et al. 2024

Adv Ther

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Introduction Chronic weight management and treatments for type 2 diabetes (T2D) involve a combination of lifestyle-based (diet, exercise) and pharmaceutical interventions. In people with obesity or T2D, understanding the impact of drivers/triggers on appetite and eating behaviors can be crucial to successful medical management. This study aimed to characterize perceptions and experiences regarding appetite and eating behaviors among people with obesity or T2D and identify drivers/triggers of food choices. Methods This non-interventional, cross-sectional, qualitative study utilized semi-structured concept elicitation interviews to explore the perceptions of people with obesity and/or T2D around appetite, eating behaviors and drivers/triggers of food choices. Adult US residents (≥ 18 years) with stable body weight (± 5 kg) in the 3 months preceding participation were included in the study. Results Forty-five participants (obesity: n = 15; overweight: n = 10; T2D: n = 20) were interviewed. Interviews were audio-recorded and transcribed verbatim for analysis. A subset of participants described eating behaviors on smartphone-based app tasks over 5 days. Most (> 96%) discussed the influence of hunger, cravings and satiety on food choices. Participants identified 22 drivers/triggers (including health, 95.6%; culture/heritage, 93.3%; location, 91.1%; stress, 88.8%). Participants also discussed associations between drivers/triggers and eating behavior concepts (appetite, hunger, cravings, satiety, motivation/determination). A conceptual model illustrating eating behavior concepts and related drivers/triggers was developed. The concept elicitation interviews identified a multitude of drivers and triggers and characterized the association of such drivers/triggers with seven core patient-reported concepts encompassing eating behaviors. Conclusion The findings build upon existing models of factors influencing food choices. Findings confirm prior research regarding impact of drivers/triggers on food choice in people with obesity and T2D and indicate underlying disease state does not appear to influence eating behaviors in people with stable body weight. Supplementary Information The online version contains supplementary material available at 10.1007/s12325-024-02846-5.

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“…In clinical research settings, open-ended dietary assessment methods such as food records and diet history interviews tend to be used to generate dietary intake data [8]. The data is generated by a stepwise process including collection and coding [9].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the dietary intake data coding process in a clinical setting: Implications for research practice

et al. 2019

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Background High 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. Methods Using 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. Results Some 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. Conclusion The 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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Predictors for Reporting of Dietary Assessment Methods in Food-based Randomized Controlled Trials over a Ten-year Period

Cited by 10 publications

References 282 publications

Food and functional dyspepsia: a systematic review

Food and functional dyspepsia: a systematic review

Perceptions and Experiences of People with Obesity and Type 2 Diabetes Around Appetite and Eating Behaviors: A Qualitative Study

Evaluation of the dietary intake data coding process in a clinical setting: Implications for research practice

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