Literature DB >> 26212597

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

Yasmine Probst1, Gail Zammit1.   

Abstract

The importance of monitoring dietary intake within a randomized controlled trial becomes vital to justification of the study outcomes when the study is food-based. A systematic literature review was conducted to determine how dietary assessment methods used to monitor dietary intake are reported and whether assisted technologies are used in conducting such assessments. OVID and ScienceDirect databases 2000-2010 were searched for food-based, parallel, randomized controlled trials conducted with humans using the search terms "clinical trial," "diet$ intervention" AND "diet$ assessment," "diet$ method$," "intake," "diet history," "food record," "food frequency questionnaire," "FFQ," "food diary," "24-hour recall." A total of 1364 abstracts were reviewed and 243 studies identified. The size of the study and country of origin appear to be the two most common predictors of reporting both the dietary assessment method and details of the form of assessment. The journal in which the study is published has no impact. Information technology use may increase in the future allowing other methods and forms of dietary assessment to be used efficiently.

Entities:  

Keywords:  Dietary assessment; food; randomized controlled trials

Mesh:

Year:  2016        PMID: 26212597     DOI: 10.1080/10408398.2013.816653

Source DB:  PubMed          Journal:  Crit Rev Food Sci Nutr        ISSN: 1040-8398            Impact factor:   11.176


  3 in total

1.  First-Stage Development and Validation of a Web-Based Automated Dietary Modeling Tool: Using Constraint Optimization Techniques to Streamline Food Group and Macronutrient Focused Dietary Prescriptions for Clinical Trials.

Authors:  Yasmine Probst; Evan Morrison; Emma Sullivan; Hoa Khanh Dam
Journal:  J Med Internet Res       Date:  2016-07-28       Impact factor: 5.428

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

Authors:  Vivienne X Guan; Yasmine C Probst; Elizabeth P Neale; Linda C Tapsell
Journal:  PLoS One       Date:  2019-08-12       Impact factor: 3.240

3.  Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping.

Authors:  Yasmine Probst; Duc Thanh Nguyen; Minh Khoi Tran; Wanqing Li
Journal:  Nutrients       Date:  2015-07-27       Impact factor: 5.717

  3 in total

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