Abstract
During recent years, the integration of technology has substantially improved self-reported dietary assessment methods, such as food frequency questionnaires (FFQ), food records, and 24-h recalls. To further reduce measurement error, additional innovations are urgently needed. Memory-related measurement error is one of the aspects that warrants attention, which is where new smartphone technologies and ecological momentary assessment (EMA) approaches provide a unique opportunity. In this article, we describe the DIASS study, which was designed to evaluate an innovative 2-h recall (2hR) smartphone-based methodology, against traditional 24-h recalls, FFQ, and biomarkers, to assess both actual and habitual dietary intake. It is hypothesized that a 2-h reporting window decreases reliance on memory and reporting burden, and increases data accuracy. We included 215 men (28%) and women (72%), with a mean ± SD age of 39 ± 19 years and a mean ± SD BMI of 23.8 ± 4.0. Most participants were highly educated (58%). Response rates for the various dietary assessment methods were >90%. Besides the evaluation of the accuracy, usability, and perceived burden of the 2hR methodology, the study set-up also allows for (further) evaluation of the other administrated dietary assessment tools.
Highlights
Accurate dietary assessment is one of the essential aspects of nutrition and health research, where 24-h recalls (24hRs), food frequency questionnaires (FFQs), and food records are currently the most commonly-used dietary assessment methods [1–4].these methods have a range of drawbacks [2,5]
The system usability scale (SUS) has been used in previous studies to assess the usability of dietary assessment apps [43,44]
We have described the design of the DIASS study, which aimed to evaluate a newly developed smartphone-based dietary assessment methodology against established methods and objective markers
Summary
Accurate dietary assessment is one of the essential aspects of nutrition and health (behavior) research, where 24-h recalls (24hRs), food frequency questionnaires (FFQs), and food records are currently the most commonly-used dietary assessment methods [1–4]. These methods have a range of drawbacks [2,5]. A food record is not memory dependent, but its prospective nature may introduce reactivity bias, due to, for instance, social desirability or to ease the recording task [2,7,9] All these methods appear to heavily burden both the participant and the researcher [5,7,10]. Numerous valuable computer- and web-based tools, mostly based on 24hRs and FFQs, have been developed during the past decade [3,10,12,13]
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