The Multiple Food Test: Development and validation of a new tool to measure food choice and applied nutrition knowledge

Schreiber, Mike; Bucher, Tamara; Collins, Clare E.; Dohle, Simone

doi:10.1016/j.appet.2020.104647

Cited by 12 publications

(10 citation statements)

References 43 publications

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“…The Multiple Food Test measures applied nutrition knowledge as it relates to food choice [ 33 ]. The test is an image selection task, where participants select which foods they would choose and then rate the perceived healthiness of those foods [ 33 ].…”

Section: Methods: the Use Of Food And Eating Behavior Questionnaires To Improve Dietary Interventionsmentioning

confidence: 99%

Measuring and Leveraging Motives and Values in Dietary Interventions

et al. 2021

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Why measure and leverage food motives and values? Every failure and every success in dietary change can be connected to motivation. Therefore, this research question naturally arises: How can food motives and values be measured and leveraged to improve diet outcomes from the individual to populations? There are four ways that food motives and values (FMVs) can assist researchers and health professionals. First, FMVs can help to create a personalized approach to dietary change. Second, FMVs can inform content for dietary interventions. Third, these FMV measures can be used in data analysis to elucidate differences in adherence and outcomes among participants. Fourth, public health nutrition messages can be tailored using information on FMVs. Each of these uses has the potential to further the literature and inform future efforts to improve diet. A central aim of our study is to provide specific examples and recommendations on how to measure and leverage FMVs. To do so, we reviewed 12 measures included in the literature citing the Food Choice Questionnaire by Steptoe, Pollard, and Wardle, which was identified as the earliest, highly cited article appearing under the search terms “food motives” AND “food values” AND “eating behavior” AND “measure”. Specific details on how articles were selected from the citing literature are described in the Methods section. We also expound on our reasoning for including the Three-Factor Eating Questionnaire, which made for 13 measures in total. Our main finding is that each measure has strengths and shortcomings to consider in using FMVs to inform nutritional recommendations at different levels.

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Section: Methods: the Use Of Food And Eating Behavior Questionnaires To Improve Dietary Interventionsmentioning

confidence: 99%

Measuring and Leveraging Motives and Values in Dietary Interventions

et al. 2021

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“…Food choice. Food choice was assessed with the Multiple Food Test, a validated measure of food choices in online contexts that has adequate psychometric properties and correlates with actual food choices [47]. In the Multiple Choice Food Test, individuals see pictures of four different foods and are asked to choose one they would most prefer to eat right now.…”

Section: Methodsmentioning

confidence: 99%

“…In the computerized test, there are 18 trials, with no practice trials. In each trial, pictures of four foods, one food per category, are randomized but counterbalanced across trials such that they appear in a random order and each food appears an equal number of times across all trials (see [47] for a list of the foods in each category and all images). In a given trial, then, individuals will see four pictures in a random order, each one from each category.…”

Section: Methodsmentioning

confidence: 99%

Self-Reported Nutritional Factors Are Associated with Weight Loss at 18 Months in a Self-Managed Commercial Program with Food Categorization System: Observational Study

Mitchell

Yang

et al. 2021

Nutrients

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Little is known about nutritional factors during weight loss on digital commercial weight loss programs. We examined how nutritional factors relate to weight loss for individuals after 4 and 18 months on a mobile commercial program with a food categorization system based on energy density (Noom). This is a two-part (retrospective and cross-sectional) cohort study. Two time points were used for analysis: 4 months and 18 months. For 4-month analyses, current Noom users who met inclusion criteria (n = 9880) were split into 5% or more body weight loss and stable weight loss (0 ± 1%) groups. Individuals who fell into one of these groups were analyzed at 4 months (n = 3261). For 18-month analyses, individuals from 4-month analyses who were still on Noom 18 months later were invited to take a one-time survey (n = 803). At 18 months 148 participants were analyzed. Noom has a system categorizing foods as low-, medium-, and high-energy-dense. Measures were self-reported proportions of low-, medium-, and high-energy-dense foods, and self-reported nutritional factors (fruit and vegetable intake, dietary quality, nutrition knowledge, and food choice). Nutritional factors were derived from validated survey measures, and food choice from a novel validated computerized task in which participants chose a food they would want to eat right now. ANOVAs compared participants with 5% or more body weight loss and participants with stable weight (0 ± 1%) at 4 months on energy density proportions. Analyses at 18 months compared nutritional factors across participants with >10% (high weight loss), 5–10% (moderate weight loss), and less than 5% body weight loss (low weight loss), and then assessed associations between nutritional factors and weight loss. Individuals with greater weight loss reported consuming higher proportions of low-energy-dense foods and lower proportions of high-energy-dense foods than individuals with less weight loss at 4 months and 18 months (all ps < 0.02). Individuals with greater weight loss had higher fruit and vegetable intake (p = 0.03), dietary quality (p = 0.02), nutrition knowledge (p < 0.001), and healthier food choice (p = 0.003) at 18 months. Only nutrition knowledge and food choice were associated with weight loss at 18 months (B = −19.44, 95% CI: −33.19 to −5.69, p = 0.006; B = −5.49, 95% CI: −8.87 to −2.11, p = 0.002, respectively). Our results highlight the potential influence of nutrition knowledge and food choice in weight loss on a self-managed commercial program. We also found for the first time that in-the-moment inclination towards food even when just depicted is associated with long-term weight loss.

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“…Assessment motor and process skills (AMPS) [57,58] Food preferences, dietary restrictions and sensory appeal Food choice 1 Food choice questionnaire [59] Food choice 1 Food choice and applied nutrition [60] Health, taste and attitudes 1 The Health Taste and Attitude Scale [61] Nutrition knowledge Nutrition knowledge-short 1 PKB-7 scale [62] Nutrition knowledge-comprehensive 1 Re-examined General Nutrition Knowledge Questionnaire (GNKQ-R) [63] Nutrition knowledge-Australian version 1 Revised General Nutrition Knowledge Questionnaire for Australia [64] Table A1. Cont.…”

Section: Constructmentioning

confidence: 99%

Cook-EdTM: A Model for Planning, Implementing and Evaluating Cooking Programs to Improve Diet and Health

et al. 2020

Self Cite

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Domestic cooking education programs are typically designed to improve an individual’s food and cooking skills, although not necessarily diet quality. Currently, there are no comprehensive models to guide the planning, implementation and evaluation of domestic cooking education programs that focus on improving diet and health. Our aim was to address this through development of the Cooking Education (“Cook-EdTM”) model, using the PRECEDE-PROCEED model as the underlying Cook-EdTM framework. A review of the food and cooking skills education literature informed the content of the Cook-EdTM model. Cook-EdTM was critiqued by experts in consumer behaviour, cooking and nutrition education research and education until consensus on model content and format was reached. Cook-EdTM leads cooking program developers through eight distinct stages, engaging key stakeholders in a co-design process from the outset to tailor programs to address the need of individuals and inform the development of program content, program delivery, and evaluation. A Cook-EdTM scenario applied in practice is described. The proposed Cook-EdTM model has potential to be adapted for use in domestic cooking education programs delivered in clinical, community, school or research settings. Further research will establish Cook-EdTM’s utility in enhancing program development and in improving food and cooking skills, dietary patterns and health outcomes.

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The Multiple Food Test: Development and validation of a new tool to measure food choice and applied nutrition knowledge

Cited by 12 publications

References 43 publications

Measuring and Leveraging Motives and Values in Dietary Interventions

Measuring and Leveraging Motives and Values in Dietary Interventions

Self-Reported Nutritional Factors Are Associated with Weight Loss at 18 Months in a Self-Managed Commercial Program with Food Categorization System: Observational Study

Cook-EdTM: A Model for Planning, Implementing and Evaluating Cooking Programs to Improve Diet and Health

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