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Purpose: To assess dietetic students’ anxiety levels before and after a series of simulations and to document students’ perceived sources of anxiety while completing simulation-based learning activities.Methods: A mixed-method convergent pilot study was conducted. Students enrolled in a Nutrition Assessment course that included a series of four simulations were invited to participate. Students completed an online pre-post simulation survey and engaged in individual interviews and a focus group discussion. The questionnaires included demographic questions and the French State-Trait Anxiety Inventory. Nonparametric tests and thematic analysis were used to examine data.Results: Fourteen students participated in the study’s quantitative component and seven in the qualitative component. There was a significant decrease in trait (44.5 ± 13.8 vs 32.0 ± 14.0, P = 0.01) and state (47.0 ± 11.2 vs 33.0 ± 18.0, P = 0.05) anxiety from pre- to post-simulations. Individual factors influencing students’ anxiety levels were stress and self-confidence. External factors influencing students’ anxiety levels were unknown situations, observers, patient profiles, observers’ feedback, preparation level, and academic setting.Conclusions: Our findings suggest that ensuring the educator is not present during simulations, advance preparation, and reassurance that simulations are a learning and not an evaluation activity may be effective pedagogical strategies for dietetic educators to reduce learners’ anxiety and facilitate competency development.

In this scoping review, “weight-related evidence” is an umbrella for various terms, phrases, and ways in which weight, body size, fatness, and/or obesity present in research and dietetic practice. Canadian Registered Dietitians’ perceptions of, experiences with, and/or knowledge of weight-related evidence in nutrition care was identified and mapped. Implementing JBI scoping review methodology, four databases were searched: (i) CINAHL (EBSCO); (ii) Medline (Ovid); (iii) Embase (Elsevier); and (iv) Scopus (Elsevier). Google and Bing were searched for grey literature. Three JBI-trained independent reviewers completed screening to extraction. Community consultation was conducted using the Delphi Method. Of 2217 results, 67 were included in the review (29 peer-reviewed; 38 grey). Identified frequencies were 67 examples of perception, 54 of experience, and 51 of knowledge. This review identified diverse definitions/perspectives of weight-related evidence, highlighting the benefits of continuing to discuss and explore this topic within and beyond dietetics. Weight-related evidence was identified in nutrition care in various settings, representing nutrition assessment, diagnoses, interventions, monitoring, and evaluation. Focused on dietetic research and practice, this work provides a foundation for future evaluation of dietitian-led intervention fidelity, utility, and effectiveness, using systematic review or other research designs. These Canadian findings can serve as a foundation for a global/international review.

Sample size estimation is a critical aspect of nutrition research methodology, yet it remains frequently overlooked, leading to underpowered studies and potentially inaccurate conclusions. This review addresses this gap by providing comprehensive guidance on how to calculate sample size in nutrition research. Emphasizing the importance of an a priori sample size calculation, the review outlines the key considerations, including the desired levels of significance and power, effect size estimation, and standard deviation assessment. Formulas for determining sample size for various comparisons, including two proportions, two means, three or more groups, and unevenly sized groups, are provided, along with strategies for addressing loss to follow-up. Hypothetical examples illustrate these formulas’ application across different research scenarios, highlighting their practical value in ensuring study robustness. Additionally, the review discusses common pitfalls in sample size estimation, such as misjudging effect size or standard deviation, and emphasizes the need for transparent reporting of sample size calculations to enable accurate interpretation of study findings. This article is a resource for nutrition researchers, offering guidance on conducting appropriate sample size calculations to bolster methodological rigor and study reliability. By embracing the principles outlined herein, researchers can elevate the quality of nutrition research.