The nutrition for sport knowledge questionnaire (NSKQ): development and validation using classical test theory and Rasch analysis

Abstract

Background: Appropriate dietary intake can have a significant influence on athletic performance. There is a growing consensus on sports nutrition and professionals working with athletes often provide dietary education. However, due to the limitations of existing sports nutrition knowledge questionnaires, previous reports of athletes' nutrition knowledge may be inaccurate.

Methods: An updated questionnaire has been developed based on a recent review of sports nutrition guidelines. The tool has been validated using a robust methodology that incorporates relevant techniques from classical test theory (CTT) and Item response theory (IRT), namely, Rasch analysis.

Results: The final questionnaire has 89 questions and six sub-sections (weight management, macronutrients, micronutrients, sports nutrition, supplements, and alcohol). The content and face validity of the tool have been confirmed based on feedback from expert sports dietitians and university sports students, respectively. The internal reliability of the questionnaire as a whole is high (KR = 0.88), and most sub-sections achieved an acceptable internal reliability. Construct validity has been confirmed, with an independent T-test revealing a significant (p < 0.001) difference in knowledge scores of nutrition (64 ± 16%) and non-nutrition students (51 ± 19%). Test-retest reliability has been assured, with a strong correlation (r = 0.92, p < 0.001) between individuals' scores on two attempts of the test, 10 days to 2 weeks apart. Three of the sub-sections fit the Rasch Unidimensional Model.

Conclusions: The final version of the questionnaire represents a significant improvement over previous tools. Each nutrition sub-section is unidimensional, and therefore researchers and practitioners can use these individually, as required. Use of the questionnaire will allow researchers to draw conclusions about the effectiveness of nutrition education programs, and differences in knowledge across athletes of varying ages, genders, and athletic calibres.

Keywords: Classical test theory; Measure; Nutrition knowledge; Questionnaire; Rasch analysis; Sports nutrition; Valid.

Fig. 1

Flow chart of 8-step methadology used to develop and validate the Nutrition for Sport Questionnaire (UNSQ). * Content Validity = the measure covers all relevant topics related to sports nutrition. † CVI = Number of experts who rated an item ‘very relevant’ or ‘relevant’ divided by total number of experts; > 0.78 is adequate. ‡ Face Validity = the measure, on face value is an adequate reflection of sports nutrition. § Difficulty index = frequency with which items were answered correctly; <20% = too hard; >80% = too easy. ǁ Discrimination index = average score of top 10% of participants minus average score of bottom 10% of participants; > 0.3 is adequate. ¶ Distractor utility = frequency with which each multi-choice option is selected; > 5% = effective distractor. **Fit residuals between −2.5 and 2.5 indicate observed = expected responses. ††DIF assessed using ANOVA; non-significant p-value = no differences in response pattern based on participant characteristics; ‡‡ Disordered thresholds are assessed graphically. §§ Perc5% statistic <5% = scale is unidimensional (assessing one concept). ǁ ǁ SD of 0 and Mean of 1for the overall item/person interaction = perfect fit to Rasch model; a SD > 1.5 = misfit. ¶¶ Significant differences in known-group comparison scores = construct validity (questionnaire test what it is supposed to). *** Pearson’s r > 0.7 = test-retest reliability (stability overtime). ^††† KR-20 > 0.7 = Internal reliability (consistency in items)