Australian Football Athletes Lack Awareness of Current Sport Nutrition Guidelines.

Sports nutrition is an evolving field, but there is a lack of data on Australian athletes' knowledge of current sports nutrition guidelines. Additionally, several tools used to assess nutrition knowledge (NK) have not undergone adequate validation. The purpose of this study was to assess and compare the sports NK of elite and nonelite Australian football (AF) athletes using a newly validated questionnaire-The Nutrition for Sport Knowledge Questionnaire. Elite AF players (n = 46) were recruited directly from their club dietitian and nonelite AF players (n = 53) were invited to participate via e-mail from their club president or secretary. The mean NK score of elite and nonelite AF players was 46 ± 16% and 51 ± 11%, respectively (p = .041). In both groups, knowledge of macronutrients, weight management, and alcohol was better than knowledge of supplements, micronutrients, and sports nutrition. Nonelite athletes achieved statistically significantly higher scores on the questionnaire subsections testing weight management (elite: 48 ± 18; nonelite: 57 ± 19, p = .019), micronutrients (elite: 39 ± 19; nonelite: 50 ± 16, p = .004), and alcohol (elite: 52 ± 13; nonelite: 71 ± 17, p = .002). While overall NK of Australian athletes was poor, scores varied greatly among individuals (range: 10-70%) and across the six subsections (topics) being assessed. Professionals working with athletes should undertake an assessment of the athletes' NK so that they can provide targeted education programs.

Developing and validating a nutrition knowledge questionnaire: key methods and considerations.

OBJECTIVE: To outline key statistical considerations and detailed methodologies for the development and evaluation of a valid and reliable nutrition knowledge questionnaire. DESIGN: Literature on questionnaire development in a range of fields was reviewed and a set of evidence-based guidelines specific to the creation of a nutrition knowledge questionnaire have been developed. The recommendations describe key qualitative methods and statistical considerations, and include relevant examples from previous papers and existing nutrition knowledge questionnaires. Where details have been omitted for the sake of brevity, the reader has been directed to suitable references. RESULTS: We recommend an eight-step methodology for nutrition knowledge questionnaire development as follows: (i) definition of the construct and development of a test plan; (ii) generation of the item pool; (iii) choice of the scoring system and response format; (iv) assessment of content validity; (v) assessment of face validity; (vi) purification of the scale using item analysis, including item characteristics, difficulty and discrimination; (vii) evaluation of the scale including its factor structure and internal reliability, or Rasch analysis, including assessment of dimensionality and internal reliability; and (viii) gathering of data to re-examine the questionnaire's properties, assess temporal stability and confirm construct validity. Several of these methods have previously been overlooked. CONCLUSIONS: The measurement of nutrition knowledge is an important consideration for individuals working in the nutrition field. Improved methods in the development of nutrition knowledge questionnaires, such as the use of factor analysis or Rasch analysis, will enable more confidence in reported measures of nutrition knowledge.

Australian team sports athletes prefer dietitians, the internet and nutritionists for sports nutrition information.

AIM: To evaluate the information sources that are used and preferred by Australian athletes and to assess if preferences influence nutrition knowledge (NK). METHODS: Elite and non-elite Australian team sport athletes, playing Australian football (AF), cricket, lawn bowls, soccer or hockey, were recruited via the sporting organisations' qualified sports dietitians or club presidents. Athletes completed one of two online, validated sports NK questionnaires. Frequency analysis on previous sources of advice, preferred sources of information and preferred type of support were assessed. Differences in NK scores (%) based on previous sources of dietary advice and preferences for obtaining information were assessed using t test or Mann-Whitney U test. RESULTS: Demographic and information source questions were completed by 410 athletes; 331 also completed NK questions. Athletes were mostly non-elite (76%) and AF players (79%). Forty-four per cent of athletes reported having previously received advice from a dietitian. Twenty per cent, 19% and 16% of athletes chose "dietitian," "internet" and "nutritionist" as their preferred source of nutrition information, respectively. Athletes preferred information on sports nutrition (35%), individual consultations (33%), and information on general healthy eating (33%), over cooking classes (4%) and group presentations (3%). There were no significant associations between preferred and previous information sources and NK scores. CONCLUSIONS: Australian athletes prefer dietitians, the internet and nutritionists for sports nutrition information. There is an interest in and need for access to a qualified sports dietitian and reputable internet-based nutrition information. Education programs and advice given to athletes need to be evaluated.

Development and validation of a brief general and sports nutrition knowledge questionnaire and assessment of athletes' nutrition knowledge.

BACKGROUND: The Nutrition for Sport Knowledge Questionnaire (NSKQ) is an 89-item, valid and reliable measure of sports nutrition knowledge (SNK). It takes 25 min to complete and has been subject to low completion and response rates. The aim of this study was to develop an abridged version of the NSKQ (A-NSKQ) and compare response rates, completion rates and NK scores of the NSKQ and A-NSKQ. METHODS: Rasch analysis was used for the questionnaire validation. The sample (n = 181) was the same sample that was used in the validation of the full-length NSKQ. Construct validity was assessed using the known-group comparisons method. Temporal stability was assessed using the test-retest reliability method. NK assessment was cross-sectional; responses were collected electronically from members of one non-elite Australian football (AF) and netball club, using Qualtrics Software (Qualtrics, Provo, UT). RESULTS: Validation - The A-NSKQ has 37 items that assess general (n = 17) and sports (n = 20) nutrition knowledge (NK). Both sections are unidimensional (Perc5% = 2.84% [general] and 3.41% [sport]). Both sections fit the Rasch Model (overall-interaction statistic mean (SD) = - 0.15 ± 0.96 [general] and 0.22 ± 1.11 [sport]; overall-person interaction statistic mean (SD) = - 0.11 ± 0.61 [general] and 0.08 ± 0.73 [sport]; Chi-Square probability = 0.308 [general] and 0.283 [sport]). Test-retest reliability was confirmed (r = 0.8, P < 0.001 [general] and r = 0.7, P < 0.001 [sport]). Construct validity was demonstrated (nutrition students = 77% versus non-nutrition students = 60%, P < 0.001 [general] and nutrition students = 60% versus non-nutrition students = 40%, P < 0.001 [sport]. Assessment of NK - 177 usable survey responses from were returned. Response rates were low (7%) but completion rates were high (85%). NK scores on the A-NSKQ (46%) are comparable to results obtained in similar cohorts on the NSKQ (49%). The A-NSKQ took on average 12 min to complete, which is around half the time taken to complete the NSKQ (25 min). CONCLUSIONS: The A-NSKQ is a valid and reliable, brief questionnaire designed to assess general NK (GNK) and SNK.

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

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.