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methods of dietary assessment. Such estimates of validity should therefore be taken into account when utilizing this method, alongside the requirement to use multiple coders when performing a dietary analysis of athletic populations. Acknowledgments The study was designed by R.G. Stables, A.M. Kasper, J

that urinary dehydration markers (both field and laboratory) exhibit large variability and inconsistency (U OSM increased by ∼16% over a 7-d period) in elite youth boxers, regardless of stable body mass or adequate macronutrient intake. 11 Sing and Peters 12 reported poor correlation between

from stable process–product discourse toward ideas of teaching and becoming teacher that acknowledge the multiple, complex, and ever‐changing factors that intersect to inform each teaching occurrence. In this argument, we follow educators such as Cochran-Smith, Ell, Ludlow, Grudnoff, and Aitken

) developing items to be included on the ToRQ, (b) identifying a stable factor structure for the ToRQ using exploratory factor analysis (EFA), (c) confirming the factor structure through confirmatory factor analysis (CFA) using a separate participant sample, and (d) examining the extent to which the ToRQ correlates

, incorporating a special silicone gasket for the best possible seal, and were wrapped tightly with Parafilm M (Bemis Co., Inc., Oshkosh, WI). We analyzed the urine samples with isotope ratio mass spectrometry (Hydra 20-20 Stable Isotope Mass Spectrometer; SerCon Ltd., Crewe, United Kingdom). The 18 O and 2 H

Associations Changes in HR submax were investigated relative to each individual’s performance over the duration of the study and compared with injury risk. A within-individual z score was calculated for HR submax before being sorted into 3 categories: decrease ( z score, <−0.5), stable ( z score, −0.5 to

and freestyle swimming were approximately 10% to 12%. However, the difference in men’s and women’s world records for 500-m speed skating was reduced to 7%. For all Olympic running events longer than 100 m, the sex differences in world records are relatively stable at 10% to 12%, without any clear

percentage of AQ already in qualifying positions were 32.1%, 42.9%, and 65.7% at 400 m, 800 m, and 1200 m. Race positions remained more stable throughout 800-m races (Figure  1 ) than through the 1500-m races which visual inspection of data suggests were characterized by a greater degree of positional change