Introduction: Monitoring an athlete’s stress and recovery state across sequential training bouts can be used to gauge fitness and fatigue levels (i.e., preparedness). Previous studies have used jumping performance, biochemical markers, and questionnaires to estimate preparedness. However, self-report questionnaires are the most common due to economical and practical means. The Short Recovery and Stress Scale (SRSS) is an 8-item questionnaire ideal for monitoring; however, convergent validity of the SRSS with physiological and performance measures needs to be investigated. Purpose: Thus, the purpose of this study was to determine whether changes in collegiate weightlifter’s training volume-load, biochemical markers, and jumping performance correlate to changes in the SRSS. Methods: 12 collegiate weightlifters (8 males, 4 females) with \u3e1yr of competition experience trained for 4 weeks and were tested at the beginning of each week (T1-T4). Training volume-load with displacement (VLd) was monitored weekly for all exercises. Testing was conducted following an overnight fast and included hydration, SRSS (0-6 scale with 6 indicating highest recovery and stress), and blood draws (resting testosterone (T), cortisol (C), T:C, creatine kinase (CK)) followed by unloaded (0kg) and loaded (20kg) squat jumps (SJ) on force platforms. Pearson correlation coefficients were calculated between the change in SRSS scores and all other variables from T1-T2, T1-T3, and T1-T4. Alpha level was set at p\u3c 0.05. Results: Inverse relationships were observed between changes in recovery items and C (r= -0.61 to -0.72, p\u3c 0.05), and unloaded and loaded SJ height and relative peak power (r= -0.59 to -0.64, p\u3c 0.05) from T1 to T2, and T1 to T3. Similarly, positive relationships were observed between changes in stress items and C (r=0.61 to 0.72, p\u3c 0.05), and unloaded and loaded SJ height and relative peak power (r=0.58 to 0.84, p\u3c 0.05) across all time points. No significant relationships were observed between changes in SRSS items and VLd or T, T:C, CK. Conclusion: Relationships between changes in some SRSS items and C agree with previous findings highlighting C as an indicator of training stress. Nonetheless, the non-significant relationships between changes in SRSS items, VLd, and other biochemical markers disagrees with previous findings. This may partly be explained by the smaller undulations in VLd in the current study, which is characteristic of actual training. Further, relationships between changes in some SRSS items and jumping performance were opposite of what was expected indicating athlete’s perception of their stress and recovery state does not always correspond with their ability to perform. Practical Application: These results provide some evidence for the convergent validity of the SRSS. Nonetheless, weightlifting coaches should be cautious in using results from a single test to estimate an athlete’s preparedness. Thus, we recommend the SRSS be included as part of a multi-dimensional monitoring program for weightlifters
