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10.1186/s40798-025-00958-y http://scihub22266oqcxt.onion/10.1186/s40798-025-00958-y 41369808!?!41369808 Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=41369808&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Sports+Med+Open 2025 ; 11 (1): 154 Nephropedia Template TP {{tp|p=41369808|t=2025. Validating Subjective Ratings with Wearable Data for a Nuanced Understanding of Load-Recovery Status in Elite Endurance Athletes |pdf=|usr=}}{{41369808}} gab.com Text Validating Subjective Ratings with Wearable Data for a Nuanced Understanding of Load-Recovery Status in Elite Endurance Athletes JO: Sports Med Open http://www.kidney.de/pget.php?&tw=1&pmid=41369808 #FOAvip BACKGROUND: The emergence of wearable technology offers enhanced real-time health management, including sleep, recovery, and exercise optimization. Despite their potential to monitor load-recovery parameters in elite athletes, the selection, combination, and interpretation or reliance of metrics in relation to perceived impact remain unclear. OBJECTIVE: This study assessed data from three wearables measuring sleep, continuous glucose, and exercise, together with the Profile of Mood State (POMS) dimensions alongside subjective ratings via the Readiness Advisor application (RA app) (Silicon Valley Exercise Analytics, svexa, Menlo Park, California, USA) to evaluate their association and value in load-recovery monitoring. METHODS: Twenty national team endurance athletes, competing at the highest international level, were monitored during one year of training, recovery, and competitions. Data collections were made with Global Positioning System (GPS) watches and heart rate monitors, Oura rings (Oura Health OY, Oulu, Finland), continuous glucose monitors, POMS questionnaires and subjective ratings in the RA app. RESULTS: Significant correlations were found between each RA question and its counterpart in a linear mixed model (r values = 0.39-0.81). However, time series analysis through autoregressive integrated moving average (ARIMA analysis) revealed individual variability. CONCLUSIONS: These findings indicate an influence of external aspects and advocate for a multifaceted approach to the assessment of load-recovery balance, well-being and performance. Moreover, personalized analyses proved more accurate than group averages, emphasizing the need for individualized monitoring. Integrating subjective and objective data appears essential for nuanced understanding of the athlete status, advancing high-performance monitoring and athletic health management. Twit Text FOAVip Validating Subjective Ratings with Wearable Data for a Nuanced Understanding of Load-Recovery Status in Elite Endurance Athletes ????Sports Med Open http://www.kidney.de/pget.php?&tw=1&pmid=41369808 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=41369808 #FOAvip English Wikipedia <ref>{{Cite pmid|41369808}}</ref> Validating Subjective Ratings with Wearable Data for a Nuanced Understanding of Load-Recovery Status in Elite Endurance Athletes #MMPMID41369808 Spetz L; Rogestedt J; Nilsson R; Mattsson CM; Larsen FJ Sports Med Open 2025[Dec]; 11 (1): 154 PMID41369808show ga BACKGROUND: The emergence of wearable technology offers enhanced real-time health management, including sleep, recovery, and exercise optimization. Despite their potential to monitor load-recovery parameters in elite athletes, the selection, combination, and interpretation or reliance of metrics in relation to perceived impact remain unclear. OBJECTIVE: This study assessed data from three wearables measuring sleep, continuous glucose, and exercise, together with the Profile of Mood State (POMS) dimensions alongside subjective ratings via the Readiness Advisor application (RA app) (Silicon Valley Exercise Analytics, svexa, Menlo Park, California, USA) to evaluate their association and value in load-recovery monitoring. METHODS: Twenty national team endurance athletes, competing at the highest international level, were monitored during one year of training, recovery, and competitions. Data collections were made with Global Positioning System (GPS) watches and heart rate monitors, Oura rings (Oura Health OY, Oulu, Finland), continuous glucose monitors, POMS questionnaires and subjective ratings in the RA app. RESULTS: Significant correlations were found between each RA question and its counterpart in a linear mixed model (r values = 0.39-0.81). However, time series analysis through autoregressive integrated moving average (ARIMA analysis) revealed individual variability. CONCLUSIONS: These findings indicate an influence of external aspects and advocate for a multifaceted approach to the assessment of load-recovery balance, well-being and performance. Moreover, personalized analyses proved more accurate than group averages, emphasizing the need for individualized monitoring. Integrating subjective and objective data appears essential for nuanced understanding of the athlete status, advancing high-performance monitoring and athletic health management. ?Validating Subjective Ratings with Wearable Data for a Nuanced Underst(epmc).pdf DeepDyve Pubget Overpricing