Identifying a perception of wellness that can be used to monitor adaptive responses to training and competition is important in the management of sports teams. While there are studies to assess the relationship between training load and wellness, very little research has focused on how athletes perceive their health and wellness before, during, and after training. A study to assess these relationships was recently conducted among college basketball players. This article describes the findings of the study and explores the relationship between wellness and training load measures.
Using subjective player wellness ratings to monitor adaptive responses to training and competition is a useful technique. However, it remains an elusive goal. Fortunately, several studies have explored the relationship between pre-training wellness scores and subsequent training load outputs.
In this study, we examined the relationship between pre-training wellness scores and training load outputs for elite basketball players. A total of 27 players were recruited for the study, each completing nine wellness items. These were rated on a scale from one to ten using a visual analog scale. The items included mood, fatigue, sleep quality, and stress level.
Pre-training wellness scores were evaluated for 13 weeks. The relationship between the wellness measures and training load outputs was investigated using two mixed-models. One model examined the relationship between training load and cumulative wellness score. The other model examined the effect of acute changes in wellness scores on training efficiency.
Using self-reported measures to monitor athlete wellness is an inexpensive method to assess performance. These measures can be used to identify athlete fatigue before it becomes an injury, and can help to prevent injuries from occurring. Despite the widespread use of these measures, there are still many questions about the validity and utility of these measures.
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The purpose of this study was to investigate the use of athlete self-report measures for monitoring the impact of training and competition on well-being. The investigators used a combination of fixed and random effects and examined associations between pre-training wellness and training load. The investigators also examined the ecological validity of their monitoring approach. They included both same-day and next-day data, as well as derived variables such as performance, workload, training load and training sessions.
Athletes were asked to complete a wellness questionnaire before and after training sessions. The questionnaire used a five-point visual analog scale rated by players on a scale from 1-5. Some of the items included mood, stress, sleep quality, fatigue, and general muscle soreness.
Associations between summed wellness and training-load measures
Several studies have investigated the association between summed wellness scores and training load. Some have focused on individual self-report measures, others have studied subjective measures in the context of training. Several studies have reported associations between the two, but the majority have not. The goal of this study was to explore the relationship between training load and wellness scores in field hockey players.
The study was conducted on male university field hockey players during the in-season phase of premier league hockey competition. A total of 23 players participated in the study, with a completion rate of over 80%. In order to evaluate the relationship between training load and wellness scores, a regression model was constructed. The model was linear with mixed-effects. Statistical significance was based on a p-value of 0.05.
The results of the linear mixed models indicate that training load and wellness scores have a moderate to moderate positive relationship. The magnitude of this association is reflected in the average percentage changes in the wellness scores.
Results of the study
Using self-reported perceptions of wellness, this study aimed to explore the effect of training and competition on the adaptations of elite level Australian football players. During in-season training and competition, players were monitored over an entire season. Specifically, players completed a wellness questionnaire before bedtime and after each training session.
Players were asked to rate nine items on a 1-5 visual analog scale. These items included stress, mood, fatigue, sleep quality, and general muscle soreness.
Players' perceptions of wellness improved throughout the week. This improved player performance, especially in game days when players were able to recover. However, the effects of acute changes in player wellness were relatively inconsequential. These findings suggest that practitioners should not make training modifications based on players' acute changes in perceived wellness.
The use of single-item self-report measures is widespread in team sports. They are easily administered and can be automated. Self-reported player wellness ratings are a valuable tool for coaches and athletes, as they provide an objective measure of player response. However, it is important to evaluate the validity of these measures, as some have been used to manipulate participation.