A influência de diferentes magnitudes de carga de treinamento no padrão de sono e nas respostas psicofisiológicas em jovens futebolistas
INTRODUCTION: Young athletes, during the pre-season and season phases, are exposed to successive periods of changes in the magnitude of training loads, which can directly affect the quantity and quality of sleep and, consequently, interfere in the recovery process. OBJECTIVE: To analyze the influenc...
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| Formato: | Dissertação |
| Idioma: | pt_BR |
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Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/handle/123456789/33365 |
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| Resumo: | INTRODUCTION: Young athletes, during the pre-season and season phases, are exposed
to successive periods of changes in the magnitude of training loads, which can directly affect
the quantity and quality of sleep and, consequently, interfere in the recovery process.
OBJECTIVE: To analyze the influence of different training load magnitudes on sleep
parameters and, in a complementary way, on psychophysiological variables: perceived
recovery, mood states, stress tolerance and salivary cortisol in young soccer players for three
weeks with different magnitudes of workload. METHODS: 13 young male soccer athletes
(age: 15.93 ± 0.59 years; body mass: 68.70 ± 6.12 kg; height: 1.75 ± 0.07 m; BMI: 22.30 ±
0.97) were evaluated during a pre-competitive mesocycle, consisting of 3 weeks of training
with different magnitudes of workload. The external training load (ETL) was verified by the
PlayerLoad method, while the internal training load (ITL) was determined by the sessionrating of perceived exertion method (session-RPE). Wrist actigraphy was used to monitor
sleep. Sleep variables, including time in bed (TIB), total sleep time (TST), sleep latency
(SL), wake after sleep onset (WASO) and sleep efficiency (SE) were evaluated in all nights
of post-workout sleep. Recovery status was measured using the Perceived Recovery Status
(PRS) scale. Mood state was assessed using the Brunel Mood Scale (BRUMS) and stress
tolerance was assessed using the Athletes' Daily Life Demand Analysis (DALDA)
questionnaire. Finally, saliva samples were collected at rest to analyze variations in salivary
cortisol concentration. Repeated measures ANOVA was used to verify the effect of time.
Friedman's test was used for data that did not meet the normality assumptions. Bonferroni
post-hoc was used to check for point differences and the squared partial eta (η2) was used
as the effect size. Pearson and Spearman correlations were used to verify associations
between training loads and sleep-related variables. RESULTS: Week 2 had the highest
workload, with a significant increase in TEC (p < 0.001) and CIT (p < 0.001) when compared
to weeks 1 and 3. In addition, there was a significant improvement in sleep parameters during
the week with the highest training load (TIB: +35 min, p = 0.044; TST: +46 min, p = 0.003;
SL: -5 min, p = 0.001; ES: + 3%, p = 0.019). However, there was no effect of time for PRS
(p = 0.741) and for the subcomponents of the BRUMS scale: tension (p = 0.378), depression
(p = 0.311), anger (p = 0.148), vigor (p = 0.178), fatigue (p = 0.063) and confusion (p =
0.630). Likewise, there was no effect of time for stress sources (p = 0.730), stress symptoms
(p = 0.986) and salivary cortisol (p = 0.859). Finally, a very strong correlation was found
between ETL and ITL (r = 0.783; p < 0.001), moderate correlation between ETL and TST (r
= 0.340; p = 0.037), ITL and TST (r = 0.458; p = 0.003), ITL and SE (r = 0.359; p = 0.025).
CONCLUSION: During a microcycle with higher loads, there is an increase in TIB, TST,
SE and a reduction in SL, without affecting bedtime and without interfering with perceived
recovery, mood states, stress tolerance and salivary cortisol levels. |
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