No abstract

The purpose of this study was two-fold: (1) to describe weekly average values for training monotony (TM) and training strain (TS) and their variations across the full soccer season, based on the number of accelerations and decelerations; (2) to analyze the differences between starter and non-starter players on weekly average TM and TS values for the pre-season and three in-season periods. In total, 21 professional soccer players were evaluated over 48 weeks during the full-season. The TM and TS were calculated based on the number of accelerations and decelerations at zone 1, zone 2 and zone 3, respectively. The results revealed that starters presented higher values compared to non-starters throughout the full season for all variables analyzed (all, p < 0.05). Generally, there were higher values in the pre-season. Specifically, accelerations at zones 1, 2 and 3 revealed moderate to very large significance of the starters compared to non-starters over the full-season. Decelerations at zone 1, 2 and 3 presented moderate to nearly optimally significant greater weekly averages for starters compared to non-starters during the full season. In conclusion, the TM and TS values were higher for starters compared to non-starters through the full-season, which confirms that the training session does not provide a sufficient load to non-starter soccer players during the full-season.

The aim of this study was to compare the weekly average training monotony new body load (wTMNBL) and strain (wTSNBL), as well as the weekly average training monotony metabolic power average (wTMMPA) and strain (wTSMPA) between four periods of a season (preseason, early-season, mid-season, and end-season), considering starters and non-starters. Twenty-one professional soccer players (age: 28.27 ± 3.78 years) were monitored throughout a season in the highest level of professional football Premier League in Iran. Data were captured by Global Positioning System (GPS) devices. Independent samples T-tests were applied to analyze the between-group differences for all dependent derived-GPS variables for the full season and its different periods (preseason, early-season, mid-season, and end-season). Based on the amount of time attending in match and training, players were divided into two groups (starters and non-starters) each week. The magnitude of the between-group difference revealed a very large significant greater weekly average TMNBL ( p<0.001, d = −2.42), TSNBL ( p<0.001; d = −2.74), TMMPA ( p<0.001; d =–2.79) and TSMPA ( p<0.001; d = −3.27) for starters when compared to non-starters during the early-season. The findings also revealed a very large significant difference when starters were compared to non-starters during the mid-season (TMNBL: p<0.001, d = −2.89; TSNBL: p<0.001, d = −2.99; TMMPA: p<0.001, d = −3.28; and TSMPA: p<0.001, d = −3.25) and end-season (TMNBL: p<0.001, d = −2.89; TSNBL: p<0.001, d = −3.07; TMMPA: p<0.001, d = −3.16; and TSMPA: p<0.001, d = −3.58). In summary, the results of this study revealed that starters present regularly higher values of NBL, MPA-based weekly training monotony, and training strain than non-starters. This result must be taken into account when planning weekly workloads for these groups. Specifically, starters might experience high values of external workloads because of match-related demands. Therefore, weekly adjustments in their training workload are required to reduce injury risk.

Regular practice of physical activity plays a fundamental role in preventing and treating cardiovascular diseases such as obesity, hypertension, diabetes, and metabolic syndrome. During the pandemic caused by COVID-19 and the lockdown established, people have reduced considerably their mobility and motor activity, which has led to an increase in unhealthy lifestyle habits, raising the risk of suffering from diseases. This paper consists of reviewing the existing scientific literature on recommendations of physical activity during the pandemic and to establish specific guidelines according to the type of population to which the activity would be directed. A search strategy has been carried out in the different databases: Embase, PubMed, SCOPUS, SPORTDiscus, and Web of Science (WoS), including all the articles published until 14 May 2020, to find essays with recommendations on aerobic activity, muscle strengthening, flexibility-stretching, meditation-relaxation, and balance exercises. The articles found have been evaluated considering the following criteria: type of publication, proposals for physical exercise, language, and, if it appears, volume of activity, frequency, intensity, and rest. The results obtained 29 articles that discuss patterns of physical activity, although there is no common consensus on such recommendations during confinement, nor are they suitable for all people. From these results, we can conclude that physical activity is widely recommended during the confinement caused by COVID-19, mainly through the performance of aerobic, strength, flexibility, and balance exercises.

This study aimed to analyze the correlations among weekly (w) acute workload (wAW), chronic workload (wCW), acute/chronic workload ratio (wACWR), training monotony (wTM), training strain (wTS), sleep quality (wSleep), delayed onset muscle soreness (wDOMS), fatigue (wFatigue), stress (wStress), and Hooper index (wHI) in pre-, early, mid-, and end-of-season. Twenty-one elite soccer players (age: 16.1 ± 0.2 years) were monitored weekly on training load and well-being for 36 weeks. Higher variability in wAW (39.2%), wFatigue (84.4%), wStress (174.3%), and wHI (76.3%) at the end-of-season were reported. At mid-season, higher variations in wSleep (59.8%), TM (57.6%), and TS (111.1%) were observed. Moderate to very large correlations wAW with wDOMS (r = 0.617, p = 0.007), wFatigue, wStress, and wHI were presented. Similarly, wCW reported a meaningful large association with wDOMS (r = 0.526, p < 0.001); moderate to very large associations with wFatigue (r = 0.649, p = 0.005), wStress, and wHI. Moreover, wTM presented a large correlation with wSleep (r = 0.515, p < 0.001); and a negatively small association with wStress (r = −0.426, p = 0.003). wTS showed a small to large correlation with wSleep (r = 0.400, p = 0.005) and wHI; also, a large correlation with wDOMS (r = 0.556, p = 0.028) and a moderate correlation with wFatigue (r = 0.343, p = 0.017). Wellness status may be considered a useful tool to provide determinant elite players’ information to coaches and to identify important variations in training responses.

This study investigated the effects on neuromuscular performance of a 6-week Optimal Load Training (OLT) and a novel modified Complex Training (MCT) (complex pairs: the same exercise using a moderate and an OL) in basketball players, in-season. Eighteen male athletes were randomly assigned to one of the protocols. Anthropometric measurements were taken to evaluate body composition. Lower- and upper-body maximum dynamic strength, countermovement jump (CMJ), standing long jump (SLJ), 10-m sprint and change of direction (COD) were also assessed. Moderate-to-large strength gains (presented as percentage change ± 90% confidence limits) were obtained for half-squat (OLT: 10.8 ± 5.3%; MCT: 17.2 ± 11.6%) and hip thrust (OLT: 23.5 ± 17.7%; MCT: 28.2 ± 19.0%). OLT athletes achieved likely small improvements in sprint (1.6 ± 1.6%) and COD (3.0 ± 3.2%). Players in the MCT attained likely moderate improvements in COD (3.0 ± 2.0%) and possibly small in SLJ (2.5 ± 4.6%). No protocol relevantly affected CMJ or body composition. An ANCOVA test revealed unclear between-group differences. In conclusion, both protocols increased basketball players' strength without the use of heavy loads (> 85% 1RM) and without impairing sprint, CMJ and SLJ performance. These findings suggest that basketball strength and conditioning professionals may use either method to counteract strength losses during the season.

Recent acute studies have shown that high-intensity resistance circuit-based (HRC) training in hypoxia increases metabolic stress. However, no intervention studies have yet proven their effectiveness. This study aimed to analyze the effect of 8 weeks of HRC in hypoxia on aerobic performance, resting energy expenditure (REE), repeat sprint ability (RSA) and hematological variables. Twenty-eight subjects were assigned to hypoxia (FiO = 15%; HRC : n = 15; age: 24.6 ± 6.8 years; height: 177.4 ± 5.9 cm; weight: 74.9 ± 11.5 kg) and normoxia (FiO = 20.9%; HRC : n = 13; age: 23.2 ± 5.2 years; height: 173.4 ± 6.2 cm; weight: 69.4 ± 7.4 kg) groups. Each training session consisted of two blocks of three exercises (Block 1: bench press, leg extension, front pull down; 2: deadlift, elbow flexion, ankle extension). Each exercise was performed at 6 repetitions maximum. Participants exercised twice weekly for 8 weeks and before and after the training program blood test, REE, RSA and treadmill running test were performed. Fatigue index in the RSA test was significantly decreased in the HRC (-0.9%; P < .01; ES = 2.75) but not in the HRC . No changes were observed in REE and hematological variables. Absolute (4.5%; P = .014; ES = 0.42) and relative (5.2%; P = .008; ES = 0.43) maximal oxygen uptake (VO max), speed at VO max (4%; P = .010; ES = 0.25) and time to exhaustion (4.1%; P = .012; ES = 0.26) were significantly increased in HRC but not in the HRC . No significant differences between groups were found. Compared with normoxic conditions, 8 weeks of HRC training under hypoxic conditions efficiently improves aerobic performance and RSA without changes in REE and red blood O -carrying capacity.

Background: Elderly caregivers present increased physical and mental health problems. These factors can lead to a lack of autonomy and a need for social support. This study aims to analyse the relationships between perceived social support and mental health status in elderly caregivers aged 65 and older. Methods: a cross-sectional study based on data from the Spanish National Health Survey (ENSE-17) carried out on 7023 people. The study population was restricted to 431 caregivers aged ≥65 years. A study of the correlation between the mental health state and the perceived social support was carried out. Both variables were related to the sex of the caregiver. Results: Perceived social support by older caregivers is significantly related to mental health (p = 0.001), and stress (p < 0.001). Also, there is a significant relationship between perceived social support and mental well-being (p = 0.001), self-esteem (p = 0.005) and stress (p = 0.001) in older women caregivers. Conclusions: Older caregivers have adequate mental well-being and perceive high social support. Perceived social support can contribute to improving the mental well-being of older caregivers.