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Carbon footprint stemming from ice sports on the Turkey and Lithuanian scale /
No full textThe aim of this study is to calculate the average carbon footprint per capita from the transportation of the Ice Hockey League in Turkey and Lithuania in the 2021–2022 season. In addition, we identified the opinions of team managers of the national hockey leagues in Turkey and Lithuania regarding the problems and possible solutions related to the sustainable environment and persons’ right to a clean and safe environment in the sport sector. In this study, which was limited to the Turkish Ice Hockey Intercity Super League and the Lithuanian National Ice Hockey League in the 2021–2022 Season, eight teams from Turkey and five teams from Lithuania took part in the research. The type of vehicle used by each team and the total traveled distance were used for the collection of data. Interviews were conducted using a semi-structured interview format seeking to identify problems and solutions proposed by sports managers regarding environmental sustainability and the implementation of persons’ right to a clean and safe environment in the sport sector. Five managers from Turkey and two managers from Lithuania were randomly selected for the research. The average carbon footprint per person was calculated as 88.23 kg/CO2-e due to the travels of the Ice Hockey Super League teams participating in the 2021–2022 Season matches in Turkey. The average carbon footprint per capita was calculated as 0.5229 kg/CO2-e, as Ice Hockey Super League teams in the 2021–2022 Season traveled to participate in matches organized in Lithuania. For solving the above-mentioned problems, the sports experts offered recommendations such as energy saving, less waste generation and reducing water consumption in order to achieve the environmental protection goals of the sports leaders. Since both teams often travel due to the intense league schedules, the Ice Hockey Super League goal should be to reduce carbon emissions, especially those related to transportation. Energy conservation policies should also be implemented, and environmentally friendly practices should be emphasized
Seilių testosterono ir kortizolio rodiklių pritaikomumas krepšininkų stebėsenoje.
No full textIn the scientific field of basketball, salivary T, C and T:C are the most investigated and adopted markers to monitor hormonal responses to given loads during different typologies of training and matches (Moreira et al., 2013; Nunes, Crewther, Viveiros, et al., 2011; Sansone et al., 2019). An analysis of these markers is indicated as an essential method to determine the balance between anabolic and catabolic processes (Kamarauskas & Conte, 2022a), allowing to evaluate the process of training and recovery in basketball. In general, an increase in T levels indicates an appropriate recovery, whereas decrease in T levels and increase in C levels represents a possible risk of overtraining, non-functional overreaching and reduced performance (Coutts et al., 2007). Previous investigations, assessing changes in hormonal responses showed that the analysis of salivary markers could be used as valuable monitoring tool in basketball. However, a more detailed analysis of hormonal responses in combination with load measures and well-being variables in different basketball populations, during different phases of the season, could provide basketball coaches the benchmarks of load, well-being, and hormone measures. Moreover, there are no findings, if changes in load measures, and well-being variables can influence changes in hormonal responses, which would indicate if hormonal levels of basketball players are affected by changes in other measures. Such findings would allow to understand if measures of load variables can be used to anticipate changes in hormonal responses. The research described in this doctoral dissertation includes four scientific studies, addressing differently designed but related research questions. The assessment of weekly fluctuations in hormonal responses in different basketball populations (i.e., semi-professional and professional, male players), during different phases of the season (i.e., pre-season and in-season) were investigated in study 1 (Chapter II), study 3 (Chapter IV), and study 4 (Chapter V). The second study question, a comparison of weekly changes in hormonal responses in relation to changes in load measures and well-being between European- and national-level professional, male basketball players was investigated in study 4 (Chapter V). Finally, the last study question of this research, investigating relationships and associations between weekly changes in hormonal responses and weekly changes in load measures and players’ well-being during different phases of the season in different basketball populations were investigated in study 1 (Chapter II), study 2 (Chapter III), and study 3 (Chapter IV). The methodological design of all four investigations of this research was observational. Only semi-professional (Chapter II) and professional (Chapter III; Chapter IV; Chapter V), male basketball players were selected as participants of this research. The inclusion criteria of participants in all four studies were based on the attendance, and only participants with attendance of ≥75% of total training sessions and matches combined, were included for the final analysis of each study. The monitoring periods of all studies described in this research were implemented, following the actual schedules of pre-season or in-season phases of investigated teams, without applying any experimental changes for the research purposes. Data was collected during strength and conditioning (except weight room sessions), basketballspecific on-court training sessions, and depending on the study, during in-season official matches or pre-season friendly matches. During the data collection, saliva samples were collected for the analysis of changes in levels of T, C, and T:C (Andre et al., 2018; Arruda et al., 2018; Nunes et al., 2014). External load measures (PL and PL·min-1 ) were monitored using triaxial accelerometers ClearSky T6 (Catapult Innovations, Melbourne, Australia) sampling at 100 Hz to calculate instantaneous movement demands (in arbitrary units, AU) (Fox et al., 2020b; Scanlan et al., 2014). Internal load measures were monitored using the sRPE method (Foster, 1998), and HR measures (Berkelmans, Dalbo, Kean, et al., 2018). The sRPE method and total duration (min) of each training session and match were used together to calculate sRPE-load in AU. Subsequently, these data were used to calculate weekly monotony and strain variables (Foster, 1998). HR was measured by Polar H10 chest-worn straps (Polar Electro; Kempele, Finland), and subsequently collected and processed via OpenField software (version 1.18, Catapult Innovations; Melbourne, Australia), to calculate SHRZ load (AU) (S. Edwards, 1994), and %HRmax (Berkelmans, Dalbo, Kean, et al., 2018). HRmax of each participant was determined as the peak HR attained during a maximal 30-15 Intermittent Fitness Test performed on a basketball court at the beginning of the monitoring period (Buchheit, 2008). The maximum HR attained during this initial testing was updated to a new peak value if it was superseded by HR responses recorded during training sessions or friendly matches throughout the monitoring period (Berkelmans, Dalbo, Fox, et al., 2018). An established well-being questionnaire was used to assess perceived fatigue, sleep quality, general muscle soreness, stress, and mood on a five-point Likert scale (scores from 1-5) (Conte et al., 2018). Overall well-being was then calculated by summing the scores across each item assessed (Conte et al., 2018). Ethical approval was obtained from the Kaunas Regional Research Ethical Committee review board (No. BE-2-97). The first purpose of this research was to assess weekly fluctuations in hormonal responses during different phases of the season, in different basketball populations. Three studies of this doctoral dissertation were aiming to assess weekly fluctuations in hormonal responses during a 4-week period of the in-season phase in semiprofessional, male players (Chapter II), across a 5-week pre-season phase in professional, male players (Chapter IV), and across a 5-week pre-season phase of European- and national-level professional, male basketball players (Chapter V). The results of three investigations showed different findings on weekly fluctuations in hormonal responses. In study 1 (Chapter II), a congested in-season phase with a constant external load and decrease in internal load measures was found causing a decrease in T and C levels, and no changes in T:C ratio. As T:C remained stable across a monitoring period, a possible explanation of imbalance between load and recovery negatively affecting T levels was rejected. A negative effect on T levels most possibly occurred due to the constant losing in official matches, resulting in a lower willingness to compete and decreased T levels (Mehta & Josephs, 2006). Contrary, a constant losing in matches did not cause an increase in C levels, which was found decreasing towards the end of the investigated period. During the in-season phase, levels of C were previously shown to increase due to a higher accumulated physical stress (Moreira et al., 2011; Nunes et al., 2014). Therefore, as monitoring period of study 1 (Chapter II) was in the middle of the in-season, a possible explanation of decreased C levels might be a lower accumulated physical stress than in other investigation, which reported an increase in C levels in the end of the in-season phase (Moreira et al., 2011). Differently than during the in-season phase in semi-professional, male basketball players, study 3 (Chapter IV) and study 4 (Chapter V) provided inconsistent findings of hormonal responses during the pre-season phase in professional, male basketball players. An increase in T and T:C levels, and no changes in C levels during the pre-season phase were found in two European-level teams (Chapter IV). Inversely, no changes or differences in T levels across the pre-season phase, but higher C and lower T:C levels in the beginning of the pre-season phase were found for the European-level team, when compared to the national-level team and other weeks of the pre-season phase (Chapter V). A different findings emphasize the importance of load management process during the pre-season phase, to maintain an appropriate balance between anabolic and catabolic processes (Alba-Jimenez et al., 2022). The main conclusion of the assessment of weekly fluctuations in hormonal responses during the in-season and pre-season phases in semi-professional and professional, male basketball players indicates the usefulness of monitoring hormonal responses in basketball to evaluate changes and maintain an appropriate balance between anabolic and catabolic processes across different phases of the season. The second purpose of this research was to compare two professional, male basketball teams, preparing for the season at different playing levels, i.e., Europeanand national-level (Chapter V). The main findings of this investigation showed different load periodization strategies, depending on playing level. European-level team, preparing for the congested season schedule had increasing training load, while national-level team, preparing for a less congested in-season phase had decreasing training load towards the end of the pre-season phase. The explanation of this dissimilarity is most possibly related to the differences in the upcoming in-season phase, which teams were trying to replicate during the pre-season phase. When considering hormonal responses, these differences in load periodization, induced no differences between teams in T levels, while European-level team had a higher C and T:C levels at week 1 of the pre-season phase. A higher European-level team C and T:C ratio levels in the beginning of monitoring period, resulted in an overall higher level of C and T:C across the pre-season phase. The main conclusion of the assessment of differences between European- and national-level professional, male basketball teams during the pre-season phase is that load periodization in preparation to play at a higher level and more congested in-season schedule, has a negative impact on the balance between anabolic and catabolic processes. The last goal of this doctoral thesis was to quantify the relationships between weekly changes in hormonal responses and weekly changes in load variables, and players’ well-being, during different phases of the season in different basketball populations. The relationships between weekly changes in T, C and T:C responses and weekly changes in external and internal load, and well-being variables during the inseason phase in semi-professional, male basketball players were investigated in study 1 (Chapter II). Relationships between separately and jointly considered weekly changes in load measures and hormonal responses during the pre-season phase in professional, male basketball players were examined in study 2 (Chapter III). The associations between weekly changes in hormonal responses and load measures with weekly changes in well-being during the pre-season phase in professional, male basketball players were determined in study 3 (Chapter IV). The main findings of study 1 (Chapter II) showed non-significant, trivial-to-moderate relationships between weekly changes in hormonal responses and weekly changes in load and well-being variables during the in-season phase in semi-professional, male basketball players. Similarly, study 2 (Chapter III) showed that neither separately, neither jointly considered changes in load measures are not influencing changes in weekly hormonal responses, during the pre-season phase in professional, male basketball players. Additionally, study 3 (Chapter IV) showed only negative and weak associations between weekly changes in well-being and weekly changes load measures, and no associations between weekly changes in well-being and weekly changes in hormonal responses, during the pre-season phase in professional, male basketball players. The findings of all three studies suggest that other measures than investigated in these studies or combination of them might be influencing weekly fluctuations in hormonal responses. Moreover, these findings suggest that all investigated measures might provide a unique insight about training and recovery process in basketball and should be separately used for the monitoring of basketball players. The main conclusion of the quantification of relationships and associations between weekly changes in hormonal responses, load measures, and well-being variables indicates that these measures are not influencing weekly changes in between each other and that weekly fluctuations in these variables might be induced by other physical, physiological, psychological measures or combination of factors
The effect of strength and dual task exercises on the physical, functional performance and cognitive functions of premenopausal women.
No full textResearch problem. Will strength or combined strength and cognitive exercises improve the physical, functional performance and cognitive functions of women in the perimenopausal period? The goal. Determine the effect of strength and cognitive exercises on the physical, functional performance and cognitive functions of women in the perimenopausal period. Tasks of the research: 1. To assess the effect of strength exercises on women's physical, functional performance and cognitive functions in the perimenopausal period. 2. To evaluate the effect of combined strength and cognitive training on women's physical, functional performance and cognitive functions in the perimenopausal period. 3. To compare the effects of combined strength and cognitive exercises with strength exercises on physical, functional performance and cognitive functions of premenopausal women. Hypothesis. Found that strength training can improve women's physical and cognitive function (Coelho-Júnior et al., 2020), but we believe that strength training combined with cognitive training will have a greater effect on women's physical, functional indicators and cognitive functions than strength training alone. Methodology of the research. The study included 30 women (aged 49.1 ± 3.2 years) who were randomly divided into two groups: combined strength and cognitive exercises (n=15) and strength exercises (n=15). Body mass components are assessed using the segmental body composition analyzer TANITA. Functional status - Functional movement assessment test. Hand grip strength - dynamometer. Reaction time and memory were evaluated with the computer program ANAM4™ TBI Battery. Apply exercises for 6 weeks. 3 times a week for 30 min. Results of the study: In both groups, body mass decreased (p 0.05). Conclusion. Combined strength and cognitive training improved women's physical and functional performance and cognitive function more than strength training alone
Ilgalaikės adaptacijos plaukime matematiniai modeliai.
No full textDuring athletes' career, there are different periods of adaptation where training specific physical ability will give bigger benefits. By using the trend of elite athlete’s progression and following biological maturation we can create a long-term development model. There have been different kinds of performance progression analyses for world championships and Olympics but not so much information about record holders, how did they progress in long-term training. The main aim of the study is to identify the ratios between distances and to create long term performance progression model for top-performing swimmers. The hypothesis is that the ratios between times and long-term performance progression models will make it possible to link athletes results to the training used. In this study the author used data from usaswimmnig.com and swimranking.com databases to create the top 15 male all-time performance models for each group. There were 3 groups’ sprinters, middle distance swimmers and distance swimmers – for distances over 100m, 400m and 1500m, respectively – Each group had top-15 male swimmers in the world. After choosing times over several distances for them were ratios between times were calculated for every swimmer. During this study the author used data collection, mathematical and statistical methods to identify the ratios between distances and to create performance progression models. The results showed how athletes train in each year and give a clear understanding of training trends. The performance model shows top-level athletes' progression, and it can be used either for setting goals to achieve or to monitor athletes' progression
The immediate effect of 90 sec. duration plantar myofascial release on static and dynamic balance and injury risk in female volleyball players.
No full textBackground. Self-administered plantar myofascial release with a tennis ball is a widely used technique to increase flexibility and range of motion, but it is unclear how effective this technique is on static and dynamic balance and injury risk in volleyball players. The aim. To determine the immediate effect of short-term (90 s duration) plan-tar myofascial release on the static and dynamic balance and injury risk of females playing volleyball. Methods. The study involved 26 female volleyball players who were randomly assigned to one of two groups. Subjects in the control group (n=13) received no intervention and were retested for 180 s. since initial testing. The participants of the study group received self-administered plantar myofascial release of 90 s duration with tennis ball for one leg and 90 s duration on the other leg (all together duration 180 s). A modified star excursion (Y test) test was used to assess dynamic balance. Static balance was assessed by the Flamingo test. Results. Myofascial release improved (p0.05) from the initial assessment. The combined dynamic balance score improved (p<0.05) only in the control group that had a rest break instead of the intervention. No significant differences were found in static balance results either between groups or within groups. Conclusions. Immediate short duration plantar myofascial release was not effective on static and dynamic balance and injury risk in volleyball players. The effect of short-term myofascial release did not differ from that of no intervention
Stanniocalcin‐2 inhibits skeletal muscle growth and is upregulated in functional overload‐induced hypertrophy /
No full textStanniocalcin‐2 (STC2) has recently been implicated in human muscle mass variability by genetic analysis. Biochemically, STC2 inhibits the proteolytic activity of the metalloproteinase PAPP‐A, which promotes muscle growth by upregulating the insulin‐like growth factor (IGF) axis. The aim was to examine if STC2 affects skeletal muscle mass and to assess how the IGF axis mediates muscle hypertrophy induced by functional overload
An ecological investigation of average and peak external load intensities of basketball skills and game-based training drills /
No full textThis study quantified average and peak external intensities of various basketball training drills. Thirteen youth male basketball players (age: 15.2±0.3 years) were monitored (BioHarness-3 devices) to obtain average and peak external load per minute (EL·min−1; peak EL·min−1) during team-based training sessions. Researchers coded the training sessions by analysing the drill type (skills, 1vs1, 2vs2, 3vs0, 3vs3, 4vs0, 4vs4, 5vs5, 5vs5-scrimmage), court area per player, player’s involvement in the drill (in percentage), playing positions (backcourt; frontcourt) and competition rotation status (starter; rotation; bench). Separate linear mixed models were run to assess the influence of training and individual constraints on average and peak EL·min−1. Drill type influenced average and peak EL·min−1 (p 0.05), except for a moderately higher EL·min−1 in starters compared to bench players. The external load intensities of basketball training drills substantially vary depending on the load indicator chosen, the training content, and task and individual constraints. Practitioners should not interchangeably use average and peak external intensity indicators to design training but considering them as separate constructs could help to gain a better understanding of basketball training and competition demands
Health literacy and lifestyle characteristics of teatchers.
No full textResearch problem: the level of health literacy of teachers and the interrelationship between healthy lifestyles. The purpose of the study is to determine the level of health literacy of teachers and to find out the characteristics of their lifestyle. Research objectives: 1. To determine teachers' general and digital health literacy. 2. To assess the association of socio-demographic factors with teachers' health To evaluate the correlations of socio-demographic factors with teachers' health literacy. 3. To find out the peculiarities of teachers' lifestyles. 4. To reveal the connections between teachers' health literacy and lifestyle. Research methods. - Lithuanian version of the questionnaire developed by the Action Network on Measuring Population and Organisational Health Literacy (M-POHL), an initiative of the World Health Organisation, in 2018. - The HLS19-Q47 questionnaire is adapted from the short version of the HLS19-Q12 scale. - HLS19-DIGI scale. - Questions on gender, age, length of service, qualification category, social status. Main results. The survey revealed that more than half of teachers have sufficient or excellent general health literacy. Teachers' digital health writing is only average. The study of teacher age and social assessment was significantly associated with both general and digital teacher health records. In the study of lifestyle, it was found that the majority of teachers rate their health as good or sufficient. 14.4 percent are sufficiently physically active. teachers. Eight out of ten teachers do not smoke for a year and on average. It was established that last year 21.3 percent did not drink alcohol at all. teachers, and in the last 30 days - a third of teachers. Summarising concusion. While the overall health writing of the teachers is good, the digital writing is only average. Teachers' age and social status are related to their health literacy. Teachers take care of their health and have few bad habits. On the other hand, no significant correlations were found between students' health literacy and lifestyle indicators
Rankinio ergometro treniruočių poveikis vyrų ir moterų, sėdinčių neįgaliųjų vežimėliuose, aerobiniam pajėgumui, sisteminė apžvalga.
No full textAim of the study: The aim of this thesis is to investigate the effectiveness of hand ergometer training in improving the aerobic capacity of wheelchair users and to find its relation in male and female population. Objectives: The main objectives of the study are as follows: 1) To find the relation between gender and effect of hand ergometer training. 2) To figure out the most advantageous duration of training per session. 3) To determine the effectiveness of the various upper body ergometer training programs in terms of aerobic capacity. 4) To evaluate the auspicious hand ergometer training program for wheelchair users. Hypothesis: In this research we hypothesize that there are benefits of hand ergometer training and it can be observed in both male and female wheelchair users. Research methods: The databases of PubMed, Google Scholar, SciHub, Scidirect and EMBASE were searched up to March 2023. The keywords included “wheelchair”, “arm ergometer”, “disability”, “hand cycle” and “upper body ergometer” in relation to aerobic capacity. 10 studies were selected based on the inclusion and exclusion criteria. In the 10 articles of acceptable quality of mean (SD) increase in VO2 peak following a period of training was 2.7 ml/kg/min. Conclusion: The ratio of men to women in the represent study was 4:1, most studies included participants of both genders but not enough data was found to make a remark on the effect of hand ergometer in male and female population. The most advantageous training routine was of 30 minutes with warm up and cooldown phase for 6 weeks training with 3 alternate day sessions per week. Hand ergometer training has proven to show significant improvement in aerobic capacities with a minimum of 6-week training. The endurance training has shown the significant change with highest effect size followed by aerobic and aerobic interval trainings. Hand ergometer training is beneficial in the rehabilitation phase as well as chronic phase of the disability
Latentinė situacinio efektyvumo kintamųjų struktūra elitiniame moterų krepšinyje.
No full textResearch problem question: Which standard situational efficiency indicators should be most important in a team's offensive and defensive structure? Aim of the study: The goal of this research is to determine the latent structure of standard indicators of situational efficiency, in elite women’s basketball; in order to determine the assumed functional dependence, and thus gain a more complete insight into their interaction. Methodology: 1. Scientific literature review 2. Statistical data collection 3. Statistical analysis using Statistica 13.2 and Microsoft Excel software Standard situational efficiency indicators are derived from the game logs on “Women’s EuroLeague on FIBA.com” (FIBA, 2022). The 13 standard indicators of the teams situational efficiency consist of the following: Two-point field goals made (2FGM), Two-point field goals attempted (2FGA), Three-point field goals made (3FGM), Three-point field goals attempted (3FGA), Free throws made (FTM), Free throws attempted (FTA), Offensive rebounds (OFF), Defensive rebounds (DEF), Assists (AST), Personal fouls (PF), Steals (STL), Blocks (BLK) and Turnovers (TO). WIN% and LOSS% were used to determine whether a Euroleague women’s team was a winning or losing team