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Search Results (283)

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14 pages, 621 KiB  
Article
“One Size Doesn’t Fit All”: Design Considerations for an Exercise Program to Improve Physical Function in Older Veterans with Serious Mental Illness
by Julia Browne, Whitney L. Mills, Courtney T. Lopez, Noah S. Philip, Katherine S. Hall, Alexander S. Young, Kate M. Guthrie and Wen-Chih Wu
Int. J. Environ. Res. Public Health 2025, 22(2), 191; https://doi.org/10.3390/ijerph22020191 - 29 Jan 2025
Viewed by 334
Abstract
Older adults with serious mental illness (SMI) (i.e., schizophrenia, schizoaffective disorder, bipolar disorder) have compromised physical function that adversely affects their quality of life. Exercise is an effective intervention to improve function in older persons; however, older people with SMI experience barriers to [...] Read more.
Older adults with serious mental illness (SMI) (i.e., schizophrenia, schizoaffective disorder, bipolar disorder) have compromised physical function that adversely affects their quality of life. Exercise is an effective intervention to improve function in older persons; however, older people with SMI experience barriers to exercise engagement. This study sought to obtain feedback on an exercise program in development for older people with SMI that comprised home-based exercise delivery, individualized exercise prescription, and motivational health coaching calls. Individual interviews and focus groups were conducted with older Veterans with SMI (n = 3) and clinical staff serving this population (directors: n = 3; clinicians: n = 15, k = 3) to elicit feedback on the perceived feasibility and acceptability of the preliminary program and recommendations for modifications to the program. Rapid analysis was used to summarize transcripts of audio-recorded interviews and focus groups. Results indicated a strong perceived feasibility and acceptability of the preliminary intervention because of how the individualized exercise prescription component (i.e., exercise plan) would be personalized to the Veteran’s preferences and abilities. Clinical staff participants expressed concerns about how the lack of real-time supervision would negatively affect exercise completion. Participants recommended tailoring the home-based exercise delivery and motivational health coaching calls components to each Veteran’s unique context. Full article
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<p>Preliminary exercise program components.</p>
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12 pages, 1302 KiB  
Article
Towards Personalized Recovery in Handball? The Effects of Playing Positions and Player Role on Internal Match Load and Well-Being Responses in Female Players
by Carlos García-Sánchez, Raúl Nieto-Acevedo, Jorge Lorenzo-Calvo, Moisés Marquina Nieto, Rafael Manuel Navarro and Alfonso de la Rubia
Appl. Sci. 2025, 15(3), 1228; https://doi.org/10.3390/app15031228 - 25 Jan 2025
Viewed by 385
Abstract
The aim of this study was to analyze the effects of the playing position (backs vs. pivots vs. wings) and the player role (starter vs. non-starter) on the internal match load and well-being status of female handball players after official matches. Fourteen female [...] Read more.
The aim of this study was to analyze the effects of the playing position (backs vs. pivots vs. wings) and the player role (starter vs. non-starter) on the internal match load and well-being status of female handball players after official matches. Fourteen female handball players from the Spanish 2nd Division were monitored during a half-season (13 matches, n = 102 individual observations) using the rate of perceived exertion (match RPE) and the Hooper questionnaire in MD+1 and MD+2. Differences in match RPE according to playing positions and player roles were determined by one-way ANOVA or by a paired t-test, respectively. Differences in well-being status according to playing positions or player roles and time (MD+1 and MD+2) were assessed through mixed two-way ANOVA. Furthermore, partial eta-squared (ηp2) and Cohen’s d (ES) were calculated and interpreted using Hopkins’ categorization criteria. Backs registered moderately more match RPE compared to pivots (p < 0.05, ES = 0.84). By contrast, wings experienced the highest values of fatigue and muscle soreness in MD+1 and MD+2 compared to all other playing positions (p < 0.05, ES = 0.66–0.93). Also, the wings reported moderately higher Hooper index scores in MD+1 and MD+2 than backs (p < 0.01, ES = 0.73–0.77). In relation to the player role, starters reported higher absolute values of match RPE, fatigue, muscle soreness, and the Hooper index in MD+1 compared to non-starters (p < 0.05, ES = 0.25–0.29). Additionally, regardless of the playing position and the role, all of the players reported moderately less fatigue and Hooper index scores in MD+2 compared to MD+1 (p < 0.05, ES = 0.66–1.34). Therefore, coaches and practitioners should consider the internal match load and well-being status of players to implement different training stimuli (e.g., recovery or compensatory strategies) in MD+1 according to playing positions and player roles. Full article
(This article belongs to the Special Issue Exercise, Fitness, Human Performance and Health: 2nd Edition)
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<p>Timeline of this study.</p>
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<p>Differences according to playing positions and player roles on match RPE. Significance level is indicated by the number of symbols: one symbol for <span class="html-italic">p</span> &lt; 0.05, two for <span class="html-italic">p</span> &lt; 0.01, and three for <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Differences according to playing positions on well-being status. Significance level is indicated by the number of symbols: one symbol for <span class="html-italic">p</span> &lt; 0.05, two for <span class="html-italic">p</span> &lt; 0.01, and three for <span class="html-italic">p</span> &lt; 0.001. * = Significant differences between playing positions. † = Significant differences vs. MD+1.</p>
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<p>Differences according to player role on well-being status. Significance level is indicated by the number of symbols: one symbol for <span class="html-italic">p</span> &lt; 0.05, two for <span class="html-italic">p</span> &lt; 0.01, and three for <span class="html-italic">p</span> &lt; 0.001. * = Significant differences between starters and non-starters. † = Significant differences vs. MD+1.</p>
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28 pages, 437 KiB  
Systematic Review
Exploring the Effects of Professional Learning Experiences on In-Service Teachers’ Growth: A Systematic Review of Literature
by Zhadyra Makhmetova, Laura Karabassova, Assel Zhakim and Abylay Karinov
Educ. Sci. 2025, 15(2), 146; https://doi.org/10.3390/educsci15020146 - 24 Jan 2025
Viewed by 636
Abstract
This systematic review examines the effects of professional learning (PL) experiences on in-service teachers’ self-perceived growth. The study compares formal and informal PL models, drawing on diverse approaches, such as coaching, mentorship, collaborative learning, and reflective practices, to understand how these frameworks impact [...] Read more.
This systematic review examines the effects of professional learning (PL) experiences on in-service teachers’ self-perceived growth. The study compares formal and informal PL models, drawing on diverse approaches, such as coaching, mentorship, collaborative learning, and reflective practices, to understand how these frameworks impact teachers’ professional efficacy and instructional practices. Using databases like Scopus, Web of Science, and ERIC we analyzed 38 empirical studies, focusing on the teachers’ PL experiences and the resulting self-perceived professional growth across its various domains. The findings indicate that while formal PD sessions (e.g., structured workshops and seminars) support skill development, they often yield mixed results due to their limited adaptability to specific contextual needs. In contrast, informal PL approaches, like mentorship and peer collaboration, foster reflective and practical growth. Combining both PL methods provides the most comprehensive benefits, blending structured learning with the flexibility of informal settings. This review underscores the need for hybrid PL models that address collective and individualized growth pathways, recommending future research into context-sensitive, mixed PL designs to effectively support in-service teachers. Full article
(This article belongs to the Section Teacher Education)
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<p>PRISMA flow diagram.</p>
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12 pages, 1158 KiB  
Article
Does Higher Maturation Make Age-Grouped Swimmers Faster? A Study on Pubertal Female Swimmers
by Kamil Sokołowski, Piotr Krężałek, Łukasz Wądrzyk, Magdalena Żegleń and Marek Strzała
Appl. Sci. 2025, 15(3), 1171; https://doi.org/10.3390/app15031171 - 24 Jan 2025
Viewed by 298
Abstract
Background: The main aim of this study was to identify the differences between subgroups of swimmers based on physiological (peak oxygen uptake—VO2peak), strength (average tethered swimming force—60Fave), stroke kinematics (v100—swimming speed at 100 [...] Read more.
Background: The main aim of this study was to identify the differences between subgroups of swimmers based on physiological (peak oxygen uptake—VO2peak), strength (average tethered swimming force—60Fave), stroke kinematics (v100—swimming speed at 100 m front crawl, stroke rate—SR, stroke length—SL), and anthropometrical (i.e.,: biological age—BA, body height—BH, body mass—BM) factors within swimmers at different levels of maturity (BA). Methods: This study involved 39 female swimmers (age: 12.88 ± 0.54 years, BA: 13.98 ± 1.91 years). Cluster analysis (k-cluster) and stepwise multiple regression was performed. Results: Significant correlations were observed between v100 and BA, 60Fave, AS, VO2peak. Stepwise multiple regression indicated 60Fave and VO2peak as the main explanatory variables of v100 (R2 = 0.60, p < 0.0001). Cluster analysis allowed us to distinguish three groups of swimmers, differing in BA (cluster 1: 14.07 ± 0.96 years, cluster 2: 17.05 ± 1.53, cluster 3: 11.94 ± 0.95) and v100, as well as in BH, FFM, AS. Conclusions: There were differences between cluster groups, with early mature swimmers characterized by the highest BH, FFM, AS, 60Fave, and VO2peak. Probably, biologically younger late mature swimmers (cluster 3) are slower than the other 2 groups (cluster 1 and 2) because of being less somatically developed. Based on these study results, coaches should ensure further development of aerobic and anaerobic conditioning among normal mature swimmers with simultaneous focus on improving technique skills among early mature ones. Full article
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<p>One of the participants during the 1 min tethered swimming test.</p>
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<p>Flowchart presenting the study design.</p>
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<p>Visualization of 3 clusters identified by k-cluster analysis. Dots represent individuals categorized to clusters.</p>
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17 pages, 1490 KiB  
Article
Athletes’ Perceived Team Climate, Social Support, and Optimistic Thoughts During the COVID-19 Pandemic
by Chelsi E. Scott, Mary D. Fry, Troy O. Wineinger, Susumu Iwasaki, Haiying Long and Theresa C. Brown
Int. J. Environ. Res. Public Health 2025, 22(1), 46; https://doi.org/10.3390/ijerph22010046 - 31 Dec 2024
Viewed by 583
Abstract
In the Spring of 2020, Coronavirus 2019 (COVID-19) was officially declared a global pandemic, which prompted an unprecedented number of changes to societal functioning. Amongst those who experienced significant life alterations were collegiate athletes within the United States (US). The purpose of this [...] Read more.
In the Spring of 2020, Coronavirus 2019 (COVID-19) was officially declared a global pandemic, which prompted an unprecedented number of changes to societal functioning. Amongst those who experienced significant life alterations were collegiate athletes within the United States (US). The purpose of this study was to examine the relationship between US athletes’ perceptions of their team motivational climate, perceived support from coaches and teammates, and their optimistic thoughts during the COVID-19 pandemic. US collegiate athletes (N = 756; 56.3% female; Mage = 20.07 years, SDage = 1.57 years) across a variety of levels (e.g., Division I) and sports (e.g., basketball) were invited to participate in this study. Structural equation modeling analyses revealed significant positive associations between a caring and task-involving climate, athletes’ feeling supported by their coaches and teammates, and athletes’ optimistic thoughts during the COVID-19 pandemic. In addition, an ego-involving climate was significantly negatively associated with athletes’ feeling supported by their coaches and teammates. The final results suggest that the supportive actions of coaches and teammates during difficult times can mediate the positive connection between perceptions of a caring-task-involving climate on athletic teams and an athlete’s ability to stay optimistic during difficult life stressors. Full article
(This article belongs to the Special Issue Physical Fitness and Exercise during and after the COVID-19 Pandemic)
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<p>Confirmatory Factor Analysis. Note. CC = Caring Climate; TIC = Task-Involving Climate; EIC = Ego-Involving Climate; SFC = Support from Coaches; SFT = Support from Teammates; OT = Optimistic Thinking.</p>
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<p>Model 1: CC—SFC and SFT—OT. Note. TIC = Task-Involving Climate; SFC = Support from Coaches; SFT = Support from Teammates; OT = Optimistic Thinking; SCH = Scholarship. All significant relationships are in bold. Observed variables and factor loadings are excluded from the figure for space; however, factor loadings are very close to those in the CFA.</p>
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<p>Model 2: TIC—SFC and SFT—OT. Note. TIC = Task-Involving Climate; SFC = Support from Coaches; SFT = Support from Teammates; OT = Optimistic Thinking; SCH = Scholarship. All significant relationships are in bold. Observed variables and factor loadings are excluded from the figure for space; however, factor loadings are very close to those in the CFA.</p>
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<p>Model 3: EIC—SFC and SFT—OT. Note. EIC = Ego-Involving Climate; SFC = Support from Coaches; SFT = Support from Teammates; OT = Optimistic Thinking; SCH = Scholarship. All significant relationships are in bold. Observed variables and factor loadings are excluded from the figure for space; however, factor loadings are very close to those in the CFA.</p>
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35 pages, 661 KiB  
Article
Managing Stress and Somatization Symptoms Among Students in Demanding Academic Healthcare Environments
by Maria Antoniadou, Georgia Manta, Antonia Kanellopoulou, Theodora Kalogerakou, Alessandra Satta and Polyxeni Mangoulia
Healthcare 2024, 12(24), 2522; https://doi.org/10.3390/healthcare12242522 - 13 Dec 2024
Cited by 1 | Viewed by 920
Abstract
Introduction: Stress is a common concern among healthcare students, due to the demands of their coursework and the elevated expectations they face. Especially among dentistry and nursing students, the phenomenon, although well-documented, covers psychosocial and physiological dimensions, with somatization symptoms being less explored. [...] Read more.
Introduction: Stress is a common concern among healthcare students, due to the demands of their coursework and the elevated expectations they face. Especially among dentistry and nursing students, the phenomenon, although well-documented, covers psychosocial and physiological dimensions, with somatization symptoms being less explored. These manifestations are crucial to identify discipline-specific stressors and health impacts that can lead to targeted interventions for both disciplines. Aim: This study investigates stress perceptions, somatization, and coping strategies among 271 nursing and dentistry students at the National and Kapodistrian University of Athens. Methodology: An e-questionnaire was open for submissions during February and March 2024. Results: Females reported higher stress somatization (M = 10.22, SD = 5.23) than males (M = 7.94, SD = 6.14; Cohen’s d = 0.412, p < 0.05). The interpretation of stress as “restlessness and psychological pressure” was more prevalent in dentistry students compared to nursing students. Moreover, nursing students who perceived stress as the “inability to manage unexpected or difficult situations, insecurity, panic” were more likely to experience stress somatization symptoms, while for dentistry students, stress somatization was related to “pressure to meet daily obligations/long-term goals”. Physical symptoms for all students included chest discomfort, digestive issues, and headaches/nausea. Also, dentistry students reported more teeth clenching or grinding than nursing students. Short-term coping strategies included emotional balance, managing stressors, situation analysis, and breathing techniques. Long-term strategies involved distraction and entertainment, physical exercise, and patience. A higher willingness to seek coaching support correlated with higher stress somatization among dental students. Nursing students favored psychological support, while dentistry students suggested curriculum revision and improved infrastructure. Discussion/Conclusions: Females exhibited higher stress somatization levels, with themes of insecurity and physical symptoms. Nursing students reported higher somatization linked to insecurity, while dental students associated stress with daily obligations and goals. The study highlights the need for improved support systems, flexible academic procedures, and better communication to address stress in healthcare academia. Full article
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<p>Clustered bar chart of clenching or grinding teeth during the day or night by the department.</p>
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13 pages, 665 KiB  
Article
The Relationship Between Training Load and Injury in Competitive Swimming: A Two-Year Longitudinal Study
by Lorna Barry, Mark Lyons, Karen McCreesh, Tony Myers, Cormac Powell and Tom Comyns
Appl. Sci. 2024, 14(22), 10411; https://doi.org/10.3390/app142210411 - 12 Nov 2024
Viewed by 1668
Abstract
Training load monitoring is employed to quantify training demands, to determine individual physiological adaptions and to examine the dose–response relationship, ultimately reducing the likelihood of injury and making a meaningful impact on performance. The purpose of this study is to explore the relationship [...] Read more.
Training load monitoring is employed to quantify training demands, to determine individual physiological adaptions and to examine the dose–response relationship, ultimately reducing the likelihood of injury and making a meaningful impact on performance. The purpose of this study is to explore the relationship between training load and injury in competitive swimmers, using the session rate of perceived exertion (sRPE) method. Data were collected using a prospective, longitudinal study design across 104 weeks. Data were collected from 34 athletes centralised in two of Swim Ireland’s National Centres. Bayesian mixed effects logistic regression models were used to analyse the relationship between sRPE-TL and medical attention injuries. The average weekly swim volume was 33.5 ± 12.9 km. The weekly total training load (AU) averaged 3838 ± 1616.1. A total of 58 medical attention injury events were recorded. The probability of an association between training load and injury ranged from 70% to 98%; however, evidence for these relationships was deemed weak or highly uncertain. The findings suggest that using a single training load metric in isolation cannot decisively inform when an injury will occur. Instead, coaches should utilise monitoring tools to ensure that the athletes are exposed to an appropriate training load to optimise physiological adaptation. Future research should strive to investigate the relationship between additional risk factors (e.g., wellbeing, lifestyle factors or previous injury history), in combination with training load and injury, in competitive swimmers. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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<p>Mean weekly training load (AU) and weekly injury count (n) across the two-year observational period.</p>
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<p>Spaghetti plots of the conditional effects of the relationships between injury types and Acute Chronic Workload Ratio (ACWR).</p>
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10 pages, 848 KiB  
Article
The Role of Affects and Emotional Styles in the Relationship Between Parents and Preschool Children
by Carolina Facci, Andrea Baroncelli and Enrica Ciucci
Children 2024, 11(11), 1369; https://doi.org/10.3390/children11111369 - 12 Nov 2024
Viewed by 601
Abstract
Background/Objectives: Parent–child relationships represent a key factor for the quality of developmental trajectories and impact on children’s social and emotional competence. Therefore, research has advanced the role of parenting by showing the significance of differentiating between distinctive aspects of a parent’s behaviors. This [...] Read more.
Background/Objectives: Parent–child relationships represent a key factor for the quality of developmental trajectories and impact on children’s social and emotional competence. Therefore, research has advanced the role of parenting by showing the significance of differentiating between distinctive aspects of a parent’s behaviors. This study aims to investigate the role of the feelings experienced in parent–child relationships (e.g., warmth and negative feelings), considering the moderating role of the parental styles toward children’s emotions (e.g., coaching and dismissing). Methods: A total of 136 mothers (M = 38.09 years, SD = 4.51 anni, 48.5% high school degree) with a preschool child (age range 3–5 years) in Central Italy have been involved in a survey during the pandemic period. Results: Multiple regression analyses show that warmth and negative feelings are associated with positive parenting; however, the moderation effect of the dismissing style on both warmth and negative feelings emerged. Conclusions: Despite the characteristics of the data collection period, the results suggest the importance of considering the emotion-related dimensions between parents and their children as they seem to influence parenting behaviors. Full article
(This article belongs to the Special Issue Child and Adolescent Psychiatry: A Post-COVID Era?)
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<p>The moderating role of dismissing in the association between warmth and positive parenting.</p>
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<p>The moderating role of dismissing in the association between negativity and positive parenting.</p>
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21 pages, 7373 KiB  
Article
Characteristics, Relationships, and Differences in Muscle Activity and Impact Load Attenuation During Tennis Forehand Stroke with Different Grips
by Rui Dong, Xinyu Su, Shichen Li, Xindi Ni and Ye Liu
Life 2024, 14(11), 1433; https://doi.org/10.3390/life14111433 - 6 Nov 2024
Cited by 1 | Viewed by 866
Abstract
In forehand strokes with different grips in tennis, the forearm muscle activities, the distribution and attenuation of the impact loads, and the effects of the muscles on the impact load attenuation exhibited different characteristics. This study aimed to explore these characteristics by analyzing [...] Read more.
In forehand strokes with different grips in tennis, the forearm muscle activities, the distribution and attenuation of the impact loads, and the effects of the muscles on the impact load attenuation exhibited different characteristics. This study aimed to explore these characteristics by analyzing electromyography (EMG) and acceleration data, and comparing the differences between the Eastern and Western grips. Fourteen level II or above tennis players (ten males, aged 22.4 ± 3.6 years; four females, aged 19.8 ± 2.0 years) were recruited and instructed to perform forehand strokes using the Eastern and Western grips, respectively. The EMG of eight forearm muscles and the acceleration data at the ulnar and radial sides of the wrist and elbow were collected. The root mean square (RMS), the peaks of the impact load, the amplitude of impact load attenuation (AC), and the jerk value (Jerk) were calculated. The cross-correlation coefficients and time delays of EMG–EMG, EMG–AC, and EMG–jerk were obtained using the cross-correlation method. The results showed that in the Eastern grip group (group E), the RMS of the flexor carpi ulnaris (FCU) was significantly greater than that in the Western grip group (group W). In group E, the peaks of impact load, AC, and Jerk on the Y axis of the wrist ulnar side were all significantly higher than those in group W. The activity of the extensor digitorum commonis (EDC) had significantly different effects on the amplitude and rate of impact load attenuation at specific locations in different grips, especially at the elbow (p < 0.05). The conclusion indicated that the FCU exhibited higher levels of EMG activity in the Eastern grip. This grip responded to greater impact loads with more substantial and rapid attenuation on the wrist ulnar side. Furthermore, the EDC appeared to contribute more to the amplitude of impact load attenuation in the Western grip and to have a more significant influence on the rate of impact load attenuation in the Eastern grip, especially at the elbow. These results suggest that tennis players and coaches should pay more attention to improving the strength of the EDC and FCU, which can improve sports performance and comfort, as well as prevent sports injuries. Full article
(This article belongs to the Section Physiology and Pathology)
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<p>The RMS of the eight forearm muscles during forehand stroke with Eastern and Western grip. Data are presented as mean ± standard deviation. The * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05). (BR: brachioradialis; FCR: flexor carpi radialis; FDS: flexor digitorum superficialis; PT: pronator teres; FCU: flexor carpi ulnaris; EDC: extensor digitorum communis; ECR: extensor carpi radialis; ECU: extensor carpi ulnaris; applies to all figures).</p>
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<p>The PEAK–acc of the X, Y, and Z axes of three acceleration sensors during forehand stroke with Eastern and Western grip. The data are presented as a box plot with the median, interquartile range, maximum, and minimum values. The * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05). E–x, U–x, and R–x represent the X-axis acceleration data of three acceleration sensors placed on the external epicondyle of the humerus, the styloid process of the ulna, and the malleolus radialis. E–y, U–y, and R–y represent the acceleration data of the Y-axis of three acceleration sensors. E–z, U–z, and R–z represent the Z-axis acceleration data of three acceleration sensors. Same below.</p>
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<p>The PAC–acc of the X, Y, and Z axes of three acceleration sensors during forehand stroke with Eastern and Western grip. The data are presented as a box plot, and the * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The PEAK–jerk of the X, Y, and Z axes of three acceleration sensors during forehand stroke with Eastern grip and Western grip. The data are presented as a box plot, and the * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The cross-correlation coefficients and delays of EMG–AC. Each small square represents the correlation coefficient or delay based on its vertical and horizontal coordinates. Same below. (<b>A</b>) indicates the rEMG–AC in group E; (<b>B</b>) indicates the rEMG–AC in group W; (<b>C</b>) indicates the ΔtEMG–AC in group E; (<b>D</b>) indicates the ΔtEMG–AC in group W. The abscissa in the figure represents the position and axis of the accelerometer (refer to the annotation in <a href="#life-14-01433-f002" class="html-fig">Figure 2</a>); the ordinate represents the eight muscles of the forearm. The time delay values are calculated based on the “EMG–AC”; a negative value indicates that the EMG was earlier than AC<sub>acc</sub>, while a positive value indicates a lag.</p>
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<p>The rEMG–AC of forehand stroke with Eastern and Western grips. (<b>A</b>–<b>H</b>) represent the cross-correlation coefficients between the EMG of BR, FCR, FDS, PT, FCU, EDC, ECR, ECU and the nine sets of acceleration data, respectively. The data are presented as box plots, and the * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The cross-correlation coefficients and delays of EMG–jerk. (<b>A</b>) indicates the rEMG–jerk in group E; (<b>B</b>) indicates the rEMG–jerk in group W; (<b>C</b>) indicates the ΔtEMG–jerk in group E; (<b>D</b>) indicates the ΔtEMG–jerk in group W. The abscissa in the figure represents the position and axis of the accelerometer (refer to the annotation in <a href="#life-14-01433-f002" class="html-fig">Figure 2</a>); the ordinate represents the eight muscles of the forearm. The time delay values are calculated based on the “EMG–jerk”. A negative value indicates that the EMG was earlier than Jerk, while a positive value indicates a lag.</p>
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<p>The rEMG–jerk during forehand stroke with Eastern and Western grips. (<b>A</b>–<b>H</b>) represent the cross-correlation coefficients between the EMG of BR, FCR, FDS, PT, FCU, EDC, ECR, ECU and the nine sets of acceleration data, respectively. The data are presented as box plots, and the * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The ΔtEMG–jerk during forehand stroke with Eastern grip and Western grip. (<b>A</b>–<b>H</b>) represent the time delays between the EMG of BR, FCR, FDS, PT, FCU, EDC, ECR, ECU and the nine sets of acceleration data, respectively. The data are presented as box plots, and the * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05). The time delay values are calculated based on the “EMG–jerk”; a negative value indicates that EMG was earlier than Jerk, while a positive value indicates a lag.</p>
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<p>Coefficient of cross-correlation and delay of EMG–EMG. (<b>A</b>) indicates the rEMG–EMG in group E; (<b>B</b>) indicates the rEMG–EMG in group W; (<b>C</b>) indicates the Δt of EMG–EMG in group E; (<b>D</b>) indicates the Δt of EMG–EMG in group W. The time delay values are calculated based on the “abscissa–ordinate”; a negative value indicates that the EMG of abscissa was earlier than that of ordinate, while a positive value indicates a lag.</p>
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<p>The rEMG–EMG during forehand stroke with Eastern grip and Western grip. (<b>A</b>–<b>D</b>) represent the cross-correlation coefficients of the EMG of two different target muscles, respectively. The data are presented as box plots, and the * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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28 pages, 2779 KiB  
Review
Anaerobic Sport-Specific Tests for Taekwondo: A Narrative Review with Guidelines for the Assessment
by Gennaro Apollaro, Ibrahim Ouergui, Yarisel Quiñones Rodríguez, Rafael L. Kons, Daniele Detanico, Emerson Franchini, Piero Ruggeri, Coral Falcó and Emanuela Faelli
Sports 2024, 12(10), 278; https://doi.org/10.3390/sports12100278 - 14 Oct 2024
Cited by 2 | Viewed by 2121
Abstract
The ATP-PCr system represents the main source of energy during high-intensity attack actions in taekwondo matches. In contrast, the glycolytic system supports the maintenance of these actions when repeated techniques are performed. Given the close relationship between anaerobic energy systems and attack activity [...] Read more.
The ATP-PCr system represents the main source of energy during high-intensity attack actions in taekwondo matches. In contrast, the glycolytic system supports the maintenance of these actions when repeated techniques are performed. Given the close relationship between anaerobic energy systems and attack activity in combat, the literature relating to the use of sport-specific test protocols for anaerobic assessment has experienced a remarkable increase. This narrative review aims to illustrate the sport-specific anaerobic tests available in taekwondo by retracing and examining development and validation process for each test. Forty-one articles published between 2014 and 2023 were selected via the MEDLINE and Google Scholar bibliographic databases. These tests are the Taekwondo Anaerobic Test and Adapted Anaerobic Kick Test (i.e., continuous mode testing); the 10 s and multiple Frequency Speed of Kick Tests; the chest and head Taekwondo Anaerobic Intermittent Kick Tests; and the Taekwondo-Specific Aerobic–Anaerobic–Agility test (i.e., intermittent mode testing). Coaches and strength and conditioning professionals can use all the tests described in taekwondo gyms as they feature short and easy-to-implement protocols for monitoring and prescribing specific anaerobic training. The guidelines in this review evaluate each test from several perspectives: basic (e.g., validity, reliability, and sensitivity), methodological (e.g., continuous or intermittent mode testing) and application (e.g., time–motion structure and performance parameters). This comprehensive approach aims to assist stakeholders in selecting the most appropriate test. Full article
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<p><b>Blood lactate values [La] post-rounds in simulated and official match</b>. First, some studies have quantified the [La] after each round of the match. Specific analysis of these values reveals a gradual increase in the values of [La] post-round, from round to round, with the highest value at the end of the last round of the match, in both simulated and official matches. However, data should be interpreted with caution as this increase throughout the rounds does not necessarily reflect glycolytic contribution increase [<a href="#B25-sports-12-00278" class="html-bibr">25</a>]. Indeed, the studies [<a href="#B17-sports-12-00278" class="html-bibr">17</a>,<a href="#B18-sports-12-00278" class="html-bibr">18</a>,<a href="#B19-sports-12-00278" class="html-bibr">19</a>,<a href="#B24-sports-12-00278" class="html-bibr">24</a>] that also calculated delta (Δ) [La] (i.e., the lactate concentration after the round minus the lactate concentration at the beginning of the round) suggest a decrease in lactate accumulation and a consequent reduction in glycolytic participation throughout the rounds. Moreover, it is important to note that identifying [La]<sub>peak</sub> after each round is not practicable after rounds 1 and 2 due to the short duration of recovery (i.e., 1 min) between rounds. Secondly, placing the [La] values in ascending order, for each round, shows that the values identified in simulated matches, in which the contribution of the three energy systems was quantified in parallel, are slightly lower (and with a certain degree of overlap for the values after the third round) than those found in simulated and official matches, in which only the contribution of the glycolytic system was quantified or a backpack was used to protect the portable gas analysis system. Values: mean ± SD.</p>
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<p><b>Anaerobic continuous sport-specific tests. Taekwondo Anaerobic Test (TAT)</b> [<a href="#B38-sports-12-00278" class="html-bibr">38</a>,<a href="#B51-sports-12-00278" class="html-bibr">51</a>]. Athlete performs the bandal-chagi by alternating the legs, beginning with dominant leg, as many times as possible at maximal intensity over 30 s. Kicks must be carried out in height between the umbilical scar and xiphoid process of the athlete, marked by placing a taekwondo body protector on the punching bag. The kicking cycle is defined as the time interval between two consecutive kicks with the same leg. From this parameter, the number of kicking cycles (only completed cycles), mean kicking time and best kicking time are calculated. In addition, by measuring the magnitude of impact in each kick, the highest kicking impact and the mean kicking impact over the 30 s of the test are identified. The fatigue index (FI) is calculated using the mean kicking time and mean impact of the initial 20% cycles and the mean of the last 20% cycles [<a href="#B38-sports-12-00278" class="html-bibr">38</a>]. During the test, the amount of performed techniques are recorded, as well as the kicking impact force. Consequently, the following performance indicators are calculated: Peak power observed during the first 5 s of the test; relative peak power; mean anaerobic power during the 30 s of the test; relative mean anaerobic power; fatigue index; and anaerobic capacity [<a href="#B51-sports-12-00278" class="html-bibr">51</a>]. <b>Adapted Anaerobic Kick Test (AAKT)</b> [<a href="#B48-sports-12-00278" class="html-bibr">48</a>]. Athlete performs the bandal-chagi with the dominant leg as many times as possible at maximal intensity over 30 s. The test is performed using a target pad positioned at the height of the iliac crest of the athlete. The first kick is performed with the dominant leg in the back. Starting from the second kick, the preferred leg is positioned forward throughout the remaining time of the test. Only kicks performed with the front leg are considered for the analysis. The following parameters are calculated: higher kick frequency performed during 3 s; lower kick frequency performed during 3 s; average kick frequency performed during 30 s; fatigue index (percentage reduction of the maximum frequency kick to minimum frequency kick); and time to higher kick frequency performed during 3 s.</p>
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<p><b>Anaerobic intermittent sport-specific tests.</b> (<b>a</b>) <b>10 s Frequency Speed of Kick Test (FSKT<sub>10s</sub>)</b> [<a href="#B56-sports-12-00278" class="html-bibr">56</a>]. The FSKT<sub>10s</sub> lasts for 10 s. After the sound signal, athlete must execute the maximum number of bandal-chagi movements possible by alternating right and left legs. In order to accomplish the test, each athlete is placed in front of the stand bag equipped with a taekwondo body protector, positioned at the same height of the athlete trunk. The performance is determined by the total number of kicks applied during the test. (<b>b</b>) <b>Multiple Frequency Speed of Kick Test (FSKT<sub>mult</sub>)</b> [<a href="#B56-sports-12-00278" class="html-bibr">56</a>]. The FSKT<sub>mult</sub> consists of five 10 s sets with a 10 s passive recovery between sets. The execution criteria for the FSKT<sub>mult</sub> are the same as those defined for the FSKT<sub>10s</sub>. The performance is determined by the number of kicks in each set, total number of kicks and kick decrement index (KDI) during the test. The KDI indicates performance decreases during the test. To calculate the KDI, the following Equation is used, which takes into account the number of kicks applied during all sets of the FSKT<sub>mult</sub>: KDI (%) = [1 − (FSKT<sub>1</sub> + FSKT<sub>2</sub> + FSKT<sub>3</sub> + FSKT<sub>4</sub> + FSKT<sub>5</sub>)/best FSKT × number of sets] × 100. <b>Video Analysis</b>. Both tests are recorded, and the videos are analyzed posteriorly to manually count the kicks performed, through video analysis software. First, the count starts when the athlete moves the attack feet and finishes when he touches the bag. Valid kicks are those that hit the target during 10 s. If the athlete starts the kick before completing 10 s but reaches the target only after 10 s, the kick is not considered valid. Second, the valid kicks are those performed with appropriate technique and power.</p>
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<p><b>Anaerobic intermittent sport-specific tests. Taekwondo Anaerobic Intermittent Kick Test (TAIKT<sub>chest</sub>)</b> [<a href="#B27-sports-12-00278" class="html-bibr">27</a>]. The TAIKT<sub>chest</sub> consists of six 5 s sets with a 10 s active recovery (i.e., very light [tempo = one bounce/s] bouncing movements controlled by an evaluator) between sets. After the sound signal, athlete must execute the maximum number of bandal-chagi movements possible by alternating right and left legs. In order to accomplish the test, each athlete is placed in front of the stand bag equipped with a taekwondo electronic body protector, positioned at the same height of the athlete trunk, i.e., at a height (y) relative to the mat. During kick execution, the athlete should not exceed a mark on the mat, the optimum distance (x) to be determined before the test, to effectively execute kicking on the body protector. The distances (x) and (y) allow to determine the distance (d) using the Pythagorean Theorem, which is the projection distance of the foot on the body protector. Participants are asked to wear their official protectors during the test. The number of kicks is automatically displayed on the computer screen after each kicking set and the scoring threshold is set according to the criteria used in the competition for each weight category. TAIKT<sub>chest</sub> performance is expressed as absolute (W) and relative (W·kg<sup>−0.67</sup>) peak power (P<sub>peakTAIKT</sub>) and mean power (P<sub>meanTAIKT</sub>), and absolute (W) fatigue index (FI<sub>TAIKT</sub>). P<sub>peakTAIKT</sub> is the highest power output of the six sets of kicks; P<sub>meanTAIKT</sub> is sum of powers of six sets of kicks/6; FI<sub>TAIKT</sub> is P<sub>peakTAIKT</sub>-minimum power (P<sub>minTAIKT</sub>)/total test duration (30 s). The authors have made an Excel spreadsheet available in which performance can be calculated by entering the known values, i.e., body mass, x and y distances, and number of kicks in each series. <b>Taekwondo Anaerobic Intermittent Kick Test (TAIKT<sub>head</sub>)</b> [<a href="#B57-sports-12-00278" class="html-bibr">57</a>]. The execution criteria and performance for the TAIKT<sub>head</sub> are the same as those defined for the TAIKT<sub>chest</sub>, except that in the TAIKT<sub>head</sub>, the kicks are projected on a dummy’s head covered by an electronic head protector.</p>
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<p><b>Anaerobic intermittent sport-specific test. Taekwondo-Specific Aerobic–Anaerobic–Agility (TAAA) test</b> [<a href="#B39-sports-12-00278" class="html-bibr">39</a>]. The test involves six 20 s (a total of 2 min) intervals of shuttle sprints over a 4 m distance, and the execution of the bandal-chagi to the punching bags alternating the legs at the end of each distance, with 10 s rest intervals between the sets. For a detailed description of this test, refer to the previous review on sport-specific assessment of endurance in taekwondo [<a href="#B9-sports-12-00278" class="html-bibr">9</a>]. To estimate anaerobic fitness are calculated: maximum kicks (maximum number of kicks in a 20 s interval); minimum kicks (minimum number of kicks in a 20 s interval); average kicks (total number of kicks at the end of the test divided by six) and kick fatigue index (KFI) according to following Equation: KFI (%) = [Maximum Kicks − Minimum Kicks)/Total Kicks] × 100.</p>
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16 pages, 3440 KiB  
Article
Towards Automatic Object Detection and Activity Recognition in Indoor Climbing
by Hana Vrzáková, Jani Koskinen, Sami Andberg, Ahreum Lee and Mary Jean Amon
Sensors 2024, 24(19), 6479; https://doi.org/10.3390/s24196479 - 8 Oct 2024
Viewed by 1243
Abstract
Rock climbing has propelled from niche sport to mainstream free-time activity and Olympic sport. Moreover, climbing can be studied as an example of a high-stakes perception-action task. However, understanding what constitutes an expert climber is not simple or straightforward. As a dynamic and [...] Read more.
Rock climbing has propelled from niche sport to mainstream free-time activity and Olympic sport. Moreover, climbing can be studied as an example of a high-stakes perception-action task. However, understanding what constitutes an expert climber is not simple or straightforward. As a dynamic and high-risk activity, climbing requires a precise interplay between cognition, perception, and precise action execution. While prior research has predominantly focused on the movement aspect of climbing (i.e., skeletal posture and individual limb movements), recent studies have also examined the climber’s visual attention and its links to their performance. To associate the climber’s attention with their actions, however, has traditionally required frame-by-frame manual coding of the recorded eye-tracking videos. To overcome this challenge and automatically contextualize the analysis of eye movements in indoor climbing, we present deep learning-driven (YOLOv5) hold detection that facilitates automatic grasp recognition. To demonstrate the framework, we examined the expert climber’s eye movements and egocentric perspective acquired from eye-tracking glasses (SMI and Tobii Glasses 2). Using the framework, we observed that the expert climber’s grasping duration was positively correlated with total fixation duration (r = 0.807) and fixation count (r = 0.864); however, it was negatively correlated with the fixation rate (r = −0.402) and saccade rate (r = −0.344). The findings indicate the moments of cognitive processing and visual search that occurred during decision making and route prospecting. Our work contributes to research on eye–body performance and coordination in high-stakes contexts, and informs the sport science and expands the applications, e.g., in training optimization, injury prevention, and coaching. Full article
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<p>Framework for object detection and activity inference: data collection using eye-tracking glasses, frame extraction, and small-scale manual annotation, and hold and grasp detection (YOLOv5). Tobii 2 glasses (Stockholm, Sweden) image by Tobii AB.</p>
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<p>Example object classes: hold (<b>left</b>), grasp (<b>middle</b>), and foot grasp (<b>right</b>). The frames illustrate the characteristics of mobile eye tracking in the climbing context—low image quality, low illumination, narrow view, and distortion—that are typical for mobile eye trackers.</p>
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<p>The climber’s view during ascending and before final jump with detected holds (red), grasps (green), and climber’s fixations and saccades (blue). The bounding boxes depict the detected objects (holds; red box) and inferred action (grasp; green box) with the detection confidence.</p>
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<p>Fixation count during route preview, climbing, and final touch. Fixation count (blue) indicates the moments of increased focus (lower count) and visual exploration (higher count) along with grasps. Automatically detected grasps (grey) are aligned with manually coded grasps (purple) that were visible in eye-tracker’s field of view. The grasps in red were annotated from the previous frames as the climbers grasped the holds without looking at them. Taken together, eye movements and grasps show moments of ascend and immobility and corresponding focus and/or visual exploration.</p>
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<p>Comparison of automatic grasp detections (blue) and manually coded grasps (purple and red) of two high-skilled climbers. Purple bars denote the grasps that were captured in the video frame, while red bars denote the grasps occurring outside of the scene camera’s field of view. Although grasps were performed out of view, detections captured the grasping hands or feet in the following frames.</p>
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<p>Time series of climbing and eye-tracking metrics of one participant at the beginning (dark blue), middle (blue), and end (light blue) of the climbing. Metrics indicate experienced difficulty, for example, the main crux of the route was presented in the first third, which is apparent in the peak value of grasp duration, fixation count, and total fixation duration.</p>
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<p>Grasping duration (<b>left</b>) and total fixation duration (<b>right</b>) of four expert climbers at the start (1), middle (2), and end (3) of the climbing route. While all expert climbers solved the routes approximately at the same pace, their grasping and total fixation durations either decreased or increased over time, suggesting different climbing and visual strategies.</p>
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17 pages, 283 KiB  
Article
It Is Leadership, but (Maybe) Not as You Know It: Advocating for a Diversity Paradigm in Sports Leadership and Beyond
by Tania Cassidy and Gary Byrne
Behav. Sci. 2024, 14(10), 860; https://doi.org/10.3390/bs14100860 - 24 Sep 2024
Viewed by 1356
Abstract
The need to ‘rethink leadership’ is on the radar of many, from global finance and auditing organisations (e.g., Deloitte) and global sports organisations (e.g., the International Olympic Committee) to national and local sports organisations concerned about the decreasing numbers of participants or the [...] Read more.
The need to ‘rethink leadership’ is on the radar of many, from global finance and auditing organisations (e.g., Deloitte) and global sports organisations (e.g., the International Olympic Committee) to national and local sports organisations concerned about the decreasing numbers of participants or the lack of women coaches. Yet, is the dominant Western leadership orthodoxy fit for purpose in the 21st century? The purpose of this article is two-fold. First, to advocate for ways of ‘rethinking leadership’ that challenge the current dominant ethnocentric, gender-biased, leader-centric orthodoxy. Second, to introduce an expanded global and diverse leadership paradigm that is underpinned by clearly delineated dimensions of diversity and cultural competence, which recognises the importance of the organisational and cultural contexts. The literature discussed in this article draws from leadership studies generally and sports leadership and sports coaching more specifically. Key to this article is the discussion of the implications of adopting a diverse leadership paradigm for policy, practice, development, and research of leadership. This advocacy article does not end with a definitive conclusion but rather with an invitation to participate in a journey to realise the potential of diverse leadership. Full article
16 pages, 342 KiB  
Article
Assessing the Reliability of the Sexual Violence Questionnaire in Sport among Spanish-Speaking Athletes
by Andrea Sáenz-Olmedo, Aitor Iturricastillo, Jon Brain, Luis Maria Zulaika and Oidui Usabiaga
Int. J. Environ. Res. Public Health 2024, 21(9), 1214; https://doi.org/10.3390/ijerph21091214 - 16 Sep 2024
Viewed by 1006
Abstract
The prevalence of sexual harassment and abuse in school sport, specifically by coaches against their athletes, remains a concerning and pervasive issue. In an attempt to better understand and prevent specific coach-behaviours associated with such sexual misconduct, researchers have developed the Sexual Violence [...] Read more.
The prevalence of sexual harassment and abuse in school sport, specifically by coaches against their athletes, remains a concerning and pervasive issue. In an attempt to better understand and prevent specific coach-behaviours associated with such sexual misconduct, researchers have developed the Sexual Violence Questionnaire in Sport. While the reliability of this measurement tool has been tested in Anglo-Saxon cultural contexts, it is not known whether the questionnaire is applicable to other cultural contexts. This study aimed to analyse the internal consistency and reliability of the questionnaire on sexual harassment in sport, originally designed and developed in English. A sample of 146 (52 female, 94 male) undergraduate students from a university in the Basque Country participated in this cross-sectional study. The questionnaire was administered twice over a two-week period to assess test–retest reliability. The internal consistency of the Sexual Violence Questionnaire in Sport was high, with Cronbach’s alpha values of 0.891 for perceptions and 0.813 for experiences across all participants. Gender-specific analysis showed similar reliability, with females having slightly lower alpha values for perceptions. Although significant differences were observed between the test and the retest on eight perception items and one experience item, Cohen’s kappa analysis indicated agreement on all items; however, some of them were low (e.g., 0.13). In conclusion, the study highlights the questionnaire’s overall reliability and suggests its effectiveness as a tool for measuring sexual violence in sport within the Spanish context. Nonetheless, the findings of this study underscore the need for further research to enhance the instrument’s stability and to better understand gender differences in perceptions and experiences of sexual violence in sport contexts. Full article
13 pages, 661 KiB  
Article
Position-Specific Reference Data for an Ice Hockey-Specific Complex Test—An Update and Practical Recommendations
by Stephan Schulze, Kevin G. Laudner, Karl-Stefan Delank, Thomas Bartels, Robert Percy Marshall and René Schwesig
Appl. Sci. 2024, 14(17), 7648; https://doi.org/10.3390/app14177648 - 29 Aug 2024
Viewed by 654
Abstract
This real-life data collection aimed to expand an existing reference database regarding an extensively evaluated ice hockey-specific complex test (IHCT). One hundred and thirty-eight third-league professional ice hockey field players (mean ± SD; age: 26.4 ± 5.24 years; forwards: n = 94, defenders: [...] Read more.
This real-life data collection aimed to expand an existing reference database regarding an extensively evaluated ice hockey-specific complex test (IHCT). One hundred and thirty-eight third-league professional ice hockey field players (mean ± SD; age: 26.4 ± 5.24 years; forwards: n = 94, defenders: n = 44) were investigated. IHCT data were collected over eight seasons from three third-league teams. The IHCT included parameters for the load (e.g., 10 m and 30 m sprint times, transition and weave agility times with and without a puck, slap and wrist shots on goal) and stress (e.g., lactate, heart rate). The only relevant (p < 0.002, ηp2 ≥ 0.10) difference between forwards and defenders for performance was found for 30 m backward sprint without a puck (p < 0.001, ηp2 = 0.10, d = 0.74). As expected, in this regard, defenders performed better than forwards. Significant differences were also found in 10 m backward sprint without a puck (p = 0.005), weave agility with a puck (p = 0.014), heart rate recovery minute 10 (p = 0.057), and goals after the test (p = 0.041). This study provides expanded position-specific third-league reference data for the IHCT. On this basis, coaches are able to evaluate players’ performance (forwards vs. defenders) and the effect of the training periods. Further research is necessary to extend this database to first- and second-league players in order to enhance the scope of the IHCT. Full article
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<p>Reevaluation of the IHCT regarding reference data based on a second median calculation [<a href="#B16-applsci-14-07648" class="html-bibr">16</a>].</p>
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<p>Example of an analysis matrix to judge players and teams. max = maximal, diff = difference, rec = recovery, heart rate = recovery heart rate (relative), rm 0 to rm 10 [%], lactate = lactate degradation rate per minute, rm 6 to rm 10 [mmol*L<sup>−1</sup>/min], red = P75 = percentile 75 = underperformance, green = P25 = percentile 25 = excellent performance, yellow = interquartile range = normal performance.</p>
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16 pages, 1466 KiB  
Article
Assessing the Impact of On-Farm Biosecurity Coaching on Farmer Perception and Farm Biosecurity Status in Belgian Poultry Production
by Arthi Amalraj, Hilde Van Meirhaeghe, Ilias Chantziaras and Jeroen Dewulf
Animals 2024, 14(17), 2498; https://doi.org/10.3390/ani14172498 - 28 Aug 2024
Viewed by 1082
Abstract
Veterinary coaching was tested to assess its efficacy in promoting adherence to biosecurity procedures. Poultry farmers (n = 13) in Belgium were profiled using ADKAR®, coached and audited prior to and 6 months after coaching. The ADKAR® (Awareness, Desire, [...] Read more.
Veterinary coaching was tested to assess its efficacy in promoting adherence to biosecurity procedures. Poultry farmers (n = 13) in Belgium were profiled using ADKAR®, coached and audited prior to and 6 months after coaching. The ADKAR® (Awareness, Desire, Knowledge, Ability, and Reinforcement) profiling technique identified 5/13 participating farmers with relatively low scores (≤3) for one or more elements that block change (biosecurity compliance in this case). Education was the only demographic variable that influenced knowledge scores. Through the Biocheck.UgentTM methodology, farm biosecurity was assessed and benchmarked to allow for tailored guidance. The farmer, farm veterinarian, and coach defined a farm-specific action plan that covered infrastructure, site access, staff/visitors, purchase policies, transport and depopulation, feed and water supplies, flock management, cleaning and disinfection between flocks, and measures between houses. From a total of 49 proposed actions, 36 were adopted. Purchasing policy had the highest (100%) and cleaning and disinfection had the lowest compliance (38%). Time, cost, and feasibility (e.g., inadequate farm layout) were the main reasons cited for not implementing action points. Overall, biosecurity improved significantly (p = 0.002) from 67.1 ± 5.7% to 70.3 ± 5.7% (mean ± Std. dev). The study, hence, presents convincing proof of how coaching can lead to new solutions not previously considered. Full article
(This article belongs to the Section Poultry)
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<p>On-farm biosecurity coaching in Belgian poultry farms: a longitudinal study.</p>
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<p>Overview of steps in the validation of the selected supporting measure “on-farm coaching”.</p>
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<p>Map of Belgium with the geographical distribution of the study farms.</p>
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<p>Individual ADKAR<sup>®</sup> profiles of poultry growers (<span class="html-italic">n</span> = 13) for the elements Awareness, Desire, Knowledge, and Ability. A score of 1 denoted the lowest possible score, while a score of 5 denoted the greatest possible score. According to [<a href="#B31-animals-14-02498" class="html-bibr">31</a>], if an element received a score of 1, 2, or 3, this element is likely to block the change or farmer’s intention towards biosecurity compliance. Poultry production types: EB—enclosed broiler, EL—enclosed layer, BR—breeder, TU—turkey, and LFR—layer free-range.</p>
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