MyMedR

Displaying all 6 publications

Abstract:

Sort:

Fulltext A longitudinal analysis of injury characteristics among elite and amateur tennis players at different tournaments from electronic newspaper reports

Musa RM, Hassan I, Abdullah MR, Latiff Azmi MN, Abdul Majeed APP, Abu Osman NA

Front Public Health, 2022;10:835119.
PMID: 36033746 DOI: 10.3389/fpubh.2022.835119

The non-complexity of tennis, coupled with its health benefits, renders it appealing and encourages varying competitions at different levels of age, gender, and expertise. However, the rapid increase in the participation rates witnesses a surge in injury occurrences, prompting the need for in-depth analysis to facilitate immediate intervention. We employed a media content analysis technique in which tennis-associated articles published in the last 5 years were examined. A total of 207 news reports were gathered and screened for analysis. Subsequently, 71 articles were excluded from the study due to content duplications or summary updates of existing news articles, while 23 news articles were also excluded from the study due to inappropriateness. Finally, 113 news reports directly related to injury in tennis were coded and analyzed. We examined various types of injuries reported from the screened articles with respect to their status (fresh, recurrent, and recovery) across expertise levels i.e., elite, or amateur. Similarly, the incidence of injury occurrences based on the types of tournaments the players engage in was also investigated. A chi-square analysis was employed to achieve the objectives of the study. Occurrences of tennis-associated injuries are disseminated across expertise levels [ χ ( 18 ) 2 = 16.542; p = 0.555], with knee, hip, elbow, and shoulder injuries being highly prevalent in both elite and amateur players. Nevertheless, it was noted that elite players suffered a staggering 72.60% of injury-related problems, while amateur players sustained 27.40% of injuries. Moreover, the status of injury spreads based on types of tournaments [ χ ( 4 ) 2 = 3.374; p = 0.497], with higher occurrences of fresh and recurrent injuries, while low recovery rates were observed. The findings further demonstrated that injuries are sustained regardless of tournament types [ χ ( 36 ) 2 = 39.393; p = 0.321]. However, most of the injuries occurred at international tournaments (85%). Whereas, only 5.30% of the injuries occurred at national/regional tournaments while 9.70% were unidentified. It could be deduced from the findings of this investigation that elite players are more prone to injuries compared with amateur players. Furthermore, the most common tennis-related injuries affect the lower, trunk, and upper regions of the body, respectively. A large number of the reported tennis injuries are fresh and recurrent, with a few recoveries. The international tennis tournaments are highly attributed to injury occurrences as opposed to the national/regional tournaments. The application of the media-based data mining technique is non-trivial in projecting injury-related problems that could be used to facilitate the development of an injury index peculiar to the tennis sport for prompt intervention.
Fulltext Disciplinary measures defining referee activity in top-European football leagues: A cross-sectional investigation

Nazarudin MN, Abdul Majeed APP, Husin Musawi Maliki AB, Abdullah MR, Kuan G, Muazu Musa R

Heliyon, 2024 Feb 15;10(3):e25402.
PMID: 38352766 DOI: 10.1016/j.heliyon.2024.e25402

The success and enjoyment of a football match depend heavily on referees and their ability to ensure fair play and uphold the rules of the game. However, there is limited research investigating the disciplinary measures and booking activities of referees in top European football leagues. In the current investigation, we explored the disciplinary measures and booking activities of top-European football league referees. The dataset of the referee activities concerning 15 indicators containing 602 matches from five consecutive seasons across the five top European leagues, namely, the English Premier League, Spanish Laliga, Italian Serie A, French Ligue1, and German Bundesliga were utilized for this study. K-means cluster analysis was used to define the activity levels of the referees. The Mann-Whitney U test was employed to determine the differences in the levels of the referees' activity with respect to the disciplinary measures, while binary regression analysis was applied to examine the association between the disciplinary measures and the activity levels of the referees. Two groups of activities were defined by k-means, that is, high and low activity. The Mann-Whitney U test revealed statistically significant differences in all 15 indicators examined between high and low activity. However, the regression model demonstrated that only fouls, yellow cards, and air challenges could significantly describe referees' activity levels. These indicators appear to be predictors of high referee activity in elite European Football. Specific training on dealing with increased aggression and foul behaviour coupled with improved game organisational management could be further incorporated into referees' training programmes amongst other measures.
Fulltext Psychometric properties and gender invariance of the 8-item emotion regulation questionnaire (ERQ-8) among Chinese university students

Zhao M, Kuan G, Zhou K, Musa RM, Majeed APPA, Kueh YC

PLoS One, 2024;19(1):e0296035.
PMID: 38166088 DOI: 10.1371/journal.pone.0296035

BACKGROUND: To assess emotion regulation strategies in a clear and direct manner, Emotion Regulation Questionnaire (ERQ) was developed based on the process model of emotion regulation. ERQ primarily assesses an individual's propensity for reappraisal (a cognitive change in the individual's psychological state in specific situations) and expressive suppression (a regulatory response where an individual alters their emotional response after the onset of an emotional reaction). Recent studies have suggested that the abbreviated 8-item version of the ERQ exhibits comparable model fit to the original version. The present study aimed to explore the psychometric properties and assess cross-gender invariance of the ERQ-8 in Chinese university students.
METHODS: University students from Jiangsu Province participated in this study. Participants completed self-report surveys assessing emotion regulation strategies. It was conducted from May 2022 to July 2022. The study employed confirmatory factor analysis (CFA) to assess the two-factor model of ERQ-8 and measurement invariance across male and female samples.
RESULTS: The mean age of 1534 participants was 19.83 years (SD = 1.54), and the majority were female (70.4%). The initial ERQ-10 model with ten items demonstrated good fit for all indicators, CFI (Comparative Fit index) = 0.967, TLI (Tucker-Lewis Index) = 0.957, RMSEA (Root Mean Square Error of Approximation) = 0.043, SRMR (Standardised Root Mean Square Residual) = 0.029. However, to assess the fit of the previously proposed ERQ-8 model, two items (Q1 and Q3) were excluded. The fit of the ERQ-8 model was further improved (CFI = 0.989, TLI = 0.984, RMSEA = 0.029, SRMR = 0.021). All item loadings exceeded or were equal to 0.573. Internal consistency analysis based on the ERQ-8 model revealed Cronbach's alpha values of 0.840 for reappraisal and 0.745 for suppression, and corresponding composite reliability (CR) values of 0.846 and 0.747, respectively. Test-retest reliability, assessed using the intraclass correlation coefficient (ICC) (95% CI) within a one-week interval, ranged from 0.537 to 0.679. The correlation coefficient between the two factors was 0.084, significantly below 0.85, which suggested a low correlation between the two factors. The results of the invariance analysis across gender demonstrated that the values of ΔCFI and ΔTLI were both below 0.01. It was supported the gender invariance of the ERQ-8 among university students.
CONCLUSION: The eight-item ERQ demonstrated validity and reliability in evaluating emotion regulation strategies, and measurement invariance was observed across gender among university students. The ERQ-8 may prove to be a practical and cost-effective tool, particularly in time-constrained situations.
Fulltext Physical fitness and motor ability parameters as predictors for skateboarding performance: A logistic regression modelling analysis

Ab Rasid AM, Muazu Musa R, Abdul Majeed APP, Musawi Maliki ABH, Abdullah MR, Mohd Razmaan MA, et al.

PLoS One, 2024;19(2):e0296467.
PMID: 38329954 DOI: 10.1371/journal.pone.0296467

The identification and prediction of athletic talent are pivotal in the development of successful sporting careers. Traditional subjective assessment methods have proven unreliable due to their inherent subjectivity, prompting the rise of data-driven techniques favoured for their objectivity. This evolution in statistical analysis facilitates the extraction of pertinent athlete information, enabling the recognition of their potential for excellence in their respective sporting careers. In the current study, we applied a logistic regression-based machine learning pipeline (LR) to identify potential skateboarding athletes from a combination of fitness and motor skills performance variables. Forty-five skateboarders recruited from a variety of skateboarding parks were evaluated on various skateboarding tricks while their fitness and motor skills abilities that consist of stork stance test, dynamic balance, sit ups, plank test, standing broad jump, as well as vertical jump, were evaluated. The performances of the skateboarders were clustered and the LR model was developed to classify the classes of the skateboarders. The cluster analysis identified two groups of skateboarders: high and low potential skateboarders. The LR model achieved 90% of mean accuracy specifying excellent prediction of the skateboarder classes. Further sensitivity analysis revealed that static and dynamic balance, lower body strength, and endurance were the most important factors that contributed to the model's performance. These factors are therefore essential for successful performance in skateboarding. The application of machine learning in talent prediction can greatly assist coaches and other relevant stakeholders in making informed decisions regarding athlete performance.
Fulltext The classification of skateboarding tricks via transfer learning pipelines

Abdullah MA, Ibrahim MAR, Shapiee MNA, Zakaria MA, Mohd Razman MA, Muazu Musa R, et al.

PeerJ Comput Sci, 2021;7:e680.
PMID: 34497873 DOI: 10.7717/peerj-cs.680

This study aims at classifying flat ground tricks, namely Ollie, Kickflip, Shove-it, Nollie and Frontside 180, through the identification of significant input image transformation on different transfer learning models with optimized Support Vector Machine (SVM) classifier. A total of six amateur skateboarders (20 ± 7 years of age with at least 5.0 years of experience) executed five tricks for each type of trick repeatedly on a customized ORY skateboard (IMU sensor fused) on a cemented ground. From the IMU data, a total of six raw signals extracted. A total of two input image type, namely raw data (RAW) and Continous Wavelet Transform (CWT), as well as six transfer learning models from three different families along with grid-searched optimized SVM, were investigated towards its efficacy in classifying the skateboarding tricks. It was shown from the study that RAW and CWT input images on MobileNet, MobileNetV2 and ResNet101 transfer learning models demonstrated the best test accuracy at 100% on the test dataset. Nonetheless, by evaluating the computational time amongst the best models, it was established that the CWT-MobileNet-Optimized SVM pipeline was found to be the best. It could be concluded that the proposed method is able to facilitate the judges as well as coaches in identifying skateboarding tricks execution.
Fulltext Genome-wide association study of genetic markers of coat color patterns in Sumatran native cattle

Hartati H, Putra WPB, Handiwirawan E, Ramon E, Firison J, Zubir Z, et al.

Vet World, 2024 Nov;17(11):2537-2543.
PMID: 39829673 DOI: 10.14202/vetworld.2024.2537-2543

BACKGROUND AND AIM: Coat color is a phenotypic trait that is affected by many functional genes. In addition, coat color is an important characteristic of breeds in livestock. This study aimed to determine functional genes for coat color patterns in Sumatran native cattle in Indonesia using a genome-wide association study method.
MATERIALS AND METHODS: A bovine single nucleotide polymorphism (SNP) 50K BeadChip was used for the investigation. A total of 46. Sumatran native cattle of three colors as follows: Brown (36 animals), white (9 animals), and black (1 animal), were used as experimental animals.
RESULTS: Results showed that the SNP markers ARS-BFGL-NGS-75486 (p = 2.46 × 10-7) and BTB-01992588 (p = 1.06 × 10-5) were selected as two genetic markers for coat color variation in animals under study, which were located at the cytoplasmic FMR1-interacting protein 2 (CYFIP2) gene at BTA7 and small G protein signaling modulator 1(SGSM1) genes at BTA17, respectively. The polymorphic informative content values of both SNP markers were 0.33 (ARS-BFGL-NGS-75486) and 0.13 (BTB-01992588). In this study, a genetic marker for coat color patterns in Sumatran native cattle was obtained based on the haplotypes of both SNP markers.
CONCLUSION: It can be concluded that CYFIP2 and SGSM1 are two coloration genes that affect the phenotype characteristics of Sumatran native cattle.