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  1. Norjali Wazir MRW, Van Hiel M, Mostaert M, Deconinck FJA, Pion J, Lenoir M
    PLoS One, 2019;14(5):e0217358.
    PMID: 31150424 DOI: 10.1371/journal.pone.0217358
    Along with the increasing popularity of taekwondo, there is a need of evidence-based talent identification (TID) and development programs based upon profiles of future elite athletes. This study first aims to investigate the differences between elite and non-elite taekwondo athletes in anthropometry, physical performance and motor coordination. The second aim is to demonstrate the applicability of z-scores in TID research. A total of 98 Taekwondo athletes between 12 and 17 years old were tested using a generic test battery consisting of four anthropometrical (Height, Weight, Fat Percentage, BMI), six physical performance (Sit & Reach, Sprint 5m, Sprint 30m, Counter Movement Jump, Squat Jump, Endurance Shuttle Run) and three motor coordination tests (Moving Sideways, Jumping Sideways, Walking Backwards). Based on the individual success at international competition level, 18 were categorised as elite athletes and 80 were considered as non-elite. T-tests (step 1) on raw test scores and MANOVAs on z-scores (step 2) were conducted to examine differences between the elite and non-elite taekwondo athletes for anthropometry, physical performance and motor coordination tests. Finally, z-scores were reconverted to raw scores to demonstrate practical significance for coaches. Overall, elite taekwondo athletes score better compared to the non-elite group. The MANOVA analysis better scores for elites on fat percentage (-0.55 versus 0.12;p = 0.006), BMI (-0.37 versus 0,08;p = 0.067) sprint speed 30m (-0.48 versus 0.11;p = 0.029), counter movement jump (0.79 versus -0.18;p = 0.000), squat jump (0.42 versus -0.11;p = 0.041), moving sideways (0.79 versus -0.18;p = 0.000) and walking backwards (0.54 versus -0.12;p = 0.006). This study confirms our knowledge on physical profiles of elite taekwondo athletes and expands our knowledge to the domain of motor coordination. This study showed how the z-score method can be used to distinguish between elite and non-elite athletes, the former being low in number by definition.
  2. Gao Z, Chee CS, Norjali Wazir MRW, Wang J, Zheng X, Wang T
    Front Psychol, 2023;14:1291711.
    PMID: 38259527 DOI: 10.3389/fpsyg.2023.1291711
    OBJECTIVES: Parents are one of the main social agents that shape young athletes' experiences and participation in sports, but they are also the least explored group in the literature. Therefore, the purpose of this study was to conduct a systematic review of research on the role of parents in the motivation of young athletes.

    METHOD: The systematic literature review consisted of four electronic databases from which 29 articles published in English and in full-text form in peer-reviewed journals between 1999 and 2023 were retrieved.

    RESULTS: A total of 29 studies met the eligibility criteria. These studies collectively surveyed 9,185 young athlete participants and 2,191 parent participants. The sample comprised 26 quantitative studies and 3 qualitative studies. The findings underscore that parents play both unique and synergistic multidimensional roles in motivating young athletes. Parents' positive goals and values, autonomy-supportive parenting styles, moderate parental involvement, positive parent-child relationships, and a parent-initiated task climate are identified as optimal parenting strategies.

    CONCLUSION: While parents undeniably play a crucial role in motivating young athletes, the manner and extent of their involvement are key.

  3. Sun H, Soh KG, Roslan S, Norjali Wazir MRW, Liu F, Zhao Z
    Brain Sci, 2022 Jul 08;12(7).
    PMID: 35884703 DOI: 10.3390/brainsci12070896
    BACKGROUND: Many investigations have been performed on the effects of mental exertion that consumes self-regulatory resources and then affects physical and/or cognitive performance later on. However, the effect of manipulating self-regulation and interventions to attenuate this negative effect remains unclear. Moreover, there is continuous controversy regarding the resource model of self-regulation.

    OBJECTIVE: We conducted a systematic review to assess the literature on manipulating self-regulation based on four ingredients (standard, monitoring, strength, and motivation) in order to counter mental exertion and improve physical and/or cognitive performance. The results provide more insight into the resource model.

    METHOD: A thorough search was conducted to extract the relevant literature from several databases, as well as Google Scholar, and the sources from the references were included as grey literature. A self-regulation intervention compared to a control condition, a physical and/or cognitive task, and a randomised controlled trial were selected.

    RESULT: A total of 39 publications were included. Regarding the four components of self-regulation, the interventions could mainly be divided into the following: (i) standard: implementation intervention; (ii) monitoring: biofeedback and time monitoring; (iii) strength: repeated exercise, mindfulness, nature exposure, and recovery strategies; (iv) motivation: autonomy-supportive and monetary incentives. The majority of the interventions led to significant improvement in subsequent self-regulatory performance. In addition, the resource model of self-regulation and attention-restoration theory were the most frequently used theories and supported relevant interventions.

    CONCLUSION: In line with the resource model, manipulating the four components of self-regulation can effectively attenuate the negative influence of mental exertion. The conservation proposed in the strength model of self-regulation was supported in the current findings to explain the role of motivation in the self-regulation process. Future studies can focus on attention as the centre of the metaphorical resource in the model.

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