99 The importance of reflection and evaluation for progressing toward the elite level 5 to be addressed beforehand. First, there is considerable inconsistency in the measurement of SRL subprocesses using subscales in self-reported questionnaires. For example, we used items describing the self-monitoring processes that were applied by Bartulovic et al. (2017) to measure reflection processes during training. Moreover, we used a 4-point and 5-point Likert scale to measure SRL subprocesses, whereas Bartulovic et al. (2017) applied a 7-point Likert scale. Such refined scale is recommended for future studies, as it could increase the power of statistical tests and, thus, the sensitivity to detect significant differences, also with small effect sizes (Wasserstein & Lazar, 2016). The inconsistency in the measurement of SRL subprocesses makes it difficult to compare findings between studies. However, this issue is not new in the literature on elite sports (see Swann et al., 2015) and psychology (see Dohme et al., 2017) and a similar approach (e.g., a systematic review) could help to create more consistency and common ground in the measurement of SRL subprocesses. Second, there is a further need to develop reliable and valid methods for mapping the quantity and quality of DP (Baker et al., 2020). To establish causal relationships between SRL, DP and performance development, variables such as weekly training hours should be further specified in terms of DP. Moreover, given that SRL is considered as a factor that contributes to the quality of DP, it would be interesting not only to examine the quantity of training-centered SRL subprocesses (as in the present study) but also their quality. For example, reflection and evaluation processes could be analyzed in relation to goalsetting and goal-evaluation standards. Finally, the present study was the first to introduce both performance level and performance progression measures in SRL. However, we were unable to include longitudinal data on SRL because of COVID-19 restrictions. Rather than cross-sectional research, longitudinal studies extend beyond a single moment in time and measure within-person change. This can enhance our understanding of how phenomena unfold over time and is a prerequisite to draw causal inferences (Stenling et al., 2017). Given the significant developmental changes that occur in maturing swimmers, the inclusion of longitudinal data would have been highly relevant for advancing the understanding of how age and developmental status could impact on the engagement and value of SRL in sport. Therefore, when studying the development of sport expertise, we call for the inclusion of longitudinal data on all key parameters (SRL, DP, and performance measures) in future studies. Such longitudinal studies could further examine whether SRL is an underlying individual characteristic with predictive value for future elite swimming performances. Practical Implications Given time constraints that affect the trajectory for reaching elite status, it is essential to get the most out of each training, especially in a competitive, globalized sport like competitive swimming. Therefore, effective and efficient learning (and training) is fundamental for swimmers who aspire to make it to the top. Consequently, it could be valuable to monitor
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