Reliability and Validity of the Adapted Chinese Student-Athlete Well-Being Scale in College Student-Athletes
Bibliographic record
Abstract
The well-being of college student-athletes plays a vital role in their overall academic and athletic success, influencing not only their performance in sports but also their mental health, academic engagement, and future career development (Ryan & Deci, 2001; Chang et al., 2020). Given the unique challenges that student-athletes face, such as balancing rigorous training schedules, academic responsibilities, and social pressures, it is essential to have reliable and culturally relevant tools to assess their well-being. The Student-Athlete Well-Being Scale (SAWS) has been widely used in various contexts, but until now, a validated Chinese version did not exist, limiting its application among Chinese-speaking populations. Recognizing this gap, the primary objective of this study was to adapt and validate the Chinese version of the SAWS for use among college student-athletes in China. By doing so, this study aimed to create a culturally appropriate tool that could capture the nuanced experiences and challenges faced by Chinese student-athletes. Three stages of analysis were conducted to ensure the robustness of this adapted scale. In the first stage, an exploratory factor analysis (EFA) was performed with a sample of 365 college student-athletes, which provided insights into the underlying factor structure of the Chinese SAWS. This process was crucial to ensure that the translated version maintained the conceptual integrity of the original scale while accounting for cultural differences. For example, certain terms or phrases that may be well understood in a Western context could carry different connotations in a Chinese cultural setting, and the EFA helped identify and adjust these nuances. The second stage involved a confirmatory factor analysis (CFA) with another sample of 502 student-athletes, along with an internal consistency evaluation and item analysis. This stage was vital for confirming the factor structure identified in the EFA and ensuring that the scale reliably measured the well-being constructs across a larger and more diverse sample. The high internal consistency of the scale (α = 0.928) indicated that the Chinese SAWS was a robust measure, with each item contributing meaningfully to the overall assessment of student-athlete well-being. In the third stage, a test-retest reliability assessment was conducted with 43 student-athletes over a two-week interval. The results demonstrated that the Chinese SAWS had excellent stability over time, reinforcing its reliability as a tool for monitoring changes in well-being among student-athletes. The findings of this study have significant implications for behavioral science, sports psychology, and health promotion. By providing a validated Chinese version of the SAWS, this study offers a valuable tool for athletic departments, coaches, mental health practitioners, and researchers. It can be used to monitor student-athletes' well-being, identify areas of support needed, and develop targeted interventions to promote mental health and overall well-being. This, in turn, can enhance not only their athletic performance but also their academic success and long-term personal development (Culbertson et al., 2010; Fogaca, 2021).In conclusion, this study's findings contribute to the field of sports psychology by providing a reliable and valid tool for assessing well-being among Chinese college student-athletes. The validated Chinese SAWS serves as a foundation for future research and interventions aimed at enhancing student-athletes' well-being in China, ultimately promoting healthier, more balanced, and successful lives both within and beyond their athletic pursuits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".