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    How accurately do large Language models interpret sport safeguarding principles: an evaluation using the International Olympic Committee framework
    (BMC, 2026) Gokmen, Mehmet Yigit; Belibagli, Mehmet Cenk; Karincaoglu, Ergin; Nazlican, Mahmut Cagatay; Turkmen, Eren; Yonal, Mehmet; Uluoz, Eren
    Background Safeguarding in sport, defined as the prevention of abuse, harassment, and exploitation, has become a core ethical responsibility for sport organizations. With the growing influence of artificial intelligence, large language models are increasingly being used to interpret, summarize, and operationalize policy documents. However, their reasoning fidelity in value-laden contexts such as athlete protection remains uncertain. Methods This document-based comparative study evaluated two advanced large language models, ChatGPT (OpenAI) and NotebookLM (Google), against twenty-five decision points derived from the 2024 International Olympic Committee Consensus on Interpersonal Violence and Safeguarding in Sport. Responses were independently scored by two evaluators across four dimensions: accuracy, ethical reasoning, applicability, and responsibility awareness. Quantitative and qualitative analyses assessed concordance with IOC recommendations, inter-rater reliability, and reasoning patterns. Structured PICO-style prompts were used to ensure standardized and comparable model interrogation across all decision points. Results ChatGPT achieved a higher mean composite score (3.84 +/- 0.41) than NotebookLM (3.32 +/- 0.77) (Wilcoxon Z = 3.41, p = 0.001, r = 0.68; n = 25 paired decision points), with full concordance in 21/25 (84.0%) versus 14/25 (56.0%) decision points. Inter-rater agreement was excellent (Cohen's kappa = 0.89). ChatGPT demonstrated stronger procedural reasoning and clearer alignment with IOC-defined responsibilities, while NotebookLM emphasized empathy and cultural nuance. Both models underperformed in survivor-centred reasoning and outcome evaluation metrics. Conclusion LLMs can partially reproduce the ethical and procedural logic embedded in sport safeguarding frameworks, but their reasoning remains incomplete without human oversight. Their integration into governance, education, and policy translation should follow clear ethical guardrails to prevent misinterpretation or amplification of harm. These systems may support policy drafting, education, and communication, yet they should function strictly as augmentative tools rather than independent decision-makers. To our knowledge, this is the first study to systematically benchmark LLM reasoning against an official international safeguarding framework in sport. Future research should evaluate interactive and multilingual applications to enhance contextual accuracy and equitable safeguarding outcomes.
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    Investigation of endocrine and cerebral response and nutrition and physical performance parameters according to bigorexia nervosa levels: a cross-sectional study in sports sciences faculty students
    (Nature Portfolio, 2025) Erkilic, Ali Ozan; Bayraktar, Bulent; Erkilic, Tugce Orkun; Turkmen, Mutlu; Kul, Murat; Yonal, Mehmet
    The aim of this study is to investigate the effects of Bigorexia nervosa (BGN) levels on endocrine (Asprosin, GLP-1) and cerebral (BDNF) responses and nutritional and physical (6MWT, Six-Minute Walk Test)), speed, metabolic equivalent unit (MET)) performance parameters in students of the faculty of sports sciences. This study investigated muscle dysmorphic disorder (MDD), physical activity levels, and specific hormonal markers in 120 university students (63 females, 57 males) aged 18-25 years, all studying sport sciences and reporting no existing health problems. Participants completed a demographic questionnaire, food frequency questionnaire and the Muscle Dysmorphic Disorder (Bigorexia) Inventory through face-to-face interviews. Physical activity was assessed using the 6-Minute Walk Test (6MWT) to measure walking distance, and Metabolic Equivalent (MET) was calculated based on the American College of Sports Medicine (ACSM) formula. Body Mass Index (BMI) was determined from anthropometric measurements of height and body weight. Saliva samples were collected to analyze Asprosin, BDNF, and GLP-1 hormone levels using the ELISA technique.Data were analyzed using number, percentage, mean, chi-square, t-test, Pearson correlation, and ANOVA tests. In all analyses, significance was accepted as p < 0.05. According to the demographic findings of the study, the majority of participants (64.2%) were third-year students, and 52.5% were female. The mean age of the participants was 22.01 years, the mean height was 168.59 cm, and the mean weight was 62.61 kg. 73.3% of the individuals were classified as normal weight, 12.5% as pre-obese, 11.7% as underweight, and 2.5% as obese. Men had significantly higher bigorexia and its subscale scores than women (p < 0.05), and bigorexia was positively correlated with height and negatively correlated with BMI (p < 0.01). Mean salivary BDNF levels were higher in participants consuming 1-2 meals per day (p = 0.035), and mean salivary asprosin levels were significantly higher in the obese group compared to the healthy group (p = 0.008). Additionally, a strong positive correlation was found between asprosin and GLP1 levels (r = 0.585; p < 0.01). Bigorexia status was significantly associated with meat, meat products, and fat consumption (p < 0.05), while no association was found with physical performance parameters such as 6MWT, speed, and MET (p > 0.05). The average MET value was found to be 4.53, indicating that participants generally engaged in moderate-intensity physical activity. In conclusion, examining endocrine (asprosin, GLP-1) and cerebral (BDNF) hormone responses, as well as nutritional and physical performance parameters, according to BGN levels reveals the impact of BGN on physiological and nutritional behaviors. Given the impact of BGN trends on students' health, examining hormone profiles and their relationships with physical performance and nutrition is believed to significantly contribute to understanding the health problems associated with BGN and developing appropriate interventions.