谷歌浏览器插件
订阅小程序
在清言上使用

Assessing Anti-Doping Knowledge among Taiwanese Pharmacists

BMC Medical Education(2023)

引用 0|浏览13
暂无评分
摘要
Background Taiwan’s unique health behaviour, such as extensive exposure to Chinese Herbal Medicine (CHM), has introduced a risk of inadvertent doping among competing athletes. Pharmacy professionals have an imperative role in advising athletes on the safe use of medicines. This study provides an overview of anti-doping knowledge and educational needs among pharmacists in Taiwan and examines influencing factors. Methods A cross-sectional online questionnaire survey consisting of five domains, namely demographic characteristics, source of prohibited substances, identification of prohibited substances, understanding of doping control, and education needs on anti-doping, was distributed to the registered pharmacists in Taiwan. In total, 491 responses were included in the analyses. Results Respondents (65% female, aged 41.9 ± 11.4 years, with 68% having a Bachelor’s degree) reported a moderate anti-doping knowledge score of 37.2 ± 4.9, ranging from 21 to 48 (out of 51). Fifteen per cent of them had the experience of being counselled about drug use in sports. Higher knowledge scores were observed in younger respondents, showing an age-dependent effect ( p < 0.001). Individuals practising in southern Taiwan (compared to northern Taiwan) and those working at clinics (compared to hospitals) exhibited lower knowledge. Most of the respondents (90%) knew that stimulant ephedrine is prohibited in sports, but few had recognised diuretic furosemide (38%) and CHM (7%) containing β 2 -agonist higenamine. Approximately 90% of respondents agreed with the need for anti-doping education. Conclusions This study highlights the heterogeneity of anti-doping knowledge among pharmacy professionals and provides practical relevance in organising future educational topics and research-based activities.
更多
查看译文
关键词
Pharmacy education,Sport,Athlete,Chinese Herbal Medicine,Performance-enhancing drug,World Anti-Doping Agency
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要