Moameri Hossein, Norouzi Mojtaba, Haghdoost Ali Akbar, Golkar Mostafa Hosseini
Department of Biostatistics and Epidemiology, Faculty of Public Health, Kerman University of Medical Sciences, Kerman, Iran.
HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Iran J Public Health. 2024 Nov;53(11):2595-2599. doi: 10.18502/ijph.v53i11.16963.
The world is changing rapidly, mainly due to the impact of megatrends that have an impact on the entire human life, particularly in medical sciences. Medical research methodologies such as cohort studies provide very critical information, but it is not clear what would be its destination in the future. In this short article, we have tried to offer a somewhat different perspective on the future of cohort studies by analyzing the texts and their conclusions from the author's viewpoint. According to our assessment, cohorts will play a key role in medical research, but their methodology will significantly change in terms of designing, implementing, analysing, and applying the findings. The new generation of cohort study extracts most of their information from electronic health records, and it is not just restricted to a particular geographic area. With the changes in the levels of occupational exposure, risk factors, and the introduction of Omics, likely, occupational and birth cohorts as well as human diseases will likely undergo fundamental changes in the future. Big data will provide researchers with new opportunities, but information extraction and analysis require a team of specialists from several scientific fields. Furthermore, participants are likely to play a more active role in setting priorities and implementing research findings.
世界正在迅速变化,这主要是由于一些大趋势的影响,这些趋势对整个人类生活产生影响,尤其是在医学领域。队列研究等医学研究方法提供了非常关键的信息,但尚不清楚其未来的发展方向。在这篇短文中,我们试图从作者的观点分析相关文本及其结论,从而对队列研究的未来提供一个略有不同的视角。根据我们的评估,队列将在医学研究中发挥关键作用,但其方法在设计、实施、分析和应用研究结果方面将发生显著变化。新一代队列研究大部分信息来自电子健康记录,并且不仅限于特定地理区域。随着职业暴露水平、风险因素的变化以及组学的引入,职业队列、出生队列以及人类疾病未来可能会发生根本性变化。大数据将为研究人员提供新的机会,但信息提取和分析需要来自多个科学领域的专家团队。此外,参与者在确定优先事项和实施研究结果方面可能会发挥更积极的作用。