Health Group, Griffith University, Gold Coast, QLD, Australia.
Library and Learning Services, Griffith University, Gold Coast, QLD, Australia.
Health Inf Manag. 2020 May-Sep;49(2-3):108-116. doi: 10.1177/1833358319831318. Epub 2019 Mar 11.
Building or acquiring research data management (RDM) capacity is a major challenge for health and medical researchers and academic institutes alike. Considering that RDM practices influence the integrity and longevity of data, targeting RDM services and support in recognition of needs is especially valuable in health and medical research.
This project sought to examine the current RDM practices of health and medical researchers from an academic institution in Australia.
A cross-sectional survey was used to collect information from a convenience sample of 81 members of a research institute (68 academic staff and 13 postgraduate students). A survey was constructed to assess selected data management tasks associated with the earlier stages of the research data life cycle.
Our study indicates that RDM tasks associated with creating, processing and analysis of data vary greatly among researchers and are likely influenced by their level of research experience and RDM practices within their immediate teams.
Evaluating the data management practices of health and medical researchers, contextualised by tasks associated with the research data life cycle, is an effective way of shaping RDM services and support in this group.
This study recognises that institutional strategies targeted at tasks associated with the creation, processing and analysis of data will strengthen researcher capacity, instil good research practice and, over time, improve health informatics and research data quality.
对于健康和医学研究人员以及学术机构来说,建立或获取研究数据管理 (RDM) 能力是一项重大挑战。考虑到 RDM 实践会影响数据的完整性和寿命,针对 RDM 服务和支持以满足需求,在健康和医学研究中尤其具有价值。
本项目旨在从澳大利亚一所学术机构的健康和医学研究人员的角度,考察他们当前的 RDM 实践情况。
采用横断面调查,从一个研究机构(68 名学术人员和 13 名研究生)的便利样本中收集信息。调查旨在评估与研究数据生命周期早期阶段相关的选定数据管理任务。
我们的研究表明,与数据创建、处理和分析相关的 RDM 任务在研究人员之间差异很大,并且可能受到他们的研究经验水平和他们所在团队内的 RDM 实践的影响。
评估健康和医学研究人员的数据管理实践,将其与研究数据生命周期相关的任务联系起来,是为这一群体塑造 RDM 服务和支持的有效方法。
本研究认识到,针对与数据创建、处理和分析相关的任务制定机构战略,将增强研究人员的能力,树立良好的研究实践,并随着时间的推移提高健康信息学和研究数据的质量。