Research data management in practice: Results from a cross-sectional survey of health and medical researchers from an academic institution in Australia

被引:6
作者
Krahe, Michelle A. [1 ]
Toohey, Julie [2 ]
Wolski, Malcolm [3 ]
Scuffham, Paul A. [4 ,5 ]
Reilly, Sheena [1 ]
机构
[1] Griffith Univ, Hlth Grp, Gold Coast, Qld, Australia
[2] Griffith Univ, Lib & Learning Serv, Gold Coast, Qld, Australia
[3] Griffith Univ, eRes Serv, Nathan, Qld, Australia
[4] Griffith Univ, Ctr Appl Hlth Econ, Nathan, Qld, Australia
[5] Griffith Univ, Menzies Hlth Inst Queensland, Gold Coast, Qld, Australia
关键词
medical informatics; health information management; data collection; research; academies and institutes; best practices; RESEARCH LIFE-CYCLE; DATA SERVICES; SUPPORT; LINKAGE; SKILLS; NEEDS;
D O I
10.1177/1833358319831318
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: 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. Objective: This project sought to examine the current RDM practices of health and medical researchers from an academic institution in Australia. Method: 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. Results: 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. Conclusion: 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. Implications: 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.
引用
收藏
页码:108 / 116
页数:9
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