Research governance as a facilitator for ethical and timely research? Learning from the experience of a large government-funded multisite research project
Bibliographic record
Abstract
Objective The processes of research ethics and research governance are core to the conduct of research in health. Each aims to facilitate research that is both ethical and practical in order to produce new knowledge about the health system and improve the lives of those who use it. However, our experience has demonstrated that the process of obtaining ethical approval for a low-risk and low-resource research project was severely confounded by the multiple layers of research governance in operation at hospitals in Queensland (Qld) and New South Wales (NSW). Methods We analysed our own experience of gaining research governance approval with the aim of improving governance processes for multicentre research projects. Our project aimed to interview and survey one person at each of 57 hospitals in NSW and 18 in Qld. We recorded and compared the steps, documents and time-frame related to research governance approval at each of these research sites. Results We found that the progress of our project was significantly impeded by the multiple steps related to research governance processes in hospitals. Research governance approval took an average of 160 days in NSW and 316 in Qld. There was inconsistency between hospitals regarding documentation and significant duplication of documentation already approved through ethical review processes. The necessity for separate research contracts for all Qld research sites also added to research delays. Conclusion Based on our experiences we make recommendations about changes to research governance including clarification of responsibility, reform of areas of duplication and inconsistency, time limitations for approval and, in Qld, reform of financial and legal oversight. What is known about the topic? The implementation of the National Statement on Ethical Conduct in Human Research in 2007 has resulted in a restructuring that separates out ethics approval from research governance approval. Although in most jurisdictions single ethical review for multicentre sites has been implemented effectively as a result of these reforms, research governance approval still needs to be obtained for each separate research site. What does this paper add? The research governance approval experiences of one large-scale, ethically low-risk research project are discussed in order to draw attention to the problems associated with the disparate and time-consuming research governance processes operating as a result of this system. What are the implications for practitioners? Policy makers and research governance administrators need to urgently address the significant problems caused by the delays and inconsistencies involved in gaining approval for research conducted in public hospitals. Researchers and those working within university ethics offices who provide support for research need to be aware of the problems associated with research governance and factor this into their decisions about research budgeting and timeframes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.161 | 0.273 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.015 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".