Uncertainties about the need for ethics approval in Switzerland: a mixed-methods study
Bibliographic record
Abstract
BACKGROUND: To ensure ethical oversight, researchers wanting to conduct “research” involving human beings are typically required to obtain prior approval from an independent ethics committee. However, it can sometimes be unclear if a project needs to be submitted for ethics approval. Swiss researchers can contact research ethics committees via a “jurisdictional inquiry” for clarification whether a project needs to be submitted for ethics approval. AIMS OF THE STUDY: (1) To examine the characteristics of Swiss jurisdictional inquiries, and (2) to identify possible uncertainties regarding the correct interpretation of existing legislation in Switzerland. METHODS: All jurisdictional inquiries submitted to Swiss research ethics committees between July and December 2017 were reviewed using qualitative content analysis. We then conducted an online survey between June 2018 and July 2018 with all researchers who had submitted a jurisdictional inquiry including a descriptive quantitative analysis. RESULTS: The review included 271 jurisdictional inquiries. Analysis identified three groups of jurisdictional inquiries: 80.4% (218/271) sought clarification whether the project had to be submitted for ethical approval; 18.5% (50/271) requested a “declaration of no objection”; and 1.1% (3/271) asked for a clarification about which of the two ordinances was applicable to the project. Analysis identified eight distinct legal issues that appeared to be the main cause for a number of jurisdictional inquiries, with the two most frequently identified issues being whether the project will produce generalisable knowledge, and whether the project uses fully anonymised data. Overall, research ethics committees decided that 78.6% (213/271) of the jurisdictional inquiries were outside their jurisdiction and did not require ethical approval, and that 15.6% required submission for ethical approval. The online survey achieved a 56.8% response rate. The majority of respondents (94/166; 56.6%) reported that all the questions they were asked during the submission of the jurisdictional inquiry were easy to understand. Respondents reported that 88% (147/166) of all projects were started or planned to start. The vast majority (154/166; 93%) of respondents also agreed with the decisions made by the research ethics committee. CONCLUSIONS: Jurisdictional inquiries are an important means for researchers to clarify whether their project requires ethical oversight. However, this mixed-methods study has identified some difficulties in the interpretation of legal terms, which often reflect persistent structural issues that many other countries also face. More detailed guidance may be helpful to reduce the researchers’ uncertainties and ethics committees’ workloads in relation to jurisdictional inquiries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.104 | 0.144 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".