{"id":5913,"date":"2020-12-03T06:54:25","date_gmt":"2020-12-03T06:54:25","guid":{"rendered":"https:\/\/wissenschaftliche-integritaet.de\/kommentare\/forschungsdesign-in-den-lebenswissenschaften\/"},"modified":"2021-06-11T18:09:35","modified_gmt":"2021-06-11T18:09:35","slug":"research-design-in-the-life-sciences","status":"publish","type":"kommentare","link":"https:\/\/wissenschaftliche-integritaet.de\/en\/comments\/research-design-in-the-life-sciences\/","title":{"rendered":"Research design in the life sciences"},"content":{"rendered":"\n

There is a relatively high risk of (unconscious) bias in the interpretation of results or in the selection of certain results due to the complex nature of the subjects of study in the life sciences. At the same time, research carried out on living organisms or in sensitive ecosystems involves an obvious ethical and legal responsibility. The same amount of care needs to be taken in the project planning phase and in establishing appropriate quality assurance measures as in the implementation and publication of the results. The time and cost involved in implementing quality assurance measures can be considerable in the life sciences, so it is vital to allow for this when planning. Approaches to validation need to be considered, especially when results were based on mainly in silico <\/em>analysis.<\/p>\n\n\n\n

Validity of results is determined by research design, the statistical parameters used and well-planned documentation of data and findings. For this reason, methods to avoid bias in the interpretation of findings should be used wherever possible, e.g. the blinding or pre-registration of trials and studies in a clinical setting.<\/p>\n\n\n\n

The choice of research approach is crucial in terms of the validity of the findings, as well as their compatibility and generalisability. The choice of methodology and modelling system should be carefully assessed; the advantages and disadvantages should be openly stated and reflected on in the evaluation. Used models should be valid and a robust research design applied.<\/p>\n\n\n\n

Statistical planning is essential in all areas and is all the more important, the more the approach is based on previously established knowledge which is to be put to the test. A particular challenge here is that statistical requirements often conflict with ethical requirements when it comes to performing studies on humans or animals. A high degree of standardisation when carrying out studies on living organisms fundamentally involves the risk that the findings cannot be transferred to other contexts due to the limited genetic diversity, social context, climate, etc. and the lack of variability of these parameters. Researchers should undertake their own independent assessment to determine whether a research question is experimental or confirmatory.<\/p>\n\n\n\n

Considerations on how to deal with the research data generated by the project should be taken into account during the planning phase, as should the aspect of making data sets available for use afterwards.<\/p>\n\n\n

Helpful suggestions in planning animal experimental studies according to the 3Rs Principle can be viewed at:<\/h3>NC3Rs<\/span><\/a><\/div>","protected":false},"excerpt":{"rendered":"

There is a relatively high risk of (unconscious) bias in the interpretation of results or in the selection of certain results due to the complex nature of the subjects of study in the life sciences. 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