Basic↦Statistic Methodology↦Study Design↦Study Blinding
What is it? Why is it important?
In studies, blinding is the act of concealing a study treatment allocation from participants, researchers, or both.
The aim of blinding is to minimize bias and enhance the validity of the study.
Biases include:
- An observer bias, where a researcher has a certain expectation towards the effectiveness of a study intervention
- An analysis bias, where the statistician has some expectation regarding the results of a study
- A participant bias, where participants who know their treatment allocation (e.g. intervention versus control group), adjust their behaviour in such way as to affect study outcome/endpoint variable(s).
Study blinding can either be:
- Single-blinded, where only the participant is unaware of the treatment allocation
- Double-blinded, where both participants and researchers are unaware of the treatment allocation
What do I need to do?
As a SP-INV, define the blinding of your study by specifying:
- The type of blinding (i.e. do you want to blind the participants, the researchers (e.g. SP-INV, Site-INV, the statistician, everyone?)
- Measure(s) implemented to ensure blinding (e.g. indistinguishable packaging of the placebo and intervention medication blinding both participants and of the person delivering the medication).
- The feasibility to implement and maintain blinding procedures during study conduct and analysis
Blinded studies may require more resources (e.g. study staff, production and management of investigational product). In order to avoid accidental unblinding, double-blinded studies pose additional challenges and require additional planning (e.g. procedures to ensure participants, site staff, and statistician remain blinded during study conduct and the analysis of study results)
Where can I get help?
Your local CTU↧ can support you with experienced staff regarding this topic
Basel, Departement Klinische Forschung, CTU, dkf.unibas.ch
Lugano, Clinical Trials Unit, CTU-EOC, www.ctueoc.ch
Bern, Clinical Trials Unit, CTU, www.ctu.unibe.ch
Geneva, Clinical Research Center, CRC, crc.hug.ch
Lausanne, Clinical Research Center, CRC, www.chuv.ch
St. Gallen, Clinical Trials Unit, CTU, www.kssg.ch
Zürich, Clinical Trials Center, CTC, www.usz.ch
References
ICH Topic E9 statistical Principles for Clinical Trials – see in particular
- 2.3.1 Blinding
ICH Topic E8(R1) on general considerations for clinical studies - see in particular
- 5.5 Methods to reduce bias