Blinding refers to keeping trial participants, health care
providers, and
sometimes those collecting and analysing clinical data unaware of the
assigned
intervention, so that they will not be influenced by that
knowledge. Blinding is important to prevent bias at several
stages of a controlled trial, although, it is not always possible to
implement.
Blinding of patients is important because knowledge of group assignment
may influence how they respond or perceive they respond to
treatment.
Patients who know that they have been assigned to receive the new
treatment may either have favourable expectations or increased
anxiety. Patients assigned to standard treatment may feel
discriminated against or reassured that they are not being exposed to
something new. Blinding is also
used to protect against the possibility that knowledge of assignment
may
affect how health professionals behave (performance
bias) or how the outcome is assessed (detection
bias), however, blinding is not always practical (e.g. when
comparing
surgery to drug treatment).
Blinding is particularly important when outcome measures are
subjective, such as patient’s assessment of pain. It is less
important for objective criteria of outcome, such as death, when there
is little scope for detection bias.
Authors should explicitly state who will be blinded and what steps will
be taken to ensure blinding. Terminology such as single-blind,
double-blind, or triple-blind should be avoided unless they are
explicitly defined when writing a protocol because there are no agreed
upon definitions for these terms.
Illustrative example - WHO pre-eclampsia
trial
|
The study will be a multicentre randomized,
placebo-controlled, double-blind
trial. |
Illustrative example - Perinatal care trial
|
Given the nature of the intervention, we cannot blind the randomisation, and data collectors will know if they belong to an intervention/control hospital. Furthermore, intervention hospitals will receive a computer to implement the intervention, which will be used, among other things, to monitor clinical data (i.e., episiotomy rate and active management of the third stage of labour). As a consequence, it is expected that the intervention will improve the capacity of intervention hospitals to collect and review clinical data and bias might be introduced in outcome assessment. To minimize this problem, the data collection system will be isolated from the intervention instruments as much as possible. (CLAP Trial - go to protocol) |
Illustrative example - From the BMJ
|
Clearly, the mothers recruited and the health educators were not blind to the assignment of mothers to different groups. The outcome assessors were always blind to the assignment at both the 3 and 6 month follow up visits. Staff who were involved in data collection at the 3 month follow up were not involved in data collection at 6 months. The data analysts were not blind to the coding of the groups. (BMJ 1998;316:805–11 - go to article (included with permission)) |
This checklist has been contributed by Dave Sackett, who prepared it for the forthcoming 3rd edition of Clinical Epidemiology; A Basic Science for Answering Questions about Health Care, to be published by Lippincott, Williams & Wilkins in 2005.
There are companies dedicated to the preparation and packaging of
clinical trial supplies. Services may include:
These can be found by searching the internet.
Schulz KF. Chalmers I. Altman DG. The landscape and lexicon of
blinding in randomized trials. Annals of Internal Medicine.
2002;136(3):254-9.
Schulz KF, Grimes DA. Blinding in randomised trials: hiding who got
what. Lancet 2002; 359: 696-700.