From the Guidelines
In randomized controlled trials (RCTs), the most effective way to evaluate intervention effectiveness is by comparing the intervention group to a control group that receives either a placebo, standard care, no treatment, or an alternative intervention, with the specific comparison groups including treatment as usual (TAU), active TAU, active nonspecific interventions, and active evidence-based interventions, as identified in a systematic review and meta-analysis 1.
Comparison Groups
The primary comparison groups used to evaluate the effectiveness of an intervention in an RCT include:
- Treatment as usual (TAU): This group receives the standard treatment for the condition being studied, which can include drug treatment, case management, or waiting lists.
- Active TAU: This group receives a more intensive version of the standard treatment, which can include multidisciplinary rehabilitative programs.
- Active nonspecific interventions: This group receives an intervention that is designed to control for nonspecific aspects of the treatment, such as social stimulation, leisure activities, or computer activities, and is matched with the intervention group for duration and schedule.
- Active evidence-based interventions: This group receives an intervention that is specifically implemented for comparison purposes and is based on the best available evidence.
Rationale
These comparison groups are used to establish a baseline for the natural course of the condition, to account for the placebo effect, and to compare the new intervention to current best practices. By using these comparison groups, researchers can determine whether the observed effects are truly attributable to the intervention rather than to chance, natural recovery, or other factors, establishing causality with greater confidence than observational studies.
Study Designs
More complex designs may include multiple intervention arms to test different doses or combinations, or factorial designs that evaluate multiple interventions simultaneously. These designs can provide more detailed information about the effectiveness of the intervention and can help to identify the most effective treatment strategies.
Evidence
A systematic review and meta-analysis of randomized clinical trials found that these comparison groups were effective in evaluating the effectiveness of cognitive remediation for schizophrenia 1. The study identified four comparison groups, including TAU, active TAU, active nonspecific interventions, and active evidence-based interventions, and found that the most effective comparison group was active evidence-based interventions.
From the Research
Comparison Groups in Randomized Controlled Trials
The effectiveness of an intervention in a randomized controlled trial (RCT) can be evaluated using different comparison groups. These groups are essential in determining the cause-effect relationship between the intervention and the outcome.
- Control Group: A control group is a group of participants who do not receive the intervention being tested 2, 3. This group serves as a baseline for comparison with the intervention group.
- Intervention Group: The intervention group receives the treatment or intervention being tested 2, 4. The outcomes of this group are compared to those of the control group to determine the effectiveness of the intervention.
- Non-Randomized Control Group: In some cases, a non-randomized control group may be used, where participants are not randomly assigned to the control or intervention group 3. This type of control group may require statistical adjustments to account for biases.
- Historical Control Group: A historical control group consists of participants who received a different treatment or intervention in the past 3. This type of control group can be used when a randomized controlled trial is not feasible.
- Wait-List Control Group: A wait-list control group consists of participants who are waiting to receive the intervention being tested 4. This type of control group can be used to evaluate the effectiveness of an intervention over time.
Evaluating Changes Between Baseline and Follow-Up
When evaluating the effectiveness of an intervention, it is essential to define changes between baseline and follow-up measurements 5. Different definitions of "change" can lead to different results, and analysis of covariance or multinomial logistic regression analysis may be used to evaluate continuous or dichotomous outcome variables, respectively.
Quality Assessment of Randomized Controlled Trials
The quality of an RCT can be assessed using a system that evaluates the design, implementation, and analysis of the trial 6. This system considers factors such as quadruple blinding, analytic techniques, and controls of quality to determine the index of quality of the RCT.