Quasi-Experimental Designs - One-group Intervention Studies

As I have addressed in a previous post, a clinical trial is defined as a research study in which one or more human participants are prospectively assigned to one or more interventions (which may include placebo or other control) to evaluate the effects of those interventions on health-related biomedical or behavioral outcomes.  My previous post provides a narrative about clinical trials that entail at least two independent groups.  This present post will describe clinical trials where one-group designs are utilized.

An intervention study in which one group of participants undergo repeated measurements before and after receiving one or more interventions is called a repeated measures design.  Because all participants receive the same interventions and the treatment effects are associated with changes within each participant, the repeated measures design is also referred to as a within-subjects design. 

In repeated measures designs, participants/subjects act as their own control, which is considered a study design strength in that the potential influence of individual differences is controlled.  For example, age and gender characteristics remain constant.  Therefore, changes in outcomes are inferred to be due to treatment effects and not differences between participants.  Using study participants are their own control provides the most equal “comparison group”.

https://journals.lww.com/pedpt/Fulltext/2017/07000/A_Home_Based_Body_Weight_Supported_Treadmill.10.aspx

 So, why is the randomized clinical trial consider the gold standard of intervention study designs?  Why isn’t the repeated measures design better?  One disadvantage of repeated measures studies is the possibility of practice effect or learning effect.  Study participants can learn how to perform better on an outcome measure through practicing or performing the outcome measurement on a repeated basis.  Consider a repeated measures intervention study in which the outcome measure is physical function.  Study participants may appear to show an improvement in physical function, but improvements could be due to participants learning how to perform the physical function test through repeated practice and not due to the treatment.

Another potential disadvantage of the repeated measures design is the carryover effect.  Study participants are at risk of experiencing a carryover effect when they are exposed to multiple forms of treatment.  Consider a study where one group of participants is exposed to three different balance training treatments (treatment A, treatment B, and treatment C) and the outcome measure is balance.  If balance is measured after each treatment, treatment A could have a carryover effect when balance is measured after the participants receive treatments B and C.  Thus, one cannot determine separate effects between treatments A, B, and C. 

Although practice effects and carryover effects are possible limitations of repeated measure designs, investigators can incorporate methods to control such limitations.  Methods to control for these limitations often depend on the nature of the independent (treatment) and dependent (outcome measure) variables.  I encourage readers of this blog to post comments on how to control for these limitations in difference types of studies!