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Quasi-experimental studies are a range of nonrandomized intervention studies. These methods are often used when it is not feasible or not ethical to conduct a randomized, controlled trial (Goodwin & Goodwin, 2017). One of the strengths of such studies is that there is higher external validity than true experiments, this is because they frequentlyinvolve real-world interventions, instead of artificial laboratory settings (Thomas, 2020). Contrary, a disadvantage isthat the lack of randomization makes it harder to rule out confounding variables, along with threatening internal validity (DeRue, 2012). An example when this type of study can be used in a counselling setting is when a few therapists in a clinic have decided to try out a new form of therapy, while others who treat similar clients have chosen to stick with the normal protocol. The research can use these two groups to study the symptom progression of the clients treated with the new therapy and those receiving the standard treatment. Although the groups were not randomly assigned, if systematic differences are accounted for, then it can be determined that any differences between the groups must arise from the treatment and not other confounding variables (Thomas, 2020).
Post RepliesFor Quasi-Experimental Designs it is important to have baseline data from before the intervention and after the intervention. This will allow the researcher to explore how much change may have been "caused" by the intervention (Barnes, 2019). If baseline data was not collected, it would be near impossible to determine the impact of the intervention because one would not know what the baseline measurements were before the intervention.Furthermore, throughout the discussions, many have acknowledged the possibility of confounding variables reducing the study’s internal validity (Goodwin & Goodwin, 2017). Internal validity can be threatened by maturation, so that participants age over time, thus the observed changes may be due to the participants maturing and not the intervention, or through reactivity, in which observed changes occur as a result of taking part of the study rather than the intervention and lastly due experimenter bias, in which the researchers may consciously or inadvertently influence the outcomes of a study (Barnes, 2019). 2.Rebecca, as you mentioned, nonequivalent control group designs are used when it is not possible to randomized participants into separate groups (Goodwin & Goodwin, 2017). Moreover, the experimental and control groups are matched upon certain preexisting characteristics, however they are not randomly assigned (Sage, 2019). An example that comes to mind is that for my first-year university psychology class,there were an excess amount of students (1800) registered for the class. So the first 600 registered students were allowed to attend thein-person lecture while the rest attended the lecture online. It would be interesting to compare grades between the two groups (in-person vs. online). The groups matched on characteristics such as both groups were taught the same topics, offered at the same university and taught by the same professor. It is important to note that in the in-person group, students were not randomly