Article Critique : Experimental Research Designs
In investigating cause and effect, experimental research designs are ranked amongst some of the most preferred study techniques in Psychology. This is because they offer an exceptional opportunity for the probing of the existential relationship that exists between various variables(Srinagesh, 2011, p. 23). In classic quantitative nature, comparisons are made between two or more groups while also (deliberately) manipulating any of the existent variables to assess any causative effect. It is through such structured procedure that experimental research designs succeed in finding appropriate answers to numerous hypotheses. Yuan et al. (2017) exploits these experimental designs in the“Attitudes to Mental Illness and Its Demographic Correlates among General Population in Singapore” article while on a quest to provide appropriate answers to their hypothesis question. This article critique thus seeks to provide a comparison of the two research designs, an identification of the variables, main effects/interactions with regard to the factorial design and an explanation of any random samples together with their subsequent limitations.
Opinions on how persons with mental health disorders should be treated often vary from one individual to the next. With such realities to contend with, persons with mental health disorders bear the full brunt of societal indifference which ultimately reduces any chance of them seeking professional help for their debilitating conditions. In particular, Yuan et al. (2017) made use of the Attitudes to Mental Health (AMH) questionnaire to assess the factor structure within a multi-ethnic society in Singapore (3). The primary purpose of this study was to; therefore, make use of experimental research designs to establish the prevalent socio-demographic parallelswhile assessing the prevailing mental health attitudes amongst members of different ethnic groups. The two-group experimental design was conducted using a placebo group that would serve as mirror of the general attitudes held by other individuals. It is possible to introduce an intervention routine while using this design with the objective being to tweak the hard stances held by subjects. In comparison, the factorial experiment design makes use of a combination of factors with all their discrete values hence allowing the researcher to gauge individual response variables. The manipulation of variables controlled by a researcher allows them to make a detailed inference of the type of interaction that exists.
Data on attitudes towards mental illness in this study was collected from a section of the general population in Singapore. It is vital to acknowledge that the study also sought to establish the attitudes of mental health professionals, especially considering the fact that they are first in line when dealing with those afflicted. In addition to exploring varying socio-demographic variables (such as the gender, marital status, cultural background and their level of education) the also researchers focused on specific factors that would ultimately guarantee the study’s authenticity. The dependable variable in this case was the 4-factor structure (better known as AMI-SG), a tool that would be applied on participants who were mental health professionals. All eligible participants would then have their mental health attitudes compared to this control group (Yuan et al., 2017). Participants from the general population and health care professionals were, in essence, the study’s independent variables which the researchers could manipulate at any given instance. The study also featured an extraneous variable in the form of the county’s multi-ethnic composition. Ethnic Indians, Chinese and Malays have co-existed in this particular region, each holding on to their distinct cultures in the midst of a diverse society. Conducting the multivariate regression analysis would thus prove challenging since mental health attitudes have been known to vary from ethnic group to the next.
The main effect on the aforementioned dependent variable was as a result of the incorporation of anexplicit independent variable. Through the AMI-SG tool, data was collected from a section of the Singaporean society to aid researchers in gaining a better understanding of the phenomenon under investigation. The research tool was applied to members of the general population and professionals in the sphere of mental health. A noticeable interaction when using the general population and mental health professionals simultaneously was a clear reduction in the construct validity. This is because, as expected, health care professionals would have a more positive attitude towards mental health in comparison to regular Singaporeans. Nevertheless, the study avoided the use of random samples and opted to select specific subjects from its pool of potential candidates. Even with that being said, the limited use of representative samples limited the study and was a visible impediment. The researchers were, hence, unable to properly investigate the mechanisms that are often in use in society and how social contact can change attitudes within a broader context.