Experimental Method Analysis

There are multiple components to consider when analyzing an experimental method. These components include the hypothesis, the theory, populations, random samples, independent variables, dependent variables, confounding variables, as well as the experimental group and the control group. Each of these terms needs to be understood in order to identify them within an experimental method. The research study being examined was published in the November 2012 edition of Iranian Journal of Reproductive Medicine. The article titled, “Association between preterm and low-birth-weight with periodontal disease: a case-control study” was written and published by Khadem, Ruhmani, Sanaer, and Afiar (2012). This study aims to find an association between periodontal disease in mothers and low-birth rate in babies through the process off experimental observation. Jay Gould, author of Concise Handbook of Experimental Methods for the Behavioral and Biological Sciences (2002) states that the “discovery of cause-and-effect is the essence and primary advantage of experimental observation.” Based on this, it is clear the research path chosen to address the research question posed are compatible. 

A hypothesis is a tentative conclusion to the proposed research question. The hypothesis needs to be something that can be observed and investigated to determine whether it is correct or incorrect. The hypothesis is sometimes referred to as an educated guess because hypothesizes are created based on prior research. In this research study, the researchers are hypothesizing that there is a link between low-birth rates and mothers with periodontal disease (Khadem et al 2012). The hypothesis is closely associated with the theory. At the start of the research study, the theory is the assumed hypothesis for the sake of argument. For example, the researchers in the above research study are assuming they will find a connection between low-birth rate and periodontal diseases because of the prior research. In they are correct, their theory will be legitimized. 

Once you have your hypothesis developed, and a research proposal is created under a working theory of the situation, a population must be determined. A population is a specific section, group, or type of people within an area or country. In the case of research, a population includes all the possible participants. This study was conducted in Iran and deals specifically with women in the final weeks of their pregnancy; this narrowed the population significantly. Researchers looked at only women referred to the Imam Reza Hospital between 2007 and 2008 (Khadem et al 2012). Women less than 37 weeks and babies less than 1500g were out in the case group. Meanwhile, women that were more than 37 weeks and babies more than 2500g were placed in the control group (Khadem et al 2012). In total, 70 women participated in the study. This group was not considered a random sampling because they were not chosen at random from the entire population. Instead, they were each specifically chosen because they fit the qualifications of the study and they consented to participation. 

The next important component to look at is the variables. Most research studies have independent variables, dependent variables, and confounding variables. The independent variable is the variable that is not influenced by other variables. In this study, the independent variable would be the presence of periodontal disease. To determine this, each participant was given a dental examination, during which they measured factors such as gum bleeding, plaque buildup, and probing depth (Khadem et al 2012). The dependent variable is a variable that is dependant on other variables. In this experiment, the researchers were trying to determine if the babies’ birth weights were dependant on the presence or extent of periodontal disease in the mother (Khadem et al 2012). There are also confounding variables, which are variables that the researcher did not control or eliminate, which damages the internal validity of the experiment. In this case, the confounding variables are the factors related to the participants’ lives and family such as age, types of vaccinations, monthly income, pregnancy age, number of deliveries, surrogacy, amniotic sac rupture, bleeding, or infections (Khadem et al 2012). These are all variables that could affect the babies’ birth rates, but they were not examined by the researchers. 

Finally, experiments have control groups and experimental groups. The control group is the group that represents the standard within the experiment. The experimental group is the one changed or observed for changes or differences, depending on the experiment. In this case, the case group was the control group and the control group was the control group. Although nothing was changed or manipulated, the case group already had low-birth-weight babies, so the goal was to see if they had more periodontal problems than the control group.

References

Gould, J. E. (2002). Concise handbook of experimental methods for the behavioral and biological sciences. Boca Raton: CRC Press.

Khadem, N., Rahmani, M., Sanaei, A., & Afiat, M. (2012). Association between preterm and low-birth-weight with periodontal disease: a case-control study. Iranian Journal of Reproductive Medicine, 10(6), 561-566.