One of the best ways to expand people’s understanding and gain greater control over their own lives is to do the research. The independent variables in the part one of the case study are exposure versus no exposure to relaxation or biofeedback. These variables are independent because they are manipulated by the experimenter to find out their effect on the dependent variable (Bailey & Burch, 2017). The dependent variables in this study are the frequency and duration of hot flashes. These variables are manipulated by the experimenter to find out their impact on the exposure or no exposure to relaxation and on biofeedback.
Another factor to pay attention to is that there was no random assignment in this research. Also, this research was quasi-experimental because the experimenter did not directly influence the participants or the conditions of the experiment but used existing groups to explore the processes of interest. The immediate name for the design of this study is time series analysis (TSA) (Huang & Deng, 2021). It is a statistical methodology suitable for longitudinal studies that involve individual subjects or study units repeatedly measured at regular intervals of time (Queirós et al., 2017). It is also worth noting that the design of this study is within the subjects. This means that all situations are tested by the same group of people, in our case, specific women experiencing hot flashes.
Another distinguishing factor of this study is that it did not use the blinding method. All the women were aware of what kind of therapy they were receiving and its aim. This study is an excellent representative of quasi-experimental research, but it could be improved by means of increasing the amount of data collected. The women could be divided into several groups and offered different intensities of therapy. In this way, it would be possible to collect data that the therapy works and specific data on its use at different intensities.
There are also some issues to consider in the second part of the practical assignment. To begin with, this study mainly collected this type of data as records – plots filled in questionnaires, the results of which were recorded, height and weight were measured and recorded (Zozus, 2017).
A structured form of data collection was used in this study because participants completed a specific questionnaire consisting of the same number of questions. In the study, Traina did not collect precise quantitative data on the age of each participant. A Likert-type scale was used in this study – the respondent indicates their degree of agreement or disagreement with statements relating to the object under study, using a scale usually containing five to seven categories. In addition, the self-administered questionnaires were used as a method of data collection. The study says that the readability of all tools was rated at grade 8 level, indicating that they were adapted for all the participants.
The quantitive data collection of this research can be improved in two ways: disputing each study member’s age and weighing study members unclothed. In the first case, capturing age would help better rank the outcome and relate the resulting level of anger suppression not only to blood pressure but also to age. The unclothed weighing will help to identify the participants’ weight accurately and to derive more relevant results.
Bailey, J.S., & Burch, M.R. (2017). Research methods in applied behavior analysis (2nd ed.). Routledge. Web.
Huang, S., & Deng, H. (2021). Data Analytics: A Small Data Approach (1st ed.). Chapman and Hall/CRC. Web.
Queirós, A., Faria, D., & Almeida, F. (2017). Strength and limitations of qualitive and quantitive research methods. European Journal of Education Studies, 27(1). Web.
Zozus, M. (2017). The data book: Collection and management of research data (1st ed.). Chapman and Hall/CRC. Web.