Bipolar disorder is the topic that I chose. Bipolar is a common mental illness I often see as a psych nurse. For the first research study, it looked at the outcome of four years with individuals receiving higher education. The second study followed participants for ten years for seasonal variation in symptoms for bipolar I and II. The designs of each study will be discussed along with the view whether the design was the correct one to use for the research. Lastly, this post will examine the repercussion for using the wrong design for a study.

Study Number One

The research study that analyzed the effects that higher education has on people diagnosed with mental illness showed positive results. The Bridge Program is a program that incorporated training that would lead to employment. Research study design was a quantitative one-group pretest-posttest survey. Surveys were given to patients before starting the Bridge Program (pretest) and after being in the program for four years (posttest) (Schindler, & Sauerwald, 2013). The before-after design is basic, but it’s a very versatile design. Researchers can add multiple groups or posttests with this design. The one-group pretest-posttest allows researchers to examine change from one point compared to another position (Polit, & Beck, 2017).

For this study, the design that was chosen was incredibly useful. The data at the end of the study showed a definite improvement in giving higher education to mentally ill patients with diagnoses of depression, bipolar and many others. At the posttest, the data showed an increase in patients who were employed from 5 to 19 of the 48 participants. It also showed the change in people receiving higher education from 7 to 11 participants. Comparing the difference from start to the four-year mark helped show the change that the Bridge Program had on the participants. Simple design but allowed for effective display that the program had a positive outcome with the participants.

Study Number Two

The Second research study analyzed the effects that specific periods of the year had on depression and manic symptoms of bipolar. Weekly participants completed a phone interview that used LIFE Psychiatric Status Rating (PSR) which kept the information collected more quantifiable. The survey analyzed for symptoms of mood disorder (Akhter, Fiedorowicz, & Zhang et al. 2013). Mood changes are one of the primary ways to diagnose bipolar disorder according to the DSM IV (American Psychiatric Association. 2000).

The design of the research was a time series design. Time series studies have multiple times of observation during the study (Polit, & Beck, 2017). The research study had two groups, the participants diagnosed with Bipolar I (202 participants) and the ones diagnosed with Bipolar II (112 participants). No intervention was done on either one of the groups they were just supposed to report weekly about their mood changes in their daily lives. Without the manipulation, it makes this study a nonexperimental study that only focuses on the phenomenon of seasonal changes in people with bipolar disorder (Polit, & Beck, 2017).  Time series was the right choice for the design of the study because of the diagnosis of the participants. Bipolar is marked with changes in mood and needs to be repeatedly observed to tell whether seasonal changes influence the changes of mood.

Why Research Designs are Important

Research designs give researchers the foundation of how and when they will conduct their observation. The validity and the significance of the data collected are also affected by the research design (Angelo.edu. 2018). The design can easily dictate if the study will give valuable information to be used in practice. In the second study of this post, it would be impossible to see the change of mood in the bipolar participants seasonally without the amounts of observation intervals that were used. If the observation were done yearly, it would create a significant limitation of the study. It is difficult for the participant to analyze their mood over a year but when observation is conducted weekly, it generates more accurate data. Feelings can also change yearly but when conducting such a longitudinal 10-year study it showed a consistency of manic episodes in fall and depressive moods peaking during the winter solstice (Akhter, Fiedorowicz, & Zhang et al. 2013). The research design is everything regarding the collection of valid data.

References

Akhter, A., Fiedorowicz, J. G., Zhang, T., Potash, J. B., Cavanaugh, J., Solomon, D. A., & Coryell, W. H. (2013). Seasonal variation of manic and depressive symptoms in bipolar disorder. Bipolar Disorders, 15(4), 377-384. doi:10.1111/bdi.12072

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders: DSM-IV-TR. Washington, DC: American Psychiatric Association.

Angelo.edu. (2018). Research Design. [online] Available at: https://www.angelo.edu/faculty/ljones/gov3301/block11/objective1.htm [Accessed 25 Jun. 2018].

Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Wolters Kluwer.

Schindler, V. P., & Sauerwald, C. (2013). Outcomes of a 4-year program with higher education and employment goals for individuals diagnosed with mental illness. Work, 46(3), 325. doi:10.3233/WOR-121548

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Bipolar disorder affects a lot of people the modern-day society. However, the impact of the illness on people depends on various factors. One of these factors is people’s….
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