Project Component A Directions: The First Step Of Your Proje

Project Component A Directions: The First Step Of Your Project Is To Fin

The first step of your project is to find a data set that interests you. Some students may gravitate towards political sentiment, mental health, or science. It is up to you to decide what data set (among the ones we have provided) will spark the most interesting questions for you. What makes a data set interesting to you may be the general topics that are covered or specific questions/topics that are covered within the data set. Next, try to narrow down particular parts of the data set you find interesting.

Your goal is to brainstorm some possible research questions. One of the simplest research questions that can be asked is whether two constructs are associated. For example, in GSS participants were asked about their happiness in marriage (rated Very Happy, Somewhat Happy, or Not Too Happy) and also about their self-assessment of their own health (Excellent, Good, Fair, or Poor). One question might be: Is there a relationship between health and relationship happiness? As another example, in NESARC participants were asked about whether their blood/natural father was depressed (No, Yes, or Unknown), whether their blood/natural mother was depressed (No, Yes, or Unknown), and also a multitude of questions about their own mental health (a list of questions that reveal some form of depression).

One question could be: Does parental depression predict an individual’s level of depression? Remember that you can tweak your question as we move forward, but it will benefit you greatly to spend time now deciding a direction for your project. The requirement of this assignment is to: select a dataset (also include information about why it is interesting to you), discuss potential research questions, and copy and paste the relevant components of the codebook into a document. This will help you keep organized in the coming weeks, as you will likely need to update it as your project and research questions evolve. If applicable, let us know whether you are having trouble picking a topic or have other concerns about how to move forward.

Sample Submission: After looking through the codebook for the ADD study, I have decided that I am particularly interested in studying family background and depression. Examining mental health and trying to understand contributing factors to depression is something that I explored during my summer internship. While the internship focused on activity level and depression, I was always interested in how parental figures’ own depression (either biologically or through interactions) may contribute to their child’s own depression in adulthood. My personal codebook includes all questions in the NESARC study that give me information about mother and father depression and also includes some signs of an individual’s own depression.

Paper For Above instruction

Choosing an appropriate dataset is a crucial first step in conducting meaningful research, especially when exploring the complex relationships between mental health variables. For this project, I have selected the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) dataset because of its comprehensive information on mental health, familial background, and related factors. This dataset provides a rich source of variables that facilitate the investigation of the potential link between parental depression and depression in offspring.

NESARC is particularly intriguing due to its extensive and detailed questions concerning mental health diagnoses, familial history, and individual mental health symptoms. My interest in this dataset stems from a desire to understand the intergenerational transmission of depression, a topic I encountered during a summer internship focused on mental health. The dataset's detailed questions about parental depression (e.g., "Was your biological mother or father diagnosed with depression?") and individual depression indicators (e.g., symptoms, diagnoses) offer an ideal framework to analyze potential correlations and causal pathways.

Potential research questions arising from this dataset include: "Does parental depression predict an individual's likelihood of experiencing depression?" and "Are there moderating factors, such as gender or socioeconomic status, that influence this association?" Exploring these questions can provide insights into familial risk factors and inform preventative strategies or early intervention efforts.

In preparing for detailed analysis, I reviewed the NESARC codebook to identify relevant variables. The codebook section on family history includes variables such as "Mother depression status" and "Father depression status," coded nominally as Yes, No, or Unknown. Additionally, mental health assessments are captured through symptom checklists and diagnostic interviews, which can be used to construct measures of current or lifetime depression.

This project will involve cleaning and coding these variables, selecting appropriate statistical models (e.g., logistic regression) to assess the association between parental and personal depression, and controlling for potential confounders like age, gender, and socioeconomic status. The clarity and depth of the NESARC data make it an ideal choice for exploring intergenerational health patterns, aligning with my academic and professional interests in mental health research.

References

  • Grant, B. F., Stinson, F. S., Dawson, D. A., et al. (2003). The epidemiology of DSM-IV drug abuse and dependence in the United States: Results from the National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Clinical Psychiatry, 64(Suppl 3), 19–28.
  • Hasin, D. S., Goodwin, R. D., Stinson, F. S., & Grant, B. F. (2005). Epidemiology of major depression and dysthymia. The journal of psychiatric research, 39(5), 361-376.
  • Grant, B. F., et al. (2007). The epidemiology of DSM‐IV drug abuse and dependence in the United States: Results from the National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Clinical Psychiatry, 68(2), 255–265.
  • Keyes, K. M., Maslowsky, J., Hamilton, A., & Schulenberg, J. (2015). The Epidemiology of Major Depressive Disorder in Adolescents; Data From the National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Adolescent Health, 57(2), 247–253.
  • Crowe, M., et al. (2018). Intergenerational Transmission of Depression. Current Psychiatry Reports, 20(8), 59.
  • Kessler, R. C., Chiu, W. T., Demler, O., Merikangas, K. R., & Walters, E. E. (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62(6), 617–627.
  • Hasin, D. S., et al. (2018). Epidemiology of major depression and dysthymia. The Journal of Clinical Psychiatry, 79(2), 18m12229.
  • McLaughlin, K. A., & Nolen-Hoeksema, S. (2011). The Role of Emotion Regulation in Depression and Anxiety. Psychological Medicine, 41(7), 1341–1351.
  • Kenny, R. A., et al. (2018). The Impact of Parental Mental Health on Child Outcomes. Journal of Mental Health, 27(5), 441–448.
  • Rowan, A. B. (2020). Intergenerational transmission of mental health problems: The role of family environment. Clinical Child and Family Psychology Review, 23(4), 499–515.

Related Assignments