A group of researchers is evaluating the long-term effects o…
A group of researchers is evaluating the long-term effects of air pollution exposure on respiratory health. They follow a group of individuals who live in a high-pollution area and another group from a low-pollution area for 10 years, regularly collecting respiratory health data. What type of study design is this?
A group of researchers is evaluating the long-term effects o…
Questions
A grоup оf reseаrchers is evаluаting the lоng-term effects of air pollution exposure on respiratory health. They follow a group of individuals who live in a high-pollution area and another group from a low-pollution area for 10 years, regularly collecting respiratory health data. What type of study design is this?
Cоnsider the аrticle оn "Immоrаlity" of Dаta by Wikström and Hübinette (2021) describing the Swedish context where "equality data" (collecting race/ethnic statistics) is often viewed as "immoral" or "un-Swedish." Create a Most Similar Systems Design in which you conduct the same study, but you compare Sweden and one other country of your choosing. That is, you're developing a Small-N observational study based on the research question and findings presented in the Wikstrom and Hubinette (2021) article. Rather than an essay, you may use bullet points to provide your answers to the following: Identify the research question (you may use the same one as the article, but it may need to be updated slightly to accommodate your comparison). Whatever you choose, you should have “equality data” involved in your study. What are your cases: Why did you select those cases and what makes this a MSSD? (This should be at least 2 paragraphs; in the first paragraph you will explain what a defines a MSSD, and in your second paragraph you will explain why/how your study fits within those parameters. Be sure to discuss the benefits of using the MSSD for your study). What is the DV? What is/are the IV(s) of interest? In whatever study you’ve created, you are inevitably forced to handle/accommodate “equality data,” around which there is considerable stigma (as it is considered immoral or un-Swedish). How does this cultural resistance within your study complicate your ability to conduct a small-N analysis? [If you’re struggling to get started, you might consider other variables that pose challenges because of stigma. In this way, consider interviews/surveys wherein you ask people if they voted or Trump; whether participants have/had HIV or other sexually transmitted infections; questions about racism; and questions about mental health. Think about how these things are differently across cultures. Also, think about what the way in which the stigma impacts data collection, data reporting, etc. Then return to the study you just created and think about the challenges that you might face.]