Week 3: Methods 2.0

Hi all,

Welcome to week 3 of independent research! If last week I made a new blueprint, this week I tore it up and redrew it (perhaps to say that I took a lot of steps to make something very similar). That being said, I’ve been having considerable difficulties with my methods. A comment last week brought up something really important: my methods are quite subjective to my personal opinion, despite the steps I added in between to prevent that. The big problem is the foggy step I came up with in which I define each variable. So, instead, this week I decided to scrap it!

Being constantly reminded of the need to create a finished product with analyzed data, I began to realize how the steps to my project were based on my own definitions or assumptions and overall was somewhat difficult to characterize as a content analysis. With many seeds of doubt sown in my mind, I retraced my steps and read other published content analyses. Image analyses are somewhat rare in the context I’m writing in, much less comparative content analyses with images. Much of the difficulties I faced in building my project format was trying to invent procedures due to the lack of similar literature. So, I decided that the best way to ground my study was to use previously established categorizations from scoping reviews in the field. I settled on Struik et al.’s two-part content analysis from 2020 which categorized vaping themes in TV advertisements into 4 categories with 16 subcategories after screening hundreds of papers. These were personal, relational, environmental, and product-related themes that were further divided into themes of curiosity and exploration, or enhancing social acceptance, sensory stimulation, new and innovative product design, smoking cessation, and more themes that I had seen in my own research. The best thing about this new framework was that the subcategories WERE the messages that advertisements conveyed, and thus didn’t require the same roundabout process I outlined.

Now, how I’m going to go about assigning advertisements with these tags remains a lasting problem. Like last week, my own bias will likely come into play. Right now I’m thinking to find a coding partner to discuss with to have another opinion.

At this point, the procedure that I follow to the data analysis step seems less treacherous.