Tuesday, April 25, 2017

Week 8

I spent most of this week gathering background information for my paper(s) as Kristina reviewed my work. There isn't any prior research on this population, so my scope was a bit broader. Basically anything related to domestic violence, traumatic brain injury, or the relationship between mood and cognitive symptoms is fair game. Dr. Zieman and I agreed on our assigned portions of the paper, and, of course, the order of the authors' names. The latter of the two wasn't really important, but I thought it was interesting that this was even negotiable. 

The highlight of my week was spending time with the clinic's speech therapist. I was finally able to observe the speech therapy process with a few of her patients. This was actually incredibly helpful since I had no knowledge about the treatment beforehand. The first patient (Patient 1) returned for a follow-up visit, while the second (Patient 2) was evaluated for the first time. Both were tested on word association and attention. I'll start with Patient 1. For her first test, she was given a letter and 1 minute to come up with as many words as possible that started with this letter. The test was repeated two more times with different letters. Overall, there was improvement since her last visit. The next test involved filling in the blanks with letter combinations that complete each word. Each row had the same letter combination somewhere in the word (i.e. skirt, mask, risky). The last word association test was also a worksheet which involved filling in the blanks. Patient 1 would choose several words that related to a given word and correct her work after every row. The alternating/selective attention tasks were a bit more interactive. One was an app which required Patient 1 to choose the correct shape or color based on a command. For example, the app would display "Color: triangle" and Patient 1 would have to choose a green star rather than a triangle. In the final test, Patient 1 was asked to sort through a deck of cards by flipping any cards that were odd and red or even and black face-up. In most of the tests, Patient 1 realized that she improved her scores by talking herself through the task or writing reminders on a Post-it note. This is what is so effective about speech therapy; it trains patients to develop skills that are applicable to their own lives. Patient 2 was tested more holistically since it was his first evaluation. In addition to the other word association tests, he was required to associate words with images. For the first task, he was shown a series of images and was required to name them as fast as possible. In the next test, he was shown a symbol key, which stated the names for each individual symbol. He was then shown a phrase created with these symbols, which he would decipher and read aloud. For example, if ☼= "sun", ↑= "above", and ⚘⚘= "trees", then ⚘⚘= "sun above the trees". 

Example of Visual-Auditory Learning Test

In the next test, the speech therapist read several short stories to Patient 2, and he was required to recount the stories using as many of the same words as possible. He was also asked to recall a series of numbers backwards. The last test was confusing even for me. The speech therapist would read a phrase with objects and numbers. Patient 2 would have to repeat the objects first and the numbers second, but in the same order as the original phrase. For example, "frog two hat five" would become "frog hat two five". These are just a few of many tests commonly used in speech therapy programs. The point is that consistent practice is required for these cognitive tasks to have any impact on patient recovery. For obvious reasons, patients who never return after their evaluation don't benefit from the skills that are practiced in therapy. Perhaps the most interesting fact that I learned by observing these sessions is that the door is intentionally left open for each patient visit. This may seem counterintuitive (and in direct violation of HIPAA), but the speech therapist claims that "the real world isn't quiet" so her practice sessions shouldn't be either. I think this focus on real-world application is what leaves a lasting impact on patients. 

Week 7

Google is wonderful. 

With absolutely no experience in statistics, I had to start from the basics and research exactly what "generalized linear model" or "binary data" mean and how they're applicable to my data. After attempting a GLM with an Excel add-in, I quickly realized just how out of my depth I was. The add-in-- or the 14-day trial, rather --was actually produced by an independent company, so there were very few instructions available online. It turns out I was missing input values that were required to generate the model. Needless to say, I had trouble interpreting my data in this format. I talked it over with Kristina, and she advised me to scrap the idea because I didn't have all of the necessary information to create an accurate model. Instead, she suggested that I compare the slopes of the study and control groups, which are actually visible in my original graphs. Let's hope the slopes test works out better than this generalized linear mess.

In other news, Dr. Zieman will be presenting my preliminary data at a conference this weekend. She mentioned that she's worried someone might steal our data before the paper is published, which completely blew my mind because I couldn't understand what anyone would want with my measly Excel graphs. I still can't believe that my work is actually making an impact in educating other professionals. Dr. Zieman also proposed that I visit a shelter to meet with domestic violence victims themselves. I think it's important to understand the emotional and personal circumstances of people with violence-related TBI. It's easy to associate the patients with numbers and symptoms, since I don't even have their names. However, seeing what their lives are like day-to-day after recovery reminds me why I wanted to do this study in the first place. I haven't been to a shelter yet, but I was lucky enough to meet one of the patients from my study here at the clinic. She came in with her service dog (who was lovely, by the way) for one of her final follow-up visits. She was one of two patients who completed the speech therapy program by attending all 10 visits. After the usual assessment, Dr. Zieman asked her a few questions about how she thought her life had changed post-therapy. This woman, a former writer, had experienced a 30-year dry spell because of the cognitive deficits resulting from her injuries. Now, she's in the process of writing two books about her experiences, and plans to participate in NaNoWriMo in November. She claimed this was made possible largely by her speech therapy treatment. Sure, this was just one case where everything went according to plan. Not all patients react the same way. Yet, hearing her story made me realize the significance of this study. Quantitatively proving that these therapies are effective would also prove that these patients are worth the time and money necessary for further research. I usually end my posts by expressing my goals and hopes for this project, but this is the most important one by far. 

Week 6

I completely forgot to mention in my last post that our final paper will be submitted to a medical journal for publication. That sounds like something that would be impossible to forget, but I've been a bit scatterbrained (as usual). 

I met with Kristina, the statistician, this week to clear up some of my questions. Her verdict: I didn't do everything wrong. So that's always good news. On the other hand, I still have my work cut out for me with some of these individual symptom graphs. See, I can't just take the difference between the correlation coefficients and call it a day. I also need to decide whether the difference between study and control is statistically significant. Kristina recommended a Generalized Linear Model (GLM), which is used to analyze linear regressions like mine. Apparently, this model is commonly utilized by medical researchers who are studying extremely rare diseases, and thus are restricted to a very small population of subjects. This method will account for error resulting from my ridiculously tiny sample size, as well as the fact that there are multiple variables involved (symptom severity vs. number of visits, study vs. control, etc.). Typically, this model is created using an actual statistics program such as SPSS. I have Excel. I'll figure it out. 

Obviously, I want to analyze my data in the most accurate way possible. Regardless of my attempts to combat sample size error, the fact still remains: this study is underpowered. We knew this ahead of time. However, we're not looking for anything revolutionary. In reality, the only novel aspect of this study is the fact that no other prior research has been done on this specific population (domestic violence victims with TBI who undergo speech therapy). Our goal is to change that. We want to encourage other doctors to conduct further research on this population despite all of the other variables that make this research difficult. Most of all, we want to prove that the treatments provided here at BNI are even working. Hopefully, that's what this GLM will demonstrate.