Data Collection Week 2

This week marked the first week of my official data collection. While I did have a later start, starting on Wednesday instead of Monday like I had anticipated, it did not set me back as much as I thought it would. While the goal for number of samples for my study is 24, I had set the week goal to be 12. I was able to look through patient folders and input data for 9 patients. I was coming in 2 hours a day, but next week I plan on coming 4 hours a day, as collecting data per a patient takes around 30 minutes. So far, I have collected consent from 20 patients, 10 adults and 10 children. Next week I hope to get 2 more adults and 2 more children to complete my study. So far, I have 13 females and 7 males, so hopefully the 4 new patients will be males to even the samples more. But if not, it does not pose a problem as gender has not been evidenced to cause variations in how ADHD progresses or manifests.

This week, I was able to organize my data by recording the scores for common, vital categories common to both the test for children (TOVA) and test for adult (IVA).  I recorded the patient number, the type of test conducted, date of birth, age, gender, first testing date, last testing date, number of sessions, targeted areas, targeted frequencies, and other mental disorders to make up the preliminary, demographic information. Then I recorded the scores for the first test of response time (how quickly the subject clicks on the answer), d prime (statistic that describes the patient’s ability to distinguish the target stimulus from other stimuli), and variability (measures reaction time to correct answers). Just to put some context to each score, I recorded how the score compared to the average score for that age through a percentile value and, consequently, if the score would be diagnosed as abnormal (possible error in testing, extremely uncommon), atypical (needs extreme improvement), average (normal for an ADHD patient), or good (above average). Then I calculated the initial “ADHD score” for each patient by adding up the first testing scores and final “ADHD score” from the final testing scores.

At my meeting with Mrs. Haag, I was able to really schedule my time down to the task per day, instead of per week. On Saturday, I worked on outlining my data analysis with my dad’s coworker. I was able to delineate step by step how to show the trend of improvement from initial to final scores. Doing a paired-t test makes the most sense, so I can compare the initial and final testing values within the children and adult age groups and then between the two.  By having figuring out what an average ADHD score is, I was able to see that generally so far my data has reflected that people generally do improve from “severe” to “average” or “good”. I cannot see an apparent difference between adults and children just yet, but I have a lot more data to collect, so I will see in the coming few weeks.

Yesterday, I reorganized my data, sectioning it off into different excel sheets to make it easier to read. While putting the data in, I have a bigger spreadsheet so it is easier to add the scores in while I am at the clinic. But for presenting the data to Mrs. Haag and for my research paper, I have a sheet for adults, children, and then the comparison sheets to show how much final scores have changed from initial to final. I have also been working on finding a way to put the data together to create a conclusion. I will most likely present the t-scores from the paired-t test for the adult group and children group and compare to see which group had a higher trend of improvement.

With my methods slightly tweaked, as now I have contextualization for the scores and average percentiles, I do have to edit my literature review and methods. So, I have been editing that today, other than doing this blog post. For the coming week. I plan to input the rest of the data and continue to edit my data analysis. I will complete 5 more patient data sets each day and have data collecting done by the end of the week.

(711)