This week is dedicated to composing a results section that conveys, ultimately, the end goal of our year-long research project. Last week, I was able to finish the bulk of my data analysis. I spent this past week finding other trends within my data that could bolster my main conclusion or provide insight that is missing or lacking in this sphere of research. I found that on average, females improved more than males, teenagers improved more than young children, but younger adults improved more than older adults. Now, I am trying to outline a way to present these results to not overwhelm the readers, but rather keep them interested and informed.
I reviewed three studies that were about ADHD, two about neurofeedback therapy, that employed the same method of the t-test as mine. While I did a one-tailed, paired t-test, these studies used a one-tailed t-test, but the results are comparable to my study.
The first study, "Attention-Deficit/Hyperactivity Disorder (ADHD) in Adulthood: Concordance and Differences between Self- and Informant Perspectives on Symptoms and Functional Impairment" by Morstedt, Corbisiero, Bitto, and Stieglitz, investigated the differences in diagnostic measures to detect ADHD. The study presented the results in a table comparing the female and male correlations on ADHD symptoms. The t-value, degrees of freedom, and the p-value were recorded. Underneath, the results were not only summarized but explained in relation to each other. For example, it was identified under the table that males were more likely to rate the hyperactivity/restlessness symptom higher than females and other trends that can be siphoned from the raw data in the table. The t-values are described in comparison with each other, rather than stated independently with no context. I can use this when I convey my results, providing further explanation under a raw table. It is vital to have the t-values there, but, without an explanation, the significance would be lost on the readers. This study also broke down the results into different categories (first explaining the internal consistency measures, then the r-value, then the t-value). My research also has several parts that can be separated in a similar fashion (determining normal distribution, average score decrease, t-scores, and other trends).
The second study, "Efficacy of Neurofeedback treatment in ADHD: The effects on Inattention, Impulsivity, and Hyperactivity: A meta-analysis" by Arns, Ridder, Strehl, Breteler, and Coenen, aimed to find the effect of neurofeedback therapy on treating ADHD in comparison to stimulant medication. Something I could replicate in my own research is the way that this study presents the general results/main conclusion first, and then goes into results of the subcategories and other data found. Like my study, they noted the number of sessions, neurofeedback therapy site on brain, age of the participant, and what brain waves frequencies were targeted. After a table of this information, the results were depicted in paragraph style above a graph describing the results. I can similarly start with my greater conclusion about the comparison of reduction of ADHD scores between children and adults and reflect the results through a graph. Then I could go into the smaller conclusions or calculations (the specific scored categories that make up the ADHD scores and the other trends). I need to be able to tie the smaller conclusions back to the adult/child group comparison at the end.
The third study, "The Effect of Neurofeedback Therapy on Reducing Symptoms Associated with Attention Deficit Hyperactivity Disorder: A Case Series Study" by Deilami, Jahandidedh, et al., aimed to measure the effect of 30 sessions of neurofeedback therapy on children 5-12 years old. Using graphs to depict the calculations with standard deviation and means of the results, the study went from the general conclusion to calculations and explanation. The results section of this paper was relatively short, describing the main conclusion with the dependent t-test in two quick paragraphs. I think a major problem with my results outline right now, as Mrs. Haag noted, is I have a lot of raw data and not enough consolidation of the information and connection back to the hypothesis and purpose of the paper. Using this study as reference, I can aim to make sure my results are not lost in calculations and are presented in a way that shows how they were found but also what they mean in easily understood terms.
All these studies had in common the presenting of the raw data in a table, a table for calculations, and then a simpler, short explanation for the general conclusions. The studies started with a general conclusion, went into specifics of its discovery, and then tied it back to the general purpose. Graphs and tables were primarily used to show the relationships between the average differences and the t values. These are all elements I can incorporate into my results section to hopefully reflect the significance of my work in a clear way.
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I reviewed three studies that were about ADHD, two about neurofeedback therapy, that employed the same method of the t-test as mine. While I did a one-tailed, paired t-test, these studies used a one-tailed t-test, but the results are comparable to my study.
The second study, "Efficacy of Neurofeedback treatment in ADHD: The effects on Inattention, Impulsivity, and Hyperactivity: A meta-analysis" by Arns, Ridder, Strehl, Breteler, and Coenen, aimed to find the effect of neurofeedback therapy on treating ADHD in comparison to stimulant medication. Something I could replicate in my own research is the way that this study presents the general results/main conclusion first, and then goes into results of the subcategories and other data found. Like my study, they noted the number of sessions, neurofeedback therapy site on brain, age of the participant, and what brain waves frequencies were targeted. After a table of this information, the results were depicted in paragraph style above a graph describing the results. I can similarly start with my greater conclusion about the comparison of reduction of ADHD scores between children and adults and reflect the results through a graph. Then I could go into the smaller conclusions or calculations (the specific scored categories that make up the ADHD scores and the other trends). I need to be able to tie the smaller conclusions back to the adult/child group comparison at the end.
The third study, "The Effect of Neurofeedback Therapy on Reducing Symptoms Associated with Attention Deficit Hyperactivity Disorder: A Case Series Study" by Deilami, Jahandidedh, et al., aimed to measure the effect of 30 sessions of neurofeedback therapy on children 5-12 years old. Using graphs to depict the calculations with standard deviation and means of the results, the study went from the general conclusion to calculations and explanation. The results section of this paper was relatively short, describing the main conclusion with the dependent t-test in two quick paragraphs. I think a major problem with my results outline right now, as Mrs. Haag noted, is I have a lot of raw data and not enough consolidation of the information and connection back to the hypothesis and purpose of the paper. Using this study as reference, I can aim to make sure my results are not lost in calculations and are presented in a way that shows how they were found but also what they mean in easily understood terms.(810)
Hey Sunskruthi! It seems like you have been pretty busy! I am really glad that you are done on your primary data analysis and are now working on the secondary analysis to strengthen your primary results. I think it is interesting that you were able to find such clear results from your data analysis. I am really excited to see in your discussion why you think you got the results that you did and then what the implications are for finding this trend in this treatment method. It seems like you have a pretty clear understanding of how you want to organize your data so that's another good thing as well. I think that it would definitely be useful to use tables to show the rate of improvement using this therapy for the different age brackets. Anyways, keep up the good work and I look forward to seeing what comes from what you found!
ReplyDeleteSunskruthi! Hi! You're project sounds really interesting and it seems like you have a pretty good grasp on the data and analysis section. However, I still think the results are a little vague. I felt like especially with the first two sources you presented they seemed like good ideas but I did not understand how the results sections and ideas you took from each could be combined into your own results. As in, I felt like you almost presented two different pictures of the results section. I think your last paragraph showed a good picture of what to do though, and i envision you using the subcategories and such that source 2 showed for the paragraph format. This will make the information easier to digest for the reader, either breaking it up by age or by symptom would be really helpful to start to see the conversation of the results like you mentioned.
ReplyDeleteHey Sunskruthi! Wow, I'm seriously impressed with the work that you've put into your project... It's looking amazing! I definitely think that you're ahead of most people in terms of having ideas of how you're going to organize your data. I'd be careful about the complexity of your information, though. Definitely include graphs and charts with clearly articulated purposes and meanings, so people will have an easier time understanding everything you're trying to say. Your topic is so rich in detail that you're really going to need to make sure that nothing gets lost in technical jargon. Great work so far!
ReplyDeleteSunskruthi -- these seem like good ideas. I'm glad that you looked at other results and figured out pieces that will be useful in incorporating into your results. I do worry, as Grace mentioned, how it's all going to come together, but in our meeting tomorrow, you should have a pretty complete results, so we can review it and figure it out together.
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