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We want to know if users are having any trouble. - -### Methods - -To address the problem, there was a survey created in Google Forms that was shared. -The first section is collecting information such as name, email, if they are viewing on computer or mobile, and hardware information. -The second section is selecting a disease and then flipping through the various pages to see identify useful data points about the outputted results. -The third section is feedback about how a patient or provider would react to the app. -The fourth section is feedback regarding which features testers did not useful, additional features, and any general comments. - -Each question was carefully crafted with the intent of ensuring that it was very clear what the user needed to do without ambiguity. -This way, results can be consistent even when future iterations of the app are developed. - -### Results - -The survey was sent out to a variety participants and there have been 15 responses. - -There is a wide variety of findings based on the responses. Each response highlights different suggestions that the tester thinks would be good to add to the app. - -### Discussion - -Most of the responses rated the pages in the app easy to use, meaning that users are able to access the information about healthy eating. - -The strengths of the results is that they are ideas that can be used to improve the app. -The limitations of these results is that everybody ultimately has a different vision of what they would like to see implemented and it is not possible to have every feature without the app become cluttered. - -The usability survey is an important part of the creation of the app since it was one of the ways of testing and marks where the team was in the development process at a given time. -Testing software like the app is important since it discovers defects before the delivery to the end user, which guarantees the quality of the software. -Testing makes the software more reliable and easy to use. -Moreover, user experience can be measured using testing since there are questions asking the testers their opinions. - -## Problem 2 - -Now I will conduct a case study into a user with obesity. This means I will pretend I am someone who wants to find more information about nutrients to fight obesity. +The first scenario I will conduct a case study into a user with obesity. This means I will pretend I am someone who wants to find more information about nutrients to fight obesity. Obesity is a disorder involving excessive body fat that increases the risk of health problems. Obesity is a problem throughout the United States of America. @@ -143,6 +109,44 @@ There are sources and specific articles accessible as linked in the app. The strengths of the results is that they are straightforward. The weaknesses of the results is that they could include more recommendations or a wider variety. +## Problem 2 + +The next problem that I am examining is creating the usability survey in order to gain a better understanding of how the users are interacting with the app. +While the Eat4Genes team understands our intent with the app, it is important to make sure that users know how the app operates. We want to know if users are having any trouble. + +### Methods + +To address the problem, there was a survey created in Google Forms that was shared. +The first section is collecting information such as name, email, if they are viewing on computer or mobile, and hardware information. +The second section is selecting a disease and then flipping through the various pages to see identify useful data points about the outputted results. +The third section is feedback about how a patient or provider would react to the app. +The fourth section is feedback regarding which features testers did not useful, additional features, and any general comments. + +Each question was carefully crafted with the intent of ensuring that it was very clear what the user needed to do without ambiguity. +This way, results can be consistent even when future iterations of the app are developed. + +### Results + +The survey was sent out to a variety participants and there have been 15 responses. + +There is a wide variety of findings based on the responses. Each response highlights different suggestions that the tester thinks would be good to add to the app. + +One of the main points of feedback is that there needs to be a better distinction between patient and provider. Currently, the app requires a high level of medical literacy so it would be more suited for a healthcare provider or researcher. + +Moreover, another suggestion that testers provided is the ability to view multiple diseases/conditions at once and how they might combine together. This has a real-world use case since a user might have conditions/diseases concurrently. + +### Discussion + +Most of the responses rated the pages in the app easy to use, meaning that users are able to access the information about healthy eating. + +The strengths of the results is that they are ideas that can be used to improve the app. +The limitations of these results is that everybody ultimately has a different vision of what they would like to see implemented and it is not possible to have every feature without the app become cluttered. + +The usability survey is an important part of the creation of the app since it was one of the ways of testing and marks where the team was in the development process at a given time. +Testing software like the app is important since it discovers defects before the delivery to the end user, which guarantees the quality of the software. +Testing makes the software more reliable and easy to use. +Moreover, user experience can be measured using testing since there are questions asking the testers their opinions. + # Summary and Recommendations From Eat4Genes, the most unique part was the data transformation process of combing through the studies into R dataframes that can be queried in a SQL-like manner to the app creation. diff --git a/StudentNotebooks/FinalNotebook/dar_final_chaij_15dec2021.Rmd b/StudentNotebooks/FinalNotebook/dar_final_chaij_15dec2021.Rmd new file mode 100644 index 0000000..27dc673 --- /dev/null +++ b/StudentNotebooks/FinalNotebook/dar_final_chaij_15dec2021.Rmd @@ -0,0 +1,325 @@ +--- +title: "MATP-4910 Final Project Notebook" +author: "Jeffrey Chai" +date: "15 December 2021" +output: + pdf_document: + toc: yes + html_document: + toc: yes +subtitle: "Eat4Genes" +--- + +```{r, echo=FALSE, results='hide', message=FALSE} +# add libraries +if(!require("tidyr")) { + install.packages("tidyr") + library(tidyr) +} +if(!require("png")){ + install.packages("png") + library(png) +} +``` + +# Final Project: Github Information + +* Github repository: https://github.rpi.edu/DataINCITE/Eat4Genes +* Your github ID: *_chaij_* +* Final notebook: *dar_final_chaij_15dec2021.Rmd* + +* Summary of github contributions including github issues addressed. + + * My branch on GitHub is dar-chaij: https://github.rpi.edu/DataINCITE/Eat4Genes/tree/dar-chaij + * I helped work on the Eat4Genes Shiny app: https://olyerickson.shinyapps.io/Eat4Genes/ + + * List of Github issues that I worked on: + * Complete About Page: https://github.rpi.edu/DataINCITE/Eat4Genes/issues/87 + * Create Gap Analysis: https://github.rpi.edu/DataINCITE/Eat4Genes/issues/95 + * Create Usability Survey: https://github.rpi.edu/DataINCITE/Eat4Genes/issues/159 + * Additionally, I added Issues and assigned them to others accordingly during the testing process: + * https://github.rpi.edu/DataINCITE/Eat4Genes/issues/135 + * https://github.rpi.edu/DataINCITE/Eat4Genes/issues/136 + * https://github.rpi.edu/DataINCITE/Eat4Genes/issues/159 + * https://github.rpi.edu/DataINCITE/Eat4Genes/issues/204 + * https://github.rpi.edu/DataINCITE/Eat4Genes/issues/206 + + * Include browsable links to all external files + + * Link to the filtering code (collaborative): https://github.rpi.edu/DataINCITE/Eat4Genes/blob/master/data/filter.Rmd + * Link to updated merge-gene-data.Rmd: https://github.rpi.edu/DataINCITE/Eat4Genes/blob/master/data/genedata/merge-gene-data.Rmd + * Link to updated merge-study-data.Rmd: https://github.rpi.edu/DataINCITE/Eat4Genes/blob/master/data/studydata/merge-study-data.Rmd + + * List of presentations, papers, or other outputs + + * The Eat4Genes Final Presentation: https://docs.google.com/presentation/d/1y-jVcOf446acTavemcBr5U-M-ZZwUA2xo_lUySiiceg/edit + * Link to Usability Survey: https://forms.gle/6PE9G4Zj5zBkH1Ba7 + + * List of references + + * The outside sources that were used are NutriGenomeDB database and 20+ scientific studies found in the GitHub repository in the data section. + * Additionally, shared codebase used is in the GitHub repository. + +# Overview & Problems Tackled + +Eat4Genes is an app designed to provide user with access to nutritional information that can prevent and help different conditions or diseases. +At a high level, users are able to select a disease/condition and then gain information about recommended foods to eat. +The goal of the app is to provide personalized nutritional recommendation depending on the diseases and conditions specified. +The Eat4Genes app utilizes data that were analyzed from various scientific studies about how certain nutrients contribute to gene expression. + +The purpose of this paper is to provide documentation regarding the successes and shortcomings of the app in hopes that it can benefit future collaborators. +In addition, there is a case study analyzed in order to provide a use case. + +Problems Tackled: At the beginning of the semester, I read through articles and then analyzed whether certain nutrients resulted in increase or decrease for particular driver genes. This information was placed into three data frames with various schemas (described below in Data Description). +Moreover, I worked on code to fix any naming inconsistencies in the nutrient names, performed a gap analysis to see where the app still needed improvement, created usability survey to see how users were interacting with the app. + +# Data Description + +The sources of the data were studies that were recommended by Dr. Dana Crawford, faculty from Albany Medical College. In total, there were over 20 studies analyzed along with information from NutriGenomeDB, a nutrigenomics exploratory and analytical platform. Each study had different sample sizes and duration. There was a wide variety in the studies since they each covered different genes. During the analysis, the team identified driver genes and the conditions that was associated with them. + +There was a ranking formula created in order to rank the studies and how credible they are that was developed by other members of the Eat4Genes team. + +In terms of data organization, this is a resource that explains how the main data frames are organized: https://docs.google.com/spreadsheets/d/1Vzzp3DnNiv3PiO-PTDPx3Ovv6y_jv2ygaRAXDk86q6s/edit#gid=0 + +The first data frame is disease2gene where the schema is made of disease, gene, and expression (either up or down). +The second data frame is genedata where the schema is made of gene, p-value, log to fold change, expression, study, nutrient. +The third data frame is studydata where the schema is made of study, nutrient, description, ranking, study name, summary, geo, link, and UDRule. + +Additionally, another team member and I worked on fixing any naming inconsistencies in the dataframes. This can be found in the filter.Rmd file: https://github.rpi.edu/DataINCITE/Eat4Genes/blob/master/app/data/filter.Rmd + +# Results + +## Problem 1 + +For the first scenario, I will conduct a case study into a user with obesity. This means I will pretend I am someone who wants to find more information about nutrients to fight obesity. + +Obesity is a disorder involving excessive body fat that increases the risk of health problems. Obesity is a problem throughout the United States of America. This scenario will demonstrate how a real user would interact with the app. + +Here is the situation: Bob is a 62 year-old high school social studies teacher from Troy, NY. +Bob was not very physically active during the COVID-19 pandemic, so he gained a significant amount of weight and feels lethargic most of the time. +As a result, he is seeking to use the Eat4Genes app in order to learn about how he can better be in control of his health and well-being. +On the scale from patient to provider, Bob fits the description of patient better because overly scientific lingo confuses him. + +### Methods + +The methods are to generate results based on the selections that Bob makes. + +After clicking on the link to the app, the first message that appears is a pop up message that states “Welcome to Eat4Genes. Bob will begin by selecting a condition to eat for. Then, Bob will see his food recommendations.” + +![Opening page](chaij-images/0-Start.PNG) + +\newpage + +After acknowledging the message by clicking “OK”, Bob will notice a selection menu. On this page, Bob will select "Obesity" from the condition/disease drop down menu. As a result, he sees that recommended foods are aspera leaves, egg yolks, grape, orange juice, white onion and yellow onion. + +![Start Here! What Should I Eat? page](chaij-images/1-Start-Here.PNG) + +\newpage + +From there, scrolling down on the page reveals a bubble plot of recommended foods that Bob should eat. +The results can also be displayed in a table view. While this chart is cool, Bob is unsure what to do with this. + +![Bubble Plot diagram](chaij-images/2-Circles.PNG) + +\newpage + +The next page is titled "Why should I eat it", which shows how each of the foods impact the gene expressions of each gene related to obesity. This page highlights any risk genes. Bob notices that there are some down regulated genes and some up regulated genes, but is unsure how these apply to him. + +![Why should I eat it? page](chaij-images/3-Why-Eat.PNG) + +\newpage + +The following page is titled "What studies say I should eat it", which displays a table with nutrients and information from the studies that show where the data comes from. + +![Why studies say I should eat it? page](chaij-images/4-Which-Studies.PNG) + +Moreover, there is a more information page to download a detailed report. Bob downloads the report, but is unsure what to do with it. + +![More Details page](chaij-images/5-More.PNG) + +Additionally, there is also an about page that provides additional insight into the project. Bob can learn more the development into the app and who is responsible for it. + +![About page](chaij-images/6-About.PNG) + +### Results + +Bob will view the recommended nutrients displayed by the app. Additionally, Bob will view the risk genes for obesity, the studies the data is pulled from, and more information. While the app is useful, there are parts that are confusing for Bob such as the up regulated and down regulated genes. + +The whole foods that were recommended are aspera leaves, egg yolks, grape, orange juice, white onion and yellow onion. Knowing this information, Bob can seek to include these foods in his diet. + +In conclusion, the first page provides the information regarding which foods should be incorporated while the later pages can provide more in-depth information if the user is interested. + +### Discussion + +Performing a case study is important since this is how actual users, like Bob, would gain information from the app. + +These findings are direct recommendations into healthy eating since the results directly give the user information about what they could do. +There are sources and specific articles accessible as linked in the app. + +The strengths of the results is that they are straightforward. +The weaknesses of the results is that they could include more recommendations or a wider variety. + +While the information is helpful, Bob might struggle navigating with the app since the language is very scientific. +Overall, Bob was able to understand the recommended the nutrients. However, he is still unsure as how to incorpoate the foods into the diet. +In order to improve user experience, it might be helpful if the app was more straight forward rather than having too much information. + +In conclusion, Bob was successful in finding appropriate information. +Something that is missing is how to incorporate the recommended foods in his diet, a feature that would be helpful for him. +An example of this would be including sample recipes. + +## Problem 2 + +The next problem that I am examining is creating the usability survey in order to gain a better understanding of how the users are interacting with the app. +While the Eat4Genes team understands our intent with the app, it is important to make sure that users know how the app operates. +We want to know if users are having any trouble. +In order to do this, there are detailed questions to ensure the user is following along. + +\newpage + +### Methods + +To address the problem, there was a survey created in Google Forms that was shared. +The first section is collecting information such as name, email, if they are viewing on computer or mobile, and hardware information. +Questions asked here include "what browser are you using?", "what hardware are you using?", "what operating system are you using?". +These questions are asked in case one browser, hardware, or operating system is not displaying results correctly. + +![First page of the survey](chaij-images/1-Page.PNG){width=40%} + +\newpage + +The second section is selecting a disease and then flipping through the various pages to see identify useful data points about the outputted results. The specific questions asked include +"On the initial Start Here! What should I eat? page, select Obesity. What whole foods were recommended?", +"Select the Why Should I Eat It? page, which genes are down regulated by the suggested nutrients?", +"Select the Which Studies Say I Should Eat It? page, what is the link for the orange juice study?", +"Select the More Details page, what is the fold change for the FTO gene in the orange juice study?", +and "Pick a different condition/disease of your choice and examine the pages, how easy was it to do this?". +These questions are asked since this is the information that a user would like to know. + +![Second page of the survey](chaij-images/2-Page.PNG){width=50%} + +\newpage + +The third section is feedback about how a patient or provider would react to the app. The questions asked here are "Imagine you are a patient, what information would you like to see in this app?", "How could we improve this app to make it more useful for a patient?", "Imagine you are a healthcare provider, what information would you like to see in this app?", and "How could we improve this app to make it more useful for a healthcare provider?". +These questions are asked since the app is aimed at both patients and providers as the two target groups. + +![Third page of the survey](chaij-images/3-Page.PNG){width=50%} + +The fourth section is feedback regarding which features testers did not useful, additional features, and any general comments. +The questions asked here are "Are there any additional features you would like to see in the app?", "Were there any features you found not useful?", "Do you have any additional comments about the Eat4Genes app?". +These questions are asked as a space to provide general feedback on the app. + +![Fourth page of the survey](chaij-images/4-Page.PNG){width=50%} + +\newpage + +Each question was carefully crafted with the intent of ensuring that it was very clear what the user needed to do without ambiguity. +This way, results can be consistent even when future iterations of the app are developed. + +### Results + +The survey was sent out to a variety participants and there have been 17 responses from a variety of people from experts to friends. + +![Responses page](chaij-images/5-Responses.PNG) + +There is a wide variety of findings based on the responses. Each response highlights different suggestions that the tester thinks would be good to add to the app. + +One of the main points of feedback is that there needs to be a better distinction between patient and provider. Currently, the app requires a high level of medical literacy so it would be more suited for a healthcare provider or researcher. Terminology like "p-value" or "fold change" is not intutive for the everyday person to understand. + +Moreover, another suggestion that testers provided is the ability to view multiple diseases/conditions at once and how they might combine together. This has a real-world use case since a user might have conditions/diseases concurrently. As an older individual, Bob might not be technolgically-literate so the tab strcuture can be confusing. + +Additionally, further feedback specifies that we should add a confidence level ranking for the likely benefit of a given nutrient for any condition/disease. + +Below is a graph visualization of how difficult it was to use the app. +The scale went from 1 to 5 where 1 is very easy to use while 5 is very difficult to use. +The results of the bar graph show that most users felt that the app was easy to use. + +```{r} +# insert bar graph +results <- c(1,4,2,2,1,3,2,1,1,1,1,3,1,3,2,4) +barplot(table(results), + main="How easy was it to use the app?", + xlab="Scores (1 - Very Easy, 2- Easy, 3 - Neutral, 4 - Hard, 5 - Very Hard)", + ylab="Count", + border="red", + col="blue", + density=10 +) +``` + +Most responders felt that the app was very easy to use. +However, we must consider that most people that used the app were technologically literate. + +Below is demographic information regarding what the testers of app identify as. +```{r} +user_results <- c("Student","InterestedUser","Student","InterestedUser","Student", + "Researcher","Student","Researcher","Faculty","Student","Provider", + "InterestedUser","InterestedUser","Student","Faculty","Researcher", + "InterestedUser","Student","Faculty","Provider","Researcher", + "Student","InterestedUser") +barplot(table(user_results), + main="Who are the testers?", + xlab="User Type", + ylab="Count", + border="red", + col="blue", + density=10 +) +``` + +Between faculty, interested user, provider, researcher, and student, most testers identified as student or interested user. +This means that the feedback we received would be most applicable to the student target demographic. +While there were only 17 unique responses, some people identified as more than one category. + + +Below is an analysis of whether survey responders accessed the app on a laptop or through a mobile device. +This information is important since the two views are different. + +```{r} +platform_results <- c("Laptop","Laptop","Laptop","Laptop","Laptop","Laptop","Laptop", + "Laptop","Laptop","Mobile","Laptop","Laptop","Laptop","Laptop", + "Laptop","Laptop","Mobile") +barplot(table(platform_results), + main="Laptop vs. Mobile", + xlab="Platform Type", + ylab="Count", + border="red", + col="blue", + density=10 +) +``` + +This shows that most people accessed the app through laptop. + +### Discussion + +Most of the responses rated the pages in the app easy to use, meaning that users are able to access the information about healthy eating. +At the same time, the testers did provide good feedback in that the Eat4Genes app must keep the target audience in mind. In its current state, the app is highly technical so there should be revisions in order for the everyday person to understand the results we provide. + +The strengths of the results is that they are ideas that can be used to improve the app. +The limitations of these results is that everybody ultimately has a different vision of what they would like to see implemented and it is not possible to have every feature without the app become cluttered. + +The usability survey is an important part of the creation of the app since it was one of the ways of testing and marks where the team was in the development process at a given time. +Testing software like the app is important since it discovers defects before the delivery to the end user, which guarantees the quality of the software. +Testing makes the software more reliable and easy to use. +Moreover, user experience can be measured using testing since there are questions asking the testers their opinions. + +In terms of next steps, it is critical that the app become more suitable for patients because it is currently more aimed at providers due to overly scientific language. The app is supposed to be for a broad audience. +Moreover, the app should also include more colors since many testers thought that the color scheme seemed rather bland with too much gray text. + +# Summary and Recommendations + +From Eat4Genes, the most unique part was the data transformation process of combing through the studies into R dataframes that can be queried in a SQL-like manner to the app creation. +All in all, the process was very detail-oriented and carefully put together. + +Additionally, this project really highlighted the importance of nutrition and creating this app can hopefully assist the accessibility of health self-care by providing beneficial information to the users. + +Moreover, I believe my analysis should be included in an expanded app or paper because it provides additional insight into the process that went into creating the Eat4Genes product. + +For the future, potential features that can be added is a feature that could highlight "Foods to Avoid". This feature would be useful since there are common misconceptions regarding what "healthy" foods are. In addition, the data is already there so this addition would not require additional studies. + +Additional work that would improve the results of the app is continuing to add data from high quality peer-reviewed studies as newer scientific breakthroughs occurs in order to maintain the most up-to-date information. + +# References + +Every study that was used in the creation in the Eat4Genes app is uploaded into the Github repository under data: https://github.rpi.edu/DataINCITE/Eat4Genes/tree/master/app/data + diff --git a/StudentNotebooks/FinalNotebook/dar_final_chaij_15dec2021.pdf b/StudentNotebooks/FinalNotebook/dar_final_chaij_15dec2021.pdf new file mode 100644 index 0000000..8b6ac44 Binary files /dev/null and b/StudentNotebooks/FinalNotebook/dar_final_chaij_15dec2021.pdf differ