Week 6

It’s crazy to me how fast this REU has gone! Time is flying and it’s honestly scaring me, but at the same time it has motivated me to push even harder this week. Let me just say that a lot of caffeine was consumed!

I started out the week by rewriting three scenarios in which we will use in our scenario-based evaluation. We also threw together a draft of our survey which we will release to participants at some point next week (because we need data!). Basically, this scenario-based evaluation (in which we are writing our paper on) will tell us which features participants feel would be most beneficial in a web-based application for the rare disease population. We plan on obtaining at the least 30 responses, as we will create an anonymous survey online to distribute to those with rare diseases.  The answers to the survey will be short answer, multiple choice, and some likert The scenarios include examples of three different mechanisms an application could provide. Here is the basic rundown (sorry it’s so long!)

First, the participant will read this to know the main goal of our application:

Goals of Application and Implemented Mechanisms:

The main goal of the Facebook Rare Disease Application is to establish an online health community specifically for the rare disease population. Although these diseases are considered to be “rare”, more than 10% of the world’s total population has one a rare disease. There are many studies dealing with common diseases that helps create awareness to provide information and support, such as a website called PatientsLikeMe.com. The rare disease population however does not receive the same amount of attention that is necessary to create an effective awareness. Due to such little awareness of rare diseases, there is a lack of information and resources provided by health professionals, along with a lack of understanding from the family and friends of those affected by a disease. This causes those with rare diseases to suffer from a serious lack of support.

The Facebook Rare Disease Application aims to solve this “lack of support” issue amongst the rare disease population by implementing an algorithm that recommends friends to users through matching. Much like an algorithm employed in a dating site, this algorithm will match users based on similarities. A study by McPherson et. al produced the homophily principle, which stated that similarity breeds connection. He goes on to mention how this principle structures every type of network ties, which creates homogeneous personal networks with regard to many sociodemographic, behavioral, and intrapersonal characteristics. The Facebook Rare Disease Application will utilize the homophily principle when matching specific user data such as age, disease, symptoms, interests, and location with other users. Using such data will help create more trustworthy bonds between users who are dealing with the same situations and cannot find proper forms of support from their own lives.

The Facebook Rare Disease Application will connect users together based on their own data, but how will this data be collected? This application will use 3 specific mechanisms to enforce the idea of friending other users similar to oneself to bring more support into the rare disease community. Most user data will be found directly on a user’s public profile – with information such as the age, location, and gender of the individual. Other data, such as a user’s diagnosis and related symptoms, will be filled out while creating their own personal profile. A short survey after signing up to be in the community will entail users to share their diagnosis and related symptoms. Along with that data, the survey will ask why they joined the group and what they are looking to obtain from such an online health community. Since we are focusing on the rare disease populations’ lack of overall support, we will formulate this question in terms of support. For example, the question may read: What kind of support do you currently lack in your life when it comes to your disease? The answers would list the types of support as defined by Cutrona et. al, who believed there to be five types: informational, tangible, esteem, emotional, and social network support. By filling this question out, the data will reflect the most needed kind of support the user lacks in their life. Another question could possibly ask users what kind of support they are most comfortable in giving, so that they would match with those who are in need of a certain type of support in which they are comfortable giving. Once a survey is completed, the user will be notified immediately of potential matches they can friend based on similar diagnosis, symptoms, and needs.

Another mechanism that will be utilized by the Facebook Rare Disease application will be the gathering of certain keywords from users’ statuses and posts. If a user posts to the group about something specific, the algorithm will scan those words into its data and connect it to other users who have posted about similar things. At that point, a notification will be delivered to both users saying that it has been recognized they have posted about the same topic. This could benefit users who are lacking information on a certain topic, or are asking questions. In this way, a user can become acquainted with someone that may have more knowledge on a topic and can provide the user asking a question with proper answers or a form of support that they need. In a study by Park et. al, the relationship between the likeness of words used on thread posts and those users’ future interactions with one another in online health communities. This study provides evidence that the similarity in vocabulary between users’ posts are crucial when it comes to engagement in online health communities.

Facebook is well known for “likes,” the clickable thumbs-up icon under someone’s post where you can share with others things that you find interesting. As many regular Facebook users share interests such as their favorite books, bands, and movies, we hope that our users can do the same. In addition, users should like things that attribute to their health. For example, maybe a user would like a certain specialist in the area. Those who are recommended to be friends with this user based on location may now see that there is a specialist in their area that they were unaware of. When creating a profile, the user will fill out the information they would like available to others. This would include some things that they “like.” If a new user is recommended a friend based on his likes of video games and a few similar movies, the user may be introduced to someone with whom they can build a friendship. More studies done by Fiore et. al analyzed the online dating community and found that those in the dating community sought after people similar to them more often than chance would predict. As applications such as dating websites tend to match their users based on this principle of sharing similarities with one another, we infer from these papers that an application that matches users based on the similarity of data could increase the chances of actually creating a strong bond between users.

Mechanisms with Included Scenarios:


  • Direct notification to user (helper) who could help the user in need.


Scenario 1: Michelle is a 28 year old woman that would like someone to help her make a decision regarding her current medication. She did a quick search and found the Rare Disease support group that is housed in the Rare Disease Application on Facebook. She creates a new post in the Rare Disease Extension application asking if anyone has ever tried Drug A or her current medication, Drug B, so that she can learn about people’s past experiences with both of the drugs. Jane, another user of the application, had previously posted about Drug A and Drug B. The Rare Disease Extension application then notifies her that Michelle is seeking assistance for the two drugs. Jane replies to Michelle’s post and explains that she switched to Drug A from Drug B because Drug A makes her feel drowsy, unlike Drug B. After consulting with Jane, Michelle decides to give Drug A a try. Michelle and and Jane’s exchange on their experiences with Drug A and Drug B in relation to Inclusion Body Myositis is indexed in the system and will continue to benefit others with similar conditions in the community.


  • Suggesting other users to friend based on similar conditions or symptoms.


Scenario 2: Molly is a 42 year old with Hereditary Angioedema. Molly has to work from home due to recurrent episodes of swelling in her limbs. She feels isolated and that she doesn’t have anyone to communicate with about her disease. While she talks to her husband about her conditions and that her husband tries to help her with daily chores such as washing the dishes and cleaning the home, she does not want to be a burden to him. To a certain extent, it can be difficult for him to understand since he does not have the disease. She would like to talk to someone who really understands how the disease affects her not only physically but mentally. After conversing with a therapist, he mentions how Facebook features a web based application that can find those with similar conditions. Molly finds and joins the Rare Disease Facebook Community. The application recommends that Molly becomes friends with 3 other women who have previously posted similar concerns. All of them were unable to bear children, and all three face the problem of not knowing anyone in particular with their disease who understands their daily pains. Molly not only forms a friendship with these women, but also formed a community to exchange the mental and physical journey of having a rare disease.


  • Suggesting other users based on similar interests/likes.


Scenario 3: Frank suffers from a extremely rare disease known as Hereditary Spastic Paraplegia. Due to his sickness, he is not able to participate in normal everyday activity and hence does not meet as many people as he would like to. Since he does not meet many people, he yearns for friendship outside of his immediate family which causes him to feel depressed. One day Frank sees a poster that tells about the rare disease facebook community at his local clinic and decides to join. Here, he sees many people who also have rare disease and others who also suffer with depression. He decides to post a link to a online game and asks the rare disease community if anyone would like to play. John’s profile information states that he likes online video games. John is notified about this post and sees it then clicks the link and also begins to play. Frank is then notified that a member from the group, John, has begun playing this game. John and Frank soon become online friends which helps both clients feel as if they have a friend who understands which soothes their feelings of depression caused by loneliness.

After creating a draft of our questions, we spent a lot of our time this week finding out exactly what Facebook wants for user data. As we our writing our paper on a scenario-based evaluation, we will not necessarily need access to this data just yet. However, after our scenario based evaluation is complete, we will have a great idea of what features users feel would facilitate support and information the best, which is how we will construct our web-based app. It feels like we’ve been dealing with Facebook forever, because at first we thought they just wanted screenshots. Then we found out that we basically had to have a mockup showing Facebook how we would use the data we were asking permission to use (people’s bios, likes, and posts) to match users together. It was a lot of work – we even had to create a logo to turn in. I feel as if we shouldn’t be spending so much time on getting approval from them, since we will mainly be taking this data after we develop an app and deploy it to a rare disease community in a user study. As for right now, we are mainly doing research on what features this app should include and writing a paper on it. Anyways, for this Facebook approval we had to create a logo, so I made this:


We also finished our screencasting of our mockup in order to send to Facebook. Fingers crossed, we will send it in by this weekend even though we are dreading what they will say back.

Mostly, we have been spending a lot of time editing our paper. We decided that since our study is only a scenario-based evaluation, that we would change the discussion section to future works. Here, we will discuss how  these features of an application can be used to benefit the rare disease community and even discuss the broader picture…for example: how can a matching algorithm (or other features) benefit other communities that lack support?

I am afraid since it is week six that we may not be able to fully create the beautiful application we had in mind, but Patrick let us know that it doesn’t have to be pretty, but should be functional. After we get the results from the survey, our plan is to get into coding straight away. I’m realizing that 10 weeks is not a lot of time to finish a bunch of research..but luckily since I’m an IU student, Vanessa and I can continue working on this with Patrick until we think it’s perfect!

Also, this week I spent some time updating my Linkedin and Mendeley profile. I read about 30 papers in the 2 weeks before I got to the REU, and I had random PDFs and summaries everywhere. I took it upon myself to do some “online organization” and create folders for my projects so I no longer have to search for things aimlessly. I also organized my Google Drive. Definitely recommend keeping your files organized, especially as you start reading papers on papers on papers…it never ends! (Good thing I like to read, haha).

Also in my spare time, I spent some time fooling around with my MacBook trying different settings and whatnot. Turns out you can change the colors of your folders on your desktop! Here’s the link on how to do it, if you’re curious. It’s kind of a tedious process though: https://www.youtube.com/watch?v=CLyrFDKIvEo

Here’s to a great 3-Day weekend! Happy 4th!