It wasn't until I read Luker's chapter for this week and saw a guest presentation in INF1001 that I came to a conclusion regarding my sample – assuming it actually is a conclusion. Following a guest lecture in INF1001 regarding the social networking website for patients called patientslikeme.com, it sort of hit me. I've consistently been struggling with an exciting “place” online where I could carry out research regarding the relationship between altruism and personal revelation. I think I may have found it. Patientslikeme.com is an extremely interesting website that encourages patients of varying diseases to share their medical history. That data is stored, analysis on that data is done via some algorithm, and then shared with the community in an attempt to better understand diagnoses, symptoms, and treatments of similar patients.
The interesting part is that the community tends to be more or less split up into two halves: those with common diseases and those with rare diseases. Each user has a profile, which takes quite a long time to fill out. Additionally, each profile consists of modules, which are meant to be filled out over time and with varying granularity. What I'm principally interested in is whether patients with rare diseases, in relation to those with common diseases, divulge more information more often – I would do my best to sample either population according to available statistics. The “so what” of this is to, as my hypothesis would suggest, potentially find that rare disease patients are more likely to participate in personal revelation in an attempt of empathetic altruism. In other words, they understand the systemic limitations of rare disease diagnoses and treatment. Perhaps a greater knowledge base could mitigate some of these failures. In addition, and most importantly, what that could suggest is that those on the margins of the “disease-occurrence spectrum” are at greater risk of personal privacy exploitation. Additionally, risk analysis could be extremely useful in such a study.
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