This week, the Stanford Medicine X conference kicks off on campus. Among the speakers presenting in the research track is Utah University Postdoctoral Fellow Carlos Nakamura, PhD, who will present findings from two studies that offer insights into the potential benefits of using data from online social networks for clinical research.
During the first study, researchers compared the prevalence of fatigue and depression for patients of amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS) and Parkinson's disease (PD), as reported on the online social network PatientsLikeMe and a large medical record data repository. The second study involved comparing clinicians' and patients' perspectives on the symptomatic treatment of ALS by comparing data from a traditional survey study of clinicians with data from a patient social network.
Nakamura describes the work in a Medicine X abstract:
In the first study, multivariable logistic regression was performed on the probability of reporting fatigue or depression as predicted by age, gender, data source, type of neurological disease and the interaction of data source and type of neurological disease. We report on the effects of the interaction of data source and type of neurological disease on the probability of reporting fatigue or depression. Our analysis addresses whether the association of reporting fatigue and depression with disease type differs between the two data sources, and, equivalently, whether the association of reporting fatigue and depression with data source varies between disease types. These results are controlled for the effects of age and gender. In the second study, we first extracted the 14 symptoms and associated top four treatments and then selected twenty symptom-treatment pairs to compare the clinicians' and patients' perceptions of treatment prevalence and efficacy.
For more information on the conference or to register, visit the Medicine X conference website.
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