Online self-reporting can improve Parkinson's disease research

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Self-reporting systems on the web can help aid researchers of Parkinson's disease, a new study published this week in the Journal of Medical Internet Research finds. Currently, there is little objective clinical information about the dynamic symptoms of Parkinson's for intervals less than three months, leaving that information unquantified--but online platforms, used for patients to self-report, can advance research on the disease.

The study aimed to assess the clinical value of self-reported PD symptoms which users recorded on the social research platform PatientsLikeMe (PLM). Patients quantified their symptoms with a subset of the Unified Parkinson's Disease Rating Scale (UPDRS). Researchers then analyzed the data to elicit a scientific window of the nature of symptoms in a shorter time frame.

According to the study, the users of PLM were consistently younger than those who use the standard Parkinson's disease Data and Organizing Center (PD-DOC) database. In evaluating the PLM users' reported systems, it was found that symptom severity can be varied and unpredictable, conflicting with the "current clinical picture of gradual, smooth changes."

"There are many clinical situations in which high-frequency symptom dynamics would be useful," the study's authors said. "For example, in testing new drug treatments there is a trade-off between minimizing exposure to the novel drug to reduce the risk of unknown side effects and maximizing the opportunity to detect significant changes in symptoms. This temporal trade-off cannot be optimized on a quantitative basis without high-frequency data upon which to base the statistical analysis."

In 2007, researchers found that cancer patients also could benefit from reporting symptoms online in real-time. Online reporting via text message also has been found useful in smoking cessation programs.

To learn more:
- read the JMIR study

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