We've updated our Privacy Policy to make it clearer how we use your personal data.

We use cookies to provide you with a better experience. You can read our Cookie Policy here.

Advertisement
Big Data From Social Media Helps Combat Prescription Drug Crisis
News

Big Data From Social Media Helps Combat Prescription Drug Crisis

Big Data From Social Media Helps Combat Prescription Drug Crisis
News

Big Data From Social Media Helps Combat Prescription Drug Crisis

Read time:
 

Want a FREE PDF version of This News Story?

Complete the form below and we will email you a PDF version of "Big Data From Social Media Helps Combat Prescription Drug Crisis"

First Name*
Last Name*
Email Address*
Country*
Company Type*
Job Function*
Would you like to receive further email communication from Technology Networks?

Technology Networks Ltd. needs the contact information you provide to us to contact you about our products and services. You may unsubscribe from these communications at any time. For information on how to unsubscribe, as well as our privacy practices and commitment to protecting your privacy, check out our Privacy Policy

Researchers at Dartmouth, Stanford University, and IBM Research, conducted a critical review of existing literature to determine whether social media big data can be used to understand communication and behavioral patterns related to prescription drug abuse. Their study found that with proper research methods and attention to privacy and ethical issues, social media big data can reveal important information concerning drug abuse, such as user-reported side effects, drug cravings, emotional states, and risky behaviors.

Their work, “Scaling Up Prescription Drug Abuse and Addiction Research Through Social Media Big Data,” is reported in the Journal of Medical Internet Research.

Prescription drug addiction is a well-known nationwide problem. Many people who are unable to get help for their addiction seek out peer support groups on Facebook or other social media platforms to share stories about their experiences and also provide social peer-based support.

Lead author, Sunny Jung Kim, PhD, an e-health communication scholar in the departments of biomedical data science and psychiatry at Dartmouth’s Geisel School of Medicine, says that because we are prolific consumers of social media, which is not limited to geography—globally, people spend more than two hours every day on social media platforms generating vast amounts of big data about our personal communications and activities—we can use these platforms to enhance public health communication strategies to help people on a large scale.

“Harnessing social media platforms and data can provide insight into important novel discoveries of collective public health risk behavior, a better understanding of peoples’ struggles with addiction, and their process of recovery,” Kim says. “I started this project because there were few studies about why people use social networking sites to share unsolicited, highly personal information about their drug use, nor about the psychological effects or consequences of this type of user-generated communication.”

Co-author Jeffrey Hancock, PhD, a professor in the department of communication and the director of computational social science at Stanford University, says, “Given the importance of this problem for the U.S. population, it’s imperative that we understand how social media is playing a role and how it can be part of the solution.”

Based on their findings, the researchers designed an evidence-based, multi-level framework to inform future social media-based substance use prevention and recovery intervention programs.

“Our review and typology suggests that social media big data and platforms can be a tremendous resource for monitoring and intervening on behalf of people with drug addiction and abuse problems,” Kim says.

This article has been republished from materials provided by Geisel School of Medicine Dartmouth. Note: material may have been edited for length and content. For further information, please contact the cited source.

Advertisement