Social Media and Healthcare
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Articles and Discussions on the intersection of Social Media and Healthcare.
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Optimizing the Design of Online Randomized Controlled Trials (The Sexunzipped Trial)

Optimizing the Design of Online Randomized Controlled Trials (The Sexunzipped Trial) | Social Media and Healthcare | Scoop.it

Sexually transmitted infection (STI), unwanted pregnancy, and abuse within relationships are public health problems that have a high impact on young people . There are high social and economic costs, making it important to identify cost-effective interventions.


Digital media interventions for sexual health have great potential because of the reach and popularity of technology such as the Internet and mobile phones, especially with young people . Such interventions offer advantages over face-to-face interventions since they can be accessed privately and at users’ convenience and programs can be tailored to meet users’ needs.


The “Sexunzipped” website is an interactive, theory-based website that aims to give young people the tools to make informed decisions about their sexual well-being . We conducted a randomized controlled trial to inform the feasibility of a future definitive online randomized controlled trial to evaluate the Sexunzipped website and to contribute to knowledge about the optimal design of online trials including the best ways to measure sexual health outcomes online .

Background: Sexual health problems such as unwanted pregnancy and sexually transmitted infection are important public health concerns and there is huge potential for health promotion using digital interventions. Evaluations of digital interventions are increasingly conducted online. Trial administration and data collection online offers many advantages, but concerns remain over fraudulent registration to obtain compensation, the quality of self-reported data, and high attrition.


Objective: This study addresses the feasibility of several dimensions of online trial design—recruitment, online consent, participant identity verification, randomization and concealment of allocation, online data collection, data quality, and retention at 3-month follow-up.


Methods: Young people aged 16 to 20 years and resident in the United Kingdom were recruited to the “Sexunzipped” online trial between November 2010 and March 2011 (n=2036). Participants filled in baseline demographic and sexual health questionnaires online and were randomized to the Sexunzipped interactive intervention website or to an information-only control website. Participants were also randomly allocated to a postal request (or no request) for a urine sample for genital chlamydia testing and receipt of a lower (£10/US$16) or higher (£20/US$32) value shopping voucher compensation for 3-month outcome data.


Results: The majority of the 2006 valid participants (90.98%, 1825/2006) were aged between 18 and 20 years at enrolment, from all four countries in the United Kingdom. Most were white (89.98%, 1805/2006), most were in school or training (77.48%, 1545/1994), and 62.81% (1260/2006) of the sample were female. In total, 3.88% (79/2036) of registrations appeared to be invalid and another 4.00% (81/2006) of participants gave inconsistent responses within the questionnaire. The higher value compensation (£20/US$32) increased response rates by 6-10%, boosting retention at 3 months to 77.2% (166/215) for submission of online self-reported sexual health outcomes and 47.4% (118/249) for return of chlamydia urine samples by post.


Conclusions: It was quick and efficient to recruit young people to this online trial. Our procedures for obtaining online consent, verifying participant identity, automated randomization, and concealment of allocation worked well. The optimal response rate for the online sexual health outcome measurement was comparable to face-to-face trials. Multiple methods of participant contact, requesting online data only, and higher value compensation increased trial retention at 3-month follow-up.


source: http://www.jmir.org/2013/12/e278/

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Social Media Can Boost Disease Outbreak Monitoring, Study Finds

Social Media Can Boost Disease Outbreak Monitoring, Study Finds | Social Media and Healthcare | Scoop.it

Monitoring social media websites like Twitter could help health officials and providers identify in real time severe medical outbreaks, allowing them to more efficiently direct resources and curb the spread of disease, according to a San Diego State University studypublished last month in the Journal of Medical Internet Research,Medical News Today reports.


Study Details


For the study, lead researcher and San Diego State University geography professor Ming-Hsiang Tsou and his team used a program to monitor tweets that originated within a 17-mile radius of 11 cities. The program recorded details of tweets containing the words "flu" or "influenza," including:


  • Origin;
  • Username;
  • Whether the tweet was an original or a retweet; and
  • Any links to websites in the tweet.


Researchers then compared their findings with regional data based on CDC's definition of influenza-like illness.

The program recorded data on 161,821 tweets that included the word "flu" and 6,174 tweets that included the word "influenza" between June 2012 and the beginning of December 2012.


According to the study, nine of the 11 cities exhibited a statistically significant correlation between an uptick in the number of tweets mentioning the keywords and regional outbreak reports. In five of the cities -- Denver, Fort Worth, Jacksonville, San Diego and Seattle -- the algorithm noted the outbreaks sooner than regional reports.

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John Mark Bwanika's curator insight, December 7, 2013 5:13 AM

Research on social media......

Drew Hodges's curator insight, February 19, 2015 5:50 PM

This is a cool article to show the real life change that social media is creating. Before it was stated that it would take up to two weeks to detect an outbreak of a disease but now with social media it can be done in a day. 

This article really shows how social media is becoming a part of our everyday life and is taking on roles that we probably didn't expect it to. 

However with the number of users increasing it is important to have tools that help us monitor the large amount of data that is present. 

Its no good having all this information if we cannot harness it's true potential, like the one illustrated in this article for disease break out.

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