BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//hacksw/handcal//NONSGML v1.0//EN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260511T050852Z
DESCRIPTION:Click for Latest Location Information: http://edw2020.dataversi
 ty.net/sessionPop.cfm?confid=128&proposalid=11426\n<p dir="ltr">Mental heal
 th conditions are highly stigmatized. Stigma perpetuates stereotypes and di
 scrimination, and increases health disparities. In creating programs that r
 educe mental health stigma, it is important to understand the ways that men
 tal health is understood and talked about. The Public Good Projects (PGP) c
 ollaborated with Kaiser Permanente to discover dominant narratives in conve
 rsation around mental health. PGP uses cutting-edge software that collects 
 and monitors big data from 12 publicly available media sources. PGP created
  a query to collect all media messages that reference mental health in some
  way. Data allow&nbsp;analysts to determine the knowledge, attitudes, and b
 ehaviors of the public; how the public perceives mental health; the source 
 and spread of facts and misinformation; and uncovers critical shifts in dis
 cussion. By harnessing the power of big data, this methodology has the pote
 ntial to drastically change health communications to reflect the ways that 
 people are talking about mental health.&nbsp;</p>\n<div>\n\n
 Since November 2017, PGP has collected 33,327,306 messages at the national 
 level&nbsp;that are related to mental health, across media sources (digital
  and social media, online news, broadcast news, print media, etc.). PGP als
 o created algorithms to automatically analyze and code each of these posts 
 into major conversation themes.&nbsp;\n
 Media data were&nbsp;analyzed to show the proportion of conversation around
  specific types of mental health conditions, as well as dominant narratives
  in conversation.&nbsp;\n
 Analysis showed that from the beginning of data collection, conversation ar
 ound mental health has predominantly focused on depression (57.4%), followe
 d by anxiety (46.8%), substance use (7.1%), bipolar (5.7%) and schizophreni
 a (2.4%).&nbsp;\n
 The top five message frames in discourse were around the following themes: 
 personal experiences with mental health conditions (20.2%), clinical treatm
 ent options or medication (13.8%), loved ones&rsquo; experiences with menta
 l health conditions (12.8%), discussion around self harm (9.2% ), and aware
 ness/promotion of mental health (9.1%).&nbsp;\n
 Over 2.5 quintillion bytes of data are now produced each day, yet they are 
 largely untapped for public health purposes. These data show critical, neve
 r-before-seen information that can help organizations understand how health
  topics are being discussed, to ultimately create more impactful programs a
 nd improve population health.\n\n</div>\n
DTSTART:20200326T094500
SUMMARY:Big Data for Public Good: Using Technology-Driven Strategies to Imp
 rove Best Practices in Health Communications
DTEND:20200326T104459
LOCATION: See Description
END:VEVENT
END:VCALENDAR