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Current trends in Internet based help- seeking behaviors by youth and implications for drug abuse treatment

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  • 1. NIDA Digital Media & Communication Technologies in Adolescent DrugAbuse Treatment ConferenceRockville MD, April 26, 2010Current Trends in Internet Based Help-Seeking Behavior by Youth andImplications for Drug Abuse TreatmentMichele Ybarra MPH PhDCenter for Innovative Public Health Research* Thank you for your interest in this presentation. Pleasenote that analyses included herein are preliminary. Morerecent, finalized analyses may be available by contactingCiPHR for further information.
  • 2. Today‟s roadmap What do we know about how youth use theinternet and cell phones; What are their online health information seekingbehaviors; What are the implications of this use in terms ofinterventions; What have other fields (e.g., mental health, HIV)done that may have application for drug abusetreatment.
  • 3. Internet use
  • 4. Internet use 93% of 12-17 year olds are online as ofSept, 2009.1 84% of 8-18 year olds have home Internetaccess (up from 47% in 1999) 2 Among those online 1: 73% use social networking sites 8% use Twitter1 “Teens and the internet: The future of digital diversity”, Purcell, 2010. Availableonline at: http://www.pewinternet.com/Presentations/2010/Mar/Fred-Forward.aspx2 “Generation M2” http://www.kff.org/entmedia/upload/mh012010presentL.pdf
  • 5. Daily Internet use by age and time17%23%31%34%48% 49%23%26%37%42%56%50%29% 31%45%52%60%53%-5%5%15%25%35%45%55%65%75%10 11 12 13 14 15 16 17GuwM W1 (2006)GuwM W2 (2007)GuwM W3 (2008)
  • 6. Daily Internet use by race and time:GuwM0%5%10%15%20%25%30%35%40%45%50%White Black / AfricanAmericanMixed race All other200620072008
  • 7. Daily Internet use by income and time:GuwM0%5%10%15%20%25%30%35%40%45%50%<$35,000 $35,000 - 74,999 >$75000200620072008
  • 8. Daily Internet use by sex and time:GuwM0%5%10%15%20%25%30%35%40%45%50%Male Female200620072008
  • 9. Text messaging use
  • 10. Daily texting by age and time: GuwM2% 4%7%15%21% 20%9%16%21%26% 30%41%18%24%41%50%50%59%-5%5%15%25%35%45%55%65%75%10 11 12 13 14 15 16 17GuwM W1 (2006)GuwM W2 (2007)GuwM W3 (2008)
  • 11. Daily texting use by race and time:GuwM0%5%10%15%20%25%30%35%40%45%50%White Black / AfricanAmericanMixed race All other200620072008
  • 12. Daily texting use by income and time:GuwM0%5%10%15%20%25%30%35%40%45%50%<$35,000 $35,000 - 74,999 >$75000200620072008
  • 13. Daily texting use race and income(2008): GuwM0%5%10%15%20%25%30%35%40%45%50%<$35,000 $35,000 -74,999>$75000WhiteBlack / African AmericanMixed raceAll other
  • 14. Daily texting use by sex and time:GuwM0%5%10%15%20%25%30%35%40%45%50%Male Female200620072008
  • 15. Text messaging trends 45% of 12-17 year olds had a cell phone in 2004.This was 71% in early 20081. Daily text messaging among 12-17 year olds wasup from 38% of teens in February of 2008 and54% of teens in September 20092.1 Data from “Teens and Mobile Phones Over the Past Five Years: Pew Internet LooksBack”, Lenhart, 2009. Available online at:http://www.pewinternet.com/Reports/2009/14--Teens-and-Mobile-Phones-Data-Memo.aspx2 Data from “Teens and Mobile Phones”, Lenhart, Ling, Campbell, Purcell, 2010.Available online at: http://www.pewinternet.org/Reports/2010/Teens-and-Mobile-Phones.aspx
  • 16. Text messaging trends Half of teens report sending 50+ per day(1,500 texts a month) Text messaging is most common amongolder (14-17) girlsData from “Teens and Mobile Phones”, Lenhart, Ling, Campbell, Purcell, 2010.Available online at: http://www.pewinternet.org/Reports/2010/Teens-and-Mobile-Phones.aspx
  • 17. Text messaging trends Text messaging is now the primary way thatteens reach their friends. It is more common than: face-to-face contact,email, instant messaging and voice calling Voice calling is most common mode forreaching parentsData from “Teens and Mobile Phones”, Lenhart, Ling, Campbell, Purcell, 2010.Available online at: http://www.pewinternet.org/Reports/2010/Teens-and-Mobile-Phones.aspx
  • 18. Intersection of Internet and cell phones Young people in low income householdsare more likely to go online from theircell phones than other devices.Data from “Teens and Mobile Phones”, Lenhart, Ling, Campbell, Purcell, 2010.Available online at: http://www.pewinternet.org/Reports/2010/Teens-and-Mobile-Phones.aspx
  • 19. Online health informationseeking
  • 20. Health information seeking 31% of 12-17 year olds go online to getinformation about health, dieting, and fitness 17% look for „sensitive‟ health topicsVs 62% who get news about current events /politicsData from September, 2009 as reported in “Teens and the internet: The future of digitaldiversity”, Purcell, 2010. Available online at:http://www.pewinternet.com/Presentations/2010/Mar/Fred-Forward.aspx
  • 21. Health information seeking 55% of 7th-12th graders have ever looked Older teens (62%) And, girls (66% of 15-18 year old girls)Are the most common health information seekersamong 8-18 year oldsData from 2009 as reported in “Generation M2”. Available online at:http://www.kff.org/entmedia/upload/8010.pdf
  • 22. Implications
  • 23. Implications: technology use More and more, technologies such as theInternet and text messaging are whereyoung people “are” This is particularly true for older youth,and older girls specifically
  • 24. Implications: technology use Race does not seem to be a big factor intext messaging use (although incomemay be) With web-enabled phones, thedistinction (and choice between) onlineand text messaging are blurring
  • 25. A look at other fields
  • 26. Data collection tool Boushey: using cell phones to collect a “mobile phone food record”(i.e., visual and recorded data about diet) (5U01CA130784) Brown: using text messaging for experience sampling amongadolescents in alcohol abuse recovery (5R21AA017321) Mundt: depression screen via text messaging for clinicians andother health professionals (1R43MH086152) Sullivan: using text messaging to collect monthly outcome data forparticipants in an online HIV prevention program(1RC1MD004370) Wu: use as a tool for ecological momentary assessment ofadolescents‟ drinking behavior (1R21DA024609)
  • 27. Adherence Belzer : using cell phones as remindersfor adherence to HIV drugs amongadolescents (5U01HD040463) Jakicic: using text messages to promoteadherence to a behavioral intervention toincrease physical activity(1U01HL096770)
  • 28. Behavior change Bull: text messaging-based HIV preventionprogram for Black and African American 16-20year olds (5R21MH083318) Cornelius: using text messaging to deliver‘boosters’ for an adolescent HIV preventionprogram (5R21NR011021) Olsen: text messaging to promote physicalactivity in adolescents (1R21HS018214)
  • 29. Behavior change: Smoking cessation Bock: text messaging-smoking cessation forthose <35 years (1R21DA027142) Miller: text messaging-based program to preventsmoking relapse post partum among low-income,minority women who quit during their pregnancy(1RC1CA145063) Ybarra: text messaging-smoking cessation foryoung adults (1R21DA027142) Ybarra: text messaging-smoking cessation foradults in Ankara, Turkey (5R01TW007918)
  • 30. Take-aways Between 1/3 and 1/2 of young people usetechnology to access health information Text messaging is increasingly common andaccessing the Internet via cell phones isincreasing
  • 31. Take-aways Technologies can reach low income andminority youth as well as more privilegedpopulations Opportunities exist both as a delivery mode ofbehavior change content, as well as a datacollection tool (i.e., stand alone or adjunct toother methods)
  • 32. Thank youMichele Ybarra MPH PhDInternet Solutions for Kids, Inc.Michele@IS4k.com1 877 302 6858, ext. 801
  • 33. Gaming
  • 34. Daily gaming by age and time21%18%22% 23%29%19%15%26%18%25%30%22%18% 17%24%20%28%21%-5%5%15%25%35%45%55%65%75%10 11 12 13 14 15 16 17GuwM W1 (2006)GuwM W2 (2007)GuwM W3 (2008)
  • 35. Daily gaming by race and time: GuwM0%5%10%15%20%25%30%35%40%45%50%White Black / AfricanAmericanMixed race All other200620072008
  • 36. Daily gaming by income and time:GuwM0%5%10%15%20%25%30%35%40%45%50%<$35,000 $35,000 - 74,999 >$75000200620072008
  • 37. Daily gaming by sex and time: GuwM0%5%10%15%20%25%30%35%40%45%50%Male Female200620072008
  • 38. Weekly texting use race and income(2008): GuwM0%10%20%30%40%50%60%70%80%90%100%<$35,000 $35,000 -74,999>$75000WhiteBlack / African AmericanMixed raceAll other