This document summarizes a presentation on current trends in internet and technology use among youth and implications for drug abuse treatment. Some key points: - 93% of 12-17 year olds use the internet daily and text messaging is increasingly common. Internet and texting are primary means for youth to communicate. - About one-third of youth search online for health information, including sensitive topics. Older teens and girls are most likely to search. - Technologies can be leveraged for data collection, treatment adherence monitoring, and delivering behavioral interventions for conditions like smoking cessation and HIV prevention. They reach diverse populations including low-income youth. - Opportunities exist to use internet and mobile technologies as

1. NIDA Digital Media & Communication Technologies in Adolescent Drug
Abuse Treatment Conference
Rockville MD, April 26, 2010
Current Trends in Internet Based Help-
Seeking Behavior by Youth and
Implications for Drug Abuse Treatment
Michele Ybarra MPH PhD
Center for Innovative Public Health Research
* Thank you for your interest in this presentation. Please
note that analyses included herein are preliminary. More
recent, finalized analyses may be available by contacting
CiPHR for further information.

2. Today‟s roadmap
 What do we know about how youth use the
internet and cell phones;
 What are their online health information seeking
behaviors;
 What are the implications of this use in terms of
interventions;
 What have other fields (e.g., mental health, HIV)
done that may have application for drug abuse
treatment.

3. Internet use

4. Internet use
 93% of 12-17 year olds are online as of
Sept, 2009.1
 84% of 8-18 year olds have home Internet
access (up from 47% in 1999) 2
 Among those online 1:
 73% use social networking sites
 8% use Twitter
1 “Teens and the internet: The future of digital diversity”, Purcell, 2010. Available
online at: http://www.pewinternet.com/Presentations/2010/Mar/Fred-Forward.aspx
2 “Generation M2” http://www.kff.org/entmedia/upload/mh012010presentL.pdf

5. Daily Internet use by age and time
17%
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 17
GuwM W1 (2006)
GuwM W2 (2007)
GuwM W3 (2008)

6. Daily Internet use by race and time:
GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
White Black / African
American
Mixed race All other
2006
2007
2008

7. Daily Internet use by income and time:
GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
<$35,000 $35,000 - 74,999 >$75000
2006
2007
2008

8. Daily Internet use by sex and time:
GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Male Female
2006
2007
2008

9. Text messaging use

10. Daily texting by age and time: GuwM
2% 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 17
GuwM W1 (2006)
GuwM W2 (2007)
GuwM W3 (2008)

11. Daily texting use by race and time:
GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
White Black / African
American
Mixed race All other
2006
2007
2008

12. Daily texting use by income and time:
GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
<$35,000 $35,000 - 74,999 >$75000
2006
2007
2008

13. Daily texting use race and income
(2008): GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
<$35,000 $35,000 -
74,999
>$75000
White
Black / African American
Mixed race
All other

14. Daily texting use by sex and time:
GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Male Female
2006
2007
2008

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 was
up from 38% of teens in February of 2008 and
54% of teens in September 20092.
1 Data from “Teens and Mobile Phones Over the Past Five Years: Pew Internet Looks
Back”, Lenhart, 2009. Available online at:
http://www.pewinternet.com/Reports/2009/14--Teens-and-Mobile-Phones-Data-
Memo.aspx
2 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 among
older (14-17) girls
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

17. Text messaging trends
 Text messaging is now the primary way that
teens reach their friends.
 It is more common than: face-to-face contact,
email, instant messaging and voice calling
 Voice calling is most common mode for
reaching parents
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

18. Intersection of Internet and cell phones
 Young people in low income households
are more likely to go online from their
cell 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 information
seeking

20. Health information seeking
 31% of 12-17 year olds go online to get
information about health, dieting, and fitness
 17% look for „sensitive‟ health topics
Vs
 62% who get news about current events /
politics
Data from September, 2009 as reported in “Teens and the internet: The future of digital
diversity”, 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 seekers
among 8-18 year olds
Data 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 the
Internet and text messaging are where
young 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 in
text messaging use (although income
may be)
 With web-enabled phones, the
distinction (and choice between) online
and 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 among
adolescents in alcohol abuse recovery (5R21AA017321)
 Mundt: depression screen via text messaging for clinicians and
other health professionals (1R43MH086152)
 Sullivan: using text messaging to collect monthly outcome data for
participants in an online HIV prevention program
(1RC1MD004370)
 Wu: use as a tool for ecological momentary assessment of
adolescents‟ drinking behavior (1R21DA024609)

27. Adherence
 Belzer : using cell phones as reminders
for adherence to HIV drugs among
adolescents (5U01HD040463)
 Jakicic: using text messages to promote
adherence to a behavioral intervention to
increase physical activity
(1U01HL096770)

28. Behavior change
 Bull: text messaging-based HIV prevention
program for Black and African American 16-20
year olds (5R21MH083318)
 Cornelius: using text messaging to deliver
‘boosters’ for an adolescent HIV prevention
program (5R21NR011021)
 Olsen: text messaging to promote physical
activity in adolescents (1R21HS018214)

29. Behavior change: Smoking cessation
 Bock: text messaging-smoking cessation for
those <35 years (1R21DA027142)
 Miller: text messaging-based program to prevent
smoking relapse post partum among low-income,
minority women who quit during their pregnancy
(1RC1CA145063)
 Ybarra: text messaging-smoking cessation for
young adults (1R21DA027142)
 Ybarra: text messaging-smoking cessation for
adults in Ankara, Turkey (5R01TW007918)

30. Take-aways
 Between 1/3 and 1/2 of young people use
technology to access health information
 Text messaging is increasingly common and
accessing the Internet via cell phones is
increasing

31. Take-aways
 Technologies can reach low income and
minority youth as well as more privileged
populations
 Opportunities exist both as a delivery mode of
behavior change content, as well as a data
collection tool (i.e., stand alone or adjunct to
other methods)

32. Thank you
Michele Ybarra MPH PhD
Internet Solutions for Kids, Inc.
Michele@IS4k.com
1 877 302 6858, ext. 801

33. Gaming

34. Daily gaming by age and time
21%
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 17
GuwM W1 (2006)
GuwM W2 (2007)
GuwM W3 (2008)

35. Daily gaming by race and time: GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
White Black / African
American
Mixed race All other
2006
2007
2008

36. Daily gaming by income and time:
GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
<$35,000 $35,000 - 74,999 >$75000
2006
2007
2008

37. Daily gaming by sex and time: GuwM
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Male Female
2006
2007
2008

38. Weekly texting use race and income
(2008): GuwM
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
<$35,000 $35,000 -
74,999
>$75000
White
Black / African American
Mixed race
All other