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Youth perpetration of online sexual solicitation:
Internet use and psychosocial characteristics
Kimberly J. Mitchell, PhD
Crimes against Children Research Center
University of New Hampshire
Michele L. Ybarra, MPH, PhD
Center for Innovative Public Health Research
International Family Violence and Child
Victimization Research Conference, July 8-10 2007
Portsmouth, New Hampshire
* Thank you for your interest in this presentation.  Analyses included
herein are preliminary. More recent, finalized analyses can be found in:
Ybarra ML, Espelage DL, Mitchell KJ. The co-occurrence of Internet
harassment and unwanted sexual solicitation victimization and
perpetration: associations with psychosocial indicators. J Adolesc Health.
2007;41(6 Suppl 1):S31-41.
Background
 An estimated 97% of youth use the Internet
(Lenhart, Madden & Hitlin, 2005; USC Annenberg School Center for the
Digital Future, 2005).
 The majority of adolescent Internet-health research
has focused on victimization (e.g., Finkelhor, Mitchell,
Wolak, 2000; Wolak, Mitchell, Finkelhor, 2006; Ybarra, Mitchell, Wolak,
Finkelhor, 2006) and health seeking behavior (e.g., Grey,
Klein, Noyce et al., 2005; Ybarra & Suman, 2006).
Background: The positive
side of the Internet
 About one in four adolescents have used the
Internet to look for health information in the last
year (Lenhart et al., 2001; Rideout et al., 2001; Ybarra & Suman, 2006).
 41% of adolescents indicate having changed their
behavior because of information they found online
(Kaiser Family Foundation, 2002), and 14% have sought
healthcare services as a result (Rideout, 2001).
Background: The negative
side of the Internet
 Internet harassment has increased from 6% to
9%, while unwanted sexual solicitation decreased
from 19% to 13% from 1999 to 2005 (Mitchell, Wolak,
Finkelhor, 2006).
 Just over one-third of youth targeted by Internet
victimization report feeling very/extremely upset or
afraid because of the incident (Wolak, Mitchell, Finkelhor,
2006; Ybarra, Mitchell, Wolak, Finkelhor, 2006)
Problem Statement
Despite recent research which has highlighted
the impact negative interpersonal experiences
some young people are having online (e.g.,
unwanted sexual solicitation, harassment), little
has been reported about the ways in which
youth are using the Internet to act out.
Panel Presentations
 Describe the Growing up with Media (GuwM) study
 Use GuwM data to examine:
 Instigation of unwanted sexual solicitation;
 Intentional exposure to pornography online –
especially violent content; and
 Intentional access to violent web sites.
GuwM Methodology
 Conducted between August 24 to September 14,
2006
 Participants recruited from Harris Poll On Line
 1,591 households (one caregiver, one child) were
surveyed online
Harris Poll On Line
 HPOL is a double opt-in panel of millions of
respondents.
 HPOL data are consistently comparable to
data that has been obtained from random
telephone samples of general populations
when sampling and weighting is applied.
GuwM Eligibility
 ADULT
 Be a US resident member of the Harris Poll Online
(HPOL) opt-in panel
 Be the most (or equally) knowledgeable of the
youth’s media use in the home
 English speaking
 YOUTH
 Aged 10-15 years
 Use the Internet at least once in the last 6 months
 English speaking
GuwM Data Methods
 Sample selection was stratified based on youth age
and sex.
 Sample was also stratified between “novice” and
“experienced” survey participants.
GuwM Data Methods
 To control the sample and the increase response
rate, the following steps were taken:
 Password-protected access to the online survey
 1 reminder invitation to non-responders
 Cash incentives ($10 for adults, $15 for youth)
 On average, the adult survey took 5 minutes and
the youth survey took 21 minutes
Growing up with Media
Data Analyses
 Response rate was 26% (rates can range from
5-50%)
 Propensity scoring was applied to adjust for the
adult’s (i.e., recruitment target) propensity to be
online
 Data were weighted to match the US
population of adults with children between the
ages of 10 and 15 years
Growing up with Media
Data Analyses
 For analyses, cases were required to have
valid data for 85% of variables examined.
 Regression estimates are adjusted for
‘dishonesty’ (6%) and the report of someone in
the room near enough to see the computer
screen (22%).
Youth Demographic
Characteristics
 48% Female
 Mean age: 12.6 years (SE: 0.05)
 71% White, 13% Black, 9% Mixed, 7% Other
 19% Hispanic
 Median household income: $50,000-$74,999
 Median time spent online on a typical day: 31
minutes – 1 hour
Kimberly J. Mitchell, PhD
Crimes against Children Research Center
Family Research Lab
University of New Hampshire
Michele L. Ybarra, MPH, PhD
Internet Solutions for Kids, Inc.
Ybarra ML, Espelage DL, Mitchell KJ. The co-occurrence of Internet harassment and unwanted sexual
solicitation victimization and perpetration: associations with psychosocial indicators. J Adolesc Health.
2007 Dec;41(6 Suppl 1):S31-41.
Background
 Adolescent sexual aggression
 5% of adolescent males and 1% of adolescent
females ever engaged in sexual violence
perpetration.
 Correlates include:
 Nonsexual deviance (e.g., starting fights)
 Alcohol and drug use
 Sexist attitudes
 Anger
 History of sexual abuse
Background
 Online sexual solicitation
 13% of youth (10-17 y.o.) Internet users
reported an unwanted online sexual solicitation
in the past year (1 in 7).
 70% girls and 30% boys
 81% ages 14 or older
 4% received an aggressive sexual solicitation
 14% of solicitations from offline friends and
acquaintances
Research questions
 What is the national 1-year prevalence of youth
engaging in technology-based sexual
solicitation?
 What are key risk markers for engaging in
technology-based sexual solicitation?
Definition
 Technology-based sexual solicitation
 Trying to get someone else to talk about sex
online when they did not want to
 Asking someone online for sexual information
about themselves when that person did not
want to tell
 (really personal questions, like what his or her
body looks like, or sexual things he or she has
done)
Definition
 Technology-based sexual solicitation
 Asking someone to do something sexual online
when the other person did not want to
 Sending a text message that was sexual in any
way when that person did not want to receive it
 Sending a picture text message that was sexual
in any way when that person did not want to
receive it
Other variables
 Offline sexual aggression
 Exposure to sexual material
 Internet use characteristics State-Trait Anger
Expression Inventory
 Caregiver-child relationship
 Exposure to violence
 Substance use
 Demographic characteristics
Statistical methods
 Chi-square: bivariate differences in
characteristics between solicitors and non-
solicitors
 Logistic regression: parsimonious model
identifying key risk markers for engaging in
sexual solicitation perpetration
Results
 4% (n = 58) of adolescents said they had
sexually solicited someone through the Internet
or text messaging at least once in the last year.
Demographic
characteristics
Characteristic Solicitors Non-
solicitors
P value
Youth age (mean) 13.53 12.59 .000
Female 47% 48% .94
Household education 53% 36% .008
Household income 15% 12% .47
Parent unemployed 5% 5% .90
White race 73% 72% .84
Hispanic ethnicity 15% 18% .54
Internet use
characteristics
Characteristic Solicitors Non-
solicitors
P value
Frequency: 7+ days/week 65% 34% .003
Intensity: 2+ hours/day 47% 20% .001
Instant messaging 52% 22% .001
Chat rooms 12% 3% .002
Social networking sites 41% 16% .001
Internet in bedroom 42% 33% .33
Substance use
Characteristic Solicitors Non-
solicitors
P value
Alcohol 66% 11% .000
Marijuana 41% 4% .000
Inhalants 24% 1% .000
All other drugs 17% 1% .000
Online Victimization
Characteristic Solicitors Non-
solicitors
P value
Any sexual solicitation 83% 13% .000
Asked to talk about sex 69% 9% .000
Asked for sexual info 78% 9% .000
Asked to do something
sexual
62% 5% .000
Received sexual text m. 20% 2% .000
Received sexual picture txt 21% 1% .000
Sexual aggression and
anger
Characteristic Solicitors Non-
solicitors
P value
Propensity for anger
(STAXI) – mean
21.28 18.73 .000
Offline sexual aggression 34% 1% .000
Exposure to sexual
material
Characteristic Solicitors Non-
solicitors
P value
Any X-rated material 86% 18% .000
X-rated movies 53% 9% .000
X-rated magazine 71% 11% .000
X-rated web site 58% 8% .000
Any sexually violent
material
41% 3% .000
Parent-child
relationship
Characteristic Solicitors Non-
solicitors
P value
Coercive discipline 5.92 5.45 .004
Emotional closeness 6.75 7.87 .000
Monitoring 7.34 9.18 .000
Key risk markers
(LR)
Characteristic Β SE OR
Household education .99 .43 2.7
Instant messaging 1.5 .44 4.5
Social networking sites 1.2 .44 3.4
Offline sexual aggression 1.4 .57 4.1
Parental monitoring -.35 .13 .70
Online sexual solicitation v 2.1 .45 8.3
Exposure to violence 1.3 .64 3.8
Exposure to pornography 1.9 .50 6.6
Conclusions
 Prevalence rates – equal for girls and boys
 Cycle of online sexual solicitation –
victimization and perpetration
 Online and offline sexual aggression
 Link with pornography

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Youth perpetration of online sexual solicitation: Internet use and psychosocial characteristics

  • 1. Youth perpetration of online sexual solicitation: Internet use and psychosocial characteristics Kimberly J. Mitchell, PhD Crimes against Children Research Center University of New Hampshire Michele L. Ybarra, MPH, PhD Center for Innovative Public Health Research International Family Violence and Child Victimization Research Conference, July 8-10 2007 Portsmouth, New Hampshire * Thank you for your interest in this presentation.  Analyses included herein are preliminary. More recent, finalized analyses can be found in: Ybarra ML, Espelage DL, Mitchell KJ. The co-occurrence of Internet harassment and unwanted sexual solicitation victimization and perpetration: associations with psychosocial indicators. J Adolesc Health. 2007;41(6 Suppl 1):S31-41.
  • 2. Background  An estimated 97% of youth use the Internet (Lenhart, Madden & Hitlin, 2005; USC Annenberg School Center for the Digital Future, 2005).  The majority of adolescent Internet-health research has focused on victimization (e.g., Finkelhor, Mitchell, Wolak, 2000; Wolak, Mitchell, Finkelhor, 2006; Ybarra, Mitchell, Wolak, Finkelhor, 2006) and health seeking behavior (e.g., Grey, Klein, Noyce et al., 2005; Ybarra & Suman, 2006).
  • 3. Background: The positive side of the Internet  About one in four adolescents have used the Internet to look for health information in the last year (Lenhart et al., 2001; Rideout et al., 2001; Ybarra & Suman, 2006).  41% of adolescents indicate having changed their behavior because of information they found online (Kaiser Family Foundation, 2002), and 14% have sought healthcare services as a result (Rideout, 2001).
  • 4. Background: The negative side of the Internet  Internet harassment has increased from 6% to 9%, while unwanted sexual solicitation decreased from 19% to 13% from 1999 to 2005 (Mitchell, Wolak, Finkelhor, 2006).  Just over one-third of youth targeted by Internet victimization report feeling very/extremely upset or afraid because of the incident (Wolak, Mitchell, Finkelhor, 2006; Ybarra, Mitchell, Wolak, Finkelhor, 2006)
  • 5. Problem Statement Despite recent research which has highlighted the impact negative interpersonal experiences some young people are having online (e.g., unwanted sexual solicitation, harassment), little has been reported about the ways in which youth are using the Internet to act out.
  • 6. Panel Presentations  Describe the Growing up with Media (GuwM) study  Use GuwM data to examine:  Instigation of unwanted sexual solicitation;  Intentional exposure to pornography online – especially violent content; and  Intentional access to violent web sites.
  • 7. GuwM Methodology  Conducted between August 24 to September 14, 2006  Participants recruited from Harris Poll On Line  1,591 households (one caregiver, one child) were surveyed online
  • 8. Harris Poll On Line  HPOL is a double opt-in panel of millions of respondents.  HPOL data are consistently comparable to data that has been obtained from random telephone samples of general populations when sampling and weighting is applied.
  • 9. GuwM Eligibility  ADULT  Be a US resident member of the Harris Poll Online (HPOL) opt-in panel  Be the most (or equally) knowledgeable of the youth’s media use in the home  English speaking  YOUTH  Aged 10-15 years  Use the Internet at least once in the last 6 months  English speaking
  • 10. GuwM Data Methods  Sample selection was stratified based on youth age and sex.  Sample was also stratified between “novice” and “experienced” survey participants.
  • 11. GuwM Data Methods  To control the sample and the increase response rate, the following steps were taken:  Password-protected access to the online survey  1 reminder invitation to non-responders  Cash incentives ($10 for adults, $15 for youth)  On average, the adult survey took 5 minutes and the youth survey took 21 minutes
  • 12. Growing up with Media Data Analyses  Response rate was 26% (rates can range from 5-50%)  Propensity scoring was applied to adjust for the adult’s (i.e., recruitment target) propensity to be online  Data were weighted to match the US population of adults with children between the ages of 10 and 15 years
  • 13. Growing up with Media Data Analyses  For analyses, cases were required to have valid data for 85% of variables examined.  Regression estimates are adjusted for ‘dishonesty’ (6%) and the report of someone in the room near enough to see the computer screen (22%).
  • 14. Youth Demographic Characteristics  48% Female  Mean age: 12.6 years (SE: 0.05)  71% White, 13% Black, 9% Mixed, 7% Other  19% Hispanic  Median household income: $50,000-$74,999  Median time spent online on a typical day: 31 minutes – 1 hour
  • 15. Kimberly J. Mitchell, PhD Crimes against Children Research Center Family Research Lab University of New Hampshire Michele L. Ybarra, MPH, PhD Internet Solutions for Kids, Inc. Ybarra ML, Espelage DL, Mitchell KJ. The co-occurrence of Internet harassment and unwanted sexual solicitation victimization and perpetration: associations with psychosocial indicators. J Adolesc Health. 2007 Dec;41(6 Suppl 1):S31-41.
  • 16. Background  Adolescent sexual aggression  5% of adolescent males and 1% of adolescent females ever engaged in sexual violence perpetration.  Correlates include:  Nonsexual deviance (e.g., starting fights)  Alcohol and drug use  Sexist attitudes  Anger  History of sexual abuse
  • 17. Background  Online sexual solicitation  13% of youth (10-17 y.o.) Internet users reported an unwanted online sexual solicitation in the past year (1 in 7).  70% girls and 30% boys  81% ages 14 or older  4% received an aggressive sexual solicitation  14% of solicitations from offline friends and acquaintances
  • 18. Research questions  What is the national 1-year prevalence of youth engaging in technology-based sexual solicitation?  What are key risk markers for engaging in technology-based sexual solicitation?
  • 19. Definition  Technology-based sexual solicitation  Trying to get someone else to talk about sex online when they did not want to  Asking someone online for sexual information about themselves when that person did not want to tell  (really personal questions, like what his or her body looks like, or sexual things he or she has done)
  • 20. Definition  Technology-based sexual solicitation  Asking someone to do something sexual online when the other person did not want to  Sending a text message that was sexual in any way when that person did not want to receive it  Sending a picture text message that was sexual in any way when that person did not want to receive it
  • 21. Other variables  Offline sexual aggression  Exposure to sexual material  Internet use characteristics State-Trait Anger Expression Inventory  Caregiver-child relationship  Exposure to violence  Substance use  Demographic characteristics
  • 22. Statistical methods  Chi-square: bivariate differences in characteristics between solicitors and non- solicitors  Logistic regression: parsimonious model identifying key risk markers for engaging in sexual solicitation perpetration
  • 23. Results  4% (n = 58) of adolescents said they had sexually solicited someone through the Internet or text messaging at least once in the last year.
  • 24. Demographic characteristics Characteristic Solicitors Non- solicitors P value Youth age (mean) 13.53 12.59 .000 Female 47% 48% .94 Household education 53% 36% .008 Household income 15% 12% .47 Parent unemployed 5% 5% .90 White race 73% 72% .84 Hispanic ethnicity 15% 18% .54
  • 25. Internet use characteristics Characteristic Solicitors Non- solicitors P value Frequency: 7+ days/week 65% 34% .003 Intensity: 2+ hours/day 47% 20% .001 Instant messaging 52% 22% .001 Chat rooms 12% 3% .002 Social networking sites 41% 16% .001 Internet in bedroom 42% 33% .33
  • 26. Substance use Characteristic Solicitors Non- solicitors P value Alcohol 66% 11% .000 Marijuana 41% 4% .000 Inhalants 24% 1% .000 All other drugs 17% 1% .000
  • 27. Online Victimization Characteristic Solicitors Non- solicitors P value Any sexual solicitation 83% 13% .000 Asked to talk about sex 69% 9% .000 Asked for sexual info 78% 9% .000 Asked to do something sexual 62% 5% .000 Received sexual text m. 20% 2% .000 Received sexual picture txt 21% 1% .000
  • 28. Sexual aggression and anger Characteristic Solicitors Non- solicitors P value Propensity for anger (STAXI) – mean 21.28 18.73 .000 Offline sexual aggression 34% 1% .000
  • 29. Exposure to sexual material Characteristic Solicitors Non- solicitors P value Any X-rated material 86% 18% .000 X-rated movies 53% 9% .000 X-rated magazine 71% 11% .000 X-rated web site 58% 8% .000 Any sexually violent material 41% 3% .000
  • 30. Parent-child relationship Characteristic Solicitors Non- solicitors P value Coercive discipline 5.92 5.45 .004 Emotional closeness 6.75 7.87 .000 Monitoring 7.34 9.18 .000
  • 31. Key risk markers (LR) Characteristic Β SE OR Household education .99 .43 2.7 Instant messaging 1.5 .44 4.5 Social networking sites 1.2 .44 3.4 Offline sexual aggression 1.4 .57 4.1 Parental monitoring -.35 .13 .70 Online sexual solicitation v 2.1 .45 8.3 Exposure to violence 1.3 .64 3.8 Exposure to pornography 1.9 .50 6.6
  • 32. Conclusions  Prevalence rates – equal for girls and boys  Cycle of online sexual solicitation – victimization and perpetration  Online and offline sexual aggression  Link with pornography

Notas do Editor

  1. Respondents are recruited through partner websites, emails with online partners, refer-a-friend, trade shows, client supplied lists of customers, TV advertisements, direct mail, telephone recruitment of targeted populations
  2. In general, panelists are invited to participate in surveys no more frequently than once every three weeks
  3. As the children were recruited from the adults who initially agreed to take the study, the sample selection bias is found primarily in the characteristics of adults who chose to take this survey. Hence, only adults were propensity weighted and the propensity weights that were generated for the adults were applied to the child. The propensity score was derived from key questions in the survey that examined the attitudes and behaviors of the respondents as well as the demographic questions.
  4. As the children were recruited from the adults who initially agreed to take the study, the sample selection bias is found primarily in the characteristics of adults who chose to take this survey. Hence, only adults were propensity weighted and the propensity weights that were generated for the adults were applied to the child. The propensity score was derived from key questions in the survey that examined the attitudes and behaviors of the respondents as well as the demographic questions.
  5. 28% report 31-1hour 24% report half hour or less 22% report 1-2 hours
  6. Sexual violence perpetration – forcing someone into a sexual act (Borowsky, Hogan, & Ireland, 1997) Further, adolescent perpetrators of unwanted sexual behavior are often also victims of unwanted sexual behavior (Bruijn, 2006)
  7. Sexual solicitation – requests to engage in sexual activities or sexual talk or give personal sexual information that were unwanted or, whether wanted or not, made by an adult. Aggressive sexual solicitation – sexual solicitations involving offline contact with the perpetrator through regular mail, by telephone, or in person or attempts or requests for offline contact.
  8. Last 12 months
  9. Last 12 months
  10. KIM, IS THERE ANY WAY TO DENOTE STATISTICAL SIGNFICANCE?