Your SlideShare is downloading. ×
  • Like
The benefits and potential risks that young people face online: A look at what the data say
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Now you can save presentations on your phone or tablet

Available for both IPhone and Android

Text the download link to your phone

Standard text messaging rates apply

The benefits and potential risks that young people face online: A look at what the data say

  • 36 views
Published

 

Published in Health & Medicine , Technology
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
36
On SlideShare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
3
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide
  • http://pewinternet.org/Reports/2011/P2PHealthcare.aspx
  • http://pewinternet.org/Reports/2011/P2PHealthcare.aspx
  • http://pewinternet.org/Reports/2010/Mobile-Health-2010.aspx
  • Finkelhor, Wolak and Mitchell noted an increase in reports of wanted exposure among youth 10-15 years of age (8% in 2000 and 13% in 2005). Note that the question was changed to add more ‘context’. Nonetheless, fewer youth report going to these sites on purpose than by accident. It might be more socially acceptable to report unwanted vs. wanted exposure; it also is possible that unwanted exposures are so frequent that youth who might otherwise be curious are exposed and do not want further exposure.
  • A quick aside: the Internet is not the most common exposure to x-rated material – including violent x-rated material
  • http://www.thenationalcampaign.org/sextech/PDF/SexTech_Summary.pdfhttp://www.pewinternet.org/~/media//Files/Reports/2009/PIP_Teens_and_Sexting.pdf
  • http://www.pewinternet.org/~/media//Files/Reports/2009/PIP_Teens_and_Sexting.pdf
  • http://www.pewinternet.org/~/media//Files/Reports/2009/PIP_Teens_and_Sexting.pdf
  • http://www.pewinternet.org/~/media//Files/Reports/2009/PIP_Teens_and_Sexting.pdf
  • Similarly, data from the Youth Internet Safety Surveys 1 and 2 (Finkelhor, Mitchell, Wolak) suggest that about one in three victims of harassment are very or extremely upset by the experience
  • As an aside, bullying is most common at school
  • As an aside, internet is the least distressing type of bullying
  • Youth Internet Safety Survey studies 1 and 2 also report that about one in three youth victims are very or extremely upset by the experience (Finkelhor, Wolak, Mitchell)
  • As an aside, USE happens just as frequently at school

Transcript

  • 1. 21st Annual Vancouver Island Child PsychologistsConferenceJune 1, 2012Victoria BCThe benefits and potential risks thatyoung people face online:A look at what the data sayMichele Ybarra MPH PhDCenter for Innovative Public Health Research* Thank you for your interest in this presentation. Please note this presentation is a morerecent version of the Emerging Technologies Conference presentation tilted “The dark side ofthe internet: Youth internet victimization”. Analyses included herein are preliminary. Morerecent, finalized analyses can be found in: Ybarra, M.L., Mitchell, K.J., & Korchmaros, J.D.(2011). National trends in exposure to and experiences of violence on the Internet amongchildren. Pediatrics,128(6),e1376-e1386.
  • 2. Roadmap Benefits of technology Risks of technology:◦ Exposures Violent content X-rated material “Sexting”◦ Experiences Bullying / harassment Unwanted sexual exposures Myths and truths about online risks
  • 3. Benefits of technologyAccess to health information: About one in four adolescents haveused the Internet to look for healthinformation in the last year (Lenhart et al.,2001; Rideout et al., 2001; Ybarra & Suman, 2006). 41% of adolescents indicate havingchanged their behavior because ofinformation they found online (Kaiser FamilyFoundation, 2002), and 14% have soughthealthcare services as a result (Rideout,2001).[Note: Recent data refute the claim that people are using theInternet to self-diagnose or self-medicate; the vast majority (70%)consult a health professional and 54% friends and families when
  • 4. Benefits of technologyTeaching healthy behaviors (as described by MyThai, Lownestein, Ching, Rejeski, 2009) Physical health: Dance DanceRevolution Healthy behaviors: Sesame Street‟sColor me Hungry (encourages eatingvegetables) Disease Management: Re-Mission(teaches children with cancer aboutthe disease)
  • 5. Benefits of technologySocial support for people with chronicdisease:One in four (23%) of people with highblood pressure, diabetes, heartconditions, lung conditions, cancer etchave gone online to connect withothers who also have the chronicdisease (Fox, 2011)
  • 6. Benefits of technologyCell phones seem to be playing a part inreducing the digital divide:Compared to 21% of white teens, 44% ofBlack and African American teens and35% of Hispanic teens go online throughtheir phones (Lenhart, Ling, Campbell, Purcell, 2010)With potential health implications:Black and African American adult cellphone owners are twice as likely asWhite adult cell phone owners to usemobile health applications (15% vs. 7%respectively; Fox, 2010)
  • 7. Growing up with MediasurveyThe data we will be discussing today largelycome from the Growing up with Media survey: Longitudinal design: Fielded 2006, 2007, 2008 Data collected online National sample (United States) Households randomly identified from the 4 million-member Harris Poll OnLine (HPOL) Sample selection was stratified based on youthage and sex. Data were weighted to match the US population ofadults with children between the ages of 10 and 15years and adjust for the propensity of adult to beonline and in the HPOL.
  • 8. Funding and CollaboratorsThe study was supported by Cooperative Agreementnumber U49/CE000206 from the Centers for DiseaseControl and Prevention (CDC).The contents of this presentation are solely theresponsibility of the authors and do not necessarilyrepresent the official views of the CDC.Collaborators who contributed to the planning andimplementation of the study included: Dr. Dana Markowfrom Harris Interactive; Drs. Philip Leaf and MarieDiener-West from the Johns Hopkins Bloomberg Schoolof Public Health; and Dr. Merle Hamburger from theCDC.
  • 9. Eligibility criteria Youth:◦ Between the ages of 10-15 years◦ Use the Internet at least once in the last 6 months◦ Live in the household at least 50% of the time◦ English speaking Adult:◦ Be a member of the Harris Poll Online (HPOL) opt-inpanel◦ Be a resident in the USA (HPOL has membersinternationally)◦ Be the most (or equally) knowledgeable of the youth‟smedia use in the home◦ English speaking
  • 10. Youth Demographic Characteristics2006(n=1,577)2007(n=1189)2008(n=1149)Female 50% 50% 51%Age (SE) 12.6 (0.05) 13.7 (0.05) 14.5 (0.05)Hispanic ethnicity 18% 17% 17%Race: White 70% 72% 72%Race: Black / AfricanAmerican15% 13% 14%Race: Mixed race 7% 9% 9%Race: Other 8% 6% 6%Household less than$35,00025% 24% 25%Internet use 1 hour+ perday47% 49% 52%
  • 11. Exposures:Violent content
  • 12. Percent of youth exposed toviolence online by website type3% 4%21%19%2% 3%22%16%3% 4%24%15%0%5%10%15%20%25%30%35%40%Hate sites Death sites War, terrorism Cartoons sitesWave1Wave2Ybarra, Mitchell, Korchmaros (under review)
  • 13. Odds of externalizing behaviorgiven exposure to violence online2.82.21.72.01.8 1.7 1.81.61.71.9 1.9 1.92.42.0 1.9 1.91.010.0Hate sites Death sites War, death, terrorismCartoons engaging in violenSeriously violent behaviorDelinquent behaviorOffline aggressionTechnology-based aggressionData from Growing up with Media survey, Waves 1-3 (PI: Ybarra). Population –based odds (GEE) of reporting externalizing behavior given report of exposure toviolence online. All odds ratios are statistically significant (p<0.001)
  • 14. Exposures:X-rated material
  • 15. Exposure to sexual material online 42% of 12-17 year olds in onenationally representative survey reportany exposure (wanted and unwanted)to x-rated material online (Wolak, Mitchell, &Finkelhor, 2007) 70% of 15-17 yr-old Internet users inanother nationally representativesurvey reported accidentally viewingpornography online “very” or“somewhat” often (Rideout, 2001)
  • 16. Percent of youth reportingunwanted exposure to x-ratedmaterial online25%34%0%5%10%15%20%25%30%35%40%2000 2005Note that unwanted may not necessarily mean unintentionalWolak, Mitchell, Finkelhor, 2006
  • 17. Challenges related to unwantedexposure 26% were very or extremely upset bythe images 26% were very or extremelyembarrassed 19% reported symptoms of extremestress (e.g., avoidance of thecomputer, obsessive thinking aboutthe event, feeling jumpy orirritable, loosing interest in thingsgenerally)
  • 18. Percent of youth reporting wantedexposure to x-rated material online8% 9% 11%1% 1%2%0%5%10%15%20%25%30%35%40%Wave 1 Wave 2 Wave 3Violent, x-rated websitesNon-violent x-rated websitesData from the Growing up with Media survey; PI: Ybarra
  • 19. Wanted exposure to nonviolent x-rated material online by age0%7% 7%5%1%4%8%16%13%15%0%5%10%15%20%25%30%35%40%10 11 12 13 14 15 16 17W1 non-violentW2 non-violentW3 non-violentData from the Growing up with Media survey; PI: Ybarra
  • 20. Wanted exposure to violent x-ratedmaterial online by age1% 2%0% 1%0% 1% 0% 0%2% 2%0%5%10%15%20%25%30%35%40%10 11 12 13 14 15 16 17W1 violentW2 violentW3 violentData from the Growing up with Media survey; PI: Ybarra
  • 21. Concurrent psychosocial problemsrelated to wanted exposure In a longitudinal study of Dutchyouth, exposure to sexually explicit Internetmaterial stimulated sexual preoccupancyamong adolescents 13-20- years old (Peter &Valkenburg, 2008). In a national study of 10-15 year olds(Ybarra, Mitchell, Hamburger, Diener-West, Leaf, 2010), intentional exposure to violentx-rated material online increased the oddsof self-reported sexually aggressivebehavior 8-fold. Exposure to non-violentx-rated material increased the odds of self-reported sexually aggressive behavior 2-fold.
  • 22. Percent of youth reporting wantedexposure to x-rated material online8% 10%7% 9%13%16%11% 10% 12%1%2%3% 1%0%3%2%1%2%0%5%10%15%20%25%30%35%40%ViolentNon-violentData from the Growing up with Media survey; PI: Ybarra
  • 23. Exposures (experiences?):“Sexting”
  • 24. DefinitionDefinitions vary but questions generallyrefer to the creation and distributionof photos or videos with a sexualovertone using technology (e.g., a cellphone, email, social networkingsite, etc).
  • 25. Involvement 20% of 13-19 year olds admit to sending/ posting a nude / nearly nude picture ofthemselves through technology(e.g., IM, SNS; The National Campaign to Prevent Teenand Unplanned Pregnancy, 2008); 9% of 13-18 yearolds admit to someone /posting via textmessage or email specifically, and 3%have forwarded one (Cox Communications, 2009) Between 17% (Cox Communications, 2009) and31% (The National Campaign to Prevent Teen andUnplanned Pregnancy, 2008) have received anude or semi-nude photo via technology
  • 26. InvolvementWhen text messaging is examined*specifically* 4% of 12-17 year olds admit tosending sexually suggestive nude ornearly nude photos or videos ofthemselves◦ Boys and girls are equally likely to send asexy picture◦ 17 year olds are more likely than allyounger ages to send a sexy picture 15% have received such a photo orimagehttp://www.pewinternet.org/~/media//Files/Reports/2009/PIP_Teens_and_Sexting.pdf
  • 27. MotivationFrom focus groups of teenagers, three reasons for „sexting‟emerge (Lenhart et al., 2010):1) Exchange between boyfriends / girlfriends2) Exchange between boyfriends / girlfriends thatare then shared with people outside of therelationship (e.g., break up; fight)3) Exchange between people not yet in arelationship but where at least one hopes toinitiate a relationship“These images are shared as a part of or instead of sexualactivity, or as a way of starting or maintaining a relationship witha significant other. And they are also passed along to friends fortheir entertainment value, as a joke or for fun.” – AmandaLenhart, Pew Internet & American Life Project
  • 28. Consequences Psychosocial impact largelyunknown Legal impact is being debated /determined through courtcases in several states (see Pewstudy for a review)
  • 29. Experiences:Internet harassmentandBullying
  • 30. DefinitionThere is wide variability in thedefinition of harassment andbullying. Generally, it refers toan act of intentional aggression(e.g., “mean things”) towardssomeone else via technology(i.e., Internet, cell phone textmessaging)
  • 31. Context Girl, 12: “These people from school werecalling me a prostitute and whore … andsaying I was raped. [It happened] because I‟man easy target. I didn‟t let it bother me untilabout a month ago and [then] I started gettingphysical with people.” Boy, 15: “I was playing a first person shootergame and unintentionally offended this personwho became very serious and began tothreaten me by saying if this was real life hewould physically harm me. [It happenedbecause he] was unable to accept this was justa game.”-Quotes from participants of the Youth Internet Safety Survey -2(Finkelhor, Wolak, Mitchell, 2005)
  • 32. Overlap between victimization andperpetrationNot involved62%Victim-only18%Perpetrator-only3%Perpetrator-victim17%Internet harassmentAverage across Waves 1-3 of the Growing up with Media study (PI: Ybarra)
  • 33. InvolvementDepending on the measureused, most studies reportbetween 20-40% of youth aretargeted by bullying orharassment online and via textmessaging (see Tokunaga, 2010 for a review).
  • 34. Overlap between harassment andbullyingNot involved62%Cyberbully-only victim1%Internetharassment-only victim24%Cyberbully +Internetharassmentvictim13%Average across Waves 2-3 of the Growing up with Media study (PI: Ybarra)(Cyberbully questions were added in Wave 2)
  • 35. Cyberbully victimization by ageacross timeData from the Growing up with Media study, PI: Ybarra(Cyberbully questions were added in Wave 2)7%8%12% 12%14%18%8%10%18%14%18% 17%0%5%10%15%20%25%30%35%40%11 12 13 14 15 16 17Wave 2 (34%)Wave 3 (39%)
  • 36. Internet harassment victimizationby age across timeData from the Growing up with Media study, PI: Ybarra11%18%26%39%50% 49%22%26% 26%37%48%44%24%34%43% 43%46% 45%0%10%20%30%40%50%10 11 12 13 14 15 16 17Wave 1 (33%)Wave 2 (34%)Wave 3 (39%)
  • 37. Text messaging harassmentvictimization by age across timeData from the Growing up with Media study, PI: Ybarra(Text messaging-based harassment questions were added in Wave 2)6%15% 15%11%15%23%9%16%25%31% 30%0%5%10%15%20%25%30%35%40%11 12 13 14 15 16 17Wave 2 (14%)Wave 3 (24%)
  • 38. Distressing cyberbullyingvictimizationData from Wave 3 of the Growing up with Media study, PI: YbarraNotvictimized86%Victim-notdistressed12%Victim -distressed2%Cyberbullying
  • 39. Distressing Internet harassmentvictimization (age constant:12-15y.o.)17%31%28%18%27%21%19%22%18%0%5%10%15%20%25%30%35%40%Rude / meancommentsRumors Threatening /aggressivecomments200620072008Distress = very or extremely upset by the experienceData from the Growing up with Media study, PI: Ybarra
  • 40. Distressing Internet harassmentvictimization (age constant:12-15y.o.)86%80%10%16%4% 4%0%10%20%30%40%50%60%70%80%90%100%Wave 2 Wave 3Harassed + upsetHarassed, not upsetNot harassedData from Waves 2 and 3 of the Growing up with Media study, PI: Ybarra
  • 41. Bullying victimization rates byenvironment1%4% 3%22%0% 0%2%12%0% 1% 2%10%1% 2% 1%8%1% 2% 2%11%0%5%10%15%20%25%30%35%40%Every day /almost everydayOnce or twice aweekOnce or twice amonthLess oftenSchoolInternetText messagingData from the Growing up with Media study, PI: Ybarra
  • 42. Distress related to bullyingvictimization rates by environment38%15%32%39%37%0%5%10%15%20%25%30%35%40%Very/extremely upset by most memorable experienceSchoolInternetText messagingData from the Growing up with Media study, PI: Ybarra
  • 43. Cyberbully perpetration by ageacross timeData from the Growing up with Media study, PI: Ybarra6%11%16%21%31%36%6%12%19%22%29%22%9%18%30%25%27%29%0%5%10%15%20%25%30%35%40%10 11 12 13 14 15 16 17Wave 1 (21%)Wave 2 (19%)Wave 3 (23%)
  • 44. Text messaging harassmentperpetration by age across timeData from the Growing up with Media study, PI: Ybarra(Text messaging-based harassment questions were added in Wave 2)28%8%12%8%11%18%6%16% 15%21%16%0%5%10%15%20%25%30%35%40%11 12 13 14 15 16 17Wave 2 (10%)Wave 3 (16%)
  • 45. Experiences:Unwanted sexualsolicitation(unwanted sexualencounters)
  • 46. DefinitionIt usually refers to the following:Being asked to do somethingsexual when you don‟t want toBeing asked to share personalsexual information when you don‟twant toBeing asked to talk about sex whenyou don‟t want toIt does not necessarily mean thatyouth are being solicited for sex.
  • 47. Context Girl, 14: “I was chatting on the Internet andthis guy just popped up in an InstantMessage and started talking really dirty tome and saying things that I had neverheard of before. He told me he was 30years old and then he said, „LOL‟ (laugh outloud).” Boy, 11, who was playing an online gamewith a man, 20: “He asked me somethingpersonal, something about a man‟sprivates.”-Quotes from participants of the Youth Internet Safety Survey-2 (Finkelhor, Wolak, Mitchell, 2005)
  • 48. Overlap between victimization andperpetrationAverage across Waves 1-3 from the Growing up with Media study (PI: Ybarra)Not involved84%Victim-only13%Perpetrator-only1%Perpetrator-victim2%Unwanted sexual encounters
  • 49. Unwanted sexual encountersvictimization by age across timeData from the Growing up with Media study, PI: Ybarra6% 6%11%17%22%24%5%14%18% 18%28%22%0%5%10%15%20%25%30%35%40%10 11 12 13 14 15 16 17Wave 1 (33%)Wave 2 (34%)Wave 3 (39%)
  • 50. Very / extremely upset by theencounter – age constant (12-15 y.o.)32% 32% 32%28%26%19%26%20%28%0%5%10%15%20%25%30%35%40%Talk about sex SexualinformationDo somethingsexual200620072008
  • 51. Unwanted sexual experiencesvictimization by environment0%2% 2%14%0% 1%3%13%0%5%10%15%20%25%30%35%40%Every day /almost everydayOnce ortwice a weekOnce ortwice amonthLess oftenSchoolInternetAverage from Waves 2-3 from the Growing up with Media study (PI: Ybarra)(Questions about unwanted sexual experiences at school were added at W2)
  • 52. Unwanted sexual encounterperpetration by age across timeData from the Growing up with Media study, PI: Ybarra1%3%0%2%5% 5%1% 1%4% 4% 4% 3%1%2%6%3% 3%4%0%5%10%15%20%25%30%35%40%10 11 12 13 14 15 16 17Wave 1 (3%)Wave 2 (3%)Wave 3 (3%)
  • 53. Concurrent psychosocial problemsfor victimsVictims of harassment, bullying, and unwantedsexual experiences online are more likely toalso report: Interpersonal victimization / bullying offline(Ybarra, Mitchell, Espelage, 2007;Ybarra, Mitchell, Wolak, Finkelhor, 2006; Ybarra, 2004) Alcohol use (Ybarra, Mitchell, Espelage, 2007) Social problems (Ybarra, Mitchell, Wolak, Finkelhor, 2006) Depressive symptomatology and suicidalideation (Ybarra, 2004; Mitchell, Finkelhor, Wolak, 2000; TheBerkman Center for Internet & Society, 2008; Hinduja & Patchin, inpress) School behavior problems (Ybarra, Diener-West, Leaf, 2007) Poor caregiver-child relationships (Ybarra, Diener-
  • 54. Concurrent psychosocial problemsfor perpetratorsPerpetrators of harassment, bullying, andunwanted sexual experiences online are morelikely to report: Interpersonal victimization and perpetration(bullying) offline (Ybarra, Mitchell, Espelage, 2007; Ybarra &Mitchell, 2007; Ybarra & Mitchell, 2004) Aggression / rule breaking(Ybarra, Mitchell, Espelage, 2007; Ybarra & Mitchell, 2007) Binge drinking (Ybarra, Mitchell, Espelage, 2007) Substance use (Ybarra, Mitchell, Espelage, 2007; Ybarra &Mitchell, 2007) Poor caregiver child relationship(Ybarra, Mitchell, Espelage, 2007; Ybarra & Mitchell, 2004; Ybarra &Mitchell, 2007) Low school commitment (Ybarra & Mitchell, 2004)
  • 55. Myths and truths aboutonline risks
  • 56. Assumptions about Internetvictimization experiencesIt‟s happening to everyoneIt‟s increasing over timeIt‟s getting nastier / kids aremore affectedThe Internet is doing it
  • 57. Research supporting and refutingassumptions about Internetvictimization Assumption: Victimization isincreasingRates of victimization appear to be holding steady(and maybe in some cases decreasing) from2006-2008 Assumption: Victimization is gettingnastierAt least as measured by rates of distress –victimization distress rates appear to be holdingsteady (and maybe in some cases decreasing)from 2006-2008
  • 58. Research supporting and refutingassumptions about Internetvictimization Assumption: Victims are alwaysinnocentThe interplay between victimization and perpetration cansometimes be complex. These data suggest that victimsare significantly more likely to also be perpetrators. It canbe a two-way street. Assumption: the Internet is doing itThe strong overlap between online and offline behaviors…and the fact that these kids are significantly more likelyto have additional psychosocial problemsSuggests that this is form of „old‟ behavior in a„new environment‟
  • 59. RecapVictimization from negative online experiencesand exposures is associated with psychologicaldistress and negative mental health outcomes forsome youth.The Internet is not the only medium throughwhich youth are having these experiences andexposures. It is important to understand howtechnology is changing the lives of youth; andalso to not forget that the Internet and cell phonesare just pieces of a larger puzzle that youth mustnavigate successfully every day.
  • 60. TakeawaysAs professionals we need to be able to sit withthese two “competing” realities: We need to raise awareness about theimpact that Internet victimization mayhave, including doing a better job ofidentifying youth negatively impacted andgetting them into services (e.g., therapy). We also need to recognize that:◦ The majority of youth are not beingvictimized online,◦ The majority who are, are not seriously upsetby it.
  • 61. Thank youMichele Ybarra MPH PhDCenter for Innovative PublicHealth ResearchMichele@InnovativePublicHealth.org1 877 302 6858, ext. 801