Cybergrooming - Risk factors, coping strategies and associations with cyberbullying

Cybergrooming –Risk factors, coping strategies and

associations with cyberbullyingDipl. Päd. Sebastian Wachs

International Conference on Cyberbullying, Paris, June 2012

Acknowledgment: Prof. Dr. K.D. Wolf

• Background

• Method

• Results

• Conclusions/Outlook

Overview



Background of the Study

Cybergrooming (CYBGR)

“Establishing a trust-based relationship betweenminors and usually adults using ICTs tosystematically solicit and exploit the minors forsexual purposes.” (Wachs, Wolf and Pan, in review)

Background


Research Questions

RQ2: Are cyberbullied students more likely to be

cybergroomed?


Background

RQ1: Which factors shape the risk to become

a victim of CYBGR?

RQ3: How students cope with CYBGR and

which strategy seems to be effective?

CyberbullyingCybergrooming


• Repetition

• Imbalance of power

• Intentional aggressive acts

• Use of ICTs

• Role Association?

• Social Relationship

Associations between CYBGR and CYBB

Background

Method


• Self-reports from 518 students

• 5th to 10th Grades (11-17 yr) from 4 German schools

• 49.0 % of the participants was male and

50.8 % was female; 0.2 % did not answer

• from a region with a high proportion of immigrant families, and a relatively poor urban economic situation.


Participants

Method

Procedure

• Online Survey

• Computer Assisted Personal Interview

• participants sat at a PC in

school computer rooms

and entered the answers


Method

‘A cybergroomer is a person who is at least 7 years older than you and who you know over a longer time exclusively through online communication. At the beginning, the cybergroomer seems to be interested in your daily life problems, but after a certain time s/he appears to be interested in sexual topics and in the exchange of sexual fantasies and/or nude material (pictures or video chats).’ Used Definition


Questionnaire

Method

‘How often did you have contact with a cybergroomer within the last twelve

month?’


Never Once a year

Once a month

Once a week

Several times a week

Once a week

Several times a week

Method

Questionnaire

Never Once a year

Once a month


Cyberbullying 4 Items each side

Never, Once or twice, Twice or thrice, About once a week orSeveral times a week

Coping Strategies

10 Items Yes, A little bit, Almost no, No

ICTs Usage and Access

access to PC or Internet at home, ownership of mobile phone or smartphone, amount of ICTs usage

Items for assessing (cyber-)bullying and coping strategies partly following the ‘Mobbing Questionnaire for students' (Jäger et al. 2007)

Method

Questionnaire

Results


21%79%

At least once a year Never

Results

Prevalence Rate Victims of CYBGR: 6.5 % (n=34)

10.4 %

4.3 %

1.9 %

4.6 %

once a year once a month

once a week several times a week


higher for girls (8.7% vs. 4.3%), t(514) = 3.28, p = .001.

lower for adolescents who are not willing to meet strangers (4.4% vs. 15.5%), t(514) = 4.91, p = <.001.

lower for adolescents who do not discuss problems with strangers (5.6% vs. 11.4%), t(514) = 3.93, p < .001.

Results

Prevalence rate for CYBGR is significantly…


Access to PC at home

Access to Internet at home

Ownership of mobile phone

Ownership of smartphone

Amount of internet usage Being cyberbullied

Gender

Migration background

Grade

Willingness to meet strangers

Willingness to discuss problems with strangers

RQ 1: Which factors shape the risk to be cybergroomed?

Results


F(3,512)=23.39,R2=0.12, p<.001.*p≤.05;**p≤.01;***p≤.001

Tab1:Model1(3predictors)betacoefficientsforstandardizedvariables

Coefficients

Estimate Std.Error

t-value

(Intercept)*** 1.43 0.041 34.49

Beingcybervictim*** 0.46 0.085 5.42Beingagirl*** 0.28 0.083 3.46

Notwillingtomeetstrangers*** -0.43 0.106 -4.10

*p≤.05;**p≤.01;***p≤.00195%confidenceinterval

Variable O.R. C.I.

Beingagirl*** 2.35 1.1–5.2

Beingcyberbullied*** 1.75 1.2–2.4

Notwillingtomeetstrangers*** 0.30 0.14–0.65

Results


RQ 2: Are cyberbullied students more likely to

be cybergroomed?

Tab. 2: Results of simple binary logistic regression for Model 1

Results

RQ 3: How students cope with cybergrooming?

The first three factors of variability summarise 62.1 %of the total inertia.

F(2,512)=60.71,p<.001, =0.19*p≤.05;**p≤.01;***p≤.001

Tab.4:Model2(5predictors)betacoefficients

Coefficients

Estimate Std.

Error

t

value

(Intercept) 1.430230.03734 38.305

Cognitive-techn.Coping*** 0.332230.075374.408

Beingagirl*** 0.326860.075144.350

Beingcyberbullied*** 0.325650.078124.168

Notwillingtomeetstrangers* -0.24815 0.09742 -2.547

AggressiveCoping*** -0.76518 0.07775 -9.841

Results



*p≤.05;**p≤.01;***p≤.00195%confidenceinterval

Tab.5:ResultsofsimplebinarylogisticregressionforModel2

Variable O.R. C.I.

Beingagirl*** 3.371.4–8.6

BeingCyberbullied*** 1.881.0–3.2

Cognitive-techn.Coping*** 1.480.8–2.4

Willingnesstomeetstrangers:No*** 0.39 0.2–0.9

AggressiveCoping*** 0.30 0.2–0.5

Results




Conclusions and Outlook on future research

Conclusion

• Identified risk factors: being a girl, willingness to meet strangers and being cyberbullied

• Coping strategies seem to make a difference:

–aggressive coping protects and

– technical-cognitive coping increases the risk


• Validated instruments with consistent definition, measuring and period of time

• Longitudinal studies (causality and directions)

• Special risk groups (LGBT and children with special needs) need more research attention

• Traditionally bullied, cyberbullied, cybergroomed?

Outlook future research


Thank you for your attention!

Dipl. Päd. Sebastian Wachs

Division Education and Socialisation

University of Bremen, Germany

[email protected]
