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Associations Between Parental Monitoring, Adolescent Disclosure, and Adolescent Risky Internet Behaviors Elizabeth Yale, M.A., Aaron Metzger, Ph.D., Amanda.

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Presentation on theme: "Associations Between Parental Monitoring, Adolescent Disclosure, and Adolescent Risky Internet Behaviors Elizabeth Yale, M.A., Aaron Metzger, Ph.D., Amanda."— Presentation transcript:

1 Associations Between Parental Monitoring, Adolescent Disclosure, and Adolescent Risky Internet Behaviors Elizabeth Yale, M.A., Aaron Metzger, Ph.D., Amanda Hanrahan Department of Psychology West Virginia University Life-Span Development Abstract Results Discussion MOTHER-REPORTED MEASURES Solicitation about internet/phone use: (7 items; =.90) Assessed frequency of mothers asking their teens about internet/phone behaviors (1 = Never to 5 = Always). Example: The types of text messages he/she sends on his/her cell phone? Family rules about internet/phone use: (4 items; =.78) Assessed the extent to which a family has rules about internet and phone use (1 = No rules to 5 = Firm, clear rules). Example: How long your is child allowed to be online? Covert monitoring of teens internet/phone use (4 items; =.70): Assessed whether parents utilized indirect strategies to gain information about their adolescents internet/phone behaviors. 1 = yes, 0 = no Example: Do you use social networking sites (such as FACEBOOK) to monitor your childs behavior? ADOLESCENT-REPORTED MEASURES Adolescent disclosure and secrecy about internet/phone use: 5 items assessed frequency of adolescents internet/phone disclosure (How often do you tell your parents about the following). 5 items assessed frequency of secrecy about internet/phone use (How often do you keep the following activities secret). 1 = Never to 5 = Always Example: The types of pictures and comments you put on your social networking site? Risky internet behaviors: (6 items; =.75) Measured the frequency of adolescents engagement in risky internet/phone behaviors (0, 1, 2-3, 4-5, 7-10, 11+ times) Example: How often in the last 30 days have you text/sexted sexual messages? Cyberbullying behaviors and cyber victimization: 5 items ( =.72) assessed frequency of engagement in cyberbullying behaviors. 7 items ( =.89) assessed frequency of cyber victimization. Table 1. Regression table for prediction of adolescent risky internet/phone behaviors Note. R 2* = adjusted R; Betas are from the final step of the regression; Non-significant 2-way interactions from the final model were excluded from the table; * p <.05; ** p <.01 Increased internet and cell phone use put adolescents at risk for: cyber bullying/victimization (Ybarra et al., 2011). other risky internet behaviors (e.g., sending sexually explicit text messages ( Ybarra et al., 2011 ). Factors which may protect against internet risks: Parent-adolescent communication Parental behavioral control strategies Parents knowledge of teens whereabouts and activities is consistently linked with positive outcomes ( Kerr et al., 2010). Parents engage in monitoring strategies to gain information including solicitation, as well as indirect approaches such as checking teens personal items (Crouter & Head, 2002). Adolescent disclosure most consistently predicts knowledge, and positive outcomes (Cumsille et al., 2010; Kerr et al., 2010). Less research has considered computer and cell phone specific family processes: Mothers internet and cell phone specific monitoring strategies Rules about internet/phone use Solicitation, or asking, about internet/phone use Covert monitoring (e.g. reading teens emails) Teens internet/cell phone specific information management Disclosure – freely sharing about internet/phone use Secrecy – actively keeping internet/phone use a secret The present study used a multi-informant (mothers and teens) approach to assess associations between: Mothers internet/phone specific information gathering strategies (rules, solicitation, covert). Teens internet/phone specific information management strategies (disclosure, secrecy). Teens internet risks, including engagement in cyberbullying, cyber victimization, and risky internet behaviors. Risky internet behaviors were significantly associated with: Adolescent disclosure about internet behaviors Mothers covert internet monitoring for girls but not boys Increased mothers covert monitoring was associated with increased risky internet behavior for girls, not boys (girls: B =.09, SE =.05, p =.04). Parent and adolescent communication about internet and cell phone behaviors: Associated with reduced risky internet behaviors, but unrelated to cyberbullying or victimization. Adolescents who discuss what they are doing online with their parents may engage in fewer risky internet behaviors (sexting, talking to strangers online). Mothers sneaky internet monitoring may lead to more risky behaviors, especially for girls. Mothers could be reacting to girls risky internet behaviors. Teen girls may feel that their privacy has been violated and react to parents sneaky monitoring. Increased cell phone use (but not internet use) was associated with increased internet risks, including cyberbullying, cyber victimization and risky internet behavior. The mobile nature of cellular phones may limit adults ability to traditionally monitor teens usage, and increase teens vulnerability. Parents may play a protective role by encouraging teens to discuss their internet behaviors, rather than setting rules about internet use, or tracking the websites teens are visiting. Future research should examine potential indirect effects of parenting on internet risks, including the facilitation of adolescent disclosure from parents open communication, less strict rules, and relationship quality. PARTICIPANTS 141 mother-adolescent dyads from Mid-Atlantic towns. Adolescents M age = 14.38, SD = 1.72; 80% Caucasian/White 60% female Mothers M age = 43.48, SD = 6.78; 80% Caucasian/White 93.6% Birth Mothers Are there associations between mothers internet monitoring strategies (solicitation, rules, covert) and youth internet risks? Do these associations vary as a function of age or gender? Are there associations between adolescent-initiated processes, internet disclosure and secrecy, and adolescents internet risks? Do these associations vary as a function of age or gender? References Background Study Questions Methods Figure 1. Mothers covert monitoring and adolescents risky internet/phone by gender Adolescent Risky Internet/Phone R 2* F Change Beta Step 1.2311.57** Age.23** Gender -.04 Internet Use -.04 Cell Phone Use.39** Step 2.26 1.97 Teen Disclosure -.23** Teen Secrecy.06 Mother Internet Rules.08 Mother Internet Solicitation.02 Mother Internet Covert Monitoring -.16 Step 3.284.13* Mother Covert X Teen Gender.24* For more information contact: Elizabeth Yale (eyale@mix.wvu.edu), or Aaron Metzger (Aaron.Metzger@mail.wvu.edu ) For more information about our research lab scan the code below with your mobile device. Crouter, A. C., & Head, M. R. (2002). Parental monitoring and knowledge of children. In M. H. Bornstein (Ed.), Handbook of Parenting: Vol. 3. Being and Becoming a Parent (pp.461-483). Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers. Cumsille, P., Darling, N., & Martinez, M. L. (2010). Shading the truth: Adolescents decisions to avoid issues, disclose, or lie to parents. Journal of Adolescence, 33, 285-296. doi: 10.1016/j.adolescence.2009.10.008 Kerr, M., Stattin, H., & Burk, W. J. (2010). A reinterpretation of parental monitoring in longitudinal perspective. Journal of Research on Adolescence, 20(1), 39-64. doi: 10.1111/j.1532-7795.2009.00623.x Ybarra, M. L., Mitchell, K. J., & Korchmaros, J. D. (2011). National trends in exposure to and experiences of violence on the Internet among children. Pediatrics, 128, e1376-e1386. doi: 10.1542/peds.2011-0118 Results Three regressions predicted cyberbullying behaviors, cyber victimization, and risky internet behaviors. Models controlled for teen age, sex, internet use, and cellphone use. Age ( β =.18, p =.03) and time spent on a cell phone ( β =.35, p <.001) predicted engagement in cyberbullying behaviors. Gender ( β =.18, p =.03) and time spent on a cell phone ( β =.27, p <.01) predicted cyber victimization.


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