Self Regulation and Online Sexual Behavior Among University Students

Norsimah Dasan; Mohd Mahadzir Rahimi Mohamed Nawi; Mohamad Nazri Ismail

doi:10.47405/mjssh.v5i12.568

Norsimah Dasan Universiti Malaysia Sabah (UMS)
Mohd Mahadzir Rahimi Mohamed Nawi Mara Vocational Institute
Mohamad Nazri Ismail Mara Vocational Institute

DOI: https://doi.org/10.47405/mjssh.v5i12.568

Keywords: online sexual behavior, self-regulation, internet, university students, gender

Abstract

The urge of information communication technology development stimulates university students with various sexual-oriented materials and can lead them into premarital relationship. Self regulation believed as one of the factors that help an individual to control themselves and plan action to avoid online sexual behaviour. Therefore, this research is meant to determine the level of self regulation and online sexual behaviour, the difference of self regulation and online sexual behaviour based on gender, and the relationship of self regulation and online sexual among university students. The sample involved was 882 students selected using simple random sampling. Data analyses was conducted using SPSS 25.0 software. Descriptive analyses show an average level of self regulation, while online sexual behaviour was found at low level. Inference analyses using t-test indicates differences between online sexual behaviour between male and female students, while no significant differences in self regulations based on gender. Pearson correlation analyses founded that; self regulation has a significance relationship with online sexual behaviour among university students. The results of this research give input to students and university to improve student self regulation and develop rules that can control online sexual behaviour.

Downloads

Download data is not yet available.

References

Bandura. (1991). Social Cognitive Theory of Self-Regulation. In Organizational Behavior And Decision Processes, 50, 248–287.

Bandura. (1986). Social foundations of thought and action: A Social Cognitive Theory. New Jersey: Prentice Hall

Bandura, A. (1994). Social Cognitive Theory and Exercise of Control Over HIV Infection. In R. J. Diclemente & J. L. Peterson (Eds.), Preventing AIDS: Theories and methods of behavioral interventions (pp. 25 - 59). New York: Plenum.

Baumeister, R. F., & Heatherton, T. F. (1996). Self-Regulation Failure: An Overview. Taylor and Francis Ltd. Psychological Inquiry, 7(1), 1-15

Baumeister, R. F. (2005). The Cultural Animal: Human Nature, Meaning, and Social Life. New York: Oxford University Press

Busse, P., Fishbein, M., Bleakly, A., Hennessy, M. (2010). The role of communication with friends and sexual initiation. PubMed, 37(2), 239–255

Cohen, M. & Morrison. (2008). Research Method in Education(6th edition). Madison Avenue. New York: Routledge

Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New Jersey: Lawrence Erlbaum

Di Clemente R. J., Crittenden C. P., Eve Rose, Sales J. M., Wingood G. M., Crosby R. A, Salazar L. F. (2008). Psychosocial predictors of HIV-associated sexual behaviors and the efficacy of prevention inteervention in adolescent at risk for infection: What works and what doesn't work?. Psychosomatic Medicine. American Psycosomatic Society, 70, 598-675.

DiClemente R. J., Wingood G. M., Crosby R. A., Sionean C., Cobb, B. K., Harrington K., Davies S. L., Hook III . E. W., Oh M. K. (2001). Parental monitoring and its association with a spectrum of adolescent health risk behaviors. Pediatrics,107, 1368-8

Doring, N., Danabeck, K., Shaughnessy, K., Grov, C., Byers, E.S. (2015). Online sexual activity experiences among college students: A four country comparison. Archive Sexual Behavior, 1-12

Hald G, N.M. Malamuth. (2008). Self-perceived effects of pornography consumption. Archives of Sexual Behavior, 37, 614-625,

Hosseini-Kamkar, Niki., & Morton, J.B. Sed differences in self-regulation: an evolutionary perspective. Journal of Front Neuroscience, 8, 233.

Kraus, S. W., Rosenberg, H., & Tompsett, C. J. (2015). Assessment of self-efficacy to employ self –initiated pornography use-reduction strategies. Journal Addictive Behaviors, 40, 115-118.

Krejcie, R. V., & Morgan, D.W. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30, 607-610

Moilanen, K. L. (2005). Parenting and sel-regulation in adolescene. Associations with adolescent behavior. Nebraska: Univeristy of Nebraska.

Moilanen, K. L. (2007). The Adolescent Self-Regulatory Inventory: The development and validation of a questionnaire of short-term and long-term self-regulation. Journal of Youth and Adolescence, 36, 835-848.

Stulhofer, A., Busko, V., & Landripet, I. (2010). Pornography,sexualsocial- ization,and satisfaction among youngmen.ArchivesofSexualBehavior, 39, 168–178.