Online Routine Activities and Self-Guardianship against Cyber Abuse

References

• Allen, W. D. (2013). Self-protection against crime victimization: Theory and evidence from university campuses. International Review of Law and Economics, 34, 21–33. https://doi.org/10.1016/j.irle.2012.11.002
   Web of Science ®Google Scholar
• Alston-Knox, C. L. (2019). An intuitive guide to linear regression. Frequentist, Lasso, and Bayesian Variable selection using AutoStat. AutoStat Institute. https://autostat.com.au/resources
   Google Scholar
• Ando, T. (2010). Bayesian model selection and statistical modeling. Chapman and Hall.
   Google Scholar
• Baker, R., Blumberg, S. J., Brick, J. M., Couper, M. P., Courtright, M., Dennis, J. M., … Lavrakas, P. J. (2010). Research synthesis: AAPOR report on online panels. Public Opinion Quarterly, 74(4), 711–781. https://doi.org/10.1093/poq/nfq048
   Web of Science ®Google Scholar
• Baxter, K., Courage, C., & Caine, K. (2015). Understanding your users. A practical guide to user research methods (2nd ed.). Elsevier.
   Google Scholar
• Behrend, T. S., Sharek, D. J., Meade, A. W., & Wiebe, E. N. (2011). The viability of crowdsourcing for survey research. Behavior Research Methods, 43(3), 800–813. https://doi.org/10.3758/s13428-011-0081-0
   PubMed Web of Science ®Google Scholar
• Bocij, P. (2006). Cyberstalking: Harassment in the Internet age and how to protect your family. Praeger Publishers.
   Google Scholar
• Bosch, O. J., Revilla, M., DeCastellarnau, A., & Weber, W. (2019). Measurement reliability, validity, and quality of slider versus radio button scales in an online probability-based panel in Norway. Social Science Computer Review, 37(1), 119–132. https://doi.org/10.1177/0894439317750089
   Web of Science ®Google Scholar
• Bossler, A. M., Holt, T. J., & May, D. C. (2012). Predicting online harassment victimization among a juvenile population. Youth & Society, 44(4), 500–523. https://doi.org/10.1177/0044118X11407525
   Web of Science ®Google Scholar
• Broidy, L. (2001). A test of general strain theory. Criminology, 39(1), 9–35. https://doi.org/10.1111/j.1745-9125.2001.tb00915.x
   Web of Science ®Google Scholar
• Casler, K., Bickel, L., & Hackett, E. (2013). Separate but equal? A comparison of participants and data gathered via Amazon’s MTurk, social media, and face-to-face behavioral testing. Computers in Human Behavior, 29(6), 2156–2160. https://doi.org/10.1016/j.chb.2013.05.009
   Web of Science ®Google Scholar
• Chang, L. C., & Krosnick, J. A. (2009). National surveys via RDD telephone interviewing versus the Internet: Comparing sample representativeness and response quality. Public Opinion Quarterly, 73(4), 641–678. https://doi.org/10.1093/poq/nfp075
   Web of Science ®Google Scholar
• Clarke, R. V., & Eck, J. E. (2003). Become a problem-solving crime analyst: In 55 small steps. Jill Dando Institute of Crime Science, UCL.
   Google Scholar
• Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44(4), 588–608. https://doi.org/10.2307/2094589
   Web of Science ®Google Scholar
• Cohen, L. E., Kluegel, J. R., & Land, K. C. (1981). Social inequality and predatory criminal victimization: An exposition and test of a formal theory. American Sociological Review, 46(5), 505–524. https://doi.org/10.2307/2094935
   Web of Science ®Google Scholar
• Cook, P. J. (1986). The demand and supply of criminal opportunities. Crime and Justice, 7, 1–27. https://doi.org/10.1086/449111
   Web of Science ®Google Scholar
• Costello, M., Hawdon, J., & Ratliff, T. N. (2017). Confronting online extremism: The effect of self-help, collective efficacy, and guardianship on being a target for hate speech. Social Science Computer Review, 35(5), 587–605. https://doi.org/10.1177/0894439316666272
   Web of Science ®Google Scholar
• Crawley, S. E., & Pring, L. (2000). When did Mrs Thatcher resign? The effects of ageing on the dating of public events. Memory, 8(2), 111–121. https://doi.org/10.1080/096582100387650
   PubMed Web of Science ®Google Scholar
• Difallah, D., Filatova, E., & Ipeirotis, P. (2018). Demographics and dynamics of Mechanical Turk workers. In Proceedings of the eleventh ACM international conference on web search and data mining (p. 135–143). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3159652.3159661
   Google Scholar
• Dressel, J., & Farid, H. (2018). The accuracy, fairness, and limits of predicting recidivism. Science Advances, 4(1). https://doi.org/10.1126/sciadv.aao5580
   Web of Science ®Google Scholar
• Eck, J. E., & Madensen, T. D. (2015). Meaningfully and artfully reinterpreting crime for useful science: An essay on the value of building with simple theory. In M. A. Andersen & G. Farrell (Eds.), The Criminal Act: The role and influence of routine activity theory (pp. 5–18). Palgrave Macmillan.
   Google Scholar
• Felson, M. (1995). Those who discourage crime. In J. E. Eck & D. Weisburd (Eds.), Crime and place (pp. 53–66). Criminal Justice Press.
   Google Scholar
• Fissel, E. R. (2018). The reporting and help-seeking behaviours of cyberstalking victims. Journal of Interpersonal Violence, 36(11–12), 5075–5100. https://doi.org/10.1177/0886260518801942.
   PubMedGoogle Scholar
• Garofalo, J., & Clark, D. (1992). Guardianship and residential burglary. Justice Quarterly, 9(3), 443–463. https://doi.org/10.1080/07418829200091471
   Google Scholar
• Garofalo, J. (1979). Victimization and the fear of crime. Journal of Research in Crime and Delinquency, 16(1), 80–97. https://doi.org/10.1177/002242787901600107
   Web of Science ®Google Scholar
• Giblin, M. J. (2008). Examining personal security and avoidance measures in a 12-city sample. Journal of Research in Crime and Delinquency, 45(4), 359–379. https://doi.org/10.1177/0022427808322610
   Web of Science ®Google Scholar
• Gottfredson, M. R., & Gottfredson, D. M. (1988). Decision making in criminal justice: Toward the rational exercise of discretion (2nd ed.). Plenum.
   Google Scholar
• Gottlieb, A. (2017). The effect of message frames on public attitudes toward criminal justice reform for nonviolent offenses. Crime & Delinquency, 63(5), 636–656. https://doi.org/10.1177/0011128716687758
   Web of Science ®Google Scholar
• Hawdon, J., Costello, M., Ratliff, T., Hall, L., & Middleton, J. (2017). Conflict management styles and cybervictimization: Extending routine activity theory. Sociological Spectrum, 37(4), 250–266. https://doi.org/10.1080/02732173.2017.1334608
   Web of Science ®Google Scholar
• Hindelang, M. J., Gottfredson, M. R., & Garofalo, J. (1978). Victims of personal crime: An empirical foundation for a theory of personal victimization. Ballinger.
   Google Scholar
• Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. (1999). Bayesian model averaging: A tutorial. Statistical Science, 14(4), 382–401. https://www.stat.colostate.edu/~jah/papers/statsci.pdf.
   Web of Science ®Google Scholar
• Hollis, M., Felson, M., & Welsh, B. (2013). The capable guardian in routine activities theory: A theoretical and conceptual reappraisal. Crime Prevention and Community Safety, 15(1), 65–79. https://doi.org/10.1057/cpcs.2012.14
   Google Scholar
• Holt, T. J., & Bossler, A. M. (2008). Examining the applicability of lifestyle-routine activities theory for cybercrime victimization. Deviant Behaviour, 30(1), 1–25. https://doi.org/10.1080/01639620701876577
   Web of Science ®Google Scholar
• Jewkes, Y. (2010). Public policing and Internet crime. In Y. Jewkes & M. Yar (Eds.), Handbook of Internet Crime (pp. 525–545). Willan.
   Google Scholar
• Kreuter, F., Presser, S., & Tourangeau, R. (2008). Social desirability bias in CATI, IVR, and Web surveys: The effects of mode and question sensitivity. Public Opinion Quarterly, 72(5), 847–865. https://doi.org/10.1093/poq/nfn063
   Web of Science ®Google Scholar
• Leukfeldt, E. R., & Yar, M. (2016). Applying routine activity theory to cybercrime: A theoretical and empirical analysis. Deviant Behavior, 37(3), 263–280. https://doi.org/10.1080/01639625.2015.1012409
   Web of Science ®Google Scholar
• Levay, K. E., Freese, J., & Druckman, J. N. (2016). The demographic and political composition of Mechanical Turk samples. SAGE Open, 1, 1–17. https://doi.org/10.1177/2158244016636433.
   Google Scholar
• Madigan, D., & Raftery, A. E. (1994). Model selection and accounting for model uncertainty in graphical models using Occam’s window. Journal of the American Statistical Association, 89(428), 1535–1546. https://doi.org/10.1080/01621459.1994.10476894
   Web of Science ®Google Scholar
• Marcum, C., Rickets, M., & Higgins, G. (2010). Assessing sex differences of online victimization: An examination of adolescent online behaviours using routine activity theory. Criminal Justice Review, 35(4), 412–437. https://doi.org/10.1177/0734016809360331
   Google Scholar
• McCullagh, P., & Nelder, J. (1989). Generalized linear models (2nd ed.). Chapman and Hall/CRC.
   Google Scholar
• Miethe, T. D., & Meier, R. F. (1994). Crime and its social context: Toward an integrated theory of offenders, victims, and situations. State University of New York Press.
   Google Scholar
• Milani, R., Caneppele, S., & Burkhardt, C. (2020). Exposure to cyber victimization: Results from a Swiss survey. Deviant Behavior, 1–13. https://doi.org/10.1080/01639625.2020.1806453
   Google Scholar
• Morwitz, V. G. (1997). It seems like only yesterday: The nature and consequences of telescoping errors in marketing research. Journal of Consumer Psychology, 6(1), 1–29. https://doi.org/10.1207/s15327663jcp0601_01
   Google Scholar
• Ngo, F. T., & Paternoster, R. (2011). Cybercrime victimization: An examination of individual and situational level factors. International Journal of Cyber Criminology, 5(1), 773–793. https://www.cybercrimejournal.com/ngo2011ijcc.pdf.
   Google Scholar
• Nobles, M. R., Reyns, B. W., Fox, K. A., & Fisher, B. S. (2014). Protection against pursuit: A conceptual and empirical comparison of cyberstalking and stalking victimization among a national sample. Justice Quarterly, 31(6), 986–1014. https://doi.org/10.1080/07418825.2012.723030
   Web of Science ®Google Scholar
• Pratt, T. C., Holtfreter, K., & Reisig, M. D. (2010). Routine online activity and Internet fraud targeting: Extending the generality of routine activity theory. Journal of Research in Crime and Delinquency, 47(3), 267–296. https://doi.org/10.1177/0022427810365903
   Web of Science ®Google Scholar
• Reynald, D. M., Moir, E., Cook, A., & Vakhitova, Z. I. (2018). Changing perspectives on guardianship against crime: An examination of the importance of micro-level factors. Crime Prevention and Community Safety, 20(4), 268–283. https://doi.org/10.1057/s41300-018-0049-4
   Web of Science ®Google Scholar
• Reynald, D. M. (2009). Guardianship in action: Developing a new tool for measurement. Crime Prevention and Community Safety, 11(1), 1–20. https://doi.org/10.1057/cpcs.2008.19
   Google Scholar
• Reyns, B. W., Henson, B., & Fisher, B. S. (2010). A situational crime prevention approach to cyberstalking victimization: Preventive tactics for Internet users and online place managers. Crime Prevention and Community Safety, 12(2), 99––118. https://doi.org/10.1057/cpcs.2009.22
   Google Scholar
• Reyns, B. W., Henson, B., & Fisher, B. S. (2011). Being pursued online: Applying cyberlifestyle routine activities theory to cyber-stalking victimization. Criminal Justice and Behaviour, 38(11), 1149–1169. https://doi.org/10.1177/0093854811421448
   Web of Science ®Google Scholar
• Reyns, B. W., Henson, B., & Fisher, B. S. (2016). Guardians of the cyber galaxy: An empirical and theoretical analysis of The Guardianship concept from routine activity theory as It applies to online forms of victimization. Journal of Contemporary Criminal Justice, 32(2), 148–168. https://doi.org/10.1177/1043986215621378
   Web of Science ®Google Scholar
• Sampson, R., Eck, J. E., & Dunham, J. (2010). Super controllers and crime prevention: A routine activity explanation of crime prevention success and failure. Security Journal, 23(1), 37–51. https://doi.org/10.1057/sj.2009.17
   Web of Science ®Google Scholar
• Sue, V. M., & Ritter, L. A. (2012). Conducting Online Surveys. Sage.
   Google Scholar
• Summative Scales. (2004). Learn about constructing summative scales in survey data in SPSS with data from the General Social Survey. http://methods.sagepub.com/base/download/DatasetStudentGuide/summative-scales-in-gss-2004-spss
   Google Scholar
• Tait, A. (2016). Is arguing online actually good for your mental health? The New Statesman. https://www.newstatesman.com/culture/observations/2016/10/arguing-online-actually-good-your-mental-health
   Google Scholar
• Tewksbury, R., & Mustaine, E. E. (2003). College students’ lifestyles and self-protective behaviours: Further considerations of The Guardianship concept in routine activity theory. Criminal Justice and Behaviour, 30(3), 302–327. https://doi.org/10.1177/0093854803030003003
   Web of Science ®Google Scholar
• Thompson, A., & Pickett, J. T. (2019). Are relational inferences from crowdsourced and opt-in samples generalizable? Comparing criminal justice attitudes in the GSS and five online samples. Journal of Quantitative Criminology, 36(4), 907–932. https://doi.org/10.1007/s10940-019-09436-7
   Web of Science ®Google Scholar
• Vakhitova, Z. I., Alston-Knox, C. L., Mawby, R. I., & Reeves, E. (2021). Explaining victim impact from cyber abuse: An exploratory mixed-methods analysis. Deviant Behaviour, 1–20. https://doi.org/10.1080/01639625.2021.1921558
   Google Scholar
• Vakhitova, Z. I., & Alston-Knox, C. L. (2018). Non-significant p-values? Strategies to understand and better determine the importance of effects and interactions in logistic regression. PLoS ONE, 13(11), 0-010-9106-6. https://doi.org/10.1007/s1094
   Google Scholar
• Vakhitova, Z. I., Reynald, D. M., & Townsley, M. K. (2016). Toward adapting routine activity and lifestyle exposure theories to account for cyber abuse victimization. Journal of Contemporary Criminal Justice, 32(2), 169–188. https://doi.org/10.1177/1043986215621379
   Web of Science ®Google Scholar
• Van Ouytsel, J., Ponnet, K., & Walrave, M. (2018). Cyber dating abuse victimization among secondary school students from a lifestyle-routine activities theory perspective. Journal of Interpersonal Violence, 33(17), 2767–2776. https://doi.org/10.1177/0886260516629390
   PubMed Web of Science ®Google Scholar
• Van Wilsem, J. (2011). Worlds tied together? Online and non-domestic routine activities and their impact on digital and traditional threat victimization. European Journal of Criminology, 8(2), 115–127. https://doi.org/10.1177/1477370810393156
   Web of Science ®Google Scholar
• Vaughan, T. J., Holleran, L. B., & Silver, J. R. (2019). Applying moral foundations theory to the explanation of capital jurors’ sentencing decisions. Justice Quarterly, 36(7), 1176–1205. https://doi.org/10.1080/07418825.2018.1537400
   Web of Science ®Google Scholar
• Vogels, E. (2021). The State of Online Harassment. Pew Research Center. https://www.pewresearch.org/internet/2021/01/13/the-state-of-online-harassment
   Google Scholar
• Wachs, S., Costello, M., Wright, M. F., Flora, K., Daskalou, V., Maziridou, E., Kwon, Y., Na, E.-Y., Sittichai, R., Biswal, R., Singh, R., Almendros, C., Gámez-Guadix, M., Gӧrzig, A., Hong, J. S. (2021). DNT LET ’EM H8 U!: Applying the routine activity framework to understand cyberhate victimization among adolescents across eight countries. Computers & Education, 160, 104026. https://doi.org/10.1016/j.compedu.2020.104026
   Web of Science ®Google Scholar
• Weinberg, D., Freese, J., & McElhattan, D. (2014). Comparing data characteristics and results of an online factorial survey between a population-based and a crowdsource- recruited sample. Sociological Science, 1, 292–310. https://doi.org/10.15195/v1.a19
   Google Scholar
• Wilcox, P., Jordan, C. E., & Pritchard, A. J. (2007). A multidimensional examination of campus safety: Victimization, perceptions of danger, worry about crime, and precautionary behavior among college women in the post-Clery era. Crime & Delinquency, 53(2), 219–254. https://doi.org/10.1177/0097700405283664
   Web of Science ®Google Scholar
• Williams, M. L. (2016). Guardians upon high: An application of routine activities theory to online identity theft in Europe at the country and individual level. The British Journal of Criminology, 56(1), 21–48. https://doi.org/10.1093/bjc/azv011
   Web of Science ®Google Scholar
• Woolnough, A. (1989). Effects of personal experience on self-protective behavior. Psychological Bulletin, 105(1), 31–50. https://doi.org/10.1037/0033-2909.105.1.31
   PubMed Web of Science ®Google Scholar
• Worsley, J. D., Wheatcroft, J. M., Short, E., & Corcoran, R. (2017). Victims’ Voices: Understanding the Emotional Impact of Cyberstalking and Individuals’ Coping Responses. SAGE Open.
   Google Scholar
• Yar, M. (2005). The novelty of “cybercrime”: An assessment in light of routine activity theory. European Journal of Criminology, 2(4), 407–427. https://doi.org/10.1177/147737080556056
   Google Scholar