The document discusses self-reported delinquency surveys and their application to studying online offending and cybercrime. It notes that while self-reported surveys have been an important tool, their use for cybercrime raises conceptual and methodological issues given measurement challenges. The document advocates for more descriptive research on online offending to better develop measures before testing theories. It also calls for integrating different data sources to avoid single-method biases and focusing on mechanisms to improve theory development and application for prevention.

1. Prof. Dr. Lieven J.R. Pauwels
t. +32 9 264 68 37
f. +32 9 264 84 94
Lieven.Pauwels @UGent.be
12-12-2019
Self-reported Delinquency Surveys and the
Study of Online Offending / Cybercrime:
Looking Back and Forward from a Total Survey
Error Approach
Lieven J.R. Pauwels (Ghent University)

2. research publications consultancy conferences
www.ircp.ugent.be
Lieven J.R. Pauwels
+32 9 264 68 37
Lieven.Pauwels@UGent.be
• KEY MESSAGES
• Understanding and preventing cybercrime / online offending,
victimization and reporting behavior require an analytical approach
(targeting mechanisms underlying stable predictors)
• Understanding cybercrime should be guided by USEFUL theory, well
supported by empirical evidence [‘the best available’].
• NEW FACTS AND NEW CONCEPTS steer the evolution of a field.
• Self-reported delinquency studies as an important ‘tool of the trade’ for
descriptive and explanatory purposes, ie to assess the status of theories.
However, but many measurement issues remain.
• Therefore, it is a legitimate question to what extent self-reported
delinquency methodology can be applied to online offending (and
victimization).
• Some persistent conceptual and methodological issues are discussed in
the light of self-reported online offending / cyber crime.
1. Introduction and goal of the presentation
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Lieven J.R. Pauwels
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• Why do scholars use self-reported delinquency questionnaires?
• Descriptive research (prevalence, frequencies of behavioral responses)
▪ What kind of online offending cyber crime?
▪ What kind of population is vulnerable?
▪ Demographics (Often attributes like Gender, status, immigrant background)
• Exploratory research (exploring covariates)
• How strong is the overlap between covariates of ‘traditional’ self-reported offending and
online offending?
• Explanatory research (can ‘established theories’ be applied to online
offending in the broadest definition)?
• Eg: self-control theory, routine activity theory, social learning theory, social control
theory
• Caveats:
• (1) Humans are more than ‘the sum of variables’
• (2) Variables do not belong to one framework.
This also applies to the study of online offending
2. Self-reported delinquency methodology in a
nutshell
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Lieven J.R. Pauwels
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• Different periods in the history of self-reported delinquency
research
• (1) Exploration and discovery of hidden crime 1940-1950s
• (2) The ‘golden years of theory testing’ 1960s
• (3) Application in nation-wide representative studies 1970s
• (4) The hyper-optimistic years: 1980-1985
• (5) The recognition of measurement problems: reliability &
validity discussions (lying, social desirability, acquiescence, recall
problems, …)
• (6) The internationalisation (eg ISRD1-2-3)
• (7) The digitalization: from PAPI survey to online surveys
(especially relevant for the study of online offending)
• Now: an established method with advantages and disadvantages.
2. Self-reported delinquency methodology in a
nutshell
4

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Lieven J.R. Pauwels
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• A quick scan of the literature suggests that:
• (1) International awareness has increased since the 1990s
• Lamenting the inability of the criminal code to fully describe cyber-related phenomena
(but a fraud in cyberspace remains a fraud)
• Recognizing the problems of lack of data on perpetrators
• (2) Published self-reported delinquency studies of cyber crime
/digital crime go back to the 1990s and beginning of Y2K (eg
Skinner and Fream, 1997; Rogers, 2001)
• (3) Number of publications have increased significantly since the
overwhelming popularity of social media
• (4) Most self-report studies on online delinquency suffer similar
criticisms of traditional (offline) self-reported delinquency studies
2. Self-reported delinquency methodology in a
nutshell
5

6. research publications consultancy conferences
www.ircp.ugent.be
Lieven J.R. Pauwels
+32 9 264 68 37
Lieven.Pauwels@UGent.be
• Survey measurement error refers to error in survey response
arising from (1) the method of data collection, (2) respondent or
(3) questionnaire
3. Cybercrime /online offending from a ‘Total
Survey Error Approach’
6
Conceptual issues:
Definitions
Operationalisation
Behaviour
victims, offenders
In the general
population

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Lieven J.R. Pauwels
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• Conceptualization and measurement (from ‘trying to steal a password’
and ‘deleting files from one’s computer’ to ‘online threatening using
social media’).
• Like early traditional self-reported delinquency surveys, ‘triviality’ is a
threat.
• Self-reported delinquency scales (from published studies):
• Usually: hacking, digital piracy (illegal downloading / uploading), cyber bullying and
harassment, cyber fraud (phishing and malware)
• Reliabilities (measures of internal consistency: ‘moderate’ but it is hardly questioned
whether measures to evaluate reliabilities of attitudinal scales should be applied to
behavior)
• Challenges: violent extremism and hate crime, sexting, child pornography, exposure
• Beyond self-reported delinquency scales: randomized scenario studies?
• Has been successfully applied to the study of victimization and reporting
behavior (Vandeweijer et al 2019), applications to digital piracy (Van
Rooij et al 2016)
3. Cybercrime /online offending from a ‘Total
Survey Error Approach’
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Lieven J.R. Pauwels
+32 9 264 68 37
Lieven.Pauwels@UGent.be
• Digital crime studies require adequate measures of digital exposure
• Measuring exposure to digital criminogenic settings
• Often restricted to internet use (frequency of use is not enough)
• Better measures necessary that capture the ‘criminogeneity’ of the setting
[3W-model: what are people doing online, with whom are people spending
time online, what kind of websites, social network sites, chat rooms, instant
messaging fora are people using] + level of online monitoring – norm
enforcement online. This is hardly done.
• Less frequently studied: measures of exposure to explicit content (e.g. hate
crime online, violent extremism online). This can be done succesfully (Pauwels
& Hardyns, 2018), but remains controversial topic (‘cause or spurious
relationship’)
• Active & passive exposure, cumulative exposure
• Target populations?
• Too much WEIRD-people, undergraduate and graduate student populations
• New panel data: is it really just a matter of time (and resources)?
3. Cybercrime /online offending from a ‘Total
Survey Error Approach’
8

9. research publications consultancy conferences
www.ircp.ugent.be
Lieven J.R. Pauwels
+32 9 264 68 37
Lieven.Pauwels@UGent.be
• Definitional issues need to be clarified.
• Much more descriptive research is necessary, before adequate
testing can take place.
• 1) First adequate descriptions of involvement (online + offline)
• 2) Development of adequate measures of exposure
(circumstances) and relevent personal characteristics (traits and
experiences).
• 3) Can sources be merged? Avoid bias stemming from the same
measurement instrument. Eg: combination with Game Theory
• 3) Discuss plausible and realistic mechanisms: improve theory
development, testing and application (it ‘s better for prevention).
• 4) Avoid the ‘endless testing of seemingly competing theories’.
Integration: 1+1=3
4. Conclusion /discussion/avenues for future
research
9

10. Thanks for your attention!
10

11. research publications consultancy conferences
www.ircp.ugent.be
Lieven J.R. Pauwels
+32 9 264 68 37
Lieven.Pauwels@UGent.be
• De Kimpe, L., Ponnet, K., Walrave, M., Snaphaan, T., Pauwels, L., & Hardyns, W. (2020). Help, I need
somebody : examining the antecedents of social support seeking among cybercrime victims. COMPUTERS
IN HUMAN BEHAVIOR, 108.
• De Kimpe, L., Ponnet, K., Walrave, M., Snaphaan, T., Pauwels, L., & Hardyns, W. (2020). Research note: An
investigation of reporting behavior among cybercrime victims. European Journal of Crime, Criminal Law
and Criminal Justice. Accepted for publication.
• Diamond, B., & Bachmann, M. (2015). Out of the beta phase: Obstacles, challenges, and promising paths
in the study of cybercriminology. International Journal of Cyber Criminology, 9(1), 24–34.
• Enzmann, D., Kivivuori, J., Marshall, I. H., Steketee, M., Hough, M., & Killias, M. (2018). A Global
Perspective on Young People as Offenders and Victims (First Results from the ISRD3 Study). Cham,
Switzerland.
• Flores, W. R., Holm, H., Svensson, G., & Ericsson, G. (2014). Using phishing experiments and scenario-
based surveys to understand security behaviours in practice. Information Management & Computer
Security.
• Groves, R. M., & Lyberg, L. (2010). Total survey error: Past, present, and future. Public opinion
quarterly, 74(5), 849-879.
• Hawdon, J., Bernatzky, C., & Costello, M. (2019). Cyber-routines, political attitudes, and exposure to
violence-advocating online extremism. Social Forces, 98(1), 329-354.
• Hardy, W., Krawczyk, M., & Tyrowicz, J. (2013). Why is online piracy ethically different from theft? A
vignette experiment. Université de Varsovie, faculté des sciences économiques, Working Paper, (2013), 24.
• Gunter, W. D. (2008). Piracy on the high speeds: A test of social learning theory on digital piracy among
college students. International Journal of Criminal Justice Sciences, 3(1), 54.
• Hawdon, J., Bernatzky, C., & Costello, M. (2019). Cyber-routines, political attitudes, and exposure to
violence-advocating online extremism. Social Forces, 98(1), 329-354.
• Higgins, G. E. (2007). Digital piracy, self-control theory, and rational choice: An examination of the role of
value. International Journal of Cyber Criminology, 1(1), 33-55.
Some references
11

12. research publications consultancy conferences
www.ircp.ugent.be
Lieven J.R. Pauwels
+32 9 264 68 37
Lieven.Pauwels@UGent.be
• Holt, T. J. (2010). Crime on-line: Correlates, causes, and context. Raleigh, NC: Carolina Academic Press.
• Kivivuori, J. (2015). Discovery of hidden crime: Self-report delinquency surveys in criminal policy context. Oxford University
Press.
• Lee, J., Onifade, E., Ryu, J., Rasul, A., & Maynard, Q. R. (2014). Online activity, alcohol use, and internet delinquency among
Korean youth: A multilevel approach. Journal of Ethnicity in Criminal Justice, 12(4), 247-263.
• Louderback, E. R., & Antonaccio, O. (2020). New Applications of Self-Control Theory to Computer-Focused Cyber Deviance
and Victimization: A Comparison of Cognitive and Behavioral Measures of Self-Control and Test of Peer Cyber Deviance and
Gender as Moderators. Crime & Delinquency, 0011128720906116.
• Marshall, I. H., & Steketee, M. (2019). What May Be Learned about Crime in Europe (and Beyond) from International Surveys
of Youth: Results from the International Self-Report Delinquency Study (ISRD3). European Journal on Criminal Policy and
Research, 25(3), 219-223.
• Morris, R. G., & Higgins, G. E. (2010). Criminological theory in the digital age: The case of social learning theory and digital
piracy. Journal of Criminal Justice, 38(4), 470-480.
• Morris, R. G., & Higgins, G. E. (2009). Neutralizing potential and self-reported digital piracy: A multitheoretical exploration
among college undergraduates. Criminal Justice Review, 34(2), 173-195.
• Pauwels, L., & Schils, N. (2016). Differential online exposure to extremist content and political violence: Testing the relative
strength of social learning and competing perspectives. Terrorism and Political Violence, 28(1), 1-29.
• Pauwels, L. J., & Hardyns, W. (2018). Endorsement for extremism, exposure to extremism via social media and self-reported
political/religious aggression. International journal of developmental science, 12(1-2), 51-69.
• Rokven, J. J., Weijters, G., Beerthuizen, M. G., & van der Laan, A. M. (2018). Juvenile delinquency in the virtual world:
Similarities and differences between cyber-enabled, cyber-dependent and offline delinquents in the Netherlands.
International journal of cyber criminology, 12(1), 27-46.
• Rogers, M. K. (2001). A social learning theory and moral disengagement analysis of criminal computer behavior: An
exploratory study.
• Smallridge, J. L., & Roberts, J. R. (2013). Crime Specific Neutralizations: An Empirical Examination of Four Types of Digital
Piracy. International Journal of Cyber Criminology, 7(2).
• Staksrud, E. (2009). Problematic conduct: Juvenile delinquency on the Internet. Kids online: Opportunities and risks for
children, 147-159.
• van de Weijer, S., Leukfeldt, R., & Van der Zee, S. (2020). Reporting cybercrime victimization: determinants, motives, and
previous experiences. Policing: An International Journal.
Some references
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Contact
Lieven J.R. Pauwels
T. +32 9 264 68 37
Lieven.Pauwels@UGent.be
IRCP
Ghent University
Universiteitstraat 4
B – 9000 Ghent