A Re-evaluation of Online Pornography Use in Germany: A Combination of Web Tracking and Survey Data Analysis.

Several researchers have questioned the reliability of pornography research's findings. Following a recent call to use more reliable data sources, we conducted two analyses to investigate patterns and predictors of online pornography use (OPU). Our analyses were based on data from a large-scale Germ...

Descripción completa

Detalles Bibliográficos
Publicado en:Archives of Sexual Behavior Vol. 52; no. 8; pp. 3491 - 3504
Autores principales: von Andrian-Werburg, Maximilian T. P., Siegers, Pascal, Breuer, Johannes
Formato: Artículo
Publicado: Springer Nature Nov2023
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=174064731&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 174064731
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        00040002
        ASX
      jtl: Archives of Sexual Behavior
      issn: 00040002
      maglogo: N
    pubinfo:
      dt: Nov2023
      vid: 52
      iid: 8
      pid: 237
      pub: Springer Nature
    artinfo:
      ui:
        174064731
        10.1007/s10508-023-02666-8
      ppf: 3491
      ppct: 13
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
              size: 1.2MB
      tig:
        atl: A Re-evaluation of Online Pornography Use in Germany: A Combination of Web Tracking and Survey Data Analysis.
      aug:
        au:
          von Andrian-Werburg, Maximilian T. P.
          Siegers, Pascal
          Breuer, Johannes
        affil:
          https://ror.org/00fbnyb24 Institute Human-Computer-Media, Faculty of Human Sciences, University of Wuerzburg, Oswald-Kuelpe-Weg 82, 97074, Wurzburg, Germany
          https://ror.org/018afyw53 GESIS–Leibnitz Institute for the Social Sciences, Mannheim, Germany
          https://ror.org/04445fp84 Center for Advanced Internet Studies, Bochum, Germany
      su:
        Internet pornography
        Pornography
        Computer sex
        Sexism
        Religiousness
        Sex on the Internet
      sug:
        subj:
          Internet pornography
          Pornography
          Computer sex
          Sexism
          Religiousness
          Sex on the Internet
      keyword:
        Online pornography use
        Religiosity
        Social dominance orientation
        Web tracking data
        Online pornography use
        Religiosity
        Social dominance orientation
        Web tracking data
      ab: Several researchers have questioned the reliability of pornography research's findings. Following a recent call to use more reliable data sources, we conducted two analyses to investigate patterns and predictors of online pornography use (OPU). Our analyses were based on data from a large-scale German online web tracking panel (N = 3018) gathered from June 2018 to June 2019. The study we present here has two parts: In the first part, we looked at group differences (gender and age) in tracked OPU. Overall, this part's results confirm questionnaire-based research findings regarding sex and age differences. In the second part of our study, we combined the web tracking data with data from an online survey which was answered by a subset of the tracking participants (n = 1315) to assess the relevance of various predictors of OPU that have been identified in previous research. Again, our results mostly echoed previous findings based on self-reports. Online pornography was used more by males and younger individuals, while relationship status, sexist attitudes, and social dominance orientation were not associated with OPU. However, we did find differences in OPU between members of different religious communities. Our study confirms some critical findings on OPU from previous questionnaire-based research while extending existing research by providing a more fine-grained analysis of usage patterns based on web tracking data.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N