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Cited by 140Sexuality, Behavior, and TechnologyGender, Feminism, and MediaStalking, Cyberstalking, and Harassment

The dark side of sexting—Factors predicting the dissemination of sexts

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Clancy, Elizabeth M., Klettke, Bianca, Hallford, David J.·2019·Computers in Human Behavior
DOI 10.1016/j.chb.2018.11.023
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Crossref · 10.1016/j.chb.2018.11.023

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29 of 29 references verified0 citation errors · 0 not checkable

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  • In both Spain and Italy, forwarding sexual content featuring someone without their consent is a form of harassment that, when it occurs, is often associated with other more frequent and normalised forms of online sexual aggression.

    “These data suggest that, in both countries, forwarding sexual content featuring someone without their consent is a form of harassment that, when it occurs, is often associated with other more frequent and normalised forms of online sexual aggression (Clancy et al., 2019; Gámez-Guadix et al., 2022b; Ybarra & Thompson, 2018), such as the direct and ambiguous forms measured in this study.”

    From Online Sexual Harassment Perpetration Among Peer Adolescents: A Cross-National and Cross-Gender Study (2025) · cites this paper as Clancy et al., 2019

  • Among studies examining nonconsensual sharing, four found women more likely than men to engage in the behavior, though difference was small in Hu et al. (2023) and Clancy et al. (2019).

    “whereas four studies found that women were more likely than men to engage in the nonconsensual sharing of other people’s intimate images, although the difference was small in Hu et al. (2023) and Clancy et al. (2019)”

    From Image-Based Sexual Abuse Perpetration: A Scoping Review (2024) · cites this paper as Clancy et al. (2019)

  • Clancy et al. (2019) found 'it was no big deal' or 'as a joke, to be funny' were most frequently endorsed reasons, and men more likely to agree that sext dissemination can enhance social status (40.7% vs 5.0%).

    “These findings were consistent with their previous study (Clancy et al., 2019), where “it was no big deal” or “as a joke, to be funny” were the most frequently endorsed reasons, and men being more likely to agree that sext dissemination can enhance social status (40.7% vs. 5.0%).”

    From Image-Based Sexual Abuse Perpetration: A Scoping Review (2024) · cites this paper as Clancy et al., 2019

  • Motivations related to bragging or improving social status were more likely to be reported by men compared to women according to one reviewed study.

    “Motivations related to bragging or improving social status were more likely to be reported by men compared to women according to one study (Clancy et al., 2019).”

    From Image-Based Sexual Abuse Perpetration: A Scoping Review (2024) · cites this paper as Clancy et al., 2019

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Authors
Clancy, E. M., Klettke, B., & Hallford, D. J.
Affiliations
Deakin University (AU)
Corresponding author
Clancy, Elizabeth M.
ORCID
Venue
Computers in Human Behavior
Publisher
Elsevier BV
Published
2019-03
Volume
92
Pages
266-272
ISSN
0747-5632 (ISSN-L)
DOI
10.1016/j.chb.2018.11.023
OpenAlex
W2900469320
Cited by
139
References
29
Citations by year
2026: 12 · 2025: 32 · 2024: 18 · 2023: 24 · 2022: 15 · 2021: 21 · 2020: 11 · 2019: 4 · 2018: 2
FWCI
11.18
Type
journal article
Language
en
Open access
Licence
Locations
  • Computers in Human Behavior (publishedVersion)
  • Own your potential (DEAKIN) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
Topics
  • Social Sciences › Psychology › Clinical Psychology › Sexuality, Behavior, and Technology
  • Social Sciences › Gender Studies › Gender, Feminism, and Media
  • Social Sciences › Sociology and Political Science › Stalking, Cyberstalking, and Harassment
Keywords
sexting, Dark Triad personality, Machiavellianism, psychopathy, narcissism, subjective norms, sexual activity, young adults, online sexual behavior

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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