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Moving beyond sexual assault research's reliance on self-report surveys using an online choose-your-own-adventure paradigm to study sexual assault behavior in college students / Joseph E. Gonzales, Melissa M. Pope, Annabelle Frazier.

SAGE Research Methods: Doing Research Online Available online

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Format:
Book
Author/Creator:
Gonzales, Joseph E., author.
Pope, Melissa M., author.
Frazier, Annabelle, author.
Series:
SAGE research methods: doing research online.
SAGE research methods: doing research online
Language:
English
Subjects (All):
Internet research--Case studies.
Internet research.
Rape--Research--Case studies.
Rape.
Physical Description:
1 online resource : illustrations.
Place of Publication:
London : SAGE Publications, Ltd., 2022.
Summary:
In the present case study, we review our novel application of a Choose-Your-Own-Adventure (CYOA) paradigm to study college students' sexual violence perpetration and consent behavior online. Specifically, we consider our adaptation of a previously developed CYOA for the study of the serious crime adjudication process to study college student proclivity to engage in sexual consent and sexual assault behavior with an intoxicated person (i.e., a nonplayer character) at a house party. We review limitations common to current methods for studying sexual consent and sexual violence perpetration, our reasons for applying a CYOA approach to this area of research, and our general findings and conclusions concerning the efficacy of the CYOA paradigm to this topic of research. Furthermore, we consider some of the limitations we experienced using the CYOA in our study and some of the challenges we encountered as a function of administering the study online. Overall, we conclude that when promoting participant immersion and realism in study materials is important but ethically challenging, and the study of participant behavior within a particular context is appropriate, the CYOA is a promising paradigm for advancing the field of sexual assault research.
Notes:
Description based on XML content.
ISBN:
9781529799750 :
OCLC:
1301362494

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