Related Experiment Video
Updated: May 21, 2025

09:49
Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
Published on: December 24, 2015
14.1K
Exploring Correlates of Multiple Perpetrator Rape Proclivity in Women
Michelle Schwier1, Alexandra M Zidenberg2, Saad Iqbal3
1Department of Psychology, Western University, London, Canada.
Violence and Victims
|March 22, 2025
Summary
This study explored women's interest in multiple perpetrator rape (MPR). Psychopathy, rape myth acceptance, aggression, and deviant sexual fantasies were linked to interest in MPR among female participants.
Area of Science:
- Psychology
- Criminology
- Forensic Psychology
Background:
- Limited research exists on women's interest in multiple perpetrator rape (MPR), with most prior studies focusing on male interest.
- Understanding factors associated with women's interest in MPR is crucial for developing targeted prevention and intervention strategies.
Purpose of the Study:
- To investigate correlates of interest in multiple perpetrator rape (MPR) specifically within a female population.
- To examine the relationship between psychological traits (loneliness, psychopathy, anger rumination) and interest in MPR in women.
Main Methods:
- A cross-sectional study involving 182 female participants who completed a series of validated questionnaires.
- Utilized the Multiple-Perpetrator Rape Interest Scale (M-PRIS), alongside measures for loneliness, psychopathy, aggression, sexual fantasies, anger rumination, and rape myth acceptance.
- Employed backward stepwise linear regression to identify significant predictors of MPR interest.
Main Results:
- Psychopathy, acceptance of rape myths, aggression, and deviant sexual fantasies were individually correlated with interest in MPR.
- A significant portion of participants (37%) reported some level of sexual arousal, behavioral propensity, or enjoyment related to hypothetical MPR scenarios.
- Loneliness and anger rumination were not found to be significant predictors in the final regression model.
Conclusions:
- Psychological factors including psychopathy, rape myth acceptance, aggression, and deviant sexual fantasies are associated with women's interest in MPR.
- Findings highlight the need for further research to establish risk factors and predictive elements for women's involvement in rape.
- This study contributes to a better understanding of female interest in MPR, informing future research and clinical practice.
Related Concept Videos
Criticisms of the Evolutionary Perspective
85
In a study where individuals posing as strangers offered compliments and proposed casual sex to students, the responses differed significantly based on gender. Not a single woman accepted the proposal, while 70% of the men agreed. This outcome provides a useful scenario to explore through the lens of evolutionary psychology and social learning theory, highlighting the diverse perspectives on human sexual behaviors.
Evolutionary psychology provides one explanation for these findings, suggesting...
Evolutionary psychology provides one explanation for these findings, suggesting...
85
Aggression
27.7K
Humans engage in aggression when they seek to cause harm or pain to another person. Aggression takes two forms depending on one’s motives: hostile or instrumental. Hostile aggression is motivated by feelings of anger with intent to cause pain; a fight in a bar with a stranger is an example of hostile aggression. In contrast, instrumental aggression is motivated by achieving a goal and does not necessarily involve intent to cause pain (Berkowitz, 1993); a contract killer who murders for...
27.7K
Cross-Sectional Research
11.1K
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
11.1K
Correlation and Causation
37.3K
Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
37.3K
Prevalence and Incidence
284
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
284
Multiple Regression
2.9K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
2.9K

