The Impact of Frequency and Type of Pornography Use on Recidivism Among Sexual Offenders

Here below, Ipce offers a "Quotes from ..." in a better readable format of this quite complex article, as well as a link to "Short explanation, short comment, questions", both written by Frans E.J. Gieles, PhD, The Netherlands, 2021.

• The original article with all statistical date and references is here:
  < pornography_use_and_sexual_aggession.pdf >
• The "Short Explanation ..." is here:
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The authors’ summary

In this study, we examined the unique contribution of pornography consumption to the longitudinal prediction of criminal recidivism in a sample of 341 child molesters. We specifically tested the hypothesis, based on predictions informed by the confluence model of sexual aggression that pornography will be a risk factor for recidivism only for those individuals classified as relatively high risk for re-offending.

Pornography use (frequency and type) was assessed through self-report and recidivism was measured using data from a national database from the Royal Canadian Mounted Police. Indices of recidivism, which were assessed up to 15 years after release, included
[a] an overall criminal recidivism index, as well as
[b] subcategories focusing on violent (including sexual) recidivism and [c] sexual recidivism alone.

Results for both frequency and type of pornography use were generally consistent with our predictions. Most importantly, after controlling for general and specific risk factors for sexual aggression, pornography added significantly to the prediction of recidivism. Statistical interactions indicated
(1) that frequency of pornography use was primarily a risk factor for higher-risk offenders, when compared with lower-risk offenders, and
(2) that content of pornography (i.e., pornography containing deviant content) was a risk factor for all groups. The importance of conceptualizing particular risk factors (e.g., pornography), within the context of other individual characteristics is discussed.

From the Introduction

“In a meta-analysis of 33 studies (N52,040), Allen et al. [1995a] examined the association between pornography and nonsexual aggression using prototypical analog measures of aggressive behavior.

The analysis divided sexually explicit material into one of the following three categories:
(a) nudity,
(b) nonviolent sexual behavior, and
(c) violent sexual behavior.

Overall, results indicated an association between pornography and aggression. However, type of pornography was a moderator, such that exposure to nudity decreased aggression, whereas exposure to the latter two categories significantly increased aggression.”

“In non-criminal populations, Malamuth et al. [2000] examined the relationship between frequency of pornography use and sexual aggression in a representative sample of men (n = 52,972).
Results indicated that pornography use was positively correlated with coercive sexual behavior and was predictive of sexual aggression.

These findings have been supported in other studies demonstrating a significant relationship between a higher frequency of pornography use and type of use (i.e., deviant images) with sexual aggression […].
However, as noted below, follow-up analyses  demonstrated that the association between pornography and sexual coercion was largely based on those individuals assessed as high risk to offend sexually.”

“Most of the research investigating the interaction effects between pornography and other variables has been conducted under the organizational framework of the Hierarchical-Mediational Confluence model HMC […].

In brief, the HMC model was constructed from research demonstrating that sexual aggressors possess several key characteristics, which are present both developmentally and at the time of aggression.
These predictor variables operationalize two proposed pathways to sexual coercion.

[1] The first is hostile masculinity ,which refers to a constellation of personality traits, combining a hostile orientation, typically toward women and satisfaction obtained through dominating, humiliating, and controlling women.

[2] The second pathway is impersonal sex and describes a noncommittal, game-playing orientation toward sexual activity and describes individual differences in the willingness to engage in such acts without closeness or commitment […].

As opposed to a path-oriented model, where the presence of a specific factor directly determines the criterion of interest, the HMC model provides both a cumulative and conditional-probability explanation for the causes of sexually aggressive behavior.

In other words, the HMC model highlights the importance of investigating a particular predictor (e.g., pornography) within the context of other variables (e.g., pretest measures of risk characteristics) and this allows for the inclusion of relevant moderating variables in a predictive model.”

“The relationship between pornography and sexual aggression has been investigated according to the conditional-probability approach suggested by the HMC model in non-criminal sexual aggressors, i.e., college students who self-report using sexual coercion; […].

Results indicated that pornography was a significant additional predictor of sexual aggression, after controlling for the other risk factors described by the model and that frequency of pornography use was only a risk factor for individuals assessed to be ‘‘at relatively high risk’’ for perpetrating sexual aggression […].

Specifically, this research highlighted an interaction effect, in which

• individuals classified as low risk demonstrated a small association between frequency of pornography use and sexual aggression,
• whereas high-risk men showed a large effect between pornography and sexual aggression.

With respect to attitudes, Hald et al. [2007] obtained similar results, such that

• individuals assessed as low or moderate risk for aggression demonstrated no effect between frequency of pornography use and negative attitudes toward women,
• whereas the highest risk group demonstrated a significant relationship.”

“The purpose of this study was to evaluate the role of pornography as a risk factor for aggression and to extend the findings of Malamuth and others — that is, to examine whether pornography use is a significant predictor of sexual aggression, when moderated by general and specific risk characteristics.

As such, we hypothesized that pornography use would be a risk factor for recidivism only for those individuals classified as relatively high risk for re-offending.

This hypothesis was tested using the following three classifications of recidivism:
(1) all criminal recidivism,
(2) violent (including sexual) recidivism, and
(3) sexual recidivism only (…).”

“Currently, research pertaining to pornography use and aggression, moderated by individual risk factors, has utilized non-criminal populations (i.e., college students) and, as such, has neglected individuals with an official history of sexual coercion (i.e., sexual offenders).

Moreover, most studies have predominantly used cross-sectional research designs, and thus, longitudinal data pertaining to the relationship between pornography and aggression have been noticeable limited. This paper addressed both of these limitations.”

Method

“Participants were adult men who had been convicted of a hands-on sexual offence against an individual under the age of 16 at the time of the offence (N = 5341). […]

The sample consisted of

• 211 (61.9%) intra-familial child molesters and
• 130 (38.1%) extra-familial child molesters.”

“The participants were assessed at a university teaching hospital in a large Canadian city between 1982 and 1992. If police records indicated that a participant had ever offended against an adult, they were excluded from the analyses.”

Measures

“Static 99 … is a brief actuarial instrument designed to predict the long-term probability of sexual recidivism among adult male sexual offenders.”

“Bradford Sexual History Inventory. … This inventory, which is completed by participants during an initial psychiatric interview, consists of 81 items grouped into nine categories and inquires about an individual’s sexual activity. For this study, questions pertaining to pornography use were of importance. Specifically, individuals were asked to rate the frequency with which they had viewed sexually explicit films and/or books over the course of their lifetime. [… ….]

Next, the individuals responded to a question concerning the type of pornography used and response categories were

(1) heterosexual sex,
(2) homosexual sex,
(3) lesbian sex,
(4) children engaged in sexual activity, and
(5) depictions of violence. […]

Deviance was defined as any self-reported use of pornography containing children and/or violence.”

Recidivism analyses

The dependent measures in this study were organized in a cumulative hierarchical manner, beginning with a comprehensive category that included all types of recidivism, followed by more specific categories of recidivism.[…] This cumulative hierarchical approach allows for the inclusion of sexually motivated offenses that were ‘‘pled down’’ to violent or criminal offences as many sexual offenders would rather admit to any offence other than a sexual offence. […]

 The subcategories were as follows:
(1) All criminal recidivism […]
(2) violent (including sexual) recidivism […]
(3) sexual recidivism.”

 “The overall rates of recidivism in this study were

• 31.7% for criminal recidivism,
• 21.4% for violent recidivism, and
• 11.1% for sexual recidivism.

 The recidivism rates for the intra-familial child molesters were 24.2%, 17.1%, and 8.1%, for criminal, violent, and sexual offences, respectively.

The recidivism rates for the extra-familial child molesters were 43.8%, 28.5%, and 16.2%, for criminal, violent, and sexual offences, respectively.

The follow-up period was assessed on release to the community and ranged up to 15 years, with an average of 8.4 years …”

Statistical Analyses

“For this study, sequential logistic regression analyses were conducted to analyze the relationship between pornography use and recidivism and to address the possibility that an individual’s risk level would be a moderator of this relationship.

 To address the strength of the relationships in these analyses, Cohen’s d and odds ratios were reported. By convention, Cohen’s d effect sizes of .20, .50, and .80 are small, medium, and large, respectively [… … …]

 Odds ratios, as reported in the regression analyses, can be interpreted as the increase or decrease in the predicted odds of recidivism, which corresponds to an increase of one point on the predictor variable (e.g., frequency of pornography use), or in the case of a dichotomous predictor (i.e., deviant pornography), the odds of recidivism in one group compared with the other. An odds ratio of 1 reflects no relationship between a predictor and a outcome.

A series of sequential logistic regression analyses were conducted for each dependent measure to test the importance of the conditional-probability approach described by the HMC model in general and examining risk to re-offend, as a moderator between pornography use and recidivism, in particular.
Specifically, pornography and risk level were entered as independent variables.”

 Results

All Criminal Recidivism

“Static 99 score made a significant contribution to the prediction of all recidivism (…), but frequency of pornography use did not (…). The interaction between risk level and pornography use was significant (…), suggesting that the relationship between pornography use and recidivism was different across levels of risk.”

Violent (Including Sexual) Recidivism

“Static 99 risk level made a significant contribution to the prediction of violent (including sexual) recidivism. … The addition of pornography use made a significant contribution to recidivism, after controlling for Static 99 risk level (…). […] The pornography by Static 99 risk-level interaction was significantly associated with the prediction of recidivism (…), suggesting that the relationship between pornography use and recidivism was different across levels of risk.”

Sexual Recidivism

“Static 99 risk level made a significant contribution to the prediction of sexual recidivism. Frequency of pornography use was added … and did not make a significant contribution to the prediction of sexual recidivism, after controlling for Static 99 risk level (…). The interaction between Static 99 and pornography use was also not significant (…).”

Interaction Between Pornography and Risk to Re-Offend

“The above analyses provided support for the hypothesis that propensity toward sexual aggression moderates the relationship between pornography use and aggression […]. To further examine these interactions, effect sizes were displayed across Static 99 risk categories (i.e., the redefined low, medium, and high-risk categories) and examined with respect to frequency of pornography use (using the 1–8 scale).”

Fig. 1.
Relationship between frequency of pornography use (continuous) and recidivism, as a function of risk to commit sexual aggression.

• kingston_a.o._figure_1.pdf

“The effect sizes shown in Figure 1 highlight the interaction indicated in the previous analyses, such that

• individuals assessed as low risk (…) demonstrated small associations between criminal (…), violent (…), sexual (…) recidivism, and the frequency of pornography use.
• Individuals assessed as medium risk (…) demonstrated small but elevated associations between frequency of pornography and criminal (…), violent (…), and sexual (…) recidivism.
• Finally, individuals assessed as high risk in our analysis (…) demonstrated moderate to large effect sizes between frequency of pornography use and criminal (…), violent (…), and sexual (…) recidivism.

      […] There were significant differences between individuals assessed as high risk and low risk for criminal and violent recidivism.” 

Additional Analyses Regarding Pornographic Content

Of the 341 child molesters in this study, 337 responded to questions pertaining to type of content. Among these individuals

• 303 (90%) reported viewing only non-deviant pornography, whereas
•     34 (10%) indicated viewing deviant [*] pornography.

[* Deviant pornography is here above defined as “any self-reported use of pornography containing children and/or violence.”]

 The use of deviant pornography was unrelated to risk level (…). Given the few participants within the recidivist categories, caution is warranted when interpreting these results. Nevertheless, to highlight possible trends, a series of logistic regression analyses were conducted to test for possible interactions between the three-level hierarchical risk variable and the two-level type of content variable on the dependent measures.

With regard to criminal recidivism, risk level made a significant contribution to the prediction of recidivism (…). The addition of pornography content into the equation was significant, after considering risk level (…). The odds ratio indicated that for individuals who viewed deviant pornography, the predicted odds of criminal recidivism increased by 177% when compared with those who did not view deviant pornography.

 The interaction between risk level and type of pornography was not significant (…). In terms of violent (including sexual) recidivism, risk level made a significant contribution to the prediction of recidivism (…). The addition of type of pornography was significant, after controlling for risk level (…).

The odds ratio indicated that for individuals who viewed deviant pornography, the predicted odds of violent (including sexual) recidivism increased by 185% when compared with those who did not view deviant pornography. The interaction between risk level and type of pornography was not significant (…).

Finally, both risk level (…) and pornography content (…) made significant contributions to the prediction of sexual recidivism (…).

The odds ratio indicated that for individuals who viewed deviant pornography, the predicted odds of sexual recidivism increased by 233% when compared with those who did not view deviant pornography. The interaction between these variables was not significant (…).

 Discussion

“The purpose of this study was to examine the relationship between pornography and aggressive behavior within the context of an important moderating variable — that is, risk to re-offend […]. […]

The results of this study supported the utility of pornography as a predictor of aggression, when examined in confluence with other general and specific risk factors for aggression.

We examined the impact of

• frequency of pornography use on the overall comprehensive measure of criminal recidivism, as well as
• the more specific categories of violent (including sexual) recidivism and
•  sexual recidivism only.

Results indicated that the frequency of pornography use contributed to the prediction of criminal and violent recidivism, while taking other risk factors for sexual aggression into account.

Follow-up analyses indicated that the interaction between pornography and risk to reoffend was consistent with the conditional-probability model outlined in the HMC model. Specifically, we found that among men who scored high on general and specific risk characteristics, frequent pornography consumption increased the risk for aggression. In contrast, amount of pornography use had little predictive value for men assessed to be at low risk for sexual aggression. […]

“Pornography activates and reinforces inappropriate cognitive representations (e.g., hostility toward women) and fosters the development of sexual preoccupation in these [high-risk] men.” […]

“Of note, the main effects and interactions between frequency of pornography use and sexual recidivism were not significant.” […]

Results indicated that the frequency of pornography use contributed to the prediction of criminal and violent recidivism, while taking other risk factors for sexual aggression into account.

Follow-up analyses indicated that the interaction between pornography and risk to reoffend was consistent with the conditional-probability model outlined in the HMC model. Specifically, we found that among men who scored high on general and specific risk characteristics, frequent pornography consumption increased the risk for aggression. In contrast, amount of pornography use had little predictive value for men assessed to be at low risk for sexual aggression.

The predictive utility of pornography use among high risk, as opposed to low-risk individuals, has been explained by social learning theory in general, and the notion of reciprocal determinism, defined as the interaction between person, behavior, and environment, in particular.” […]

“Pornography activates and reinforces inappropriate cognitive representations (e.g., hostility toward women) and fosters the development of sexual preoccupation in these [high-risk] men.” […]

“Of note, the main effects and interactions between frequency of pornography use and sexual recidivism were not significant.”[…]

“Importantly, however, the interaction was significant for violent (including sexual) recidivism, which we feel is a better representation of the influence of pornography on sexually aggressive behavior. [… …]

The significant interaction found among violent (including sexual) recidivists in our study [… indicates] that individual risk is an important variable moderating the relationship between pornography and sexual aggression.”

“Next, we examined the degree to which self-reported use of deviant pornography was predictive of the overall comprehensive measure of criminal recidivism, as well as the more specific categories of violent (including sexual) recidivism and sexual recidivism.

Results supported a main effect of pornographic content, after controlling for general and specific risk characteristics, as contained in the Static 99. Specifically, results indicated that individuals who viewed deviant pornography were more likely to recidivate when compared with individuals who did not view deviant pornography and this difference was consistent across levels of risk (i.e., no interactions).”

“Importantly, however, the interaction was significant for violent (including sexual) recidivism, which we feel is a better representation of the influence of pornography on sexually aggressive behavior. [… …]

The significant interaction found among violent (including sexual) recidivists in our study [… indicates] that individual risk is an important variable moderating the relationship between pornography and sexual aggression.”

“There is a growing body of literature investigating the impact of exposure to deviant pornography on attitudes supportive of

• sexual aggression […],
• physiological arousal to sexual aggression […], and 
• actual aggressive behavior

among non-offenders […].

Thus far, results have generally supported the negative impact from viewing deviant pornography on these outcome measures and our findings were consistent with such results.
Both observational learning and conditioning processes suggest that repeated exposure to deviant forms of pornography, given the focus on male entitlement and power, help shape an individual’s fantasies, perceptions, rationalizations, and deeper core beliefs […].

It is important to note that such development is most likely multifaceted and that pornography may simply accelerate a process that is already underway […].

Of equal importance, however, is that the impact of deviant pornography on behavior was consistent across levels of risk. This suggests that

• exposure to unconventional sexual activity fosters the progression toward reoffending, regardless of the earlier existence of historical risk factors.
• In contrast, frequency of pornography use, as indicated above, was a predictor for individuals already possessing such a predisposition toward re-offending.”

[Limitations]

“Several issues must be considered when interpreting these results.

First, the assessment of pornography was problematic, as it was based solely on self-report and required individuals to recall information over the course of their lifetimes. Regarding the first point, individuals undergoing assessment in a forensic setting are sometimes reluctant to be forthcoming with information, especially when such information could have negative consequences for their evaluation. This type of limitation is consistently identified in forensic research […].

Additionally, individuals were asked to recall information spanning much of theirlifetime and problems with adequate retrieval of early events may have influenced the results.

A final problem regarding the assessment of pornography use pertained to the type of pornographic stimuli examined. In other words, the type of pornography involved films and/or books and thus neglected Internet pornography.

Unfortunately, given the dates of assessment (1982–1992), this was not possible and future research should examine similar questions pertaining to individuals who use the Internet to obtain sexually explicit material.”

“In spite of these limitations, this current research supported and extended the results reported by other studies with noncriminal sexual aggressors indicating that pornography exposure was a significant predictor of aggression when examined in confluence with other risk factors.

Specifically, this study highlighted the importance of considering various interactive factors that can act synergistically in determining the probability for a particular behavioral outcome. The important implications of the cumulative-conditional-probability conceptualization, as described in research investigating the HMC [Malamuth et al., 2000], is not limited to pornography use but has important implications for examining the complex relationships between distal and proximal factors as predictors of sexual aggression.”