Child pornography and the internet

Patterns of risk-Using machine learning and structural neuroimaging to identify pedophilic offenders

Background

Child sexual abuse (CSA) has become a focal point for lawmakers, law enforcement, and mental health professionals. With high prevalence rates around the world and far-reaching, often chronic, individual, and societal implications, CSA and its leading risk factor, pedophilia, have been well investigated. This has led to a wide range of clinical tools and actuarial instruments for diagnosis and risk assessment regarding CSA. However, the neurobiological underpinnings of pedosexual behavior, specifically regarding hands-on pedophilic offenders (PO), remain elusive. Such biomarkers for PO individuals could potentially improve the early detection of high-risk PO individuals and enhance efforts to prevent future CSA.

Aim

To use machine learning and MRI data to identify PO individuals.

Methods

From a single-center male cohort of 14 PO individuals and 15 matched healthy control (HC) individuals, we acquired diffusion tensor imaging data (anisotropy, diffusivity, and fiber tracking) in literature-based regions of interest (prefrontal cortex, anterior cingulate cortex, amygdala, and corpus callosum). We trained a linear support vector machine to discriminate between PO and HC individuals using these WM microstructure data. Post hoc, we investigated the PO model decision scores with respect to sociodemographic (age, education, and IQ) and forensic characteristics (psychopathy, sexual deviance, and future risk of sexual violence) in the PO subpopulation. We assessed model specificity in an external cohort of 53 HC individuals.

Results

The classifier discriminated PO from HC individuals with a balanced accuracy of 75.5% (sensitivity = 64.3%, specificity = 86.7%, P ₅₀₀₀ = 0.018) and an out-of-sample specificity to correctly identify HC individuals of 94.3%. The predictive brain pattern contained bilateral fractional anisotropy in the anterior cingulate cortex, diffusivity in the left amygdala, and structural prefrontal cortex-amygdala connectivity in both hemispheres. This brain pattern was associated with the number of previous child victims, the current stance on sexuality, and the professionally assessed risk of future sexual violent reoffending.

Conclusion

Aberrant white matter microstructure in the prefronto-temporo-limbic circuit could be a potential neurobiological correlate for PO individuals at high-risk of reoffending with CSA. Although preliminary and exploratory at this point, our findings highlight the general potential of MRI-based biomarkers and particularly WM microstructure patterns for future CSA risk assessment and preventive efforts.

Philosophical issues in the paraphilias

PURPOSE OF REVIEW

Controversies surrounded the development of paraphilias in the Diagnostic and Statistical Manual of Mental Disorders (DSM) 5. This review examines the philosophical issues that emerge from an analysis of those debates and current literature.

RECENT FINDINGS

The resolution of controversies in the publication of the DSM 5 drew upon the available evidence, theories of mental disorder, and normative assumptions. The rise of the Internet presents difficult challenges in this field.

SUMMARY

Numerous philosophical assumptions underlie the psychiatric understandings of paraphilias. The focus here is on the nosological issues such as boundary justification for the determinations of normative and nonnormative human sexuality; the importance of not collapsing the distinction between mental disorder and crime, and the relationship between fantasy and action; epistemological questions of perspectivity, reasons-giving, and relationship of communication to truth claims; and sex differences not only in the paraphilias but also in the social context in which sex is formed and given expression.