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.

A comparison of the predictive accuracy of structured and unstructured risk assessment methods for the prediction of recidivism in individuals convicted of sexual and violent offense.

One of the most commonly replicated results in the research area of recidivism risk assessment is the superiority of structured and standardized prediction methods in comparison to unstructured, subjective, intuitive, or impressionistic clinical judgments. However, the quality of evidence supporting this conclusion is partly still controversially discussed because studies including direct comparisons of the predictive accuracy of unstructured and structured risk assessment methods have been relatively rarely conducted. Therefore, we examined in the present study retrospectively N = 416 expert witness reports written about individuals convicted of violent and/or sexual offenses in Germany between 1999 and 2015. The predictive accuracy of different methodological approaches of risk assessment (subjective clinical [i.e., unstructured clinical judgment; UCJ], structured professional judgment [SPJ], actuarial risk assessment instruments [ARAIs], and combinations of ARAIs-/SPJ-based risk assessments) was compared by analyzing the actual reoffenses according to the Federal Central Register (average follow-up period M = 7.08 years). In accordance with previously published results, the results indicated a higher predictive accuracy for structured compared to unstructured risk assessment approaches for the prediction of general, violent, and sexual recidivism. Taken together, the findings underline the limited accuracy of UCJs and provided further support for the use of structured and standardized risk assessment procedures in the area of crime and delinquency. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

[Response distortion or symptom severity? Symptom description by psychiatric patients and sociomedical assessment subjects]. / Antwortverzerrung oder Symptombelastung? Beschwerdeschilderung von psychiatrischen Patienten und sozialmedizinischen Begutachtungsprobanden.

BACKGROUND: Psychiatric disorders are the most frequent cause for premature retirement; however, trying to verify claims of performance deficits due to psychiatric disorders without the actual existence of the latter in sociomedical assessments is problematic. For this reason, differentiation between actual psychiatric disorders with real presence of symptoms and simulated or aggravated symptoms is of importance in sociomedical assessments. In recent years, symptom validity tests (SVT) have been increasingly utilized in psychiatric/psychological assessments; however, knowledge of the validity of these tests and the relation to symptom severity is still lacking. OBJECTIVE: This study aimed to compare the validity of different SVTs depending on symptom severity (Structured Inventory of Malingered Symptomatology (SIMS), Word Memory Test (WMT), Symptom Checklist-90-R (SCL-90­R), Minnesota Multiphasic Personality Inventory­2 (MMPI-2)). MATERIAL AND METHODS: Clinically treated inpatient psychiatric patients (n = 30) were compared with subjects of sociomedical assessments (n = 29) regarding their tendency to simulate or aggravate symptoms. RESULTS: It could be shown that the WMT and the SIMS both failed in the differentiation between psychiatric patients and subjects of sociomedical assessments, regarding description of symptoms or (un)restricted performance motivation. Furthermore, 20% of psychiatric patients were classified as false positive in WMT. The results of the SIMS were significantly related to the severity of psychiatric symptoms in SCL-90­R, therefore the severity of symptoms was assessed rather than the response distortion. CONCLUSION: The results underline the importance of further research on SVTs in sociomedical assessments, especially regarding symptom severity and response distortion.