Forensic Sciences
[Abbr: Acd. Jr. AJFSc]Predicting Unconscious Violence: Behavioral Analysis and Threat Assessment
by Haque, Bidisha
This study proposes and evaluates the Unconscious Violence Risk Index (UVRI), a novel threat assessment model combining behavioral and environmental indicators with machine learning to predict violent acts committed without conscious intent. Unconscious violence—aggressive acts precipitated by acute intoxication, medical conditions, or traumatic stress—is poorly captured by traditional tools. Despite extensive use of instruments like the Historical-Clinical-Risk Management-20 (HCR-20) and the Psychopathy Checklist–Revised (PCL-R) in violence risk assessment ("Structured Professional Judgment Tools"), existing methods focus on conscious intent and static traits (e.g. past violence, psychopathy) and often ignore dynamic emotional or situational cues (Ling et al. 55). In response, we developed the UVRI to integrate indicators such as acute distress, physiological dysregulation, and social isolation. In a mixed-methods study (N≈300 forensic/psychiatric clients), coded behavioral interviews and records were used to train a supervised ML model. The UVRI demonstrated superior predictive validity (AUC≈0.85) compared to HCR-20 (≈0.70) and PCL-R (≈0.65) in classifying risk of unconscious violent episodes. Sensitivity and specificity exceeded 0.80. Key predictive features included emotional dysregulation, trauma history, and contextual stressors, aligning with findings that emotion regulation deficits mediate stress-related aggression (Herts et al. 1111). Qualitative interviews revealed themes of sudden loss of control and unintentional harm (e.g. "I didn't even know I was hurting anyone"), underscoring complex subjective experiences. These results suggest that UVRI's fusion of behavioral analysis and ML enhances early detection of latent violence risk, with potential to improve preventive interventions. Implications for forensic practice, ethical considerations of automated risk prediction, and avenues for refining dynamic threat assessment are discussed.
AI-Assisted Psychodrama for Emotional Mapping in Offenders with Antisocial and Borderline Traits: A Mixed-Methods Pilot Study
by Haque, Bidisha
Understanding implicit emotional processes in individuals with antisocial or borderline traits remains a central challenge in forensic psychology. This mixed-methods pilot study evaluated an integrative framework combining psychodrama-based experiential therapy with AI-driven behavioral analytics in forensic and community samples. Eighty participants (40 offenders with documented antisocial or borderline traits and 40 controls) completed structured psychodrama role-plays under “emotionally charged” and “neutral” conditions. During sessions, multimodal AI tools (facial action coding, voice prosody analysis, and movement tracking) quantified implicit affective markers – emotional variability, facial micro-expression frequency, and interpersonal synchrony. Participants also completed standardized measures (Difficulties in Emotion Regulation Scale [DERS][1], Interpersonal Reactivity Index [IRI], Positive and Negative Affect Schedule [PANAS]) and provided written reflections. In quantitative analyses, forensic participants showed higher emotion dysregulation (DERS) and lower trait empathy (IRI empathic concern) than controls (p
Exploring the Effect of Mode of Crime - Online vs. Offline on Detection of Deception by Eye Detect System (EDS)
by Rohini Kumar
The present study aimed to explore the effect of the mode of crime, online versus offline, on the detection of deception by the Eye Detection Test (EDS) from a forensic psychological perspective. Participants were divided into two groups: Group A, instructed to commit a mock crime offline and lie during the EDS test, and Group B, instructed to commit a mock crime online via a social media platform (Instagram) and lie during the EDS test. Sampling was conducted using a random sampling method, resulting in a total of 12 participants divided equally between the two groups. Participants were tasked with performing the mock crime within a specified time frame and were subsequently evaluated using the EDS test. Analysis of the collected data suggests that the Eye Detection Test is efficient in detecting various types of deception. Given the limited existing research in this area, there is significant scope for further investigation. This research could potentially aid in preventing the wrongful punishment of innocent individuals who may falsely confess under pressure.
Forensic Radiology In Death Investigations
by Nisruti Anuja Behura
Forensic radiology is a new and a developing technique which combines medical imaging and forensics to aid death investigation. In the last 20 years, the development of imaging technologies has provided the possibility of studying the dead person, especially by means of Post Mortem Computed Tomography (PMCT) and Post Mortem Magnetic Resonance imaging (PMMRI). Forensic radiology helps solve legal cases by using imaging to identify victims, detect injuries from accidents or abuse, and analyze things like bite marks or dental patterns. It’s also used to estimate age and identify people through unique skull features like the frontal sinuses. The complex skeletal radiological process such as the study of hand-wrist bones, clavicle, bone pelvis, etc enables precise age and sex identification particularly in scenarios where there is skeletal remains. Imaging using X ray, CT scan, MRI, post mortem angiography and virtual autopsy (Virtopsy) aids in high-resolution inner investigations, 3D reproductions and wound documentations. Forensic radiology has strengths, such as, being culturally sensitive, complete, non-invasive, and having permanent digital records. But it has issues which are a high cost of access, restricted accessibility and special labor requirements. Ethical issues are consent, confidentiality, and respect of culture. Recent surveys have also indicated increasing appreciation of forensics radiology via the digital mediums although there is no formal training. The effective and widespread application of forensic radiology in such countries as India necessitates reasonable investments, interagency collaboration, and national standards to make the best of it in terms of medicolegal investigations.