Editorial: New directions in forensic psychology: applying neuropsychology, biomarkers and technology in assessment & intervention
Bibliographic record
Abstract
diversity of the submissions, which mirrors the widespread global interest in cutting-edge diagnostic and therapeutic options in forensic mental health care.The collection is organized into four thematic sections: neuropsychology and neurofeedback, wearables, qualitative VR studies, and quantitative VR studies. The following sections provide a concise overview of the respective papers included. They found that the training was rated sufficiently usable and feasible by patients and their therapists. Given the emergence of neurotechnological applications in forensic psychiatry and criminal law more broadly, such as the above-described neurofeedback treatment, there is a call for the implementation of so-called neurorights. Díaz Soto & Borbón evaluated the status of this matter and concluded that, although the interpretation of the current human rights should be made in such a way as to protect the dignity of the accused or client, new neurorights may offer reduced protection of human rights.Two notable studies investigated the role of wearable technology in forensic psychiatry. De Looff et al. conducted a randomized crossover trial to evaluate the usability and acceptance of four wearable devices among forensic psychiatric patients and staff. Their findings revealed that while fitness trackers like Fitbit and Garmin were more user-friendly, none of the devices met international usability standards, highlighting the need for improved gamification and motivational features. In a complementary study, Ter Harmsel et al. assessed the Sense-IT bio cueing app's effectiveness when added to Aggression Regulation Therapy (ART) for forensic outpatients. Although the app increased interoceptive awareness in most participants, its impact on aggression and emotion regulation was inconsistent.These studies contribute valuable insights into the forensic field, emphasizing the potential of wearable technology to enhance therapeutic outcomes. Key lessons include the critical importance of usability, personalized interventions, and seamless integration into therapy for successful adoption. Both studies demonstrate solid methodologies, though limitations such as small sample sizes and the need for better algorithm validation highlight areas for future improvement. Overall, these studies underscore the necessity of tailoring technology-based interventions to individual needs for effective forensic psychiatric treatment.The implementation of Virtual Reality in forensic psychiatric treatment is relatively new. Whereas VRAPT and Triggers and Helpers are blended applications in which roleplaying assists patients in improving awareness and social skills, e.g., reduction of aggressive behavior, DEEP is an application in which a patient practices deep breathing in a gamified biofeedback underwater world.These three studies used interviews to explore the participants' experiences and seek answers to the questions of for whom and when these applications are helpful in forensic psychiatric treatment. In the DEEP study, the authors sought answers to which application method would suit whom best. Apart from suggestions on improving immersiveness, ideas on implementing DEEP in clinical practice emerged. The study by Kouijzer and colleagues focused on implementation and used Triggers and Helpers as a showcase. Patient characteristics must be considered when deciding to whom this method should be offered, and continuously assisting clinicians when they use VR seems a vital necessity. The Swedish qualitative evaluation of patients' experience with VRAPT also highlighted the need to thoroughly implement innovative treatments such as VR and personalize treatment goals for which VR can be used.There were six quantitative studies, most from Europe (the Netherlands, Sweden) and one from Canada. All studies except one tested different VR interventions in clinical forensic settings, while one investigated a chatbot developed for risk assessment training. Given the state of the field, the quantitative studies overall had a feasibility and effect approach and described interventions with the need for continued development and evaluation. Common findings were that all users' attitudes towards technology-driven interventions were generally positive and that outcomes depended on successful implementation in interventional settings.Several studies focused on the treatment of aggression regulation for either forensic psychiatric patients or imprisoned offenders, evaluating either a method specifically designed for VR-assisted treatment only (Virtual Reality Aggression Prevention Training) or comparing outcomes from a treatment (Responsive Aggression Regulation Therapy) being delivered either in virtual environments or in real life settings. The results of the two studies presenting longitudinally followed outcomes over time were promising, with decreased levels of anger, aggression, and emotion regulation maintained over follow-up. Two studies focused on assessment, both with an experimental design, where one investigated the feasibility of paranoia assessment in virtual environments, and the other determined acceptance and trust of students on chatbot-assisted risk assessment training. For both studies, not only the technology but also the user characteristics seemed necessary for the usefulness of the assessment. So far, we cannot replace standard training and assessment with technologydriven versions. Finally, a study used a VR-based intervention to prepare forensic psychiatric patients for authorized leave, and the potential of VR to increase patient motivation and reduce stress was evident.In summary, many of the quantitative studies on this special issue benefited from the characteristics of VR, which facilitates exposure to specific environments in preparation for real-life occurrences. However, it is evident that much is left to investigate and that further developments, especially concerning individual tailoring, are needed. The current findings can guide clinicians and researchers in forensic settings in their coming ventures on these matters.The collective insights from the 15 papers featured in our special issue highlight the transformative potential of integrating neuropsychology, biomarkers, and advanced technology into forensic psychology. Through diverse methodologies, these studies illustrate how neuropsychological assessments, wearable devices, and virtual reality (VR) interventions can enhance diagnosis, treatment, and overall therapeutic outcomes in forensic populations. Key lessons from these studies include the importance of feasibility and usability in implementing new technologies. For instance, neuromodulation and neurofeedback have shown initial promise in addressing impulse control issues, but practical challenges must be addressed to ensure broader application. Similarly, using wearables, while beneficial in some cases, reveals that user engagement and device adaptability are crucial for sustained success.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.018 | 0.016 |
| Insufficient payload (model declined to judge) | 0.022 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".