Journal of the American Academy of Psychiatry and the Law最新文献

Generative artificial intelligence (AI), with its increasing ubiquity and power, will likely transform forensic psychiatry, sparking both advances and new challenges for the field. A possible consequence of the technology is that it will be used to assist malingerers in learning about and feigning psychiatric symptoms. In this study, the AI chatbot ChatGPT was asked to provide information about the insanity defense and psychosis and to use this information to assist the user in simulating a psychotic illness to avoid legal consequences. We found that ChatGPT 3.5 demonstrated a relatively nuanced understanding of typical symptoms of psychosis and that it could translate that knowledge into practical guidance on how to exploit the mental health system for secondary gain. Our findings suggest that, although significant limitations exist with the technology in its current form, forensic psychiatrists should be prepared for its increasing sophistication and the potential consequences in malingering assessments.

This study examined predictors of child and parent offender removal from the home following substantiated incidents of child neglect in U.S. Army families. Case records (n = 390) were coded to identify neglect types and incident characteristics associated with removal in prior studies. Results indicate that the removal of a child and the removal of a parent from the home following an incident of neglect are associated with distinct neglect types and incident characteristics. In bivariate analyses, failure to provide physical needs (FTP), family mental health problems, and co-occurring abuse were each associated with higher odds of child removal. In multivariate analyses, offender substance use, co-occurring abuse, and early parenting, but not FTP, were associated with child removal. Interaction models indicated that high-severity FTP incidents in families with mental health problems were more likely to result in child removal compared with other neglect incidents. In contrast, incidents involving emotional neglect and service member offenders were associated with higher odds of parent removal. Findings advance understanding of the characteristics of neglect incidents associated with family separations, which can improve the judiciousness of legal decisions regarding removal actions and inform prevention efforts that effectively protect children from harm while minimizing disruptions to family integrity.

Generative artificial intelligence (AI), including the large language model ChatGPT, has introduced potential new opportunities and challenges to the practice of forensic psychiatry. These powerful AI-based tools may offer substantial benefits in administrative tasks, report generation, and record summarization yet simultaneously present areas for further consideration, such as aiding evaluees in feigning psychiatric symptoms. Additional ethics and legal considerations exist regarding privacy, bias within AI models, and the introduction of fabricated or misleading AI-generated content into forensic assessments. Legislative efforts, privacy safeguards, and professional guidelines essential for responsible AI use are being developed. Forensic psychiatrists are uniquely positioned to influence responsible AI integration through education, advocacy, and development of best practices within psychiatry.

Forensic mental health professionals are often provided with aspirational guidelines to inform their practice; however, disparities exist between what such professionals should strive to do and what they actually do. This article considers pathways to improving practice not only in terms of knowledge base but also in terms of ethics, skills, and intellectual, dispositional, and interpersonal qualities. Obstacles are identified that could prevent forensic mental health professionals from practicing at higher levels of excellence.

In 2020, cognitive neuroscientist Itiel Dror developed a cognitive framework to address biases influenced by cognitive processes and external pressures in decisions made by forensic experts. Dror's model highlights how ostensibly objective data, such as toxicology or fingerprints, can be affected by bias driven by contextual, motivational, and organizational factors. Forensic mental health evaluations, often more subjective than physical forensic evidence analysis, are particularly vulnerable to these cognitive biases. Dror identified six expert fallacies, such as the belief that bias only affects unethical or incompetent practitioners, and proposed a pyramidal model showing how biases infiltrate expert decisions. This article adapts Dror's model to forensic mental health, exploring how biases influence data collection and interpretation and proposing mitigation strategies like Linear Sequential Unmasking-Expanded (LSU-E). We emphasize that mitigating cognitive biases requires structured, external strategies, as self-awareness alone is insufficient. By applying Dror's concepts and framework, we offer a practical approach to reduce biases and improve the fairness and accuracy of forensic mental health assessments.

Medical students have limited exposure to correctional health, and their attitudes toward inmates are understudied. We investigated medical students' attitudes toward inmates, assessing whether an intervention can improve their understanding of the correctional system and help them develop more positive attitudes toward inmates. One hundred thirty third-year medical students at the University of Ottawa attended a one-hour lecture on correctional health and adverse childhood experiences (ACEs) and subsequently observed a three-hour correctional telepsychiatry clinic during their clerkship psychiatry rotation. Students completed a preintervention and postintervention questionnaire that included a modified 20-item Attitudes Toward Prisoners (ATP) scale (quantitative) and feedback questions (qualitative). Of 130 students who completed the preintervention questionnaire, 106 completed the postintervention questionnaire (81.5%). Students' mean total modified ATP scores increased significantly after our intervention, from 72.8 to 78.4 (p < 001). Fourteen of 20 ATP items increased significantly, reflecting greater understanding of the correctional system and more positive attitudes toward inmates. Thematic analysis of qualitative feedback revealed students gained a better understanding of the correctional system and increased comfort treating inmates. Scarce criticism included minimal interactivity and a desire for more sessions. Although students perceived benefits, further research is required to determine its educational significance.