Although in principle the legal system expects and professional ethics demand that expert witnesses be unbiased and objective in their forensic evaluations, anecdotal evidence suggests that accusations of financial bias, partisanship, and other forms of nonobjectivity are common. This descriptive survey of published legal cases expands on an earlier case law review (Mossman, 1999) attempting to encapsulate and summarize key issues concerning perceptions or allegations of bias in mental health expert witness testimony. Using a series of search terms reflecting various potential forms of accusatory bias, a total of 160 published civil and criminal court cases were identified in which 185 individuals (e.g., attorneys, trial and appellate judges, other witnesses) made one or more references to clinicians' alleged lack of neutrality. Allegations most typically involved describing the expert as having an opinion that was "for sale," or as a partisan or advocate for one side, although aspersions also were made concerning "junk science" testimony and comparing mental health experts to mystics and sorcerers. Our results indicate that diverse forms of bias that go beyond financial motives are alleged against mental health experts by various players in the legal system. Means are discussed by which experts can attempt to reduce the impact of such allegations.
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http://dx.doi.org/10.1037/a0028264 | DOI Listing |
J Neural Transm (Vienna)
January 2025
Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Tianjin, 300222, China.
Bipolar disorder (BD) frequently coexists with anxiety disorders, creating complex challenges in clinical therapy and management. This study investigates the prevalence, prognostic implications, and treatment strategies for comorbid BD and anxiety disorders. High comorbidity rates, particularly with generalized anxiety disorder, underscore the necessity of thorough clinical assessments to guide effective management.
View Article and Find Full Text PDFJ Immigr Minor Health
January 2025
Watson Institute for International and Public Affairs and the School of Public Health, Brown University, Providence, USA.
Eur J Hum Genet
January 2025
Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India.
Mitochondrial membrane protein-associated neurodegeneration (MPAN) is a rare neurodegenerative disorder characterized by spastic paraplegia, parkinsonism and psychiatric and/or behavioral symptoms caused by variants in gene encoding chromosome-19 open reading frame-12 (C19orf12). We present here seven patients from six unrelated families with detailed clinical, radiological, and genetic investigations. Childhood-onset patients predominantly had a spastic ataxic phenotype with optic atrophy, while adult-onset patients were presented with cognitive, behavioral, and parkinsonian symptoms.
View Article and Find Full Text PDFJ Occup Rehabil
January 2025
Faculty of Health Sciences, Curtin School of Allied Health, Curtin University, Perth, WA, Australia.
Purpose: Workers' compensation claims can negatively affect the wellbeing of injured workers. For some, these negative effects continue beyond finalisation of the workers' compensation claim. It is unclear what factors influence wellbeing following finalisation of a workers' compensation claim.
View Article and Find Full Text PDFCommun Psychol
January 2025
Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
How do people model the world's dynamics to guide mental simulation and evaluate choices? One prominent approach, the Successor Representation (SR), takes advantage of temporal abstraction of future states: by aggregating trajectory predictions over multiple timesteps, the brain can avoid the costs of iterative, multi-step mental simulation. Human behavior broadly shows signatures of such temporal abstraction, but finer-grained characterization of individuals' strategies and their dynamic adjustment remains an open question. We developed a task to measure SR usage during dynamic, trial-by-trial learning.
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