Objective: Very few studies have quantified the level of agreement among alternative diagnostic procedures that use a common set of fixed operational criteria. The authors examined the procedural validity of four independent methods of assigning DSM-III-R diagnoses of psychotic disorders.
Method: The research was conducted as a satellite study to the DSM-IV Field Trial for Schizophrenia and Related Psychotic Disorders. The setting was the National Health and Medical Research Council Schizophrenia Research Unit's Early Psychosis Prevention and Intervention Centre, which focuses on first-episode psychosis. Consecutively admitted patients (N = 50) were assessed by independent raters who used four different procedures to determine a DSM-III-R diagnosis. These procedures were 1) the diagnostic instrument developed for the DSM-IV field trial, 2) the Royal Park Multidiagnostic Instrument for Psychosis, 3) the Munich Diagnostic Checklists, and 4) a consensus DSM-III-R diagnosis assigned by a team of clinician researchers who were expert in the use of diagnostic criteria.
Results: Concordance between pairs of diagnostic procedures was only moderate. Corresponding levels of percent agreement, however, ranged from 66% to 76%, with converse misclassification rates of 24%-34% (assuming one procedure to be "correct").
Conclusions: These findings have significant research and clinical implications. Despite the introduction of operationally defined diagnoses, there remained an appreciable level of differential classification or misclassification arising from variability in the method of assigning the diagnostic criteria rather than the criteria themselves. Such misclassification may impede neurobiological research and have harmful clinical effects on patients with first-episode psychosis.
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http://dx.doi.org/10.1176/ajp.152.2.220 | DOI Listing |
JMIR Form Res
January 2025
Department of Psychology, The University of Texas at San Antonio, San Antonio, TX, United States.
Background: Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists use personalized and high-dimensional visual search strategies, otherwise known as search patterns. Qualitative descriptions of these search patterns, which involve the physician verbalizing or annotating the order he or she analyzes the image, can be unreliable due to discrepancies in what is reported versus the actual visual patterns.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Shanghai Institute of Early Childhood Education, Shanghai Normal University, Shanghai, China.
Background: Parental technoference, the interruption of parent-child interactions by technology, has been associated with negative outcomes in children's media use. However, the magnitude of this relationship and its moderating factors remain unclear.
Objective: This study aims to systematically examine the relationship between parental technoference and child problematic media use, as well as to identify moderating factors such as age, parental technoference group, study design, and type of problematic media use.
Neurology
February 2025
Schools of Pharmacy and Public Health Sciences, University of Waterloo, Ontario, Canada.
Background And Objectives: Peripartum mood and anxiety disorders constitute the most frequent form of maternal morbidity in the general population, but little is known about peripartum mental illness in mothers with multiple sclerosis (MS). We compared the incidence and prevalence of peripartum mental illness among mothers with MS, epilepsy, inflammatory bowel disease (IBD), and diabetes and women without these conditions.
Methods: Using linked population-based administrative health data from ON, Canada, we conducted a cohort study of mothers with MS, epilepsy, IBD, and diabetes and without these diseases (comparators) who had a live birth with index dates, defined as 1 year before conception, between 2002 and 2017.
Purpose: Predicting long-term anatomical responses in neovascular age-related macular degeneration (nAMD) patients is critical for patient-specific management. This study validates a generative deep learning (DL) model to predict 12-month posttreatment optical coherence tomography (OCT) images and evaluates the impact of incorporating clinical data on predictive performance.
Methods: A total of 533 eyes from 513 treatment-naïve nAMD patients were analyzed.
Purpose: Clinical variables alone have limited ability to determine which patients will have recurrence after radical prostatectomy (RP). We evaluated the ability of locked multimodal artificial intelligence (MMAI) algorithms trained on prostate biopsy specimens to predict prostate cancer specific mortality (PCSM) and overall survival (OS) among patients undergoing radical prostatectomy with digitized RP specimens.
Materials And Methods: The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Randomized Controlled Trial randomized subjects from 1993-2001 to cancer screening or control.
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