Predictors of outcome following psychological therapy for depression and anxiety in an urban primary care service: a naturalistic Bayesian prediction modeling approach.

Background: England's primary care service for psychological therapy (Improving Access to Psychological Therapies [IAPT]) treats anxiety and depression, with a target recovery rate of 50%. Identifying the characteristics of patients who achieve recovery may assist in optimizing future treatment. This naturalistic cohort study investigated pre-therapy characteristics as predictors of recovery and improvement after IAPT therapy.

Diagnostic Accuracy of a Custom Large Language Model on Rare Pediatric Disease Case Reports.

Accurately diagnosing rare pediatric diseases frequently represent a clinical challenge due to their complex and unusual clinical presentations. Here, we explore the capabilities of three large language models (LLMs), GPT-4, Gemini Pro, and a custom-built LLM (GPT-4 integrated with the Human Phenotype Ontology [GPT-4 HPO]), by evaluating their diagnostic performance on 61 rare pediatric disease case reports. The performance of the LLMs were assessed for accuracy in identifying specific diagnoses, listing the correct diagnosis among a differential list, and broad disease categories.

Evaluating the Effectiveness of Empathy-Based Education in Undergraduate Nursing: A Scoping Review.

Background: Empathy is an essential trait in nursing practice that improves the quality of patient care. Nursing curricula that incorporate empathy-based experiential learning (i.e.

A prospective study of sexual risk patterns associated with delinquency and justice involvement among child welfare system-involved male adolescents in the United States.

Introduction: Early sexual activity and teen pregnancy are known risk factors for delinquency and justice involvement among male adolescents. However, less is known about these patterns among child welfare system (CWS)-involved boys who face significant social barriers and past/current traumatic experiences.

Methods: We prospectively examined these associations among male adolescents who identified as low and high risk for child-maltreatment via a secondary data analysis of the Longitudinal Studies of Child Abuse and Neglect dataset-a large scale assessment of children, their parents, and their teachers in the United States to understand issues of child abuse and neglect.

The spectrum of neurological presentation in individuals affected by TBL1XR1 gene defects.

Background: TBL1XR1 encodes a F-box-like/WD40 repeat-containing protein that plays a role in transcription mediated by nuclear receptors and is a known genetic cause of neurodevelopmental disease of childhood (OMIM# 608628). Yet the developmental trajectory and progression of neurologic symptoms over time remains poorly understood.

Methods: We developed and distributed a survey to two closed Facebook groups devoted to families of patients with TBL1XR1-related disorder.