Obsessive-compulsive disorder (OCD) is a debilitating psychiatric condition with multidetermined etiological and maintaining mechanisms. Cognitive behavioral therapy (CBT), specifically exposure and response prevention (ERP), is the first line behavioral intervention to treat OCD. ERP directly targets threat learning that characterizes OCD through processes of habituation (fear extinction) and inhibitory learning, in addition to eliciting neuronal changes implicated in OCD. Although ERP has a strong evidence base, not all OCD patients respond fully to standard, weekly or twice-weekly outpatient ERP. High intensity ERP-treatment delivered through more and/or longer sessions in a condensed manner-is a potential alternative approach that has also demonstrated efficacy for adults and youth with OCD. The goal of this review article is to describe the nature, rationale, and evidence for high intensity ERP for OCD treatment. We describe the foundations of ERP for OCD, various formats of intensive ERP, clinical research on the efficacy of this approach including neuronal changes, and potential pharmacological and neurosurgical augmentation strategies. We conclude with limitations of the current literature on intensive approaches and recommendations for future directions. While additional research is needed, high intensity ERP may be a promising approach for patients who have not responded to standard ERP or for patients requiring rapid symptom improvement.
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http://dx.doi.org/10.1016/j.bbr.2025.115427 | DOI Listing |
Eur Arch Otorhinolaryngol
January 2025
Motion Sickness and Human Performance Laboratory, The Israel Naval Medical Institute, IDF Medical Corps, Haifa, Israel.
Purpose: Acute acoustic trauma (AAT) is a sudden sensorineural hearing loss (SNHL) due to exposure to high intensity impulse noise. There are no acceptable treatment guidelines, although several studies showed steroids could be effective in restoring hearing levels. A recent report suggested that steroids combined with hyperbaric oxygen therapy (HBOT) are a superior regiment for AAT.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Human Movement Science, Hunan Normal University, 36 Lushan Road, Changsha, Hunan, China.
Loneliness and low self-esteem are among the more prominent mental health problems among left-behind children, but most of the current research stays in cross-sectional surveys, with fewer studies proposing specific solutions. In addition, although the effective impact of dance interventions on loneliness and self-esteem has been demonstrated, the impact in the group of left-behind children remains under-explored. Therefore, this study validated the effectiveness of a dance intervention on loneliness and self-esteem in left-behind children through a 16-week randomised controlled trial.
View Article and Find Full Text PDFTo establish a multivariate linear regression model for predicting the difficulty of high-intensity focused ultrasound (HIFU) ablation of uterine fibroids based on multi-sequence magnetic resonance imaging radiomics features. A retrospective analysis was conducted on 218 patients with uterine fibroids who underwent HIFU treatment, including 178 cases from Yongchuan Hospital of Chongqing Medical University and 40 cases from the Second Affiliated Hospital of Chongqing Medical University (external validation set). Radiomics features were extracted and selected from magnetic resonance images, and potentially related imaging features were collected.
View Article and Find Full Text PDFSci Data
January 2025
Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, 04103, Germany.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models.
View Article and Find Full Text PDFLight Sci Appl
January 2025
National Research Center for High-Efficiency Grinding, College of Mechanical and Vehicle Engineering, Hunan University, 410082, Changsha, China.
Accurately and swiftly characterizing the state of polarization (SoP) of complex structured light is crucial in the realms of classical and quantum optics. Conventional strategies for detecting SoP, which typically involves a sequence of cascaded optical elements, are bulky, complex, and run counter to miniaturization and integration. While metasurface-enabled polarimetry has emerged to overcome these limitations, its functionality predominantly remains confined to identifying SoP within the standard Poincaré sphere framework.
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