Treatment-resistant obsessive-compulsive disorder (OCD) patients from around the United Kingdom who employed computer-guided self-help by using BTSteps over 17 weeks were randomized to have brief live phone support from a clinician either (1) in nine Scheduled clinician-initiated calls or (2) only in calls Requested by the patient (n=22 per condition). Call content and mean duration were similar across conditions. Scheduled-support patients dropped out significantly less often, did more homework of self-exposure and self-imposed ritual prevention (95% vs. 57%), and showed more improvement in OCD symptoms and disability. Mean total support time per patient over 17 weeks was 76 minutes for Scheduled and 16 minutes for Requested patients. Giving brief support proactively by phone enhanced OCD patients' completion of and improvement with computer-aided self-help.
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http://dx.doi.org/10.1002/jclp.20204 | DOI Listing |
BMJ Open
January 2025
National Poison Centre, Universiti Sains Malaysia, Georgetown, Penang, Malaysia
Objective: Glyphosate is widely used in Malaysian agriculture but poses a significant under-reported public health concern due to poisoning. This paper aims to study the epidemiology of glyphosate poisoning in Malaysia, assessing severity, identifying risk factors, and high-risk groups.
Setting: All glyphosate-related data of the Malaysia National Poison Centre from 2006 to 2023.
Lung Cancer
January 2025
Department of Respiratory Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK; Leeds Institute of Health Sciences, University of Leeds, Leeds, UK. Electronic address:
Introduction: Lung cancer screening saves lives by detecting cancers early, but continued adherence to screening rounds is required for participants to experience the maximum clinical benefit. Here we describe factors associated with screening adherence in the Yorkshire Lung Screening Trial.
Methods: All eligible individuals following baseline (prevalent) screening were invited for a biennial incident screen in a community setting.
JMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.
View Article and Find Full Text PDFJMIR Ment Health
January 2025
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.
Background: Mental health concerns have become increasingly prevalent; however, care remains inaccessible to many. While digital mental health interventions offer a promising solution, self-help and even coached apps have not fully addressed the challenge. There is now a growing interest in hybrid, or blended, care approaches that use apps as tools to augment, rather than to entirely guide, care.
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