Recognition has grown that peer support workers serve an important role in facilitating decision making about treatment and recovery among people with mental health conditions. This article provides examples of peer-facilitated decision support interventions in the literature, discusses promises and potential pitfalls associated with peers serving in decision support roles, and offers recommendations for research and practice. Examples were selected from the literature on decision support interventions for people with serious mental illnesses, such as schizophrenia, bipolar disorder, and major depression. Promises, pitfalls, and recommendations were informed by this research and by the literature on lived experience perspectives, the helper-therapy principle, and reported barriers to and facilitators of peers assisting with decision making. According to the included studies, peers may facilitate decision making in several ways (e.g., by asking service users about their goals or preferences, assisting them with using decision support tools, sharing stories, and facilitating access to information and resources). Peer-facilitated decision support may be associated with positive decision making and health outcomes for service users and peer support workers. However, providers need to carefully consider barriers to implementation of this support, such as inadequate resourcing, poor integration, and compromising of peer support values.
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http://dx.doi.org/10.1176/appi.ps.20220086 | DOI Listing |
iScience
January 2025
International Institute for Applied Systems Analysis, Laxenburg, Lower Austria, Austria.
Cost reductions are essential for accelerating clean technology deployment. Because multiple factors influence costs, traditional one-factor learning models, solely relying on cumulative installed capacity as an explanatory variable, may oversimplify cost dynamics. In this study, we disentangle learning and economies of scale effects at unit and project levels and introduce a knowledge gap concept to quantify rapid technological change's impact on costs.
View Article and Find Full Text PDFFront Med (Lausanne)
January 2025
School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom.
Introduction: When implemented by national and regional regulatory agencies good review practices (GRevPs) support the timely high-quality review of medicines for enhanced patients' availability to safe, quality and efficacious innovative and generic products. It is important that all aspects of GRevPs are continuously evaluated and updated to promote the continuous improvement of regulatory systems at national and regional levels. The aim of this study was to assess and compare the GRevPs of the national medicines regulatory agencies (NMRAs) of Burkina Faso, Cote d'Ivoire, Ghana, Nigeria, Senegal, Sierra Leone and Togo, who are active participants of the ECOWASMRH initiative to identify opportunities for improvement.
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January 2025
Department of Gastroenterology and Hepatology, Tianjin Third Central Hospital, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Institute of Hepatobiliary Disease, Tianjin, China.
Objective: Although pegylated interferon α-2b (PEG-IFN α-2b) therapy for chronic hepatitis B has received increasing attention, determining the optimal treatment course remains challenging. This research aimed to develop an efficient model for predicting interferon (IFN) treatment course.
Methods: Patients with chronic hepatitis B, undergoing PEG-IFN α-2b monotherapy or combined with NAs (Nucleoside Analogs), were recruited from January 2018 to December 2023 at Tianjin Third Central Hospital.
Front Immunol
January 2025
School of Nursing, Zunyi Medical University, Zunyi, China.
Background: Most patients initially diagnosed with non-muscle invasive bladder cancer (NMIBC) still have frequent recurrence after urethral bladder tumor electrodesiccation supplemented with intravesical instillation therapy, and their risk of recurrence is difficult to predict. Risk prediction models used to predict postoperative recurrence in patients with NMIBC have limitations, such as a limited number of included cases and a lack of validation. Therefore, there is an urgent need to develop new models to compensate for the shortcomings and potentially provide evidence for predicting postoperative recurrence in NMIBC patients.
View Article and Find Full Text PDFFront Immunol
January 2025
Department of Medical Laboratory, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, China.
Background: Multidrug-resistant Klebsiella pneumoniae (MDR-KP) infections pose a significant global healthcare challenge, particularly due to the high mortality risk associated with septic shock. This study aimed to develop and validate a machine learning-based model to predict the risk of MDR-KP-associated septic shock, enabling early risk stratification and targeted interventions.
Methods: A retrospective analysis was conducted on 1,385 patients with MDR-KP infections admitted between January 2019 and June 2024.
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