Written against the backdrop of the 2020 twin pandemics of a global health crisis and greater national awareness of structural racism, this article issues a call for psychology to invest in training all psychologists to respond to the social ills of racial and other forms of oppression. We introduce a public psychology for liberation (PPL) training model. Essentially, the model reflects a science, a pedagogical commitment, and practice of, by, and with the people who have been most marginalized in society. The PPL consists of five foundational domains or cross-cutting areas of expertise (e.g., facilitate human relationships; generate reciprocal knowledge and translation) and 10 interrelated lifelong practices (e.g., cultural humility; care and compassion) that foster healing and equity. The model centers the perspectives of the Global Majority, focuses on radical healing and equity, and emphasizes a developmental, culturally grounded, strengths-based approach to training. Various training initiatives consistent with a public psychology for liberation approach are presented. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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PLoS One
January 2025
Graduate Group in Science & Mathematics Education (SESAME), University of California-Berkeley, Berkeley, California, United States of America.
Participation in technical/research internships may improve undergraduate graduation rates and persistence in science, technology, engineering, and mathematics (STEM), yet little is known about the benefits of these activities a) for community college students, b) when hosted by national laboratories, and c) beyond the first few years after the internship. We applied Social Cognitive Career Theory (SCCT) to investigate alumni perspectives about how CCI at Lawrence Berkeley National Laboratory (LBNL) impacted their academic/career activities. We learned that alumni had low confidence and expectations of success in STEM as community college students.
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January 2025
Academy of Fine Arts, Jiangsu Second Normal University, Nanjing, China.
Urban waterfront areas, which are essential natural resources and highly perceived public areas in cities, play a crucial role in enhancing urban environment. This study integrates deep learning with human perception data sourced from street view images to study the relationship between visual landscape features and human perception of urban waterfront areas, employing linear regression and random forest models to predict human perception along urban coastal roads. Based on aesthetic and distinctiveness perception, urban coastal roads in Xiamen were classified into four types with different emphasis and priorities for improvement.
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January 2025
King's College London-Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.
Major depressive disorder (MDD) is defined by an array of symptoms that make it challenging to understand the condition at a population level. Subtyping offers a way to unpick this phenotypic diversity for improved disorder characterisation. We aimed to identify depression subtypes longitudinally using the Inventory of Depressive Symptomatology: Self-Report (IDS-SR).
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January 2025
Institute of Psychiatry, Psychology & Neuroscience at King's College London, London, United Kingdom.
Fluctuation-related pain (FRP) affects more than one third of people with Parkinson's disease (PwP, PD) and has a harmful effect on health-related quality of life (HRQoL), but often remains under-reported by patients and neglected by clinicians. The National Institute for Health and Care Excellence (NICE) recommends The Parkinson KinetiGraphTM (the PKGTM) for remote monitoring of motor symptoms. We investigated potential links between the PKGTM-obtained parameters and clinical rating scores for FRP in PwP in an exploratory, cross-sectional analysis of two prospective studies: "The Non-motor International Longitudinal, Real-Life Study in PD-NILS" and "An observational-based registry of baseline PKG™ in PD-PKGReg".
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January 2025
Evidence-based Public Health, Centre for International Health Protection, Robert Koch Institute, Berlin, Germany.
Health system resilience is defined as the ability of a system to prepare, manage, and learn from shocks. This study investigates the resilience of the German health system by analysing the system-related factors that supported health care workers, a key building block of the system, during the COVID-19 pandemic. We thematically analysed data from 18 semi-structured interviews with key informants from management, policy and academia, 17 in-depth interviews with health care workers, and 10 focus group discussions with health care workers.
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