The study explored people's reactions to observing the ostracism of stigmatized targets. Participants ( = 198) who observed ostracism experienced need threat regardless of the target's identity. Participants regarded included addicts more positively than ostracized addicts, especially on traits that are considered unique to humans. As for dehumanization, subtle measures demonstrate that ostracized targets are perceived as less human. In contrast, our original measure of blatant dehumanization suggests that targets of ostracism are perceived as more human. The study stresses the inconsistency between dehumanization measurements and the need to specify what each measure taps into and how each contributes to the theory.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/00224545.2024.2307577 | DOI Listing |
BMC Public Health
January 2025
School of Nursing and Midwifery, Queen's University Belfast, Belfast, Northern Ireland, UK.
Background: Stigma significantly impacts individuals with Parkinson's disease (PD) and their caregivers, exacerbating social isolation, psychological distress, and reducing quality of life (QoL). Although considerable research has been conducted on PD's clinical aspects, the social and emotional challenges, like stigma, remain underexplored. Addressing stigma is crucial for enhancing well-being, fostering inclusivity and improving access to care and support.
View Article and Find Full Text PDFIndian J Psychol Med
December 2024
Dept. of Mental Health and Community Nursing, Faculty of Medicine, Public Health, and Nursing Universitas Gadjah Mada, Yogyakarta, Indonesia.
Background: Mental health literacy among lay community health workers (CHWs) is crucial to ensuring that mental health services are accessible to all. This research explores the mental health literacy of community health workers in Indonesia.
Methods: A cross-sectional study was carried out among 454 female community health workers from various villages.
J Am Med Inform Assoc
December 2024
Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, United States.
Objective: To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques.
Materials And Methods: We first created a lexicon and regular expression lists from literature-driven stem words for linguistic features of stigmatizing patient labels, doubt markers, and scare quotes within EHRs. The lexicon was further extended using Word2Vec and GPT 3.
BMC Psychol
December 2024
UMR7267 Ecology and Biology of Interactions (EBI), University of Poitiers, University Hospital Center of Poitiers, Poitiers, France.
Background: After a literature review and interviews with patients living with obesity, key psychosocial determinants such as coping strategies, weight bias internalization, body dissatisfaction and self-efficacy were identified as critical to address obesity-related stigma. The intervention was tailored using evidence-based techniques and input from health professionals to ensure relevance and avoid redundancy. This randomized controlled trial (RCT) aims to evaluate the effect of an intervention specifically designed to address weight stigma among individuals living with obesity.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!