There is little research on virtual service models like chat and text services in agencies that work with survivors of intimate partner violence (IPV) and sexual assault (SA). This study fills a gap in the research by exploring how chat and text services are provided in one IPV and SA-focused community organization. We analyzed chat and text transcripts ( = 392) from a large multiservice, multivictimization focused agency, and conducted interviews with 11 advocates providing chat and text services through the agency hotline. Staff interviews were analyzed using grounded theory and transcripts were analyzed using content analysis. Results indicate chat/text services provide a space for connection, resource provision, education, and access to resource gain in a timely, concise, and survivor-centered way. The five major goals for chat/text advocacy models include the following: (1) rapid access to support and connection; (2) identification of options and needs for each service user; (3) increased access to resources and supports; (4) expanded understanding of violence, abuse, and harm; and (5) improvement of survivor safety. The research team identified 15 general advocacy skills and 4 chat and text specific skills used by chat/text advocates to reach program goals. Findings highlight the utility of chat/text services for increasing access to support services for survivors of violence, particularly adolescents, emerging adults, those living with an abusive individual, and during times of emergency. Future research should continue to explore the promising practice modality of chat/text services for providing advocacy to underserved and hard-to-reach populations.
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http://dx.doi.org/10.1177/08862605211043573 | DOI Listing |
J Pediatr Urol
December 2024
Manisa Celal Bayar University, School of Medicine, Department of Paediatric Nephrology, Manisa, TR-45010, Turkey. Electronic address:
Introduction: Vesicoureteral reflux (VUR) is a common congenital or acquired urinary disorder in children. Chat Generative Pre-trained Transformer (ChatGPT) is an artificial intelligence-driven platform offering medical information. This research aims to assess the reliability and readability of ChatGPT-4o's answers regarding pediatric VUR for general, non-medical audience.
View Article and Find Full Text PDFCureus
November 2024
Ophthalmology, Florida Atlantic University Charles E. Schmidt College of Medicine, Boca Raton, USA.
Introduction: The emergence of large language models (LLMs) has led to significant interest in their potential use as medical assistive tools. Prior investigations have analyzed the overall comparative performance of LLM versions within different ophthalmology subspecialties. However, limited investigations have characterized LLM performance on image-based questions, a recent advance in LLM capabilities.
View Article and Find Full Text PDFAesthetic Plast Surg
December 2024
Department of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan 1#, Dongcheng District, Beijing, 100730, P. R. China.
After the groundbreaking release of the highly acclaimed chatbot ChatGPT, which revolutionized the field of artificial intelligence (AI) last year, OpenAI has once again astounded the world with the unveiling of their latest generative AI model, Sora, on February 16, 2024. This cutting-edge model has the remarkable ability to generate videos up to a duration of 60 seconds solely through text instructions. With a series of AI-generated contents, such as AI chat, AI drawing, and AI music, emerging one after another, the era of "AI revolution" that had a disruptive impact on modern life has arrived.
View Article and Find Full Text PDFPeerJ Comput Sci
October 2024
Electrical and Computer Engineering, The University of Memphis, Memphis, TN, United States.
Large language models (LLMs) have become transformative tools in areas like text generation, natural language processing, and conversational AI. However, their widespread use introduces security risks, such as jailbreak attacks, which exploit LLM's vulnerabilities to manipulate outputs or extract sensitive information. Malicious actors can use LLMs to spread misinformation, manipulate public opinion, and promote harmful ideologies, raising ethical concerns.
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