Context: Decision making regarding the place of end-of-life (EOL) care is an important issue for patients with terminal cancer and their families. It often requires surrogate decision making, which can be a burden on families.
Objectives: To explore the burden on the family of patients dying from cancer related to the decisions they made about the place of EOL care and investigate the factors affecting this burden.
Methods: This was a cross-sectional mail survey using a self-administered questionnaire. Participants were 700 bereaved family members of patients with cancer from 133 palliative care units in Japan. The questionnaire covered decisional burdens, depression, grief, and the decision-making process.
Results: Participants experienced emotional pressure as the highest burden. Participants with a high decisional burden reported significantly higher scores for depression and grief (both P < 0.001). Multiple regression analyses revealed that higher burden was associated with selecting a place of EOL care that differed from that desired by participants (P < 0.001) and patients (P = 0.034), decision making without knowing the patient's wishes and values (P < 0.001) and without participants sharing their wishes and values with the patient's doctors and/or nurses (P = 0.022), and making the decision because of a due date for discharge from a former facility or hospital (P = 0.005).
Conclusion: Decision making regarding the place of EOL care was recalled as burdensome for family decision makers. An early decision-making process that incorporates sharing patients' and family members' values that are relevant to the desired place of EOL care is important.
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http://dx.doi.org/10.1016/j.jpainsymman.2016.12.348 | DOI Listing |
Background: The purpose of this study was to evaluate the performance and evolution of Chat Generative Pre-Trained Transformer (ChatGPT; OpenAI) as a resource for shoulder and elbow surgery information by assessing its accuracy on the American Academy of Orthopaedic Surgeons shoulder-elbow self-assessment questions. We hypothesized that both ChatGPT models would demonstrate proficiency and that there would be significant improvement with progressive iterations.
Materials And Methods: A total of 200 questions were selected from the 2019 and 2021 American Academy of Orthopaedic Surgeons shoulder-elbow self-assessment questions.
Am J Hosp Palliat Care
January 2025
Department of Pediatrics, University of Chicago, Comer Children's Hospital, Chicago, IL, USA.
Pediatric neuro-oncology patients have one of the highest mortality rates among all children with cancer. Our study examines the potential relationship between palliative care consultation and intensity of in-hospital care and determines if racial and ethnic differences are associated with palliative care consultations during their terminal admission. Retrospective observational study using the Pediatric Health Information System (PHIS) database with data from U.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Cancer Screening, American Cancer Society, Atlanta, GA, United States.
Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.
Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.
Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.
JMIR Res Protoc
January 2025
Division of Services and Interventions Research, National Institute of Mental Health, Bethesda, MD, United States.
Background: Although substantial progress has been made in establishing evidence-based psychosocial clinical interventions and implementation strategies for mental health, translating research into practice-particularly in more accessible, community settings-has been slow.
Objective: This protocol outlines the renewal of the National Institute of Mental Health-funded University of Washington Advanced Laboratories for Accelerating the Reach and Impact of Treatments for Youth and Adults with Mental Illness Center, which draws from human-centered design (HCD) and implementation science to improve clinical interventions and implementation strategies. The Center's second round of funding (2023-2028) focuses on using the Discover, Design and Build, and Test (DDBT) framework to address 3 priority clinical intervention and implementation strategy mechanisms (ie, usability, engagement, and appropriateness), which we identified as challenges to implementation and scalability during the first iteration of the center.
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