Context: Medical interpreters play a critical role in communicating with patients and families with non-English language preference (NELP), previously referred to as limited English proficiency , near the end-of-life (EOL) but often receive minimal education about providing this type of care.

Objectives: To understand interpreter experiences with providing services for patients near the end of life and needs for professional support and training in EOL care.

Methods: A 60 question survey, was distributed to 1,660 medical interpreters at two hospitals and one interpreter service company. The survey included questions about participant characteristics, examined interpreter experiences, self-efficacy responding to EOL symptoms and EOL concerns, comfort levels, educational needs, racial discrimination, and barriers to effective interpretation for patients who are near EOL.

Results: Medical interpreters (n = 162) generally report high self-efficacy in interpreting conversations about EOL care but have lower scores regarding the communication and decision-making subscale compared to symptom management subscale (Diff=0.90 (95% CI 0.48 - 1.32), p<.0001). Many (70.4%) of the interpreters indicated that they never or seldom meet with the patient's medical providers prior to a goals of care meeting and only 52.2% report they are usually or always treated as part of the medical team. Interpreters often received little warning about conversation topics prior to interpreting. Qualitative comments revealed experiences of high emotional distress during and after these conversations. Approximately three quarters of the interpreters indicated they would be interested in receiving education regarding EOL topics. Increased experience as an interpreter was associated with a lower fear of death (r=-0.204, p=0.0092 and witnessed discrimination (r=0.179, p=0.0236).

Conclusion: Although self-efficacy for interpreting EOL conversations is generally high, interpreters desire education about EOL care. Interventions are also needed to address the high emotional toll of interpreting EOL conversations. Education and training about EOL care may help them to not only convey information accurately but also cope with emotional nuances characteristic of these significant conversations, ultimately elevating the quality of care for patients and family members in vulnerable and important moments.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jpainsymman.2025.02.468DOI Listing

Publication Analysis

Top Keywords

medical interpreters
12
interpreter experiences
8
eol
5
medical
4
medical interpreters'
4
interpreters' experiences
4
patients
4
experiences patients
4
patients end-of-life
4
end-of-life family
4

Similar Publications

Purpose: Medically tailored transitional foods (TFs) may be a clinically viable alternative to pureed consistency for individuals requiring texture-modified foods. However, little remains known about the performance of TFs during the swallow. The purpose of this investigation was to describe oropharyngeal swallowing physiology in patients with dysphagia during consumption of TFs as compared to pureed solids.

View Article and Find Full Text PDF

Background: The increasing integration of artificial intelligence (AI) systems into critical societal sectors has created an urgent demand for robust privacy-preserving methods. Traditional approaches such as differential privacy and homomorphic encryption often struggle to maintain an effective balance between protecting sensitive information and preserving data utility for AI applications. This challenge has become particularly acute as organizations must comply with evolving AI governance frameworks while maintaining the effectiveness of their AI systems.

View Article and Find Full Text PDF

Cancer gene identification through integrating causal prompting large language model with omics data-driven causal inference.

Brief Bioinform

March 2025

School of Artificial Intelligence, Jilin University, 3003 Qianjin Street, Changchun 130012, Jilin Province, China.

Identifying genes causally linked to cancer from a multi-omics perspective is essential for understanding the mechanisms of cancer and improving therapeutic strategies. Traditional statistical and machine-learning methods that rely on generalized correlation approaches to identify cancer genes often produce redundant, biased predictions with limited interpretability, largely due to overlooking confounding factors, selection biases, and the nonlinear activation function in neural networks. In this study, we introduce a novel framework for identifying cancer genes across multiple omics domains, named ICGI (Integrative Causal Gene Identification), which leverages a large language model (LLM) prompted with causality contextual cues and prompts, in conjunction with data-driven causal feature selection.

View Article and Find Full Text PDF

The link between abnormal sleep duration and stroke outcomes remains contentious. This meta-analysis quantifies how both short and long sleep durations impact stroke incidence and mortality. A comprehensive search was conducted in PubMed, Web of Science, Cochrane Library, Embase, and Google Scholar up to November 1, 2024, to identify cohort studies evaluating sleep duration and stroke outcomes.

View Article and Find Full Text PDF

Sleep duration is a crucial factor influencing health outcomes, yet its relationship with mortality remains debated. In this meta-analysis, we aimed to investigate the association between short and long sleep duration and all-cause mortality in adults, including sex-specific differences. A systematic search was performed in multiple databases, including PubMed, Cochrane Central, and Web of Science, up to October 2024.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!