Observance of patients' rights is a significant indicator in evaluating the quality of healthcare services. The COVID-19 pandemic has become a global crisis and affected the interactions between healthcare providers and patients. This study examined the COVID-19 patients' viewpoint about the observance of their rights by physicians and nurses. This study is a descriptive cross-sectional work of research conducted on the COVID-19 patients in Zanjan Province, Iran, in September 2020. The subjects were selected through convenience sampling, and data was collected using a two-section questionnaire consisting of a demographic characteristics survey and a Likert-type scale for evaluating patients' rights observance. The validity and reliability of the questionnaire were found to be acceptable, and the collected data was analyzed in SPSS v.26 using descriptive statistics, independent t-test, and ANOVA test. The mean score of observance of patients' rights was 69.60±7.36, representing a moderate level. The highest and lowest scores for the observance of patients' rights were related to the dimensions of courteous communication and responsibility, respectively. A significant relationship was found between the observance of patients' rights and their marital status, health insurance, and education level (<0.05). This study showed that the observance of the COVID-19 patients' rights has not been affected by the social agitation caused by this disease.
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http://dx.doi.org/10.18502/jmehm.v13i33.5315 | DOI Listing |
BMC Med Ethics
January 2025
Ethics and Work Research Unit, Institute of Advanced Studies (EPHE), Paris, France.
Aim: To carry out a detailed study of existing positions in the French public of the acceptability of refusing treatment because of alleged futility, and to try to link these to people's age, gender, and religious practice.
Method: 248 lay participants living in southern France were presented with 16 brief vignettes depicting a cancer patient at the end of life who asks his doctor to administer a new cancer treatment he has heard about. Considering that this treatment is futile in the patient's case, the doctor refuses to prescribe it.
Trials
January 2025
Internal Medicine (Rheumatology), Academic Hospital, Istanbul, Turkey.
Background: It was our impression that safety outcome trials were getting more frequent, raising ethical issues mainly related to patient autonomy. We and others had also proposed this autonomy would be best served if wording of the informed consents would be in the public domain.
Methods: Initially two observers and an arbiter tabulated the main aims of randomized controlled trials (RCTs) published in 1990-1991 vs.
Sex Reprod Healthc
January 2025
Department of Obstetrics and Gynecology, University of Washington, Seattle, WA, USA.
Objective: To examine abortion care in the largest academic medical center in Washington, a state protective of abortion rights, before and after the Supreme Court Dobbs decision.
Methods: This retrospective cohort study evaluated abortion provision at the University of Washington between January 1, 2022 and October 31, 2023. Data on patient sociodemographic and clinical characteristics were extracted from electronic medical records.
Curr Pain Headache Rep
January 2025
Universidad de Alcalá, School of Medicine and Health Sciences, Department of Surgery, Medical and Social Sciences, Area of Human Anatomy and Embryology, Universidad de Alcalá, University Campus - C/ 19 Av de Madrid Km 33 600, 28871, Alcalá de Henares, Madrid, Spain.
Purpose Of Review: Low back pain (LBP) is considered an important issue of public health, with annual prevalence estimations almost achieving 60% of the worldwide population. Available treatments have a limited impact on this condition, although they allow to alleviate pain and recover the patient's quality of life. This review aims to go deeper on the understanding of this condition, providing an updated, brief, and concise whole picture of this common musculoskeletal problem.
View Article and Find Full Text PDFIn the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.
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