This study was undertaken to assess patient satisfaction with the decision making process as well as with the decision made at the end of in-vitro fertilization (IVF) treatment. Couples who had decided to end treatment after unsuccessful IVF at a single hospital within the last 24 months were invited to complete a questionnaire. Valid questionnaires were returned by 71 (51%) out of a total of 139 couples. Sixty-nine (97%) questionnaires were completed by the female partner. Most women (73%) felt that they were adequately informed about the issues important to the decision. Fifty-eight women (81%) were involved with the decision making process; 38 (58%) felt supported by the clinic doctor and 41 (62%) were satisfied with the decision made. In response to a number of questions about information provision, few women (18 - 24%, depending on the individual question) felt that they had received enough information from the IVF clinician about advantages and disadvantages of stopping treatment and options such as adoption and fostering. Women contemplating the end of IVF treatment appear to be satisfied with the clinician's attitude, the decision making process and the decision made. While information provided during the final consultation is felt to be adequate for decision making, discussion about certain important options such as adoption and fostering could be more detailed.
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http://dx.doi.org/10.1080/1464727042000198069 | DOI Listing |
Afr J Reprod Health
December 2024
Midwifery Department, Faculty and Health Sciences, Karabük University, Turkey.
This study investigated the professional values of midwifery students and the factors influencing these values. Conducted from January 6 to March 6, 2021, it involved 715 midwifery students who participated voluntarily. Data was collected using a Descriptive Data Sheet and the Professional Values of Midwives Scale.
View Article and Find Full Text PDFViruses
November 2024
Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights.
View Article and Find Full Text PDFVaccines (Basel)
December 2024
School of Healthcare, University of Leicester, Leicester LE1 7RH, UK.
Vaccinating care home staff is essential to protect vulnerable residents by reducing infection risks and creating a safer care environment. However, vaccine hesitancy amongst staff remains a challenge, particularly since the COVID-19 pandemic raised concerns about side effects and vaccination mandates. This study examines how the pandemic influenced flu vaccine hesitancy amongst UK care home staff.
View Article and Find Full Text PDFVaccines (Basel)
December 2024
The Shamir Medical Center (Assaf Harofeh), Rishon LeZion, 4 Icet, Zrifin 7033001, Israel.
In response to the COVID-19 pandemic, Israel prioritized pregnant women for vaccination, recognizing them as a high-risk group. This study aims to explore factors influencing the acceptance of Influenza, Pertussis (T-dap), and COVID-19 vaccines among pregnant women, focusing on attitudes, social norms, perceived control, and risk perceptions. Additionally, the study compares acceptance patterns between traditional vaccines and the newer COVID-19 vaccine.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Organ Support and Automation Technologies Group, U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
Prehospital medical care is a major challenge for both civilian and military situations as resources are limited, yet critical triage and treatment decisions must be rapidly made. Prehospital medicine is further complicated during mass casualty situations or remote applications that require more extensive medical treatments to be monitored. It is anticipated on the future battlefield where air superiority will be contested that prolonged field care will extend to as much 72 h in a prehospital environment.
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