Background: Although medical educators acknowledge the importance of ethics in medical training, there are few validated instruments to assess ethical decision-making. One instrument is the Ethics in Health Care Questionnaire--version 2 (EHCQ-2). The instrument consists of 12 scenarios, each posing an ethical problem in health care, and asking for a decision and rationale. The responses are subjectively scored in four domains: response, issue identification, issue sophistication, and values.
Goals: This study was intended to examine the inter-rater and inter-case reliability of the AHCQ-2 and validity against a national licensing examination of the EHCQ-2 in an international sample.
Methods: A total of 20 final year McMaster students and 45 final year Glasgow students participated in the study. All questionnaires were scored by multiple raters. Generalizability theory was used to examine inter-rater, inter-case and overall test reliability. Validity was assessed by comparing EHCQ-2 scores with scores on the Canadian written licensing examination, both total score and score for the ethics subsection.
Results: For both samples, reliability was quite low. Except for the first task, which is multiple choice, inter-rater reliability was 0.08-0.54, and inter-case reliability was 0.14-0.61. Overall test reliability was 0.12-0.54. Correlation between EHCQ-2 task scores and the licensing examination scores ranged from 0.07 to 0.40; there was no evidence that the correlation was higher with the ethics subsection.
Conclusions: The reliability and validity of the measure remains quite low, consistent with other measures of ethical decision-making. However, this does not limit the utility of the instrument as a tool to generate discussion on ethical issues in medicine.
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http://dx.doi.org/10.3109/0142159X.2012.687845 | DOI Listing |
J Med Ethics
January 2025
Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Introduction: The integration of artificial intelligence (AI) into healthcare introduces innovative possibilities but raises ethical, legal and professional concerns. Assessing the performance of AI in core components of the United States Medical Licensing Examination (USMLE), such as communication skills, ethics, empathy and professionalism, is crucial. This study evaluates how well ChatGPT versions 3.
View Article and Find Full Text PDFMedicina (Kaunas)
January 2025
Department of Physical Therapy and Health Rehabilitation, College of Applied Medical Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia.
: Sports injury prevention programs (SIPPs) are crucial for mitigating sports injuries and enhancing athletes' performance. In Saudi Arabia, the sports sector is growing, and the awareness and implementation of sports injury prevention programs (SIPPs) among physical therapists require examination. This study aims to evaluate physiotherapists' awareness of and the implementation of sports injury prevention programs (SIPPs) in the Saudi Arabian region with findings that could enhance rehabilitation and sports injury prevention practices.
View Article and Find Full Text PDFJMIR Med Educ
January 2025
Institute of Medicine, Suranaree University of Technology, 111 University Avenue, Nakhon Ratchasima, 30000, Thailand, 66 44223956.
Background: Artificial intelligence (AI) has become widely applied across many fields, including medical education. Content validation and its answers are based on training datasets and the optimization of each model. The accuracy of large language model (LLMs) in basic medical examinations and factors related to their accuracy have also been explored.
View Article and Find Full Text PDFCureus
December 2024
Department of Rehabilitation Medicine, Mie University Graduate School of Medicine, Tsu, JPN.
Background Generative artificial intelligence (AI), such as Chat Generative Pre-trained Transformer (ChatGPT), has shown potential in various medical applications, including answering licensing examination questions. However, its performance in rehabilitation medicine remains underexplored. This study aimed to evaluate the accuracy of ChatGPT4o in answering questions from the Japanese Board-Certified Physiatrist Examination and assess its potential as an educational and clinical support tool.
View Article and Find Full Text PDFClin Orthop Relat Res
January 2025
Department of Radiology, Chongqing Health Center for Women and Children/Women and Children's Hospital of Chongqing Medical University, Chongqing, PR China.
Background: Nonweightbearing preoperative assessments avoid quadriceps contraction that tends to affect patellar motion and appear to be inaccurate in quantifying anatomic factors, which can lead to incorrect corrections and postoperative complications.
Questions/purposes: (1) Does the relationship of patellar axial malalignment and other anatomic factors change during weightbearing? (2) What anatomic factor was most strongly correlated with recurrent patellar dislocation during weightbearing?
Methods: This prospective, comparative, observational study recruited participants at our institution between January 2023 and September 2023. During this time, all patients with recurrent patellar dislocations received both weightbearing and nonweightbearing CT scans; control patients who received unilateral CT scans because of injuries or benign tumors received both weightbearing and nonweightbearing CT scans.
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