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2.
BMC Med Ethics ; 25(1): 18, 2024 02 17.
Article in English | MEDLINE | ID: mdl-38368332

ABSTRACT

AIMS: To examine the understanding of the ethical dilemmas associated with Big Data and artificial intelligence (AI) among Jordanian medical students, physicians in training, and senior practitioners. METHODS: We implemented a literature-validated questionnaire to examine the knowledge, attitudes, and practices of the target population during the period between April and August 2023. Themes of ethical debate included privacy breaches, consent, ownership, augmented biases, epistemology, and accountability. Participants' responses were showcased using descriptive statistics and compared between groups using t-test or ANOVA. RESULTS: We included 466 participants. The greater majority of respondents were interns and residents (50.2%), followed by medical students (38.0%). Most participants were affiliated with university institutions (62.4%). In terms of privacy, participants acknowledged that Big Data and AI were susceptible to privacy breaches (39.3%); however, 59.0% found such breaches justifiable under certain conditions. For ethical debacles involving informed consent, 41.6% and 44.6% were aware that obtaining informed consent posed an ethical limitation in Big Data and AI applications and denounced the concept of "broad consent", respectively. In terms of ownership, 49.6% acknowledged that data cannot be owned yet accepted that institutions could hold a quasi-control of such data (59.0%). Less than 50% of participants were aware of Big Data and AI's abilities to augment or create new biases in healthcare. Furthermore, participants agreed that researchers, institutions, and legislative bodies were responsible for ensuring the ethical implementation of Big Data and AI. Finally, while demonstrating limited experience with using such technology, participants generally had positive views of the role of Big Data and AI in complementing healthcare. CONCLUSION: Jordanian medical students, physicians in training and senior practitioners have limited awareness of the ethical risks associated with Big Data and AI. Institutions are responsible for raising awareness, especially with the upsurge of such technology.


Subject(s)
Physicians , Students, Medical , Humans , Cross-Sectional Studies , Big Data , Artificial Intelligence , Jordan , Morals
3.
Ann Med Surg (Lond) ; 76: 103552, 2022 Apr.
Article in English | MEDLINE | ID: mdl-35495384

ABSTRACT

Background: Diabetes mellitus (DM) is a common metabolic disorder that significantly affects public health. Diabetic foot ulcer (DFU) is one of the serious complications of diabetes. DFU has a wide spectrum of bacterial isolates comprising Gram-positive, Gram-negative, aerobic bacteria and anaerobes. In the last two decades there has been an increase in the multidrug-resistant isolates (MDR). Materials and methods: This cross-sectional prospective observational study was conducted in southern Jordan among patients with DFU. The included variables are sociodemographic and clinical information. Isolates from swab culture of ulcers and antimicrobial susceptibility pattern are also recorded. Results: A total of 64 diabetic patients with DFU were included in this study. Most patients included in the study were males with male-to-female ratio of (2.2:1). The mean age was 54 years (SD ± 10.7). The mean duration of DM was 16.4 years (SD ± 7.5) and the mean HbA1c was 9.9% (SD ± 2.1). Neuropathy and anemia were noted in 72% and 44% of patients, respectively. The most frequent bacterial isolates were gram negative bacteria accounts for 29 isolates (45.3%). About 37.5% (24) of bacterial isolates showed MDR pattern. Previous antibiotic use in the last 30 days showed significant association with MDR bacteria (p-value <0.05). Previous history of amputations, presence of neuropathy, renal impairment, retinopathy, presence of anemia, limited joint mobility and presence of foot deformity were significantly associated with Wagner's grade ≥ three. Conclusion: Many factors affect and increase the risk of having high grade diabetic foot ulcer. The most frequent bacterial isolates from diabetic foot ulcers were gram negative bacteria. High rates of MDR in this study reflect the loose implementation of regulations in Jordan regarding antibiotics dispensing.

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