Privacy and confidentiality are among the inalienable rights of every human being that contribute to preservation of a sense of reverence and dignity. The present study was conducted to examine patients' awareness of their entitlement to these important rights. This cross-sectional study was conducted on 200 patients in Tehran, Iran during the year 2010. Collected data included patients' demographics (age, gender, marital status, place of residence, and educational level), type of hospital ward, frequency of hospitalization, duration of hospital stay, and patients' awareness of privacy and confidentiality. Two trained interviewers gathered the data using a self-made questionnaire, which was specifically designed to assess patients' awareness of privacy and confidentiality. Validity and reliability of the questionnaire were determined using content validity and Cronbach's Coefficient Alpha (a = 0.7), respectively. To analyze data, patients were assigned to three categories of poor (0 ≤ scores ≤ 3), moderate (4 ≤ scores ≤ 7) and good (8 ≤ scores ≤ 10) levels of awareness. Statistical analysis was performed by SPSS software version 21. The results showed that 21% of the patients had poor, 72% moderate, and 7% good awareness of privacy and confidentiality, with a mean of 4.61 ± 1.63. In this study, 153 patients (76.5%) provided a correct definition of privacy, and 161 patients (80.5%) were aware of instances of privacy violation. In addition, a good level of awareness was found in 77 patients (38.5%) in terms of physician confidentiality, and in 158 patients (81.4%) regarding confidentiality of examination results and medical consultations. Our study results highlight the necessity to inform patients about the ethical and legal issues related to privacy and confidentiality, before or during admission.
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J Imaging Inform Med
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College of Computer, Chongqing University, No. 55 Daxuecheng South Rd, Shapingba, 401331, Chongqing, China.
Convolutional neural networks (CNNs) have become indispensable to medical image diagnosis research, enabling the automated differentiation of diseased images from extensive medical image datasets. Due to their efficacy, these methods raise significant privacy concerns regarding patient images and diagnostic models. To address these issues, some researchers have explored privacy-preserving medical image diagnosis schemes using fully homomorphic encryption (FHE).
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School of Library and Information Management, Emporia State University, Emporia, KS, USA.
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January 2025
Department of Sociology, Addis Ababa University, Addis Ababa, Ethiopia.
This article details the religious experiences of family caregivers in living with and caring for people with chronic illnesses in Addis Ababa, Ethiopia. This phenomenological study conducted in-depth interviews with 20 family caregivers recruited from Tikur Anbessa Specialized Hospital, who accompanied their loved ones during medical appointments or hospital stays. It used a thematic analysis to analyze the collected data.
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Department of Urology, Charité - Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany.
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