Truth-telling in oncology is a major challenge, particularly in the absence of disclosure protocols in Egypt and the lack of Egyptian studies examining patients' preferences regarding cancer disclosure. This study aimed to reveal the preferences of patients seeking care at the National Cancer Institute - Cairo University regarding disclosing cancer diagnosis and the type and amount of information to be told.

Background:Patients generally have the right to be informed of their condition, but the debate over the issue of truth disclosure is still present. The attempt of this study is to review the approaches toward truth- telling to cancer patients in Iran. Materials and Methods: This study is a narrative review that included articles published in Iran on attitudes toward telling the truth to cancer patients. The present study extracted data from articles published in PubMed, Science Direct, Scientific Information Database (SID), Magiran, Iran Medex, Google Scholar, Iranian Research Institute for Information Science and Technology with key terms such as truth disclosure, breaking bad news, death awareness and disclosure of diagnosis without any time restriction. Results: Totally, 21 articles including 14 in English and 7 in Persian were selected and reviewed. The results of the study have shown that although treatment team and caregivers are unwilling to disclose the truth to patients, they have a tendency to obtain more information about their disease. Conclusion: As the incidence of cancer has increased worldwide, telling the truth to patients seeking more information about cancer disease would be inevitable, but more studies are required to provide scientific procedures based on evidence for truth disclosure, not the whole, to cancer patients.

Evidence suggests that truth telling and honest disclosure of cancer diagnosis could lead to improved outcomes in cancer patients. To examine such findings in Iran, this trial aimed to study the various dimensions of quality of life in patients with gastrointestinal cancer and to compare these variables among those who knew their diagnosis and those who did not.

The systematic review presented in this article aims to reveal what supports and hampers refugee children in telling their, often traumatic, life stories. This is important to ensure that migration decisions are based on reliable information about the children's needs for protection. A systematic review was conducted in academic journals, collecting all available scientific knowledge about the disclosure of life stories by refugee minors in the context of social work, guardianship, foster care, asylum procedures, mental health assessment, and therapeutic settings. The resulting 39 studies were thoroughly reviewed with reference to what factors aided or hampered the refugee children's disclosure of their life stories. The main barriers to disclosure were feelings of mistrust and self-protection from the side of the child and disrespect from the side of the host community. The facilitators for disclosing life stories were a positive and respectful attitude of the interviewer, taking time to build trust, using nonverbal methods, providing agency to the children, and involving trained interpreters. Social workers, mentors, and guardians should have time to build trust and to help a young refugee in revealing the life story before the minor is heard by the migration authorities. The lack of knowledge on how refugee children can be helped to disclose their experiences is a great concern because the decision in the migration procedure is based on the story the child is able to disclose.

This study is a systematic review that aims to assess how healthcare professionals manage ethical challenges regarding information within the clinical context.

Human Immunodeficiency Virus (HIV) is continued as a major public health problem, especially in developing countries. Therefore, this study aimed to estimate the effect of counseling, antiretroviral therapy (ART) and relationship on disclosing HIV positive status to sexual partner among adult HIV patients in Ethiopia.

Background: There is a lack of empirical data on lay attitudes toward different sorts of deception in medicine. However, lay attitudes toward deception should be taken into account when we consider whether deception is ever permissible in a medical context. The objective of this study was to examine lay attitudes of U.S. citizens toward different sorts of deception across different medical contexts. Methods: A one-time online survey was administered to U.S. users of the Amazon "Mechanical Turk" website. Participants were asked to answer questions regarding a series of vignettes depicting different sorts of deception in medical care, as well as a question regarding their general attitudes toward truth-telling. Results: Of the 200 respondents, the majority found the use of placebos in different contexts to be acceptable following partial disclosure but found it to be unacceptable if it involved outright lying. Also, 55.5% of respondents supported the use of sham surgery in clinical research, although 55% claimed that it would be unacceptable to deceive patients in this research, even if this would improve the quality of the data from the study. Respondents supported fully informing patients about distressing medical information in different contexts, especially when the patient is suffering from a chronic condition. In addition, 42.5% of respondents believed that it is worse to deceive someone by providing the person with false information than it is to do so by giving the person true information that is likely to lead them to form a false belief, without telling them other important information that shows it to be false. However, 41.5% believed that the two methods of deception were morally equivalent. Conclusions: Respondents believed that some forms of deception were acceptable in some circumstances. While the majority of our respondents opposed outright lying in medical contexts, they were prepared to support partial disclosure and the use of placebos when it is in the patient's interests or when it is what the person would want. These results support the position that physicians should be allowed a greater degree of authority to make a professional judgment about whether deception might be morally warranted by the circumstances, provided that it doesn't involve outright lying.

Statistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages.

Owning to its clinical accessibility, T1-weighted MRI (Magnetic Resonance Imaging) has been extensively studied in the past decades for prediction of Alzheimer's disease (AD) and mild cognitive impairment (MCI). The volumes of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) are the most commonly used measurements, resulting in many successful applications. It has been widely observed that disease-induced structural changes may not occur at isolated spots, but in several inter-related regions. Therefore, for better characterization of brain pathology, we propose in this paper a means to extract inter-regional correlation based features from local volumetric measurements. Specifically, our approach involves constructing an anatomical brain network for each subject, with each node representing a Region of Interest (ROI) and each edge representing Pearson correlation of tissue volumetric measurements between ROI pairs. As second order volumetric measurements, network features are more descriptive but also more sensitive to noise. To overcome this limitation, a hierarchy of ROIs is used to suppress noise at different scales. Pairwise interactions are considered not only for ROIs with the same scale in the same layer of the hierarchy, but also for ROIs across different scales in different layers. To address the high dimensionality problem resulting from the large number of network features, a supervised dimensionality reduction method is further employed to embed a selected subset of features into a low dimensional feature space, while at the same time preserving discriminative information. We demonstrate with experimental results the efficacy of this embedding strategy in comparison with some other commonly used approaches. In addition, although the proposed method can be easily generalized to incorporate other metrics of regional similarities, the benefits of using Pearson correlation in our application are reinforced by the experimental results. Without requiring new sources of information, our proposed approach improves the accuracy of MCI prediction from 80.83% (of conventional volumetric features) to 84.35% (of hierarchical network features), evaluated using data sets randomly drawn from the ADNI (Alzheimer's Disease Neuroimaging Initiative) dataset.

Accurate prediction of clinical changes of mild cognitive impairment (MCI) patients, including both qualitative change (i.e., conversion to Alzheimer's disease (AD)) and quantitative change (i.e., cognitive scores) at future time points, is important for early diagnosis of AD and for monitoring the disease progression. In this paper, we propose to predict future clinical changes of MCI patients by using both baseline and longitudinal multimodality data. To do this, we first develop a longitudinal feature selection method to jointly select brain regions across multiple time points for each modality. Specifically, for each time point, we train a sparse linear regression model by using the imaging data and the corresponding clinical scores, with an extra 'group regularization' to group the weights corresponding to the same brain region across multiple time points together and to allow for selection of brain regions based on the strength of multiple time points jointly. Then, to further reflect the longitudinal changes on the selected brain regions, we extract a set of longitudinal features from the original baseline and longitudinal data. Finally, we combine all features on the selected brain regions, from different modalities, for prediction by using our previously proposed multi-kernel SVM. We validate our method on 88 ADNI MCI subjects, with both MRI and FDG-PET data and the corresponding clinical scores (i.e., MMSE and ADAS-Cog) at 5 different time points. We first predict the clinical scores (MMSE and ADAS-Cog) at 24-month by using the multimodality data at previous time points, and then predict the conversion of MCI to AD by using the multimodality data at time points which are at least 6-month ahead of the conversion. The results on both sets of experiments show that our proposed method can achieve better performance in predicting future clinical changes of MCI patients than the conventional methods.

Health professionals are often involved in the process of breaking bad news (BBN), which remains a difficult challenge, as it requires not only theoretical knowledge, but also the development of humanistic, emotional and communication skills. Therefore, optimal BBN assessment is essential. In this regard, sound measurement instruments are needed to evaluate BBN properly in research, teaching and clinical settings. Several instruments have been designed and validated to assess BBN. In this context, choosing the most appropriate instrument for assessing health professionals' skills in BBN is essential. The aims of this systematic review are to: (1) identify all the instruments used for assessing health professionals' skills in BBN; and (2) critically appraise their measurement properties.