Celikvargas4125

There were no differences in the concerns about drug utilization or beliefs about medication at any time. We conclude that a web-based education can improve drug utilization literacy in elderly individuals and might contribute to the safer use of medications.Patient access to electronic health records gives rise to ethical questions related to the patient-doctor-computer relationship. Our study aims to examine patients' moral attitudes toward a shared EHR, with a focus on autonomy, information access, and responsibility. LOXO-292 order A de novo self-administered questionnaire containing three vignettes and 15 statements was distributed among patients in four different settings. A total of 1688 valid questionnaires were collected. Patients' mean age was 51 years, 61% was female, 50% had a higher degree (college or university), and almost 50% suffered from a chronic illness. Respondents were hesitant to hide sensitive information electronically from their care providers. They also strongly believed hiding information could negatively affect the quality of care provided. Participants preferred to be informed about negative test results in a face-to-face conversation, or would have every patient decide individually how they want to receive results. Patients generally had little experience using patient portal systems and expressed a need for more information on EHRs in this survey. They tended to be hesitant to take up control over their medical data in the EHR and deemed patients share a responsibility for the accuracy of information in their record.Creating a learning health system could help reduce variations in quality of care. Success is dependent on timely access to health data. To explore the barriers and facilitators to timely access to patients' data, we conducted in-depth semi-structured interviews with 37 purposively sampled participants from government, the NHS and academia across Scotland. Interviews were analysed using the framework approach. Participants were of the view that Scotland could play a leading role in the exploitation of routine data to drive forward service improvements, but highlighted major impediments (i) persistence of paper-based records and a variety of information systems; (ii) the need for a proportionate approach to managing information governance; and (iii) the need for support structures to facilitate accrual, processing, linking, analysis and timely use and reuse of data for patient benefit. There is a pressing need to digitise and integrate existing health information infrastructures, guided by a nationwide proportionate information governance approach and the need to enhance technological and human capabilities to support these efforts.Extracting information from unstructured clinical text is a fundamental and challenging task in medical informatics. Our study aims to construct a natural language processing (NLP) workflow to extract information from Chinese electronic dental records (EDRs) for clinical decision support systems (CDSSs). We extracted attributes, attribute values, and tooth positions based on an existing ontology from EDRs. A workflow integrating deep learning with keywords was constructed, in which vectors representing texts were unsupervised learned. Specifically, we implemented Sentence2vec to learn sentence vectors and Word2vec to learn word vectors. For attribute recognition, we calculated similarity values among sentence vectors and extracted attributes based on our selection strategy. For attribute value recognition, we expanded the keyword database by calculating similarity values among word vectors to select keywords. Performance of our workflow with the hybrid method was evaluated and compared with keyword-based method and deep learning method. In both attribute and value recognition, the hybrid method outperforms the other two methods in achieving high precision (0.94, 0.94), recall (0.74, 0.82), and F score (0.83, 0.88). Our NLP workflow can efficiently structure narrative text from EDRs, providing accurate input information and a solid foundation for further data-based CDSSs.This study aims to capture the online experiences of young people when interacting with algorithm mediated systems and their impact on their well-being. We draw on qualitative (focus groups) and quantitative (survey) data from a total of 260 young people to bring their opinions to the forefront while eliciting discussions. The results of the study revealed the young people's positive as well as negative experiences of using online platforms. Benefits such as convenience, entertainment and personalised search results were identified. However, the data also reveals participants' concerns for their privacy, safety and trust when online, which can have a significant impact on their well-being. We conclude by recommending that online platforms acknowledge and enact on their responsibility to protect the privacy of their young users, recognising the significant developmental milestones that this group experience during these early years, and the impact that algorithm mediated systems may have on them. We argue that governments need to incorporate policies that require technologists and others to embed the safeguarding of users' well-being within the core of the design of Internet products and services to improve the user experiences and psychological well-being of all, but especially those of children and young people.Nowadays, it is common for people to look for health care information on the internet. The eHealth Literacy Scale (eHEALS) is commonly used to measure eHealth literacy. As of the publication of this study, the Indonesian version for eHEALS has not been published even though eHealth literacy is necessary, especially in the current COVID-19 pandemic. We aimed to evaluate the validity and reliability of the Indonesian version of eHEALS (I-eHEALS). A total of 100 respondents in East Java were involved in this cross-sectional study. Pearson-product moment correlation method and construct validity were used to validate the results. The reliability was determined based on the Cronbach's alpha internal consistency measurement and intraclass correlation coefficient (ICC). The Pearson correlation analysis results are significantly higher (r > 0.254, p  less then  0.01) compared to the critical value table. Single factors accounting for 57.66% variance in the scales exhibit a unidimensional latent structure. The internal consistency between items is excellent as shown by the Cronbach's alpha coefficient (0.91). The ICC analysis shows an acceptable result (0.552, p  less then  0.01). The I-eHEALS is valid and reliable to be used for evaluating the eHealth literacy of the Indonesian population.Learning Objects represent a widespread approach to structuring instructional materials in a large variety of educational contexts. The main aim of this work consists of analyzing the process of generating reusable learning objects followed by Clavy, a tool that can be used to retrieve data from multiple medical knowledge sources and reconfigure such sources in diverse multimedia-based structures and organizations. From these organizations, Clavy is able to generate learning objects that can be adapted to various instructional healthcare scenarios with several types of user profiles and distinct learning requirements. Moreover, Clavy provides the capability of exporting these learning objects through standard educational specifications, which improves their reusability features. The analysis proposed is conducted following criteria defined by the MASMDOA framework for comparing and selecting learning object generation methodologies. The analysis insights highlight the importance of having a tool to transfer knowledge from the available digital medical collections to learning objects that can be easily accessed by medical students and healthcare practitioners through the most popular e-learning platforms.Chronic pain is a lifelong issue, being one of the main causes of disability, affecting a great number of people worldwide, many of which often avoid seeking medical advice from pain experts and/or demonstrate poor adherence to their therapeutic plan. One of the most important steps in achieving a manageable course of disease, is the ability of self-management. We aimed at applying a method of systematic patient education and self-management through the use of Virtual Patients (VPs), a well-established method for educating medical doctors and students but never before targeting patients. Two VPs scenarios were designed, tested and evaluated by patients with rheumatic disorders, achieving a SUS score of 88/100 "Best Imaginable", alongside with positive reviews from the participants. The positive feedback from the patients supports the potential of VP educational paradigm to educate these patients and equip them with disease coping skills and strategies.In Sub-Saharan Africa, young women 15-24 years of age account for nearly 30% of all new HIV infections, however, biological and epidemiological factors underlying this disproportionate infection rate are unclear. In this study, we assessed biological contributors of SIV/HIV susceptibility in the female genital tract (FGT) using adolescent (n = 9) and adult (n = 10) pigtail macaques (PTMs) with weekly low-dose intravaginal challenges of SIV. Immunological variables were captured in vaginal tissue of PTMs by flow cytometry and cytokine assays. Vaginal biopsies were profiled by proteomic analysis. The vaginal microbiome was assessed by 16S rRNA sequencing. We were powered to detect a 2.2-fold increase in infection rates between age groups, however, we identified no significant differences in susceptibility. This model cannot capture epidemiological factors or may not best represent biological differences of HIV susceptibility. No immune cell subsets measured were significantly different between groups. Inflammatory marker MCP-1 was significantly higher (adj p = .02), and sCD40L trended higher (adj p = .06) in vaginal cytobrushes of adults. Proteomic analysis of vaginal biopsies showed no significant (adj p  less then  .05) protein or pathway differences between groups. Vaginal microbiomes were not significantly different between groups. No differences were observed between age groups in this PTM model, however, these animals may not reflect biological factors contributing to HIV risk such as those found in their human counterparts. This model is therefore not appropriate to explore human adolescent differences in HIV risk. Young women remain a key population at risk for HIV infection, and there is still a need for comprehensive assessment and intervention strategies for epidemic control of this uniquely vulnerable population.A high prevalence of intimate partner violence (IPV) has been documented among women living in conflict-affected and refugee-hosting areas, but why this occurs is not well understood. Conflict and displacement deteriorate communities' social cohesion and community connectedness; these neighborhood social environments may influence individual IPV outcomes. We explored neighborhood-level social disorganization and cohesion as predictors of recent IPV in refugee-hosting communities in northern Ecuador by conducting multi-level logistic regression on a longitudinal sample of 1,312 women. Neighborhood social disorganization was marginally positively associated with emotional IPV (AOR 1.17, 95% CI .99, 1.38) and physical and/or sexual IPV (AOR 1.20, 95% CI .96, 1.51). This was partially mediated by neighborhood-level civic engagement in the case of emotional IPV. At the household level, perceived discrimination and experience of psychosocial stressors were risk factors for both types of IPV, whereas social support was protective.