View clinical trials related to Information Dissemination.
Filter by:History and scientific evidence show that it is critical to maintain public trust and confidence in vaccination. Any crisis in confidence has the potential to cause significant disruption and a detrimental impact on vaccination. Vaccine hesitancy is a complex and context-specific issue that varies across time, place, and vaccines. It has been cited by World Health Organization(WHO) as one of the top ten threats to global health in 2019. Coronavirus disease(COVID-19) pandemic may change public confidence in vaccines. Therefore, it is necessary to establish a surveillance system to monitor vaccine confidence and hesitancy in real time. To date, a growing body of literature has used social media platforms such as Twitter and weico for public health research. Large amounts of real time data posted on social media platforms can be used to quickly identify the public's attitudes on vaccines, as a way to support health communication and health promotion, messaging. However, textual data on social media is difficult to be analyzed. Recent progress in machine learning makes it possible to automatically analyze textual data on social media in real time. In this study, the investigators will establish a social media surveillance and analysis platform on vaccines, develop a series of machine learning models to monitor vaccine confidence and early detect emerging vaccine-related risks, and assess public communication around vaccines. The investigators will assess the temporal and spatial distribution of vaccine confidence and hesitancy globally using Twitter data and in China using weico data, for all vaccines and Human Papilloma Virus(HPV) vaccine, respectively. Our study will guide the design of effective health communication strategies to improve vaccine confidence.
Patient data from clinical records are increasingly recognised as a valuable resource and a number of global initiatives exist to promote and enable the sharing of data. However, some mental health service-users have expressed concerns about the use of their data by services, but these have not been explored in depth and the acceptable limits of data sharing remain unclear. The purpose of the study is to present different approaches to data sharing, with examples taken from across the world, varying in levels of anonymity and amounts of data stored and shared, with a view to extracting relevant principles directly from mental health service users. The primary objective of this study is to understand from service-users the limits of acceptable pseudonymised data sharing and data collection methods. This will inform the wider scientific community about any emerging questions and issues on pseudonymised clinical data sharing. We aim to explore the level of benefit service-users would accept, in exchange for the level of pseudonymised data they provide. Additionally, this study aims to investigate what service-users consider "identifiable" data, for example whether they consider demographic or location data or purely their real name to be identifiable. This study will ensure service-user views are an integral contribution to future pseudonymised data sharing systems, maximising applicability and acceptability. This study will use qualitative methods, in the form of focus groups, to gather service-user views. Focus groups will consider what participants believe to be identifiable data, who should get access, how should individuals and/or companies get access, how should data be protected and whether these answers change if pertaining to mental health information. Focus group data will be analysed using thematic analysis. Themes produced will be presented to participants in a second focus group. Participants will be encouraged to expand or change anything.
The aim of the proposed project is to identify an optimal implementation strategy using a set of evidence-based interventions that aim to increase early detection of breast, prostate, and colorectal cancer among African Americans as a model. These three interventions will be packaged and interwoven into a single branded project, Project HEAL (Health through Early Awareness and Learning) which will be delivered through trained Community Health Advisors (CHA) in African-American church settings. The implementation and sustainability will be evaluated using the RE-AIM Framework. Fourteen African American churches in Prince George's County, MD will be randomized to a traditional classroom training approach or an online training approach, in which the CHA training approach and level of technical assistance is varied (in-person classroom training of CHAs + monitoring/evaluation + technical assistance and training vs. online training of CHAs + monitoring and evaluation only, respectively). By varying the training methodology and level of technical assistance, we will be able to determine what level of technical assistance leads to successful implementation and sustainability. We will also identify church organizational capacity characteristics that lead to successful implementation and sustainability. The specific aims of this research are to: (1) Package the three interventions into a single branded project (Project HEAL), develop a local cancer screening resource guide, and pilot test the materials and training. (2) Implement Project HEAL in 14 churches in Prince George's County, Maryland. We will evaluate the implementation outcomes involving treatment fidelity and identify church organizational capacity characteristics that led to successful implementation. We will compare the two implementation strategies (traditional vs. online) to determine the optimal level of technical assistance necessary for successful implementation. (3) Evaluate the sustainability of Project HEAL over a two-year period of time. We will identify church organizational capacity characteristics that led to sustainability, and compare the two implementation strategies (traditional vs. online) to determine the optimal level of technical assistance for successful sustainability.
The purpose of this study is to identify and evaluate dissemination strategies to promote the uptake of evidence-based cancer and other chronic disease prevention among state-level public health practitioners. Dissemination strategies such as multi-day in-person training workshops and electronic information exchange modalities are hypothesized to associate with improved access and use of public health evidence and organizational supports for program and policy decision making based on evidence-based public health.
CPIC is a community initiative and research study funded by the NIH. CPIC was developed and is being run by community and academic partners in Los Angeles underserved communities of color. CPIC compares two ways of supporting diverse health and social programs in under-resourced communities to improve their services to depressed clients. One approach is time-limited expert technical assistance coupled with culturally-competent community outreach to individual programs, on how to use quality improvement toolkits for depression that have already been proven to be effective or helpful in primary care settings, but adapted for this study for use in diverse community-based programs in underserved communities. The other approach brings different types of agencies and members in a community together in a 4 to 6-month planning process, to fit the same depression quality improvement programs to the needs and strengths of the community and to develop a network of programs serving the community to support clients with depression together. The study is designed to determine the added value of community engagement and planning over and above what might be offered through a community-oriented, disease management company. Both intervention models are based on the same quality improvement toolkits that support team leadership, care management, Cognitive Behavioral Therapy, medication management, and patient education and activation. Investigators hypothesized that the community engagement approach would increase agency and clinician participation in evidence-based trainings and improve client mental health-related quality of life. In addition, during the design phase, community participants prioritized adding as outcomes indicators of social determinants of mental health, including physical functioning, risk factors for homelessness and employment. Investigators hypothesized by activating community agencies that can address health and social services needs to engage depressed clients, these outcomes would also be improved more in the collaboration condition. Investigators also hypothesized that the collaboration approach would increase use of services.
The transition from hospital to home is a high-risk period in a patient's illness. Poor communication between healthcare providers at hospital discharge is common and contributes to adverse events affecting patients after discharge. The importance of good communication at discharge will increase as more primary care providers delegate inpatient care to hospitalists. Any process that improves information transfer among providers at discharge might improve the health and safety of patients discharged from U.S. hospitals each year, and to appreciably reduce unnecessary healthcare expenditures. Information transfer among healthcare providers and their patients can be undermined because of inaccuracies, omissions, illegibility, logistical failure (e.g., information is never delivered), and delays in generation (i.e., dictation or transcription) or transmission. Root causes include recall error, increased physician workloads, interface failures (e.g., physician-clerical) and poor training of physicians in the discharge process. Many of the deficiencies in the current process of information transfer at hospital discharge could be effectively addressed by the application of information technology. The proposed study will measure the value of a software application to facilitate information transfer at hospital discharge. The study is designed to compare the benefits of discharge health information technology versus usual care in high-risk patients recently discharged from acute care hospitalization. The design is a randomized, single-blind, controlled trial. The outcomes are readmission within 6 months, adverse events, and effectiveness and satisfaction with the discharge process from the patient and physician perspectives. The cost outcome is the physician time required to use the discharge software.