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579 results for “supportive care”
Data and supplementary material in support of article "Can robots express facial emotions dominantly enough for use in dementia care?"
<p>Data and supplementary material in support of article "Vlachos, E. and Tan, Z. H. (2020). Can robots express facial emotions dominantly enough for use in dementia care?, <em>International Psychogeriatrics</em>, Cambridge University Press". </p> <p>Our objective is to evaluate the recognition, and denomination of the six basic emotional facial expressions as displayed by a social robot to persons with dementia, and to compare it with the results from the evaluation of static photographs of humans from the Paul Ekman database in order to investigate the differences in recognition rates among the two stimuli.</p>
Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning: A real-world case study of decision support system using blood test & GP referral letters - Bing Wang and Prof Weizi (Vicky) Li (University of Reading)
<p>This video is the sixth talk from our two day Future Blood Testing: Challenges & Opportunities Event that took place on the 13/09/2022.</p> <p>Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning: A real-world case study of decision support system using blood test & GP referral letters - Bing Wang and Prof Weizi (Vicky) Li (University of Reading)</p> <p>Bio: Dr Weizi (Vicky) Li is the PI of the Future Blood Testing Network, an Associate Professor of Informatics and Digital Health, Deputy Director in Informatics Research Centre, Henley Business School, University of Reading. She is an interdisciplinary researcher focusing on using informatics, data science, machine learning, and digital information systems to solve real-world healthcare challenges. She is the academic lead of a large collaborative project of Improving the Quality of Healthcare through an Integrated Clinical Pathway Management Approach and Cloud based Digital Data Integration Platform, which was awarded ESRC O2RB Excellence in Impact Award in 2018 for her research impact on healthcare quality improvement. She is the academic lead of machine learning based decision support system for outpatient management which has successfully been implemented in Royal Berkshire NHS Foundation Trust and has received Research Engagement and Impact award in 2020. She has been PI on projects funded by ESRC, EPSRC, The Health Foundation, NHS and companies, working on data-driven decision support systems that use real-world data (under privacy preserving framework) from multiple sources including Electronic Patient Record in acute, community hospital and primary care settings, remote health monitoring and patient reported outcomes to develop novel technologies (including AI based methods) to support clinical and operational decision makings in patient pathway. Bing Wang is currently a PhD candidate in informatics and system science at the Informatics Research Center, Henley Business School, University of Reading. Bing’s research interests are Natural Language Processing, Machine Learning and Graph Machine Learning. Bing been working as a data scientist at Royal Berkshire NHS Foundation Trust since December 2019 during his PhD.</p> <p>Further details on this event can be found at: https://futurebloodtesting.org/event/13-14-09-2022/</p> <p>This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1</p> <p>YouTube Link: https://youtu.be/W6EH5l80NmU</p>
Study in Primary Care Evaluating Inclisiran Delivery Implementation + Enhanced Support
ClinicalTrials.gov study NCT04807400. IPD Sharing: YES. Countries: 1. Publications: 2.
Everolimus Plus Best Supportive Care vs Placebo Plus Best Supportive Care in the Treatment of Patients With Advanced Neuroendocrine Tumors (GI or Lung Origin)
ClinicalTrials.gov study NCT01524783. IPD Sharing: YES. Countries: 25. Publications: 5.
Individualized Nutritional Support versus Usual Care in Medical Inpatients at Risk of Malnutrition: Randomized Trial
<p>Dataset for analysis of the trial "Individualized Nutritional Support versus Usual Care in Medical Inpatients at Risk of Malnutrition"</p>
CONSORT flow diagram for The assessment of educational and supportive care to the infertile females undergoes In Vitro Fertilization procedure by clinical pharmacist: a randomized clinical trial
<p><strong>The assessment of educational and supportive care to the infertile females undergoes In Vitro Fertilization procedure by </strong>a <strong>clinical pharmacist: a randomized clinical trial</strong>.</p>
Quality of care and performance indicators of mental health supported accommodation services in England
<p class="MsoNormal"><span>This dataset includes data from Mental Health supporting accommodation services in England. It includes information on resources (inputs) and outcomes (outputs) of care, which are described in the manuscript published in Plos One: "Almeda, N., García-Alonso, C. R., Killaspy, H., Gutiérrez-Colosía, M. R., & Salvador-Carulla, L. (2022). The critical factor: The role of quality in the performance of supported accommodation services for complex mental illness in England. Plos One, 17(3), e0265319. https://doi.org/10.1371/journal.pone.0265319"</span></p> <p class="MsoNormal"><span>The research associated with the present data focused on developing an analytical process for assessing the performance of the Mental health (MH) supporting accommodation services from 14 different regions of England considering the effect of the quality-of-care indicators in the performance. For doing so every service was classified in Residential Care (move on and non-move on oriented), Supported Housing or Floating Outreach. Then, information about the quality-of-care was collected from each domain of the instrument QuIRC-SA. Finally, a decision support system that integrated data envelopment analysis, Monte Carlo simulation and artificial intelligence was used.</span></p> <p class="MsoNormal"><span>The main results of the analyses pointed out that the incorporation of quality domains as variables (outputs) in DEA had a neutral-positive or positive global impact on the performance of MH-supported accommodation services.</span></p>
Supporting information for: The Time Requirements for Primary Care Consultations: Initial Sick Child Visits in Low- and Middle-income Countries Using the Integrated Management of Childhood Illness (IMCI) Clinical Algorithm
<p>Few studies have examined the time required for primary care consultations; none have focused on sick child visits in low- and middle-income countries (LMICs). This project begins to fill that gap by providing evidence-based estimates of the time needed for initial visits with under-five infants and children at public or not-for-profit facilities in countries using the Integrated Management of Childhood Illness (IMCI) clinical algorithm.</p> <p>Estimates of the mean expected duration of IMCI consultations require (a) classification profiles, i.e., tabulations of the gold standard health issues presented by patients less than 5 years old; (b) lists of the tasks included in applicable versions of the IMCI algorithm and the conditions that elicit them, and (c) an estimate of the time needed to perform tasks with no pre-defined minimum duration. The latter requires, in addition to classification profiles, information on rates of task performance and the mean observed duration of consultations.</p> <p>The IMCI clinical algorithm and the research surrounding it provide unusually rich sources of such information. Developed in the mid 1990s by the World Health Organization and the United Nations Children’s Fund, the IMCI algorithm seeks to reduce child mortality in LMICs by improving the technical quality of primary care services. For infants less than 2 months old, the algorithm focuses on bacterial infections, feeding problems, low weight, and, in some versions, jaundice. For children 2-59 months old, the foci include acute respiratory infections, especially pneumonia; diarrhea; fevers, especially malaria and measles; malnutrition, and anemia. Immunization status is a concern for both age groups. The algorithm provides a scheme to classify the health issues with which infants and children present, an array of tasks providers may be expected perform, and criteria by which tasks are elicited. Research on the design and utility of the algorithm, its effects on provider performance, and related topics furnishes data on the prevalence of gold standard IMCI classifications in a variety of patient populations. In some cases, it also enables one to calculate the time required to perform tasks.</p> <p>I found such information by searching MEDLINE, the database of the International Network for Rational Use of Medicines, the websites of the WHO and its regional offices, GOOGLE, and GOOGLE SCHOLAR using search terms such as ‘Integrated Management of Childhood Illness’, ‘observational’, ‘prospective’, ‘classification’, ‘clinical signs’, ‘health facility survey’, and ‘validity’. I also reviewed studies that cited a qualified study and, conversely, material included in the bibliographies of qualified studies.</p> <p>The supplemental information files contain the following:</p> <p>WORKBOOK S1_STUDIES USED</p> <p>Lists features of, and sources for, the studies used to construct classification profiles and to estimate the time required to perform the average task with no predefined minimum duration. With 2 exceptions (see below, DATA S1 and DATA S2), all the studies have been published or are readily available on the internet. None of the data can be used to identify individuals.</p> <p>DATA S1_REPORT OF THE HEALTH FACILITY SURVEY IN BOTSWANA, 2007-08 and DATA S2_REPORT OF THE HEALTH FACILITY SURVEY IN TANZANIA, 2003</p> <p>PDF files of Health Facility Survey reports that were found on the internet but have since been taken down.</p> <p>DATA S3_BURKINA FASO CHART BOOKLET, 2015</p> <p>PDF provided <span>Drs. Sophie Sarrassat (London School of Hygiene and Tropical Medicine) and Serge M. A. Somda (Université Nazi BONI).</span></p> <p>WORKBOOK S2_CLASSIFICATION PROFILES: INFANTS; WORKBOOK S3_CLASSIFICATION PROFILES: CHILDREN IN UPPER MIDDLE-INCOME COUNTRIES; WORKBOOK S4_CLASSIFICATION PROFILES: CHILDREN IN LOWER MIDDLE-INCOME COUNTRIES (I); WORKBOOK S5_CLASSIFICATION PROFILES: CHILDREN IN LOWER MIDDLE-INCOME COUNTRIES (II), and WORKBOOK S6_CLASSIFICATION PROFILES: CHILDREN IN LOW INCOME COUNTRIES </p> <p>The design of the worksheets in these workbooks is described in TEXT S1_NOTES OF THE CONSTRUCTION OF CLASSIFICATION PROFILES (see below).</p> <p>WORKBOOK S7_IMCI CLINICAL TASKS</p> <p>Lists the clinical tasks provided by relevant IMCI algorithms for the care of infants and children. Consists of 6 worksheets covering mandatory tasks, conditional assessments, and treatment and counseling tasks for infants and children.</p> <p>WORKBOOK S8_MINUTES PER TASK WITH NO MINIMUM DURATION</p> <p>Provides estimate of the mean time required to perform a task with no minimum duration for each of 7 populations for which the required data are available, corrected, where necessary, for the effect of an observer on the rate and pace of task performance. Also provides a geometric mean for all 7 populations.</p> <p>TEXT S1_NOTES ON METHODOLOGY</p> <p>WORD document describing the steps involved in estimating the expected durations of consultations.</p> <p>TEXT S2_NOTES OF THE CONSTRUCTION OF CLASSIFICATION PROFILES</p> <p>WORD document describing the steps involved in constructing each profile, problems encountered, and how they were solved.</p> <p>TEXT S3_NOTES ON THE IDENTIFICATION OF IMCI CLINICAL TASKS</p> <p>WORD document describing the standards used in identifying clinical tasks in IMCI algorithms.</p> <p>TEXT S4_NOTES ON THE ESTIMATION OF MINUTES PER TASK WITH NO MINIMUM DURATION</p> <p>WORD document describing the steps involved in estimating the mean time required to perform a task with no predefined minimum duration, problems encountered, and how they were solved.</p>
Training of maternity service providers on supportive and dignified maternity care: pre-post training assessment
<p>Poor psychosocial support and lack of respectful care for women during childbirth are commonplace in health facilities in low- and middle-income countries. While WHO recommends providing supportive care to pregnant women, there is a scarcity of material for building the capacity of maternity staff to provide systematic and inclusive psychosocial support to women in the intrapartum phase and prevent work stress and burnout in maternity teams. To address this need we adapted WHO's mhGAP and its training manual for maternity care staff to provide psychosocial support in labour room settings. Mental Health Gap Action Programme (mhGAP) is an evidence-based intervention which focuses on providing psychosocial support to people with mental, neurological and substance-use disorders (MNS).</p> <p>The objective of this paper is to describe the adaptation of mhGAP to develop psychosocial support-capacity-building materials for maternity staff to provide support to maternity patients, and also to staff, in the labour room.</p> <p>Adaptation was conducted within the Human-Centered Design framework in three phases: inspiration, ideation, and implementation feasibility. In the inspiration phase, a review of national-level maternity service-delivery documents and formative study via in-depth interviews of maternity staff were conducted. Ideation involved a multidisciplinary team to develop capacity-building materials by adapting mhGAP. This phase was iterative and included cycles of pretesting with staff, deliberations among the core team, and revision of materials. In the implementation feasibility phase, materials were tested via the training of 98 maternity staff and exploring system feasibility via post-training visits to health facilities.</p> <p>The inspiration phase identified gaps in policy directives and implementation. A formative study found that staff lacked the understanding and skills to assess patients' psychosocial needs and provide appropriate support. Allied with this, it became evident that maternity staff themselves needed psychosocial support. In ideation, the team developed capacity-building materials comprising two modules: one dedicated to conceptual understanding, and the other to implementing psychosocial support in collaboration with maternity staff. In the implementation feasibility phase, Staff found the materials relevant, acceptable and feasible for the labour room setting. Finally, users and experts reviewed and endorsed the relevance and usefulness of the materials. </p> <p>Our work in developing psychosocial-support training materials for maternity staff extends the utility of mhGAP by building the capacity of maternity staff to identify specific, hitherto-neglected needs of patients and staff, and by supporting, respectively, pregnant women to have positive birthing experiences, and maternity staff to manage workplace stress and avoid burnout. These materials can be used in a similar maternity setting after cultural adaptation.</p>
Program of Intensive Support in Emergency Departments for Care Partners of Cognitively Impaired Patients
ClinicalTrials.gov study NCT03325608. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Care Partners: Web-based Support for Caregivers of Veterans Undergoing Chemotherapy
ClinicalTrials.gov study NCT00983892. IPD Sharing: NO. Countries: 1. Publications: 1.
CONFIDENT: Supporting Long-term Care Workers During COVID-19
ClinicalTrials.gov study NCT05168800. IPD Sharing: YES. Countries: 1. Publications: 2.
A Study to Evaluate the Efficacy and Safety of CNTO328 Plus Best Supportive Care in Multicentric Castleman's Disease
ClinicalTrials.gov study NCT01024036. IPD Sharing: Not stated. Countries: 23. Publications: 3.
Supportive Care for Cognitively Impaired Patients and Families
ClinicalTrials.gov study NCT03881579. IPD Sharing: YES. Countries: 1. Publications: 0.
Collaborative Perinatal Mental Health and Parenting Support in Primary Care
ClinicalTrials.gov study NCT02724774. IPD Sharing: NO. Countries: 1. Publications: 3.
Effect of Peer Support Intervention on Medication Adherence, Self-care and Knowledge Among Patients With Diabetes
ClinicalTrials.gov study NCT07145983. IPD Sharing: NO. Countries: 1. Publications: 16.
Supporting Decisions About Health Insurance to Improve Care for the Uninsured
ClinicalTrials.gov study NCT02522624. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Integrating Online Weight Management With Primary Care Support
ClinicalTrials.gov study NCT02656693. IPD Sharing: NO. Countries: 1. Publications: 3.
Work And Vocational advicE Study - Effectiveness of Adding a Brief Vocational Support Intervention to Usual Primary Care
ClinicalTrials.gov study NCT04543097. IPD Sharing: YES. Countries: 1. Publications: 1.
Family Support Intervention in Intensive Care Units
ClinicalTrials.gov study NCT05280691. IPD Sharing: NO. Countries: 1. Publications: 7.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.