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599 results for “health data”
Data from: Postpartum family planning integration with maternal, newborn, and child health services: a cross-sectional analysis of client flow patterns in India and Kenya
Objectives: Maternal, newborn, and child health (MNCH) services represent opportunities to integrate postpartum family planning (PPFP). Objectives were to determine levels of MNCH-family planning (FP) integration and associations between integration, client characteristics, and service delivery factors in facilities that received programmatic PPFP support. Design and setting: Cross-sectional client flow assessment conducted May–July 2014, over 5 days at 10 purposively selected public sector facilities in India (four hospitals) and Kenya (two hospitals, four health centers). Participants: 2,158 client visits tracked (1,294 India; 864 Kenya). Women aged 18 or older accessing services while pregnant and/or with a child under 2 years. Interventions: PPFP/postpartum intrauterine device—Bihar, India (2012–2013); Jharkhand, India (2010–2014); Embu, Kenya (2008–2012). Maternal, infant, and young child nutrition/FP integration—Bondo, Kenya (2011–2013). Primary outcome measures: Proportion of visits where clients received integrated MNCH-FP services, client characteristics as predictors of MNCH-FP integration, and MNCH-FP integration as predictor of length of time spent at facility. Results: Levels of MNCH-FP integration varied widely across facilities (5.3% to 63.0%), as did proportion of clients receiving MNCH-FP integrated services by service area. Clients traveling 30–59 minutes were half as likely to receive integrated services versus those traveling under 30 minutes (odds ratio [OR] 0.5, 95% confidence interval [CI] 0.4–0.7, p<.001). Clients receiving MNCH-FP services (versus MNCH services only) spent an average of 10.5 minutes longer at the facility (95% CI −0.1–21.9, not statistically significant). Conclusions: Findings suggest importance of focused programmatic support for integration by MNCH service area. FP integration was highest in areas receiving specific support. Integration does not seem to impose an undue burden on clients in terms of time spent at the facility. Clients living furthest from facilities are least likely to receive integrated services.
Data from: Association between attitudes of stigma toward mental illness and attitudes toward adoption of evidence-based practice within health care providers in Bahrain
<p><span>The health care system is one of the key areas where people with mental illnesses could experience stigma. Clinicians can hold stigma attitudes during their interactions with patients with mental illness. To improve the quality of mental health services and primary care, evidence-based practices should be disseminated and implemented. In this study, <a name="_Hlk23098053">we evaluated the attitudes of health care providers in Bahrain toward people with mental illness and adoption of evidence-based practice </a>using the Opening Minds Stigma Scale for Healthcare Providers (OMS-HC) and Evidence-Based Practice Attitude Scale (EBPAS).<b> </b>We conducted a cross-sectional study across 12 primary health care centers and a psychiatric hospital (the country's main mental health care facility). A self-report questionnaire was distributed among all health care providers.<b> </b>A total of 547 health care providers participated, with 274 from mental health services and 273 from primary care services. Results of the OMS-HC indicated differences between both main groups and subgroups. Regression model analysis reported significant outcomes. There was no statistical difference found between both groups in EBPAS scores. A weak but statistically significant negative association was reported between both scales.<b> </b>Participants showed varying stigma attitudes across different working environments, with less stigma shown in mental health services than in primary care services. <a name="_Hlk23098110">Providers who were more open to adopting evidence-based practices showed less stigma toward people with mental illness. Comparing our findings with previous research</a> showed that health care providers in Bahrain hold more stigma attitudes than other groups studied. We hope that this study serves as an initial step toward future campaigns against the stigma of mental illness in Bahrain and across the region.</span></p>
Philippines - Open, validated health, climate, environment and socioeconomic data
<p>The <strong>Project Climate Change, Health, and Artificial Intelligence (Project CCHAIN)</strong> dataset is a validated, open-sourced linked dataset containing 20 years (2003-2022) of climate, environmental, socioeconomic, and health dimensions at the barangay (village) level across twelve Philippine cities (Dagupan, Palayan, Navotas, Mandaluyong, Muntinlupa, Legazpi, Iloilo, Mandaue, Tacloban, Zamboanga, Cagayan de Oro, Davao).</p> <p>The full documentation can be accessed <a href="https://thinkingmachines.github.io/project-cchain">here</a>.</p> <p>The tables are designed in a way that users can <strong>choose variables that are most relevant</strong> to their focus city and use case, and <strong>link these variables</strong> to form a single dataset by merging using standard geography codes and calendar dates. This can be done using the provided <a href="https://drive.google.com/drive/folders/123MrMXSVT6149MvJ8hGoDgN1s-YlQoH_">linking notebook</a>, or offline using the user's own code.</p> <p>Here are some tips on how make most use of this dataset:</p> <ul> <li> <p><strong>Focus on one location.</strong> Starting with a detailed analysis of one location allows for a better understanding of the local dynamics, which may differ across locations.</p> </li> <li> <p><strong>Choose one health data source.</strong> Pick one of either a central or local data source. Using two different data health sources is not advised because it will lead to double/overcounting of disease cases.</p> </li> <li> <p><strong>Do not use all variables at once- do a literature review first to identify possible key variables</strong>. to identify possible key variables. More often than not, using all variables is not necessary and may even yield subpar results.</p> </li> <li> <p><strong>Check data availability</strong> on your focus location and make sure they fit the requirements of your study.</p> </li> </ul>
Supplementary Material for Healthcare costs following falls and cataract surgery in older adults using Australian linked health data from 2012–2019
<p><strong>Note</strong>: The material contained herein is supplementary to the article:</p><p>Huang-Lung J, Chun Ho K, Lung T, Palagyi A, McCluskey P, White AJR, Boufous S, Keay L. Healthcare costs following falls and cataract surgery in older adults using Australian linked health data from 2012–2019. Public Health Res Pract. November 2023; Online early publication. https://doi.org/10.17061/phrp33342311</p><p> </p><p><strong>Contents</strong></p><p>Appendix Table A1. Details of linked administrative health data extracted for this study. </p><p>Appendix Table A2. ICD-10-AM codes for identification of fall-related hospital admissions in this study. As multiple diagnosis codes can be recorded for each hospital admission, all diagnosis codes associated with the episode of care were considered. </p><p>Appendix Table A3. SNOMED CT codes associated with fall-related emergency department presentations observed in this study. The SNOMED CT codes were searched in the CSIRO Shrimp database, version dated 31/10/21 (http://ontoserver.csiro.au/shrimp/). </p><p>Appendix Table A4. Results from the multivariable generalised linear model assessing factors associated with higher healthcare costs in study participants. </p><p>Appendix Table A5. Mean monthly healthcare costs according to cataract surgeries, sex and faller status groups, estimated from the generalised linear model using marginal means, with co-variates appearing in the model fixed at the following mean values: age = 75.5 and medications = 4.5.</p><p>Appendix Box 1. Data cleaning methods. </p><p>Figure A1. Flowchart of the study cohort. </p>
Dataset for "Public Health Benefits from Improved Identification of Severe Air Pollution Events with Geostationary Satellite Data"
<p>Dataset for "Public Health Benefits from Improved Identification of Severe Air Pollution Events with Geostationary Satellite Data" to be published in GeoHealth doi: 10.1029/2023GH000890</p>
Delving into the Impact of Stress on Mental Health: A Data-Driven Approach
<p>This comprehensive dataset delves into the intricate relationship between stress and mental health, providing valuable insights for researchers, healthcare professionals, and individuals alike. The dataset encompasses a diverse range of variables, including self-reported stress levels, standardized mental health assessments, demographic information, and lifestyle factors. This rich data empowers researchers to conduct in-depth analyses and uncover the multifaceted connections between stress and mental Health.</p>
Supplements and underlying data for the study: Using Health Claims to Teach Evidence-Based Practice to Healthcare Students: A Mixed Methods Study
<p>Supplements and English translation of the Norwegian data sets, in addition to checklists for the manuscript.</p>
Figures for Developing an online data-driven approach for prognostics and health management of lithium-ion batteries
Open the record for dataset details and reuse information.
Data for "Citizen Science for Health: an international survey on its characteristics and enabling factors"
<p>Data and data analysis code for manuscript "Citizen Science for Health: an international survey on its characteristics and enabling factors"</p>
Covid Data from WHO (World Health Organization)
<p>Created and published by José Luis Villar, using github user "thisnotatest".</p>
COVIDIAGNOSTIX - Health Technology Assessment in Covid serological diagnostics - Data OPBG
<p><strong>COVIDIAGNOSTIX - Health Technology Assessment in Covid serological diagnostics</strong>.</p> <p>SARS-COV-2 serologcal results, obtained in serial evaluations at 0,1,3,6 months from the first dose of anti-Sars-CoV-2 vaccine, in the healthcare workers of the Bambino Gesù Children' Hospital. The antibody dosage was performed with the Roche (anti-N and anti-S) and DiaSorin (anti-S Trimeric) assays.</p> <p><em><strong>COVID-2020-12371619 funded by the Italian Ministry of Health - </strong></em>Codice CUP C49C20000080001</p> <p> </p>
Health condition data for Platypus from New South Wales and Victoria
<p>Platypuses (<i>Ornithorhynchus anatinus</i>) inhabit the permanent rivers and creeks of eastern Australia, from north Queensland to Tasmania, but are experiencing multiple and synergistic anthropogenic threats. Baseline information of health is vital for effective monitoring of populations but is currently sparse for mainland platypuses. Focusing on six hematology and serum chemistry metrics as indicators of health and nutrition (packed cell volume (PCV), total protein (TP), albumin, globulin, urea, creatinine, and triglycerides), we investigated their variation across the species' range and across seasons. We analyzed 259 samples collected from platypuses in three river catchments in New South Wales and Victoria. Health metrics significantly varied across the species' range, with platypuses from the most northerly catchment, having lower levels of PCV, albumin and triglycerides, potentially reflecting thermal stress. The Snowy River showed significant seasonal patterns<b> </b>which varied between the sexes and coincided with differential reproductive stressors. Male creatinine and triglyceride levels were significantly lower than females, suggesting that reproduction is energetically more taxing on males. Age specific differences were also found, with juvenile PCV and TP levels significantly lower than adults. Additionally, the commonly used body condition index (tail volume index) was only negatively correlated with urea, and triglyceride levels. A meta-analysis of available literature <a>did not reveal any significant latitudinal relationship</a>, but this was confounded by variation in sampling times which is not commonly reported. We provide the first reference intervals of hematology and blood chemistry for mainland platypus, highlighting the importance of considering seasonal variation, enabling future assessments of individual and population health.</p>
Food and waterborne outbreaks data complementing the European Union One Health 2020 Zoonoses Report
<p>Food and waterborne outbreaks data reported under the framework of Directive 2003/99/EC and in accordance with the update of the technical specifications for harmonised reporting of FBOs through the EU reporting system in accordance with Directive 2003/99/EC. This dataset includes the number of outbreaks, as well as the number of human cases, hospitalisations and deaths, per causative agent. In addition, other information can include data on causative agents, food vehicles, and the factors in food preparation and handling that contributed to the food-borne outbreaks. Reporting countries can also provide information on the nature of the evidence supporting the suspicion of the food vehicle. This evidence can be epidemiological, microbiological, descriptive environmental, or based on product tracing investigations. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: PubliFBO2020_20211109: >></p>
Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Croatia
<p>This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agents in foodstuffs. Relevant EU legislation: Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014.</p>
Animal population data complementing the European Union One Health 2020 Zoonoses Report
<p>This dataset includes animal population aggregated data under the framework of Directive 2003/99/EC. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: Animal_p20_20211109: >></p>
Data from: Assessment of fear, anxiety, obsession and functional impairment due to COVID-19 amongst health-care workers and trainees: a cross-sectional study in Nepal
<p><b>Background:</b> The emergence of the COVID-19 epidemic threw the world into turmoil. The medical community bore the brunt of the pandemic's toll. It became clear that there was a shortage of medical personnel and resources. Long work hours, and a lack of personal protective equipment (PPE) and social support all had an influence on mental health.</p> <p><b>Methods: </b>This cross-sectional study was conducted among Lumbini Medical College Teaching Hospital students and employees in Palpa, Nepal. Data entailing their demographic details, pre-existing comorbidities, or death in the family due to COVID-19 was collected using a self-administered survey. In addition, the level of fear, anxiety, obsession, and functional impairment due to COVID-19 was recorded using previously validated respective scales.</p> <p><b>Results:</b> In total, 403 health care workers and trainees participated in our study. The average age of the study participants was 23±4 years, and more than half of them (n=262, 65%) were females. A significant association was found between fear score with age (p=0.04), gender (p-value <0.01) and occupation (p-value<0.001). Participants suffering from chronic diseases (p-value=0.36), and those who had experienced a COVID-19 death in the family (p-value=0.18), were not found to be significantly obsessed with COVID-19. However, for those who had experienced a COVID-19 death in the family (p-value=0.51) and age (p-value=0.34), these factors were not found to be significantly associated with higher anxiety levels. Nursing students suffered from a significantly greater functional impairment than people of other medical professionals (mean score=269.15, p-value < 0.001). A moderately positive correlation was observed between fear, anxiety, obsession, and functional impairment scales.</p> <p><b>Conclusion:</b> Unpredictability and uncertainty are considerable in the aftermath of the pandemic. People's psychological well-being deteriorates due to the repercussions of developing a severe sickness, being isolated, and confronting the stigma of being infected. With the health care personnel at the front lines, the stakes are considerably higher for them. This study revealed various socio-demographic characteristics as risk factors for psychological stress in the healthcare personnel of Nepal during the COVID-19 pandemic. A viable answer to this quandary might be adequate psychosocial intervention by health care authorities, increased social support, and the introduction of better mental health management measures for healthcare personnel.</p>
Data from: Crop health is predicted by soil microbial diversity across phylogenetic scales
<p>Soils contain diverse living communities that provide key ecosystem functions in agroecosystems. In many systems, ecosystems functions are positively related to the taxonomic, phylogenetic, and functional diversity of the community. Despite calls to incorporate microbial diversity in measures of soil health, whether increased microbial diversity <em>per se</em> can predict increased crop health and productivity has rarely been documented. Here we used microbial communities from commercial potato fields varying in diversity and composition, and experimentally assessed their ability to promote crop yield under low or high nutrient conditions and to suppress a soil-borne pathogen. Across two independent sets of communities, we found that yields under low nutrient conditions were predicted by high initial microbial diversity measured at broad phylogenetic levels, consistent with greater niche complementarity among unrelated taxa leading to greater total resource use. However, disease suppression was inconsistently linked to diversity and explained as well or better by microbial composition rather than diversity <em>per se</em>. Ecosystem multifunctionality was predicted by high diversity at broad to intermediate phylogenetic scales. These results indicate that the diversity of microbial taxa may influence multiple soil functions; however, the mechanisms underlying the diversity-function relationships may vary.</p>
Attitudes of Health Care Professionals Toward Older Adults' Abilities to Use Digital Technology: Open Access Data Sets
<p>Open access dataset related to 2 studies published under:</p> <p>Mannheim I, Wouters EJM, van Boekel LC, van Zaalen Y<br> Attitudes of Health Care Professionals Toward Older Adults’ Abilities to Use Digital Technology: Questionnaire Study<br> J Med Internet Res 2021;23(4):e26232<br> URL: https://www.jmir.org/2021/4/e26232<br> doi: 10.2196/26232</p>
Data and code from: A spectral three-dimensional color space model of tree crown health
<p>Protecting the future of forests in the United States and other countries depends in part on our ability to monitor and map forest health conditions in a timely fashion to facilitate management of emerging threats and disturbances over a multitude of spatial scales. Remote sensing data and technologies have contributed to our ability to meet these needs, but existing methods relying on supervised classification are often limited to specific areas by the availability of imagery or training data, as well as model transferability. Scaling up and operationalizing these methods for general broadscale monitoring and mapping may be promoted by using simple models that are easily trained and projected across space and time with widely available imagery. Here, we describe a new model that classifies high resolution (~1 m<sup>2</sup>) 3-band red, green, blue (RGB) imagery from a single point in time into one of four color classes corresponding to tree crown condition or health: green healthy crowns, red damaged or dying crowns, gray damaged or dead crowns, and shadowed crowns where the condition status is unknown. These Tree Crown Health (TCH) models trained on data from the United States (US) Department of Agriculture, National Agriculture Imagery Program (NAIP), for all 48 States in the contiguous US and spanning years 2012 to 2019, exhibited high measures of model performance and transferability when evaluated using randomly withheld testing data (<em>n</em> = 122 NAIP state x year combinations; median overall accuracy 0.89-0.90; median Kappa 0.85-0.86). We present examples of how TCH models can detect and map individual tree mortality resulting from a variety of nationally significant native and invasive forest insects and diseases in the US. We conclude with discussion of opportunities and challenges for extending and implementing TCH models in support of broadscale monitoring and mapping of forest health.</p>
Data on community-based health insurance enrollment trends in northeast Ethiopia
Background <p>The term "community-based health insurance" refers to a broad range of nonprofit, prepaid health financing models designed to meet the health financing needs of disadvantaged populations, particularly those in the rural and informal sectors. Due to their voluntary nature, such initiatives suffer from persistently low coverage in low- and middle-income countries. In Ethiopia, the schemes' membership growth has not been well investigated so far. This study sought to examine the scheme's enrollment trend over a five-year period, and to explore the various challenges that underpin membership growth from the perspectives of various key stakeholders.</p> Results <p>Over the course of the study period, enrollment in the scheme at both districts exhibited non-linear trends with both positive and negative growth rates being identified. Overall, the scheme in Tehulederie has a relatively higher population coverage and better membership retention, which could be due to the strong foundation laid by a rigorous public awareness campaign and technical support during the pilot phase. The challenges contributing to the observed level of performance have been summarized under four main themes that include quality of health care, claims reimbursement for insurance holders, governance practices, and community awareness and acceptability. </p> Conclusions <p>The scheme experienced negative growth ratios in both districts, indicating that it is not functionally viable. It will fail to meet its mission unless relevant stakeholders at all levels of government demonstrate political will and commitment to its implementation, as well as advocate for the community. Interventions should target on the highlighted challenges in order to boost membership growth and ensure the scheme's viability.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.