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2,586 results for “nursing”
Nursing Education Study
<p>The objective of this study was to evaluate the effectiveness of an educational intervention based on the creation of video-pills to improve teamwork, communication, and digital skills among first-year nursing students, with a follow-up assessment one year after the intervention.</p> <p>This Dataset shows results from the questionnaires done pre and afer the intervention by the Nursing Degree students coming from University of Zaragoza.</p> <p>Two questionnaires were provided:</p> <p>- Teamwork questionnaire. This questionaire was completed pre and post-intervention, and one year later (super-post). Just in the post-intervention, a co-evaluation of a partner was included in order to compare their self-perception competencies with them from their partners. </p> <p>- Comunicative&Digital tools skills questionaire (C&D skills). This questionaire was completed pre and post-intervention, and one year later (super-post). </p> <p>.</p>
Dataset of the publication "Cross-sectional study of prevalence of dementia, behavioural symptoms, mobility, pain and other health parameters in nursing homes in Austria and the Czech Republic: results from the DEMDATA project"
<p>Dataset of the publication Stefanie R. Auer , Margit Höfler, Elisabeth Linsmayer, Anna Beránková, Doris Prieschl, Paulina Ratajczak,<br> Michal Šteffl and Iva Holmerová (2018) "Cross-sectional study of prevalence of dementia, behavioural symptoms, mobility, pain and other health parameters in nursing homes in Austria and the Czech Republic: results from the DEMDATA project"</p>
Fig. 3 in Evasive mating behaviour by female nurse sharks, Ginglymostoma cirratum (Bonnaterre, 1788), in an equatorial insular breeding ground
Fig. 3. Nurse shark mating activity witnessed at Enseada dos Tubarões, Fernando de Noronha. The panels depict (I) an aggregation of at least 14 nurse sharks in shallow water adjacent to the shore; (II) a pregnant female shark; (III) a group of 8 female sharks clustering together in shallow waters; (IV) a female shark exhibiting (a) a freshly-inflicted, crescent-shaped bite mark on the left pectoral fin; (V) a female shark exhibiting (b) a freshly-inflicted, crescent-shaped bite mark on the right pectoral fin; (VI) a female shark exhibiting (c) a freshly-inflicted bite mark on the tip of the caudal fin.
Fig. 2 in Evasive mating behaviour by female nurse sharks, Ginglymostoma cirratum (Bonnaterre, 1788), in an equatorial insular breeding ground
Fig. 2. Nurse shark mating activity witnessed at Baía do Sueste, Fernando de Noronha. The panels depict (I) a coupling male shark (a) grasping the female pectoral fin with his mouth while coiling his body around the female, as evidenced by the alignment of male (b) first dorsal and (c) caudal fins; (II) a female shark ventral side up exhibiting emerged pelvic fins; (III) a female shark ventral side up rising her (d) right pectoral fin and (e) pelvic fins out of the water; (IV) a stranded female shark; (V) a female shark exhibiting f) a cloaca suggestive of earlier copulatory activity while being harassed by (g) a male shark; (VI) a female shark exhibiting (h-i) two small, crescent-shaped bite marks on the caudal fin.
Fig. 1 in Evasive mating behaviour by female nurse sharks, Ginglymostoma cirratum (Bonnaterre, 1788), in an equatorial insular breeding ground
Fig. 1. Map of the Archipelago of Fernando de Noronha (FEN), Brazil, depicting the locations of (a) Baía do Sueste and (b) Enseada dos Tubarões, where nurse shark mating activity was witnessed. The "X" in the inset represents the location of FEN in relation to South America. Map plotted with ggmap package (Kahle & Wickham, 2013) in R statistical software.
Linked collectors and determiners for: A new species of nurse-frog (Aromobatidae, Allobates) from the Juami River basin, northwestern Brazilian Amazonia.
Natural history specimen data linked to collectors and determiners held within, "A new species of nurse-frog (Aromobatidae, Allobates) from the Juami River basin, northwestern Brazilian Amazonia". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/a501cc62-619a-4c9b-b350-58a3aada4240">https://bionomia.net/dataset/a501cc62-619a-4c9b-b350-58a3aada4240</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/a501cc62-619a-4c9b-b350-58a3aada4240">https://gbif.org/dataset/a501cc62-619a-4c9b-b350-58a3aada4240</a>. Formatted as a Frictionless Data package.
Girls in early childhood increase food returns of nursing women during subsistence activities of the BaYaka in the Republic of Congo
<p>Nursing mothers face an energetic trade-off between infant care and work. Under pooled energy budgets, this trade-off can be reduced by assistance in food acquisition and infant care tasks from non-maternal caregivers. Across cultures, children also often provide infant care. Yet the question of who helps nursing mothers during foraging has been understudied, especially the role of children. Using focal follow data from 140 subsistence expeditions by BaYaka women in the Republic of Congo, we investigated how potential support from caregivers increased mothers' foraging productivity. We found that the number of girls in early childhood (ages 4–7) in subsistence groups increased food returns of nursing women with infants (kcal collected per minute). This effect was stronger than that of other adult women, and older girls in middle childhood (ages 8–13) and adolescence (ages 14–19). Child helpers were not necessarily genetically related to nursing women. Our results suggest that it is young girls who provide infant care while nursing mothers are acquiring food – by holding, monitoring, and playing with infants– and, thus, that they also contribute to the energy pool of the community during women's subsistence activities. Our study highlights the critical role of children as caregivers from early childhood.</p>
Immersive haptic simulation for training nurses in emergency medical procedures - Data collected and statistical analysis
<p>Data collected during the evaluation presented in "Haptic simulation for emergency procedures in nursing training" paper.</p> <table> <caption>HR ALL</caption> <thead> <tr> <th>Measure 1</th> <th> </th> <th>Measure 2</th> <th>t</th> <th>df</th> <th>p</th> </tr> </thead> <tbody> <tr> <td>Mann pre HR</td> <td>-</td> <td>Mann post HR</td> <td>2.857</td> <td>29</td> <td>0.008</td> </tr> <tr> <td>VR pre HR</td> <td>-</td> <td>VR post HR</td> <td>-8.089</td> <td>29</td> <td>< .001</td> </tr> <tr> <td>Mann pre HR</td> <td>-</td> <td>VR pre HR</td> <td>7.567</td> <td>29</td> <td>< .001</td> </tr> <tr> <td>Mann post HR</td> <td>-</td> <td>VR post HR</td> <td>-2.962</td> <td>29</td> <td>0.006</td> </tr> <tr> </tr> </tbody> <tbody> <tr> <td><em>Note.</em> Paired samples student's t-test.</td> </tr> </tbody> </table> <p> </p> <table> <caption>HR FIRST MANN</caption> <thead> <tr> <th>Measure 1</th> <th> </th> <th>Measure 2</th> <th>t</th> <th>df</th> <th>p</th> </tr> </thead> <tbody> <tr> <td>Mann pre HR</td> <td>-</td> <td>Mann post HR</td> <td>1.665</td> <td>14</td> <td>0.118</td> </tr> <tr> <td>VR pre HR</td> <td>-</td> <td>VR post HR</td> <td>-7.104</td> <td>14</td> <td>< .001</td> </tr> <tr> <td>Mann pre HR</td> <td>-</td> <td>VR pre HR</td> <td>6.498</td> <td>14</td> <td>< .001</td> </tr> <tr> <td>Mann post HR</td> <td>-</td> <td>VR post HR</td> <td>-1.461</td> <td>14</td> <td>0.166</td> </tr> <tr> </tr> </tbody> <tbody> <tr> <td><em>Note.</em> Paired samples student's t-test.</td> </tr> </tbody> </table> <p> </p> <table> <caption>HR FIRST VR</caption> <thead> <tr> <th>Measure 1</th> <th> </th> <th>Measure 2</th> <th>t</th> <th>df</th> <th>p</th> </tr> </thead> <tbody> <tr> <td>Mann pre HR</td> <td>-</td> <td>Mann post HR</td> <td>2.341</td> <td>14</td> <td>0.035</td> </tr> <tr> <td>VR pre HR</td> <td>-</td> <td>VR post HR</td> <td>-4.612</td> <td>14</td> <td>< .001</td> </tr> <tr> <td>Mann pre HR</td> <td>-</td> <td>VR pre HR</td> <td>4.482</td> <td>14</td> <td>< .001</td> </tr> <tr> <td>Mann post HR</td> <td>-</td> <td>VR post HR</td> <td>-2.688</td> <td>14</td> <td>0.018</td> </tr> <tr> </tr> </tbody> <tbody> <tr> <td><em>Note.</em> Paired samples student's t-test.</td> </tr> </tbody> </table> <p> </p> <table> <caption>HR BETWEEN GROUPS</caption> <thead> <tr> <th> </th> <th>t</th> <th>df</th> <th>p</th> </tr> </thead> <tbody> <tr> <td>Mann pre HR</td> <td>-1.958</td> <td>28</td> <td>0.060</td> </tr> <tr> <td>Mann post HR</td> <td>-1.902</td> <td>28</td> <td>0.068</td> </tr> <tr> <td>VR pre HR</td> <td>-4.013</td> <td>28</td> <td>< .001</td> </tr> <tr> <td>VR post HR</td> <td>-2.344</td> <td>28</td> <td>0.026</td> </tr> <tr> </tr> </tbody> <tbody> <tr> <td><em>Note.</em> Independent samples student's t-test.</td> </tr> </tbody> </table> <p> </p> <table> <caption>Physiological T-Test results for the participants who started the experiment performing the procedure in the mannequin.</caption> <thead> <tr> <th>First variable</th> <th>μ</th> <th>σ</th> <th>Second variable</th> <th>μ</th> <th>σ</th> <th>t</th> <th>df</th> <th>p</th> </tr> </thead> <tbody> <tr> <td>SBP pre-mannequin</td> <td>128.333</td> <td>10.715</td> <td>SBP pre-simulator</td> <td>134.533</td> <td>11.819</td> <td>-1.870</td> <td>14</td> <td>0.083</td> </tr> <tr> <td>SBP post-mannequin</td> <td>125.600</td> <td>11.648</td> <td>SBP post-simulator</td> <td>131.467</td> <td>14.643</td> <td>-2.094</td> <td>14</td> <td>0.055</td> </tr> <tr> <td>DBP pre-mannequin</td> <td>80.133</td> <td>5.527</td> <td>DBP pre-simulator</td> <td>81.533</td> <td>9.039</td> <td>-0.623</td> <td>14</td> <td>0.544</td> </tr> <tr> <td>DBP post-mannequin</td> <td>78.667</td> <td>6.956</td> <td>DBP post-simulator</td> <td>81.400</td> <td>8.475</td> <td>-2.073</td> <td>14</td> <td>0.057</td> </tr> <tr> <td>HR pre-mannequin</td> <td>92.133</td> <td>14.837</td> <td>HR pre-simulator</td> <td>75.733</td> <td>9.9625</td> <td>6.498</td> <td>29</td> <td>< .001</td> </tr> <tr> <td>HR post-mannequin</td> <td>87.400</td> <td>9.132</td> <td>HR post-simulator</td> <td>91.400</td> <td>14.217</td> <td>-1.461</td> <td>29</td> <td>0.166</td> </tr> </tbody> </table> <p>SBP = Systolic blood pressure. DBP = Diastolic blood pressure. HR = Heart Rate.</p> <table> <caption>Physiological T-Test results for the participants who started the experiment performing the procedure in the ParaVR simulator.</caption> <thead> <tr> <th>First variable</th> <th>μ</th> <th>σ</th> <th>Second variable</th> <th>μ</th> <th>σ</th> <th>t</th> <th>df</th> <th>p</th> </tr> </thead> <tbody> <tr> <td>SBP pre-mannequin</td> <td>119.067</td> <td>12.898</td> <td>SBP pre-simulator</td> <td>130.600</td> <td>12.188</td> <td>-3.799</td> <td>14</td> <td>0.002</td> </tr> <tr> <td>SBP post-mannequin</td> <td>117.533</td> <td>13.410</td> <td>SBP post-simulator</td> <td>128.200</td> <td>13.385</td> <td>-4.022</td> <td>14</td> <td>0.001</td> </tr> <tr> <td>DBP pre-mannequin</td> <td>76.533</td> <td>8.943</td> <td>DBP pre-simulator</td> <td>80.200</td> <td>6.899</td> <td>-1.815</td> <td>14</td> <td>0.091</td> </tr> <tr> <td>DBP post-mannequin</td> <td>74.333</td> <td>8.541</td> <td>DBP post-simulator</td> <td>79.133</td> <td>7.864</td> <td>-2.003</td> <td>14</td> <td>0.065</td> </tr> <tr> <td>HR pre-mannequin</td> <td>102.067</td> <td>12.876</td> <td>HR pre-simulator</td> <td>91.533</td> <td>11.825</td> <td>4.482</td> <td>29</td> <td>< .001</td> </tr> <tr> <td>HR post-mannequin</td> <td>95.867</td> <td>14.623</td> <td>HR post-simulator</td> <td>103.667</td> <td>14.450</td> <td>-2.688</td> <td>29</td> <td>0.018</td> </tr> </tbody> </table>
Effects of nurse shrubs and biochar on planted conifer seedling survival and growth in a high-severity burn patch in New Mexico, USA
<p>The synergistic effects of widespread high-severity wildfire and anthropogenic climate change are driving large-scale vegetation conversion. In the southwestern United States, areas that were once dominated by conifer forests are now shrub- or grasslands after high-severity wildfire, an ecosystem conversion that could be permanent without human intervention. Yet, the reforestation of these landscapes is rarely successful, with a mean planted seedling survival of just 25 %. Given these low rates, we carried out a planting experiment to quantify the impacts of biochar as a soil amendment and shrubs as nurse plants on planted conifer seedling survival and growth following high-severity wildfire. We planted 1200 seedlings of three species (<em>Pinus</em> <em>ponderosa</em>, <em>P. strobiformis</em>, and <em>Pseudotsuga</em> <em>menziesii</em>) in a 2-ha area within the footprint of the Las Conchas fire in New Mexico, USA. We used four treatments: under shrubs, or in the open and with or without biochar in a full-factorial design. We found that planting tree seedlings underneath shrubs increased tree seedling survival by 46 % after 3 years, with some marginal evidence that shrubs inhibited seedling diameter growth (mean <em>R<sup>2</sup></em> = 0.08). The addition of biochar increased seedling survival by 11 % but had no effect on seedling growth. Our study suggests that planted seedling survival in post-wildfire areas can be increased by planting under shrubs in soil amended with biochar. The widespread adoption of these methods may improve the success rates of post-wildfire reforestation efforts in semi-arid areas, regaining some of the ecosystem services lost to high-severity wildfire.</p>
SONAR: A Nursing Activity Dataset with Inertial Sensors
<p>Accurate and comprehensive nursing documentation is essential to ensure quality patient care. To streamline this process, we present SONAR, a publicly available dataset of nursing activities recorded using inertial sensors in a nursing home. The dataset includes 14 sensor streams, such as acceleration and angular velocity, and 23 activities recorded by 14 caregivers using five sensors for 61.7 hours. The caregivers wore the sensors as they performed their daily tasks, allowing for continuous monitoring of their activities.</p>
Data for "The use of bibliometrics in nursing research: topics, data sources and applications"
<p>Dataset to reproduce the analysis of the paper "The use of bibliometrics in nursing research: topics, data sources and applications". It contains a list of 129 nursing bibliometric articles and, or each article, the topic of the study, the data source employed to gather the literature, the time frame, the number of records considered, and whether the article analysed, or not, fourteen variables.</p>
Data Hospital Beds, Physicians, Nurses and Expenditure for 20 Latin American Countries from 1960 to 2022
<p>Long-term quantitative series for 20 Latin American countries, spanning from 1960 to 2020, on the number of hospital beds, physicians, nurses and healthcare expenditure.</p> <p>Matus-Lopez, M. and Fernández Pérez, P. 2023. "Transformations in Latin American Healthcare: A Retrospective Analysis of Hospital Beds, Medical Doctors, and Nurses from 1960 to 2022". <em>Journal of Evolutionary Studies in Business</em>.</p> <p>The information was extracted from official reports and cross-country databases. Official reports were available in digital format in the Institutional Repository for Information Sharing (IRIS) of Pan American Health Organization (PAHO). They were summary of four-year reports on Health Conditions in the Americas (PAHO 1962, 1966, 1970, 1974, 1978, 1982, 1986, 1990, 1994, 1998, 2002a), annual reports of Basic Indicators (PAHO 2002b, 2007, 2008, 2010, 2013), Health in South America (PAHO 2012) and Core Indicators (PAHO 2016). Databases were Open Data Portal of the Pan American Health Organization (PLISA) (PAHO 2023), Core Indicator Database provided directly by PAHO (PAHO 2022), Data Portal of National Health Workforce Accounts of the World Health Organization (NHWA) (WHO 2022), and the Global Health Expenditure Database of the World Health Organization (GHED) (WHO 2023).</p> <p>Serie 1. Hospital Beds per 1,000 inhabitants</p> <p>Serie 2. Physicians per 10,000 inhabitants</p> <p>Serie 3. Nurses per 10,000 inhabitants</p> <p>Serie 4. Government spending on health, per capita. Constant US dollars of 2020</p> <p>Cite as:</p> <p> </p> <p> </p>
Secondary data: Describing the Status Quo of Person-Centred Dementia Care within Different Types of Care Units in German Nursing Homes
<p>This is the secondary data set and R-Code of R statistical software (version 4.2.1) to investigate the differences and commonalities in the existence of policies regarding person-centred dementia care (PCDC) measured with the Dementia Policy Questionnaire (DemPol-Q) in different care unit types in German nursing homes using a contingency table and Fisher’s exact test. The data from the secondary data analysis were collected in the “BeStaDem” Survey Study, funded by the German Research Foundation (DFG, project number: 430919791), and performed by Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) e.V., site Witten. This quantitative analysis is one part of the article “Describing the Status Quo of Person-Centred Dementia Care within Different Types of Care Units in German Nursing Homes – A Convergent Mixed Methods Study”.</p>
The Relationship between Nursing Job Satisfaction and Missed Nursing Care in Critical Care Units
<p>Data set for The Relationship between Nursing Job Satisfaction and Missed Nursing Care in Critical Care Units</p>
Enhancing Sleep Quality for Nursing Home Residents With Dementia
ClinicalTrials.gov study NCT04533815. IPD Sharing: YES. Countries: 1. Publications: 1.
A Nurse-led Intervention to Extend the Veteran HIV Treatment Cascade for Cardiovascular Disease Prevention
ClinicalTrials.gov study NCT04545489. IPD Sharing: YES. Countries: 1. Publications: 2.
Certified Nursing Assistants' Wellbeing
ClinicalTrials.gov study NCT03720652. IPD Sharing: YES. Countries: 1. Publications: 52.
Effects of nurse shrubs and biochar on planted conifer seedling survival and growth in a high-severity burn patch in New Mexico, USA
Open the record for dataset details and reuse information.
Girls in early childhood increase food returns of nursing women during subsistence activities of the BaYaka in the Republic of Congo
Open the record for dataset details and reuse information.
Exploring the influence of core-self evaluations, situational factors, and coping on nurse burnout: A cross-sectional survey study
<p>Stress has become an inherent aspect of the nursing profession. Chronically experienced work stress can lead to burnout. Although situational stressors show a significant influence on burnout, their power to predict the complete syndrome is rather limited. After all, stressors only exist “in the eye of the beholder”. This study aimed to explore how individual vulnerability factors such as core-self evaluations and coping, contribute to burnout in relation to situational stressors within a population of hospital nurses.</p> <p>Cross-sectional data was collected in 2014, using five validated self-report instruments: Dutch Core Self Evaluations Scale, Nursing Work Index Revised, Utrecht Coping List, Ruminative Response Scale, and Utrecht Burnout Scale. 219 of the 250 questionnaires were returned. This database is available here.</p> <p>Core-self evaluations, situational factors and coping each contributed significantly to the predictive capacity of the models of the separate burnout dimensions. Core-self evaluations was significantly related to emotional exhaustion. It was suggested that Core-self evaluations might be placed at the initiation of the loss cycle. However, further research is warranted.</p>
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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.