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1,733 results for “Fatigue”
A triple distinction of cerebellar function for oculomotor learning and fatigue compensation
<p>This depository contains the data and modeling code of the publication </p> <p><em>Masselink J., Cheviet, A., Froment-Tilikete, C., Pélisson, D., & Lappe, M. (2023). A triple distinction of cerebellar function for oculomotor learning and fatigue compensation. PLoS Comput Biol</em></p> <p>Please see the publication for detailed description of experimental and modeling methods. Data are provided in a mat-file, modeling code is provided in m-files (Matlab).</p>
Supplemental Material to Article "Quantification of process-induced effects on fatigue life of short-glass-fiber-filled adhesive used in wind turbine rotor blades"
<p>This set supplements the figure data to the article "Quantification of process-induced effects on fatigue life of short-glass-fiber-filled adhesive used in wind turbine rotor blades", DOI: xxx</p>
Dataset for Evaluating the Construct Validity of the Charité Alarm Fatigue Questionnaire
<p>These are the datasets that we used for evaluating the construct validity of the Charité Alarm Fatigue Questionnaire (CAFQa) in a forthcoming publication. All items were answered on a 5-point Likert scale and were scored by us as follows: -2/“I do not agree at all”, -1/“I do not agree”, 0/“I agree in part”, 1/“I agree”, 2/"I very much agree".</p> <p>A previous version of this upload included only the data of Study 1. A new version provides the data of Study 2. Please refer to the methods section of the forthcoming publication for more details.</p> Variable names and their corresponding item. Items marked with <table><tbody><tr> <th>Variable Name</th> <th>CAFQa Item</th> </tr> </tbody><tbody> <tr> <td>procedural_instruction</td> <td>In my ward, procedural instruction on how to deal with alarms is regularly updated and shared with all staff.<sup>a</sup></td> </tr> <tr> <td>respond_quickly</td> <td>Responsible personnel respond quickly and appropriately to alarms.<sup>a</sup></td> </tr> <tr> <td>motivation_decrease</td> <td>With too many alarms on my ward, my work performance, and motivation decrease.</td> </tr> <tr> <td>physical_symptoms</td> <td>Too many alarms trigger physical symptoms for me, e.g., nervousness, headaches, and sleep disturbances.</td> </tr> <tr> <td>ward_floor</td> <td>The acoustic and visual monitor alarms used on my ward floor and in my nurse station allow me to assign the patient, the device, and the situation clearly.<sup>a</sup></td> </tr> <tr> <td>reduce_concentration</td> <td>Alarms reduce my concentration and attention.</td> </tr> <tr> <td>alarm_limits</td> <td>Alarm limits are regularly adjusted based on patients' clinical pictures (e.g., blood pressure limits for conditions after bypass surgery).<sup>a</sup></td> </tr> <tr> <td>interrupt_workflow</td> <td>My or neighboring patients' alarms or crisis alarms frequently interrupt my workflow.</td> </tr> <tr> <td>alarms_confuse</td> <td>There are situations when alarms confuse me.</td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> Other variables in the data set. <table><tbody><tr> <th>Variable Name</th> <th>Explanation</th> </tr> </tbody><tbody> <tr> <td>self_reported_AF</td> <td>self-estimated alarm fatigue in percent</td> </tr> <tr> <td>estimated_false_alarms</td> <td>perceived rate of false alarms in the participant's ICU</td> </tr> <tr> <td>monthly_time_on_ICU</td> <td>the average number of workdays per month in an intensive care or monitoring area</td> </tr> <tr> <td>ICU_experience</td> <td>number of years/months of ICU experience</td> </tr> <tr> <td>profession</td> <td>physician, nurse, or supporting nurse</td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p><strong>Members of the Study Group</strong> <strong>in alphabetical order</strong>: <em>Dr. med. Mirza Aghamov</em><sup><em>1</em></sup><em>, Prof. Dr. med. Manfred Blobner<sup>2</sup>, Prof. Dr. med. Ulrich Frey<sup>3</sup></em><em>, Prof. Dr. Christian von Heymann<sup>4</sup></em><em>, Prof. Dr. med. Bettina Jungwirth</em><sup><em>1</em></sup><em>, Dr. med. Dragutin Popovic<sup>4</sup></em><em>, Prof. Dr. med. Michael Sander<sup>5</sup></em><em>. </em></p> <p>1: <em>Department of Anesthesiology and Intensive Care Medicine, University Hospital Ulm, Ulm University, Ulm, Germany</em></p> <p>2: <em>Technical University Munich, School of Medicine, Klinikum Rechts der Isar, Department of Anaesthesiology & Intensive Care Medicine, Munich, Germany</em></p> <p>3: <em>Department for Anesthesiology, Surgical Intensive Care, Pain and Palliative Medicine, Marien Hospital Herne – Universitätsklinikum der Ruhr-Universität Bochum, Herne, Germany</em></p> <p>4: <em>Department for Anaesthesiology, Intensive Care Medicine and Pain Therapy, Vivantes Klinikum im Friedrichshain, Berlin, Germany</em></p> <p>5: <em>Department for Anaesthesiology, Intensive Care Medicine and Pain Therapy, Justus Liebig University, Giessen, Germany</em></p> <p> </p>
Data: Double Task Switching: an investigation into the effects of similarity and task-rule congruency on cognitive flexibility in the context of mental fatigue
<p>This is the data that was collected for the Double Task Switching Experiment (Hinss, Brock & Roy 2023). The File contains the behavioral as well as the subjective data of all participants.</p> <p><br> Some details:<br> Switch<br> 1= repetition trial<br> 2= internal switch<br> 3= external switch</p> <p>Task<br> 1= Low/High<br> 2= Even/Odd<br> 3= Vertical/Horizontal<br> 4= Cold/Hot</p> <p>Language (of instructions)<br> 0= French<br> 1= English</p> <p>Congruency<br> 1= Neutral<br> 2= Internally incongruent<br> 3= Externally incongruent<br> 4= Double incongruent<br> 5= Internally congruent<br> 6= Externally congruent<br> 7= Double congruent</p> <p>Correct<br> 1= Correct Response<br> 0= Error</p> <p>Hit<br> 0= Correct response on letter S<br> 1= Correct response on letter L</p> <p>Response<br> 0= Participants response on letter S<br> 1= Participants response on letter L</p> <p>EDI (Edinburgh Handedness questionnaire)</p> <p>MaryA1: What time did you settle in for the night?<br> MaryA2: What time did you fall asleep last night?<br> MaryA3: What time did you wake up this morning?<br> MaryA4: What time did you get up this morning?<br> MaryB1: How was your sleep<br> MaryB2: How many times did you wake up last night ?<br> MaryB3: How many hours did you sleep last night?<br> MaryB4: How many hours did you sleep during the day yesterday?<br> MaryB5: How well did you sleep last night?<br> MaryC1: If you didn't sleep well, what was the problem? (e.g., restless, etc.)<br> MaryD1: How much caffine/theine did you consume today ( in cups of coffee) ?<br> MaryD2: How much caffeine/theine would you usually have consumed at this time of the day ( in cups of coffee)?</p> <p> </p> <p>For any further questions, please refer to the full journal paper (<a href="https://doi.org/10.1371/journal.pone.0279021">https://doi.org/10.1371/journal.pone.0279021</a>).</p> <p>For publications, please cite as:</p> <p>Hinss MF, Brock AM, Roy RN (2023) The double task-switching protocol: An investigation into the effects of similarity and conflict on cognitive flexibility in the context of mental fatigue. PLOS ONE 18(2): e0279021. <a href="https://doi.org/10.1371/journal.pone.0279021">https://doi.org/10.1371/journal.pone.0279021</a><br> </p>
Dataset for "Enabling Machine Learning Models in Alarm Fatigue Research: Creation of a Large Relevance-annotated Oxygen Saturation Alarm Data Set"
<p>Chromik and Flint et al. (2024) (under review) propose an algorithm that uses clinical alarm logs, an annotation guideline (Klopfenstein et al. 2023), and routinely collected intensive care data to create a data set of relevance-annotated oxygen saturation alarms. We provide the algorithm's source code and data set of annotated oxygen saturation alarms as supplementary material to the publication.</p> <ul> <li>The algorithm's implementation is open-source and can be re-used on similar data sets.</li> <li>Our implementation used airway management data mappings to identify airway devices (AD), ventilation devices (VD), and ventilation modes (VM). These mappings can be found here: <a href="../doi/10.5281/zenodo.7511031">https://zenodo.org/doi/10.5281/zenodo.7511031</a></li> <li>The data set suggests that the majority of oxygen saturation alarms in the intensive care unit is non-actionable.</li> <li>We are the first to provide such an extensive data set of annotated oxygen saturation alarms.</li> </ul>
Internal large field of view observations with optical microscope of fatigue damage in composite materials during bending loading
<p>Stitched microscope pictures ...</p> <p>References to this data-set should include a reference to one of the following two papers in where the data has been used.</p> <p>Mortensen U., Andersen, T.L., Mikkelsen, L.P., Observation of Edge Effect in Flexural Fatigue Test of Composites using Large Field of View Microscopy, Journal of Composite Materials. https://doi.org/10.1177/0021998320902233, 2020</p> <p>Mortensen, U.A., Mikkelsen, L.P., Andersen, T.L. Observation of the interaction between transverse cracking and fibre breaks in uni-directional non-crimp fabric composites subjected to cyclic bending fatigue damage mechanism, submitted, Feb. 2022.</p> <p>The naming of the pictures are build up by the follwing elements</p> <p>EL_05 is the plate ID,<br> J01-J09 is the sample ID where the following load level are defined:</p> <ul> <li>J01: 1 000 cycles</li> <li>J02: 2 500 cycles</li> <li>J03: 5 000 cycles</li> <li>J04: 10 000 cycles</li> <li>J05: 50 000 cycles</li> <li>J06: 100 000 cycles</li> <li>J07: 250 000 cycles</li> <li>J08: 500 000 cycles</li> <li>J09: 1 000 000 cycles</li> </ul> <p>S01-04: is the 4 surfaces inside the sample as shown in the picture saved in: xxx. The picture show the sample where the red planes indicate the polished surfaces where the microscopy pictures from the internal surfaces are taken.</p> <p>The pictures are oriented with the compression side upward and the tensile side downward similar to the orientation of the actual 4-point fatigue bending test sample.</p>
Study and Treatment of Visual Dysfunction and Motor Fatigue in Multiple Sclerosis
ClinicalTrials.gov study NCT02391961. IPD Sharing: NO. Countries: 1. Publications: 1.
Activate For Life: mHealth Intervention To Address Pain And Fatigue In Low-income Older Adults Aging In Place
ClinicalTrials.gov study NCT03853148. IPD Sharing: NO. Countries: 1. Publications: 2.
Effects of Probiotics on Gut Microbiota, Endocannabinoid and Immune Activation and Symptoms of Fatigue in Dancers
ClinicalTrials.gov study NCT05567653. IPD Sharing: NO. Countries: 1. Publications: 46.
Hatha Yoga in Improving Physical Activity, Inflammation, Fatigue, and Distress in Breast Cancer Survivors
ClinicalTrials.gov study NCT00486525. IPD Sharing: Not stated. Countries: 1. Publications: 1.
American Ginseng to Improve HIV-Associated Fatigue: A Randomized, Placebo-Controlled, Parallel Design, Multiple-Dose Clinical Trial
ClinicalTrials.gov study NCT01500096. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Comparison of Bystander Fatigue and CPR Quality When Using Two Different CPR Ratios.
ClinicalTrials.gov study NCT00380757. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Music Therapy in Acute Leukemia Patients With Fatigue
ClinicalTrials.gov study NCT06286332. IPD Sharing: Not stated. Countries: 1. Publications: 10.
Physical Fatigue, Compassion Fatigue, and Quiet Quitting in Physiotherapists
ClinicalTrials.gov study NCT07340866. IPD Sharing: NO. Countries: 1. Publications: 4.
The Individual Response of Healthy Individuals to Mental Fatigue
ClinicalTrials.gov study NCT05576935. IPD Sharing: YES. Countries: 1. Publications: 5.
Effects of Bright Light on Sleep Quality, Fatigue , and Mood Symptoms in Survivors With Gynecologic Cancer
ClinicalTrials.gov study NCT07132580. IPD Sharing: YES. Countries: 1. Publications: 3.
Methylphenidate in Treating Patients With Fatigue Caused by Cancer
ClinicalTrials.gov study NCT00376675. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Healing Touch in Treating Fatigue in Women Undergoing Radiation Therapy for Breast Cancer
ClinicalTrials.gov study NCT00574145. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Music Intervention on Golfers Under Mental Fatigue
ClinicalTrials.gov study NCT06952283. IPD Sharing: NO. Countries: 1. Publications: 48.
Anamorelin Hydrochloride, Physical Activity, and Nutritional Counseling in Decreasing Cancer-Related Fatigue in Patients With Incurable Metastatic or Recurrent Solid Tumors
ClinicalTrials.gov study NCT03035409. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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