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100 results for “medical training”
MESINESP: Medical Semantic Indexing in Spanish - Train dataset
<p><em><strong>Please use the <a href="https://doi.org/10.5281/zenodo.4612274">MESINESP2 corpus (the second edition of the shared-task)</a> since it has a higher level of curation, quality and is organized by document type (scientific articles, patents and clinical trials).</strong></em></p> <p> </p> <p> </p> <p><strong>INTRODUCTION</strong>:</p> <p>The Mesinesp (Spanish BioASQ track, see https://temu.bsc.es/mesinesp) training set has a total of 369,368 records. </p> <p>The training dataset contains all records from LILACS and IBECS databases at the Virtual Health Library (VHL) with a non-empty abstract written in Spanish. The URL used to retrieve records is as follows:<br> http://pesquisa.bvsalud.org/portal/?output=xml&lang=es&sort=YEAR_DESC&format=abstract&filter[db][]=LILACS&filter[db][]=IBECS&q=&index=tw&</p> <p>We have filtered out empty abstracts and non-Spanish abstracts. </p> <p>The training dataset was crawled on 10/22/2019. This means that the data is a snapshot of that moment and that may change over time. In fact, it is very likely that the data will undergo minor changes as the different databases that make up LILACS and IBECS may add or modify the indexes.</p> <p> </p> <p><strong>ZIP STRUCTURE:</strong></p> <p>The training data sets contain 369,368 records from 26,609 different journals. Two different data sets are distributed as described below:</p> <p> - <em>Original Train set</em> with 369,368 records that also include the qualifiers, as retrieved from VHL. <br> - <em>Pre-processed Train set</em><strong> </strong>with the 318,658 records with at least one DeCS code and with no qualifiers. </p> <p> </p> <p> </p> <p><strong>STATISTICS</strong>:</p> <p>Abstracts’ length (measured in characters)<br> Min: 12<br> Avg: 1140.41<br> Median: 1094<br> Max: 9428</p> <p>Number of DeCS codes per file<br> Min: 1<br> Avg: 8.12<br> Median: 7<br> Max: 53</p> <p> </p> <p> </p> <p><strong>CORPUS FORMAT</strong>:</p> <p>The training data sets are distributed as a JSON file with the following format:</p> <pre><code>{ "articles": [ { "id": "Id of the article", "title": "Title of the article", "abstractText": "Content of the abstract", "journal": "Name of the journal", "year": 2018, "db": "Name of the database", "decsCodes": [ "code1", "code2", "code3" ] } ] } </code></pre> <p>Note that the decsCodes field lists the DeCs Ids assigned to a record in the source data. Since the original XML data contain descriptors (no codes), we provide a DeCs conversion table (https://temu.bsc.es/mesinesp/wp-content/uploads/2019/12/DeCS.2019.v5.tsv.zip) with:</p> <p> - DeCs codes<br> - Preferred descriptor (the label used in the European DeCs 2019 set)<br> - List of synonyms (the descriptors and synonyms from both European and Latin Spanish DeCs 2019 data sets, separated by pipes)</p> <p> </p> <p>For more details on the Latin and European Spanish DeCs codes see: http://decs.bvs.br and http://decses.bvsalud.org/ respectively.</p> <p>Please, cite: Krallinger M, Krithara A, Nentidis A, Paliouras G, Villegas M. BioASQ at CLEF2020: Large-Scale Biomedical Semantic Indexing and Question Answering. InEuropean Conference on Information Retrieval 2020 Apr 14 (pp. 550-556). Springer, Cham.</p> <p> </p> <p>Copyright (c) 2020 Secretaría de Estado de Digitalización e Inteligencia Artificial</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>
Data from: Effectiveness of Online Off-the-Job Training in Attracting Participants and Video-On-Demand Streaming in Improving Work-Life Balance: A Study Focusing on Medical Technologists
<p>The Nara Association of Medical Technologists has introduced online Off-Job Training (Off-JT) starting from FY2020 in response to the COVID-19 pandemic. This study aims to evaluate the online Off-JT, which differs from the traditional face-to-face format. Firstly, we compared the online format's ability to attract participants with the face-to-face format based on the number of training sessions and attendees. Despite having fewer training sessions (40.8% less), the online format had an average attendance of 105.4% higher (39.7 vs. 19.3) than the face-to-face format. To enhance participant convenience, we offered a limited number of live and video-on-demand (VOD) sessions on YouTube, evaluating their usefulness through an online survey focusing on work-life balance (WLB). The survey results showed that 81.9% (458/559) of respondents reported an improvement in WLB. The effect on WLB improvement varied depending on the viewing method, with VOD sessions showing 84.1% (376/447) and live sessions showing 73.2% (82/112). We believe that the increased ability to attract participants in the online Off-JT is mainly due to the elimination of travel burdens through internet-connected devices. The combination of live and VOD sessions on YouTube allowed participants to adjust their viewing time, leading to better allocation of free time and improved WLB. The online Off-JT and VOD delivery have shown to enhance convenience for participants by removing geographical and time constraints, resulting in positive effects.</p>
Careers in Science and Healthcare - How changes to medical device regulation have increased training needs
<p>Article contributed to Careers in Science and Healthcare report.</p>
Pediatric standardized residency training faculty's perceptions of medical education research
<p><strong>Background:</strong> Rigorous medical education research (MER) conducted by faculty in pediatric standardized residency training (SRT) can contribute to the promotion of child health care. </p> <p><strong>Aim:</strong> This study aimed to assess the perceptions of pediatric SRT faculty regarding MER in Guangdong Province, China. </p> <p><strong>Methods:</strong> A questionnaire survey was conducted involving 40 pediatric SRT clinical teachers from 10 hospitals in Guangdong Province.</p> <p><strong>Results:</strong> Among the 40 teachers, 16 (40.00%) stated that they did not participate any MER activities. The main challenges they encountered in conducting MER were the lack of training (72.50%), limited time (80.00%), and lack of grants funding (60.00%). Only 10 (25.00%)teachers were reported to have received grants for MER projects. </p> <p><strong>Conclusion: </strong>The findings highlight the importance of providing support and training to pediatric SRT faculty in Guangdong Province, China, to enhance their engagement in MER. Addressing these challenges can lead to significant improvements in child heal care promotion through evidence-based educational practices. </p>
To Evaluate the Effect of Inhaled Medication Together With Exercise and Activity Training on Exercise Capacity and Daily Activities in Patients With Chronic Lung Disease With Obstruction of Airways
ClinicalTrials.gov study NCT02085161. IPD Sharing: Not stated. Countries: 11. Publications: 2.
Improving Performance of Paracentesis in Medical Residency Training
ClinicalTrials.gov study NCT01403987. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Video-Based Versus Simulation-Based Basic Life Support Training in Medical Students
ClinicalTrials.gov study NCT07368452. IPD Sharing: NO. Countries: 1. Publications: 0.
Exercise Training Effects on Metabolic Syndrome: Interactions With Medication
ClinicalTrials.gov study NCT03019796. IPD Sharing: NO. Countries: 1. Publications: 27.
ChatGPT Helping Advance Training for Medical Students: A Study on Self-Directed Learning Enhancement
ClinicalTrials.gov study NCT06276049. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Serious Game Versus Online Course to Pre-train Medical Students on the Management of an Adult Cardiac Arrest.
ClinicalTrials.gov study NCT02758119. IPD Sharing: NO. Countries: 1. Publications: 5.
Improving Medical Training for the Care of Chronic Conditions
ClinicalTrials.gov study NCT00676208. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Pediatric standardized residency training faculty’s perceptions of medical education research
Open the record for dataset details and reuse information.
Evaluating the educational effectiveness of a structured, simulator-assisted, peer-led training on cardiovascular physical examination in third-year medical students: A randomized, controlled trial
<p class="AbstractCxSpFirst"><span><span><span><span><span><span><span><span><span><span><span><b>Background:</b> Previous research suggests that cardiac examination skills in undergraduate medical students frequently need improvement. There are different ways to enhance physical examination (PE) skills such as simulator-based training or peer-assisted learning (PAL). </span></span></span></span></span></span></span></span></span></span></span></p> <p class="AbstractCxSpMiddle"><span><span><span><span><span><span><span><span><span><span><span><b>Aim:</b> The aim of this study was to evaluate the effectiveness of a structured, simulator-assisted, peer-led training on cardiovascular PE.</span></span></span></span></span></span></span></span></span></span></span></p> <p class="AbstractCxSpMiddle"><span><span><span><span><span><span><span><span><span><span><span><b>Methods:</b> Participants were third-year medical students at Leipzig University Faculty of Medicine. Students were randomly assigned to an intervention group (IG) and a control group (CG). In addition to standard curricular training, IG received a peer-led, simulator-based training in cardiac PE. Participant performance in cardiac PE was assessed using a standardized checklist with a maximum of 25 points. Primary outcome was assessed via checklist point distribution.</span></span></span></span></span></span></span></span></span></span></span></p> <p class="AbstractCxSpMiddle"><span><span><span><span><span><span><span><span><span><span><span><b>Results:</b> 89 students were randomised to either CG (<i>n</i> = 43) or IG (<i>n</i> = 46) with 70 completing the study. Overall, IG students performed significantly better than CG students did (max. points: 25, IG M ± SD in IG was 17 ± 3, in CG 12 ± 4, p < .0001). Simple mistakes such as not using the stethoscope correctly were more frequent in CG students. Prior experience did not lead to a significant difference in performance. </span></span></span></span></span></span></span></span></span></span></span></p> <p class="Abstract"><span><span><span><span><span><span><span><span><span><span><span><b>Conclusions:</b> Structured, peer-led and simulator-assisted teaching sessions improve cardiac PE skills in this setting compared to control students that did not receive this training.</span></span></span></span></span></span></span></span></span></span></span></p>
Impact of Training of GPs on Adherence of Hypertensive Individuals to Antihypertensive Medication
ClinicalTrials.gov study NCT00330408. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Effect of Protein and Resistance Training on Muscle Mass in Acutely Ill Old Medical Patients
ClinicalTrials.gov study NCT02077491. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Preclinical Medical Student Echocardiography Training American Society of Echocardiography Curriculum
ClinicalTrials.gov study NCT04083924. IPD Sharing: NO. Countries: 1. Publications: 2.
Self-guided vs Traditional Instructor-led Learning for Medical Device Training
ClinicalTrials.gov study NCT05530382. IPD Sharing: NO. Countries: 1. Publications: 2.
Exercise Training Versus Best Medical Treatment Only in Peripheral Artery Disease
ClinicalTrials.gov study NCT00926081. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Effect of a Checklist on the Quality of Education During Insulin Initiation by Trained Medical Students
ClinicalTrials.gov study NCT02313805. IPD Sharing: Not stated. Countries: 1. Publications: 5.
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