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38 results for “Profession”
Dataset Musculoskeletal pain in health professionals at the end of their studies and 1 year after entry into the profession: A multi-center longitudinal study.
<p>Dataset related to the paper "Musculoskeletal pain in health professionals at the end of their studies and 1 year after entry into the profession: A multi-center longitudinal study."</p> <p><strong>Abstract</strong></p> <p>Background: Musculoskeletal pain, especially back pain, is common among health professionals (HPs). They reduce work productivity and cause high costs. This follow up study investigates the prevalence and individual course of Musculoskeletal pain among HP students at the end of their studies and one year after entering the health care workforce. Participants were asked whether their Musculoskeletal pain was related to study or work conditions.</p> <p>Method: Self reported one year prevalence for lower back pain, neck and shoulder pain, pain in arms or hands, and pain in legs or feet was collected by an online questionnaire at two timepoints from 1046 participating HPs. Generalized estimating equation (GEE) models of the binomial family with log link were employed to estimate adjusted prevalence and corresponding normal based 95% confidence intervals were derived using the bootstrap method with 1,000 replications.</p> <p>Results: Prevalence of lower back pain as well as neck and shoulder pain was very high at baseline and follow up in all students and later HPs. Prevalence for pain in arms or hands, legs or feet was lower and there were significant differences between the professions. HP associated their lower back pain and neck and shoulder pain clearly with study and work conditions; HPs linked pain in arms or hands, legs or feet strongly with work conditions only.</p> <p>Conclusion: The prevention of lower back pain and neck and shoulder pain must be included in the curricula of all health professions at universities. As best practice example, they should incorporate ergonomic measures and exercises as a daily routine of the formation of health professionals. The impact of physically demanding professional tasks on upper and lower extremities needs to be investigated in further studies in order to take preventive measures.</p>
Data for the article "Professionalism, emotional wellbeing, and dropout intention in health professions students during the pandemic"
<p>Dataset from a study of attitudes and perceptions of medicine and nursing students in Peru during the COVID-19 pandemic. Survey was applied from 2020-07-24 to 2021-04-16.</p> <p>This dataset is described in the article: </p> <p>Castagnetto, J.M., Hancco-Monrroy, D.E., Caballero-Apaza, L.M. <em>et al.</em> Professionalism, emotional wellbeing, and dropout intention in health professions students during the pandemic. <em>Sci Data</em> <strong>12</strong>, 1259 (2025). <a href="https://doi.org/10.1038/s41597-025-05508-5">https://doi.org/10.1038/s41597-025-05508-5</a> (<a href="https://www.nature.com/articles/s41597-025-05508-5">https://www.nature.com/articles/s41597-025-05508-5</a>)</p>
ChatGPT's answers to requests about the librarian profession
<p>Dataset containing questions and answers about the library profession requested to ChatGPT.</p>
Wikidata Dump Multilang professions
<p> RDF dump of wikidata produced with <a href="https://tools.wmflabs.org/wdumps/">wdumps</a>. </p> <p> The previous one failed for some reason. Trying again with more filters.<br> <a href="https://tools.wmflabs.org/wdumps/dump/335">View on wdumper</a> </p> <p> <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 38 </p>
AI4PROFHEALTH - Profession-health status knowledge graph
<p>This dataset comprises a profession-clinical knowledge graph, derived from the co-occurrence of normalised concepts identified in two distinct corpora: the Mesinesp2 corpus, a manually annotated corpus in which domain experts have labelled a set of scientific literature, clinical trials, and patent abstracts, as well as clinical case reports. The application of different NER systems to each corpus has enabled the extraction of clinical mentions related to diseases, drugs, locations, procedures, species, species-human, and symptoms.</p> <p>The repository contains a .zip file for each of the corpus, each containing the following columns order:</p> <ul> <li><code><strong>span_mention_1</strong></code>: Mention string (original): profession</li> <li><code><strong>normalized_entity_1</strong></code>: Controlled vocabulary entry for this term</li> <li><code><strong>code_mention_1</strong></code>: ID terminology for normalization</li> <li><code><strong>mention_controlled_vocab</strong></code>: Terminology used for normalization</li> <li><code><strong>mention1_category</strong></code>: Semantic class (i.e., NER label)</li> <li><code><strong>mention1_freq</strong></code>: Absolute frequency of this mention entity 1</li> <li><code><strong>span_mention_2</strong></code>:<strong> </strong>Mention string (original): entity 2 (disease, symptom, species, etc.)</li> <li><code><strong>normalized_entity_2</strong></code>: Controlled vocabulary entry for this term</li> <li><code><strong>code_mention_2</strong></code>: ID terminology for normalization</li> <li><code><strong>mention_controlled_vocab</strong></code>:<strong> </strong>Terminology used for normalization</li> <li><code><strong>mention2_category</strong></code>:<strong> </strong>Semantic class (i.e., NER label)</li> <li><code><strong>mention1_freq</strong></code>:<strong> </strong>Absolute frequency of this mention entity 2</li> <li><code><strong>co-occurrence</strong></code>: Number of co-occurrences</li> </ul> <p><strong>Notes</strong></p> <p>This resource been funded by the Spanish National Proyectos I+D+i 2020 AI4ProfHealth project PID2020-119266RA-I00 (PID2020-119266RA-I0/AEI/10.13039/501100011033).</p> <p><strong>Contact</strong></p> <p>If you have any questions or suggestions, please contact us at:</p> <p>- Miguel Rodríguez Ortega (<miguel [dot] rod [at] bsc [dot] com>)<br>- Martin Krallinger (<krallinger [dot] martin [at] gmail [dot] com>)</p> <p><strong>Additional resources and corpora</strong></p> <p>If you are interested, you might want to check out these corpora and resources:</p> <ul> <li><a href="../records/7116201">MEDDOPROF</a> (Corpus of mentions of professions, occupations and working status and normalization, different document collection with some overlapping documents)</li> <li><a href="https://zenodo.org/records/5602914">MESINESP-2</a> (Corpus of manually indexed records with DeCS /MeSH terms comprising scientific literature abstracts, clinical trials, and patent abstracts, different document collection)</li> </ul> <p> </p>
Building Interprofessional Learning in the Midst of the COVID-19 Pandemic: Implementation of Online Simulation for Students in Health Profession
<p><strong>Abstract</strong></p> <p>COVID-19 has significantly affected the learning process of health institutions. It is inevitable that face-to-face learning activities will shift to online learning, including Interprofessional Education (IPE). The purpose of this article is to describe our experiences in developing a simulation of a two-day interprofessional learning and teaching session for students in nursing, midwifery, pharmacy, environmental sanitation, medical laboratory technology, dental health, and nutrition. A total of 956 students, 112 lecturers, and 15 standardized patients (SP) took part in this research. The study conducted in 6 schools of health profession in Indonesia. Students were assigned to two simulation models. The data were collected using an online questionnaire with the variables readiness to cooperate, interprofessional group discussions, and facilitator role with a 5-point Likert scale. In the implementation of the two simulation models, significant results have been demonstrated and their uniqueness is revealed. The simulation models that make direct anamnesis of the SP results in a higher level of readiness for IPE learning, and is significantly different. Meanwhile, the simulation model that is preceded by a scenario discussion process before making anamnesis to the SP shows a significantly positive attitude to the interprofessional groups discussion and the role of the facilitator.</p> <p><strong>Keywords:</strong> interprofessional education, COVID-19 pandemic, online simulation, health professionals, standardized patient</p>
PRoFESS - Prevention Regimen For Effectively Avoiding Second Strokes
ClinicalTrials.gov study NCT00153062. IPD Sharing: Not stated. Countries: 36. Publications: 8.
AI4PROFHEALTH - Profession-health status co-occurrence graph statistics
<p>This dataset contains the Pointwise Mutual Information (PMI) values for co-occurrence pairs between different mention categories extracted from two distinct clinical datasets: <strong>MESINESP2</strong> and the <strong>Clinical Case Reports Collection</strong>. PMI is a statistical measure used to assess the strength of association between pairs of entities by comparing their observed co-occurrence to the expected frequency under the assumption of independence.</p> <p>The datasets include PMI values for each co-occurrence pair, derived from the association of professions and clinical concepts, with the aim of identifying potential occupational health risks. By sharing these datasets, we aim to support further research into the relationships between professions and clinical entities, enabling the development of more accurate and targeted occupational health risk models.</p> <p>There is a separate file for each corpus, and each dataset is provided in <strong>CSV format</strong> for easy access and analysis. These files include the PMI values for co-occurrence pairs extracted from the respective corpora, making them suitable for further data analysis.</p> <p><strong>Data Structure:</strong></p> <ul> <li><strong>MESINESP2: <code>mesinesp2_co-occurrence_pmi.zip</code></strong></li> <li><strong>Clinical case reports: <code>clinical_cases_co-occurrence_pmi.zip</code></strong></li> </ul> <p>The repository contains a .zip file for each of the corpus, each containing a .csv file with the co-occurrences between the detected professions and clinical entities. The file has the following columns order:</p> <ul> <li><code><strong>span_mention_1</strong></code>: Mention string (original): profession</li> <li><code><strong>normalized_entity_1</strong></code>: Controlled vocabulary entry for this term</li> <li><code><strong>mention1_category</strong></code>: Semantic class (i.e., NER label)</li> <li><code><strong>mention1_freq</strong></code>: Absolute frequency of this mention entity 1</li> <li><code><strong>span_mention_2</strong></code>:<strong> </strong>Mention string (original): entity 2 (disease, symptom, species, etc.)</li> <li><code><strong>normalized_entity_2</strong></code>: Controlled vocabulary entry for this term</li> <li><code><strong>mention2_category</strong></code>:<strong> </strong>Semantic class (i.e., NER label)</li> <li><code><strong>mention1_freq</strong></code>:<strong> </strong>Absolute frequency of this mention entity 2</li> <li><code><strong>co-occurrence</strong></code>: Number of co-occurrences</li> <li><code><strong>PMID</strong></code>: PMID value</li> </ul> <p><strong>Notes</strong></p> <p>This resource been funded by the Spanish National Proyectos I+D+i 2020 AI4ProfHealth project PID2020-119266RA-I00 (PID2020-119266RA-I0/AEI/10.13039/501100011033).</p> <p><strong>Contact</strong></p> <p>If you have any questions or suggestions, please contact us at:</p> <p>- Miguel Rodríguez Ortega (<miguel [dot] rod [at] bsc [dot] com>)<br>- Martin Krallinger (<krallinger [dot] martin [at] gmail [dot] com>)</p> <p><strong>Additional resources and corpora</strong></p> <p>If you are interested, you might want to check out these corpora and resources:</p> <ul> <li><a href="../records/7116201">MEDDOPROF</a> (Corpus of mentions of professions, occupations and working status and normalization, different document collection with some overlapping documents)</li> <li><a href="https://zenodo.org/records/5602914">MESINESP-2</a> (Corpus of manually indexed records with DeCS /MeSH terms comprising scientific literature abstracts, clinical trials, and patent abstracts, different document collection)</li> </ul> <p> </p>
Supplementary files for article "Health and social care professions students' health literacy knowledge: a qualitative exploratory study"
<p>Supplementary file A: Complete list of student-reported definition of health literacy</p> <p>Supplementary file B: Complete list of student-reported signs which suggest inadequate health literacy</p> <p>Supplementary file C: Complete list of student-reported potential consequences of inadequate health literacy</p> <p>Supplementary file D: Complete list of student-reported actions that a health or social care professional can take to help a patient with inadequate health literacy</p>
Data from: Graduate health professions education programs as they choose to represent themselves: A website review
<p>Introduction: In an age of increasingly face-to-face, blended, and online Health Professions Education, students have more selections of where they will receive a degree. For an applicant, oftentimes, the first step is to learn more about a program through its website. Websites allow programs to convey their unique voice and to share their mission and values with others, such as applicants, researchers, and academics. Additionally, as the number of Health Professions Education programs rapidly grows, websites can share the priorities of these programs. </p> <p>Methods: In this study, we conducted a website review of 158 Health Professions Education websites to explore their geographical distributions, missions, educational concentrations, and various programmatic components.</p> <p>Results: We compiled this information and synthesized pertinent aspects, such as program similarities and differences, or highlighted the omission of critical data.</p> <p>Conclusion: Given that websites are often the first point of contact for prospective applicants, curious collaborators, and potential faculty, the digital image of HPE programs matters. We believe our findings demonstrate opportunities for growth within institutions and assist the field in identifying the priorities of HPE programs. As programs begin to shape their websites with more intentionality, they can reflect their relative divergence/convergence compared to other programs as they see fit and, therefore, attract individuals to best match this identity. Periodic reviews of the breadth of programs, such as those undergone here, are necessary to capture diversifying goals, and serve to help advance the field of Health Professions Education as a whole.</p>
Turning to Religion as a Mediator of the Relationship Between Hopelessness and Job Satisfaction During the COVID-19 Pandemic Among Individuals Representing the Uniformed Services or Working in Professions of Public Trust in Poland
<p><strong>Introduction.</strong> During the COVID-19 pandemic individuals performing uniformed service or working in a profession of public trust are particularly exposed to chronic stress. The consequences of stress in turn translate into a decrease in quality of life across various domains, including professional functioning. The perceived mental difficulties can lead to feeling of hopelessness, which in turn can generate a decrease in job satisfaction. Religiosity is a factor which, in stress-inducing conditions, not only stops the spiral of perceived resource losses but also triggers gains in the resources possessed.</p> <p><strong>Aim.</strong> In this study, we tested - in the light of Conservation of resources theory (COR) - whether during the COVID-19 pandemic, the preference for positive religious coping strategies (turning to religion) by people declaring religiosity is a mediator for the relationship between perceived hopelessness and job satisfaction.</p> <p><strong>Methods.</strong> The study covered 238 individuals representing the uniformed services or working in professions of public trust in Poland. The Inventory for Measuring Coping with Stress (MINI-COPE) and The Beck Hopelessness Scale (BHS) and were employed in the research. <strong>Results.</strong> The mediating role of turning to religion in relationship between perceived hopelessness and job satisfaction was confirmed only in the group of women. The relationship found in this group indicates that perceived hopelessness is alleviated by turning to religion, which at the same time leads to an increase in job satisfaction.</p> <p><strong>Conclusion.</strong> The obtained results prove that it should be standard practice to offer specialist help after potentially traumatic events in the workplace not only in the form of emotional and/or instrumental support but also in the form of spiritual help.</p>
A Randomized Trial Comparing "Push" Versus "Pull" Technology for Mobilizing Pain Evidence Into Practice Across Different Health Professions
ClinicalTrials.gov study NCT01348802. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Knowledge of Nursing Theories of Teaching With Creative Drama in Fundamentals of Nursing Course Level and Perception of Nursing Profession
ClinicalTrials.gov study NCT06485570. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Graduate health professions education programs as they choose to represent themselves: A website review
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Data from: Prevalence of tobacco use and perceptions of student health professionals about cessation training: results from Global Health Professions Student Survey
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MANUAL LABOR IS TRENDING: WHY PEOPLE ARE TURNING TO CRAFT PROFESSIONS IN UZBEKISTAN
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MUTUAL INTEGRATION OF DISCIPLINES IN EDUCATION OF STUDENTS FOR THE ENGINEERING PROFESSION
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CREATIVE ACTIVITY IN PREPARING PRIMARY CLASS TEACHERS TO DIRECT NATIONAL PROFESSIONS
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USING KOMPAS-3D IN ENGINEERING EDUCATION: DEVELOPING SKILLS AND PREPARING FOR A PROFESSION
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Generational Diversity in the Medical Profession
ClinicalTrials.gov study NCT06446297. IPD Sharing: NO. Countries: 0. Publications: 1.
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