To identify the nursing care problems related to the clinical process of disease by COVID-19. METHOD: The study applied the taxonomic triangulation technique on a clinical management guide to coronavirus disease, COVID-19, from the World Health Organization. The technique is divided into the phases: extraction of knowledge in natural language about assessment, planning and intervention, translation into standard language NOC and NIC, linking to NANDA-I diagnoses, triangulation looking for diagnostic matches in the three sets, and, finally, validation by a panel of experts from a hospital and a university. FINDINGS: The extraction identified 159 terms in natural language that were translated into 173 variables: 34 NOC for assessment, 19 NOC for planning, and 120 NIC for intervention. The relationships to NANDA-I diagnoses recorded 2,182 links and the triangulation returned 109 diagnoses, 54 of them for a critical situation. The panel of experts unanimously validated the 29 diagnoses with the highest number of links. CONCLUSION: Coronavirus disease, COVID-19, involves a complex situation with multiple associated care problems that can be identified using the taxonomic triangulation technique. IMPLICATIONS FOR NURSING PRACTICE:The links between taxonomies and the taxonomic triangulation technique are an important tool for generating knowledge. The results of this study may guide the diagnosis and treatment of coronavirus disease, COVID-19, as well as similar processes that occur with acute respiratory distress syndrome.
Modern handheld devices and wireless communications foster new kinds of communication and interaction that can define new approaches to teaching and learning. Mobile learning (m-learning) seeks to use them extensively, exactly in the same way in which e-learning uses personal computers and wired communication technologies. In this new mobile environment, new applications and educational models need to be created and tested to confirm (or reject) their validity and usefulness. In this article, we present a mobile tool aimed at self-assessment, which allows students to test their knowledge at any place and at any time. The degree to which the students' achievement improved is also evaluated, and a survey on the students' opinion of the new tool was also conducted. An experimental group of 20- to 21-year-old nursing students was chosen to test the tool. Results show that this kind of tool improves students' achievement and does not make necessary to introduce substantial changes in current teaching activities and methodology.
Objective: to construct and validate a tool for the evaluation of responders in tactical casualty care simulations. Method: three rubrics for the application of a tourniquet, an emergency bandage and haemostatic agents recommended by the Hartford Consensus were developed and validated. Validity and reliability were studied. Validation was performed by 4 experts in the field and 36 nursing participants who were selected through convenience sampling. Three rubrics with 8 items were evaluated (except for the application of an emergency bandage, for which 7 items were evaluated). Each simulation was evaluated by 3 experts. Results: an excellent score was obtained for the correlation index for the 3 simulations and 2 levels that were evaluated (competent and expert). The mean score for the application of a tourniquet was 0.897, the mean score for the application of an emergency bandage was 0.982, and the mean score for the application of topical haemostats was 0.805. Conclusion: this instrument for the evaluation of nurses in tactical casualty care simulations is considered useful, valid and reliable for training in a prehospital setting for both professionals who lack experience in tactical casualty care and those who are considered to be experts.
Modern handheld devices and wireless communications foster new kinds of communication and interaction that can define new approaches to teaching and learning. Mobile learning (m-learning) seeks to use them extensively, exactly in the same way in which e-learning uses personal computers and wired communication technologies. In this new mobile environment, new applications and educational models need to be created and tested to confirm (or reject) their validity and usefulness. In this article, we present a mobile tool aimed at self-assessment, which allows students to test their knowledge at any place and at any time. The degree to which the students' achievement improved is also evaluated, and a survey on the students' opinion of the new tool was also conducted. An experimental group of 20- to 21-year-old nursing students was chosen to test the tool. Results show that this kind of tool improves students' achievement and does not make necessary to introduce substantial changes in current teaching activities and methodology.
The COVID-19 pandemic is a challenge for health systems. The absence of prior evidence makes it difficult to disseminate consensual care recommendations. However, lifestyle adaptation is key to controlling the pandemic. In light of this, nursing has its own model and language that allow these recommendations to be combined from global and person-centred perspectives. The purpose of the study is to design a population-oriented care recommendation guide for COVID-19. The methodology uses a group of experts who provide classified recommendations according to Gordon’s functional patterns, after which a technical team unifies them and returns them for validation through the content validity index (CVI). The experts send 1178 records representing 624 recommendations, which are unified into 258. In total, 246 recommendations (95.35%) are validated, 170 (65.89%) obtain high validation with CVI > 0.80, and 12 (4.65%) are not validated by CVI < 0.50. The mean CVI per pattern is 0.84 (0.70–0.93). These recommendations provide a general framework from a nursing care perspective. Each professional can use this guide to adapt the recommendations to each individual or community and thus measure the health impact. In the future, this guideline could be updated as more evidence becomes available.
Taxonomic triangulation is a data mining technique for the management of care knowledge. This technique uses standardized languages, such as North American Nursing Diagnosis Association International, Nursing Outcomes Classification, and Nursing Interventions Classification, as well as logic. Its purpose is to find patterns in the data and identify care diagnoses. Triangulation can be applied to databases (clinical records) or to bibliographic sources (eg, protocols). The objective of this study is to identify the care diagnoses implicit in the nursing care protocols of the Community of Madrid. The method followed has three phases: knowledge extraction for mapping of variables, linking to diagnoses, and triangulation with analysis. The study analyzes six protocols, and 344 variables (167 assessment, 29 planning, and 148 intervention) and 6118 links have been extracted. Triangulation identified 165 NANDA diagnoses (68.48%), and only 25 labels were not revealed through this process. As a limitation, the results depend on the knowledge presented in protocols and change with language editions. Some labels included in the sample are recent and are not included in the links with nursing outcomes classification and nursing interventions classification. In conclusion, taxonomic triangulation makes it possible to manage knowledge, discover data patterns, and represent care situations.
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