Care Robotics: An Assessment of Professional Perception in the Face of the COVID-19 Pandemic.

The COVID-19 crisis accelerated the adoption of technologies. Technological advancement is also expected in robotics applied to any sector, including in healthcare. The aim is to assess the professional perception of care robotics facing COVID-19. This study aimed to (1) select a tool for assessing different aspects of healthcare, (2) analyse the professional perception about the development, usefulness and helpfulness of technologies and robotics in the field of healthcare and (3) evaluate the correlation between the perceived helpfulness of care robotics and the selected tool. We implement five validated clinical tests which integrate 80 items about a person and their clinical situation. From the sample of 46 professionals, 95.65% affirmed that technology was moderately to completely useful for professional performance in the context of the pandemic, lowering to 67.39% when asked only about robotics; 93.48% stated that the inclusion of robotics in at least one health area affected by COVID-19 would have helped them. Finally, the variables extracted from clinical tests corresponded to the most relevant health areas as identified by the professionals. This research shows the potential of care robotics oriented towards healthcare from a care paradigm.

Care Recommendations for the Chronic Risk of COVID-19: Nursing Intervention for Behaviour Changes.

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.

Diagnostics of care about environment: A systematic review through nursing taxonomies.

AIM: To analyse the representation of the environment in nursing diagnostic taxonomies. DESIGN: Systematic scoping review through nursing taxonomies. METHODS: The first phase identified nursing diagnostic taxonomies by systematic review. The diagnoses were associated with the environment by analysis of terms into the diagnosis label and definition. Data analysis was quantitative with frequency measurements. The second phase mapped the identified diagnoses to establish equivalences using analysis by terms in the diagnostic labels. Finally, the findings obtained in the first phase were compared with the OMAHA System. RESULTS: The bibliographic search identified 112 studies and 16 standardized languages for diagnoses. NANDA-I and ICNP were the most frequent taxonomies; ATIC, the most recent; and OMAHA, the oldest. 2,062 diagnoses from four diagnostic taxonomies were analysed, and 361 associations corresponding to 352 environmental diagnoses were identified. All taxonomies included the environment but with different weight relative to the interpersonal and geopolitical category.

Nursing Diagnoses for Coronavirus Disease, COVID-19: Identification by Taxonomic Triangulation.

PURPOSE: 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.