Validation and reliability of the Care Vulnerability Index: A study by interrater agreement and test–retest method

Batalla, Marta Fernández; Macario, Enrique Monsalvo San; Aguña, Alexandra González; Jaén, Sara Herrero; Diego, Blanca Gonzalo de; Manrique-Anaya, Yolima; Jiménez, Lourdes; Herrera, Estela Melguizo; García, José María Santamaría

doi:10.1002/nop2.1203

Cited by 8 publications

(4 citation statements)

References 26 publications

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“…The person is the central element of care, and it is defined from their vulnerability . Vulnerability is an essential human condition; it accompanies a person throughout life and is linked to the need and competence for self-care [ 21 , 22 ]. The environment circumscribes the person, constituting an open, complex, and multidimensional system in constant interaction that defines the risk in care.…”

Section: Introductionmentioning

confidence: 99%

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

Aguña

Batalla

Diego

et al. 2022

IJERPH

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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.

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Section: Introductionmentioning

confidence: 99%

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

Aguña

Batalla

Diego

et al. 2022

IJERPH

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“…A similar perspective is the one applied in Spain, where a vulnerability analysis is established according to populations and the conditions of the neighbourhoods where they live [ 48 ]. The rest of the assessment tools implemented in the robotic device were internationally known and validated in previous published studies [ 32 , 33 , 34 , 35 , 36 ]. In Spain, these tools are used by the public health system and are integrated in the Primary Care Services Portfolio, a document that includes the areas of action of health professionals [ 49 ].…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2023

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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.

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“…In this sense, the World Health Organization determines that men have a lower life expectancy, and this is due, among other factors, to those related to gender [51]. Furthermore, there is research that establishes that sex is a conditioning variable in people's care and, together with other variables, such as the perception of gender limitations, determines their level of vulnerability [28,52].…”

Section: Clinical Validationmentioning

confidence: 99%

Validation of the Health Index in the Postoperative Period: Use of the Nursing Outcome Classification to Determine the Health Level

Herrero Jaén,

González Aguña,

Fernández Batalla

et al. 2024

Healthcare

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Background: The postoperative period is the recovery time after surgery and is defined as an individual process whose purpose is to return the person to the state of normality and integrity that they had prior to surgery. Aim: Demonstrate the modification of the level of health of people in the early postoperative period through the development and validation of the Health Index Instrument, which is built from the Nursing Outcomes Classification (NOC) standardized language. Design: The design used a mixed method, which involved a first phase of instrument development and a second phase of instrument validation. Methods: The methods was based on focus group techniques with text analysis techniques, internal validation with a group of care language experts, external validation with a group of clinical nursing experts and a clinical validation with quantitative and qualitative analysis. A panel of experts in Language of Care evaluated the (NOC) labels and their correlation with the 11 Health Variables to construct the instrument. The instrument developed was subjected to external validation with a panel of clinical nurse experts in post-anesthesia care. The clinical validation included a cross-sectional descriptive study in a postoperative unit. The final sample of the cross-sectional descriptive study was 139 cases. Results: Of the 89 NOCs proposed in the preliminary construction phase of the instrument, 36 passed through the first round. Of those 36 NOCs, 25 passed through to the second round with a review performance and 11 directly as approved. The total number of approved NOCs were 4. The results of the research show that there are changes in the global score of the health level and in each health variable. It is observed that there was a significant increase in the scores of the health variables at admission and discharge (p < 0.001). Conclusions: The results of the data analysis show that six groups present a similar pattern of evolution of the health variables. A correlation was found between the time of stay in the unit with the scores obtained in the health variables, the physical functioning, comfort status and the presence of symptoms being particularly significant.

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Validation and reliability of the Care Vulnerability Index: A study by interrater agreement and test–retest method

Cited by 8 publications

References 26 publications

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

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

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

Validation of the Health Index in the Postoperative Period: Use of the Nursing Outcome Classification to Determine the Health Level

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