The health assets model is a field of work that has protective effects on children associated with the protection, safety, and to their well being. This assets model is complementary, to the deficit model, which is often absent. From this point of view, we present the case of a 4 year old who was healthy and for whom a series of activities were designed with parents as primary implementers and directed primarily to the maintenance of health and child welfare. To do this, a care plan for parents caring for the learning child was developed based NANDA nursing taxonomy, and the NOC and NIC classifications in order to achieve the desired outcomes and carry out the appropriate nursing interventions. From the methodological point of view, possessing a common language and a nursing diagnostic taxonomy are keys to the development of our profession, but to work from a salutogenic perspective based on the NANDA International diagnoses, we believe that this does not fit properly. There is a lack of development in this area and would be interesting to develop it.
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http://dx.doi.org/10.1016/j.enfcli.2011.10.002 | DOI Listing |
J Gerontol B Psychol Sci Soc Sci
January 2025
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Objectives: Prosociality, defined as positive other-regarding intentions and behaviors, is a modifiable factor demonstrated to be associated with better mental, physical, and cognitive health in older adults. Prior studies have largely focused on individual prosocial behaviors, especially volunteering. This study examines whether prosocial intentions are associated with maintaining cognitive health over time.
View Article and Find Full Text PDFBMC Health Serv Res
January 2025
Department of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, 21205, USA.
Background: Since the inception of the ASHAs in the year 2005, their work horizons have increased from Reproductive, Maternal, Newborn, Child, and Adolescent health (RMNCH + A), Communicable and Non-Communicable Diseases (CD & NCD) to oral health, ophthalmologic care, and other supportive community level healthcare services. The present literature lacks comprehensive understanding and synthesis of domain-wise knowledge of ASHAs and the factors affecting their knowledge. Therefore, this study aimed to synthesize and collate the relevant evidence to understand the overall knowledge of ASHAs.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, Australia.
Civil infrastructure assets' contribution to countries' economic growth is significantly increasing due to the rapid population growth and demands for public services. These civil infrastructures, including roads, bridges, railways, tunnels, dams, residential complexes, and commercial buildings, experience significant deterioration from the surrounding harsh environment. Traditional methods of visual inspection and non-destructive tests are generally undertaken to monitor and evaluate the structural health of the infrastructure.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China.
With the rapid development of blockchain technology, fraudulent activities have significantly increased, posing a major threat to the personal assets of blockchain users. The blockchain transaction network formed during user transactions can be represented as a graph consisting of nodes and edges, making it suitable for a graph data structure. Fraudulent nodes in the transaction network are referred to as anomalous nodes.
View Article and Find Full Text PDFSci Rep
January 2025
University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Subjective wellbeing data are increasingly used across the social sciences. Yet, despite the widespread use of such data, the predictive power of approaches commonly used to model wellbeing is only limited. In response, we here use tree-based Machine Learning (ML) algorithms to provide a better understanding of respondents' self-reported wellbeing.
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