Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 5 de 5
Filter
Add more filters










Database
Publication year range
2.
J Pediatr Nurs ; 77: 89-95, 2024.
Article in English | MEDLINE | ID: mdl-38490106

ABSTRACT

BACKGROUND/AIM: The humanization of the hospital environment of pediatric departments represents an area of research and intervention on improving the quality of life for hospitalized patients, but also that one of relatives and health professionals. The aim of the study was to test, in a sample of nurses and hospitalized children's parents, whether the pictorial intervention impacted the perceptions of affective qualities of hospital environment. METHODS: This quasi-experimental design study investigated the effects of a pictorial humanization intervention which consisted of some naturalistic and colorful illustrations in the corridor of two pediatric wards of an Italian hospital. A total of 425 parents of hospitalized children and 80 nurses were asked to complete the Italian version of the "Scale of measurement of the affective qualities of places" in two different moments: 1) before the pictorial intervention and 2) three months after its implementation. RESULTS: For all participants (parents and nurses), results showed a significant effect of pictorial intervention with the four positive dimensions investigated (Relaxing, Exciting, Pleasant, and Stimulating) reporting higher scores after being performed it, and with the four negative dimensions (Distressing, Gloomy, Unpleasant, Sleepy) showing lower scores. CONCLUSIONS: Data suggest that the pictorial intervention could be particularly useful to create more welcoming hospital environments, reducing distress levels from hospitalized patients, but also of relatives and healthcare professionals. IMPLICATIONS TO PRACTICE: Pictorial interventions improve the emotional atmosphere in pediatric healthcare settings. Integrating visual elements related to care and healing enhances user experience, creating a more welcoming environment.


Subject(s)
Hospitals, Pediatric , Parents , Humans , Female , Male , Parents/psychology , Child , Italy , Adult , Child, Hospitalized/psychology , Quality of Life , Child, Preschool , Pediatric Nursing , Nursing Staff, Hospital/psychology
3.
Phys Med ; 91: 140-150, 2021 Nov.
Article in English | MEDLINE | ID: mdl-34801873

ABSTRACT

Artificial Intelligence (AI) techniques have been implemented in the field of Medical Imaging for more than forty years. Medical Physicists, Clinicians and Computer Scientists have been collaborating since the beginning to realize software solutions to enhance the informative content of medical images, including AI-based support systems for image interpretation. Despite the recent massive progress in this field due to the current emphasis on Radiomics, Machine Learning and Deep Learning, there are still some barriers to overcome before these tools are fully integrated into the clinical workflows to finally enable a precision medicine approach to patients' care. Nowadays, as Medical Imaging has entered the Big Data era, innovative solutions to efficiently deal with huge amounts of data and to exploit large and distributed computing resources are urgently needed. In the framework of a collaboration agreement between the Italian Association of Medical Physicists (AIFM) and the National Institute for Nuclear Physics (INFN), we propose a model of an intensive computing infrastructure, especially suited for training AI models, equipped with secure storage systems, compliant with data protection regulation, which will accelerate the development and extensive validation of AI-based solutions in the Medical Imaging field of research. This solution can be developed and made operational by Physicists and Computer Scientists working on complementary fields of research in Physics, such as High Energy Physics and Medical Physics, who have all the necessary skills to tailor the AI-technology to the needs of the Medical Imaging community and to shorten the pathway towards the clinical applicability of AI-based decision support systems.


Subject(s)
Artificial Intelligence , Cloud Computing , Humans , Italy , Nuclear Physics , Precision Medicine
4.
Assist Inferm Ric ; 26(4): 210-8, 2007.
Article in Italian | MEDLINE | ID: mdl-18297985

ABSTRACT

UNLABELLED: To assess the effectiveness of a new organizational model for professional development, that assigns and financially rewards 12 positions that encompass specific responsibilities (such as responsible of Evidence based Nursing; expert in pressure ulcers, responsible of the newly employed nurses), nurses' satisfaction was measured. METHOD: From November to December 2003 the MC Closey Muller Satisfaction Questionnaire was administered to all the nurses in service in the wards. Levels of satisfaction of nurses with and without specific responsibilities were compared. The answers for each item are on a five points Likert scale. RESULTS: The questionnaire was administered to 1.167 nurses (58.9% of the nurses of the hospital); 602 were assigned positions with specific responsibilities. Overall, nurses with positions assigned were more satisfied (2.76 vs 2.61, p.0.01) and statistically significant differences were obtained for 14/31 items of the scale, and for 5/8 subscales. CONCLUSIONS: The results obtained, although the level of satisfaction is lower compared to other studies, confirm the strategy of professional development adopted in the Hospital. The analysis of results for each position allowed some reflections and to identify strategies to improve the organizational support to some positions.


Subject(s)
Job Satisfaction , Models, Organizational , Nursing Staff, Hospital/organization & administration , Nursing Staff, Hospital/psychology , Humans , Italy , Nurse's Role , Surveys and Questionnaires , Time Factors
5.
Development ; 131(10): 2475-84, 2004 May.
Article in English | MEDLINE | ID: mdl-15128675

ABSTRACT

Production of genetically identical non-human primates through somatic cell nuclear transfer (SCNT) can provide diseased genotypes for research and clarify embryonic stem cell potentials. Understanding the cellular and molecular changes in SCNT is crucial to its success. Thus the changes in the first cell cycle of reconstructed zygotes after nuclear transfer (NT) of somatic cells in the Long-tailed Macaque (Macaca fascicularis) were studied. Embryos were reconstructed by injecting cumulus and fibroblasts from M. fascicularis and M. silenus, into enucleated M. fascicularis oocytes. A spindle of unduplicated premature condensed chromosome (PCC spindle) from the donor somatic cell was formed at 2 hours after NT. Following activation, the chromosomes segregated and moved towards the two PCC spindle poles, then formed two nuclei. Twenty-four hours after activation, the first cell division occurred. A schematic of the first cell cycle changes following injection of a somatic cell into an enucleated oocyte is proposed. Ninety-three reconstructed embryos were transferred into 31 recipients, resulting in 7 pregnancies that were confirmed by ultrasound; unfortunately none progressed beyond 60 days.


Subject(s)
Cell Cycle/physiology , Cell Nucleus/ultrastructure , Fibroblasts/cytology , Macaca fascicularis/embryology , Nuclear Transfer Techniques , Animals , Cell Division , Cell Nucleus/physiology , Cells, Cultured , Embryonic and Fetal Development , Female , Flow Cytometry , Genotype , Male , Pregnancy
SELECTION OF CITATIONS
SEARCH DETAIL
...