Baza Publikacji Pracowników Politechniki Lubelskiej

Status:
Autorzy:	Nowicki Grzegorz, Mazurek Wiktoria, Waśkowicz Alicja, Kowalczyk Ewa, Kozioł Julia, Miłosz Marek, Dzieńkowski Mariusz, Ślusarska Barbara
Dyscypliny:
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Rok wydania:	2024
Wersja dokumentu:	Drukowana \| Elektroniczna
Język:	angielski
Wolumen/Tom:	14
Numer artykułu:	29765
Strony:	1 - 15
Impact Factor:	3,8
Web of Science® Times Cited:	1
Scopus® Cytowania:	0
Bazy:	Web of Science \| Scopus
Efekt badań statutowych	NIE
Finansowanie:	With regard to this endeavour, the Ministry of Science and Higher Education provided co-financing as part of the „Studenckie koła naukowe tworzą innowacje” program [“Student research groups create innovations”], which allowed the project to be implemented (contract number: SKN/SP/535770/2022). Open access funding provided by the Medical University of Lublin, Poland.
Materiał konferencyjny:	NIE
Publikacja OA:	TAK
Licencja:
Sposób udostępnienia:	Otwarte czasopismo
Wersja tekstu:	Ostateczna wersja opublikowana
Czas opublikowania:	W momencie opublikowania
Data opublikowania w OA:	30 listopada 2024
Abstrakty:	angielski
	Healthcare workers are increasingly utilising cutting-edge technology, including mobile apps, to enhance patient health care and ensure efficient professional performance. The aim of this study was to design, develop and evaluate an educational mobile app dedicated towards being employed by nursing students and practicing nurses to support the clinical assessment of a patient’s health condition in nursing care. In order to develop the mobile app, the Analysis, Design, Development, Implementation and Evaluation (ADDIE) model was employed. Between 2022 and 2023, a “Diagnostic Nurse” mobile app was developed in the “Android Application Package (APK).” The app’s usability was tested in the laboratory by 20 participants. Three methods were employed in the study, that is, an eye-tracking technique, a qualitative evaluation and a quantitative evaluation. According to the System Usability Scale (SUS), the app test score for the nursing student group was assessed as 83.3 ± 8.9, and for the practicing nursing group, this was 84 ± 12.7. These results indicate that the mobile app’s is highly usable. The app received high ratings in the “user-friendliness”, “ease-of-use”, and “user satisfaction” categories. The “DiagNurse” app makes it easier to learn how to conduct a clinical assessment of a patient’s condition in nursing care, resulting in better information acquisition, assessment accuracy and speed. Given the low cost of the app development and the ADDIE model on which it is based, the app may be beneficial to nursing students, practicing nurses and other health-care professionals and students.

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Development and pre-evaluation of a “DiagNurse” mobile app to support nurses in clinical diagnosis using the ADDIE model

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