Evidence map›Paper›PMID 39613888›Full record

ArticleScientific reports2024

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

Grzegorz Józef Nowicki, Wiktoria Mazurek, Alicja Waśkowicz, Ewa Kowalczyk, Julia Kozioł, Marek Miłosz, Mariusz Dzieńkowski, Barbara Ślusarska

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Grzegorz Józef NowickiDepartment of Family and Geriatric Nursing, Medical University of Lublin, Lublin, Poland. gnowicki84@gmail.com.ORCID http://orcid.org/0000-0002-0503-8847
Wiktoria MazurekStudent Research Association at the Department of Family and Geriatric Nursing, Medical University of Lublin, Lublin, Poland.
Alicja WaśkowiczStudent Research Association at the Department of Family and Geriatric Nursing, Medical University of Lublin, Lublin, Poland.
Ewa KowalczykStudent Research Association at the Department of Family and Geriatric Nursing, Medical University of Lublin, Lublin, Poland.
Julia KoziołStudent Research Association at the Department of Family and Geriatric Nursing, Medical University of Lublin, Lublin, Poland.
Marek MiłoszDepartment of Computer ScienceFaculty of Electrical Engineering and Computer Science, Lublin University of Technology, Lublin, Poland.ORCID http://orcid.org/0000-0002-5898-815X
Mariusz DzieńkowskiDepartment of Computer ScienceFaculty of Electrical Engineering and Computer Science, Lublin University of Technology, Lublin, Poland.ORCID http://orcid.org/0000-0002-1932-297X
Barbara ŚlusarskaDepartment of Family and Geriatric Nursing, Medical University of Lublin, Lublin, Poland.ORCID http://orcid.org/0000-0003-0101-9216

Funding

Ministry of Science and Higher Education SKN/SP/535770/2022
6 · The paper itself

Abstract

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.

Indexed as

Mobile ApplicationsStudents, NursingAdultFemaleHumansMaleNursesADDIE modelClinical assessmentMobile applicationNursesNursing studentsPatients

Identifiers

PMID39613888
PMCPMC11607312

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.