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

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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.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-81813-0.

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Most cited references 43

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The Law of Attrition

Gunther Eysenbach (2005)

In an ongoing effort of this Journal to develop and further the theories, models, and best practices around eHealth research, this paper argues for the need for a “science of attrition”, that is, a need to develop models for discontinuation of eHealth applications and the related phenomenon of participants dropping out of eHealth trials. What I call “law of attrition” here is the observation that in any eHealth trial a substantial proportion of users drop out before completion or stop using the appplication. This feature of eHealth trials is a distinct characteristic compared to, for example, drug trials. The traditional clinical trial and evidence-based medicine paradigm stipulates that high dropout rates make trials less believable. Consequently eHealth researchers tend to gloss over high dropout rates, or not to publish their study results at all, as they see their studies as failures. However, for many eHealth trials, in particular those conducted on the Internet and in particular with self-help applications, high dropout rates may be a natural and typical feature. Usage metrics and determinants of attrition should be highlighted, measured, analyzed, and discussed. This also includes analyzing and reporting the characteristics of the subpopulation for which the application eventually “works”, ie, those who stay in the trial and use it. For the question of what works and what does not, such attrition measures are as important to report as pure efficacy measures from intention-to-treat (ITT) analyses. In cases of high dropout rates efficacy measures underestimate the impact of an application on a population which continues to use it. Methods of analyzing attrition curves can be drawn from survival analysis methods, eg, the Kaplan-Meier analysis and proportional hazards regression analysis (Cox model). Measures to be reported include the relative risk of dropping out or of stopping the use of an application, as well as a “usage half-life”, and models reporting demographic and other factors predicting usage discontinuation in a population. Differential dropout or usage rates between two interventions could be a standard metric for the “usability efficacy” of a system. A “run-in and withdrawal” trial design is suggested as a methodological innovation for Internet-based trials with a high number of initial dropouts/nonusers and a stable group of hardcore users.

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Determining what individual SUS scores mean: adding an adjective rating scale

A. Bangor, P Kortum, J. Miller … (2009)

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Is Open Access

Barriers to the acceptance of electronic medical records by physicians from systematic review to taxonomy and interventions

Albert Boonstra, Manda Broekhuis (2010)

Background The main objective of this research is to identify, categorize, and analyze barriers perceived by physicians to the adoption of Electronic Medical Records (EMRs) in order to provide implementers with beneficial intervention options. Methods A systematic literature review, based on research papers from 1998 to 2009, concerning barriers to the acceptance of EMRs by physicians was conducted. Four databases, "Science", "EBSCO", "PubMed" and "The Cochrane Library", were used in the literature search. Studies were included in the analysis if they reported on physicians' perceived barriers to implementing and using electronic medical records. Electronic medical records are defined as computerized medical information systems that collect, store and display patient information. Results The study includes twenty-two articles that have considered barriers to EMR as perceived by physicians. Eight main categories of barriers, including a total of 31 sub-categories, were identified. These eight categories are: A) Financial, B) Technical, C) Time, D) Psychological, E) Social, F) Legal, G) Organizational, and H) Change Process. All these categories are interrelated with each other. In particular, Categories G (Organizational) and H (Change Process) seem to be mediating factors on other barriers. By adopting a change management perspective, we develop some barrier-related interventions that could overcome the identified barriers. Conclusions Despite the positive effects of EMR usage in medical practices, the adoption rate of such systems is still low and meets resistance from physicians. This systematic review reveals that physicians may face a range of barriers when they approach EMR implementation. We conclude that the process of EMR implementation should be treated as a change project, and led by implementers or change managers, in medical practices. The quality of change management plays an important role in the success of EMR implementation. The barriers and suggested interventions highlighted in this study are intended to act as a reference for implementers of Electronic Medical Records. A careful diagnosis of the specific situation is required before relevant interventions can be determined.

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Author and article information

Contributors

Grzegorz Józef Nowicki:

ORCID: http://orcid.org/0000-0002-0503-8847

gnowicki84@gmail.com

Journal

Journal ID (nlm-ta): Sci Rep

Journal ID (iso-abbrev): Sci Rep

Title: Scientific Reports

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2045-2322

Publication date (Electronic): 30 November 2024

Publication date PMC-release: 30 November 2024

Publication date Collection: 2024

Volume: 14

Electronic Location Identifier: 29765

Affiliations

[1 ]Department of Family and Geriatric Nursing, Medical University of Lublin, ( https://ror.org/016f61126) Lublin, Poland

[2 ]Student Research Association at the Department of Family and Geriatric Nursing, Medical University of Lublin, ( https://ror.org/016f61126) Lublin, Poland

[3 ]Department of Computer ScienceFaculty of Electrical Engineering and Computer Science, Lublin University of Technology, ( https://ror.org/024zjzd49) Lublin, Poland

Author information

Grzegorz Józef Nowicki http://orcid.org/0000-0002-0503-8847

Marek Miłosz http://orcid.org/0000-0002-5898-815X

Mariusz Dzieńkowski http://orcid.org/0000-0002-1932-297X

Barbara Ślusarska http://orcid.org/0000-0003-0101-9216

Article

Publisher ID: 81813

DOI: 10.1038/s41598-024-81813-0

PMC ID: 11607312

PubMed ID: 39613888

SO-VID: 2fa7d728-557f-49a3-98ee-ea8c304eebc0

License:

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

History

Date received : 21 February 2024

Date accepted : 29 November 2024

Funding

Funded by: Ministry of Science and Higher Education

Award ID: SKN/SP/535770/2022

Custom metadata

ScienceOpen disciplines: Uncategorized

Keywords: mobile application,nursing students,nurses,patients,clinical assessment,addie model,health care,health occupations,medical research,signs and symptoms

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ScienceOpen disciplines: Uncategorized

Keywords: mobile application, nursing students, nurses, patients, clinical assessment, addie model, health care, health occupations, medical research, signs and symptoms

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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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Most cited references 43

The Law of Attrition

Determining what individual SUS scores mean: adding an adjective rating scale

Barriers to the acceptance of electronic medical records by physicians from systematic review to taxonomy and interventions

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