Accepted for/Published in: JMIR Formative Research
Date Submitted: Feb 10, 2023
Date Accepted: Jan 2, 2024
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
DEVELOPMENT OF A MOBILE APPLICATION FOR DATA COLLECTION IN NURSING RESEARCH: Survey study
ABSTRACT
Background:
Advances in health have highlighted the need to implement technologies as a fundamental part of the diagnosis, treatment and recovery of patients at risk or health alterations. In this sense, the use of digital platforms has demonstrated its applicability in the identification of care needs.
Objective:
To describe the process of developing a mobile application for collecting health research data .
Methods:
They used the CommCare Dimagi platform for developing a custom application for mobile smart to allow data collection on the bed of the patient in an easy, fast and practical way. Once the data collection format for an ongoing investigation had been prepared , the health professionals together with the engineer met to conduct the digitization of the forms.
Results:
An application was developed for the validation of nursing diagnosis in 3 steps: Operationalization of nursing diagnosis, development of the application and pilot test. The pilot test yielded descriptive data such as Average age of 65 ± 10 years, where 80.0% were men. The defining characteristics present in this group of patients were Exercise discomfort: (67.5%), alliteration in the electrocardiogram, (55.0%), fatigue (30.0%), abnormal heart rate in response to exercise (27.5%), dyspnea ( 25.0%), weakness (20.0%), and abnormal blood pressure in response to activity (5.0%)
Conclusions:
A mobile application was developed for implementation in the validation process of the activity intolerance-nursing diagnosis. Its use will guarantee not only an optimal data collection, minimizing errors to perform validation, but will also allow the identification of individual care needs.
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