Evidence map›Paper›PMID 38498019›Full record

ArticleJMIR formative research2024

Using Principles of Digital Development for a Smartphone App to Support Data Collection in Patients With Acute Myocardial Infarction and Physical Activity Intolerance: Case Study.

Diana Isabel Cáceres Rivera, Luz Mileyde Jaimes Rojas, Lyda Z Rojas, Diana Canon Gomez, David Andrés Castro Ruiz, Luis Alberto López Romero

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 100% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 3 institutions in 2 countries.

Diana Isabel Cáceres Rivera *Facultad de Enfermería, Universidad Cooperativa de Colombia, Bucaramanga, Colombia.ORCID https://orcid.org/0000-0002-4751-6173
Luz Mileyde Jaimes Rojas *Facultad de Enfermería, Universidad Cooperativa de Colombia, Bucaramanga, Colombia.ORCID https://orcid.org/0000-0003-1298-3182
Lyda Z Rojas *Centro de Investigaciones, Fundación Cardiovascular de Colombia, Floridablanca, Colombia.ORCID https://orcid.org/0000-0002-4252-7105
Diana Canon Gomez *Centro de Investigaciones, Fundación Cardiovascular de Colombia, Floridablanca, Colombia.ORCID https://orcid.org/0000-0002-0373-9260
David Andrés Castro Ruiz *Facultad de Enfermería, Universidad Cooperativa de Colombia, Bucaramanga, Colombia.ORCID https://orcid.org/0000-0002-4411-1613
Luis Alberto López RomeroDepartamento de Pediatría, de Obstetricia y Ginecología y de Medicina Preventiva y Salud Pública, Universidad Autónoma de Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0002-7698-7900
Fundación Cardiovascular de Colombia · COUniversidad Cooperativa de Colombia · COUniversitat Autònoma de Barcelona · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdvances in health have highlighted the need to implement technologies as a fundamental part of the diagnosis, treatment, and recovery of patients at risk of or with health alterations. For this purpose, digital platforms have demonstrated their applicability in the identification of care needs. Nursing is a fundamental component in the care of patients with cardiovascular disorders and plays a crucial role in diagnosing human responses to these health conditions. Consequently, the validation of nursing diagnoses through ongoing research processes has become a necessity that can significantly impact both patients and health care professionals.

objectiveWe aimed to describe the process of developing a mobile app to validate the nursing diagnosis "intolerance to physical activity" in patients with acute myocardial infarction.

methodsWe describe the development and pilot-testing of a mobile system to support data collection for validating the nursing diagnosis of activity intolerance. This was a descriptive study conducted with 11 adults (aged ≥18 years) who attended a health institution for highly complex needs with a suspected diagnosis of coronary syndrome between August and September 2019 in Floridablanca, Colombia. An app for the clinical validation of activity intolerance (North American Nursing Diagnosis Association [NANDA] code 00092) in patients with acute coronary syndrome was developed in two steps: (1) operationalization of the nursing diagnosis and (2) the app development process, which included an evaluation of the initial requirements, development and digitization of the forms, and a pilot test. The agreement level between the 2 evaluating nurses was evaluated with the κ index.

resultsWe developed a form that included sociodemographic data, hospital admission data, medical history, current pharmacological treatment, and thrombolysis in myocardial infarction risk score (TIMI-RS) and GRACE (Global Registry of Acute Coronary Events) scores. To identify the defining characteristics, we included official guidelines, physiological measurements, and scales such as the Piper fatigue scale and Borg scale. Participants in the pilot test (n=11) had an average age of 63.2 (SD 4.0) years and were 82% (9/11) men; 18% (2/11) had incomplete primary schooling. The agreement between the evaluators was approximately 80% for most of the defining characteristics. The most prevalent characteristics were exercise discomfort (10/11, 91%), weakness (7/11, 64%), dyspnea (3/11, 27%), abnormal heart rate in response to exercise (2/10, 20%), electrocardiogram abnormalities (1/10, 9%), and abnormal blood pressure in response to activity (1/10, 10%).

conclusionsWe developed a mobile app for validating the diagnosis of "activity intolerance." Its use will guarantee not only optimal data collection, minimizing errors to perform validation, but will also allow the identification of individual care needs.

Indexed as

appapplications of medical informaticscoronary diseasedata collectiondevelopmenthealth care reformhealth datamedical informaticsmedical informatics appsmobile appmobile applicationsnursing diagnosisnursing researchresearch datasoftwarevalidation

Identifiers

PMID38498019
PMCPMC10985596
OpenAlexW4390515637

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.