Evidence map›Paper›PMID 39353603›Full record

ArticleInternational wound journal2024

Co-creation and evaluation of an algorithm for the development of a mobile application for wound care among new graduate nurses: A mixed methods study.

Julie Gagnon, Julie Chartrand, Sebastian Probst, Éric Maillet, Emily Reynolds, Michelle Lalonde

Abstract read
In one paragraph

Article in International wound journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

6 authors.

Julie GagnonSchool of Nursing, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada.ORCID https://orcid.org/0009-0000-1045-5584
Julie ChartrandSchool of Nursing, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada.ORCID https://orcid.org/0000-0001-9075-054X
Sebastian ProbstHES-SO, University of Applied Sciences and Arts Western Switzerland, Geneva, Switzerland.ORCID https://orcid.org/0000-0001-9603-1570
Éric MailletSchool of Nursing, Faculty of Medicine and Health Sciences, University of Sherbrooke, Sherbrooke, QC, Canada.ORCID https://orcid.org/0000-0002-2222-5783
Emily ReynoldsSchool of Nursing, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada.
Michelle LalondeSchool of Nursing, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada.ORCID https://orcid.org/0000-0002-8242-3159

Funding

CIHR 202111FBD-476880-67262Fonds de Recherche du Québec Santé 2022-2023-BF2-_319284University of Ottawa
6 · The paper itself

Abstract

Chronic wounds are a growing concern due to aging populations, sedentary lifestyles and increasing rates of obesity and chronic diseases. The impact of such wounds is felt worldwide, posing a considerable clinical, environmental and socioeconomic challenge and impacting the quality of life. The increasing complexity of care requires a holistic approach, along with extensive knowledge and skills. The challenge experienced by health-care professionals is particularly significant for newly graduate nurses, who face a gap between theory and practice. Digital tools, such as mobile applications, can support wound care by facilitating more precise assessments, early treatment, complication prevention and better outcomes. They also aid in clinical decision-making and improve healthcare delivery in remote areas. Several mobile applications have emerged to enhance wound care. However, there are no applications dedicated to newly graduate nurses. The aim of this study was to co-create and evaluate an algorithm for the development of a wound care mobile application supporting clinical decisions for new graduate nurses. The development of this mobile application is envisioned to improve knowledge application and facilitate evidence-based practice. This study is part of a multiphase project that adopted a pragmatic epistemological approach, using the 'Knowledge-to-Action' conceptual model and Duchscher's Stages of Transition Theory. Following a scoping review, an expert consensus, and stakeholder meetings, this study was pursued through a sequential exploratory mixed methods design carried out in two phases. In the initial phase, 21 participants engaged in semi-structured focus groups to explore their needs regarding clinical decision support in wound care, explore their perceptions of the future mobile application's content and identify and categorize essential components. Through descriptive analysis, five overarching themes emerged, serving as guiding principles for conceptual data model development and refinement. These findings confirmed the significance of integrating a comprehensive glossary complemented by photos, ensuring compatibility between the mobile application and existing documentation systems, and providing quick access to information to avoid burdening work routines. Subsequently, the algorithm was created from the qualitative data collected. The second phase involved presenting an online SurveyMonkey® questionnaire to 34 participants who were not part of the initial phase to quantitatively measure the usability of this algorithm among future users. This phase revealed very positive feedback regarding the usability [score of 6.33 (±0.19) on a scale of 1-7], which reinforces its quality. The technology maturation process can now continue with the development of a prototype and subsequent validation in a laboratory setting.

Indexed as

AlgorithmsMobile ApplicationsAdultFemaleHumansMaleWound HealingWounds and Injuriesclinical decision‐makingevidence‐based practicemobile applicationsuser‐centred designwounds

Identifiers

PMID39353603
PMCPMC11444739

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.