Self‐supporting wound care mobile applications for nurses: A scoping review
Bibliographic record
Abstract
AIM: This study provides an overview of the literature to identify and map the types of available evidence on self-supporting mobile applications used by nurses in wound care regarding their development, evaluation and outcomes for patients, nurses and the healthcare system. DESIGN: Scoping review. REVIEW METHOD: Joanna Briggs Institute scoping review methodology was used. DATA SOURCES: A search was performed using MEDLINE, Embase, CINAHL (via EBSCO), Web of Science, LiSSa (Littérature Scientifique en Santé), Cochrane Wounds, Érudit and grey literature, between April and October 2022, updated in April 2023, to identify literature published in English and French. RESULTS: Eleven studies from 14 publications met the inclusion criteria. Mostly descriptive, the included studies presented mobile applications that nurses used, among other things, to assess wounds and support clinical decision-making. The results described how nurses were iteratively involved in the process of developing and evaluating mobile applications using various methods such as pilot tests. The three outcomes most frequently reported by nurses were as follows: facilitating care, documentation on file and access to evidence-based data. CONCLUSION: The potential of mobile applications in wound care is within reach. Nurses are an indispensable player in the successful development of these tools. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: If properly developed and evaluated, mobile applications for wound care could enhance nursing practices and improve patient care. The development of ethical digital competence must be ensured during initial training and continued throughout the professional journey. IMPACT: We identified a dearth of studies investigating applications that work without Internet access. More research is needed on the development of mobile applications in wound care and their possible impact on nursing practice in rural areas and the next generation of nurses. REPORTING METHOD: The Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Review guidelines were used. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".