Association of a structured prevention algorithm with nurse knowledge and device-related pressure injury severity in critical care: A pre‑post study

Yarkaram Zamani Shiva, Fateme Hasandoost, Malihe Nasiri and Tayebeh Mahvar

PLOS ONE, 2026, vol. 21, issue 10, 1-14

Abstract: Background: Medical Device-Related Pressure Injuries (MDRPI) are a serious complication in intensive care units (ICUs), yet structured prevention algorithms are lacking. Methods: This single-group, pre-test/post-test quasi-experimental study was conducted in the General Intensive Care Unit from February 2025 to April 2025. The sample comprised 38 nurses and 77 patients (39 pre-intervention, 38 post-intervention). Nurses’ knowledge was assessed using the MDRPUKQ questionnaire, and patient outcomes were monitored using baseline and post-intervention data on pressure injury prevalence and severity. Data were analyzed using SPSS version 26, employing descriptive and inferential statistics including paired t-tests, independent t-tests, chi-square tests, Fisher’s exact tests, and multivariable logistic regression. Results: The mean knowledge score increased significantly from 57.74 (SD = 11.15) before training to 89.55 (SD = 5.17) afterward (mean difference: 31.81, 95% CI: 28.35–35.27, P

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0359842

DOI: 10.1371/journal.pone.0359842

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