Background Pressure injuries remain a major patient safety concern in critically ill patients admitted to intensive care units (ICUs). Although the Braden Scale is widely used for pressure injury risk assessment, its performance may be limited in highly complex critical care settings. The COMHON Index was developed as an ICU‐specific tool integrating physiological variables related to tissue perfusion and oxygenation. Aim To compare the performance of the COMHON Index and the Braden Scale for pressure injury risk assessment in critically ill patients. Study Design A retrospective,longitudinal, comparative observational study was conducted in a single ICU inSpain between January 2023 and December 2024, using consecutive nonprobabilitysampling. Results A total of 476 critically ill patients were included; ICU‐acquired pressure injuries developed in 1.9% of patients during the first 24 h after ICU admission. Greater disease severitywas associated with a higher risk of pressure injury. Higher total Braden scores showed a protective effect, whereas COMHON domains related to consciousness, mobility, hemodynamic stability, and oxygenation were directly associated with pressure injury development. The COMHON Nutrition subscale did not reach statistical significance in univariable analysis (OR: 1.38; p = 0.303). In multivariable analysisusing Firth’s penalized logistic regression, impaired nutritional status(COMHON) was associated with pressure injury, whereas the Braden sensoryperception and moisture exposure subscales showed inverse associations. At the Youden‐optimized cutoffs (Braden ≤ 10; COMHON ≥ 15), the Braden Scale demonstrated 100.0% sensitivity (95% CI: 66.4–100.0) and 77.1% specificity (95% CI: 73.0–80.8), while the COMHON Index demonstrated 88.9% sensitivity (95% CI: 51.8–99.7) and 73.2% specificity (95% CI: 69.0–77.2). Both instruments showed very high negative predictive values (Braden: 100.0%; COMHON: 99.7%). Conclusions Both instruments were associated withpressure injury occurrence. The final multivariable model incorporated physiological domains from both instruments, two Braden Scale subscales (sensory perception and moisture exposure) and one COMHON Index domain (nutritional status), suggesting complementary rather than substitutive clinical utility. These findings should be interpreted cautiously given the retrospective single‐center design and low event rate. Prospective multicenter studies are needed to confirm the clinical utility of ICU‐specific risk assessment tools in pressure injury prevention. Relevance to Clinical Practice Integrating ICU‐specific physiological parameters into pressure injury risk assessment may support earlier identification of critically ill patients requiring intensified preventive interventions, including repositioning protocols, advanced pressure‐redistributing surfaces, nutritional optimization, and closer hemodynamic monitoring. These findings may contribute to more individualized nursing care planning and improved allocation of preventive resources in intensive care settings. Impact Statement This study supports the use of ICU‐specific risk assessment tools to strengthen patient safety strategies and optimize individualized nursing interventions in critical care settings.
Health literacy requires new competences as healthcare evolves, particularly when genomics is applied to disease prevention. Genomic literacy has been described from the same foundations as health literacy, but it also has its own unique characteristics, including an emphasis on numeracy. The aim of this longitudinal feasibility pilot study was to assess the health and genomic literacy of participants at risk of Type 2 diabetes, to better understand the factors influencing health and genomic literacy, as well as the relationship between these two literacy perspectives. The Everyday Health Information Literacy (EHIL) instrument, the European Health Literacy Survey Questionnaire (HLS‐EU‐Q16), and genomic literacy measures were used with 60 participants at baseline, and 49 participants completed postsurveys. Participants were informed of their personal polygenic risk score (PRS) for Type 2 diabetes before they filled the postsurveys. The data were analyzed using statistical methods. Health literacy did not change significantly during intervention, but genomic literacy, Section A, scores improved at postsurvey. There was no association between health literacy, EHIL, and genomic literacy, Section A, at baseline; however, a correlation was observed at postsurvey. Motivation was also correlated with health literacy, HLS‐EU‐Q16, and genomic literacy, Sections A and C, at postsurvey. In contrast, education, which appeared to influence genomic literacy, Section A, at baseline, no longer had a significant role at postsurvey. Even brief health counseling and genomic risk information can improve genomic literacy. We recommend that PRS results be disclosed in person, combined with lifestyle counseling. Personal counseling allows for the results to be explained according to the participant’s health literacy and understanding.
Artificial intelligence (AI) is transforming healthcare and nursing education globally. Despite its growing relevance, limited research has explored how orientation sessions influence nursing students’ knowledge and attitudes toward AI, particularly in maternity care settings in Egypt. This study evaluated the effect of structured orientation sessions on maternity nursing students’ knowledge and attitudes regarding AI applications in obstetric nursing at Ain Shams and Beni Suef universities. A quasiexperimental pre–post design was conducted among convenient sample of (786) third‐year maternity nursing students. Data were collected using a validated knowledge questionnaire and a Likert attitude scale before and after AI‐focused orientation sessions. Sessions included interactive lectures and culturally adapted educational materials. Statistical analyses assessed within‐ and between‐group differences. Preintervention, both groups demonstrated low‐to‐moderate knowledge and mixed attitudes toward AI. Postintervention, significant improvements were observed in knowledge and positive attitudes in both groups ( p < 0.001). Ain Shams students showed a higher postintervention awareness level (58.8%) compared to Beni Suef (19.8%). Attitudinal shifts were also more pronounced among Ain Shams students across multiple domains, including AI’s role in education, clinical practice, and student assessment. The study concluded that the orientation sessions improved knowledge, enhanced attitudes toward AI in obstetric nursing, and produced significant differences between the two study settings. Integrating AI education into nursing curricula is essential to prepare future professionals for technology‐integrated healthcare environments. Further research is recommended to explore long‐term impacts and scalability across diverse educational settings.
Purpose To examine whether aggregated unit‐level nurse burnout is associated with patient‐reported experience across hospital units using a multilevel framework, conceptualizing burnout as aggregated contextual strain rather than homogeneous unit climate. Methods A cross‐sectional multilevel study was conducted across 11 regional public hospitals in Albania (October 2024–July 2025). Nurse burnout was assessed using the Maslach Burnout Inventory among 2000 nurses, and patient experience was measured with HCAHPS among 679 patients. Burnout scores were aggregated at the clinical‐unit level. Multilevel linear modeling with patients nested within units examined associations between emotional exhaustion, depersonalization, personal accomplishment, and patient experience. Cluster‐robust standard errors and leave‐one‐unit‐out sensitivity analyses were conducted to assess estimate stability. Results Patient experience varied significantly between units (ICC = 0.229). In the multilevel model, higher unit‐level emotional exhaustion and depersonalization were both associated with lower patient experience. Under cluster‐robust estimation (t‐distribution, df = 9), depersonalization remained statistically significant (robust p < 0.001), and emotional exhaustion remained significant (robust p = 0.028), whereas personal accomplishment was not significant (robust p = 0.187). Leave‐one‐cluster‐out and exact wild‐cluster‐bootstrap sensitivity analyses confirmed depersonalization as the most robust association across all specifications (bootstrap p = 0.003), whereas emotional exhaustion, while directionally consistent, was only borderline under the most conservative correction (exact wild‐bootstrap p = 0.052), underscoring the statistical fragility inherent to a 10‐cluster design. Conclusion Aggregated unit‐level depersonalization, and to a lesser and more fragile extent emotional exhaustion, may be relevant to patient‐centered care, but the strength and consistency of these unit‐level estimates are constrained by the small number of analytical clusters and by heterogeneity in how those clusters were formed across hospitals. Given the modest number of clinical units, findings should be interpreted as exploratory contextual associations. These findings support further investigation of workload support and team‐level resources as potential targets for improving nurse well‐being and patient‐centered care.
Background Depressive symptoms are common among older adults with Type 2 diabetes mellitus (T2DM) and may be associated with both physical and psychological factors. However, the combined associations of comorbidity burden, sarcopenia risk, handgrip strength and diabetes distress with depressive symptom severity remain insufficiently examined. Objective To identify factors associated with depressive symptom scores among older adults with T2DM. Methods A cross‐sectional study using convenience sampling was conducted in a diabetes outpatient clinic in central Taiwan. A total of 170 older adults with T2DM were recruited. Measures included the Charlson comorbidity index, the Sarcopenia Functional Questionnaire, handgrip strength testing, the Diabetes Distress Scale and the Geriatric Depression Scale. Stepwise multiple linear regression was used to identify factors associated with depressive symptom scores. Results Depressive symptoms were present in 15.9% of participants. Stepwise multiple linear regression identified diabetes distress, high sarcopenia risk, low handgrip strength and comorbidity burden as significant factors associated with depressive symptom scores. The final model explained 69% of the variance in depressive symptom scores. Diabetes distress showed the strongest association ( β = 0.71, p < 0.001). Conclusion/Implications for Practice Diabetes distress, high sarcopenia risk, low handgrip strength and comorbidity burden were associated with depressive symptom severity among older adults with T2DM, with diabetes distress showing the strongest association. Routine assessment of diabetes distress, sarcopenia risk, muscle strength and comorbidity burden may help to identify individuals with more severe depressive symptoms and inform timely supportive care.
