Innovations in nurse education: creating the multisensory learning approach of The WISE Room.

BACKGROUND: Nursing students often face anxiety and cognitive overload, leading to high attrition rates; meanwhile, traditional pastoral interventions have proved insufficient. A novel, digitally enhanced learning environment named The Wellbeing in Student Education (WISE) Room, was introduced as an alternative at a UK university. AIMS: This study investigated the impact of The WISE Room, a 4m × 4m digital platform containing touch-interactive walls, co-created with students and academic staff, designed to promote insight through immersive experiences beyond traditional learning settings. METHODS: A mixed-methods approach was adopted, collecting data from nursing students, healthcare staff and academic faculty. Data were collected at three stages, each corresponding with the iterative development of The WISE Room, including an evaluation of the intervention. RESULTS: Feedback from 240 participants was positive. In Phase 2 of the study, 93% of the 79 students and 21 staff who visited the room and completed a survey were satisfied with the room's suitability in three key areas: emotional wellbeing, academic readiness, and placement preparedness. CONCLUSION: The WISE Room has proved effective in supporting nursing students' wellbeing, and educational and placement preparation requirements. Its multisensory, digital and experiential nature is beneficial for students throughout their learner journey. Additional trials and content development will be required to enhance the learning and teaching experience further.

RePAIRing the student nurse journey: empowering interrupted students through innovative support strategies.

This article reports on a study that evaluated an innovative 6-week summer returners' programme, part of the Health Education England RePAIR project, designed to support nursing students who have interrupted their studies. Held from May to July 2022, the programme addressed diverse needs through academic guidance, mental health and resilience workshops, creative arts, professional identity development, and practical nursing skills training. The programme ran alongside support from the programme team, student engagement services, and ongoing communication via phone and email. Despite non-mandatory sessions leading to varying attendance, the combined efforts facilitated the return of 67 out of 135 interrupted students. Thematic analysis identified four key themes: anticipation and fear, making contact and reaching out, preparing for return, and psychological wellbeing. The programme's effectiveness underscores the necessity of tailored support strategies to enhance retention and wellbeing. This innovative approach highlights the importance of personalised support in aiding nursing students' return to education and addressing nursing workforce shortages.

Rheumatic?-A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study.

Introduction: Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a risk score for several rheumatic diseases. We ran a pilot study retrospectively testing Rheumatic? for its ability to differentiate symptoms from existing or emerging immune-mediated rheumatic diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics. Materials and Methods: The performance of Rheumatic? was tested using in three university rheumatology centers: (A) patients at Risk for RA (Karolinska Institutet, n = 50 individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity) (B) patients with early joint swelling [dataset B (Erlangen) n = 52]. (C) Patients with early arthritis where the clinician considered it likely to be of auto-immune origin [dataset C (Leiden) n = 73]. In dataset A we tested whether Rheumatic? could predict the development of arthritis. In dataset B and C we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic diseases. We examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC). Next, we calculated the test characteristics for these patients passing the first or second expert-based Rheumatic? scoring threshold. Results: The total test scores differentiated between: (A) Individuals developing arthritis or not, median 245 vs. 163, P < 0.0001, AUC-ROC = 75.3; (B) patients with an immune-mediated arthritic disease or not median 191 vs. 107, P < 0.0001, AUC-ROC = 79.0; but less patients with an immune-mediated arthritic disease or not amongst those where the clinician already considered an immune mediated disease most likely (median 262 vs. 212, P < 0.0001, AUC-ROC = 53.6). Threshold-1 (advising to visit primary care doctor) was highly specific in dataset A and B (0.72, 0.87, and 0.23, respectively) and sensitive (0.67, 0.61, and 0.67). Threshold-2 (advising to visit rheumatologic care) was very specific in all three centers but not very sensitive: specificity of 1.0, 0.96, and 0.91, sensitivity 0.05, 0.07, 0.14 in dataset A, B, and C, respectively. Conclusion: Rheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. The current scoring system needs to be further optimized.

Toward Earlier Diagnosis Using Combined eHealth Tools in Rheumatology: The Joint Pain Assessment Scoring Tool (JPAST) Project.

Outcomes of patients with inflammatory rheumatic diseases have significantly improved over the last three decades, mainly due to therapeutic innovations, more timely treatment, and a recognition of the need to monitor response to treatment and to titrate treatments accordingly. Diagnostic delay remains a major challenge for all stakeholders. The combination of electronic health (eHealth) and serologic and genetic markers holds great promise to improve the current management of patients with inflammatory rheumatic diseases by speeding up access to appropriate care. The Joint Pain Assessment Scoring Tool (JPAST) project, funded by the European Union (EU) European Institute of Innovation and Technology (EIT) Health program, is a unique European project aiming to enable and accelerate personalized precision medicine for early treatment in rheumatology, ultimately also enabling prevention. The aim of the project is to facilitate these goals while at the same time, reducing cost for society and patients.