Cases of dementia have increased significantly in recent years. The family represents the main cornerstone of assistance to the elderly suffering from dementia, in particular the caregiver. Family members who take on the role of caregiver are subjected to physical, psychological, emotional, social and financial stress, which can be conceptualised with the term “burden”. The aim of this study was to investigate which tools are best suited to measure the type of burden based on the type of dementia for each caregiver. A literature search was undertaken in MEDLINE, CINHAL and The Cochrane Database in September 2022, including articles from the last 20 years and using a combination of keywords and defined inclusion criteria. This literature review has been performed according to the PRISMA statement. From a total of 116 articles regarding the use of burden rating scales for caregivers, 18 scales were selected. The review provides a useful overview of burden assessment scales, classified into three categories, one-dimensional, multidimensional, or distinct concept with a subjective and objective component, in order to adopt appropriate strategies to assess caregiver burden and improve the quality of their health, both in the community and in hospitals. Indeed, the domestic context is the most studied as there is a greater risk of developing the burden of the caregiver: for this reason, some scales include the assessment of both the caregiver and the patient receiving treatment.

Background: Pain is often difficult to assess, particularly in non-communicative patients. While artificial intelligence (AI)-based objective Automatic Pain Assessment (APA) systems are a promising solution, their clinical implementation raises essential questions, primarily regarding clinician acceptance. Methods: We conducted a survey-to-consensus investigation on the feasibility and application of APA for clinical use. Firstly, the steering committee implemented the CHERRIES guidelines and designed a questionnaire for healthcare professionals. Given the survey results, 26 experts in pain medicine were asked to participate in a two-round consensus by rating 10 statements through a 7-point Likert scale. Consensus was defined as ≥ 75% agreement ("agree" or "completely agree"). For both phases, data was collected through online questionnaires and analyzed quantitatively. Results: For the survey, we collected responses from 628 healthcare professionals. The output highlighted excellent acceptance of the technology and a preference for multidimensional techniques. After two rounds, consensus was achieved on 8 out of 10 statements. Experts agreed on APA utility in supporting healthcare professionals and real-time pain monitoring. A strong consensus (96.2%) supported the need to inform patients about the use and limitations of AI systems. Adequate staff training is mandatory. Moreover, 92.3% agreed on the importance of implementing risk management, data quality control, and AI governance throughout the APA lifecycle. The experts stressed the need for internal and external validation processes and periodic updates, even for research purposes. Consensus was also reached about the importance of involving interdisciplinary stakeholders and addressing regulatory, ethical, and social implications. Multimodal inputs (e.g., physiological signals, facial expressions, speech, and clinical data) in APA systems are recommended. Additionally, APA systems should be capable of grading pain levels (e.g., via NRS), not just detecting the presence of pain. On the other hand, two statements did not reach consensus: the applicability of APA systems for acute and chronic pain conditions and their potential to improve therapeutic strategies. Conclusion: APA is viewed as a promising and potentially feasible technology for clinical pain assessment, particularly in vulnerable populations. Further research is needed to validate the dedicated tools, define applications in different clinical conditions (e.g., acute and chronic pain), and demonstrate their impact on routine clinical practice for pain management.

Background: The integration of artificial intelligence (AI) in healthcare has the potential to revolutionize clinical practice, particularly in the management of complex conditions such as fibromyalgia (FM). Despite its promise, the adoption of this technology in practice faces several challenges, including limited knowledge and preparedness among healthcare professionals. Aim: To evaluate the level of knowledge before and after a workshop on AI in FM among clinicians of different disciplines. Methods: A survey was conducted at the end of the lab. An anonymous 21-item questionnaire was administered to participants. Results: This survey (n=26) revealed that while most had extensive clinical experience and some prior exposure to AI, the majority lacked sufficient knowledge and felt unprepared to integrate AI into FM management. Post-congress, perceptions of AI improved for many, but significant barriers remained, including lack of training, resistance to change, and cost concerns. Key benefits identified were symptom monitoring and decision support. Targeted training and technical support were highlighted as essential for effective AI adoption in clinical practice. Conclusion: Despite a generally positive shift in perception following the congress, many doctors still feel unprepared and lack the necessary knowledge to effectively utilize AI tools. These results underscore the importance of targeted training and support to implement research and facilitate the integration of AI tools in FM and other clinical settings.

We conducted a bibliometrics analysis utilizing the Web of Science database, selecting 1925 articles concerning artificial intelligence (AI) in nursing. The analysis utilized the network visualization tool VOSviewer to explore global collaborations, highlighting prominent roles played by the United States, China, and Japan, as well as institutional partnerships involving Columbia University and Harvard Medical School. Keyword analysis identified prevalent themes and co-citation analysis highlighted influential journals. A notable increase in AI-related publications in nursing was observed over time, reflecting the growing interest in AI in nursing. However, high-quality clinical research and increased scientific collaboration are needed.

Background: Gamification is an innovative pedagogical strategy for improving learning outcomes, motivation, engagement, and knowledge retention. Nevertheless, evidence on the effectiveness of gamification remains heterogeneous. Methods: A systematic review was conducted. Searches were performed across PubMed/MEDLINE, CINAHL, PsycINFO, Scopus, Web of Science, Google Scholar, and grey literature (2010–2025). Eligible studies included quantitative, qualitative, and mixed-methods research involving undergraduate nursing students exposed to gamification interventions. Data extraction and quality assessment were independently performed using RoB-2, ROBINS-I, and JBI tools. Narrative synthesis was adopted due to the heterogeneity of interventions and outcome measures. Results: A total of 48 studies were included. Gamification strategies varied widely and included interactive quizzes, gamified flipped classroom models, serious games with explicit game elements, escape rooms, digital badges, and audience-response systems. For learning outcomes, most studies reported improvements in knowledge or performance, particularly when gamification included immediate feedback and repeated practice. While the knowledge retention was evaluated less frequently (12%), it was generally maintained or improved up to 2–4 weeks and across semester assessments. Strong positive trends of motivation and engagement were found across most studies, especially with competitive quizzes, missions, and narrative-based activities. Self-efficacy and satisfaction frequently improved, particularly in gamified simulations and team-based activities. Risk of bias was variable, with many quasi-experimental and descriptive studies limiting causal inference. Evidence certainty ranged from low to moderate according to GRADE criteria. Conclusions: Gamification is a promising educational approach in undergraduate nursing programs. Effects on long-term retention and practical skills remain less clear due to methodological variability and limited follow-up data. Future research focused on standardized outcome measures and longer follow-up intervals is required to consolidate evidence and guide educational policy. Protocol registered on PROSPERO (CRD420251117719).

Background/Aim: Chemotherapy-induced peripheral neuropathy (CIPN) is a common and disabling side-effect of various chemotherapeutic agents. This scoping review aimed to systematically map the existing literature on diagnostic methods used to identify, assess, and monitor CIPN. The review was guided by the research question: “What diagnostic methods have been used in the literature to identify, assess, or monitor chemotherapy-induced peripheral neuropathy in adult cancer patients?” Materials and Methods: We searched PubMed, Web of Science, Scopus, and the Cochrane Library from 2000 to 2024. Studies were included if they evaluated diagnostic methods for CIPN such as clinical assessments, patient-reported outcomes, biomarkers, neurophysiological tests, or digital tools. Data were extracted and narratively synthesized by diagnostic method type. The methodological quality of each included study was assessed using the Joanna Briggs Institute Critical Appraisal Tools. Results: Twenty-nine studies met the inclusion criteria. The most frequently used tools were patient-reported questionnaires, notably the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire – Chemotherapy-Induced Peripheral Neuropathy 20 (EORTC QLQ-CIPN20) and the National Cancer Institute Common Terminology Criteria for Adverse Events (NCI-CTCAE). Biomarkers such as neurofilament light chain and microRNAs, neurophysiological tests including nerve conduction studies, diffusion tensor imaging, functional magnetic resonance imaging, as well as digital technologies, such as mobile applications and wearable sensors, were also employed. Studies showed considerable heterogeneity in design, population, timing of assessments, and tool validation. Conclusion: Despite growing interest in multimodal approaches that integrate subjective and objective tools, a lack of standardization and validation limits the clinical applicability of many diagnostic methods. There is an urgent need to develop and validate reliable, reproducible, and feasible tools for the diagnosis and monitoring of CIPN in routine practice.