Valeria Habib

The agri-food supply chain is a relevant contributor to the Italian economy but shows a high incidence of occupational injuries and musculoskeletal disorders, such as lower back pain. Repetitive manual handling and biomechanical overload highlight the need for a prevention-oriented, system-level assessment. This protocol aims to implement a harmonized One Health approach procedure for the multidimensional evaluation of food supply chain workers in real-world settings. The protocol integrates bioelectrical impedance vector analysis (BIVA), nutritional parameters, quality-of-life and psychological measures, and assessments of systemic oxidative stress and systemic serotonin levels. Data from active workers will be compared with those from sedentary individuals. The study will evaluate whether BIVA profiles differ between these groups and examine how the additional indicators contribute to a multidimensional well-being framework. By operationalizing an integrated One Health approach that bridges nutritional, psychological, and biomarker domains, this protocol is designed to guide targeted preventive and educational strategies and inform evidence-based occupational and public health policies across the food supply chain. Trial registration: NCT06896877 (ClinicalTrials.gov), 26 March 2025.

Background: Body representation is a complex process involving sensory, motor, and cognitive information. Frequently, it is disrupted after a stroke, impairing rehabilitation, emotional functioning, and daily functioning. The human figure graphic representation has emerged as a holistic tool to assess post-stroke outcomes. Objectives: This systematic review examines the methodologies of human figure representation tests and their application in assessing post-stroke body representation, emphasizing its role in bridging subjective patient experiences with objective metrics. Methods: This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A literature search was conducted through the databases PubMed, Scopus, Embase, Web of Science, and Google Scholar, collecting publications eligible for qualitative analysis. We selected studies where patients drew human figures in the study design to assess body representation, involving exclusively the adult stroke population. The Newcastle–Ottawa Scale was used to assess the risk of bias. Results: Ten studies were analyzed. The tool demonstrated versatility in capturing unilateral spatial neglect, emotional disturbances, and functional independence. Qualitative metrics and quantitative indices correlated with cognitive deficits, mood disorders, and activities of daily living. Human figure representation also predicted rehabilitation outcomes, with improvements aligning with motor recovery. Innovations included digital quantification of evaluation metrics. Conclusions: Human figure graphic representation is a low-cost, adaptable tool bridging motor, cognitive, and emotional assessments in stroke survivors. While methodological variability persists, AI-driven analytics and standardized frameworks could enhance objectivity. Future research should prioritize validating parameters and developing hybrid models combining traditional qualitative insights with machine learning, thus advancing precision neurorehabilitation and personalized care.

Background/Objectives: Robotic rehabilitation holds great potential for improving patient outcomes, but the integration of these technologies into clinical practice is hindered by a lack of comprehensive tools for assessing patients’ needs. This systematic review aimed to identify gaps in the current literature, with a focus on methodologies and tools for evaluating such needs, particularly those based on the International Classification of Functioning, Disability, and Health (ICF) framework. Methods: A systematic review of qualitative studies published between 2021 and 2023 was conducted, updating a previous (2020) review. Studies were identified through PubMed, Scopus, and Web of Science using inclusion criteria focused on qualitative methods capturing patients’ experiences with robotic and technological rehabilitation devices. Results: The review analyzed 19 new studies and 20 from the prior review, revealing a reliance on semi-structured interviews targeting small, heterogeneous populations. No studies employed standardized ICF-based tools, and gaps were noted in the exploration of conditions such as Parkinson’s disease, frailty, or conditions that allowed for multi-device experiences. Conclusions: The findings emphasize the necessity for tailored surveys grounded in the ICF framework to completely evaluate the needs of patients suffering from sensory, motor, and/or cognitive disorders caused by different health conditions. This work lays the foundation for more inclusive, effective, and patient-centered robotic rehabilitation strategies.