Natural environments are known to foster positive emotions and well-being, while Virtual Reality (VR) represents a powerful tool to explore such effects. This study investigates the restorative potential of virtual natural environments for emotional recovery, combining self-report and physiological measures. Fifty-two participants were divided into three Natural groups—formed spontaneously based on their preferred natural scenarios—and a Neutral group—exposed to a neutral scenario. The results reveal that virtual natural scenarios effectively restored positive emotions (valence) after exposure to arousing stimuli. Both neutral and natural scenarios reduced arousal, but the physiological data show higher activation in Natural groups. Interestingly, this activation was positively appraised, supporting emotional recovery. These findings confirm the restorative potential of VR nature, with nuanced arousal effects.

The management of natural hazard events has significant consequences for the well-being of the operators who find themselves intervening in these situations. In order to protect their mental health and ensure an effective response in support of the community, it is necessary to identify the factors that protect the well-being and resilience of operators and to exploit and enhance them. This rapid systematic literature review aims to detect and summarize evidence about protective factors of resilience and well-being among natural hazard events helpers; the literature was searched for on Scopus, Web of Science, Pub-med, and PsycINFO, resulting in 876 records. After a full-text screening, 84 records were selected to meet the inclusion criteria and examined in this paper. The results underline the variety of research methods and samples adopted by the included studies. Moreover, the results highlight the relevance of both the role of individual factors, such as personality aspects, coping strategies, and the level of exposure to the disaster/community, and the role of organizational/social factors, such as training, organizational issues and social support on the well-being and resilience of helpers. In conclusion, this rapid review indicates that the empowerment of helpers is an important source of resilience; it must be promoted inside the organization both at an individual and supportive level (through, for example, training on self-care strategies) and at a more organizational and social level, enhancing internal and team resources.

The adoption of artificial intelligence (AI) is reshaping organizational practices, yet workers’ attitudes remain crucial for its successful integration. This study examines how perceived organizational ethical culture, organizational innovativeness, and job performance influence workers’ attitudes towards AI. A survey was administered to 356 workers across diverse sectors, with analyses focusing on 154 participants who reported prior AI use. Measures included the Attitudes Towards Artificial Intelligence at Work (AAAW), Corporate Ethical Virtues (CEV), Inventory of Organizational Innovativeness (IOI), and an adapted version of the In-Role Behaviour Scale. Hierarchical regression analyses revealed that ethical culture dimensions, particularly Clarity and Feasibility, significantly predicted attitudes towards AI, such as anxiety and job insecurity, with Feasibility also associated with the attribution of human-like traits to AI. Supportability, reflecting a cooperative work environment, was linked to lower perceptions of AI human-likeness and adaptability. Among innovation dimensions, only Raising Projects, the active encouragement of employees’ ideas, was positively related to perceptions of AI adaptability, highlighting the importance of participatory innovation practices over abstract signals. Most importantly, perceived job performance improvements through AI predicted more positive attitudes, including greater perceived quality, utility, and reduced anxiety. Overall, this study contributes to the growing literature on AI in organizations by offering an exploratory yet integrative framework that captures the multifaceted nature of AI acceptance in the workplace.

This study contributes to the growing interest in evaluating environmental qualities and characteristics for the enhancement of social and individual well-being by introducing and validating the Landscape Assessment Scale (LAS), a standardized tool designed to assess key environmental qualities across both natural and urban landscapes within metropolitan settings. The scale comprises 30 items related to 10 key environmental components: coherence, complexity, ephemera, imageability, naturalness, safety, visual scale, stewardship, disturbance, and historicity of places. In study 1, the LAS was first tested on 327 participants, who evaluated either a natural (N = 176) or urban (N = 151) environment. Exploratory Factor Analysis (EFA) revealed three correlated factors: Landscape Disharmony, Landscape Organized Complexity, and Landscape Naturalistic Impact. In study 2, participants (N = 185) were asked to select and to assess two environments (natural and urban) using the shortened LAS and the Perceived Restorativeness Scale (PRS). A Confirmatory Factor Analysis (CFA) was used to investigate the invariance of the LAS factor structure in both natural and urban environments, and the correlational analysis was used to investigate LAS convergent validity. The CFA supported the three-factor structure and showed significant correlations between LAS and PRS components, supporting convergent validity. By capturing key perceptual dimensions that are relevant across landscape types, the LAS offers a practical and scientifically robust tool for informing evidence-based urban planning and landscape design.