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To answer the question "How will technology change people's Home Care in the next 20 years?", a hybrid approach called Human-Centered Foresight was used. It allowed the multidisciplinary research team to define a road map with medium- and long-term goals from today until 2041.

Integrating collaborative robots in manufacturing, logistics, and agriculture: Expert perspectives on technical, safety, and human factors.

This study investigates the implementation of collaborative robots across three distinct industrial sectors: vehicle assembly, warehouse logistics, and agricultural operations. Through the SESTOSENSO project, an EU-funded initiative, we examined expert perspectives on human-robot collaboration using a mixed-methods approach. Data were collected from 31 technical experts across nine European countries through an online questionnaire combining qualitative assessments of specific use cases and quantitative measures of attitudes, trust, and safety perceptions.

How will technology change people's home care in the next 20 years? A strategic foresight study.

The rapid expansion of home health care has raised many unresolved issues and will have far-reaching consequences that can only be overcome with a holistic approach to help build and use collective intelligence in a structured, systemic way to anticipate developments. In this frame, the set of issues covered by the human factors research field will significantly impact the safety, quality, and effectiveness of home health care. However, only with a gaze of strategic foresight will we be capable of exploring, anticipating, and shaping the future.

Updating design guidelines for cognitive ergonomics in human-centred collaborative robotics applications: An expert survey.

Within the framework of Industry 5.0, human factors are essential for enhancing the work conditions and well-being of operators interacting with even more advanced and smart manufacturing systems and machines and increasing production performances. Nevertheless, cognitive ergonomics is often underestimated when implementing advanced industrial human-robot interaction.

Occupational safety in homecare organizations: the design and implementation of a train-the-trainer program.

Homecare workers face significant occupational risks, necessitating effective safety training programs. This paper presents a comprehensive Train-the-Trainer (TTT) program developed to enhance occupational safety in homecare organizations. Through an analysis of 229 reported safety events, the frequency and type of incidents, such as injuries during handling, road crashes, slips, trips, and falls, were identified and primarily attributed to human errors and violations.

Development and evaluation of design guidelines for cognitive ergonomics in human-robot collaborative assembly systems.

Industry 4.0 is the concept used to summarize the ongoing fourth industrial revolution, which is profoundly changing the manufacturing systems and business models all over the world. Collaborative robotics is one of the most promising technologies of Industry 4.

Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector.

Human reliability analysis (HRA) is a major concern for organizations. While various tools, methods, and instruments have been developed by the scientific community to assess human error probability, few of them actually consider human factors impact in their analysis. The active role that workers have in shaping their own performance should be taken into account in order to understand the causal factors that may lead to errors while performing a task and identifying which human factors may prevent errors from occurring.

Visual Scanning Techniques and Mental Workload of Helicopter Pilots During Simulated Flight.

The visual scanning techniques used by helicopter pilots are a critical skill to accomplish safe and correct landing. According to the human information processing theory, visual scanning techniques can be analyzed as a function of fixation location, number, and duration of fixations. This study assessed these techniques in expert and novice pilots during an open sea flight simulation in a low-workload condition, consisting of a daylight and good weather simulation, and in a high-workload condition of night-time, low visibility, and adverse weather conditions.

Gender differences in cyclists' crashes: an analysis of routinely recorded crash data.

Previous research on gender differences in road crashes has focussed uniquely on car drivers and there has been little research examining such differences among cyclists. In this study, we investigated gender differences in bicycle crashes, using routinely recorded crash data. The present paper focussed on characteristics related to the type of crashes (type of collision and opponent vehicle), the infrastructure (road type and type of road segment), the environmental (season, road surface condition and weather) and time period (time of the day and day of the week).

Green wave for cyclists: Users' perception and preferences.

Several innovative measures in traffic control applied in Europe have successfully improved the comfort and safety of cycling, among which is the green waves for cyclists. Consecutive traffic lights are synchronised to create a green wave, increasing comfort and decreasing waiting times and related deliberate red-light running. This study focused on exploring the user acceptance of green wave systems and the user evaluation of six distinct interface designs (i.

Red-light running behavior of cyclists in Italy: An observational study.

Accident analysis and studies on traffic revealed that cyclists' violation of red-light regulation is a typical infringement committed by cyclists. Furthermore, an association between cyclists' crash involvement and red-light violations has been found across different countries. The literature on red-light running cyclists' behavior in relation to their characteristic is still scarce.

Cyclists' Anger As Determinant of Near Misses Involving Different Road Users.

Road anger constitutes one of the determinant factors related to safety outcomes (e.g., accidents, near misses).

Unsafe cycling behaviours and near crashes among Italian cyclists.

This study investigates the direct and indirect effect of three types of unsafe behaviours (i.e. errors, generic violations and smartphone-specific violations) on the likelihood of near crashes and actual crashes among Italian cyclists.

Using data mining techniques to predict the severity of bicycle crashes.

To investigate the factors predicting severity of bicycle crashes in Italy, we used an observational study of official statistics. We applied two of the most widely used data mining techniques, CHAID decision tree technique and Bayesian network analysis. We used data provided by the Italian National Institute of Statistics on road crashes that occurred on the Italian road network during the period ranging from 2011 to 2013.

Characteristics of cyclist crashes in Italy using latent class analysis and association rule mining.

The factors associated with severity of the bicycle crashes may differ across different bicycle crash patterns. Therefore, it is important to identify distinct bicycle crash patterns with homogeneous attributes. The current study aimed at identifying subgroups of bicycle crashes in Italy and analyzing separately the different bicycle crash types.

Social Influence and Different Types of Red-Light Behaviors among Cyclists.

Accident analysis and studies on traffic revealed that cyclists' violation of red-light regulation is one typical infringement committed by cyclists. Furthermore, an association between cyclists' crash involvement and red-light violations has been found across different countries. The literature on cyclists' psychosocial determinants of red-light violation is still scarce.