Light enables us to see and perceive our environment but it also initiates effects beyond vision, such as alertness. Literature describes that at least six factors are relevant for initiating effects beyond vision. The exact relationship between these factors and alertness is not yet fully understood. In the current field study, personal lighting conditions of 62 Dutch office workers (aged 49.7 ± 11.4 years) were continuously measured and simultaneously self-reported activities and locations during the day were gathered via diaries. Each office worker participated 10 working days in spring 2017. Personal lighting conditions were interpreted based on four of the six factors (light quantity, spectrum, timing, and duration of light exposure). Large individual differences were found for the daily luminous exposures, illuminances, correlated colour temperatures, and irradiances measured with the blue sensor area of the dosimeter. The average illuminance (over all participants and all days) over the course of the day peaked three times. The analysis of the duration of light exposure demonstrated that the participants were on average only exposed to an illuminance above 1000 lx for 72 minutes per day. The interpretation of personal lighting conditions based on the four factors provides essential information since all of these factors may be relevant for initiating effects beyond vision. The findings in the current paper give first in-depth insight in the possibilities to interpret personal lighting conditions of office workers.
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Health symptoms may be influenced, supported, or even controlled via a lighting control system which includes personal lighting conditions and personal factors (health characteristics). In order to be effective, this lighting control system requires both continuous information on the lighting and health conditions at the individual level. A new practical method to determine these continuous personal lighting conditions has been developed: location-bound estimations (LBE). This method was validated in the field in two case studies; comparisons were made between the LBE and location-bound measurements (LBM) in case study 1 and between the LBE and person-bound measurements (PBM) in case study 2. Overall, the relative deviation between the LBE and LBM was less than 15%, whereas the relative deviation between the LBE and PBM was 32.9% in the best-case situation. The relative deviation depends on inaccuracies in both methods (i.e., LBE and PBM) and needs further research. Adding more input parameters to the predictive model (LBE) will improve the accuracy of the LBE. The proposed first approach of the LBE is not without limitations; however, it is expected that this practical method will be a pragmatic approach of inserting personal lighting conditions into lighting control systems.
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Sensors in offices mainly measure environmental data, missing qualitative insights into office workers’ perceptions. This opens the opportunity for active individual participation in data collection. To promote reflection on office well-being while overcoming experience sampling challenges in terms of privacy, notification, and display overload, and in-the-moment data collection, we developed Click-IO. Click-IO is a tangible, privacy-sensitive, mobile experience sampling tool that collects contextual information. We evaluated Click-IO for 20-days. The system enabled real-time reflections for office workers, promoting self-awareness of their environment and well-being. Its non-digital design ensured privacy-sensitive feedback collection, while its mobility facilitated in-the-moment feedback. Based on our findings, we identify design recommendations for the evelopment of mobile experience sampling tools. Moreover, the integration of contextual data with environmental sensor data presented a more comprehensive understanding of individuals’ experiences. This research contributes to the development of experience sampling tools and sensor integration for understanding office well-being.
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Many companies struggle with their workplace strategy and corporate real-estate strategy, especially when they have a high percentage of knowledge workers. How to balance employee satisfaction and productivity with the cost of offices.This project focused on developing methods and tools to design customer journeys and predict the impact of investments and changes on user satisfaction with the work environment. The tools, including a game and simulation tool, allowed to focus on the needs of particular subgroups of employees while at the same time keeping an overview on the satisfaction and perceived productivity of all employees and guests. We applied Quality Function Deployment techniques to understand how needs of different types of users of (activity-based) office environments can catered for in smart customer-centric office design.
The Healthy Workplace monitor is being developed to monitor the health and well-being of knowledge workers in relation to the office space and their home workplace. Since the corona period, a lot has changed in the way knowledge workers work. Both offices and employees require more flexibility to carry out work in an efficient but also healthy and enjoyable way. It is important to identify office workers needs with regard to workspaces at the office and at home from a holistic view, in which mental , physical and social aspects play a role. A vital, happy employee is a productive employee.
Movebite aims to combat the issue of sedentary behavior prevalent among office workers. A recent report of the Nederlandse Sportraad reveal a concerning trend of increased sitting time among Dutch employees, leading to a myriad of musculoskeletal discomforts and significant health costs for employers due to increased sick leave. Recognizing the critical importance of addressing prolonged sitting in the workplace, Movebite has developed an innovative concept leveraging cutting-edge technology to provide a solution. The Movebite app seamlessly integrates into workplace platforms such as Microsoft Teams and Slack, offering a user-friendly interface to incorporate movement into their daily routines. Through scalable AI coaching and real-time movement feedback, Movebite assists individuals in scheduling and implementing active micro-breaks throughout the workday, thereby mitigating the adverse effects of sedentary behavior. In collaboration with the Avans research group Equal Chance on Healthy Choices, Movebite conducts user-centered testing to refine its offerings and ensure maximum efficacy. This includes testing initiatives at sports events, where the diverse crowd provides invaluable feedback to fine-tune the app's features and user experience. The testing process encompasses both quantitative and qualitative approaches based on the Health Belief Model. Through digital questionnaires, Movebite aims to gauge users' perceptions of sitting as a health threat and the potential benefits of using the app to alleviate associated risks. Additionally, semi-structured interviews delve deeper into user experiences, providing qualitative insights into the app's usability, look, and feel. By this, Movebite aims to not only understand the factors influencing adoption but also to tailor its interventions effectively. Ultimately, the goal is to create an environment encouraging individuals to embrace physical activity in small, manageable increments, thereby fostering long-term engagement promoting overall well-being.Through continuous innovation and collaboration with research partners, Movebite remains committed to empowering individuals to lead healthier, more active lifestyles, one micro-break at a time.
