Keywords

1 Introduction

The European workforce is rapidly ageing. In 2030, workers aged 55–64 will make up 30% or more of the workforce in many countries, while the phenomenon of workforce shrinkage phenomenon is also evident with a decline of 0.4% every year between now and 2040 [1]. As a consequence, many governments are planning to raise the official retirement age, resulting in longer working lives with direct effects on the management of the workforce of companies. There is evidence that sustainable long-term employment can be associated with positive health outcomes if working conditions are appropriate [2, 3]. This is especially relevant in the case of industrial workplaces, as they appear to be increasingly dependent on the skills, knowledge, and experience of mature workers, and they must maintain the workability and employability of workers with adaptable working conditions. Industry 5.0 is booming to put workers at the core of the technological revolution initiated a decade ago by Industry 4.0, facilitating worker positioning to more complex activities such as abstraction and problem solving. Although Industry 4.0 could make an intelligent decision through real time communication and cooperation between manufacturing things thanks to Artificial Intelligence (AI) and the Internet of Things (IoT), Industry 5.0 introduces the principles of social fairness and sustainability in the digitalization and AI-driven technologies process initiated a decade ago, to highlights the importance of human and machines cooperation [4].

This new paradigm enables workers, and specially aged workers explore new opportunities for expanding their capabilities by the qualitative enrichment of their work, changing their role to supervision and solving unexpected problems, a position where the aged workers can find major benefits from the experiences and skills. However, fast-evolving labor conditions are also a source of daunting challenges for mature workers. They need from a friendly, flexible work arrangement in the work environment to help mature and experimented workers cope with their intrinsic and extrinsic body and life changes as years ago by and while working places introduce new workflows and technologies.

The combination of the digitalization process initiated during Industry 4.0, the vision of the human center of Industry 5.0, and the adaptation of industrial environments to occupational safety and health (OSH) practices enable the promotion of adaptable and sustainable working lives. Workability enhancing models suggest different actions and strategies to promote it at different levels [5, 6]. In the case of older workers, most of the proposed solutions recommend a stage model that addresses different dimensions of daily living of individuals that cover aspects such as health, competence and skills, and motivation, in the promotion of health at the core. In all of them, health promotion plays an essential role, but understanding the work adjustments needed to compensate for ageing-related functional changes. Redesigning work tasks according to the strengths, needs, and abilities of each individual is crucial to ensure the well-being, productivity, and workability of ageing workers, and an important success factor in successful ageing. Therefore, innovative models to promote better health and life expectancy in older workers are necessary to improve their opportunities to enhance their later life.

This paper analyses the collaborative design of a self-quantified dashboard to introduce improvements in worker well-being and self-track for task performance improvement and increase efficiency and productivity. This dashboard aims to lead to positive behavioural changes to maintain well-being at work and in private life, towards a successful ageing process, allowing workers to play an assisting role in workability and the successful transition to an active and healthy retirement.

2 The Design of the Self-quantified Dashboard

When designing human-centered solutions in an industrial environment, the individual worker point of view is central in the design and evaluation activities. New solutions should be designed to meet the real needs of workers while being meaningful and engaging with their daily work activities. Consequently, the medium- and long-term results of the proposed solution should have a positive impact on worker well-being, productivity, and workability.

Our aim is to design a dashboard that supports self-management of mental and physical wellness outcomes while aged workers are embedded in an adaptable intelligent working environment that supports them with different interventions that support the beneficial, productive, and safe ageing process. This dashboard aims to lead to positive behavioral changes to maintain well-being at work and in private life, towards a successful ageing process. The dashboard design aims to adapt the principles of the Quantified Self movement to the real needs of the aged industry workers to favour the engagement with the adaptation intervention proposed by their managers. Quantified self-movement refers to the practices of tracking and self-measurement of personal health data as a practise orientated toward self-improvement and healthy lifestyle routines [7].

The initial design involved aged workers from the beginning of the process. Focus groups were held with the participation of 16 employees from four different industrial settings in Spain and Germany, all over 50 years old. During the focus group the researchers participating in the session used a funnel approach (REF) to discover the workers daily routines, their needs regarding the ageing process and the possibility to include ICT to support them or to mitigate negative aspects of the work due to the ageing process. During this first process the unmet needs and requirements about ageing, workability and private life-work balance emerge.

Fig. 1.
figure 1

Main Barriers, Needs and requirements identified during the Focus Group Session

Full size image

Based on this initial identification of requirements, a hierarchical representation of goals, questions, and measurements discovered during the session with the workers were described using a GQM model [8], and based on this model, designers proposed a first visualization mockup of the dashboard. This first design included three aspects considered for a successful ageing process: physical, cognitive, and social/mental domains that were in alignment with the needs and requirements discovered during focus group sessions and organized in the GQM model. In this sense, the three domains were presented separately for the work environment and for private life. Following the approach proposed by Hall, the dashboards build on common and well-established self-tracking approaches. Based on the data automatically collected by worker personal devices (smartwatch and smartphone), feedback and environmental context awareness perform automatic detection of the worker’s behavior pattern and stimulates it to self- challenges and encourages him to achieve the goals.

Once the first mockup was designed, a set of collaborative workshops were performed. In these workshops, a variable number of age workers, designers, and technicians participated to iterative co-create the final version of the dashboard. In the workshops, the participants used the available mockup to highlight the important data, prioritize and link them, using a pre-attentive processing technique. Thanks to this, the participant was able to iteratively identify the graphical properties of each piece of information; hence, the mockup was refined and improved between workshops. In addition to the graphical representation, the participants discussed and selected self-quantified measures that better improve workers’ performance towards goal attainment.

During the workshop sessions, field notes were collected, while suggested changes were made to the prototype to continue discussion. After each of the workshop sessions, the notes were reviewed looking for common preferences among the participants, which were incorporated into the dashboard design, and it was used as a starting point for the next workshop session.

The emotional status of the worker plays a key role in the dashboard due to its influence in workability and private life. To avoid lack of participation or negative attitudes toward quantification of their roles due to the influence of emotional status, self-regulation techniques based on goal attributes were proposed to support self-qualified approaches. In this way, the individual worker proposed his/her own goals, allowing workers who set specific challenges to appreciate the qualified self-characteristics. This simple technical aspect has the potential to make workers perceive their change more positively and take greater benefits from it [9].

To implement this approach, a dedicated algorithm was designed and employed. This algorithm automatically monitors the level of achievement of each goal using the data gathered by smartphones and smartwatches mainly, but other sensors network available on the factory shopfloor could be also added, and according to the gathered data and the moment of the day, different motivational messages are sent to the users to encourage them to work harder or maintain this behaviour. Ideally, workers should achieve their challenges not only on the physical level, but also on the socialisation level, so motivational messages are aimed at balancing these life aspects. The rules on the delivery of motivational messages were discussed in the different co-creation sessions, with the aim of guaranteeing a fair and stimulating motivational system. In these, particularly, motivational messages always try to show positive aptitude.

The final version of the worker dashboard consists of 4 main sections presented below.

2.1 My Messages

This section aims to present notifications and messages to the user. This directly addresses the need for recall and awareness identified during the focus groups. Even this section is not really a graphical dashboard functionality, workers demanding the need of having a global view of those aspects that should be considered during the day, as well as reminders that contribute to the long-term positive habits acquisition. The section has the basic functionality of a mailing box, so they can manage the messages with the following features read, filter, and delete. Different types of messages are shown using different types of icons that have been chosen after research on the different types of information to be shown.

2.2 My Daily Habits and My Job

My daily habits and My job are the core sections of the dashboard, and they are interconnected, hence, workers can perceive the influence of their daily habits on their workability and on their private life. The emotional state of the worker plays a central role in this evaluation and follow-up. The graphical representation of the data shows a relative scale that aims to show the level of achievement of the personal goals. The graphic representation is supported by a colour scale that represents a low, medium, or high level of achievement, which also depends on the time of day. In this way, the level of achievement and motivational messages are adapted to the daily routine of the user. Additional textual information is provided to support the interpretation of the data and contribute to employee motivation and long-term positive habit acquisition.

In support of the self-quantified strategies adopted in the dashboard, a self-assessment questionnaire has been included in the My Job section. This questionnaire attempts to collect additional information from the user, in terms of stress, concentration, tiring after work, and pain during the workday, and allows dashboard algorithms and early detection of worker problems that can affect your workability or private life. The information of these variables is also presented in the form of a trend graph, supported by a three-colour scale (from red to green).

Finally, the dashboard presents a set of graphical information that supports workers with ergonomic assessment of the job position, hence preventing physical problems and work breaks, and prevent the detection of situations that cause stress, fatigue, and lack of concentration.

2.3 My Goals

The My Goals section is the core of the self-regulation theory implemented in the dashboard. Thanks to this section, workers can personalise their goals and better manage their daily habits. Additionally, goals are used to personalise the visual analytics and feedback messages that workers receive during the day according to their achievement of their goals (Fig. 2).

Fig. 2.
figure 2

Different versions of the My daily habits sections developed during the collaborative workshops

Full size image

3 Evaluation Results

User acceptance was measured using a self-developed acceptance questionnaire with the participation of real potential users. The questionnaire consisted of 11 items on the following dimensions: Perception of ease of use, perceived usefulness, intention of behavioral use, and self-efficacy. Items are rated using a 5-Likert scale (0, Extremely disagree-extremely agree). In addition, a common-based UTAUT questionnaire was also used. A total of 125 workers over 50 years participated in the evaluation.

Almost all participants perceived the system as useful for their daily tasks at work. The functionalities proposed in the dashboard were considered useful and covered the needs and barriers identified by the workers. Participants indicated their desire to use the system and they considered that they would not have significant learning problems using it properly.

The results (Table 1) also clarified some subjective statements. Feedback on the following items was particularly positive: (1) The tool was clear and easy to understand, (2) receiving recommendations through the tool would provide you useful measurements of your health (for example, your cardiac rhythm), and (3) you can use the tool if someone shows you how to do it first.

Table 1. Results of the acceptance questionnaire
Full size table

The UTAUT results (Fig. 1) show that the more positive domains were performance expectancy (the degree to which an individual believes that using a system will help achieve gains in job performance) and attitude (the person’s acceptance process) while the less positive domains were social influence (the degree to which others believes will affect someone to use the new system) and willing to pay (Confidence, commitment, and motivation to accomplish to acquire the solution) (Fig. 3).

Fig. 3.
figure 3

UTAUT questionnaire results

Full size image

4 Discussion

More than 200 participants, designers, developers, experts in labour health, and final users have participated in the co-creation process presented in this paper. As a result of this work, a dedicated dashboard has been successfully implemented to support and accompany aged workers in their ageing process, so that they can maintain their abilities and develop their potential. The results of the needs and requirement elicitation study show that older workers have positive intentions to use technological support that mitigates the impact of hard work conditions on their physical and emotional health and are willing to stay active as much as possible if they have good health conditions. The workers appreciated the increased sense of early detection of potential work issues that negatively affect both their workability and their health.

Close cooperation with aged workers gave us valuable insight into the discovery of the critical requirements for both the development and implementation of the dashboard, but also facilitates the development of current demographic change policies.

Workers indicated their willingness to use the system since the results improved the well-being even though there is little evidence of the technological development of older workers; this agrees with the finding from [10,11,12]. Furthermore, in this study, most of the 125 workers reported very good acceptance and high satisfaction in terms of usability. The influential role of improving the balance of private work on motivation, perception, and engagement with the proposed solutions emerged in worker interviews. In this sense, critical requirements are related to the adaptation of the working environment to normal functional decline. Early detection of physical and mental problems has the potential to alleviate factors that negatively impact the workability of these workers, contributing to increased job participation and successful retirement. In this sense, this work contributes directly to the research agenda proposed by [13], providing older workers with new assistive technology and new age-friendly workspaces.

One limitation of this study is that, even though the large number of real users involved during the whole process, especially at the last stage, during the usability assessment, it is a need to corroborate the good acceptance results with acceptability studies using the real setting pilot. The lack of this fully piloted implementation during this study allows only a purely descriptive evaluation of the tendencies and potential results. Therefore, the high number of real users during the whole process is sufficient to refine the dashboard design as an optimal process. Design procedures, made as user-centred design as possible, reduce failure risk due to acceptability or usability issues during a real-setting pilot. Aspects such as the impact on workability and well-being were not addressed in this first study. For this reason, a full pilot of the solution is planned, with the participation of more than 100 workers, to show the efficacy of the proposed dashboard in supporting the workability and well-being of the affected workers.

This study is the first milestone on the way to achieve successful intervention and technology support systems that have a positive influence on the successful ageing process of older workers before their retirement.

5 Conclusions

Due to demographic change, there is a need for greater participation of older adults in society. Policy developments in industrial countries incorporate work as a means to achieve this, but the practical implementation of these policies is required to be with the aim of improving the understanding of the aged works, daily routines, and accompany them in the ageing process, so they can maintain their abilities, developing their potential; this paper proposes the co-creation of a dashboard.

Drawing upon self-tracking devices, dashboards, and corporative dashboards used to monitor workability and productivity, this article uses conceptual and empirical techniques to guide the research and design work of technological tools supporting the workability and well-being of aged workers. The main contribution of this paper is the application of co-creation techniques to a more general understanding of the specific need of aged workers in workability and well-being supported tools.