This is an MIT Portugal flagship project in a consortium with academic and business partners. At a time of high prevalence of mental health disorders and high absenteeism, we are trying to place shopfloor workers at the centre of the research process to design digital technology that allows reconciling productivity, ergonomics and mental health. Here is a glimpse of the research process so far.

We began by qualitative and quantitative data collection during 4 weeks at the shopfloor of a garment factory. We interviewed 30 people, shadowed 12 and enrolled 10 operators as lead users for our participatory design process, who began by taking part in a paper diary study to understand whether they would find self-report easy and meaningful.

We then did free and systematic observations of operators’ work, seeking to understand their routines, their workspace arrangements, their priorities, the context where new pieces of technology can live and their perception of environmental comfort levels.

In a second round of interviews, we did an externalisation exercise to dig deeper into power dynamics and concerns. We showed operators an array of artefacts that can be found on the shopfloor and asked them to select artefacts to represent a set of 4 stakeholders in the company, after which they elaborated on the reasons for their choices. This was followed by a speculative scenario in which we simulated aggregated data about workers being visible per sector.

The qualitative data were analysed using Thematic Analysis which derived four themes. The themes, in turn, informed endpoints (what to measure with the new technology), how to design appropriate technology and how to appropriately engage with operators in a participatory design process.

We designed a wearable device for productivity and ergonomic risk assessment, a portable self-report device (to report Pain, Pressure and Social support), as well as an environmental sensor to collect data on temperature, illuminance, vibration and noise.

To visualise the data and establish relations between the different variables (e.g., peak in productivity — ergonomic risk — subjective wellbeing), we have created a dashboard where operators can see their personal data and decision makers can see aggregated data.