How do you measure happiness in a representative way? That is the premise of the research from PhD-candidate Renaud Gaucher (Erasmus School of Social and Behavioral Sciences). He proposes new ways to measure the quality of work life and developed a new indicator to measure happiness.
What is happiness? Many policymakers, psychologists, and scholars struggle to define this, let alone measure it in a representative way. In his PhD thesis, Renaud Gaucher from France studied new and innovative ways to measure well-being. For him, the best definition of happiness requires the French language: ‘Aimer la vie que l’on mène’, which translates to loving the life that one leads. “My main motivation to study happiness is my profound belief that a happier world is the best way to build a better world. We can apply knowledge from happiness studies to the real world and public policies"
Gaucher and his colleagues developed an indicator for public policies built on ultimate goals. Their starting point was the question: what is really important for us as an individual? “Answering this question allows us to distinguish between ultimate goals and the rest. It allows us to develop an indicator measuring the extent to which individuals experience a happy, long and sustainable life.”
"Studying well-being is the best way to reduce silent suffering and help us address the problems of groups that often go unheard in today's society."
This is a so-called ‘negative utilitarianist’ indicator, which means that for example, more weight is given to the people who suffer. Gaucher himself is also a convinced negative utilitarianist which means he believes it’s important to focus on reducing suffering, rather than on improving happiness. As one of his propositions says, studying well-being is the best way to ‘reduce silent suffering and help us address the problems of groups that often go unheard in today's society'.
In his thesis, he also analyzed existing questionnaires on the quality of work life. Gaucher sees that in order to analyze questionnaires in a reliable and replicable way, it is important to justify why each item is in a certain category. Not all questionnaires have a proper justification, he sees, which reduces the validity of the analyses. “Professor Veenhoven and I developed the quality of work life matrix. This matrix creates an overview of the existing qualities of work life, and this overview can be helpful to see and understand better how the quality of our work life can be conceptualized and measured.”
In another study, Gaucher presented a new measure that brings together mood at work and mood at home. When work life is measured, often only how one feels at work is taken into account. In his Dutch sample, this showed that the difference in the mood at work and mood at home was higher in the private sector compared to the public sector. The researcher sees that comparing the two situations brings valuable insights and should be added to job satisfaction research: “When an employee is happier at work than at home, this could be an incentive to overwork. The other way around, if he feels better at home, this could be an incentive to be disengaged at work.”
The researcher also proposed an adaptation to a well-known survey, the Day Reconstruction Method (DRM), towards a survey that focuses on the workday only (The Work Day Reconstruction Method). This is a questionnaire where people have to indicate how they feel at different episodes during the workday. The adaptation allows more detailed insight into the emotions of workers during their work day. He studies this among French sales representatives. “A funny detail is that they felt best during lunch. We French like to eat of course. They felt worst while doing administrative work and were happier with clients than with coworkers."
Still, Gaucher doesn’t believe in making generalizations about certain populations based on surveys. “This data is of one day and only applies to the people who filled in the survey. The best would be to ask all people to fill out the survey on one day.”