Innovation in measuring well-being

The study of well-being is aimed at contributing to greater well-being for a greater number of people. This study faces two main issues. One, there are various ways to define well-being. Well-being can be defined as an objective construct. In this vein, well-being is related to economic, social or ecological circumstances. Well-being can also be defined as a subjective construct. Here, well-being can be hedonic or eudaimonic and is based on personal appreciation of one’s own life. Well-being can also be defined as a hybrid concept, that is a mix of different approaches. Two, defining well-being well is not enough. Well-being has to be measured to be taken into account, and measuring well-being well can be difficult. When it comes to measuring well-being as a subjective construct, we need well-written items to fit the chosen construct, psychometrics to check the quality of the scale, and a reduction of the possible biases in respondents’ responses.
The goal of this dissertation was to improve the quality of research on the definition and measurement of well-being, with a focus on well-being as a subjective construct and well-being in the work setting.
In chapter 2, we suggest a simple, but relevant technique to help construct better indicators of well-being as objective and subjective constructs. This technique is to centre an indicator on the ultimate goals by using the question: What is really important to us as individuals? We used this technique to develop a new indicator, the indicator of a happy, long and sustainable life. This indicator is a negative utilitarianist indicator, this means that more weight is given to the people who suffer and those who die prematurely.
In chapter 3, we suggest a simple content analysis technique to use to select questionnaires on well-being in the work context and to improve the quality of the writing of items when one wants to develop a new questionnaire on this topic. We adapted Veenhoven’s matrices on quality of life and satisfaction to the work setting and called the matrix we obtained the quality of work life matrix, we developed rules to sort items into this matrix, we carefully read 246 items from 12 questionnaires, we sorted them into the matrix, and we gave a written justification of each sorting to allow other researchers to discuss our choices. The results obtained showed that some questionnaires do not cover their intended construct, and that our technique is useful to help researchers and practitioners write better questionnaires.
In chapter 4, we introduce a new scale that allows us to bring together hedonic and eudaimonic perspectives and adapt them to the work setting. The name of the scale is the Well-Being at Work Scale.
In chapter 5, we propose a new indicator that bridges well-being at work and well-being in general, the difference in mood at work and home. This indicator was calculated using a Day Reconstruction Method. We subtracted the weighted average of mood at home from the weighted average of mood at work. This technique allowed us to give a new view on well-being at work by taking into account well-being outside work. It also allowed us to reduce some cognitive biases as the indicator is a within-person comparison.
In chapter 6, we propose an adaptation of the Day Reconstruction Method and the U-Index to the work setting. We called this adaptation the Work Day Reconstruction Method. The main characteristics of this adaptation are the focus on a work day and work activities and the reduction in time spent to respond to a questionnaire. This adaptation could be hybridized with the Day Reconstruction Method to allow the Day Reconstruction Method to give more precise data. This adaptation also showed that it is possible to adapt the DRM to other contexts, for example school, to get more precise data on particular topics.
We hope that some of the advances proposed in this dissertation will be used to make the world a less bad or better place according to one’s perspective.