Scholars have documented different work characteristics that are associated with employee outcomes such as burnout, depression, and well-being. These work characteristics, also known as job demands or resources, are crucial in explaining how specific work conditions impact an employee's well-being. However, the current approach to studying work characteristics focuses on individual components rather than capturing the entire employment situation.This fragmented approachis insufficient because individuals experience a variety of interdependent work characteristics and conditions that form an employment situation. Furthermore, current research has led to inconclusive findings due to the complex nature of employment that cannot be fully captured through the study of simple two-way interactions between component parts.

In this article, Haines, Ricardeau Registre and Guerrero affirm that work situation should be evaluated through the conceptual prism of "challenging" or "hindering", rather than limiting research to the interactions between a few of the many possible characteristics and conditions. Moreover, this approach takes research away from societal conversations about the integrated concepts of good and bad jobs.

The distinction between "good" and "bad" jobs is unclear when using work characteristics and conditions to define employment types.There is little theoretical agreement on the types of high- and low-quality jobs, and a precise definition of job quality is still lacking. Confusion is also apparent when nonstandard jobs are associated with bad employment even though some are not all that bad. Job satisfaction is sometimes viewed as an indicator of job quality and sometimes as an outcome of job quality. Therefore, a common template for the integrated study of employment quality remains elusive.

The main contribution of the study will be to present specific demands and resources as part of a system of work characteristics and conditions. Complex interactions will be captured through latent class analysis (LCA) with mixture modeling. This statistical methodology sorts individuals into classes based on their responses to a set of observed variables. This approach allows for a more comprehensive understanding of how work characteristics and conditions interact to affect employee well-being.

The current approach to studying work characteristics is insufficient in understanding how work relates to employee well-being. It is necessary to develop a more holistic and interactive view of work characteristics and conditions to capture the entire employment situation. The study seeks to contribute to this area of research by better characterizing the phenomenon of employment and validating this characterization in relation to employee health outcomes.