Cristina Martinez Montes, Interaction Design and Software Engineering

Software engineers face unique circumstances that shape a specific work context distinct from many other professions. They experience frequent stress due to tight deadlines, heavy cognitive load demands and the constantly changing technology they work with. Hence, it is necessary to pay special attention to engineers’ well-being, stress management and resilience. General theories of well-being address several aspects that engineers face. However, due to their specific characteristics, these theories require adaptation to capture the distinct pressures and contextual demands of software engineering work. Moreover, current methodologies require refinement
through data triangulation and context-sensitive approaches. Single-source data often falls short in capturing the full experiences, perceptions, and context of engineers.
This thesis aimed to develop a software engineering well-being framework that considers the field’s unique circumstances. In addition, it sought to design, test and evaluate interventions targeting engineers’ well-being and stress management. Finally, it also investigated a suitable methodological approach that incorporates data triangulation to better capture the complexity of software engineering contexts.
Various empirical methodologies were employed, including interventions, quasi-experiments, experiments, and surveys. The data were analysed using thematic and content analysis for the qualitative data, and descriptive, frequentist, and Bayesian statistics for the quantitative data.
The main outcomes are: First, results provide a context-specific software engineering well-being framework. Second, we present tailored interventions targeting stress
and well-being, developed considering engineers’ unique circumstances. Third, we propose a data-triangulation approach for data collection and analysis. Finally, they introduce a framework for integrating AI into qualitative data analysis.
The thesis contributions advance the state of the art by offering a framework that explains factors influencing the well-being of software engineers. This framework also offers policy recommendations and interventions to enhance work environments that support well-being. Finally, we advance human factors research with our data triangulation proposal and a hybrid qualitative data analysis framework.