From Stress to Strength: Well-Being and Resilience in Software Engineering
Doctoral thesis, 2026
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.
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.
Resilience
Stress
Human Factors
Software Engineers
Well-being
Author
Cristina Martinez Montes
Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering
The Factors Influencing Well-Being in Software Engineers: A Mixed-Method Study
ACM Transactions on Software Engineering and Methodology,;Vol. In Press(2025)
Journal article
Emotional Strain and Frustration in LLM Interactions in Software Engineering
Proceedings of the 29th International Conference on Evaluation and Assessment in Software Engineering (EASE 2025),;(2025)p. 193-204
Paper in proceeding
Take a deep breath: Benefits of neuroplasticity practices for software developers and computer workers in a family of experiments
Empirical Software Engineering,;Vol. 27(2022)
Journal article
Evaluating the Impact of a Yoga-Based Intervention on Software Engineers' Well-Being
Proceedings of the 29th International Conference on Evaluation and Assessment in Soware Engineering (EASE),;(2025)p. 227-237
Paper in proceeding
Cristina Martinez Montes, Daniela Grassi, Nicole Novielli, Birgit Penzenstadler. A Multimodal Approach Combining Biometrics and Self-Report Instruments for Monitoring Stress in Programming: Methodological Insights
Cristina Martinez Montes, Robert Feldt, Cristina Miguel Martos, Sofia Ouhbi, Shweta Premanandan, Daniel Graziotin. Large Language Models in Thematic Analysis: Prompt Engineering, Evaluation, and Guidelines for Qualitative Software Engineering Research
Software engineers build the digital systems that shape modern life, yet their own well-being is often pushed to the background. Tight deadlines, constant interruptions, rapidly changing technologies, and the growing use of AI tools place engineers under significant stress.
This thesis aimed to explain why engineers feel overwhelmed, motivated, frustrated, or resilient by looking at the systems they work in. To do so, we listened to engineers describe their daily experiences, measured stress using questionnaires and physiological signals, examined how new tools, such as large language models, affect emotions, and tested practical interventions, such as breathing exercises and yoga.
The results show that stress in software engineering is frequently subtle and cumulative, sometimes invisible to the person experiencing it. The findings also call for organisations to design humane work practices, for tools that respect human limits, and for research methods that capture what people feel and how they make sense of their experiences. By combining psychology, software engineering, and data-driven methods, this thesis seeks to help turn stress into something manageable for the people who build our digital world.
This thesis aimed to explain why engineers feel overwhelmed, motivated, frustrated, or resilient by looking at the systems they work in. To do so, we listened to engineers describe their daily experiences, measured stress using questionnaires and physiological signals, examined how new tools, such as large language models, affect emotions, and tested practical interventions, such as breathing exercises and yoga.
The results show that stress in software engineering is frequently subtle and cumulative, sometimes invisible to the person experiencing it. The findings also call for organisations to design humane work practices, for tools that respect human limits, and for research methods that capture what people feel and how they make sense of their experiences. By combining psychology, software engineering, and data-driven methods, this thesis seeks to help turn stress into something manageable for the people who build our digital world.
Subject Categories (SSIF 2025)
Other Engineering and Technologies
DOI
10.63959/chalmers.dt/5825
ISBN
978-91-8103-368-7
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5825
Publisher
Chalmers
Kuggen Gradängen
Opponent: Dr. Emitza Guzman Ortega, Vrije Universiteit, Amsterdam, the Netherlands