Building the Empirical Foundations of SEWL
THE RESEARCH PROGRAMME AT A GLANCE
The Systems Epidemiology of Working Life (SEWL) Research Programme translates the scientific framework into empirical, methodological, and comparative investigation.
Its central task is to make the explanatory propositions of SEWL scientifically testable. The programme measures Labour Systems and exposure-generating processes; characterises Working-Life Exposure Systems and exposure biographies; investigates their relationships with Biological Embodiment, population health, Human Functioning, Functional Sustainability, and inequalities. It also uses variation across Labour Systems and contexts to evaluate explanatory relationships and identify potentially modifiable leverage points for prevention.
The programme combines longitudinal and lifecourse epidemiology, comparative and multilevel research, causal inference and policy evaluation, exposure-system analysis, systems and network modelling, computational approaches, and measurement science. These approaches are supported by complementary population-level, occupational, administrative, biological, environmental, institutional, and multimodal data.
Research is explicitly iterative: empirical evidence is used not only to evaluate SEWL propositions, but to support, challenge, refine, revise, or potentially reject them as the science develops.
Research Programme Overview
The SEWL Research Programme operationalises the science through measurable constructs, testable propositions, appropriate research designs, and empirical evidence through which its explanatory relationships can be evaluated.
Scientific progress is inherently iterative. Questions guide conceptual development; concepts create measurement and methodological requirements; methods enable empirical investigation; findings evaluate explanatory propositions; and evidence generates new questions and opportunities for prevention.
Figure 10 presents a simplified overview of the iterative SEWL research cycle.
Figure 10
From Scientific Questions to Empirical Investigation
The fundamental scientific questions of SEWL define what the science seeks to explain. The Research Programme translates these questions into seven empirical operations through which its propositions can be measured, investigated, compared, evaluated, and refined.
Measure Labour Systems
Develop and validate comparable indicators of the institutional, economic, organisational, technological, regulatory, and social arrangements through which working life is organised, making Labour Systems measurable objects of epidemiological investigation.
Identify Exposure-Generating Processes
Identify and measure the processes through which Labour Systems generate and pattern exposures, protections, resources, opportunities, and constraints across working populations.
Characterise Working-Life Exposure Systems
Characterise multidomain exposure configurations and exposure biographies, including their co-occurrence, potential interaction, timing, duration, sequencing, transitions, and accumulation across working lives.
Investigate Biological Embodiment
Examine whether and through what biological processes working-life exposure histories become embodied over time, and how such embodiment relates to subsequent health and functional change.
Investigate Health and Functioning Trajectories
Investigate how Working-Life Exposure Systems and exposure biographies may contribute to longitudinal trajectories of population health, Human Functioning, Functional Sustainability, work ability, and related outcomes across the lifecourse.
Compare Systems, Populations, and Contexts
Use variation across Labour Systems, institutions, policies, organisations, occupations, and populations as empirical leverage to investigate whether and how differences in the organisation of working life are associated with differences in Working-Life Exposure Systems and subsequent health and functional trajectories.
Identify and Evaluate Leverage Points
Identify potentially modifiable exposure-generating processes and system characteristics, and evaluate whether changes in work organisation, occupational protection, labour policy, technological governance, or social protection alter Working-Life Exposure Systems and subsequent health and functioning.
Together, these operations test whether Labour-System characteristics, exposure-generating processes, Working-Life Exposure Systems, and exposure biographies provide explanatory value beyond established individual, occupational, socioeconomic, and contextual explanations.
Empirical Objects and Measurement
Empirical investigation of SEWL requires translating its principal constructs and explanatory relationships into measurable objects across populations, Labour Systems, and time. Measurement therefore extends beyond individual occupational exposures to encompass the principal components of the SEWL explanatory architecture and their population distribution.
Labour Systems
Labour Systems are operationalised through comparable indicators of employment relations, working time, occupational protection, worker representation, income security, social protection, technological governance, and related institutional characteristics, enabling investigation across populations, sectors, countries, and historical periods.
Exposure-Generating Processes
Exposure-generating processes are measured through employment arrangements, work organisation and scheduling, occupational protection, compensation and resources, technology, social protection, organisational governance, and worker participation. The aim is to determine how these processes vary across contexts and contribute to Working-Life Exposure Systems and exposure biographies.
Working-Life Exposure Systems and Exposure Biographies
Working-Life Exposure Systems describe multidomain configurations of exposures across working lives, distinguishing them from the upstream Labour Systems and exposure-generating processes through which those configurations arise. Measurement encompasses physical, chemical, biological, psychosocial, organisational, technological, behavioural, socioeconomic, and environmental exposures, including work-mediated nonwork exposures where these are generated, patterned, or amplified through working life.
SEWL investigates their co-occurrence and potential interaction, timing and duration, sequencing and transitions, cumulative burden, exposure-system phenotypes, and longitudinal exposure biographies. The objective is to characterise how these systems develop and change over time rather than treating exposure as a static snapshot. Exposure specificity is retained where needed for causal investigation and prevention.
Figure 11 presents a simplified overview of how Labour Systems operate through exposure-generating processes to generate and pattern multidomain Working-Life Exposure Systems and exposure biographies across working lives.
Figure 11
Biological Embodiment
Biological Embodiment is investigated by examining whether and through what biological processes working-life exposure histories influence physiological regulation and dysregulation, biological ageing, disease susceptibility, and subsequent health and functional change. Biological indicators are treated as measures of particular dimensions of embodiment rather than as equivalent to the broader process itself.
Human Functioning and Functional Sustainability
Human Functioning is investigated across physical, cognitive, psychological, social, and occupational dimensions and longitudinal trajectories of development, maintenance, decline, adaptation, and recovery. Functional Sustainability is investigated by examining the capacity to maintain, adapt, or recover functioning and participation over time. Related outcomes—including population health, work ability, disability, workforce participation, occupational transitions, and premature workforce exit—provide complementary indicators of health and functioning across the lifecourse.
Population Inequalities
Population inequalities are investigated as a cross-cutting property of the SEWL explanatory architecture, rather than solely as differences in outcomes between population groups. Research examines how Labour Systems and exposure-generating processes pattern and distribute exposures, protections, resources, opportunities, constraints, and Working-Life Exposure Systems across populations. It also investigates whether these processes may contribute to inequalities in health, Human Functioning, Functional Sustainability, and participation. The empirical objective is to identify where, how, and through which Labour-System characteristics and exposure-generating processes unequal exposure systems and exposure biographies are produced, reproduced, amplified, reduced, or potentially prevented.
Scientific Methods and Research Infrastructure
SEWL requires complementary methodological and empirical approaches capable of investigating multilevel systems, multidomain Working-Life Exposure Systems, longitudinal change, causal processes, and variation across Labour Systems and populations. Methods and data sources are selected and integrated according to the scientific question, level of explanation, and component of the SEWL architecture being investigated.
Methodological Toolkit
Comparative and Multilevel Epidemiology
Comparative and multilevel approaches investigate variation across individuals, workplaces, organisations, occupations, Labour Systems, countries, and institutional contexts, and how processes operating across these levels contribute to population patterns of exposure, health, and Human Functioning.
Causal Inference and Policy Evaluation
Causal and quasi-experimental approaches investigate hypothesised relationships and evaluate whether changes in work organisation, occupational protection, labour policy, social protection, technology, and other system characteristics alter Working-Life Exposure Systems and subsequent health and functional trajectories.
Lifecourse and Longitudinal Epidemiology
Longitudinal approaches investigate timing, duration, sequencing, transitions, accumulation, and change across working lives, supporting the reconstruction of exposure biographies and analysis of subsequent health and Human Functioning trajectories.
Exposure-System Analysis
Exposure-system approaches investigate multidomain exposure configurations, co-occurrence, potential interactions, dynamics, and accumulation across working lives, while retaining exposure-specific analyses needed for causal investigation and prevention.
Network and Systems Modelling
Network and systems approaches investigate interdependencies, dynamic relationships, feedback, system configurations, and potential leverage points, complemented by epidemiological methods appropriate to the scientific question and causal estimand.
AI, Machine Learning, and Computational Approaches
Computational approaches support high-dimensional exposure characterisation, phenotype identification, longitudinal pattern detection, multimodal data integration, prediction, and hypothesis generation. They are analytical tools—not substitutes for epidemiological reasoning, rigorous study design, causal identification, or external validation.
Measurement Science
Measurement science develops and validates indicators for constructs that remain difficult to capture with conventional occupational-health data, including Labour Systems, exposure-generating processes, Working-Life Exposure Systems and exposure biographies, Human Functioning, and Functional Sustainability, with emphasis on construct validity, comparability, longitudinal sensitivity, and reproducibility.
Figure 12 summarises the complementary methodological approaches that form the SEWL empirical toolkit.
Figure 12
Data and Research Infrastructure
The empirical development of SEWL draws on complementary and potentially linkable data sources that capture different levels and components of its explanatory architecture.
Longitudinal Cohorts and Population Studies
Repeated observations provide the temporal structure needed to investigate Working-Life Exposure Systems, exposure biographies, health transitions, ageing, and functional trajectories.
Occupational, Workplace, and Organisational Data
Data on occupations, tasks, working conditions, scheduling, employment arrangements, technologies, organisational practices, and workplace governance support measurement of exposure-generating processes and Working-Life Exposure Systems.
Administrative and Register Data
Employment histories, earnings, sickness absence, disability, healthcare use, occupational transitions, retirement, and related records enable large-scale longitudinal investigation of working-life histories, health and functioning, workforce participation, and occupational exit.
Biological and Functional Measurement
Biomarkers, physiological and clinical indicators, biological-ageing measures, and repeated functional assessments provide complementary measures of Biological Embodiment and trajectories of Human Functioning.
Sensors and Environmental Measurement
Wearable sensors, environmental monitoring, geospatial measures, and related technologies provide higher-resolution measurement of selected physical, environmental, behavioural, physiological, and temporal dimensions of working life.
Labour-System, Institutional, and Policy Data
Comparable indicators of employment regulation, working time, occupational protection, collective representation, income security, social protection, and technological governance enable Labour Systems to be investigated as measurable and comparable epidemiological objects.
Qualitative and Contextual Data
Qualitative and contextual evidence complements quantitative investigation by helping to characterise institutional and organisational processes, mechanisms, implementation, and lived experience across settings.
Linked Multilevel and Multimodal Data
Linkage across individual, occupational, organisational, institutional, environmental, and biological levels enables investigation of larger portions of the SEWL explanatory architecture than any single data source can capture.
The longer-term objective is to develop a distributed empirical infrastructure through which SEWL propositions can be investigated across datasets, Labour Systems, populations, and historical periods without dependence on any single cohort or research resource.
Figure 13 summarises the complementary data sources and research infrastructure supporting empirical investigation of SEWL.
Figure 13
The empirical value of SEWL ultimately depends on whether its explanatory propositions can be tested against evidence. Box 1 illustrates how several central propositions can be translated into empirical tests capable of supporting, refining, challenging, or potentially rejecting them.
Box 1
Current Empirical Priorities and Next-Generation Research
The current phase of the SEWL Research Programme focuses on strengthening its empirical and methodological foundations and developing the capabilities required for increasingly rigorous longitudinal, causal, biological, and comparative investigation.
Current Empirical Priorities
Labour-System Measurement
Develop and validate comparable indicators of Labour-System organisation across countries, populations, sectors, and historical periods, including employment relations, working time, occupational protection, worker representation, income security, social protection, and technological governance.
Working-Life Exposure Biographies
Develop and apply methods for reconstructing and analysing Working-Life Exposure Systems longitudinally through exposure biographies, and test whether these histories provide explanatory information beyond current, single-exposure, or conventional cumulative exposure measures.
Work-Structured Ageing
Investigate whether and how Working-Life Exposure Systems and exposure biographies contribute to heterogeneity in biological ageing, health and functional trajectories, work ability, and later-life participation, and which Labour-System conditions are associated with more favourable or more adverse trajectories.
Functional Sustainability Measurement
Develop and validate longitudinal measures distinguishing maintenance, adaptation, recovery, and erosion of Human Functioning and participation. Investigate how these trajectories relate to Working-Life Exposure Systems, exposure biographies, and changing Labour-System conditions.
Comparative Systems Epidemiology
Use variation across Labour Systems, policies, institutions, and populations to test SEWL propositions across contexts, while addressing compositional differences, measurement equivalence, policy endogeneity, correlated institutional arrangements, migration, occupational structure, and contextual confounding.
Biological Embodiment
Investigate whether and through what biological processes working-life exposure histories become embodied, and how such embodiment relates to subsequent health and Human Functioning.
AI and the Transformation of Working Life
Investigate how artificial intelligence, automation, algorithmic management, digitalisation, and related technologies reorganise exposure-generating processes and reshape Working-Life Exposure Systems across populations.
Next-Generation Research Capabilities
Advancing these priorities will require research designs and infrastructures that increase the temporal, causal, biological, measurement, and comparative resolution of SEWL research.
Purpose-Designed Prospective Studies
Develop prospective studies integrating repeated measures of Working-Life Exposure Systems and exposure biographies, biological processes, Human Functioning, and Labour-System conditions.
Natural Experiments and Policy Evaluation
Use changes in labour regulation, social protection, occupational policy, organisational practices, and technological systems to test whether upstream changes alter exposure-generating processes, Working-Life Exposure Systems, and subsequent health and functional trajectories.
Integrated Biological and Functional Measurement
Combine repeated biological and functional measures to investigate relationships among working-life exposure histories, Biological Embodiment, and trajectories of Human Functioning over time.
High-Resolution Multimodal Measurement
Integrate surveys, administrative and organisational data, sensors, environmental measures, biological indicators, and computationally derived measures to characterise working-life systems with greater temporal and multidimensional resolution.
International Harmonisation and Comparative Infrastructure
Develop harmonised constructs, measures, and data-linkage strategies enabling replicable comparisons and triangulation across Labour Systems, populations, datasets, and historical periods.
Together, these priorities and capabilities define the next empirical phase of SEWL: increasingly rigorous longitudinal, comparative, biological, and causal investigation of its central explanatory propositions.
From Research Programme to Research Portfolio
The SEWL Research Programme defines the empirical objects, methodological approaches, research infrastructure, and priorities through which the science is investigated and tested.
The Research Portfolio translates this programme into specific studies, research streams, occupational applications, collaborations, and scholarly outputs. No single study is expected to capture the entire SEWL explanatory architecture; evidence instead accumulates across complementary projects, populations, Labour Systems, methods, and levels of analysis.
research portfolio