Theo Bodin

This project investigates the role of Artificial Intelligence in future-proofing long-term care (LTC). The sector faces multiple challenges: an ageing population, limited productivity gains in a labour-intensive sector, labour shortages, and the crisis of traditional modes of care provision amid rising female employment rates. This project explores AI’s potential to help the sector respond to long-standing and growing workforce challenges, improve its value proposition and care quality. We will inform industry standards, care models, and share best practices to inform viable and high-quality care solutions.The project focus is on algorithmic management (AM) as an element of AI and its effects on job & care quality. AM may alter the dynamics of the manager-worker-care recipient. However, existing literature rarely engages systematically with the job quality-AM/AI nexus. By offering a research study that compares five countries’ (Austria, Belgium, Sweden, Spain and the UK) this project will systematically investigate efforts to address issues affecting the sustainability of LTC. A key research focus is to explore the challenges and potential of AM/AI to (i) address recruitment & retention challenges through enhancing working conditions and (ii) improve care quality with potentially better outcomes for workers, care recipients and their families, using company case studies in three subsectors within LTC. Special attention will be paid to certain dimensions of job quality relevant to AM/AI: intrinsic elements (OH&S, work intensification, surveillance, consultative rights, and voice) and extrinsic elements (wages, working hours, benefits, employment conditions, skills).Empirically, the project will strengthen the LTC and job quality literature by exploring the less researched role of how public and private care providers across LTC regimes have embraced AM/AI. It will advance the understanding of the effects of deploying AM/AI at workplace level to shed light on the dynamics between AM and job quality within LTC. Theoretically, it will extend the job quality and LTC literature by refining and reframing present job indicators in the context of AM/AI with the aim to develop viable solutions to address labour shortage challenges. On the societal level the project contribute to national & EU policy agendas on the digital transformation of care work.

The project aims to improve the quality and accessibility of Swedish occupational data to support labor market and occupational health research. By developing and publishing open-access code libraries, translation keys, and tools on GitHub, we strive to lower the entry barriers for new researchers, reduce the risk of incorrect handling of variables, and improve comparability between research projects. We will use machine learning to impute missing or incorrect occupational codes in historical data. The project is closely linked to the Laborocto network, a collection of eight ongoing Forte program grants, and involves collaboration with Statistics Sweden (SCB) and other academic networks to ensure that the developed resources are relevant and useful. By enhancing occupational data, we can support better analysis of labor market developments and their impacts on society and individuals. The results are expected to benefit not only researchers but also policymakers and other stakeholders who use these data to make well-informed decisions.

For decades, JEMs have been used to classify occupational exposures in large scale epidemiological studies, where the study participants were too many to be able to carry out individual exposure measurements, or where exposure backwards in time had to be assessed. With a Job Exposure Matrix (JEM), one can assess the exposure of several different occupational exposures in a cohort or registry study, using only an occupational code and knowledge of the time period of the exposure. SweJEM is a Swedish infrastructure that contains JEMs for chemicals, particles, metals, noise, vibrations, physical (ergonomic) strain, psychosocial working conditions, and low employment quality. SweJEM was launched externally in autumn 2023, https://ki.se/imm/swejem and JEMs has since then been sent out to research groups around the country. In addition, the JEMs have formed the basis for regions and authorities´ risk assessment of the work environment. Already during the development phase, it has followed exposure trends in over time in Sweden and have evaluated occupational exposures during pregnancy and health effects in the mother and child as well as occupational exposures in relation to our most common public diseases such as cardiovascular disease and cancer. The first version of this unique national infrastructure now needs further development to become more detailed and more comprehensive than before. To achieve this, we need funds to collect new data from workplaces in Sweden. New data increases the relevance of the infrastructure by adding new later years of exposure, as well as improving the exposure history going back in time. In addition, we want to receive data from different types of employers, in order to e.g. be able to observe difference in exposure between large and small companies or for different demographic groups so that we can study differences in exposure patterns between men and women and between different age groups. Right now, this is only covered in parts of SweJEM. Finally, we also want to collect new occupational exposures such as UV-light, heat and cold in order to better cover the climate changes that affect the working environment. The aim is to keep the relevance of the infrastructure so that research groups, occupational and environmental medicine clinics, regions, occupational health care and authorities around Sweden can have access to the best possible exposure classification.

Research Problem and Specific Questions: This comprehensive study investigates the differential impacts of adverse life events on labor market trajectories and health outcomes between standard and non-standard employees in Sweden. The research aims to address two pivotal questions: First, how do adverse life events affect the labor market and health trajectories of these two groups? Second, how do non-standard workers cope with such events, particularly in terms of support from welfare and social security systems?Data and Method: The study utilizes a robust dataset encompassing approximately 5.4 million individuals aged 16-64 registered in Sweden from 2005 to 2022, integrating key administrative and healthcare registers. This includes the Total Population Register, Multi-generation Register (MGR), LISA, and others. The study comprises three work packages: a quantitative analysis using longitudinal methods and Cox Proportional Hazards Model to assess labor market outcomes and mortality risks

a qualitative analysis of interviews with non-standard employees focusing on personal experiences and coping strategies

and the development of a policy handbook informed by both quantitative and qualitative findings.Societal Relevance and Utilisation: This research is highly relevant in understanding the complexities of non-standard employment and its impact on individuals´ lives, especially during adverse events. Insights from this study will inform policy makers, government agencies and labor organizations, about the unique challenges faced by non-standard employees, guiding them to develop more inclusive and supportive policies and practices.Plan for Project Realisation: Ethics and most of the data is already in place, building on previous successful projects. The project will be executed in three phases: quantitative analysis of registry data, qualitative analysis of interviews, and synthesis of findings into a comprehensive policy handbook. The handbook will be reviewed by stakeholders and disseminated widely to maximize impact. The project builds on previous successful policy dialogues and aims to enhance the support and reduce the vulnerability of non-standard employees through informed policy-making and practices.

Algorithms are changing the World of Work: from the tasks that consitute work to how it is organised and governed. Lack of data and knowledge about the impacts of algorithmic management (AM) on work and workers pose a societal challenge today. This deficit is particularly pronounced outside of platform work - in economic sectors where the use of AM is growing, such as logistics, including transport, storage and delivery services and the retail and hospitality industry. In both platform and non-platform work there is a lack of research about the effects of AM on the work environment and workers’ health and well-being. Therefore, the overall aim of this multi-disciplinary research program is to improve data and knowledge about algorithmic management in non-platform sectors and its effects on health, safety, and well-being, as well as develop risk-reducing tools and strategies by:Facilitating the development of a standard for measurement of algorithmic management at work and related risks for health, safety and well-being.Increasing knowledge about the effects of algorithmic management on workers’ health, safety, and well-being.Investigating the balance of interests related to the control of algorithms in different legal contexts regarding occupational health and safety (OSH).The proposed program will contribute with enhanced data and knowledge about challenges and opportunities of AM to safety, health and well-being as well as evidence-based tools and strategies to be used by stakeholders in discussions and action related to AM. The program applies multiple methods including quantitative, qualitative, literature reviews and participatory research.The program will be performed by an international and multidisciplinary team of researchers, involving experts in human-computer-interaction, cognitive ergonomics, labour economics, political science, occupational epidemiology, comparative labour law, industrial relations, work organization and psychology.

Research problem and specific questions: Long-term disruption of circadian rhythms, particularly due to light exposure during the biological night, is associated with a wide range of common non-communicable diseases (NCDs). Approximately 12% of the European working population engages in night-shift work

therefore, studying the impact of night-shift work has important implications for public health. The proposed study aims to a) collect individual-level data on multiple exposures among night-shift workers, using new sensors, information technology, and advanced biomonitoring

b) examine how short-term night-shift work affects bodily functions related to the development of NCDs and ageing

c) identify key biological pathways for health effects associated with night-shift work

d) evaluate longitudinal changes in biomarkers among night- and day-shift workers from baseline to a two-year follow-up

and e) develop a screening battery relevant to night-shift work and development of NCDs to be implemented in the pre-assignment and periodical medical examination conducted by the occupational health services.Data and method: We will address these aims by collecting comprehensive information about occupational and environmental exposures, lifestyle factors, and dietary patterns. We will measure cognitive function, established biomarkers of cardiovascular and metabolic health, hormones, stress, immune function, ageing and epigenetic programming in blood, saliva, and adipose tissue of night- and day-shift workers.Plan for project realization: At baseline, we will compare night- with day-shift workers among Swedish workers (county council health workers n=400) and European workers (n=800) examined with the same protocol during a work week, and we will follow up the Swedish workers (n=400) two years later applying the same protocol.Relevance: This study will generate new knowledge of the long-term impact of circadian disruption on determinants of NCDs and identify the important biological pathways underlying health outcomes among night-shift workers. This will inform preventive actions such as improved work schedules, medical surveillance via the occupational health service of exposed populations, and advising exposed workers.

Many studies nowadays focus on taking stock of the platform economy in Europe (e.g., investigating its magnitude, business models, career and job characteristics of workers, ...), surprisingly the occupational safety and health (OSH) implications of platform work have remained largely under the radar. Against this background, the proposed project aims to (i) investigate the OSH risks and regulations of platform work and (ii) provide recommendations to foster a safe and healthy occupational environment for platform workers in European countries based on the results of this study. Pursuing these aims, the project adopts a mixed-method study design organised into two work packages (WP) and involves platform workers living in Belgium, Denmark, Finland, Poland, Spain, Sweden and the United Kingdom. WP1 will consist in a European mixed-method cohort of platform workers. WP1 will explore longitudinally ways in which platform work is associated with OSH-risks and poor health and the experiences of platform workers in regard to OSH of their jobs. WP2 aims to research ways for promoting changes for safer and healthier occupational environments for platform work. For doing so, WP2 will explore how do platform work managers perceive the OSH of employees/workers, what are the characteristics of platforms that maintain a healthy work environment and what are the regulatory contexts and challenges in terms of OSH posed by platform of work. Both WPs will explore similarities and differences across countries and forms of platform work, thereby contextualising the findings about health and platform work within different regulatory environments. The expected results of this project will provide new and original scientific understanding of an understudied and evolving challenge for the future world of work. Drawing on the new scientific understanding, the project will provide new guidance for policymakers, companies and trade unions to protect the health of the European workforce.

The retirement age is being raised gradually to counteract the financial consequences of an increasingly older population. However, with increasing age, and in particular after 50 years of age, an increasing number of persons are excluded from the labour market due to health problems. There are also increasing difficulties for young people and people in marginalized labor market positions to establish in the labor market. The research program addresses major challenges to create opportunities for a sustainable working life for all groups on the labor market by strengthening and updating the research on risk factors for poor health, and labor market marginalization and exclusion over the life-span among young, middle aged, and older male and female workers.The aims of the program are to extend knowledge on risk factors for labor market marginalisation and exclusion over the life course (WP1-3), and to identify policies and measures at workplaces that support a long working life (WP4). In four work packages we will study:WP1. Effects of long-term and accumulated poor working conditions on preterm labor-market exit, and potentially risk-reducing effects of occupational change and reduced occupational exposure WP2 Working-life expectancy among different occupational and socioeconomic groups WP3. Determinants and consequences of labor market marginalization over the life courseWP4. Work organizational structures promoting a sustainable working life for all The program is based on research and research collaborations that we have been involved in for many years, in an established environment now under expansion and development. The research team consists of both established and junior researchers from Sweden, the Netherlands, Norway, and the USA. A large, compiled register-based cohort (SWIP) that includes the entire Swedish population, born around 1990 or earlier, will be used in WP1-3. Data from surveys and qualitative interviews will also be collected (WP4).