Job quality, health and at-work productivity

Many countries invest considerable resources into promoting employment and the creation of jobs. At the same time, policies and institutions still pay relatively little attention to the quality of jobs although job quality has been found to be a major driver of employee well being and may be an important factor for work productivity. Eventually, job quality might also influence labour supply choices and lead to higher employment. Providing robust evidence for the relationship between job quality and worker productivity could make a strong case for labour market policies directed at the improvement of job quality.This paper reviews existing evidence on the relationship between the quality of the work environment and individual at-work productivity, defined as reduced productivity while at work,and assesses the effect of health on this relationship. After screening 2319 studies from various fields and disciplines, including economics and medicine, 48studies are reviewed. Strong evidence is found for a negative relationship between job stress or job strain and individual at-work productivity and for a positive relationship between job rewards and productivity. Moderate evidence is found for a negative relationship between work-family conflict and at-work productivity and for a positive relationship between fairness at work and social support from co-workers and productivity. Health influences the relationship between the quality of the work environment and productivity.Specifically, the relationship is stronger for people in good health. Job quality needs a more prominent place in labour market policy. More attention needs to be paid to workers’ perceptions of the quality of their work environment and how policies and practices at both the level of the worker and the work environment may influence this.Furthermore, as health-related factors significantly influence the relationship between job quality and productivity, multidisciplinary approaches are needed to support at-work productivity

Work-family trajectories in young adulthood:Associations with mental health problems in adolescence

During young adulthood, several transitions in work and family lives occur, but knowledge of the work-family trajectories of the current generation of young adults, i.e. people born in the 1990s, is lacking. Moreover, little is known about whether the mental health status before the start of the working life may shape work-family trajectories. We used 18-year follow-up data from the TRAILS cohort study of individuals born between 1989 and 1991 (n = 992; 63.2% women). Internalising and externalising problems were measured with the Youth Self-Report at ages 11, 13 and 16 years. Monthly employment, education and parenthood states were recorded between 18 and 28 years. Applying sequence analysis, we identified six work-family trajectories in women and men. The first five trajectories were labelled: long education, continuous education and work, education and work to work, early work, and inactive. The main difference between trajectories of women and men was in the timing of parenthood, thus the remaining trajectory of women was labelled active with children, and the remaining trajectory of men active. Women who experienced externalising problems in adolescence were more likely to belong to the trajectory characterised by parenthood. Men who experienced internalising problems in adolescence were more likely to belong to the trajectory characterised by a long time spent in education. The TRAILS data allowed us to consider timing, duration and ordering of the work and family states in young adulthood, and to use multiple assessments of mental health in adolescence. Further research needs to examine the mechanisms through which early mental health affects later work and family outcomes

Work-family trajectories and health:A systematic review

BACKGROUND: Work and family lives interact in complex ways across individuals’ life courses. In the past decade, many studies constructed work-family trajectories, some also examined the relation with health. The aims of this systematic review were to summarise the evidence from studies constructing work-family trajectories, and to synthesise the evidence on the association between work-family trajectories and health. METHODS: We searched MEDLINE, EMBASE, PsycINFO, SocINDEX and Web of Science databases. Key search terms related to work, family and trajectories. Studies that built combined work-family trajectories or examined the relationship between work and family trajectories were included. Risk of bias was assessed independently by two authors. The identified work-family trajectories were summarised and presented for men and women, age cohorts and contexts. The evidence on the association with health as antecedent or consequence was synthesised. RESULTS: Forty-eight studies, based on 29 unique data sources, were included. Thirty-two studies (67%) were published in 2015 or later, and sequence analysis was the primary analytic technique used to construct the trajectories (n = 43, 90%). Trajectories of women were found to be more diverse and complex in comparison with men. Work-family trajectories differed by age cohorts and contexts. Twenty-three studies (48%) examined the association between work-family trajectories and health and most of these studies found significant associations. The results indicate that work-family trajectories characterised by an early transition to parenthood, single parenthood, and weak ties to employment are associated with worse health outcomes. CONCLUSIONS: Work-family trajectories differed greatly between men and women, but differences seemed to decrease in the youngest cohorts. Given the current changes in labour markets and family formation processes, it is important to investigate the work and family lives of younger cohorts. Work-family trajectories were associated with health at different life stages. Future research should examine longitudinal associations of work-family trajectories with health and focus on elucidating why and under which circumstances some trajectories are associated with better or worse health compared with other trajectories

Mental Health and Work:Achieving Well-integrated Policies and Service Delivery

Mental ill-health can lead to poor work performance, high sickness absence and reduced labour market participation, resulting in considerable costs for society.Improving labour market participation of people with mental health problems requires well-integrated policies and services across the education, employment, health and social sectors. This paper provides examples of policy initiatives from 10OECDcountries for integrated services. Outcomes and strengths and weaknesses of the policy initiatives are presented, resulting in the following main conclusions for future integrated mental health and work policies and services: - More rigorous implementation and evaluation of integrated policies is necessary to improve labour market outcomes. Implementation cannot be left to the discretion of stakeholders only. - Better financial incentives and clearer obligations and guidelines need to be provided to stakeholders and professionals to participate in integrated service delivery. - Each sector has a responsibility to assure integrated services in line with client needs, in turn requiring much better knowledge about the needs of clients with a mental illness. - More integrated provision of services within each sector–e.g. through employment advice brought into the mental health system and psychological expertise brought into employment services –appears to be the easiest and most cost-effective approach

Proposing network analysis for early life adversity:An application on life event data

Commonly used methods for modelling early life adversity (e.g., sum-scores, latent class or trajectory approaches, single-adversity approaches, and factor-analytical approaches) have not been able to capture the complex nature of early life adversity. We propose network analysis as an alternative way of modelling early life adversity (ELA). Our aim was to construct a network of fourteen adverse events (AEs) that occurred before the age of 16 in the TRacking Adolescents Individual Lives Survey (TRAILS, N = 1029). To show how network analysis can provide insight into why AEs are associated, we compared findings from the resulting network model to findings from tetrachoric correlation analyses. The resulting network of ELA comprised direct relationships between AEs and more complex, indirect relationships. A total of fifteen edges emerged in the network of AEs (out of 91 possible edges). The correlation coefficients suggested that many AEs were associated. The network model of ELA indicated, however, that several associations were attributable to interactions with other AEs. For example, the zero-order correlation between parental addiction and familial conflicts (0.24) could be explained by interactions with parental divorce. Our application of network analysis shows that using network analysis for modelling the ELA construct allows capturing the constructs' complex nature. Future studies should focus on gaining more insight into the most optimal model estimation and selection procedures, as well as sample size requirements. Network analysis provides researchers with a valuable tool that allows them as well as policy-makers and professionals to gain insight into potential mechanisms through which adversities are associated with each other, and conjunctively, with life course outcomes of interest

Does the timing and duration of mental health problems during childhood and adolescence matter for labour market participation of young adults?

BACKGROUND: Little is known about the timing and duration of mental health problems (MHPs) on young adults’ labour market participation (LMP). This life-course study aims to examine whether and how the timing and duration of MHPs between childhood and young adulthood are associated with LMP in young adulthood. METHODS: Logistic regression analyses were performed with data from the Tracking Adolescents’ Individual Lives Survey (TRAILS), a Dutch prospective cohort study with 15-year follow-up (N=874). Internalising and externalising problems were measured by the Youth/Adult Self-Report at ages 11, 13, 16, 19 and 22. Labour market participation (having a paid job yes/no) was assessed at age 26. RESULTS: Internalising problems at all ages and externalising problems at age 13, 19 and 22 were associated with an increased risk of not having a paid job (internalising problems ORs ranging from 2.24, 95% CI 1.02 to 4.90 at age 11 to OR 6.58, CI 3.14 to 13.80 at age 22; externalising problems ORs from 2.84, CI 1.11 to 7.27 at age 13 to OR 6.36, CI 2.30 to 17.56 at age 22). Especially a long duration of internalising problems increased the risk of not having a paid job in young adulthood. CONCLUSION: The duration of MHPs during childhood and adolescence is strongly associated with not having paid work in young adulthood. This emphasises the necessity of applying a life-course perspective when investigating the effect of MHPs on LMP. Early monitoring, mental healthcare and the (early) provision of employment support may improve young adult’s participation in the labour market

Investigating young adults' mental health and early working life trajectories from a life course perspective:the role of transitions

BACKGROUND: Many young adults leave the labour market because of mental health problems or never really enter it, through early moves onto disability benefits. Across many countries of the Organisation for Economic Co-operation and Development, between 30% and 50% of all new disability benefit claims are due to mental health problems; among young adults this moves up to 50%-80%. OUTLINE: We propose a research agenda focused on transitions in building young adults' mental health and early working life trajectories, considering varying views for subgroups of a society. First, we briefly review five transition characteristics, then we elaborate a research agenda with specific research questions. RESEARCH AGENDA: Our research agenda focuses on transitions as processes, in time and place and as sensitive periods, when examining young adults' mental health and early working life trajectories from a life course perspective. As more and more childhood and adolescent cohorts mature and facilitate research on later life labour market, work and health outcomes, transition research can help guide policy and practice interventions. FUTURE CROSS-DISCIPLINARY RESEARCH: In view of the many challenges young adults face when entering the changing world of work and labour markets, future research on transitions in young adults related to their mental health and early working life trajectories will provide ample opportunities for collaborative cross-disciplinary research and stimulate debate on this important challenge

Allowing course compensation in higher education: a latent class regression analysis to evaluate performance on a follow-up course

In this study, the consequences of allowing course compensation in a \nhigher education academic dismissal policy are evaluated by examining \nperformance on a second-year follow-up (i.e. sequel) course that builds \non material from a first-year precursor course. Up to now, differences in \nthe consequences of compensation on student performance across \ngroups of students who portray different unobserved study processes \nwere not considered. In this study we used a latent class regression \nmodel to distinguish latent groups of students. Data from two undergraduate curricula were used and latent classes were formed based on \nsimilar patterns in averages, variability in grades, the number of compensated courses, and the number of retakes in the first year. Results \nshow that students can be distinguished by three latent classes. \nAlthough the first-year precursor course is compensated in each of \nthese latent classes, low performance on the precursor course results in \nlow performance on the second-year sequel course for psychology students who belong to a class in which the average across first-year \ncourses is low and the average number of compensated courses and \nretakes are high. For these students, compensation on a precursor \ncourse seems more likely to relate to insufficient performance on a \nsequel course