Objectives This study investigated sustainability and multimorbidity alongside barriers to employment including health and policy to demonstrate intersectional impact on return-to-work success within a UK welfare-to-work programme.Design Cohort study design: The study calculated the proportion of time spent employed after experiencing a job start and the proportion retaining work over 6 months. Employment/unemployment periods were calculated, sequence-index plots were produced and visualisations were explored by benefit type and age.Setting This study used confidential access to deidentified data from unemployed Work Programme clients operated by Ingeus on behalf of the UK Government in Scotland between 1 April 2013 and 31 July 2014.Participants 13 318 unemployed clients aged 18–64 years were randomly allocated to a Work Programme provider and monitored over 2 years.Results This study has two distinct groupings. ‘Employment and Support Allowance (ESA)’ corresponding to those with work-limiting disability in receipt of related state financial support, and ‘Jobseeker’s Allowance (JSA)’ corresponding to unemployment claimants. Despite fewer and later job starts for ESA clients, those that gained employment spend relatively more subsequent time in employment when compared with individuals without work-limiting conditions (ESA clients under 50, 0.73; ESA clients over 50, 0.79; JSA clients under 50, 0.67 and JSA clients over 50, 0.68). Proportion in permanent jobs was higher among ESA than JSA clients (JSA under 50, 92%; JSA over 50, 92%; ESA under 50, 95% and ESA over 50, 97%).Conclusion The research demonstrated that returning to paid employment after a reliance on welfare benefits is challenging for people aged over 50 and those with disability. The study found that although fewer older ESA claimants entered employment, they typically remained in employment more than JSA clients who did not leave the Work Programme early. This indicates the importance of identifying risk factors for job loss in ageing workers and the development of interventions for extension of working lives.

Abstract Background The information technology (IT) workforce has been growing more rapidly than others, with occupational health (OH) risks of sedentary behaviour, physical inactivity and poor diet, yet studies of their non-communicable disease risk, notably cancer, are lacking. Aims To investigate cancer risk in IT workers compared to others in employment and the nine major Standard Occupational Classification (SOC) groups. Methods We evaluated incident diagnosed cancers in the UK Biobank cohort through national cancer registry linkage. Cox proportional hazard regression models, with 15-year follow-up, were used to compare incident cancer risk among IT workers with all other employed participants and with the nine major SOC groups. Results Overall, 10 517 (4%) employed participants were IT workers. Adjusting for confounders, IT workers had a slightly lower cancer incidence compared to all other employed participants (Model 2: hazard ratio = 0.91, 95% confidence interval [CI] 0.83–1.01). Compared to the nine major SOC groups, they had a similar (Major Groups 2, 5 and 8) or lower (Major Groups 1, 3, 4, 6, 7 and 9) cancer incidence. Conclusions Despite their occupational risks of sedentary behaviour, poor diet and physical inactivity, IT workers do not have an increased cancer incidence compared to all other employed participants and the nine major SOC groups. This study paves the way for large, longitudinal health outcome studies of this under-researched and rapidly growing occupational group.

I wish to make some observations on the significant editorial and related paper by Lalloo and Macdonald [1,2]. I make these comments as an Independent Medical Examiner appointed by a WorkCover authority in an Australian jurisdiction. My work mainly relates to workers compensation cases in contrast to the paper by Lalloo and Macdonald which mainly relates to referrals for sickness absence. However, I find the issues and principles they raised are similar which underlines the importance of their paper for clinical practice. I have found the overall concept in approaching ‘complex’ patients should be one of exploring illness behaviour and the several medical, psychosocial, organizational and systems influences that may shape this behaviour. The concept of red, yellow, blue and black flags is a useful structural framework. I am surprised that the authors downplay the importance of biopsychosocial factors in case complexity. Their comment is based on the analysis of 200 complex cases of experienced occupational physicians using a template. Therefore, adequacy of the history taking becomes critical to the soundness of the database. In my experience explorations of childhood trauma (‘did you have a happy childhood?’) and for migrants an exploration of the circumstances in which they fled their country sometimes reveals horrific traumas causing long-term psychological scars [3]. If these sensitive but crucial matters were not covered in the template history, their importance will be downplayed.

Objectives Despite reported psychological hazards of information technology (IT) work, studies of diagnosed mental health conditions in IT workers are lacking. We investigated self-reported mental health outcomes and incident anxiety/depression in IT workers compared to others in employment in a large population-based cohort. Methods We evaluated self-reported mental health outcomes in the UK Biobank cohort and incident diagnosed anxiety/depression through health record linkage. We used logistic regression and Cox models to compare the risks of prevalent and incident anxiety/depression among IT workers with all other employed participants. Furthermore, we compared outcomes within IT worker subgroups, and between these subgroups and other similar occupations within their major Standard Occupational Classification (SOC) group. Results Of 112 399 participants analyzed, 4093 (3.6%) were IT workers. At baseline, IT workers had a reduced odds (OR = 0.66, 95%CI: 0.52-0.85) of anxiety/depression symptoms and were less likely (OR = 0.87, 95%CI: 0.83-0.91) to have ever attended their GP for anxiety/depression, compared to all other employed participants, after adjustment for confounders. The IT technician subgroup were more likely (OR = 1.22, 95%CI: 1.07-1.40) to have previously seen their GP or a psychiatrist (OR = 1.31, 95%CI: 1.06-1.62) for anxiety/depression than their SOC counterparts. IT workers had lower incident anxiety/depression (HR = 0.84, 95%CI 0.77-0.93) compared to all other employed participants, after adjustment for confounders. Conclusions Our findings from this, the first longitudinal study of IT worker mental health, set the benchmark in our understanding of the mental health of this growing workforce and identification of high-risk groups. This will have important implications for targeting mental health workplace interventions.

Purpose To compare outcomes in employed people from an enhanced routine management pathway for musculoskeletal disorders within National Health Service Scotland with an existing active case-management system, Working Health Services Scotland. Materials and methods The study comprised a service evaluation using anonymised routinely collected data from all currently employed callers presenting with musculoskeletal disorder to the two services. Baseline demographic and clinical data were collected. EuroQol EQ-5D(TM) scores at the start and end of treatment were compared for both groups, overall and by age, sex, socio-economic status, and anatomical site, and the impact of mental health status at baseline was evaluated. Results Active case-management resulted in greater improvement than enhanced routine care. Case-managed service users entered the programme earlier in the recovery pathway; there was evidence of spontaneous improvement during the longer waiting time of routine service clients but only if they had good baseline mental health. Those most disadvantaged through mental health co-morbidity showed the greatest benefit. Conclusions People with musculoskeletal disorders who have poor baseline mental health status derive greatest benefit from active case-management. Case-management therefore contributes to reducing health inequalities and can help to minimise long-term sickness absence. Shorter waiting times contributed to better outcomes in the case-managed service.

BACKGROUND:There are still uncertainties in our knowledge of the amount of SARS-CoV-2 virus present in the environment - where it can be found, and potential exposure determinants - limiting our ability to effectively model and compare interventions for risk management. AIM:This study measured SARS-CoV-2 in three hospitals in Scotland on surfaces and in air, alongside ventilation and patient care activities. METHODS:Air sampling at 200 L/min for 20 min and surface sampling were performed in two wards designated to treat COVID-19-positive patients and two non-COVID-19 wards across three hospitals in November and December 2020. FINDINGS:Detectable samples of SARS-CoV-2 were found in COVID-19 treatment wards but not in non-COVID-19 wards. Most samples were below assay detection limits, but maximum concentrations reached 1.7×103 genomic copies/m3 in air and 1.9×104 copies per surface swab (3.2×102 copies/cm2 for surface loading). The estimated geometric mean air concentration (geometric standard deviation) across all hospitals was 0.41 (71) genomic copies/m3 and the corresponding values for surface contamination were 2.9 (29) copies/swab. SARS-CoV-2 RNA was found in non-patient areas (patient/visitor waiting rooms and personal protective equipment changing areas) associated with COVID-19 treatment wards. CONCLUSION:Non-patient areas of the hospital may pose risks for infection transmission and further attention should be paid to these areas. Standardization of sampling methods will improve understanding of levels of environmental contamination. The pandemic has demonstrated a need to review and act upon the challenges of older hospital buildings meeting current ventilation guidance.

Objectives: Clinical case complexity is an inherent factor in occupational health (OH), yet it is poorly defined and understood. Our aim was to identify the multiple sources of complexity in OH and propose a conceptual complexity framework model for clinical OH practice. Methods: Through a scoping review, expert panel consensus, and content analysis of OH clinical case reports, we identified relevant complexity-contributing factors (CCFs) specifically tailored to the OH setting, which we defined and validated. Results: The proposed model consists of three primary domains (PDs); health factors, workplace factors and biopsychosocial factors. Twenty-seven CCFs are described and defined within these PDs. Conclusions: This work lays the foundation for improved understanding, identification, and assessment of complexity in OH. This is imperative for ensuring high quality clinical practice standards, identifying training needs and appropriate triaging/resource allocation.

BACKGROUND:Case management interventions have shown to be effective to prevent musculoskeletal pain and disability, but a single definition has not been achieved, nor an agreed profile for case managers. OBJECTIVE:To describe the elements that define case management and case managers tasks for return-to-work of workers with musculoskeletal disorders (MSDs). METHODS:A comprehensive computerized search of articles published in English until February 16, 2021 was carried out in several bibliographic databases. Grey literature was obtained through a search of 13 key websites. A peer-review screening of titles and abstracts was carried out. Full text in-depth analysis of the selected articles was performed for data extraction and synthesis of results. RESULTS:We identified 2,422 documents. After full-text screening 31 documents were included for analysis. These were mostly European and North American and had an experimental design. Fifteen documents were published between 2010 to 2021 and of these 7 studies were published from 2015. Fifteen elements were identified being the commonest "return-to-work programme" (44.4%) and "multidisciplinary assessment/interdisciplinary intervention" (44.4%). Of 18 tasks found, the most frequent was "establishing goals and planning return-to-work rehabilitation" (57.7%). Eighteen referral services were identified. CONCLUSIONS:Despite there were several elements frequently reported, some elements with scientific evidence of their importance to deal with MSDs (e.g. early return-to-work) were almost not mentioned. This study proposes key points for the description of case management and case managers tasks.

Introduction Informational technology (IT) and the IT workforce are rapidly expanding with potential occupational health implications. Yet to date, IT worker health is under-studied and large-scale studies are lacking. Objectives To investigate health, lifestyle and occupational risk factors of IT workers. Methods We evaluated self-reported health, lifestyle and occupational risk factors for IT workers in the UK Biobank database. Using logistic regression, we investigated differences between IT workers and all other employed participants. Regression models were repeated for IT worker sub-groups (managers, professionals, technicians) and their respective counterparts within the same Standard Occupational Classification (SOC) major group (functional managers, science and technology professionals, science and technology associate professionals). Results Overall, 10,931 (4%) employed participants were IT workers. Compared to all other employed participants, IT workers reported similar overall health, but lower lifestyle risk factors for smoking and obesity. Sedentary work was a substantially higher occupational exposure risk for IT workers compared to all other employed participants (OR=5.14, 95%CI:4.91–5.39) and their specific SOC group counterparts (managers: OR=1.83, 95%CI:1.68–1.99, professionals: OR=7.18, 95%CI:6.58–7.82, technicians: OR=4.48, 95%CI:3.87–5.17). IT workers were also more likely to engage in computer screen-time outside work than all other employed participants (OR=1.42, 95%CI:1.35–1.51). Conclusions Improved understanding of health, lifestyle and occupational risk factors from this, the largest to date study of IT worker health, can help inform workplace interventions to mitigate risk, improve health and increase the work participation of this increasingly important and rapidly growing occupational group.

Objectives: Clinical case complexity is an inherent factor in occupational health (OH), yet it is poorly defined and understood. Our aim was to identify the multiple sources of complexity in OH and propose a conceptual complexity framework model for clinical OH practice. Methods: Through a scoping review, expert panel consensus, and content analysis of OH clinical case reports, we identified relevant complexity-contributing factors (CCFs) specifically tailored to the OH setting, which we defined and validated. Results: The proposed model consists of three primary domains (PDs); health factors, workplace factors and biopsychosocial factors. Twenty-seven CCFs are described and defined within these PDs. Conclusions: This work lays the foundation for improved understanding, identification, and assessment of complexity in OH. This is imperative for ensuring high quality clinical practice standards, identifying training needs and appropriate triaging/ resource allocation.

Welfare to work interventions seek to move out-of-work individuals from claiming unemployment benefits towards paid work. However, previous research has highlighted that for over-50s, particularly those with chronic health conditions, participation in such activities are less likely to result in a return to work. Using longitudinal semi-structured interviews, we followed 26 over-50s during their experience of a mandated welfare to work intervention (the Work Programme) in the United Kingdom. Focusing on their perception of suitability, we utilise and adapt Candidacy Theory to explore how previous experiences of work, health, and interaction with staff (both in the intervention, and with healthcare practitioners) influence these perceptions. Despite many participants acknowledging the benefit of work, many described a pessimism regarding their own ability to return to work in the future, and therefore their lack of suitability for this intervention. This was particularly felt by those with chronic health conditions, who reflected on difficulties with managing their conditions (e.g., attending appointments, adhering to treatment regimens). By adapting Candidacy Theory, we highlighted the ways that mandatory intervention was navigated by all the participants, and how some discussed attempts to remove themselves from this intervention. We also discuss the role played by decision makers such as employment-support staff and healthcare practitioners in supporting or contesting these feelings. Findings suggest that greater effort is required by policy makers to understand the lived experience of chronic illness in terms of ability to RTW, and the importance of inter-agency work in shaping perceptions of those involved.

Objectives: Clinical case complexity is an inherent factor in occupational health (OH), yet it is poorly defined and understood. Our aim was to identify the multiple sources of complexity in OH and propose a conceptual complexity framework model for clinical OH practice. Methods: Through a scoping review, expert panel consensus, and content analysis of OH clinical case reports, we identified relevant complexity-contributing factors (CCFs) specifically tailored to the OH setting, which we defined and validated. Results: The proposed model consists of three primary domains (PDs); health factors, workplace factors and biopsychosocial factors. Twenty-seven CCFs are described and defined within these PDs. Conclusions: This work lays the foundation for improved understanding, identification, and assessment of complexity in OH. This is imperative for ensuring high quality clinical practice standards, identifying training needs and appropriate triaging/resource allocation.

Objectives: This systematic review aimed to evaluate the evidence for air and surface contamination of workplace environments with SARS-CoV-2 RNA and the quality of the methods used to identify actions necessary to improve the quality of the data. Methods: We searched Web of Science and Google Scholar until 24 December 2020 for relevant articles and extracted data on methodology and results. Results: The vast majority of data come from healthcare settings, with typically around 6% of samples having detectable concentrations of SARS-CoV-2 RNA and almost none of the samples collected had viable virus.There were a wide variety of methods used to measure airborne virus, although surface sampling was generally undertaken using nylon flocked swabs. Overall, the quality of the measurements was poor. Only a small number of studies reported the airborne concentration of SARS-CoV-2 virus RNA, mostly just reporting the detectable concentration values without reference to the detection limit. Imputing the geometric mean air concentration assuming the limit of detection was the lowest reported value, suggests typical concentrations in healthcare settings may be around 0.01 SARS-CoV-2 virus RNA copies m -3 . Data on surface virus loading per unit area were mostly unavailable. Conclusions: The reliability of the reported data is uncertain.The methods used for measuring SARS-CoV-2 and other respiratory viruses in work environments should be standardized to facilitate more consistent interpretation of contamination and to help reliably estimate worker exposure.

Widespread unemployment would be worse for population health than covid -19

Background For all doctors, including occupational physicians (OPs), research and teaching are considered core requirements of medical education and continuing professional development. Academic skills are also vital to evidence-based practice and advancement of occupational health (OH) as a specialty. In recent years, attention has focussed on the declining UK OH academic base and the research-practice gap, and increased practitioner participation in research is encouraged. Aims An establish a baseline of research and teaching activity among UK OPs, identify related barriers and inform strategies to overcome them. Methods An online survey including specific career profile questions derived from consensus following expert panel discussions. It formed part of a larger Delphi study on UK OH research priorities. Results We received 213 responses, about 18% of 1207 practising UK OPs. Of these, 162 (76%) undertook research at some career-point, of which 44 (27%) were currently research-active. Similarly, 154 (72%) undertook teaching at some career-point, of which 99 (64%) were currently teaching-active. Of those who had never undertaken research (n = 51) or teaching (n = 59), 40 and 42% were interested in doing so, respectively. Key barriers were lack of time and opportunity, the former particularly for respondents practising in industry, where 'commercial' demands take priority, rather than healthcare. Conclusions this study establishes a benchmark of academic activity among UK OPs and identifies related barriers.These 'target' barriers can shape research funding priorities and education to increase participation and develop the UK OH academic base.

Objectives To investigate severe COVID-19 risk by occupational group. Methods Baseline UK Biobank data (2006–10) for England were linked to SARS-CoV-2 test results from Public Health England (16 March to 26 July 2020). Included participants were employed or self-employed at baseline, alive and aged <65 years in 2020. Poisson regression models were adjusted sequentially for baseline demographic, socioeconomic, work-related, health, and lifestyle-related risk factors to assess risk ratios (RRs) for testing positive in hospital or death due to COVID-19 by three occupational classification schemes (including Standard Occupation Classification (SOC) 2000). Results Of 120 075 participants, 271 had severe COVID-19. Relative to non-essential workers, healthcare workers (RR 7.43, 95% CI 5.52 to 10.00), social and education workers (RR 1.84, 95% CI 1.21 to 2.82) and other essential workers (RR 1.60, 95% CI 1.05 to 2.45) had a higher risk of severe COVID-19. Using more detailed groupings, medical support staff (RR 8.70, 95% CI 4.87 to 15.55), social care (RR 2.46, 95% CI 1.47 to 4.14) and transport workers (RR 2.20, 95% CI 1.21 to 4.00) had the highest risk within the broader groups. Compared with white non-essential workers, non-white non-essential workers had a higher risk (RR 3.27, 95% CI 1.90 to 5.62) and non-white essential workers had the highest risk (RR 8.34, 95% CI 5.17 to 13.47). Using SOC 2000 major groups, associate professional and technical occupations, personal service occupations and plant and machine operatives had a higher risk, compared with managers and senior officials. Conclusions Essential workers have a higher risk of severe COVID-19. These findings underscore the need for national and organisational policies and practices that protect and support workers with an elevated risk of severe COVID-19.

Objectives: To investigate COVID-19 risk by occupational group. Design: Prospective study of linked population-based and administrative data. Setting: UK Biobank data linked to SARS-CoV-2 test results from Public Health England from 16 March to 3 May 2020. Participants: 120,621 UK Biobank participants who were employed or self-employed at baseline (2006-2010) and were 65 years or younger in March 2020. Overall, 29% (n=37,890) were employed in essential occupational groups, which included healthcare workers, social and education workers, and other essential workers comprising of police and protective service, food, and transport workers. Poisson regression models, adjusted for baseline sociodemographic, work-related, health, and lifestyle-related risk factors were used to assess risk ratios (RRs) of testing positive in hospital by occupational group as reported at baseline relative to non-essential workers. Main outcome measures: Positive SARS-CoV-2 test within a hospital setting (i.e. as an inpatient or in an Emergency Department). Results: 817 participants were tested for SARS-CoV-2 and of these, 206 (0.2%) individuals had a positive test in a hospital setting. Relative to non-essential workers, healthcare workers (RR 7.59, 95% CI: 5.43 to 10.62) and social and education workers (RR 2.17, 95% CI: 1.37 to 3.46) had a higher risk of testing positive for SARS-CoV-2 in hospital. Using more detailed groupings, medical support staff (RR 8.57, 95% CI: 4.35 to 16.87) and social care workers (RR 2.99, 95% CI: 1.71 to 5.24) had highest risk within the healthcare worker and social and education worker categories, respectively. In general, adjustment for covariates did not substantially change the pattern of occupational differences in risk. Conclusions: Essential workers in health and social care have a higher risk of severe SARS-CoV-2 infection. These findings underscore the need for national and organisational policies and practices that protect and support workers with elevated risk of SARS-CoV-2 infection.