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Background: In the UK, tens of millions of working days are lost due to work‐related ill health every year, costing billions of pounds. The role of Occupational Health (OH) services is vital in helping workers to maintain employment when they encounter injury or illness. OH providers traditionally rely on a clinical workforce to deliver these services, particularly doctors and nurses with OH qualifications. However, the increasing demand for OH services is unlikely to be met in the future using this traditional model, due to the declining number of OH‐trained doctors and nurses in the UK. Multi‐disciplinary models of OH delivery, including a more varied range of healthcare and non‐healthcare professionals, could provide a way to meet this new demand for OH services. There is a need to identify collaborative models of OH service delivery and review their effectiveness on return‐to work outcomes. There is an existing pool of systematic review evidence evaluating workplace based, multi‐disciplinary OH interventions, but it is difficult to identify which aspects of the content and/or delivery of these interventions may be associated with improved work‐related outcomes. Objectives: The aim of this evidence and gap map (EGM) was to provide an overview of the systematic review evidence that evaluates the effectiveness and cost‐effectiveness of multi‐disciplinary OH interventions intending to improve work‐related outcomes. Search Methods: In June 2021 we searched a selection of bibliographic databases and other academic literature resources covering a range of relevant disciplines, including health care and business studies, to identify systematic review evidence from a variety of sectors of employment. We also searched Google Search and a selection of topically relevant websites and consulted with stakeholders to identify reports already known to them. Searches were updated in February 2023. Selection Criteria: Systematic reviews needed to be about adults (16 years or over) in employment, who have had absence from work for any medical reason. Interventions needed to be multi‐disciplinary (including professionals from different backgrounds in clinical and non‐clinical professions) and designed to support employees and employers to manage health conditions in the workplace and/or to help employees with health conditions retain and/or return to work following medical absence. Effectiveness needed to be measured in terms of return to work, work retention or measures of absence, or economic evaluation outcomes. These criteria were applied to the title and abstract and full text of each systematic review independently by two reviewers, with disagreements resolved through discussion. We awarded each systematic review a rating of 'High', 'Medium' or 'Low' relevance to indicate the extent to which the populations, interventions and their contexts synthesised within the review were consistent with our research question. We also recorded the number of primary studies included within each of the 'High' and 'Medium' reviews that were relevant to research question using the same screening process applied at review level. Data Collection and Analysis: Summary data for each eligible review was extracted. The quality of the systematic reviews, rated as 'High' or 'Medium' relevance following full text screening, was appraised using the AMSTAR‐2 quality appraisal tool. All data were extracted by one reviewer and checked by a second, with disagreements being settled through discussion. Summary data for all eligible systematic reviews were tabulated and described narratively. The data extracted from reviews of 'High' and 'Medium' relevance was imported into EPPI‐Mapper software to create an EGM. Stakeholder Involvement: We worked alongside commissioners and policy makers from the Department of Health and Social Care (DHSC) and Department of Work and Pensions (DWP), OH personnel, and people with lived experience of accessing OH services themselves and/or supporting employees to access OH services. Individuals contributed to decision making at all stages of the project. This ensured our EGM reflects the needs of individuals who will use it. Main Results: We identified 98 systematic reviews that contained relevant interventions, which involved a variety of professionals and workplaces, and which measured effectiveness in terms of return to work (RTW). Of these, we focused on the 30 reviews where the population and intervention characteristics within the systematic reviews were considered to be of high or medium relevance to our research questions. The 30 reviews were of varying quality, split evenly between High/Moderate quality and Low/Critically‐Low quality ratings. We did not identify any relevant systematic review evidence on any other work‐related outcome of interest. Interventions were heterogenous, both within and across included systematic reviews. The EGM is structured according to the health condition experienced by participants, and the effectiveness of the interventions being evaluated, as reported within the included systematic reviews. It is possible to view (i) the quality and quantity of systematic review evidence for a given health condition, (ii) how review authors assessed the effectiveness or cost‐effectiveness of the interventions evaluated. The EGM also details the primary studies relevant to our research aim included within each review. Authors' Conclusions: This EGM map highlights the array of systematic review evidence that exists in relation to the effectiveness or cost‐effectiveness of multi‐disciplinary, workplace‐based OH interventions in supporting RTW. This evidence will allow policy makers and commissioners of services to determine which OH interventions may be most useful for supporting different population groups in different contexts. OH professionals may find the content of the EGM useful in identifying systematic review evidence to support their practice. The EGM also identifies where systematic review evidence in this area is lacking, or where existing evidence is of poor quality. These may represent areas where it may be particularly useful to conduct further systematic reviews. [ABSTRACT FROM AUTHOR]

Background and Aims: Loot boxes are purchasable randomised rewards in video games that share structural and psychological similarities with gambling. Systematic review evidence has established reproducible associations between loot box purchasing and both problem gambling and problem video gaming. We aimed to measure the association between loot box engagement and socioeconomic correlates. Design The study was a cross‐sectional online survey using the recruitment platform, Prolific. Setting: United Kingdom (UK). Participants: A cohort of 16 196 UK adults (18 + years) self‐reporting as video gamers. Measurements Respondents were asked about their game‐related purchasing behaviour (including loot boxes), recent monthly spend on loot boxes and gambling engagement (gambling in any form; gambling online; playing 'social casino' games). A range of demographic variables were simultaneously captured, including age, sex, ethnicity, earnings, employment and educational attainment. Findings Overall, 17.16% of gamers in our cohort purchased loot boxes, with a mean self‐reported monthly spend of £29.12. These loot box purchasers are more likely to gamble (45.97% gamble) than people who make other types of game‐related purchases (on aggregate, 28.13% of non‐loot box purchasers gamble), and even greater still than those who do not make any game related purchases (24.38% gamble P < 0.001). Loot box engagement (as binary yes/no or as monthly spend normalised to earnings) was significantly associated with younger age (P < 0.001 and P < 0.001; respectively, for binary yes/no and monthly spend, adjusted for false discovery rate correction), male sex (P < 0.001 and P = 0.025), non‐university educational attainment (P < 0.001 and P < 0.001) and unemployment (P = 0.003 and P = < 0.001). Lower earners spent a higher proportion of monthly earnings on loot boxes (P < 0.001). Conclusions: The demographic associations of video game loot box engagement (younger age, male sex, non‐university educational attainment and unemployment) mirror those of other addictive and problematic behaviours, including disordered gambling, drug and alcohol misuse. [ABSTRACT FROM AUTHOR]