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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: Different dementia support roles exist but evidence is lacking on which aspects are best, for whom, and in what circumstances, and on their associated costs and benefits. Phase 1 of the Dementia PersonAlised Care Team programme (D-PACT) developed a post-diagnostic primary care)based intervention for people with dementia and their carers and assessed the feasibility of a trial. Aim: Phase 2 of the programme aims to 1) refine the programme theory on how, when, and for whom the intervention works; and 2) evaluate its value and impact. Design & setting: A realist longitudinal mixed-methods evaluation will be conducted in urban, rural, and coastal areas across South West and North West England where low-income or ethnic minority populations (for example, South Asian) are represented. Design was informed by patient, public, and professional stakeholder input and phase 1 findings. Method: High-volume qualitative and quantitative data will be collected longitudinally from people with dementia, carers, and practitioners. Analyses will comprise the following: 1) realist longitudinal case studies; 2) conversation analysis of recorded interactions; 3) statistical analyses of outcome and experience questionnaires; 4a) health economic analysis examining costs of delivery; and 4b) realist economic analysis of high-cost events and ‘near misses’. All findings will be synthesised using a joint display table, evidence appraisal tool, triangulation, and stakeholder co-analysis. Conclusion: The realist evaluation will describe how, why, and for whom the intervention does or does not lead to change over time. It will also demonstrate how a non-randomised design can be more appropriate for complex interventions with similar questions or populations. [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]

Loot boxes (LBs) are video game-related purchases with a chance-based outcome. Due to similarities with gambling, they have come under increasing scrutiny from media, academics and policymakers alike. Initial evidence suggested that LB engagement might be associated with both problem gambling (PG) and problem video gaming (PVG). We therefore conducted a systematic review of the evidence for associations between LB purchasing, PG and PVG. For LB/PG, 12 of 13 publications reported a positive relationship, with a moderately sized mean effect of r =.27. For LB/PVG, the mean effect was r =.40, although this finding was drawn from only six surveys in total. For PG/PVG, the mean effect was r =.21, with only 11 of 20 studies reporting significant effects. While further evidence is required to determine the direction of causality, the strength of relationships suggests that policy action on LBs may have benefits for harm minimisation. [ABSTRACT FROM AUTHOR]

Qualitative studies have identified a diverse array of motivations for purchasing items within video games through chance-based mechanisms (i.e., "loot boxes"). Given that some individuals—particularly those at risk of disordered gaming and/or gambling—are prone to over-involvement with loot box purchasing, it is important to have a reliable, valid means of measuring the role of different motivations in driving purchasing behaviour. Building on prior qualitative research, this paper reports the development and validation of the "RAFFLE" scale, to measure the Reasons and Facilitators for Loot box Engagement. A 23-item, seven-factor scale was developed through cognitive interviews (n = 25) followed by two surveys of UK-based gamers who purchase loot boxes; analysed via exploratory (n = 503) and confirmatory (n = 1495) factor analysis, respectively. Subscales encompassed "enhancement'; "progression'; "social pressure'; "distraction/compulsion'; "altruism'; "fear of missing out'; and "resale". The scale showed good criterion and construct validity (correlating well with measures of loot box engagement; the risky loot box index (r = 0.63) and monthly self-reported spend (r = 0.38)), and good internal validity (Cronbach's alpha = 0.84). Parallels with, and divergence from, motivations for related activities of gaming and gambling, and alignment with broader theoretical models of motivation, are discussed. [ABSTRACT FROM AUTHOR]

Excessive engagement with (increasingly prevalent) loot boxes within games has consistently been linked with disordered gambling and/or gaming. The importance of recognising and managing potential risks associated with loot box involvement means understanding contributing factors is a pressing research priority. Given that motivations for gaming and gambling have been informative in understanding risky engagement with those behaviours, this qualitative study investigated motivations for buying loot boxes, through in-depth interviews with 28 gamers from across the UK. A reflexive thematic analysis categorised reasons for buying into seven "themes"; opening experience; value of box contents; game-related elements; social influences; emotive/impulsive influences; fear of missing out; triggers/facilitators. These themes are described in detail and discussed in relation to the existing literature and motivation theories. This study contributes to understanding ways in which digital items within loot boxes can be highly valued by purchasers, informing the debate around parallels with gambling. Findings that certain motivations were disproportionately endorsed by participants with symptoms of problematic gambling has potential implications for policy and warrants further study. [ABSTRACT FROM AUTHOR]

Background: NHS England's 'Enhanced Health in Care Homes' specification aims to make the healthcare of care home residents more proactive. Primary care networks (PCNs) are contracted to provide this, but approaches vary widely: challenges include frailty identification, multidisciplinary team (MDT) capability/capacity and how the process is structured and delivered., Aim: To determine whether a proactive healthcare model could improve healthcare outcomes for care home residents., Design and Setting: Quality improvement project involving 429 residents in 40 care homes in a non-randomised crossover cohort design. The headline outcome was 2-year survival., Method: All care home residents had healthcare coordinated by the PCN's Older Peoples' Hub. A daily MDT managed the urgent healthcare needs of residents. Proactive healthcare, comprising information technology-assisted comprehensive geriatric assessment (i-CGA) and advanced care planning (ACP), were completed by residents, with prioritisation based on clinical needs.Time-dependent Cox regression analysis was used with patients divided into two groups:Control group: received routine and urgent (reactive) care only.Intervention group: additional proactive i-CGA and ACP., Results: By 2 years, control group survival was 8.6% (n=108), compared with 48.1% in the intervention group (n=321), p<0.001. This represented a 39.6% absolute risk reduction in mortality, 70.2% relative risk reduction and the number needed to treat of 2.5, with little changes when adjusting for confounding variables., Conclusion: A PCN with an MDT-hub offering additional proactive care (with an i-CGA and ACP) in addition to routine and urgent/reactive care may improve the 2-year survival in older people compared with urgent/reactive care alone., Competing Interests: Competing interests: The IT-assisted Comprehensive Geriatric Assessment (i-CGA) is owned by Target Health Solutions (THS, a company that enhances primary care IT). DA and JB are directors in THS., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

In a pre-registered survey linked to this paper (Exploring the relationships between psychological variables and loot box engagement, part 1: pre-registered hypotheses), we confirmed bivariate associations between engagement with loot boxes (purchasable randomized rewards in video games) and measures of problem gambling, problem video gaming, impulsivity, gambling cognitions, experiences of game-related 'flow', psychological distress and reduced wellbeing. However, these variables have complex relationships, so to gain further insights, we analysed the dataset (1495 gamers who purchase loot boxes and 1223 purchasers of non-randomized content) in a series of Bayesian mixed-effects multiple regressions with a zero-inflation component. The results challenge some well-established results in the literature, including associations between loot box engagement and problematic gambling measures, instead suggesting that this relationship might be underpinned by shared variance with problem video gaming and gambling-related cognitions. An entirely novel discovery revealed a complex interaction between experiences of flow and loot box engagement. Distress and wellbeing are both (somewhat contradictorily) predictive of participants engaging with loot boxes, but neither correlate with increasing loot box risky engagement/spend (among those who engage). Our findings unravel some of the nuances underpinning loot box engagement, yet remain consistent with narratives that policy action on loot boxes will have benefits for harm minimization., Competing Interests: This work was supported by funding from the charity GambleAware (a UK-based independent charity and strategic commissioner of gambling harm education, prevention, early intervention and treatment), and thus (via the funding model for GambleAware) the work was indirectly supported by voluntary contributions to GambleAware from the gambling industry., (© 2024 The Authors.)

Loot boxes are purchasable randomized 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, perhaps driven by a range of overlapping psychological processes (e.g. impulsivity, gambling-related cognitions, etc.) It has also been argued that loot box engagement may have negative influences on player financial and psychological wellbeing. We conducted a pre-registered survey of 1495 loot box purchasing gamers (LB cohort) and 1223 gamers who purchase other, non-randomized game content (nLB cohort). Our survey confirms 15 of our 23 pre-registered hypotheses against our primary outcome (risky loot box engagement), establishing associations with problem gambling, problem gaming, impulsivity, gambling cognitions, experiences of game-related 'flow' and specific 'distraction and compulsion' motivations for purchase. Results with hypotheses concerning potential harms established that risky loot box engagement was negatively correlated with wellbeing and positively correlated with distress. Overall, results indicate that any risks from loot boxes are liable to disproportionately affect various 'at risk' cohorts (e.g. those experiencing problem gambling or video gaming), thereby reiterating calls for policy action on loot boxes., Competing Interests: This work was supported by funding from the charity GambleAware (a UK-based independent charity and strategic commissioner of gambling harm education, prevention, early intervention and treatment), and thus (via the funding model for GambleAware) the work was indirectly supported by voluntary contributions to GambleAware from the gambling industry., (© 2023 The Authors.)

Theories of associative learning often propose that learning is proportional to prediction error, or the difference between expected events and those that occur. Spicer et al. (2020) suggested an alternative, that humans might instead selectively attribute surprising outcomes to cues that they are not confident about, to maintain cue-outcome associations about which they are more confident. Spicer et al. reported three predictive learning experiments, the results of which were consistent with their proposal ("theory protection") rather than a prediction error account (Rescorla, 2001). The four experiments reported here further test theory protection against a prediction error account. Experiments 3 and 4 also test the proposals of Holmes et al. (2019), who suggested a function mapping learning to performance that can explain Spicer et al.'s results using a prediction-error framework. In contrast to the previous study, these experiments were based on inhibition rather than excitation. Participants were trained with a set of cues (represented by letters), each of which was followed by the presence or absence of an outcome (represented by + or -). Following this, a cue that previously caused the outcome (A+) was placed in compound with another cue (B) with an ambiguous causal status (e.g., a novel cue in Experiment 1). This compound (AB-) did not cause the outcome. Participants always learned more about B in the second training phase, despite A always having the greater prediction error. In Experiments 3 and 4, a cue with no apparent prediction error was learned about more than a cue with a large prediction error. Experiment 4 tested participants' relative confidence about the causal status of cues A and B prior to the AB- stage, producing findings that are consistent with theory protection and inconsistent with the predictions of Rescorla, and Holmes et al. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Spicer et al. (2020) reported a series of causal learning experiments in which participants appeared to learn most readily about cues when they were not certain of their causal status and proposed that their results were a consequence of participants' use of theory protection. In the present issue, Chan et al. (2021) present an alternative view, using a modification of Rescorla and Wagner's (1972) influential model of learning. Although the explanation offered by Chan et al. appears very different from that suggested by Spicer et al., there are conceptual commonalities. Here we briefly discuss the similarities and differences of the 2 approaches and agree with Chan et al.'s proposal that the best way to advance the debate will be to test situations in which the 2 theories make differing predictions. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Three experiments were conducted to investigate a possible role for certainty in human causal learning. In these experiments, human participants were initially trained with a set of cues, each of which was followed by the presence or absence of an outcome. In a subsequent training stage, 2 of these cues were trained in a causal compound, and the change in associative strength for each of the cues was compared, using a procedure based on Rescorla (2001). In each experiment, the cues differed in both their causal certainty (on the part of participants) and size of their prediction error (with respect to the outcome). The cue with the larger prediction error was always the cue with the more certain causal status. According to established prediction error models (Bush & Mosteller, 1951; Rescorla, 2001; Rescorla & Wagner, 1972), a larger prediction error should result in a greater updating of associative strength. However, the opposite was observed, as participants always learned more about the cue with the smaller prediction error. A plausible explanation is that participants engaged in a form of theory protection, in which they were resistant to updating their existing beliefs about cues with a certain causal status. Instead, participants appeared to attribute outcomes to cues with a comparatively uncertain causal status, in an apparent violation of prediction error. The potential role of attentional processes (Mackintosh, 1975; Pearce & Hall, 1980) in explaining these results is also discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

In 2 spatial navigation experiments, human participants were asked to find a hidden goal (a WiFi signal) that was located in 1 of the right-angled corners of a kite-shaped (Experiment 1) or a cross-shaped (Experiment 2) virtual environment. Goal location was defined solely with respect to the geometry of the environment. Following this training, in a test conducted in extinction, participants were placed onto the outside of the same environments and asked to locate the WiFi signal. The results of both experiments revealed that participants spent more time searching in regions on the outside of the environments that were closest to where the WiFi signal was located during training. These results are difficult to explain in terms of analyses of spatial navigation and reorientation that emphasize the role of local representational encoding or view matching. Instead, we suggest that these results are better understood in terms of a global representation of the shape of the environment. (PsycINFO Database Record (c) 2019 APA, all rights reserved).