What is the volume, quality and characteristics of evidence relating to the effectiveness and cost-effectiveness of multi-disciplinary occupational health interventions aiming to improve work-related outcomes for employed adults? An evidence and gap map o
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.
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.
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.
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.
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.
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.
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.
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.
Shaw E
，Nunns M
，Spicer SG
，Lawal H
，Briscoe S
，Melendez-Torres GJ
，Garside R
，Liabo K
，Coon JT
... -
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Exposure to hate in online and traditional media: A systematic review and meta-analysis of the impact of this exposure on individuals and communities.
People use social media platforms to chat, search, and share information, express their opinions, and connect with others. But these platforms also facilitate the posting of divisive, harmful, and hateful messages, targeting groups and individuals, based on their race, religion, gender, sexual orientation, or political views. Hate content is not only a problem on the Internet, but also on traditional media, especially in places where the Internet is not widely available or in rural areas. Despite growing awareness of the harms that exposure to hate can cause, especially to victims, there is no clear consensus in the literature on what specific impacts this exposure, as bystanders, produces on individuals, groups, and the population at large. Most of the existing research has focused on analyzing the content and the extent of the problem. More research in this area is needed to develop better intervention programs that are adapted to the current reality of hate.
The objective of this review is to synthesize the empirical evidence on how media exposure to hate affects or is associated with various outcomes for individuals and groups.
Searches covered the period up to December 2021 to assess the impact of exposure to hate. The searches were performed using search terms across 20 databases, 51 related websites, the Google search engine, as well as other systematic reviews and related papers.
This review included any correlational, experimental, and quasi-experimental study that establishes an impact relationship and/or association between exposure to hate in online and traditional media and the resulting consequences on individuals or groups.
Fifty-five studies analyzing 101 effect sizes, classified into 43 different outcomes, were identified after the screening process. Initially, effect sizes were calculated based on the type of design and the statistics used in the studies, and then transformed into standardized mean differences. Each outcome was classified following an exhaustive review of the operational constructs present in the studies. These outcomes were grouped into five major dimensions: attitudinal changes, intergroup dynamics, interpersonal behaviors, political beliefs, and psychological effects. When two or more outcomes from the studies addressed the same construct, they were synthesized together. A separate meta-analysis was conducted for each identified outcome from different samples. Additionally, experimental and quasi-experimental studies were synthesized separately from correlational studies. Twenty-four meta-analyses were performed using a random effects model, and meta-regressions and moderator analyses were conducted to explore factors influencing effect size estimates.
The 55 studies included in this systematic review were published between 1996 and 2021, with most of them published since 2015. They include 25 correlational studies, and 22 randomized and 8 non-randomized experimental studies. Most of these studies provide data extracted from individuals (e.g., self-report); however, this review includes 6 studies that are based on quantitative analysis of comments or posts, or their relationship to specific geographic areas. Correlational studies encompass sample sizes ranging from 101 to 6829 participants, while experimental and quasi-experimental studies involve participant numbers between 69 and 1112. In most cases, the exposure to hate content occurred online or within social media contexts (37 studies), while only 8 studies reported such exposure in traditional media platforms. In the remaining studies, the exposure to hate content was delivered through political propaganda, primarily associated with extreme right-wing groups. No studies were removed from the systematic review due to quality assessment. In the experimental studies, participants demonstrated high adherence to the experimental conditions and thus contributed significantly to most of the results. The correlational and quasi-experimental studies used consistent, valid, and reliable instruments to measure exposure and outcomes derived from well-defined variables. As with the experimental studies, the results from the correlation and quasi-experimental studies were complete. Meta-analyses related to four dimensions were performed: Attitudinal changes, Intergroup dynamics, Interpersonal behaviors, and Psychological effects. We were unable to conduct a meta-analysis for the "Political Beliefs" dimension due to an insufficient number of studies. In terms of attitude changes, exposure to hate leads to negative attitudes (d Ex = 0.414; 95% confidence interval [CI] = 0.005, 0.824; p < 0.05; n = 8 and d corr = 0.322; 95% CI = 0.14, 0.504; p < 0.01; n = 2) and negative stereotypes (d Ex = 0.28; 95% CI = -0.018, 0.586; p < 0.10; n = 9) about individuals or groups with protected characteristics, while also hindering the promotion of positive attitudes toward them (d exp = -0.227; 95% CI = -0.466, 0.011; p < 0.10; n = 3). However, it does not increase support for hate content or political violence. Concerning intergroup dynamics, exposure to hate reduces intergroup trust (d exp = -0.308; 95% CI = -0.559, -0.058; p < 0.05; n = 2), especially between targeted groups and the general population, but has no significant impact on the perception of discrimination among minorities. In the context of Interpersonal behaviors, the meta-analyses confirm a strong association between exposure to hate and victimization (d corr = 0.721; 95% CI = 0.472, 0.97; p < 0.01; n = 3) and moderate effects on online hate speech perpetration (d corr = 0.36; 95% CI = -0.028, 0.754; p < 0.10; n = 2) and offline violent behavior (d corr = 0.47; 95%CI = 0.328, 0.612; p < 0.01; n = 2). Exposure to online hate also fuels more hate in online comments (d = 0.51; 95% CI = 0.034-0.984; p < 0.05; n = 2) but does not seem to affect hate crimes directly. However, there is no evidence that exposure to hate fosters resistance behaviors among individuals who are frequently subjected to it (e.g. the intention to counter-argue factually). In terms of psychological consequences, this review demonstrates that exposure to hate content negatively affects individuals' psychological well-being. Experimental studies indicate a large and significant effect size concerning the development of depressive symptoms due to exposure (d exp = 1.105; 95% CI = 0.797, 1.423; p < 0.01; n = 2). Additionally, a small effect size is observed concerning the link between exposure and reduced life satisfaction(d corr = -0.186; 95% CI = -0.279, -0.093; p < 0.01; n = 3), as well as increased social fear regarding the likelihood of a terrorist attack (d corr = -0.206; 95% CI = 0.147, 0.264; p < 0.01 n = 5). Conversely, exposure to hate speech does not seem to generate or be linked to the development of negative emotions related to its content.
This systematic review confirms that exposure to hate in online and in traditional media has a significant negative impact on individuals and groups. It emphasizes the importance of taking these findings into account for policymaking, prevention, and intervention strategies. Hate speech spreads through biased commentary and perceptions, normalizing prejudice and causing harm. This not only leads to violence, victimization, and perpetration of hate speech but also contributes to a broader climate of hostility. Conversely, this research suggests that people exposed to this type of content do not show increased shock or revulsion toward it. This may explain why it is easily disseminated and often perceived as harmless, leading some to oppose its regulation. Focusing efforts solely on content control may then have a limited impact in driving substantial change. More research is needed to explore these variables, as well as the relationship between hate speech and political beliefs and the connection to violent extremism. Indeed, we know very little about how exposure to hate influences political and extremist views.
Madriaza P
，Hassan G
，Brouillette-Alarie S
，Mounchingam AN
，Durocher-Corfa L
，Borokhovski E
，Pickup D
，Paillé S
... -
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ResearchGate
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