Research Expertise and the Framework of Harms: Social Network Analysis, Phase One

In 2019, the Gambling Commission announced a National Strategy to Reduce Gambling Harms. Underlying the strategy is the Framework of Harms, outlined in Measuring gambling-related harms: A framework for action. "The Framework" adopts a public health approach to address gambling-related harm in Great Britain across multiple levels of measurement. It comprises three primary factors and nine related subfactors. To advance the National Strategy, all componentsneed to be supported by a strong evidence base. This report examines existing research expertise relevant to the Framework amongacademics based in the UK. The aim is to understand the extent to which the Framework factors and subfactors have been studied in order to identify gaps in expertise and provide evidence for decision making thatisrelevant to gambling harms research priorities. A social network analysis identified coauthor networks and alignment of research output with the Framework. The search strategy was limited to peer-reviewed items and covered the 12-year period from 2008 to 2019. Articles were selected using a Web of Science search. Of the 1417 records identified in the search, the dataset was refined to include only those articles that could be assigned to at least one Framework factor (n = 279). The primary factors and subfactors are: Resources:Work and Employment, Money and Debt, Crime;Relationships:Partners, Families and Friends, Community; and Health:Physical Health, Psychological Distress, and Mental Health. We used Gephi software to create visualisations reflecting degree centrality (number of coauthor networks) so that each factor and subfactor could be assessed for the density of research expertise and patterns of collaboration among coauthors. The findings show considerable variation by framework factor in the number of authors and collaborations, suggesting a need to develop additional research capacity to address under-researched areas. The Health factor subcategory of Mental Health comprised almost three-quarters of all citations, with the Resources factor subcategory of Money and Debt a distant second at 12% of all articles. The Relationships factor, comprised of two subfactors, accounted for less than 10%of total articles. Network density varied too. Although there were few collaborative networks in subfactors such as Community or Work and Employment, all Health subfactors showed strong levels of collaboration. Further, some subfactors with a limited number of researchers such as Partners, Families, and Friends and Money and debt had several active collaborations. Some researchers’ had publications that spanned multiple Framework factors. These multiple-factor researchers usually had a wide range of coauthors when compared to those who specialised (with the exception of Mental Health).Others’ collaborations spanned subfactors within a factor area. This was especially notable forHealth. The visualisations suggest that gambling harms research expertise in the UK has considerable room to grow in order to supporta more comprehensive, locally contextualised evidence base for the Framework. To do so, priority harms and funding opportunities will need further consideration. This will require multi-sector and multidisciplinary collaboration consistent with the public health approach underlying the Framework. Future research related to the present analysis will explore the geographic distribution of research activity within the UK, and research collaborations with harms experts internationally.