Theme: Social Science & Policy Research Year: 2022
Factors relating to the prevention of drug-related deaths (DRD) comprise a ‘complex system’; we
need to take account of the complexity of causes, from individual to structural, and non-linear
relationships between variables. Our study takes a broad approach to provide a better
understanding of DRDs in Scotland, to provide key insights, build communication pathways, and
We are in the process of facilitating three stakeholder workshops, following the 6 Steps in Quality
Intervention Development Framework for early-stage intervention development. We started by
using a Critical Systems Heuristic to identify stakeholder groups with diverse knowledge and
expertise. Groups included local/national decision makers, statutory health/social care sectors and
disciplines, third-sector agencies, academics, and people with lived experience. Each workshop
includes structured activities from Systems Science, drawing on Group Model Building. Network
analysis of administrative data from the National Drug-Related Deaths Database (NDRDD) and of
workshop outputs, are used simultaneously in subsequent workshops.
Workshop 1 outputs included diagrams representing multiple interacting influences on DRDs, from
psychosocial to wider community, area-based, political, economic, environmental, and cultural
factors. Each diagram contained between 40 and 128 factors. We have identified several influential
factors that would not be detected in administrative data, e.g. role of power, citizenship,
problematic division of services. The workshop output is currently being combined with network
analysis of the NDRDD for 4,451 drug-related deaths in Scotland (2009-2016), and the results will be
considered at Workshop 2. Workshop 3 aims to gain agreement on key factors that could be
addressed in future intervention development.
The process of collaboratively mapping a system and integrating analysis of administrative data on
DRDs, can help gain insight, develop consensus on key issues, enhance communication, and
ultimately inform decision-making. We will produce a series of action points, including identifying
factors most amenable to change.
Disclosure of Interest Statement:
The authors declare no conflict of interest.