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Exploring International Views on Key Concepts for Mass-gathering Health through a Delphi Process

Published online by Cambridge University Press:  23 May 2016

Malinda Steenkamp
Affiliation:
Flinders University, World Health Organization Collaborating Centre for Mass Gatherings and High Visibility/High Consequence Events, Adelaide, Australia Torrens Resilience Institute, Flinders University, Adelaide, Australia
Alison E. Hutton
Affiliation:
Flinders University, World Health Organization Collaborating Centre for Mass Gatherings and High Visibility/High Consequence Events, Adelaide, Australia School of Nursing and Midwifery, Flinders University, Adelaide, Australia
Jamie C. Ranse
Affiliation:
University of Canberra, Australian Capital Territory, Australia
Adam Lund
Affiliation:
Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia, Canada School of Nursing, University of British Columbia, Vancouver, British Columbia, Canada Justice Institute of British Columbia, British Columbia, Canada
Sheila A. Turris
Affiliation:
Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia, Canada School of Nursing, University of British Columbia, Vancouver, British Columbia, Canada Justice Institute of British Columbia, British Columbia, Canada
Ron Bowles
Affiliation:
Justice Institute of British Columbia, British Columbia, Canada
Katherine Arbuthnott
Affiliation:
London School of Hygiene and Tropical Medicine, London, United Kingdom
Paul A. Arbon
Affiliation:
Flinders University, World Health Organization Collaborating Centre for Mass Gatherings and High Visibility/High Consequence Events, Adelaide, Australia Torrens Resilience Institute, Flinders University, Adelaide, Australia School of Nursing and Midwifery, Flinders University, Adelaide, Australia
Corresponding

Abstract

Introduction

The science underpinning mass-gathering health (MGH) is developing rapidly. However, MGH terminology and concepts are not yet well defined or used consistently. These variations can complicate comparisons across settings. There is, therefore, a need to develop consensus and standardize concepts and data points to support the development of a robust MGH evidence-base for governments, event planners, responders, and researchers. This project explored the views and sought consensus of international MGH experts on previously published concepts around MGH to inform the development of a transnational minimum data set (MDS) with an accompanying data dictionary (DD).

Report

A two-round Delphi process was undertaken involving volunteers from the World Health Organization (WHO) Virtual Interdisciplinary Advisory Group (VIAG) on Mass Gatherings (MGs) and the MG section of the World Association for Disaster and Emergency Medicine (WADEM). The first online survey tested agreement on six key concepts: (1) using the term “MG HEALTH;” (2) purposes of the proposed MDS and DD; (3) event phases; (4) two MG population models; (5) a MGH conceptual diagram; and (6) a data matrix for organizing MGH data elements. Consensus was defined as ≥80% agreement. Round 2 presented five refined MGH principles based on Round 1 input that was analyzed using descriptive statistics and content analysis. Thirty-eight participants started Round 1 with 36 completing the survey and 24 (65% of 36) completing Round 2. Agreement was reached on: the term “MGH” (n=35/38; 92%); the stated purposes for the MDS (n=38/38; 100%); the two MG population models (n=31/36; 86% and n=30/36; 83%, respectively); and the event phases (n=34/36; 94%). Consensus was not achieved on the overall conceptual MGH diagram (n=25/37; 67%) and the proposed matrix to organize data elements (n=28/37; 77%). In Round 2, agreement was reached on all the proposed principles and revisions, except on the MGH diagram (n=18/24; 75%).

Discussion/Conclusions

Event health stakeholders require sound data upon which to build a robust MGH evidence-base. The move towards standardization of data points and/or reporting items of interest will strengthen the development of such an evidence-base from which governments, researchers, clinicians, and event planners could benefit. There is substantial agreement on some broad concepts underlying MGH amongst an international group of MG experts. Refinement is needed regarding an overall conceptual diagram and proposed matrix for organizing data elements.

Steenkamp M , Hutton AE , Ranse JC , Lund A , Turris SA , Bowles R , Arbuthnott K , Arbon PA . Exploring International Views on Key Concepts for Mass-gathering Health through a Delphi Process. Prehosp Disaster Med. 2016;31(4):443453.

Type
Special Report
Copyright
© World Association for Disaster and Emergency Medicine 2016 

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References

1. World Health Organization. Public Health for Mass Gatherings: Key Considerations. Geneva, Switzerland: World Health Organization; 2015: 1-177.Google Scholar
2. Arbon, P. Mass-gathering medicine: a review of the evidence and future directions for research. Prehosp Disaster Med. 2007;22(2):131-135.CrossRefGoogle ScholarPubMed
3. Lund, A, Turris, SA, Bowles, R, et al. Mass-gathering health research foundational theory: part 1 - population models for mass gatherings. Prehosp Disaster Med. 2014;29(6):648-654.Google ScholarPubMed
4. Ranse, J, Hutton, A, Turris, S, et al. Enhancing the minimum data set for mass-gathering research and evaluation: an integrative literature review. Prehosp Disaster Med. 2014;29(3):280-289.CrossRefGoogle Scholar
5. Arbon, P, Cusack, L, Verdonk, N. Mass gathering public health and emergency medicine literature review: levels of evidence. Australasian Journal of Paramedicine. 2013;10(1):1-5.Google Scholar
6. Turris, SA, Steenkamp, M, Lund, A, et al. International consensus on key concepts and data definitions for mass gathering health: process and progress. Prehosp Disaster Med. In press.Google ScholarPubMed
7. Keeney, S, Hasson, F, McKenna, H. “Analyzing data from a Delphi and reporting results.” In: Keeney S, McKenna H, (eds). The Delphi Technique in Nursing and Health Research. Malaysia: Wiley-Blackwell; 2011: 84-95.CrossRefGoogle Scholar
8. Homer, J, Hirsch, G. System dynamics modeling for public health: background and opportunities. Am J Public Health. 2006;96(3):452-458.CrossRefGoogle ScholarPubMed
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