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Methods of analyzing patterns of multimorbidity using network analysis: a scoping review protocol

journal contribution
posted on 2023-05-21, 00:25 authored by Imogen Jones, Fiona CockerFiona Cocker, Matthew JoseMatthew Jose, Michael CharlestonMichael Charleston, Amanda NeilAmanda Neil

Objective: The purpose of this review is to summarize the techniques used for network analysis of multimorbidity to inform development of a standard methodology.

Introduction: There is a growing trend of using network analysis to investigate relationships between chronic illnesses in people with multimorbidities. However, there is currently no recommended approach to calculating and displaying networks of chronic health conditions. This review intends to summarize the current literature to further the development of a standard methodology.

Inclusion criteria: Studies will be included if they investigated the relationships between multiple chronic health conditions without referring to an index condition, using network analysis techniques. Studies using both survey and administrative data will be included. Studies including biological or genomic data sets will not be included as they are out of scope.

Methods: Databases searched will include PubMed (MEDLINE), Science Direct, Scopus, and PsycINFO. All relevant publications will be included provided they were published before October 2020. Publications from all languages will be included where an appropriate translation in English can be obtained. Data extracted will include country of origin, type of data used, measure of association, software used, and notes on any specific points of methodological interest relevant to the review question.

History

Publication title

JBI Evidence Synthesis

Volume

19

Issue

10

Pagination

2857-2862

ISSN

2689-8381

Department/School

Tasmanian School of Medicine

Publisher

Wolters Kluwer

Place of publication

United States

Rights statement

Copyright 2021 JBI

Repository Status

  • Restricted

Socio-economic Objectives

Applied computing; Expanding knowledge in the health sciences

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