Using social network analysis to understand multisectoral governance in district-level tobacco control programme implementation in India

Abstract

IntroductionInterest in multisectoral policies has increased, particularly in the context of low-income and middle-income countries and efforts towards Sustainable Development Goals, with greater attention to understand effective strategies for implementation and governance. The study aimed to explore and map the composition and structure of a multisectoral initiative in tobacco control, identifying key factors engaged in policy implementation and their patterns of relationships in local-level networks in two districts in the state of Karnataka, India.MethodsSocial network analysis (SNA) was used to examine the structure of two district tobacco control networks with differences in compliance with the India’s national tobacco control law. The survey was administered to 108 respondents (n=51 and 57) in two districts, producing three distinct network maps about interaction, information-seeking and decision-making patterns within each district. The network measures of centrality, density, reciprocity, centralisation and E-I index were used to understand and compare across the two districts.ResultsMembers from the department of health, especially those in the District Tobacco Control Cell, were the most frequently consulted actors for information as they led district-level networks. The most common departments engaged beyond health were education, police and municipal. District 1’s network displayed high centralisation, with a district nodal officer who exercised a central role with the highest in-degree centrality. The district also exhibited greater density and reciprocity. District 2 showed a more dispersed pattern, where subdistrict health managers had higher betweenness centrality and acted as brokers in the network.ConclusionCollaboration and cooperation among sectors and departments are essential components of multisectoral policy. SNA provides a mechanism to uncover the nature of relationships and key actors in collaborative dynamics. It can be used as a visual learning tool for policy planners and implementers to understand the structure of actual implementation and concentrate their efforts to improve and enhance collaboration.

From theory to practice: The pragmatic value of applying systems thinking and complexity sciences in healthcare

“…Use of social network analysis provides a complex systems methodology for exploring and understanding agency in decision-making. 36…”

“…Idealised processes of care maybe remote from the practice‐based experience, thus not necessarily enacted in real world environments without examination and feedback. Use of social network analysis provides a complex systems methodology for exploring and understanding agency in decision‐making 36 …”

Literature Review: Tinjauan Social Network Analysis Dalam Konteks Climate Change

“…(1) Survei diberikan kepada 108 responden pada dua distrik negara bagian Karnataka, India sehingga menghasilkan tiga peta jaringan berbeda tentang interaksi, pencarian informasi, dan pola pengambilan keputusan (Mondal et al, 2022).…”

“…(1) Mengeksplorasi dan memetakan komposisi dan struktur inisiatif dalam pengendalian tembakau, mengindetifikasi faktor-faktor kunci yang terlibat dalam implemantasi kebijakan serta pola hubungan dalam jaringan tingkat lokal di dua distrik negara bagian Karnataka, India (Mondal et al, 2022).…”

“…(1) Hasil SNA memberikan gambar eksplisit mengenai pemetaan aktor kunci, hubungannya, dan pengambilan keputusan, memberikan wawasan kepada para pemimpin sistem kesehatan mengenai implementasi yang efektif (Mondal et al, 2022).…”