David A Kim1, Alison R Hwong1, Derek Stafford2, D Alex Hughes3, A James O'Malley4, James H Fowler5, Nicholas A Christakis6. 1. Interfaculty Initiative in Health Policy, Harvard University, Cambridge, MA, USA. 2. Yale Institute for Network Science, Yale University, New Haven, CT, USA. 3. Department of Political Science, University of California, San Diego, La Jolla, CA, USA. 4. Dartmouth Institute of Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 5. Departments of Political Science and Medical Genetics, University of California, San Diego, La Jolla, CA, USA. 6. Departments of Medicine, Ecology and Evolutionary Biology, Biomedical Engineering, and Sociology, Yale University, New Haven, CT, USA. Electronic address: nicholas.christakis@yale.edu.
Abstract
BACKGROUND: Information and behaviour can spread through interpersonal ties. By targeting influential individuals, health interventions that harness the distributive properties of social networks could be made more effective and efficient than those that do not. Our aim was to assess which targeting methods produce the greatest cascades or spillover effects and hence maximise population-level behaviour change. METHODS: In this cluster randomised trial, participants were recruited from villages of the Department of Lempira, Honduras. We blocked villages on the basis of network size, socioeconomic status, and baseline rates of water purification, for delivery of two public health interventions: chlorine for water purification and multivitamins for micronutrient deficiencies. We then randomised villages, separately for each intervention, to one of three targeting methods, introducing the interventions to 5% samples composed of either: randomly selected villagers (n=9 villages for each intervention); villagers with the most social ties (n=9); or nominated friends of random villagers (n=9; the last strategy exploiting the so-called friendship paradox of social networks). Participants and data collectors were not aware of the targeting methods. Primary endpoints were the proportions of available products redeemed by the entire population under each targeting method. This trial is registered with ClinicalTrials.gov, number NCT01672580. FINDINGS:Between Aug 4, and Aug 14, 2012, 32 villages in rural Honduras (25-541 participants each; total study population of 5773) receivedpublic health interventions. For each intervention, nine villages (each with 1-20 initial target individuals) were randomised, using a blocked design, to each of the three targeting methods. In nomination-targeted villages, 951 (74·3%) of 1280 available multivitamin tickets were redeemed compared with 940 (66·2%) of 1420 in randomly targeted villages and 744 (61·0%) of 1220 in indegree-targeted villages. All pairwise differences in redemption rates were significant (p<0·01) after correction for multiple comparisons. Targeting nominated friends increased adoption of the nutritional intervention by 12·2% compared with random targeting (95% CI 6·9-17·9). Targeting the most highly connected individuals, by contrast, produced no greater adoption of either intervention, compared with random targeting. INTERPRETATION: Introduction of a health intervention to the nominated friends of random individuals can enhance that intervention's diffusion by exploiting intrinsic properties of human social networks. This method has the additional advantage of scalability because it can be implemented without mapping the network. Deployment of certain types of health interventions via network targeting, without increasing the number of individuals targeted or the resources used, could enhance the adoption and efficiency of those interventions, thereby improving population health. FUNDING: National Institutes of Health, The Bill & Melinda Gates Foundation, Star Family Foundation, and the Canadian Institutes of Health Research.
RCT Entities:
BACKGROUND: Information and behaviour can spread through interpersonal ties. By targeting influential individuals, health interventions that harness the distributive properties of social networks could be made more effective and efficient than those that do not. Our aim was to assess which targeting methods produce the greatest cascades or spillover effects and hence maximise population-level behaviour change. METHODS: In this cluster randomised trial, participants were recruited from villages of the Department of Lempira, Honduras. We blocked villages on the basis of network size, socioeconomic status, and baseline rates of water purification, for delivery of two public health interventions: chlorine for water purification and multivitamins for micronutrient deficiencies. We then randomised villages, separately for each intervention, to one of three targeting methods, introducing the interventions to 5% samples composed of either: randomly selected villagers (n=9 villages for each intervention); villagers with the most social ties (n=9); or nominated friends of random villagers (n=9; the last strategy exploiting the so-called friendship paradox of social networks). Participants and data collectors were not aware of the targeting methods. Primary endpoints were the proportions of available products redeemed by the entire population under each targeting method. This trial is registered with ClinicalTrials.gov, number NCT01672580. FINDINGS: Between Aug 4, and Aug 14, 2012, 32 villages in rural Honduras (25-541 participants each; total study population of 5773) received public health interventions. For each intervention, nine villages (each with 1-20 initial target individuals) were randomised, using a blocked design, to each of the three targeting methods. In nomination-targeted villages, 951 (74·3%) of 1280 available multivitamin tickets were redeemed compared with 940 (66·2%) of 1420 in randomly targeted villages and 744 (61·0%) of 1220 in indegree-targeted villages. All pairwise differences in redemption rates were significant (p<0·01) after correction for multiple comparisons. Targeting nominated friends increased adoption of the nutritional intervention by 12·2% compared with random targeting (95% CI 6·9-17·9). Targeting the most highly connected individuals, by contrast, produced no greater adoption of either intervention, compared with random targeting. INTERPRETATION: Introduction of a health intervention to the nominated friends of random individuals can enhance that intervention's diffusion by exploiting intrinsic properties of human social networks. This method has the additional advantage of scalability because it can be implemented without mapping the network. Deployment of certain types of health interventions via network targeting, without increasing the number of individuals targeted or the resources used, could enhance the adoption and efficiency of those interventions, thereby improving population health. FUNDING: National Institutes of Health, The Bill & Melinda Gates Foundation, Star Family Foundation, and the Canadian Institutes of Health Research.
Authors: Jennifer L Gardy; James C Johnston; Shannan J Ho Sui; Victoria J Cook; Lena Shah; Elizabeth Brodkin; Shirley Rempel; Richard Moore; Yongjun Zhao; Robert Holt; Richard Varhol; Inanc Birol; Marcus Lem; Meenu K Sharma; Kevin Elwood; Steven J M Jones; Fiona S L Brinkman; Robert C Brunham; Patrick Tang Journal: N Engl J Med Date: 2011-02-24 Impact factor: 91.245
Authors: Jay J Van Bavel; Katherine Baicker; Paulo S Boggio; Valerio Capraro; Aleksandra Cichocka; Mina Cikara; Molly J Crockett; Alia J Crum; Karen M Douglas; James N Druckman; John Drury; Oeindrila Dube; Naomi Ellemers; Eli J Finkel; James H Fowler; Michele Gelfand; Shihui Han; S Alexander Haslam; Jolanda Jetten; Shinobu Kitayama; Dean Mobbs; Lucy E Napper; Dominic J Packer; Gordon Pennycook; Ellen Peters; Richard E Petty; David G Rand; Stephen D Reicher; Simone Schnall; Azim Shariff; Linda J Skitka; Sandra Susan Smith; Cass R Sunstein; Nassim Tabri; Joshua A Tucker; Sander van der Linden; Paul van Lange; Kim A Weeden; Michael J A Wohl; Jamil Zaki; Sean R Zion; Robb Willer Journal: Nat Hum Behav Date: 2020-04-30