Effect of Peer Education on Stroke Prevention: The Prevent Recurrence of All Inner-City Strokes Through Education Randomized Controlled Trial

Background and Purpose—Efforts to reduce disparities in recurrent stroke among Black and Latino stroke survivors have met with limited success. We aimed to determine the effect of peer education on secondary stroke prevention among predominantly minority stroke survivors. Methods—Between 2009 and 2012, we enrolled 600 stroke or transient ischemic attack survivors from diverse, low-income communities in New York City into a 2-arm randomized clinical trial that compared a 6 week (1 session/week), peer-led, community-based, stroke prevention self-management group workshop (N=301) to a wait-list control group (N=299). The primary outcome was the proportion with a composite of controlled blood pressure (<140/90 mm Hg), low-density lipoprotein cholesterol <100 mg/dL, and use of antithrombotic medications at 6 months. Secondary outcomes included control of the individual stroke risk factors. All analyses were by intent-to-treat. Results—There was no difference in the proportion of intervention and control group participants achieving the composite outcome (34% versus 34%; P=0.98). The proportion with controlled blood pressure at 6 months was greater in the intervention group than in the control group (76% versus 67%; P=0.02). This corresponded to a greater change in systolic blood pressure in the intervention versus control group (−3.63 SD, 19.81 mm Hg versus +0.34 SD, 23.76 mm Hg; P=0.04). There were no group differences in the control of cholesterol or use of antithrombotics. Conclusions—A low-cost peer education self-management workshop modestly improved blood pressure, but not low-density lipoprotein cholesterol or antithrombotic use, among stroke and transient ischemic attack survivors from vulnerable, predominantly minority urban communities

Exploiting social influence to magnify population-level behaviour change in maternal and child health: study protocol for a randomised controlled trial of network targeting algorithms in rural Honduras

Introduction: Despite global progress on many measures of child health, rates of neonatal mortality remain high in the developing world. Evidence suggests that substantial improvements can be achieved with simple, low-cost interventions within family and community settings, particularly those designed to change knowledge and behaviour at the community level. Using social network analysis to identify structurally influential community members and then targeting them for intervention shows promise for the implementation of sustainable community-wide behaviour change. Methods and analysis We will use a detailed understanding of social network structure and function to identify novel ways of targeting influential individuals to foster cascades of behavioural change at a population level. Our work will involve experimental and observational analyses. We will map face-to-face social networks of 30 000 people in 176 villages in Western Honduras, and then conduct a randomised controlled trial of a friendship-based network-targeting algorithm with a set of well-established care interventions. We will also test whether the proportion of the population targeted affects the degree to which the intervention spreads throughout the network. We will test scalable methods of network targeting that would not, in the future, require the actual mapping of social networks but would still offer the prospect of rapidly identifying influential targets for public health interventions. Ethics and dissemination The Yale IRB and the Honduran Ministry of Health approved all data collection procedures (Protocol number 1506016012) and all participants will provide informed consent before enrolment. We will publish our findings in peer-reviewed journals as well as engage non-governmental organisations and other actors through venues for exchanging practical methods for behavioural health interventions, such as global health conferences. We will also develop a ‘toolkit’ for practitioners to use in network-based intervention efforts, including public release of our network mapping software. Trial registration number NCT02694679; Pre-results

Life after Stroke in an Urban Minority Population: A Photovoice Project

Stroke is a leading cause of disability in the United States and disproportionately affects minority populations. We sought to explore the quality of life in urban, minority stroke survivors through their own photos and narratives. Using the Photovoice method, seventeen stroke survivors were instructed to take pictures reflecting their experience living with and recovering from stroke. Key photographs were discussed in detail; participants brainstormed ways to improve their lives and presented their work in clinical and community sites. Group discussions were recorded, transcribed, and coded transcripts were reviewed with written narratives to identify themes. Participants conveyed recovery from stroke in three stages: learning to navigate the initial physical and emotional impact of the stroke; coping with newfound physical and emotional barriers; and long-term adaptation to physical impairment and/or chronic disease. Participants navigated this stage-based model to varying degrees of success and identified barriers and facilitators to this process. Barriers included limited access for disabled and limited healthy food choices unique to the urban setting; facilitators included presence of social support and community engagement. Using Photovoice, diverse stroke survivors were able to identify common challenges in adapting to life after stroke and important factors for recovery of quality of life

Using Trellis software to enhance high-quality large-scale network data collection in the field

© 2021 The Authors Trellis is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use Trellis to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate Trellis’ ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location

Exploiting social influence to magnify population-level behaviour change in maternal and child health: study protocol for a randomised controlled trial of network targeting algorithms in rural Honduras.

IntroductionDespite global progress on many measures of child health, rates of neonatal mortality remain high in the developing world. Evidence suggests that substantial improvements can be achieved with simple, low-cost interventions within family and community settings, particularly those designed to change knowledge and behaviour at the community level. Using social network analysis to identify structurally influential community members and then targeting them for intervention shows promise for the implementation of sustainable community-wide behaviour change.Methods and analysisWe will use a detailed understanding of social network structure and function to identify novel ways of targeting influential individuals to foster cascades of behavioural change at a population level. Our work will involve experimental and observational analyses. We will map face-to-face social networks of 30 000 people in 176 villages in Western Honduras, and then conduct a randomised controlled trial of a friendship-based network-targeting algorithm with a set of well-established care interventions. We will also test whether the proportion of the population targeted affects the degree to which the intervention spreads throughout the network. We will test scalable methods of network targeting that would not, in the future, require the actual mapping of social networks but would still offer the prospect of rapidly identifying influential targets for public health interventions.Ethics and disseminationThe Yale IRB and the Honduran Ministry of Health approved all data collection procedures (Protocol number 1506016012) and all participants will provide informed consent before enrolment. We will publish our findings in peer-reviewed journals as well as engage non-governmental organisations and other actors through venues for exchanging practical methods for behavioural health interventions, such as global health conferences. We will also develop a 'toolkit' for practitioners to use in network-based intervention efforts, including public release of our network mapping software.Trial registration numberNCT02694679; Pre-results