Represent: A community engagement roadmap to improve participant representation in cancer early detection research: An Oregon case study

INTRODUCTION: While authentic and sustained community involvement in the research process is critically important to making new technologies and interventions effective and socially acceptable, there is uneven participation across sociodemographic, racial, and ethnic communities in many research areas, including cancer early detection research. Currently, 18% of cancer in the United States impacts Hispanics and Latinos, this population accounts for < 10% of research participants. Understanding barriers and facilitators to cancer early detection research is imperative to the ultimate success of this research. Therefore, the objectives of this study were to: understand Hispanic and Latino community perspectives in participation in cancer early detection research; and identify sustainable and mutually beneficial approaches to community engagement and involvement. METHODS: The Oregon Case Study, led by Oregon Health & Science University's Community Outreach, Research and Engagement (CORE) in partnership with colleagues at Vocal, a partnership between Manchester University NHS Foundation Trust and the University of Manchester and Cambridge University, adopted a participatory research approach to better understand participation in cancer early detection research from the perspectives of Oregon's Hispanic and Latino community members. We implemented two evidence-based community engagement models, the Community Engagement Studio and the Community Readiness Assessment Model. Using a facilitated format prescribed by each community engagement model, community members helped us to answer two research questions: (1) What methods help us increase participation of underrepresented communities in cancer early detection research?; and (2) How can we build trust between researchers and underrepresented communities within cancer early detection research? Quantitative (i.e., descriptive statistic) and qualitative (i.e., thematic analysis) analytic methods were used to measure and assess community knowledge, leadership, beliefs, and resources regarding participation in cancer early detection research. RESULTS: A total of 36 Hispanic and Latino community members participated in the two community engagement models. We identified three emergent themes pertaining to participation in cancer early detection research that include: low-level awareness of cancer early detection research and opportunities for research participation, structural barriers to research participation, and uncertainty of the benefits of research participation. CONCLUSION: Our approach, using two evidence-based community engagement models, yielded valuable insights about perceptions of research participation for Hispanic and Latino community members. These findings, synthesized into three key themes, led to actionable recommendations to increase research participation

Assessing Health Beliefs about Colonoscopy

The purpose of this study was to assess by questionnaire health beliefs related to colorectal cancer screening ( colonoscopy) in a population 50 years of age and older. The Health Belief Model provided the theoretical framework for data collection. This study was a non-experimental exploratory survey. A total of 42 subjects (31% male and 69% female) completed a 14-item questionnaire that covered psychological factors including health beliefs. Descriptive statistics were used for data analysis. Results of this study shows there is a need for appropriate health education to trigger people to take preventive action ( colonoscopy). Community based health education programs should be designed to induce behavioral change, by teaching the client the benefits of prevention and early detection of colorectal cancer, to which the client is susceptible. Future health education programs guided by this research will greatly contribute to the reduction of highly preventable deaths from colorectal cancer while lowering the enormous cost of treating this condition

Viewpoint Discovery and Understanding in Social Networks

The Web has evolved to a dominant platform where everyone has the opportunity to express their opinions, to interact with other users, and to debate on emerging events happening around the world. On the one hand, this has enabled the presence of different viewpoints and opinions about a - usually controversial - topic (like Brexit), but at the same time, it has led to phenomena like media bias, echo chambers and filter bubbles, where users are exposed to only one point of view on the same topic. Therefore, there is the need for methods that are able to detect and explain the different viewpoints. In this paper, we propose a graph partitioning method that exploits social interactions to enable the discovery of different communities (representing different viewpoints) discussing about a controversial topic in a social network like Twitter. To explain the discovered viewpoints, we describe a method, called Iterative Rank Difference (IRD), which allows detecting descriptive terms that characterize the different viewpoints as well as understanding how a specific term is related to a viewpoint (by detecting other related descriptive terms). The results of an experimental evaluation showed that our approach outperforms state-of-the-art methods on viewpoint discovery, while a qualitative analysis of the proposed IRD method on three different controversial topics showed that IRD provides comprehensive and deep representations of the different viewpoints

Local Disease Concepts Relevant to the Design of a Community-Based Surveillance Program for Influenza in Rural Guatemala

Background Early detection of emergent influenza strains is a global health priority. However, maintaining active surveillance is economically and logistically challenging. While community-based surveillance is an attractive alternative, design and operation of an effective epidemiological surveillance program requires community engagement that can be linked to public health reporting and response. We report the results of a study in rural Guatemalan communities aimed at identifying opportunities for and barriers to community engagement in disease surveillance. Methods Using an ethnographic approach followed by a descriptive cross-sectional survey, we documented local terms and ideas about animal illnesses, including the possibility of animal-human transmission. Results The community perceived disease causation principally in terms of changes in the physical environment and weather and categorized illnesses using local terminology based on observable clinical signs. Knowledge about prevention and treatment was derived predominantly from local networks of family and friends without evidence of professionally-based knowledge being regularly introduced into the community. Conclusions Bridging the divide between professional and community-based descriptive disease terminology, incorporating animal and human health responsiveness to common illnesses, and providing professional knowledge into the community-based networks were identified as addressable challenges to effective implementation of community-based surveillance

A qualitative meta-synthesis: public health nurses role in the identification and management of perinatal mental health problems

Aim: To report findings of a systematic review and meta-synthesis of qualitative studies exploring public health nurses’ perceptions and experiences of identifying and managing women with perinatal mental health (PMH) problems. Background: Public health nurses play a key role in supporting women who experience PMH problems and several qualitative studies have explored their role. Design: Systematic review and meta-synthesis. Data sources: A comprehensive search was developed and multiple databases were searched from 2000–2015. Review methods: Studies that employed qualitative methods to explore experiences of public health nurses in identifying and managing women with PMH problems were included. Two reviewers independently assessed the methodological quality of studies. Themes, concepts and interpretations were extracted and synthesized using the process of thematic analysis. Results: Fifteen papers including 14 unique qualitative studies were included. Two overarching themes were identified: ‘conceptualization and detection of PMH problems’ and ‘barriers and facilitators to management’. The former of these comprised several subthemes including the use of formal screening tools vs. clinical intuition and challenges encountered in detection. The latter theme, barriers to management included availability of referral pathways and time. In terms of facilitators, training, public health nursing interventions, support groups and referral pathways were identified as factors that optimize management. Conclusions: Public health nurses use a variety of methods to identify women with PMH problems. However, several support structures are needed to optimize management including access to appropriate referral pathways, support groups and relationship continuity

Exploring pig trade patterns to inform the design of risk-based disease surveillance and control strategies

An understanding of the patterns of animal contact networks provides essential information for the design of risk-based animal disease surveillance and control strategies. This study characterises pig movements throughout England and Wales between 2009 and 2013 with a view to characterising spatial and temporal patterns, network topology and trade communities. Data were extracted from the Animal and Plant Health Agency (APHA)’s RADAR (Rapid Analysis and Detection of Animal-related Risks) database, and analysed using descriptive and network approaches. A total of 61,937,855 pigs were moved through 872,493 movements of batches in England and Wales during the 5-year study period. Results show that the network exhibited scale-free and small-world topologies, indicating the potential for diseases to quickly spread within the pig industry. The findings also provide suggestions for how risk-based surveillance strategies could be optimised in the country by taking account of highly connected holdings, geographical regions and time periods with the greatest number of movements and pigs moved, as these are likely to be at higher risk for disease introduction. This study is also the first attempt to identify trade communities in the country, information which could be used to facilitate the pig trade and maintain disease-free status across the country in the event of an outbreak

Strategic Pest Management Booklets for Farmers in Kaffrine, Senegal

abstract: When Kaffrine, Senegal, is faced with the threat of a locust plague, farmers tend to struggle with determining what actions and when they should take place to prevent a plague from occurring. The inability of farmers to readily identify the early threats of a locust plague is a primary issue that has been affecting communities in Kaffrine for millennia. Locust plagues affect the functionality of Senegal’s ecosystems, the welfare of its social systems, and the peoples’ economic opportunities. The project focuses on the creation of 300 pest identification booklets that provide five villages in Kaffrine the proper education to prevent locust plagues from forming. I have partnered with the Global Locust Initiative (GLI) to help make these booklets come to fruition as the booklets target the lack of early detection awareness that is at the root of locust plagues. By providing the villages with these booklets, the farmers and community members, will be more educated on how to identify and act on the early threats of a plague. Additional outcomes of creating these booklets are as follows: improved well-being of the farming community, increased millet yields, and enhanced global food system sustainability. As locusts are a migratory pest, it is recommended that more stakeholders are provided the proper educational material to help them identify the early threats of a locust plague to prevent negative externalities from being imposed on the surrounding ecology, individuals, and agriculture

Discourse network analysis: policy debates as dynamic networks

Political discourse is the verbal interaction between political actors. Political actors make normative claims about policies conditional on each other. This renders discourse a dynamic network phenomenon. Accordingly, the structure and dynamics of policy debates can be analyzed with a combination of content analysis and dynamic network analysis. After annotating statements of actors in text sources, networks can be created from these structured data, such as congruence or conflict networks at the actor or concept level, affiliation networks of actors and concept stances, and longitudinal versions of these networks. The resulting network data reveal important properties of a debate, such as the structure of advocacy coalitions or discourse coalitions, polarization and consensus formation, and underlying endogenous processes like popularity, reciprocity, or social balance. The added value of discourse network analysis over survey-based policy network research is that policy processes can be analyzed from a longitudinal perspective. Inferential techniques for understanding the micro-level processes governing political discourse are being developed

Evaluating deterrents of illegal behaviour in conservation: Carnivore killing in rural Taiwan

Rules restricting resource use are ubiquitous to conservation. Recent increases in poaching of iconic species such as African elephant and rhino have triggered high-profile interest in enforcement. Previous studies have used economic models to explore how the probability and severity of sanctions influence poacher-behaviour. Yet despite evidence that compliance can be substantial when the threat of state-imposed sanctions is low and profits high, few have explored other factors deterring rule-breaking. We use the randomised response technique (RRT) and direct questions to estimate the proportion of rural residents in north-western Taiwan illegally killing wildlife. We then model how potential sources of deterrence: perceived probabilities of detection and punishment, social norms and self-imposed guilt, relate to non-compliant behaviour (reported via RRT). The perceived likelihood of being punished and two types of social norms (injunctive and descriptive) predict behaviour and deter rule-breaking. Harnessing social norms that encourage compliance offers potential for reducing the persecution of threatened species