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This study seeks to provide an examination of a health policy network operating in a single, small community along the US‐Mexican border. The purpose of the paper is to discuss why and how this network evolved, and then to present findings on how the network was structured. Analysis will focus especially on agency involvement, or “embeddedness” in the network, and its relationship to attitudes held by network members regarding trust, reputation, and perceived benefit.

Data were collected from 15 public and nonprofit agencies trying to work collaboratively to influence local policy and services regarding the prevention of obesity‐related chronic disease, especially diabetes. Embeddedness was measured in three different ways and both confirmed and unconfirmed networks were assessed. Network analysis methods were utilized as well as nonparametric correlation statistics.

The network was found to be densely connected through unconfirmed linkages, but much less so when these links were confirmed. Strongest findings were found for shared information. Measures of agency embeddedness in the network were strong predictors of agency reputation, but findings for trust and perceived benefit were generally weak.

From a practice perspective, the study points to the problems in building and sustaining community‐based chronic disease health networks, especially in a small community with substantial health needs. The research also contributes to theory on embeddedness and to methodology for collecting and analyzing data on community health networks.

While Chapter 3 highlights contextual conditions that foster the formation of policy networks, Chapter 5 highlights contextual conditions that impede the formation of policy networks. The overarching question of this chapter is the following: What are the factors that hinder cross-sectoral arrangements from becoming collaborative in complex policy settings such as low- and middle-income countries with a tradition in centralized policy making? In an attempt to address this question, this study provides a detailed assessment of all cross-sectoral arrangements within the Turkish health sector focusing on the post-2003 period. Within this framework, three types of networks will be examined including (a) consultative networks where stakeholders come together primarily to legitimize certain government policies within national level health policy platforms; (b) cluster networks where stakeholder interaction falls short of becoming collaborative due to diverging interests and persistent competition at the regional level; and (c) patronage networks where governmental actors and a selected number of NGOs linked by clientelism serve as a bridge between the ruling party and its constituency at the community level. Unlike policy networks, these actor constellations observed at different levels of governance do not serve the purpose of policy collaboration. On the contrary, they have the potential to trigger politicization, fragmentation, and even polarization at the social level, especially through the distribution of selective benefits. Ultimately, this chapter aims to rise to the challenge of policy collaboration by assessing the impediments to network collaboration based on insights from the Turkish case.

Online health communities can be both supportive and vulnerable and highly rely on stable engagement from core members. Understanding the factors affecting core member churn is vital. This study examines a hair-loss-related online health community, taking a meso-level community approach. It investigates how users’ potential social capital, proactive social engagement and received social support in the community influence their churn.

This study collected the complete dataset spanning 13 years from a hair-loss-related online health community in mainland China. It identified 4,270 core users with over ten posted messages each, along with their associated text. Social network analysis and survival analysis were then used to calculate user node centrality and create a hazard model for user churn.

The findings indicate that increased social capital and social support can help prevent churn. However, higher social engagement alone does not directly reduce users’ likelihood to withdraw. Instead, users are more likely to stay in the community when highly engaged if they also receive substantial social support. Social support emerges as a critical factor in this mechanism.

This study innovatively adopts a meso-level community perspective, investigating user churn within an online health community for individuals with a self-limiting condition – hair loss. The research probes the interactive effects of user engagement and social support on churn within the online health community. Advice on sustaining member participation is given based on the findings as well as Chinese culture.

Corporate foundations – entities established to regularize corporate giving at an arm’s length removed from the firm – command substantial resources, root companies in the nonprofit sectors of their host communities, indirectly augment perceptions of corporate responsibility, and help firms to deflect controversies in an attentive global media environment. Despite these important roles, relatively little research has examined the institutional and strategic factors that influence such proximate charitable giving by firms. Using systematic data on foundations linked to S&P 3000 firms in the health sector – a growing domain in which public trust in high-stakes products and services is critical – fixed-effects models illustrate the primary role of network influences on giving: corporate foundations give substantially more in years following higher contributions by other (noncorporate) foundations in the health sector in a firm’s headquarters locality and also following increased contributions by industry peers through their corporate foundations. Giving also appears to reflect strategic reputational concerns, in that foundation contributions increase significantly following controversies associated with the corporate parent’s products and/or services. By contrast, giving tends to decline as the presence of outside directors on a firm’s board increases, as well as when firms carry heavier debt loads. Combined, these findings suggest that corporate foundations serve as a strategic proxy for the firm, reflecting both a company's position in community and interfirm networks while also mitigating the threat of reputational challenges.

Networked forms of organizing in health care are increasingly viewed as an effective means of addressing “wicked”, multifaceted health and societal challenges. This is because networks attempt to address these challenges via collaborative approaches in which diverse stakeholders together define the problem(s) and implement solutions. Consequently, there has been a sharp increase in the number and types of networks used in health care. Despite this growth, our understanding of how these networks are governed has not kept pace. The purpose of this chapter is to chart a research agenda for scholars who are interested in studying health care network governance (i.e., the systems of rules and decision-making within networks), which is of particular importance in deliberate networks between organizations. We do so based on our knowledge of the literature and interviews with subject matter experts, both of which are used to identify core network governance concepts that represent gaps in our current knowledge. Our analysis identified various conceptualizations of networks and of their governance, as well as four primary knowledge gaps: “bread and butter” studies of network governance in health care, the role of single organizations in managing health care networks, governance through the life-cycle stages of health care networks, and governing across the multiple levels of health care networks. We first seek to provide some conceptual clarity around networks and network governance. Subsequently, we describe some of the challenges that researchers may confront while addressing the associated knowledge gaps and potential ways to overcome these challenges.

A question of interest is whether online social networks are effective in promoting behavioral changes and weight loss. The purpose of this paper is to examine the contagion effect of an online buddy network on individuals’ self-monitoring behavior.

This study collects data from an online weight-loss community and constructs an online buddy network. This study compares the effects of the network structure of the buddy network and the actor attributes when predicting self-monitoring performance by employing the auto-logistic actor attribute models.

This study confirms the contagion effect on weigh-in behavior in the online buddy network. The contagion effect is significantly predictive when controlling for actor attribute and other network structure effects.

There is limited evidence that one’s weight-related behavior can be affected by online social contacts. This study contributes to the literature on peer influence on health by examining the contagion effect on weight-related behavior between online buddies. The findings can assist in designing peer-based interventions to harness influence from online social contacts for weight loss.

The health equity and prosperity of communities is closely linked to the effectiveness and success of local health coalitions. Social network analysis (SNA) is one mechanism to quantify and understand the factors leading to collaboration and effectiveness within these coalitions. This study aims to investigate network characteristics associated with perceived success and satisfaction in a health coalition and determine significant factors related to organizational collaborations.

This study examined the Olympic Peninsula Healthy Community Coalition (OPHCC) which aims to prevent chronic disease in rural Clallam County, Washington. Representatives (n = 21) from member organizations (n = 18) were asked to report on organization characteristics, perceived satisfaction in coalition activities, perceived success toward coalition's mission, and collaborations with other organizations in the coalition. Multilevel modeling used to analyze whether an organization's position within the coalition network was associated with their perceived satisfaction and perceived success. Exponential random graph modeling was used to examine what factors may impact collaboration ties between coalition members.

Organization representatives reported a total of 252 collaboration ties. In multilevel models, organization characteristics and network centrality scores accounted for between 61 and 68% of variance displayed in satisfaction scores and 45–61% of variance in perceived success scores. Exponential random graph modeling revealed activity level, for-profit status, and transitivity as significant factors in collaborative tie presence.

Encouraging consistent active participation, a balance of organizational type, and projects which require more than two collaborators may provide an environment for collaborative ties between organizations.

This chapter focuses on community and social group networks. All six facets of knowledge networks are described. The importance of three of the six facets is called out, including geography, domain, and the messages exchanged across the network. The authors provide profiles of five networks, including family networks, neighborhood networks, issue and support networks, community organization networks, gangs and criminal networks, and sports and gaming networks.

The purpose of this paper is to measure the spatial accessibility of primary healthcare facility in Ghanaian rural areas, by determining the barriers to healthcare accessibilities in the Amansie Central District.

Both network and proximity analyses were performed on the digitized data such as road networks, settlements, population, district boundary, natural resources (rivers, streams and forest) and site location (health facilities). To quantify the population who have access to healthcare the authors used the Ghana Health Service access criteria that health facility should be accessible to an estimated population within 8 km radius from the facility.

The overall mean distance to the nearest health facility in the district was 8.9 km. Fiankoma sub-district recorded the highest mean distance whereas Tweapease sub-district recorded the least. In general, 31.2 percent of the district population has no access to healthcare facility. Transportation was identified to be one of the major hindrances to healthcare accessibility and this was as a result of poor road network in the district.

The study was restricted to the Amansie Central District of Ghana. This limits the extent of generalization of results.

The study proposed additional sites for siting new health facilities base on criteria such as population, distance, centrality and existing infrastructural development. This will consequently improve healthcare accessibility and utilization by increasing total coverage closer to 100 percent.

The purpose of this paper is to describe the structure and impact of a Queensland Research Support Network (RSN) in emergency medicine (EM).

This paper presents a descriptive summary of EM networks, network evaluations and the structure and development of the Emergency Medicine Foundation’s (EMF) RSN in Queensland, including an observational pre- and post-study of research metrics.

In two years, the RSN supported 33 Queensland emergency departments (EDs), of which 14 developed research strategies. There was an increase in research active clinicians, from 23 in 2015 to 181 in 2017. Collaborator engagement increased from 9 in 2015 to 276 in 2017 as did the number of research presentations, from 6 in 2015 to 61 in 2017. EMF experienced a growth in new researchers, with new investigators submitting approximately 60 per cent of grant applications in 2016 and 2017. EMF also received new applications from a further three HHS (taking EMF-funded research activity from 8 to 11 HHS).

This paper describes changes in KPIs and research metrics, which the authors attribute to the establishment of the RSN. However, it is possible that attribution bias plays a role in the KPI improvements.

This network has actively boosted and expanded EM research capacity and capability in Queensland. It provides services, in the form of on-the-ground managers, to develop novice clinician-researchers, new projects and engage entire EDs. This model may be replicated nationwide but requires funding commitment.

The RSN improves front-line clinician research capacity and capability and increases research activity and collaborations with clear community outcomes. Collaborations were extended to community, primary health networks, non-government organisations, national and international researchers and academic institutions. Evaluating and measuring a network’s benefits are difficult, but it is likely that evaluations will help networks obtain funding.