Managing community engagement initiatives in health and social care: lessons learned from Italy and the United Kingdom : Health Care Management Review

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Managing community engagement initiatives in health and social care: lessons learned from Italy and the United Kingdom

Longo, Francesco; Barsanti, Sara; Bonciani, Manila; Bunea, Anita; Zazzera, Angelica

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Health Care Management Review: 1/3 2023 - Volume 48 - Issue 1 - p 2-13
doi: 10.1097/HMR.0000000000000343
  • Open

Abstract

There is a general agreement about the importance of social networks and social capital for health and social care service design and planning (Igalla et al., 2020; Popay et al., 2007). The integration and involvement of volunteers, peers, groups of patients, and social networks with formal health and social care services or programs have bolstered the concept of community engagement initiatives (CEIs). Concrete examples range from self-support groups of peer patients (e.g., addicts) or their caregivers to volunteer aid to the fragile older adults or people with disabilities or to walking groups for older adults. CEIs can also operate in ex post public accountability processes regarding the quality of care involving users, caregivers, and the general community or from an ex ante participatory perspective for service design or redesign (Watt, 1986). This approach recognizes that health and social inclusion are driven by multiple behaviors and different cognitive maps influenced by cultural, economic, social, and environmental variables that are embedded in social networks but which are difficult to address and positively influence. Each local portfolio of social network drivers may have a positive or negative effect on community health and social outcomes. A crucial policy and managerial question thus arises: Are traditional formalized welfare institutions able to recognize and influence these social networks and community drivers in order to promote positive health and social behaviors? There is a growing stream of research documenting the direct relationship between social capital and initiatives that involve community engagement (Igalla et al., 2020), in which social networks are conceived as a core determinant for healthy and inclusive communities. However, determining the features and effectiveness of CEIs to achieve health and social-related outcomes is challenging for both researchers and policy makers. Moreover, as Cyril et al. (2015) underlined, there is a need for innovative frameworks and approaches based on a better understanding of the potential impacts of CEIs on health and well-being. This article thus aims to (a) explore the nature of CEIs in health and social care by conducting an in-depth analysis of 79 CEIs in Italy and the United Kingdom using primary data, specific frameworks developed, and a comparative approach (Stake, 1995) and (b) understand the managerial and primary policy implications derived from the different features of CEIs and their potential social and health impacts. First, we provide a definition of CEIs; then, we discuss their potential benefits in tackling some social and health challenges on the rise in Western countries. A framework to classify CEIs and their different features is then provided, together with the methodology applied to analyze 79 cases. After, we present our empirical evidence, which is then discussed. The last section outlines the strategic policy and managerial implications for local social and health authorities.

A Definition of CEIs Aimed at Improving Health and Social Care

A Definition of CEIs

Initiatives based on community engagement have often been poorly understood. They tend to be on the fringes of mainstream practice, which has largely been dominated by professionally led solutions (South, 2015) based on individual demand services. However, harnessing the “renewable energy” of communities is no longer a “discretionary extra” but instead is key to the sustainability of health and social care services (Maruthappu et al., 2014). In 1997, the Centers for Disease Control and Prevention (CDC) defined community engagement as “the process of working collaboratively with and through groups of people affiliated by geographic proximity, special interest, or similar situations to address issues affecting the well-being of those people.” CDC provided a new guide for understanding community engagement (CDC, 2011), considering the increasing volume and diversity of initiatives, terminology, approaches, and literature on the issue, depending on the characteristics and level of community involvement (World Health Organization, 2020). Evidence suggested that the more community members were supported by being involved in the design, development, and implementation of activities to improve their lives (i.e., coproduction, delegated power, or community control), the more likely their health and well-being might improve and health inequalities decrease (Popay et al., 2007). By offering self-support, promoting peer networks, and fostering neighbor relationships or volunteering, social groups can complement formal welfare programs. There are fundamental differences between CEIs and traditional health and social services. First, CEIs focus on the determinants of health and social inclusion from a health promotion approach rather than one focused on curing diseases and eliminating social gaps. Second, they focus on groups, networks of people, and communities but not on individual needs. Third, individual and community resources are exploited as complementary inputs to those of the formal welfare system, enriching the global energies available and developing individual and community empowerment and consciousness (Hogg & Varda, 2016). Improved levels of social cohesion and access to informal and formal social support and social capital are the fundamental outcomes of CEIs, which may provide some answers to the current challenging scenario (Merzel & D’Afflitti, 2003). The definition we use in this study for CEIs is “the active involvement of the community, through the promotion and integration of its social networks with formal welfare services, to improve health and social outcomes, developing self-support processes within social groups, fostering forms of social aggregation also to positively influence cognitive maps and health and social behaviors, and promoting participation in health and social needs assessment, service design and service evaluation.” Bearing this definition in mind, we pose the following research questions in order to understand how CEIs can be steered from a public authority perspective: (a) How could CEIs be classified? (b) What are the features of implemented CEIs? (c) What are the fundamental policy and managerial implications of different CEIs? Management is a contextual and case-specific science: It is important to understand the characteristics of existing or potential CEIs in order to select the most appropriate strategies and steering tools.

CEIs, Social Networks, and Community Partnership

How should CEIs be steered from a managerial perspective? How can public authorities foster CEIs? To answer these questions, communities should be regarded as systems of social networks that interact with each other. Each citizen may be member of a number of social networks, because each one of us may at the same time be a neighbor, a parent of school children, a volunteer, an employee, and also possibly a chronic patient. Ecological models of health are based on the premise that an individual’s behavior is shaped by a dynamic interaction with the social environment, which includes influences at the interpersonal, organizational, community, and social network level (Merzel & D’Afflitti, 2003). In this sense, CEIs directly affect the health, social outcomes, and habits of people belonging to social networks; however, they also have the potential to enhance the health of others connected to those individuals (Umberson & Montez, 2010). A combination of three possible local strategies can be adopted to manage CEIs: (a) promoting existing social networks and partnerships and coordinating and integrating their action with formal welfare services; (b) developing the size and scope of existing networks fostering their capacity and competences—supporting the development of additional partnerships, members, and social connections; and (c) promoting new social networks and partnerships, such as associations between peers, new volunteer groups, new forms of social aggregation, and so forth (Hogg & Varda, 2016). In addition, formal and informal partnerships among community stakeholders and institutional actors (such as hospitals) from different sectors can be effective vehicles for addressing community health needs (Prybil et al., 2014) or a mediator between resources and service provision (Beatty et al., 2010). A recent study in the United States (Cronin et al., 2021) shows that the presence of social capital in the surrounding state is associated with hospitals fostering partnerships, especially with public health and social service organizations, two areas where hospitals have traditionally faced barriers in developing community health activities. A policy focused on community, social networks, and partnerships that act as cultural and relational ties among individuals and organizations may thus prove to be a cost-effective strategy for enhancing the health and well-being at the population or community level (Latkin & Knowlton, 2015). Indeed, Brewster et al. (2018) suggest that U.S. communities that perform well on health care costs and services utilization may be partially explained by effective cross-sector partnerships between hospitals and other organizations. As tracing social ties may help to identify a community’s leadership, understanding its behavior patterns and drivers (Minkler & Pies, 1997) and mapping and understanding social networks are critical in steering CEIs toward health promotion and social inclusion.

Why Do We Need CEIs in Contemporary Health Care? The Cases of Italy and the United Kingdom

Have CEIs merely inherited features from other historical periods (mainly because of their sensitivity to social values and the emphasis on democratic participation), or are we at the forefront of something new and crucial to effectively tackle contemporary health and social care issues? Western societies have to deal with many fundamental transitions and challenges such as the financial sustainability of welfare systems, the “demographic” desert (aging and reduced fertility), increasing inequalities, climate change, political disruption, and antibiotic resistance (Walsh et al., 2018). CEIs are not the answer to all of these challenges; however, they can be effective for enriching welfare modes and redesigning health and social services to meet emerging issues. There is a need to rethink the welfare portfolio in order to tackle (a) profound changes in the demographic, social, and epidemiological patterns and (b) the disruptive impact of digital and sharing services, in terms of both provision and consumption. Demographic transition involves important changes in health and social needs such as the aging population, the increasing demand for long-term care (LTC) services, the low birth rate, and the lack of availability of informal family care givers. This social transformation has created a new landscape of people living alone (around 30% of families are made up of just one person in Italy [Istat, 2019] and a high divorce rate is reported in Western countries, for example, in Italy 46 divorces are recorded out of 100 marriages [Istat, 2019]), thus increasing the cultural and economic distances between different social clusters and fostering social fragmentation and political polarization. This article does not analyze the impacts of these trends on Western welfare systems in detail; however, it highlights that traditional health and social care services alone are not able to tackle the size, nature, and drivers of the emerging challenges. Using several examples, we aim to underline the complementary role that CEIs may play in formal welfare services. On the other hand, there has been a general disruptive change in all service formats, derived from the platform economy and the tendency to build upon users’ coproduction. The “sharing economy” or the peer-to-peer-based sharing of access to goods and services has expanded rapidly (Botsman & Rogers, 2010). CEIs can be supported by sharing economy platforms, which reinforce connections between members of social networks, increasing their mutual recognition and support, the sharing of health and social care-related information and positive experiences, and social interactions overall. Table 1 summarizes the literature on the challenges posed by the discussed scenario (referring mainly to Italy and the United Kingdom), together with their consequences on health and social care needs. In the third column, for each issue and its consequence, we list what we consider to be some potential benefits of CEIs, which correspond to the goals shown in Table 3.

Table 1 - Contemporary issues, related health and care needs, and possible benefits of community engagement initiatives (CEIs)
Issue/problems Health and social care needs/consequences Possible benefits of the CEIs
Changes in the demographic, social, and epidemiological geography
Increase in average life expectancy and population aging (79.5 years for males and 83.1 years for females in the United Kingdom, 83 years in Italy; OECD, 2019) Correlation between health care expenditures and age, until the age of 90 years when they decrease. The need for health and social care integration is positively related with aging (Leichsenring, 2004). Involvement of people on a scale large enough to monitor the community frailty and proactively provide access to welfare (World Health Organization, 2020). (Proactive Welfare Access)
Increase in chronic disease prevalence (40% in the United Kingdom and 60% in Italy) and related costs (70% of budget consumption of health care systems; OECD, 2019) Chronic diseases have important societal consequences (Cockerham et al., 2017) that can be influenced by empowerment, compliance, and self-controlled healthy lifestyles. Increase peer support among people with similar experiences to improve and maintain health (Doull et al., 2017). (Users’ compliance support)
Insufficient coverage of long-term care needs by health and social services (guaranteed by family networks) Need for integrated care pathways for preventing frailty, loss of autonomy, and maintaining mental health of elderly patients and caregivers (Dubuc et al., 2013). Social networks may support families in their care activities, foster health literacy, and offer psychological help (Umberson & Montez, 2010). (Social and health care system integration)
Fast growth in loneliness and families’ social isolation: 9 million lonely people in the United Kingdom (Allen, 2020) and 33% of total population live alone in Italy (Istat, 2019) Correlation between loneliness and patients’ compliance and between family isolation and reduction in community-shared knowledge about service access and health literacy (National Academies of Sciences, Engineering, and Medicine, 2020). Mobilize existing resources and social capital to enhance the informal ways people connect with each other and give reciprocal assistance (Dale & Newman, 2010). (Foster social relationships)
Sharing economy and digital transformation
Increased customer empowerment and coproduction (Voorberg, 2015) Potential negative impacts on health and exacerbation of health inequities: potential selection of more interested and advantaged users (Curtis et al., 2020). Development of collective capacity/social literacy to mitigate health inequalities (Batterham et al., 2016). (Health education)
Change in economic landscape as a result of online platforms: decrease in consumers’ costs (Botsman & Rogers, 2010) Big data and social knowledge may be captured mostly by private platform-based corporations, which keep most of the potential added value (OECD, 2019). Enhance responsiveness and accountability of service providers by working in partnership with public agencies and social networks (Igalla et al., 2020). (Service delivery support)
Social and geographical inequalities in access to care and quality of care are increasing (OECD, 2019) A more proactive health and welfare approach to patients’ needs is required to tackle inequalities and achieve better health literacy and quality of care (Mayberry et al., 2006). Foster community involvement in decision-making processes, delivery and evaluation of services and initiatives for the whole population. (Popay et al., 2007). (Services participatory design)

Methodology

To explore the characteristics of CEIs and identify the resulting managerial and policy implications, a threefold qualitative analysis was performed, including (a) development of three ad hoc frameworks of analysis, (b) collection of primary data of Italian CEIs and secondary data of U.K. CEIs, and (c) data analysis applying a cross-case analysis approach (Miles & Huberman, 1994) and comparison of CEIs in Italy and the United Kingdom through the developed frameworks in order to test both the robustness of our classification matrices and the differences between implemented CEIs. The first two steps of the study were performed in parallel, but the framework of analysis is presented first following the logical–theoretical approach. The grids corresponding to the frameworks of analysis are presented in the Results section, where they are used to classify our panel of CEI cases as results of the comparative analysis.

The Frameworks of Analysis

To analyze the features and implications of CEIs, three grids were created. In particular, each matrix has a different classification and an analytical focus: (a) characteristics of CEI promoters and the social networks involved (Table 2), (b) CEI goals and targets (Tables 3 and 4), and (c) CEI public support modes and their impact on social networks (Table 5). The order in which the grids are presented represents the three logical steps to manage CEIs. First, the public sector may search for the social networks available. During the scouting process, public administrations (PAs) can discover their main features in order to select the most suitable ones or the ones they think would be effective for community initiatives (Hogg & Varda, 2016). The second grid can be used to discuss the goals of any CEI related to the specific target identified in order to be coherent with the strategic goals of public authorities. Finally, the third grid can be used to assess the relationships between social networks and formal welfare services and to decide how to influence social network behaviors (CDC, 2011).

Table 2 - Characteristics of community engagement initiative (CEI) promoters and the social networks involved
Social connection driver Degree of formalization Country CEI promoter Total country Total
Public Professional third sector Volunteers Peers
Natural Informal United Kingdom 1 1 0 5 7 10
Italy 2 1 0 0 3
Formal United Kingdom 1 0 0 0 1 3
Italy 2 0 0 0 2
Constructed Informal United Kingdom 4 2 1 2 9 15
Italy 5 1 0 0 6
Formal United Kingdom 10 8 4 1 23 51
Italy 20 6 2 0 28
Total 45 19 7 8 79 79

Table 3 - Goals and primary activities of community engagement initiatives
Goal Activity Country n Total (activity) Total (goal)
Proactive welfare access Community fragility monitoring United Kingdom 3 8 15
Italy 5
Proactive welfare programs United Kingdom 1 7
Italy 6
Users’ compliance support User coproduction support United Kingdom 4 7 12
Italy 3
Psychological support United Kingdom 4 5
Italy 1
Service delivery support Drugs and MD United Kingdom 0 0 3
Italy 0
Treatments United Kingdom 0 3
Italy 3
Health education Health literacy education United Kingdom 2 4 21
Italy 2
Health promotion programs United Kingdom 10 17
Italy 7
Social and health care integration Users’ transport and accompaniment United Kingdom 0 0 5
Italy 0
Social support to patients United Kingdom 3 5
Italy 2
Foster social relationships Platforms for social contacts and relationships United Kingdom 5 10 13
Italy 5
Collaborative lifestyles United Kingdom 0 3
Italy 3
Services participatory design Service monitoring United Kingdom 1 1 10
Italy 0
Service auditing United Kingdom 1 3
Italy 2
Service design United Kingdom 6 6
Italy 0
Total 79 79 79

Table 4 - Targets of community engagement initiatives
Target United Kingdom Italy Total
Patients with chronic conditions 1 8 9
Lonely older adults 4 1 5
Fragile older adults 3 12 15
Elderly patients in long-term care facilities 5 2 7
Mental health conditions/addicted patients 7 6 13
Disabled adults 2 3 5
Poor families 13 7 20
Minors/children 2 4 6
Palliative patients 0 2 2
Community 14 5 19
Other 2 1 3
Total 53 51 104

Table 5 - Mutual exchanges among social networks and public administration within community engagement initiatives
Public support to social networks Country Impact on social clusters Total country Total
Bonding Bridging Linking/mixing
Social or institutional recognition United Kingdom 0 3 2 5 11
Italy 2 1 3 6
Public facilities for free United Kingdom 0 0 1 1 4
Italy 1 2 0 3
Human or monetary resources United Kingdom 2 3 3 8 20
Italy 7 4 1 12
Promotion, marketing in order to increase members United Kingdom 0 0 0 0 0
Italy 0 0 0 0
Integration with public services United Kingdom 2 6 4 12 24
Italy 8 2 2 12
Training and education United Kingdom 1 0 3 4 9
Italy 3 1 1 5
Digital support United Kingdom 0 0 0 0 0
Italy 0 0 0 0
No public support United Kingdom 5 4 1 10 11
Italy 0 1 0 1
Total United Kingdom 10 16 14 40 79
Italy 21 11 7 39

Different Promoters of CEIs and Characteristics of Involved Social Networks

The first classification grid identifies the promoters of CEIs and considers the characteristics of the engaged social networks. The promoter refers to the subject leading the process and designing the social mechanisms that embed CEIs. In this respect, the promoter clarifies which followers should be engaged in the initiative. The nature of the promoter inevitably influences the kind of community initiative—namely, the social and interorganizational relationships—that will be set up. CEIs may start as a result of the input of a public authority, and social networks may be involved as followers. On the other hand, the promoter may be private, working in close collaboration with PAs in a public–private partnership, or CEIs can be started by a professional nonprofit organization, by a group of nonprofessional volunteers, or by a group of peer patients (Hogg & Varda 2016). The CEI framework does not concern institutional networks of different welfare actors such as hospitals, local health authorities (LHAs), local governments, and third-sector organizations. These institutional networks may act as promoters, supporters, or steerers of CEIs: They may represent a decisive facilitator, a fundamental precondition of the environment, or an addition to the work of CEIs. Involved social networks may be natural or artificial and formalized or informal and may play different roles in the CEIs (Umberson & Montez, 2010). “Natural” social networks are stable personal relationships within an existing recognized group (minority or ethnic groups) or spontaneously set up by common interests (members of a church, fans of a sport club, or parents with children in the same school), or by using common services or settings (neighbors, library users, employers of the same organizations, commuters’ cluster, etc.) or living in similar conditions (same illness [e.g., on dialysis], in public housing, etc.). “Formalized networks” may have internal rules, a recognized status, some organizational structure, or representative bodies or formal public recognition. Formal and informal social networks require different steering and relational approaches, which entail the public component having a diversified portfolio of communication and integration competences. To sum up, social networks may play different roles within CEIs: Promoters and pivotal actors or followers may be the target group of the initiative or may act as a welfare resource and tool to tackle a local social issue (e.g., a volunteer group).

Goals and Targets of CEIs

CEIs may benefit local health and social care systems (see Table 1 for further details). To reach a specific goal, they can be enhanced by traditional welfare services or even work within an integrated approach with structured health and social organizations (Boonstra & Boelens, 2011). As shown in Table 1, CEIs' goals may focus on foster equity and easy access to welfare services as a result of a better monitoring of people in need. Patients’ compliance to therapies and correct lifestyles may be enhanced by CEIs by supporting coproduction or with psychological aids for sustaining chronic conditions, which thus enables self-empowerment. The home delivery of drugs and medical devices can be provided by social networks, as well as support for medical treatments. Health promotion programs can work effectively on social network grounds, offering both health literacy and health promotion programs and services. The lack of integration between social and health care can be tackled by CEIs, because social networks can support health care access, for example, through transportation and consumption aids or by offering frequent and regular social relationships. A richer social life can be promoted using physical or virtual platforms, or by setting up collaborative lifestyles (e.g., social housing). Community participation in steering public services can focus more on monitoring, audit processes, or codesign logics.

Mutual Exchanges Among Social Networks and PA Within CEIs

PAs support social networks through different forms of incentives, including (CDC, 2011) (a) providing social or institutional recognition, (b) offering public facilities for free, (c) supporting social networks with human or financial resources, (d) promoting social networks to attract new members, (e) integrating social network actions with public services, (f) training volunteers or patient peer groups, and (g) supporting social interactions between the network members (Edelenbos et al., 2018). Some of these incentives are traditional tools of public action, whereas others are new. At the same time, social networks have different impacts on the social clusters they help. It can affect closer connections within a homogenous group of people that are often based on kinship and reciprocity (bonding social capital), or more distant connections between people who are dissimilar in terms of their socioeconomic status (bridging social capital) or interactions between communities and people in positions of influence in formal organizations (linking social capitals; Szreter & Woolcock, 2004). The interventions bond community members within a given social cluster by decreasing social gaps, or support social bridging between heterogeneous clusters, or even produce social mixing (Aldrich, 2012; Szreter & Woolcock, 2004; Voorberg et al., 2015). Although the intervention does not reach the best desirable goal, it is important to be aware of the impacts on these aspects of the social capital.

Collection of Primary Data on Italian CEIs and Secondary Data on U.K. CEIs

We focus our study on CEIs in the United Kingdom and Italy, because these are two nations that have a similar national health system based on general taxation (Beveridge model), and both social care systems are managed by local governments with a strong integration with LHAs for planning functions and third-sector organizations for the provision of social services. For the Italian CEIs, we conducted a primary data collection, because at the time of research, there was no database of CEIs available. To gather data, we first created a network of LHAs and third-sector institutions with the collaboration of two prominent associations of public health organizations (FIASO and ANCI Federsanità). The network was built as a result of a research project implemented by Bocconi University and Sant'Anna School of Advanced Studies in Pisa. The network involved 30 LHAs from all over Italy, whose services address approximately 30% of the Italian population. Second, we conducted an online survey of the 30 LHAs to analyze the following: their cognitive maps of CEIs, their initial strategies in the field, their goals in the new approach (general aims and target population), the actors involved (institutional and noninstitutional), the managerial approaches and tools applied, and the expected and obtained results. Third, we searched for concrete CEIs within our network of 30 LHAs through a second survey. We gathered 80 CEIs and analyzed 39 of them. Our selection criteria included being in line with our definition of CEI, in particular, the prominent engagement of social networks. Many interesting but excluded projects were related to institutional networks, such as collaborations between local governments and LHAs or between LHAs and general practitioners. The survey found that there was a cognitive difficulty to frame and differentiate social networks from interinstitutional networks. All the 80 initiatives are now published in an online catalogue of community interventions. For the U.K. CEIs, we used secondary data and analyzed 40 out of 54 “community-centered practice examples” published in the Public Health England (PHE) catalogue, curated by the PHE’s Knowledge and Library Services (PHE, 2019). For the purpose of this work, we consider the features of CEIs developed in the region of England as generalizable to the whole United Kingdom. Again, as selection criteria, we examined the level of consistency of each intervention with the definition of CEI presented in the section above. In the PHE catalogue, the following information is provided for each CEI: (a) title and author, (b) a brief summary, (c) timescale for the project, (d) setting and population covered, (e) main objective, (f) motivation to act, (g) detailed description, (h) motivation for the intervention’s selection, (i) outcome, (j) learned lessons, (k) suggestions for the initiative replication, (l) future actions, and (m) contacts for additional information. In total, we analyzed and compared data from 79 case studies (39 from Italy and 40 from the United Kingdom).

Case Assessment and Cross-Case Analysis Methodology

The entire research group, made up of six researchers, became familiar with the classification grids, as well as the logic and the meaning given to each variable considered. In two 90-minute meetings, the meaning of each classification dimension and criteria was discussed, until every member of the research team had a common interpretation. Each case was read and evaluated separately by two different researchers, who then discussed any divergent assessments of specific items for each case. Some doubts emerging from the case reports were solved through a phone interview with a representative of the steering LHA (for the Italian panel) and through a meeting with the research team who collected the cases from the PHE catalogue (for the English panel) with whom the final aggregate results had been previously discussed. The aggregate analysis of Italian cases was also discussed in a 3-hour focus group meeting involving a representative of all the 30 LHAs involved.

Results: A Comparative Analysis of the Cases in Italy and the United Kingdom

CEI Promotors and Nature of Social Networks Involved

Table 2 presents the results of application of the first grid outlined in the methodology section with promoters of selected CEIs and the various types of social networks. The table highlights that, in Italy, the role of promoter is largely covered by PAs (74%, 29 of 39 cases), whereas in the United Kingdom, although public entities are still a frequent promoter (16 of 40 cases), the percentage is considerably lower (40%). In both cases, nonprofit organizations are the second most frequent promoter (21% in Italy and 28% in the United Kingdom), apart from two exceptions in the United Kingdom where two for-profit organizations were identified. Unlike in the United Kingdom, in Italy, there are very few volunteers and peers acting as promoters, as they often act as followers. The two panels of national cases have a similar distribution of “natural” versus artificial social networks and the same degree of formalization. Formalized networks are the most common (72% in Italy and 58% in the United Kingdom). Peer-promoted CEIs also have more informal and natural social networks, whereas formalized volunteer associations and professional third-sector organization have more formalized social networks. Finally, only initiatives promoted by PAs show the involvement of “natural” and formalized social networks.

Goals and Targets of CEIs

To analyze the goals of CEIs according to the second grid (goals and targets of CEIs), we considered both the main objective of the initiative (core goal and activities) along with any ancillary objectives. The majority of U.K. CEIs concern health promotion (25% of cases), participatory service design (15%), the creation of platforms for social contacts and relationships (12.5%), user coproduction (10%), and the monitoring of community fragility (7.5%). In Italy, CEIs involved in promoting health are again the most frequent (18%), followed by proactive welfare programs (15%), the monitoring of community fragility (13%), and the creation of platforms for social contacts and relationships (13%). In both nations, some goals and activities are not primary activities or are rarely implemented, for example, support for service delivery, service monitoring, and the transport and accompaniment of users. Unlike in the United Kingdom, in Italy, service design is not a priority goal. On the other hand, collaborative lifestyles and treatments are primary goals in Italy, but not in the United Kingdom. CEIs are multitargeted both in Italy and in the United Kingdom. There is thus a complexity in both the design of the intervention and the involvement of possible networks. The goals are in line with the targets tackled by CEIs in the United Kingdom, which are mainly the community as a whole (14 cases) and families and people living in poor conditions (13 cases). Findings regarding CEI targets in Italy show the predominance of the fragile older adults (12 cases), followed by patients with chronic conditions (8 cases) and families and people living in poor conditions (7 cases). The main targets in the United Kingdom are related to social issues. This explains why only a few CEIs in the United Kingdom are addressed to the fragile older adults or to patients with chronic conditions. Italian CEIs are more influenced by health care policy priorities driven by epidemiological challenges. The goals most frequently pursued are distributed proportionally with respect to targets; however, some activities seem specific to some targets. For example, programs for supported and proactive access to welfare services and psychological aid are addressed to people in poor economic conditions and psychiatric patients or drug addicts. In addition, social support of patients is offered more often to psychiatric or addicted patients, the fragile older adults, people in LTC, and the general community. Some CEIs in the United Kingdom are addressed to women (either young, mothers to be, or immigrants), whereas this does not happen at all in Italy. The following tables show the goals and the activities (Table 3) and the targets (Table 4) of the Italian and U.K. cases. Although the tables correspond to a single grid, they are presented separately for better readability of the data.

Mutual Exchanges Among Social Networks and PAs Within CEIs

The third step of the comparative analysis focuses on the kind of mutual exchanges between PAs and social networks within CEIs and their impact on community relationships. In Italy, there are always contributions from public authorities, with a predominance of integration with public services (20.5% of cases) and economic support (18% of cases). The most frequent impact on social clusters created by CEIs in Italy is bonding among participants (54%, 21 of 39 cases). On the other hand, in the United Kingdom, CEIs often lack support from public authorities (25% of cases). This might be explained by the fact that, in the United Kingdom, numerous cases of professional third-sector organizations, volunteer organizations, and peers act as promoters, as seen in Table 2. When CEIs in the United Kingdom have public support, it is generally with regard to integration with public services (30%) and economic support (20%), as in Italy. However, unlike in Italy, in the United Kingdom, CEIs mostly create bridging among social clusters (40% of cases) and linking/mixing connections (35% of cases). This is not surprising given that the most common targets tackled by initiatives in the United Kingdom are the general population and people living in poor economic or social conditions with a more relevant social policy focus. The promotion and marketing of social networks by PAs are lacking in both the United Kingdom and Italy, despite the existence of social platforms. Overall, both in the United Kingdom and Italy, public sector support for social networks is essentially institutional recognition, human and monetary resources, and free community facilities. Finally, there is little digital support in either nation. Table 5 shows the distribution of the kind of social support offered to social networks by the public sector and the CEIs' impact on social clusters in Italy and the United Kingdom.

Discussion

In line with our research questions, the tools used to classify and analyze CEIs have three aims: (a) to test the robustness and managerial importance of our classification grids; (b) to highlight the broad diversity of features and opportunities for health and the socially relevant goals that CEIs can provide for public welfare authorities; and (c) to discuss the different managerial approaches needed to steer heterogeneous CEIs, depending on their different features, social arenas, and natures (section below). After analyzing 79 cases, the three classification grids appear to be useful and robust for both scholars and practitioners. First of all, they work well according to their different scopes. The first grid focuses on the characteristics of the actors involved and their social networks. The second grid examines goals and targets. The third grid analyzes the public contribution to social networks and CEI impacts on social inclusion. The three logical steps derived from the different grids are coherent with strategic managerial approaches: scouting for influential stakeholders, planning possible goals and targets, negotiating a system of exchange in order to build and foster the implementation alliance, and defining expected impacts. In addition, the different classification scopes provided by the three grids support different analytical steps, which can initially be run autonomously, in order to have simplified and sequential assessment processes. The grids seemed to be easy to use and provided converging assessments between different researchers, because the variables suggested for each item result to be sufficiently clustered and polarized. Not all the cells available were used, which is usually an indicator of excessive theoretical differentiation, not related to actual real-life situations. However, we have to consider that CEIs are in an early stage of evolution and innovations appear to converge in both countries. The empty or not-often-used cells appeared in the discussion to be plausible or at least significant possible policy and managerial options, and probably they will be applicable in future, more mature and diffused phases of CEIs. CEIs represent a broad portfolio of heterogeneous public health and/or social programs, which need to be understood in terms of their extensive characteristics in order to integrate them within institutional welfare goals and steer them effectively (CDC, 2011; Popay et al., 2007). From a general perspective, the nature of the promoter seems to drive the entire mission in terms of private philanthropic actors versus public authorities (Hogg & Varda, 2016). In the first case, in our panel, there was a stronger commitment to evident social fragilities. In contrast, public authorities have more evidence-based epidemiological approaches, which may lean toward more health care-related clusters (e.g., LTC and chronic conditions), which are probably politically less sensitive. The portfolio of targets is really broad because of both the different selection metrics and policy priorities. CEIs also have many different goals—from fostering social aggregation to promoting health literacy and from enriching welfare services to fostering participatory services. Public sector contributions to social networks do not always appear fundamental if the philanthropic commitment to CEIs is sufficiently strong, although this can lead to the risk of a silo effect because of the lack of integration between CEIs and traditional welfare services. Value for money, in any case, appears to be very beneficial in terms of formal welfare, considering the modest financial value of public sector support (institutional accreditation, spare facilities, and integration with welfare services) and the great potential health and social-related benefits guaranteed by CEIs. The expected results are not always the optimal ones (e.g., social bonding effect); however, they still represent an improvement compared to preexisting local scenarios. We found a relevant level of heterogeneity and also differences between U.K. and Italian cases. The biggest difference regards the nature of CEI promoters: More philanthropic initiatives were identified in the United Kingdom, and more public sector initiatives were identified in Italy. This highlights the different focuses of the United Kingdom, which is more social care oriented, and Italy, which is more health care oriented. This also explains the differences in targets and benefits expected from CEIs. In the United Kingdom, more attention is paid to poverty, low literacy levels, and social loneliness, with a particular focus on vulnerable women. Italian CEIs are more oriented to support chronic conditions and LTC care, which are across all social conditions and genders. Public authorities in Italy spend resources on fostering CEIs, which happens less frequently in the United Kingdom. Infra- and international differences are always good news from a managerial perspective, because they leave room for local autonomy and adaptation to contexts.

Policy and Managerial Implications

We believe that our evidence highlights three major policy and management implications. One is related to the choice of CEIs priorities. The second regards the selection of partners, whereas the third regards different managerial approaches and tools needed to steer heterogeneous CEIs models. First of all, different CEI models cover specific targets that tackle precise service goals and expected social impacts. Public steering authorities must reflect which CEIs should be fostered, depending upon the strategic goals for their area and awareness of their particular implementation capacity and competency to steer social networks. This helps to understand whether CEIs are able to compliment the strategic goals of public organizations or substitute them because traditional solutions are ineffective or not affordable (Boonstra & Boelens 2011). CEIs are complex and long lasting social processes based on different steps: scouting, choice or building of community network, network engagement, capacity and program development, mutual exchange and negotiation, and CEI management (Igalla et al., 2020). It is thus not easy to change from one CEI model to another and expect to immediately gain new outcomes. This makes the choice of CEI priorities even more strategic because the reversibility costs are very high. Second, there is a need to identify the right and effective institutional partners, especially among the existing social and community networks. They need to be selected in order to fulfill the aims of the CEI programs, in line with the CEI strategy, considering competences, attitudes, and activities. Social networks need to be fostered or promoted with a community-building approach. Besides the centrality of social networks for CEIs, other organizations may also be involved in the steering and integrating role with the formal welfare services (Local governments, health and social care providers, etc.; Hogg & Varda, 2016). From a public health or social care perspective, the availability of a social network or the external entrepreneurship of well-intentioned stakeholders should not act as drivers for the activation of CEIs. This should work the other way around: Institutional goals or gaps should act as key drivers for the promotion or fostering of particular CEIs. This is especially true, considering the broad range of opportunities available in the CEIs portfolio, in any context characterized by a medium-range social capital. Third, because the features, goals, and service portfolio of the social networks involved differ, heterogeneous managerial styles and approaches are needed for public authorities to become effective in the implementation process. In fact, different social networks have different sensitivities to different messages and behaviors (Minkler & Pies, 1997; Umberson & Montez, 2010). For example, a very hierarchical network requires direct contact between leaders, whereas a peer and participatory network may be more sensitive to community and peer-to-peer dialogue. However, steering the process becomes more complex, because the promoter of the intervention may have already established various social interaction rules or service features. The opposite situation, where the public actor plays the role of the entrepreneur, requires the selection of the right social networks, which may need to be created, developed, or only involved in the interventions. Also, the nature of the social networks makes a difference for the right managerial approach and communication (Umberson & Montez, 2010). Finally, our analysis highlights that the kind of public–private exchanges between the public authority and the social networks involved are fundamental to understand mutual expectations, perceived value opinions, and interexchange equity in order to implement the right incentive scheme to foster social networks and internal dynamics. Incentives may be based on social or institutional recognition, offering free access to public facilities, professional or monetary resources, promotion of the network in order to increase its members, or integration with public services (Edelenbos et al., 2018). This is seldom just a matter of financial resources. It is more about understanding networks and their leaders or members’ expectations, which may, in some cases, be even more challenging than finding additional monetary resources. The ability to choose the right incentive is related to public steering competences and organizational capacity. This is another important managerial challenge in order to guide the overall health and social impact of public organizations as a result of exchanges with their related social environment.

Conclusions

The evidence collected shows that CEIs are fundamental pillars of contemporary welfare systems because of the changes in both demography and epidemiology and because of the disruptive impact of platform economy models. In fact, both phenomena increase social inequalities, because there is heterogeneity of health literacy and coproduction competences, which are important in self-managing the increasing chronic conditions (Ricciardi, 2019). The CEI portfolio is very broad. It is crucial to become familiar with all the different solutions available in order to be able to choose which one should be implemented, depending on the local public health priorities. The characteristics of the different social networks involved in CEIs are heterogeneous. This requires applying appropriate public relational style, activating consistent internal competences, and selecting the right incentives in order to make the steering of social networks effective and affordable. The features of CEIs and the related managerial recommendations provided are based on deductive research logic, with an in-depth analysis of the characteristics of the networks. This represents a limitation of our research approach, which might need to become more inductive, also looking at the quantitative data of each case, considering the internal and external resources invested in CEIs and the global impact of their interplay. Moreover, an increasing number of CEIs from different countries should be studied in order to understand the convergences and local cultural specificities. The early stage of this kind of approach requires a managerial framework and classification in order to provide initial recommendations for managerial local action, which are provided here. CEIs are an innovative, broad, diffused, diversified and complex social mechanism, which requires new and focused awareness and competences. There is a new public health management era in front of us. The first goal of all the new global and local platforms (most of which are profit oriented) is to establish a new virtual community, which refers constantly to its new developed ecosystem (Parker et al., 2016). At the forefront of business is community engagement, driven by the awareness of the influential power that social networks are able to exercise on consumers’ behaviors. If the mechanisms of influence of social bonds are of interest in the private sector, also in the public welfare sector, these currently constitute an area to be explored and exploited in order to face the contemporary challenges.

Acknowledgments

The authors wish to thank all the researchers of Laboratorio Management e Sanità of Scuola Superiore Sant’Anna of Pisa and of Bocconi University Center for Research on Health and Social Care Management who took part in the research project for their contribution and effort. The authors are also particularly grateful to Prof. Jane South of Leeds Beckett University.

Author contributions: Francesco Longo and Sara Barsanti conceived the idea and designed the research. Angelica Zazzera and Anita Bunea performed the data collection and data analysis. Francesco Longo, Sara Barsanti, and Manila Bunea performed the data interpretation and the critical revision of the article. All the authors discussed the results and contributed to the final article.

References

Aldrich D. P. (2012). Building resilience: Social capital in post-disaster recovery. University of Chicago Press.
Allen K., Morrell L., Hay C. (2020). Lonely and left behind: Tackling loneliness at a time of crisis. The British Red Cross Society. Retrived November 7, 2020, from https://www.redcross.org.uk/-/media/documents/about-us/research-publications/health-and-social-care/lonely-and-left-behind.pdf
Batterham R. W., Hawkins M., Collins P. A., Buchbinder R., Osborne R. H. (2016). Health literacy: Applying current concepts to improve health services and reduce health inequalities. Public Health, 132, 3–12.
Beatty K., Harris J. K., Barnes P. A. (2010). The role of interorganizational partnerships in health services provision among rural, suburban, and urban local health departments. The Journal of Rural Health, 26(3), 248–258.
Boonstra B., Boelens L. (2011). Self-organization in urban development: Towards a new perspective on spatial planning. Urban Research & Practice, 4(2), 99–122.
Botsman R., Rogers R. (2010). What’s mine is yours. The rise of collaborative consumption. Collins.
Brewster A. L., Kunkel S., Straker J., Curry L. A. (2018). Cross-sectoral partnerships by area agencies on aging: Associations with health care use and spending. Health Affairs (Project Hope), 37(1), 15–21.
Centers for Disease Control and Prevention. (1997). Principles of community engagement (1st ed.). Author.
Centers for Disease Control and Prevention. (2011). Principles of community engagement (2nd ed.). Author.
Cockerham W. C., Hamby B. W., Oates G. R. (2017). The social determinants of chronic disease. American Journal of Preventive Medicine, 52(1), S5–S12.
Cronin C. E., Berkeley F., Garlington S. (2021). Population health partnerships and social capital: Facilitating hospital–community partnerships. SSM—Population Health, 13, 100739.
Curtis S. K., Singh J., Mont O., Kessler A. (2020). Systematic framework to assess social impacts of sharing platforms: Synthesising literature and stakeholder perspectives to arrive at a framework and practice-oriented tool. PLOS ONE, 15(10), e0240373.
Cyril S., Smith B. J., Possamai-Inesedy A., Renzaho A. M. (2015). Exploring the role of community engagement in improving the health of disadvantaged populations: A systematic review. Global Health Action, 8, 29842.
Dale A., Newman L. (2010). Social Capital: A Necessary and Sufficient Condition for Sustainable Community Development?Community Development Journal, 45(1), 5–21.
Doull M., O'Connor A. M., Welch V., Tugwell P., Wells G. A. (2017). Peer support strategies for improving the health and well-being of individuals with chronic diseases. Cochrane Database of Systematic Reviews, 2017(6), CD005352.
Dubuc N., Bonin L., Tourigny A., Mathieu L., Couturier Y., Tousignant M., Delli-Colli N., Raîche M. (2013). Development of integrated care pathways: Toward a care management system to meet the needs of frail and disabled community-dwelling older people. International Journal of Integrated Care, 13, e017.
Edelenbos J., Van Meerkerk I., Schenk T. (2018). The evolution of community self-organization in interaction with government institutions cross-case insights from three countries. The American Review of Public Administration, 48(1), 52–66.
Hogg R. A., Varda D. (2016). Insights into collaborative networks of nonprofit, private, and public organizations that address complex health issues. Health Affairs (Project Hope), 35(11), 2014–2019. 10.1377/hlthaff.2016.0725
Igalla M., Edelenbos J., van Meerkerk I. (2020). What explains the performance of community-based initiatives? Testing the impact of leadership, social capital, organizational capacity, and government support. Public Management Review, 22(4), 602–632.
Istat. (2019). Rapporto annuale 2019. La situazione del paese [Annual report 2019. The situation in the country]. Retrieved September 3, 2020, from https://www.istat.it/it/archivio/230897
Latkin C. A., Knowlton A. R. (2015). Social network assessments and interventions for health behavior change: A critical review. Behavioral Medicine, 41(3), 90–97.
Leichsenring K. (2004). Developing integrated health and social care services for older persons in Europe. International Journal of Integrated Care, 4, e10.
Maruthappu M., Sood H. S., Keogh B. (2014). The NHS five year forward view: Implications for clinicians. BMJ, 349, g6518.
Mayberry R. M., Nicewander D. A., Qin H., Ballard D. J. (2006). Improving quality and reducing inequities: A challenge in achieving best care. Proceedings (Baylor University. Medical Center), 19(2), 103–118).
Merzel C., D’Afflitti J. (2003). Reconsidering community-based health promotion: Promise, performance, and potential. American Journal of Public Health, 93(4), 557–574.
Miles M. B., Huberman A. M. (1994). Qualitative data analysis: An expanded source book. Sage.
Minkler M., Pies C. (1997). Ethical issues in community organization and community participation. In Minkler M. (Ed.), Community organizing and community building for health (pp. 116–133).  Rutgers University.
National Academies of Sciences, Engineering, and Medicine. (2020). Social isolation and loneliness in older adults: Opportunities for the health care system. National Academies Press.
    OECD. (2019). Enhancing access to and sharing of data: Reconciling risks and benefits for data re-use across societies. Author.
      Parker G. G., Van Alstyne M. W., Choudary S. P. (2016). Platform revolution: How networked markets are transforming the economy and how to make them work for you. W. W. Norton.
      Popay J., Attree P., Hornby D., Milton B., Whitehead M., French B., Kowarzik U., Simpson N., Povall S. L. (2007). Community engagement in initiatives addressing the wider social determinants of health: A rapid review of evidence on impact, experience and process. University of Lancaster.
      Prybil L., Scutchfield F. D., Killian R., Kelly A., Mays G. P., Carman A., Levey S., McGeorge A., Fardo D. W. (2014). Improving community health through hospital–public health collaboration: Insights and lessons learned from successful partnerships. Health management and policy faculty book gallery (Vol. 2).
      Public Health England. (2019). Community-centred and asset-based approaches. Retrieved May 15, 2020, from https://phelibrary.koha-ptfs.co.uk/practice-examples/caba/
      Ricciardi W. (2019). Assessing the impact of digital transformation of health services: Opinion by the Expert Panel on Effective Ways of Investing in Health (EXPH). European Journal of Public Health, 29(Suppl. 4), ckz185.769.
      South J. (2015). A guide to community-centred approaches for health and wellbeing. Public Health London.
      Stake R. E. (1995). The art of case study research. Sage.
      Szreter S., Woolcock M. (2004). Health by association? Social capital, social theory, and the political economy of public health. International Journal of Epidemiology, 33, 650–667.
      Umberson D., Montez J. K. (2010). Social relationships and health: A flashpoint for health policy. Journal of Health and Social Behavior, 51(Suppl), S54–S66.
      Voorberg W. H., Bekkers V. J. J. M., Tummers L. G. (2015). A systematic review of co-creation and co-production: Embarking on the social innovation journey. Public Management Review, 17(9), 1333–1357.
      Walsh M., Kittler M. G., Mahal D. (2018). Towards a new paradigm of healthcare: Addressing challenges to professional identities through community operational research. European Journal of Operational Research, 268(3), 1125–1133.
      Watt A. (1986). Community health initiatives and their relationship to general practice. The Journal of the Royal College of General Practitioners, 36(283), 72–73.
      World Health Organization. (2020). Community engagement: A health promotion guide for universal health coverage in the hands of the people. Retrieved August 28, 2021 from https://www.who.int/publications/i/item/9789240010529
      Keywords:

      Classification of CEIs; community engagement initiatives (CEIs); health and social care; integration of social networks with public services; Italy; management of CEIs; United Kingdom

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