The value of participating in a community lies in the users’ ability to gain prompt access to a range of people. As more users join a community, a catalyst of social medical capital is structural defragmentation; that is, social interaction becomes more valuable as more pairs of users become mutually reachable along some path. Recent work has suggested that communities undergo defragmentation by self-organizing into hub-dominated structures [11]. The emergence of a small number of “superusers” (ie, the hubs engaging in conversations with a disproportionally large number of other users) engenders normative control and safeguards the communities from splitting into disjoint components [18].

In a socially cohesive closed network, links are forged locally, and pairs of connected individuals tend to be tied to at least one third party that they have in common (Figure 1A). Previous studies have suggested that closed structures, rich in third-party relationships, engender a shared identity and a sense of belonging, foster trust and cooperation, and sustain emotional support [16,17,19]. Evidence from two communities where patients primarily seek social support has shed light on the role of social cohesion in eliciting social medical capital [11]. Two empirical regularities have been uncovered: (1) highly connected support-giving superusers preferentially communicate with poorly connected support-seeking users; and (2) pairs of support-seeking users who communicate with the same support-giving superuser tend to communicate with each other as well, thus creating closed connected triangles centered on superusers. Local redundancy is therefore the structural engine of a support-oriented community.

An open network is rich in structural gaps and opportunities of intermediation between individuals (Figure 1B). Open structures, where connections tend to be weak and constitute “local bridges” between otherwise disconnected parts, have long been associated with informational benefits [16,17,20]. In an openly structured community, communication is likely to take users closer to complementary sources of information they do not already possess [21]. Brokerage opportunities between distinct social circles expose users to greater variance and novelty of resources, and eventually help them to satisfy their informational needs [20,21]. Paucity of local redundancy is therefore the structural engine of an information-oriented community.

In cases where the community aims to provide both emotional and informational support, social medical capital lies at the interface between bonding and bridging [17,22]. In such cases, the community will be most beneficial to the users if they can combine local redundancy with brokerage opportunities (Figure 1C). In a limiting case, this can be achieved when the following conditions are met: (1) a given user is a member of multiple clusters of users; (2) these clusters do not have any other users in common except the focal one (who therefore is the only intermediary between otherwise disconnected clusters); and (3) each cluster has an underlying closed cohesive structure (ie, all members are connected with one another).

Empirically testing our theoretical framework will require the construction of large-scale longitudinal network data sets with information on users and their time-stamped messages. To comparatively assess the efficacy of network mechanisms of social capital, content analysis of messages would be needed so as to uncover how users’ phycological well-being and access to information vary as social connections also change over time.

To help policy makers to realize our vision of social medical capital as a crucial enabler of large-scale health care interventions in resource-constrained systems, we propose four targets: (1) promote patients’ and caregivers’ participation in online health communities to ensure continuous provision of socially embedded resources (eg, information, advice, support) that users can access through their (direct and indirect) social connections [14]; (2) support superusers’ role in online health communities through appropriate training programs [1]; (3) enhance the quality of peer support and patients’ self-care through robust evaluation systems; and (4) develop governance modes for maintaining privacy and confidentiality, cultivating trust and a participatory culture, and promptly detecting and preventing the spreading of misleading information and malicious behavior.