A Dynamic Ethnography of Digital Care Networks and Social Resilience

Thesis Abstract

This study investigates how digital care networks—interactions among formal healthcare providers, informal caregivers, community organizations, and technology-enabled platforms—shape social resilience in the face of chronic health burdens and collective crises. The problem addressed concerns the fragmentation of care in digitally mediated environments, which can undermine continuity, trust, and adaptive capacity among diverse populations. The aim is to develop a dynamic ethnographic account and a theoretical framework that explicates the mechanisms through which digital care networks contribute to social resilience, with particular attention to relational ecologies, information flows, and boundary-spanning practices. Specific objectives are (1) to map the configuration and evolution of digital care networks across multiple sites; (2) to identify how digital practices reconfigure trust, reciprocity, and social capital among patients, caregivers, and professionals; (3) to examine temporal patterns of collaboration during routine management and crisis moments; (4) to assess the role of platform affordances, data governance, and digital literacy in resilience outcomes; and (5) to develop a middle-range theory that integrates care network dynamics with resilience frameworks such as the Social-Ecological Model and Actor-Network Theory. The methodology adopts a dynamic ethnography approach, combining longitudinal fieldwork with digital trace analysis. The population includes adult patients with multimorbidity, their primary informal caregivers, community health workers, and clinicians operating within three urban clinical networks and two rural outreach programs. A purposive sample of 60 patients, 40 informal caregivers, and 20 clinicians will be followed over 18 months, with an embedded sub-sample of 15 patient-caregiver dyads for in-depth, biweekly interview cycles. Data collection instruments comprise participant observations within clinics and home-based digital interactions, semi-structured interviews, focus groups with caregivers and clinicians, and digital trace data from electronic health records, care coordination platforms, and caregiver messaging apps. The study also employs photo–elicitation and diary methods to capture daily care routines and perceived resilience. Validity and reliability will be ensured through triangulation across methods, member checking, and intercoder reliability checks with a Cohen’s kappa target of 0. Eight analytical techniques will be deployed thematic analysis to identify emergent patterns in qualitative data; grounded theory coding to iteratively build a middle-range theory; social network analysis (SNA) to quantify network density, betweenness centrality, and information flow; longitudinal sequence analysis to trace evolution of care configurations; time-series analysis of platform usage metrics; content analysis of policy and governance documents; cross-case synthesis to compare urban and rural contexts; and regression analysis to test predictors of resilience outcomes, controlling for age, health status, and digital literacy. Key expected findings include (1) identification of core care network archetypes and their transitions over time; (2) evidence that high-quality digital communications, trust-rich interactions, and timely information sharing mediate improved self-management and caregiver well-being; (3) demonstration that platform affordances such as interoperability and clear data governance correlate with greater network stability and resilience; (4) recognition of boundary-spanning actors (navigators, community health workers) as critical brokers of resilience during shocks; and (5) a theoretically grounded model linking digital care network configurations to social resilience, incorporating elements of Actor-Network Theory and the Social-Ecological Model. The study contributes to knowledge by offering a novel dynamic ethnography of digital care networks, articulating a middle-range theory that explains how digitally mediated collaboration sustains social resilience, and providing a methodological blueprint for integrating qualitative ethnography with digital trace analytics in health systems research. The main conclusion anticipates that resilient care ecosystems emerge from adaptive network structures, intentional governance of data and privacy, and empowered broker roles that align patient needs with platform capabilities. Policy and practice implications include recommendations for interoperable health information platforms, formal recognition and training of care navigators, and governance frameworks that foster trust, transparency, and equitable access to digital care resources. Suggestions for future research encompass comparative analyses across additional cultural contexts and the examination of resilience outcomes in pandemic-related care scenarios.