Unraveling the quality-of-life network: how activities of daily living are embedded in the multidimensional quality of life after stroke

Quality of Life (QoL) after stroke is a multidimensional construct, yet its internal interactive architecture and how objective functional capacity, specifically Activities of Daily Living (ADL), embeds within this subjective network remain poorly understood. This study aimed to delineate the interdependent network structure of post-stroke quality of life domains and to investigate the specific role of ADL within this system. In this cross-sectional study, a sample of 451 stroke survivors was recruited. Psychometric network analysis was conducted on the 12 domains of the Stroke-Specific Quality of Life (SS-QOL) scale to estimate the core QoL network. Subsequently, ADL was integrated as an external node to examine its precise connections. Centrality indices and bridge centrality were calculated to identify hubs and bridges. Edge-weight accuracy and centrality stability were assessed via bootstrap analysis. The core 12-domain QoL network was stable and interpretable. Self-Care and Thinking emerged as the most central hubs (strength centrality: 1.24 and 1.16). Social Roles acted as a key bridge (highest betweenness centrality: 26). Crucially, ADL showed its strong direct association with Self-Care (edge weight = 0.169) and Mobility (edge weight = 0.207). This pattern shows that ADL is directly associated with these core functional domains, without being directly linked to more subjective domains like Mood or Social Roles. This study provides a cross-sectional map of interdependencies within the post-stroke QoL system. Within this observed network, Self-Care emerged as a central and interconnected domain, thereby suggesting it as a candidate for future intervention research. The peripheral yet specialized connectivity of ADL suggests its effect on broader QoL is likely system-mediated. These hypotheses regarding directional influences and intervention efficacy require explicit testing in longitudinal or experimental studies.