Network Analysis of Factors Influencing ICU Patient Transfer Readiness: A Social‐Ecological Model Approach

Background ICU transfer readiness is a multidimensional state influenced by informational, functional, emotional and support‐related needs. Network analysis can clarify how readiness indicators and emotional distress co‐occur as a system, rather than as independent factors. Aims To (1) model conditional associations among ICU transfer‐readiness indicators and anxiety/depressive symptoms and (2) identify highly connected and highly predictable targets that may be prioritised in transitional‐care interventions. Study Design Transfer readiness was measured using the ICU Transfer Readiness Scale (15 items; 0–10) and emotional distress using the Hospital Anxiety and Depression Scale (HADS; 14 items; 0–3). A regularised mixed graphical model (MGM) was estimated to accommodate mixed/ordinal data. Edge‐weight accuracy, centrality robustness and node predictability ( R 2 ) were assessed using bootstrap procedures. Age and gender were included as background variables. Results A total of 276 ICU patients were included in the analysis. The estimated network showed a clear modular structure: transfer‐readiness indicators clustered into personal status, disease knowledge, coping after transition and expected‐support domains; HADS symptoms clustered into anxiety and depression domains. Within transfer readiness, the strongest association occurred between two expected‐support indicators, suggesting perceived support is tightly interlinked. Within HADS, multiple strong within‐subscale connections were observed for both anxiety and depression symptoms. Node predictability ranged from 0.224 to 0.633 (mean 0.434), with the highest predictability for key readiness indicators in the knowledge/coping domains ( R 2 ≈0.63). Bootstrap analyses supported acceptable stability of the main edge and centrality patterns. Demographic nodes showed comparatively weaker and more cautious‐to‐interpret associations. Conclusions ICU transfer readiness and emotional symptoms form structured conditional interdependencies, indicating readiness should be conceptualised and addressed as a connected system rather than isolated determinants. Relevance to Clinical Practice Transitional‐care strategies may be strengthened by prioritising highly connected/predictable readiness targets—particularly expected support and key knowledge/coping indicators—while concurrently screening for and addressing anxiety/depressive symptoms to improve transfer preparation and early post‐transfer adjustment.