Actual status of visitor and telephone restrictions for Japanese psychiatric inpatients: A retrospective observational study.

Spinal cord injury (SCI) is a severe central nervous system disorder caused by traumatic or non-traumatic etiologies and is commonly associated with complete or partial loss of sensory, motor, and autonomic function below the level of injury. With continuing advances in acute care and rehabilitation, survival after SCI has improved substantially; however, lifelong physical disability, altered social roles, and prolonged adaptation challenges impose a considerable psychosocial burden on affected individuals and markedly compromise quality of life (, ). Among the psychological sequelae of SCI, depression and anxiety are the most prevalent emotional problems. Meta-analytic evidence suggests that depressive symptoms are highly prevalent in people with SCI, while anxiety is also common, and the two often co-occur (, ). This high level of comorbidity not only intensifies subjective suffering but is also associated with poorer functional outcomes, lower rehabilitation adherence, and less favorable long-term psychological adjustment (). Most previous studies on emotional problems in SCI have relied on latent-variable approaches and have used total scores to quantify depression and anxiety severity. Although total-score models are useful for summarizing overall symptom burden, they obscure the complex interactions among individual symptoms within these heterogeneous syndromes and provide limited insight into the specific roles of particular symptoms in maintaining comorbidity (). Consequently, interventions derived from such models may fail to identify the most clinically relevant targets for individualized psychological management. In recent years, symptom network analysis has emerged as a useful framework for understanding the internal structure of mental disorders. According to network theory, mental disorders do not necessarily arise from a single underlying latent entity; instead, they may reflect a system of mutually interacting symptoms linked through conditional dependence relations (, ). Within this framework, expected influence (EI) can be used to identify “core symptoms” that exert relatively large global influence on the overall symptom network (), whereas bridge centrality—especially bridge expected influence (bEI)—can be used to identify “bridge symptoms” that connect different symptom communities and may facilitate the spread of comorbidity (). Identifying such core and bridge symptoms may help clarify the micro-level architecture of depression–anxiety comorbidity and inform more targeted clinical interventions.