Prevalence and network structure of depression, insomnia and suicidality among mental health professionals who recovered from COVID-19: a national survey in China.

Translational psychiatry(2024)

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Abstract
Psychiatric syndromes are common following recovery from Coronavirus Disease 2019 (COVID-19) infection. This study investigated the prevalence and the network structure of depression, insomnia, and suicidality among mental health professionals (MHPs) who recovered from COVID-19. Depression and insomnia were assessed with the Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index questionnaire (ISI7) respectively. Suicidality items comprising suicidal ideation, suicidal plan and suicidal attempt were evaluated with binary response (no/yes) items. Network analyses with Ising model were conducted to identify the central symptoms of the network and their links to suicidality. A total of 9858 COVID-19 survivors were enrolled in a survey of MHPs. The prevalence of depression and insomnia were 47.10% (95% confidence interval (CI) = 46.09-48.06%) and 36.2% (95%CI = 35.35-37.21%), respectively, while the overall prevalence of suicidality was 7.8% (95%CI = 7.31-8.37%). The key central nodes included "Distress caused by the sleep difficulties" (ISI7) (EI = 1.34), "Interference with daytime functioning" (ISI5) (EI = 1.08), and "Sleep dissatisfaction" (ISI4) (EI = 0.74). "Fatigue" (PHQ4) (Bridge EI = 1.98), "Distress caused by sleep difficulties" (ISI7) (Bridge EI = 1.71), and "Motor Disturbances" (PHQ8) (Bridge EI = 1.67) were important bridge symptoms. The flow network indicated that the edge between the nodes of "Suicidality" (SU) and "Guilt" (PHQ6) showed the strongest connection (Edge Weight= 1.17, followed by "Suicidality" (SU) - "Sad mood" (PHQ2) (Edge Weight = 0.68)). The network analysis results suggest that insomnia symptoms play a critical role in the activation of the insomnia-depression-suicidality network model of COVID-19 survivors, while suicidality is more susceptible to the influence of depressive symptoms. These findings may have implications for developing prevention and intervention strategies for mental health conditions following recovery from COVID-19.
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