Internet addiction and its association with quality of life in patients with major depressive disorder: a network perspective.

Depressive disorders and internet addiction (IA) are often comorbid. The aims of this study were to examine the network structure of IA in patients with major depressive disorders (MDD) and explore the association between IA and quality of life (QoL) in this population. This was a multicenter, cross-sectional survey. IA and QoL were assessed with the Internet Addiction Test (IAT) and the World Health Organization Quality of Life-brief version, respectively. Node expected influence (EI) was used to identify central symptoms in the network model, while the flow network of QoL was generated to examine its association with IA. A total of 1,657 patients with MDD was included. "Preoccupation with the Internet," "Job performance or productivity suffer because of the Internet," and "Neglect chores to spend more time online" were central symptoms. The symptom "Form new relationships with online users" had the strongest direct positive relation with QoL, while "Spend more time online over going out with others" and "Job performance or productivity suffer because of the Internet" had the strongest direct negative relations with QoL. Neglecting work caused by IA correlated with QoL, while making friends online appropriately was related to better QoL among MDD patients. Appropriate interventions targeting the central symptoms may potentially prevent or reduce the risk of IA in MDD patients.

Mapping network connectivity between internet addiction and residual depressive symptoms in patients with depression.

Background and aims: Depression often triggers addictive behaviors such as Internet addiction. In this network analysis study, we assessed the association between Internet addiction and residual depressive symptoms in patients suffering from clinically stable recurrent depressive disorder (depression hereafter). Materials and methods: In total, 1,267 depressed patients were included. Internet addiction and residual depressive symptoms were measured using the Internet Addiction Test (IAT) and the two-item Patient Health Questionnaire (PHQ-2), respectively. Central symptoms and bridge symptoms were identified via centrality indices. Network stability was examined using the case-dropping procedure. Results: The prevalence of IA within this sample was 27.2% (95% CI: 24.7-29.6%) based on the IAT cutoff of 50. IAT15 ("Preoccupation with the Internet"), IAT13 ("Snap or act annoyed if bothered without being online") and IAT2 ("Neglect chores to spend more time online") were the most central nodes in the network model. Additionally, bridge symptoms included the node PHQ1 ("Anhedonia"), followed by PHQ2 ("Sad mood") and IAT3 ("Prefer the excitement online to the time with others"). There was no gender difference in the network structure. Conclusion: Both key central and bridge symptoms found in the network analysis could be potentially targeted in prevention and treatment for depressed patients with comorbid Internet addiction and residual depressive symptoms.

Prevalence of suicidality in clinically stable patients with major depressive disorder during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic is associated with an increased risk of mental health problems including suicide in many subpopulations, but its influence on stable patients with major depressive disorder (MDD) has been studied fleetingly. This study examined the one-year prevalence of suicidality including suicidal ideation (SI), suicide plans (SP), and suicide attempts (SA) as well as their correlates in clinically stable MDD patients during the COVID-19 pandemic. METHODS: A cross-sectional, observational study was conducted between October 1, 2020, and October 15, 2021, in six tertiary psychiatric hospitals. Socio-demographic information, clinical data and one-year prevalence of suicidality were recorded. RESULTS: Altogether, 1718 participants who met the eligibility criteria were included. The overall one-year prevalence of suicidality during the COVID-19 pandemic was 68.04% (95% confidence intervals (CI) =65.84-70.25%), with one-year SI prevalence of 66.4% (95%CI = 64.18-68.65%), SP prevalence of 36.26% (95%CI = 33.99-38.54%), and SA prevalence of 39.35% (95%CI = 37.04-41.66%). Binary logistic regression analyses revealed male gender, married marital status, college education level and above and age were negatively associated with risk of suicidality. Urban residence, unemployed work status, experiences of cyberbullying, a history of suicide among family members or friends, and more severe fatigue, physical pain, and residual depressive symptoms were positively associated with risk of suicidality. CONCLUSIONS: Suicidality is common among clinically stable MDD patients during the COVID-19 pandemic. Regular suicide screening and preventive measures should be provided to clinically stable MDD patients during the pandemic.

Suicidality in clinically stable bipolar disorder and schizophrenia patients during the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has a disproportionate impact on vulnerable subpopulations, including those with severe mental illness (SMI). This study examined the one-year prevalence of suicidal ideation (SI), suicide plans (SP), and suicide attempts (SA) in bipolar disorder (BD) and schizophrenia (SCZ) patients during the pandemic. Prevalence rates were compared between the two disorders and associated factors were examined. A survey was conducted in six tertiary psychiatric hospitals and psychiatric units. People with a diagnosis of BD or SCZ were invited to participate. SI, SP, and SA (suicidality for short) were assessed and associated factors were examined using binary logistical regression. The 1-year prevalence of SI, SP and SA in BD patients were 58.3%, (95% CI: 54.1-62.6%), 38.4% (95% CI: 34.3-42.6%) and 38.6% (95% CI: 34.5-42.8%), respectively, which were higher than the corresponding figures in SCZ patients (SI: 33.2%, 95% CI: 28.6-37.8%; SP: 16.8%, 95% CI: 13.2-20.5%; SA: 19.4%, 95% CI: 15.5-23.3%). Patients with younger age, experience of cyberbullying, a history of SA among family or friends, a higher fatigue and physical pain score, inpatient status, and severe depressive symptoms were more likely to have suicidality. The COVID-19 pandemic was associated with increased risk of suicidality, particularly in BD patients. It is of importance to regularly screen suicidality in BD and SCZ patients during the pandemic even if they are clinically stable.