Long-term psychological profile of general population following COVID-19 outbreak: symptom trajectories and evolution of psychopathological network.

AIMS: COVID-19 has long-term impacts on public mental health, while few research studies incorporate multidimensional methods to thoroughly characterise the psychological profile of general population and little detailed guidance exists for mental health management during the pandemic. This research aims to capture long-term psychological profile of general population following COVID-19 by integrating trajectory modelling approaches, latent trajectory pattern identification and network analyses. METHODS: Longitudinal data were collected from a nationwide sample of 18 804 adults in 12 months after COVID-19 outbreak in China. Patient Health Questionnaire-9, Generalised Anxiety Disorder-7 and Insomnia Severity Index were used to measure depression, anxiety and insomnia, respectively. The unconditional and conditional latent growth curve models were fitted to investigate trajectories and long-term predictors for psychological symptoms. We employed latent growth mixture model to identify the major psychological symptom trajectory patterns, and ran sparse Gaussian graphical models with graphical lasso to explore the evolution of psychopathological network. RESULTS: At 12 months after COVID-19 outbreak, psychological symptoms generally alleviated, and five psychological symptom trajectories with different demographics were identified: normal stable (63.4%), mild stable (15.3%), mild-increase to decrease (11.7%), mild-decrease to increase (4.0%) and moderate/severe stable (5.5%). The finding indicated that there were still about 5% individuals showing consistently severe distress and approximately 16% following fluctuating psychological trajectories, who should be continuously monitored. For individuals with persistently severe trajectories and those with fluctuating trajectories, central or bridge symptoms in the network were mainly 'motor abnormality' and 'sad mood', respectively. Compared with initial peak and late COVID-19 phase, aftermath of initial peak might be a psychologically vulnerable period with highest network connectivity. The central and bridge symptoms for aftermath of initial peak ('appetite change' and 'trouble of relaxing') were totally different from those at other pandemic phases ('sad mood'). CONCLUSIONS: This research identified the overall growing trend, long-term predictors, trajectory classes and evolutionary pattern of psychopathological network of psychological symptoms in 12 months after COVID-19 outbreak. It provides a multidimensional long-term psychological profile of the general population after COVID-19 outbreak, and accentuates the essentiality of continuous psychological monitoring, as well as population- and time-specific psychological management after COVID-19. We believe our findings can offer reference for long-term psychological management after pandemics.

A systematic review and meta-analysis on prevalence of and risk factors associated with depression, anxiety and insomnia in infectious diseases, including COVID-19: a call to action.

Infectious disease epidemics have become more frequent and more complex during the 21st century, posing a health threat to the general public and leading to psychological symptoms. The current study was designed to investigate the prevalence of and risk factors associated with depression, anxiety and insomnia symptoms during epidemic outbreaks, including COVID-19. We systematically searched the PubMed, Embase, Web of Science, OVID, Medline, Cochrane databases, bioRxiv and medRxiv to identify studies that reported the prevalence of depression, anxiety or insomnia during infectious disease epidemics, up to August 14th, 2020. Prevalence of mental symptoms among different populations including the general public, health workers, university students, older adults, infected patients, survivors of infection, and pregnant women across all types of epidemics was pooled. In addition, prevalence of mental symptoms during COVID-19 was estimated by time using meta-regression analysis. A total of 17,506 papers were initially retrieved, and a final of 283 studies met the inclusion criteria, representing a total of 948,882 individuals. The pooled prevalence of depression ranged from 23.1%, 95% confidential intervals (95% CI: [13.9-32.2]) in survivors to 43.3% (95% CI: [27.1-59.6]) in university students, the pooled prevalence of anxiety ranged from 25.0% (95% CI: [12.0-38.0]) in older adults to 43.3% (95% CI: [23.3-63.3]) in pregnant women, and insomnia symptoms ranged from 29.7% (95% CI: [24.4-34.9]) in the general public to 58.4% (95% CI: [28.1-88.6]) in university students. Prevalence of moderate-to-severe mental symptoms was lower but had substantial variation across different populations. The prevalence of mental problems increased over time during the COVID-19 pandemic among the general public, health workers and university students, and decreased among infected patients. Factors associated with increased prevalence for all three mental health symptoms included female sex, and having physical disorders, psychiatric disorders, COVID infection, colleagues or family members infected, experience of frontline work, close contact with infected patients, high exposure risk, quarantine experience and high concern about epidemics. Frequent exercise and good social support were associated with lower risk for these three mental symptoms. In conclusion, mental symptoms are common during epidemics with substantial variation across populations. The population-specific psychological crisis management are needed to decrease the burden of psychological problem and improve the mental wellbeing during epidemic.

Accessibility to Digital Mental Health Services among the General Public throughout COVID-19: Trajectories, Influencing Factors and Association with Long-Term Mental Health Symptoms.

Digital mental health services (DMHSs) have great potential for mitigating the mental health burden related to COVID-19, but public accessibility (ease of acquiring services when needed) to DMHSs during the pandemic is largely unknown. Accessibility to DMHSs was tracked longitudinally among a nationwide sample of 18,804 adults in China from before to one year after COVID-19 outbreak. Unconditional and conditional latent growth curve models and latent growth mixture models were fitted to explore the overall growth trend, influencing factors, and latent trajectory classes of accessibility to DMHSs throughout COVID-19. Generalized estimating equation models and generalized linear mixed models were employed to explore the association between accessibility to DMHSs and long-term mental health symptoms. We found that people generally reported increased difficulty in accessing DMHSs from before to one year after COVID-19 outbreak. Males, youngsters, individuals with low socioeconomic status, and individuals greatly affected by COVID-19 reported greater difficulty in accessing DMHSs. Four DMHS accessibility trajectory classes were identified: "lowest-great increase" (6.3%), "moderate low-slight increase" (44.4%), "moderate high-slight decrease" (18.1%) and "highest-great decrease" (31.2%). Trajectory classes reporting greater difficulty in accessing DMHSs were at higher risk for long-term mental symptoms. In conclusion, an overall increase in difficulty in accessing DMHSs is observed throughout COVID-19, and heterogeneity exists in DMHS accessibility trajectories. Our results suggest that easy access to DMHSs should be consistently facilitated. Moreover, access gaps should be reduced across demographic groups, and target populations for service allocation should alter as the pandemic evolves.

The Impact of Quarantine on Pain Sensation among the General Population in China during the COVID-19 Pandemic.

During the pandemic era, quarantines might potentially have negative effects and disproportionately exacerbate health condition problems. We conducted this cross-sectional, national study to ascertain the prevalence of constant pain symptoms and how quarantines impacted the pain symptoms and identify the factors associated with constant pain to further guide reducing the prevalence of chronic pain for vulnerable people under the pandemic. The sociodemographic data, quarantine conditions, mental health situations and pain symptoms of the general population were collected. After adjusting for potential confounders, long-term quarantine (≥15 days) exposures were associated with an increased risk of constant pain complaints compared to those not under a quarantine (Odds Ratio (OR): 1.26; 95% Confidence Interval (CI): 1.03, 1.54; p = 0.026). Risk factors including unemployment (OR: 1.55), chronic disease history (OR: 2.38) and infection with COVID-19 (OR: 2.15), and any of mental health symptoms including depression, anxiety, insomnia and PTSD (OR: 5.44) were identified by a multivariable logistic regression. Additionally, mediation analysis revealed that the effects of the quarantine duration on pain symptoms were mediated by mental health symptoms (indirect effects: 0.075, p < 0.001). These results advocated that long-term quarantine measures were associated with an increased risk of experiencing pain, especially for vulnerable groups with COVID-19 infection and with mental health symptoms. The findings also suggest that reducing mental distress during the pandemic might contribute to reducing the burden of pain symptoms and prioritizing interventions for those experiencing a long-term quarantine.

Analysis of the Mediating Effect of Risk Perception on the Relationship Between Time Perception and Mental Health of College Students During the COVID-19 Epidemic.

Background: COVID-19 has had a wide impact on the mental health of college students. This study aims to explore the relationship between time perception, risk perception, and the mental health of college students during COVID-19 through a questionnaire survey. Subjects: One thousand two hundred and eighteen college students, 449 male and 769 female, who studied online during the COVID-19 epidemic were selected. Methods: Time Perception Scale, Risk Perception Scale, and SCL-90 were used to investigate the relationship using correlation analysis. Results: During the COVID-19 period, mental health problems of college students were widespread, and 65.93% of college students reported moderate to severe mental health problems. The correlation analysis showed that risk perception, time perception, and the mental health of college students were significantly related. Risk perception played a partial mediating role between present enjoyment and mental health, and risk perception played a partial mediating role between future time perception and mental health. Conclusion: In the case of sudden public crises, we should pay close attention to the mental health of college students, adjust their attitude toward the present and the future, and pay attention to their perception of risk so as to improve their mental health level under crisis.

Neuropsychiatric manifestations of COVID-19, potential neurotropic mechanisms, and therapeutic interventions.

The coronavirus disease 2019 (COVID-19) pandemic has caused large-scale economic and social losses and worldwide deaths. Although most COVID-19 patients have initially complained of respiratory insufficiency, the presence of neuropsychiatric manifestations is also reported frequently, ranging from headache, hyposmia/anosmia, and neuromuscular dysfunction to stroke, seizure, encephalopathy, altered mental status, and psychiatric disorders, both in the acute phase and in the long term. These neuropsychiatric complications have emerged as a potential indicator of worsened clinical outcomes and poor prognosis, thus contributing to mortality in COVID-19 patients. Their etiology remains largely unclear and probably involves multiple neuroinvasive pathways. Here, we summarize recent animal and human studies for neurotrophic properties of severe acute respiratory syndrome coronavirus (SARS-CoV-2) and elucidate potential neuropathogenic mechanisms involved in the viral invasion of the central nervous system as a cause for brain damage and neurological impairments. We then discuss the potential therapeutic strategy for intervening and preventing neuropsychiatric complications associated with SARS-CoV-2 infection. Time-series monitoring of clinical-neurochemical-radiological progress of neuropsychiatric and neuroimmune complications need implementation in individuals exposed to SARS-CoV-2. The development of a screening, intervention, and therapeutic framework to prevent and reduce neuropsychiatric sequela is urgently needed and crucial for the short- and long-term recovery of COVID-19 patients.

Long-Term Impact of COVID-19 on Mental Health among the General Public: A Nationwide Longitudinal Study in China.

COVID-19 might have long-term mental health impacts. We aim to investigate the longitudinal changes in mental problems from initial COVID-19 peak to its aftermath among general public in China. Depression, anxiety and insomnia were assessed among a large-sample nationwide cohort of 10,492 adults during the initial COVID-19 peak (28 February 2020 to 11 March 2020) and its aftermath (8 July 2020 to 8 August 2020) using the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Insomnia Severity Index. We used generalized estimating equations and linear mixed models to explore factors associated with long-term mental health symptoms during COVID-19. During the five months, mental health symptoms remained consistently elevated (baseline 46.4%; follow-up 45.1%). Long-term depression, anxiety and insomnia were associated with several personal and work-related factors including quarantine (adjusted OR for any mental health symptoms 1.31, 95%CI 1.22-1.41, p < 0.001), increases in work burden after resuming work (1.77, 1.65-1.90, p < 0.001), occupational exposure risk to COVID-19 (1.26, 1.14-1.40, p < 0.001) and living in places severely affected by initial COVID-19 peak (1.21, 1.04-1.41, p = 0.01) or by a COVID-19 resurgence (1.38, 1.26-1.50, p < 0.001). Compliance with self-protection measures, such as wearing face masks (0.74, 0.61-0.90, p = 0.003), was associated with lower long-term risk of mental problems. The findings reveal a pronounced and prolonged mental health burden from the initial COVID-19 peak through to its aftermath in China. We should regularly monitor the mental health status of vulnerable populations throughout COVID-19.