•The prevalence of posttraumatic stress symptoms (PTSS) in China hardest-hit areas a month after the COVID-19 outbreak was 7%.•Hierarchical regression analysis and non-parametric test suggested that ...women reported significant higher PTSS in the domains of re-experiencing, negative alterations in cognition or mood, and hyper-arousal.•Participants with better sleep quality or less frequency of early awakenings reported lower PTSS.
The outbreak of COVID-19 in China in December 2019 has been identified as a pandemic and a health emergency of global concern. Our objective was to investigate the prevalence and predictors of posttraumatic stress symptoms (PTSS) in China hardest-hit areas during COVID-19 outbreak, especially exploring the gender difference existing in PTSS. One month after the December 2019 COVID-19 outbreak in Wuhan China, we surveyed PTSS and sleep qualities among 285 residents in Wuhan and surrounding cities using the PTSD Checklist for DSM-5 (PCL-5) and 4 items from the Pittsburgh Sleep Quality Index (PSQI). Hierarchical regression analysis and non-parametric test were used to analyze the data. Results indicated that the prevalence of PTSS in China hardest-hit areas a month after the COVID-19 outbreak was 7%. Women reported significant higher PTSS in the domains of re-experiencing, negative alterations in cognition or mood, and hyper-arousal. Participants with better sleep quality or less frequency of early awakenings reported lower PTSS. Professional and effective mental health services should be designed in order to aid the psychological wellbeing of the population in affected areas, especially those living in hardest-hit areas, females and people with poor sleep quality.
•The prevalence of PTSD among the Chinese public one month after the COVID-19 outbreak was 4.6%.•Female, having recent epidemic area contact history, population at high risk of infection, and poor ...sleep quality were identified as risk factors for PTSD.•With regard to psychological intervention during the COVID-19 outbreak, females, people with poor sleep quality, and those who are at high risk of infection, such as people residing in high disease-prevalent regions and having had close contact with patients deserve special attention.
To examine the prevalence of and risk factors for acute posttraumatic stress disorder (PTSD) shortly after the massive outbreak of COVID-19 in China.
An online anonymous survey was conducted between 30 January and 3 February, 2020. The survey included two self-administered questionnaires: one collected personal information (gender, age, education background), current location, recent epidemic area contact history, the classification of population, and subjective sleep quality; the other was the PTSD Checklist for DSM-5 (PCL-5).
A total of 2091 Chinese participated in the current study. The prevalence of PTSD among the Chinese public one month after the COVID-19 outbreak was 4.6%. Multiple linear regression analysis revealed that gender (p < 0.001), epidemic area contact history (p = 0.047), classification of population (p < 0.001), and subjective sleep quality (p < 0.001) could be regarded as predictors for PTSD.
First, the majority of participants in this study were the general public, with confirmed or suspected patients being a small part. Second, the measurement of PTSD in this study might be vulnerable to selection bias because of an online self-report study, such as participants’ recruitment. Third, the prevalence of PTSD in this study was estimated by an online questionnaire rather than a clinical interview.
The results suggested that some Chinese showed acute PTSD during the COVID-19 outbreak. Therefore, comprehensive psychological intervention needs further implementation. Furthermore, females, people who had recent epidemic area contact history, those at high risk of infection or with poor sleep quality deserve special attention.
Corona virus disease 2019 (COVID‐19) outbreak has attracted worldwide attention. The COVID‐19 outbreak is unique in its rapid transmission and results in heavy stress for the front‐line health care ...workers (HCWs). The current study aimed to exam posttraumatic stress symptoms (PTSSs) of HCWs fighting for the COVID‐19 and to evaluate their sleep quality after 1‐month stressful suffering. Three hundred seventy‐seven HCWs working in different provinces of China participated in the survey between February 1 and 5. The demographic information was collected first. Posttraumatic Stress Disorder Checklist for DSM‐5 (PCL‐5) and the Pittsburgh Sleep Quality Index (PSQI) were selected to measure PTSSs and sleep quality. Results showed that 1 month after the outbreak, the prevalence of PTSSs was 3.8% in HCWs. Female HCWs were more vulnerable to PTSSs with hazard ratio of 2.136 (95% CI = 1.388–3.286). HCWs with higher exposure level also significantly rated more hyperarousal symptoms (hazard ratio = 4.026, 95% CI = 1.233–13.140). There was a significant difference of sleep quality between participants with and without PTSSs (z value = 6.014, p < .001) and among different groups with various contact frequencies (chi‐square = 7.307, p = .026). Path analysis showed that there was a significant indirect effect from exposure level to PTSSs through sleep quality (coefficient = 1.750, 95% CI of Boostroop test = 0.543–2.998). In summary, targeted interventions on sleep contribute to the mental recovery during the outbreak of COVID‐19. Understanding the mental health response after a public health emergency might help HCWs and communities prepare for a population's response to disaster.
The long-term health consequences of the COVID-19 pandemic on health care workers (HCWs) are largely unclear. The purpose of the present study was to investigate the development of posttraumatic ...stress disorder (PTSD) in HCWs in a longitudinal manner. Additionally, we further explored the role of risk perception in the evolution of PTSD over time based on a one-year follow-up study. HCWs were recruited from hospitals in Guangdong, China. Demographic information, the PTSD checklist for DSM-5 (PCL-5) and the risk perception questionnaire were obtained online at two different time points: May to June 2020 (T1), with 317 eligible responses, and June 2021 (T2), with 403 eligible responses. Seventy-four HCWs participated in the survey at both T1 and T2. The results revealed that (1) the PTSD prevalence rate in the HCWs (cut-off = 33) increased from 10.73% at T1 to 20.84% at T2, and the HCWs reported significantly higher PTSD scores at T2 than at T1 (p < 0.001); (2) risk perception was positively correlated with PTSD (p < 0.001); and (3) PTSD at T1 could significantly positively predict PTSD at T2 (β = 2.812, p < 0.01), and this longitudinal effect of PTSD at T1 on PTSD at T2 was mediated by risk perception at T2 (coefficient = 0.154, 95% CI = 0.023 to 0.297). Our data provide a snapshot of the worsening of HCWs' PTSD along with the repeated pandemic outbreaks and highlight the important role of risk perception in the development of PTSD symptoms in HCWs over time.
The impact of 2019 coronavirus disease (COVID-19) outbreak on mental health was of widespread concern recently. The present study aimed to exam sleep quality and posttraumatic stress symptoms (PTSS) ...and potential influence factors in the first phases of COVID-19 massive outbreak in China. A snowball sampling technique was used and a total of 2027 Chinese participated in the present study. Demographic information, epidemic area contact history, sleep quality and PTSS data were collected with an internet-based cross-sectional survey. Results suggested that 59.7% participants were not fully satisfied with their sleep quality, and 50.9% participants had various degrees of short sleep duration problems. 44.1% and 33.0% participants had sleep disturbance and sleep onset latency problems. Also, the prevalence of PTSS reached 4.7% in the self-rating survey. Epidemic area contact history affected PTSS and latency onset of sleep under the influence of COVID-19. Epidemic area contact history and sleep quality had interaction effects on PTSS. The present study was one of the first to evaluate acute psychological responses and possible risk factors during the peak of COVID-19 in China and results indicate that keeping good sleep quality in individuals with pandemic exposure experiences is a way to prevent PTSS.
The Omicron pandemic struck Shanghai, China, resulting in impairments of both physical and psychological health on those patients who were confirmed and transferred to the Fangcang shelters. The way ...of isolation led to high risk of posttraumatic stress symptoms (PTSS) and depressive symptoms among the patients in Fangcang shelters. We aim to estimate the prevalence and comorbidity of PTSS and depressive symptoms in patients from China's Fangcang shelters during the epidemic.
Demographic information questionnaire, the posttraumatic stress disorder checklist for DSM-5 (PCL-5), and Patient Health Questionnaire (PHQ-9) were used in the study. The data were collected online via mobile phones during 10th April to 20th April, 2022, as part of our Psychological Trauma Recover Project-5-6 (PTRP-5-6), a longitudinal study focusing on individuals who have experienced trauma.
A total of 336 subjects were included in the analysis. The results revealed (1) the prevalence of depressive symptoms, and PTSS were 30.1% (cut-off = 10) and 6% (cut-off = 33); (2) Multiple logistic regression showed that female (OR = 3.04, p < 0.05), suffering from dyspnea (OR = 5.83, p < 0.05) or gastrointestinal symptoms (OR = 6.38, p < 0.05) were risk factors for PTSS; higher education level (OR = 3.27, p < 0.05) and suffering from dizziness or headache (OR = 2.46, p < 0.05) were risk factors for depressive symptoms; (3)Respectively, 85% of the patients who reported PTSS also experienced depressive symptoms, 16.8% of the patients who reported depressive symptoms presented PTSS.
In the context of COVID-19, the comorbidity rate of PTSS and depressive symptoms among patients in Fangcang shelters increased with the severity of depressive symptoms.
Background
Isolation is a special environment that will affect the mental health and behavior of individuals. The current study was to explore the relationship between behavior intention (BI) and ...perceived stress in isolated environment during Shanghai Omicron pandemic.
Methods
A cross‐sectional study was conducted between April 8 and 14, 2022. Three self‐reported questionnaires were used to evaluate quarantine duration, stress perception, and BI. A total of 1042 participants in Shanghai under quarantine at home were included by random sampling. Logistic regression and one‐way variance analysis were used to determine the risk factors related to BI.
Results
The finding implicated negative BI was more reported by the population of males, with lower educational background, with jobs, and youngers. A negative association existed between perceived stress and BI (B = −1.004, p = .003, OR = 0.367, 95% CI = .191–.703). The proportion of positive BI decreased with quarantined duration, whereas the negative BI seemed vibrate upward then downward.
Conclusion
There existed a significant effect of quarantined days on perceived stress with different BIs. High perceived stress was a risk factor of positive BI. This preliminary study has significance to understand the effect of compulsory measures on BI and for policies makers to take a psychosocial perspective to consider the effective pandemic intervention strategies.
This preliminary study was to see the feasibility of behavioral intentions (BI) as an indirect evaluation on psychosocial endurance, by exploring the relationship between BI and perceived stress, of individuals isolated. There existed a significant effect of quarantined days on perceived stress with different BIs. High perceived stress was a risk factor of positive BI. Understanding the effect of compulsory measures on BI may inform future effective pandemic intervention strategies.
Abstract
Background
Since COVID-19 broke out worldwide, it had caused extensive public health concerns and psychological distress, including PTSD and stigmatization towards recovered patients and ...people from high-risk areas. However, the association between PTSD, stigmatization and certain related factors have not been confirmed.
Methods
Through cluster random sampling, 946 Chinese graduates were investigated from 5 universities in Shanghai at three months after China lifted its coronavirus lockdown. PTSD symptoms were evaluated with PCL-5. Demographic and disease-related characteristics including stigmatization, educational attainment and working position were collected to assess their association with PTSD.
Results
12.4% graduates were reported significant PTSD symptoms in PCL-5 screening with a cut-off of 33. Graduates with a Master’s degree (
P
= 0.02) or working position like “looking for a job” and “planning to go abroad” (
P
= 0.038) showed severer stigmatization related to COVID-19. Stigmatization towards both patients recovering from COVID-19 and people from high-risk areas had significant association with PTSD symptoms. Multivariate linear regression analysis showed that stigmatization can explain 5% of variation of PCL-5 scores after controlling gender, age, educational attainments and working position.
Conclusion
Graduates who were looking for jobs or preparing to go abroad showed more stigmatization related to COVID-19. There was a positive correlation between stigma against COVID-19 and PTSD symptoms. More attention should be paid to the mental health status of graduates who are preparing to go abroad or looking for jobs.
Posttraumatic stress disorder (PTSD) recently becomes one of the most important mental health concerns. However, no previous study has comprehensively reviewed the application of big data and machine ...learning (ML) techniques in PTSD. We found 873 studies meet the inclusion criteria and a total of 31 of those in a sample of 210,001 were included in quantitative analysis. ML algorithms were able to discriminate PTSD with an overall accuracy of 0.89. Pooled estimates of classification accuracy from multi-dimensional data (0.96) are higher than single data types (0.86 to 0.90). ML techniques can effectively classify PTSD and models using multi-dimensional data perform better than those using single data types. While selecting optimal combinations of data types and ML algorithms to be clinically applied at the individual level still remains a big challenge, these findings provide insights into the classification, identification, diagnosis and treatment of PTSD.
Recent years have witnessed a persistent threat to public mental health, especially during and after the COVID-19 pandemic. Posttraumatic stress disorder (PTSD) has emerged as a pivotal concern ...amidst this backdrop. Concurrently, machine learning (ML) techniques have progressively applied in the realm of mental health. Therefore, our present undertaking seeks to provide a comprehensive assessment of studies employing ML methods that use diverse data modalities on the classification of people with PTSD.
In pursuit of pertinent studies, we will search both English and Chinese databases from January 2000 to May 2022. Two researchers will independently conduct screening, extract data and assess study quality. We intend to employ the assessment framework introduced by Luis Francisco Ramos-Lima in 2020 for quality evaluation. Rate, standard error and 95% CIs will be utilized for effect size measurement. A Cochran's Q test will be applied to assess heterogeneity. Subgroup and sensitivity analysis will further elucidate the source of heterogeneity and funnel plots and Egger's test will detect publication bias.
This systematic review and meta-analysis does not encompass patient interactions or engagements with healthcare providers. The outcomes of this research will be disseminated through scholarly channels, including presentations at scientific conferences and publications in peer-reviewed journals.
CRD42023342042.
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