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BackgroundNurses are at high risk for depression and anxiety symptoms after the outbreak of the COVID-19 pandemic. We aimed to assess the network structure of anxiety and depression symptoms among Chinese nurses in the late stage of this pandemic.MethodA total of 6,183 nurses were recruited across China from Oct 2020 to Apr 2021 through snowball sampling. We used Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder scale-7 (GAD-7) to assess depression and anxiety, respectively. We used the Ising model to estimate the network. The index “expected influence” and “bridge expected influence” were applied to determine the central symptoms and bridge symptoms of the anxiety-depression network. We tested the stability and accuracy of the network via the case-dropping procedure and non-parametric bootstrapping procedure.ResultThe network had excellent stability and accuracy. Central symptoms included “restlessness”, “trouble relaxing”, “sad mood”, and “uncontrollable worry”. “Restlessness”, “nervous”, and “suicidal thoughts” served as bridge symptoms.ConclusionRestlessness emerged as the strongest central and bridge symptom in the anxiety-depression network of nurses. Intervention on depression and anxiety symptoms in nurses should prioritize this symptom.

Atrial fibrillation (AF) is one of the most common types of arrhythmia worldwide; although a number of theories have been proposed to explain the mechanisms of AF, the treatment of AF is far from satisfactory. Energy metabolism is associated with the development of AF. Mitochondrial transcription factor A (TFAM) serves a role in the maintenance and transcription of mitochondrial DNA. The present study aimed to investigate the association between TFAM and AF and the effect of TFAM on ATP content in cardiomyocytes. Left atrial appendage tissues were collected from 20 patients with normal sinus rhythm (SR) and 20 patients with AF, and the expression levels of TFAM in SR and AF tissues were evaluated. In addition, a tachypacing model of primary cultured cardiomyocytes was constructed to assess ATP content, cell viability and expression levels of TFAM, mitochondrially encoded (MT)-NADH dehydrogenase 1 (ND1), MT-cytochrome c oxidase 1 (CO1), NADH ubiquinone oxidoreductase core subunit 1 (NDUFS1) and cytochrome c oxidase subunit 6C (COX6C). Finally, the effects of overexpression and inhibition of TFAM on ATP content, cell viability and the expression levels of MT-ND1 and MT-CO1 were investigated. The expression levels of TFAM were decreased in AF tissues compared with SR tissues (P0.05). Overexpression of TFAM increased ATP content, cell viability and expression levels of MT-ND1 and MT-CO1 (P

BACKGROUND AND AIMS Since its first release in 2011, WeChat (Chinese pinyin: Wei Xin) has been widely used to promote health. As the most popular all-in-one social media application providing free instant messaging, voice, text, pictures, videos and location information exchange via smartphone, WeChat holds promise for delivering smoking cessation services to a large number of people at low unit cost in China, a country with more than 300 million smokers. This protocol is for a study that aims to assess the efficacy of a WeChat-based smoking cessation intervention ('WeChat WeQuit') for treatment-seeking smokers in China. DESIGN In this two-arm randomized controlled trial (RCT), the control group will receive only a digital version of a booklet of 'Happy Quit'. The intervention group will also receive the 2 weeks pre- and 12 weeks post-quit 'WeChat WeQuit' intervention. Both groups will be followed-up to 26 weeks (6 months) after quit day. SETTING This on-line trial has no restrictions on setting or location. PARTICIPANTS Chinese-speaking current smokers (have smoked ≥100 cigarettes in their life-time and currently smoke cigarettes) aged 18+ years willing to make a quit attempt within 1 month (n = 2000) will be recruited by on- and off-line advertising. Potential participants will register their interest by sending WeChat messages or text messages, or making a voice call. MEASUREMENTS The primary outcome measure is self-reported 26-week continuous smoking abstinence with biological verification [test by clinic visit: expired carbon monoxide concentration

This meta-analysis and systematic review aimed to evaluate the global prevalence and risk factors of mental problems (i.e., depression, anxiety, stress, sleep disorder, posttraumatic stress disorder (PTSD), burnout, psychological distress, and suicidal ideation) among medical students during the COVID-19 pandemic.We searched PubMed, Embase, Web of Science, psycARTICLES, PsycINFO, CNKI, and Wan Fang for studies on the prevalence of mental problems among medical students from January 1, 2020, to April 1, 2022. The pooled prevalence was calculated by random-effect models. We performed a narrative review to identify the risk factors.The meta-analysis included 201 studies (N = 198,000). The prevalence of depression (41 %, 95 % CI, 37-45 %,), anxiety (38 %,95 % CI, 34 %-42 %), stress (34 %, 95 % CI, 27 %-42 %), sleep disorder (52 %, 95 % CI, 44 %-60 %), psychological distress (58 %, 95 % CI, 51 %-65 %), PTSD (34 %, 95 % CI, 22 %-46 %), suicidal ideation (15 %, 95 % CI, 11 %-18 %) and burnout (38 %, 95 % CI, 25 %-50 %) was high. The major risk factors were being female, being junior or preclinical students, exposure to COVID-19, academic stress, psychiatric or physical disorders history, economic trouble, fear of education impairment, online learning trouble, fear of infection, loneliness, low physical activity, low social support, problematic internet or smartphone use, and young age.Most studies were cross-sectional. Few studies provided a reasonable response rate, suggesting potential selection bias.The study demonstrated a high prevalence and risk factors for mental problems during COVID-19, calling for mental health services. Our findings are valuable for college and health authorities to identify high-risk students and provide targeted intervention.

A high attrition rate in medical students has exacerbated the physician shortage in China. However, few studies have explored the risk factors of dropout intention in medical postgraduates. This study compared the prevalence of dropout intention and mental distress between medical and non-medical postgraduates in China and investigated risk factors for dropout intention. This study also explored the impact of medical postgraduates' perception of the Chinese healthcare environment on their mental status and dropout intention.This cross-sectional study was conducted using online questionnaires from October 2020 to April 2021. Convenience sampling was used to recruit postgraduates in different majors. Outcomes included dropout intention and potential risk factors, including mental distress, quality of life, and fatigue. Medical postgraduates were additionally assessed for healthcare environment satisfaction, burnout, career choice regret, and experiences of workplace violence. A logistic regression model was constructed to evaluate the association between dissatisfaction, mental distress, and turnover intention.A total of 740 medical and 670 non-medical postgraduates participated in the survey. The rates of depression symptoms (33.8% vs. 39.0%, p 0.001), anxiety symptoms (22.2% vs. 32.4%, p 0.001), and somatic symptoms (34.7% vs. 42.4%, p = 0.004) were lower in medical postgraduates, while more medical postgraduates (58.4% vs. 48.4%, p 0.001) reported dropout intention. Dissatisfaction with the healthcare environment (odds ratio [OR]: 1.65; 95% confidence interval [CI]: 1.17-2.34, p = 0.005), career choice regret (OR: 6.23; 95% CI: 4.42-8.78, p 0.001), and high perceived stress (OR: 2.74; 95%CI: 1.90-3.94, p 0.001) remained independently associated with turnover intention.Mental distress is common among postgraduates, calling for timely interventions. Medical postgraduates reported higher turnover intention. Healthcare environment perception also affected the mental health and dropout intentions of medical students. A decent future income, reduced workload, shorter duration medical training, and better doctor-patient relationships are urgently needed.

The outbreak of the novel coronavirus disease 2019 (COVID-19) has posed a great impact on people’s mental health, especially for undergraduate students. This study aimed to compare the mental health conditions and academic burnout between medical and non-medical undergraduates in China when the COVID-19 pandemic is mitigating. A cross-sectional online survey was conducted among 4,972 undergraduates between October 2020 and April 2021, when the pandemic was basically under control. The survey included basic demographics information and standardized scales to evaluate depression, anxiety, perceived stress, daytime sleepiness, alcohol abuse/dependence, quality of life, fatigue, and academic burnout. Compared with medical undergraduates, non-medical undergraduates had higher rates of moderate to severe depression symptoms (29.1% vs. 17.9%, P P P P = 0.018), high perceived stress (34.7% vs. 22.2%, P P P P P

Background Although some psychological processes, such as stigma and self-efficacy, affect the complicated relationship between social support and depressive symptoms, few studies explored a similar psychological mechanism among individuals with substance use disorders (SUDs). Hence, this research investigates the mediating effects of stigma and the moderating effects of self-efficacy among the psychological mechanism that social support affects depressive symptoms. Methods The study included 1040 Chinese participants with SUDs and completed a series of self-report questionnaires. R software was used to organize and clean up data sets and analyze mediation and moderation effects. Results The result showed that stigma partially mediated depressive symptoms, while self-efficacy moderated this relationship. More specifically, less social support increased depression symptoms by bringing about higher stigma. Besides, subjects with higher self-efficacy are less susceptible to stigma and therefore have mild depressive symptoms. Furthermore, clinical and theoretical implications are discussed in our study. Conclusions Chinese SUDs patients’ depressive symptoms were indirectly affected by perceived social support via stigma and less affected by stigma with improved self-efficacy. The theoretical and practical implications of these results are discussed.

The doctor–patient relationship (DPR) is essential in the process of medical consultations and treatments. Poor DPR may lead to poor medical outcomes, medical violence against doctors, and a negative perception of the healthcare system. Little is known about how DPR is affected during this novel coronavirus disease 2019 (COVID-19) pandemic. This cross-sectional study aimed to explore the DPR during the COVID-19 pandemic. There were 1,903 participants in China (95% response rate) who were recruited during the pandemic online via convenience and snowball sampling. Several questionnaires were used to evaluate participants' attitudes toward DPR, including the Patient–Doctor Relationship Questionnaire (PDRQ-9), Chinese Wake Forest Physician Trust Scale (C-WFPTS), a survey on medical violence against doctors, factors that affect and improve DPR, and general trust in medical services. Results revealed that DPR improved, and doctor–patient trust increased compared to participants' retrospective attitude before the pandemic. In addition, patients' violence against doctors decreased during the pandemic. Better doctor–patient trust and lower violence toward doctors are related to better DPR. Furthermore, we found that the main factors that could improve DPR include communication between doctors and patients, medical technology and services, and medical knowledge for patients. This study helped to better understand DPR in China, which may contribute to future health policies and medical practices in order to improve DPR and doctor–patient trust.

Background Nearly half of the patients with depression experience suboptimal benefits from antidepressants. Neuromodulation therapies, a kind of technology that can regulate neuronal firing activity by electrical or magnetic stimulation, were introduced to improve this situation. However, the results from clinical trials have been inconsistent. Methods We followed the extension of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to perform this network meta-analysis (NMA). The results were evaluated by relative risk (RR) for the response, remission, and discontinuation rates. Results In total, 49 trials with 2,941 patients were included in this study. Bilateral theta burst stimulation (TBS, RR 5.00, 95% CI 1.11-22.44), priming transcranial magnetic stimulation (pTMS, RR 2.97, 95% CI 1.20-7.39), low-frequency right repetitive transcranial magnetic stimulation (TMS) (LFR-rTMS, RR 2.62, 95% CI 1.56-4.39), high-frequency left repetitive TMS (HFL-rTMS, RR 2.18, 95% CI 1.52-3.13), and bilateral repetitive TMS (BL-rTMS, RR 3.08, 95% CI 1.78-5.31) were demonstrated to have higher response rates than sham control. BL-rTMS (RR 3.12, 95% CI 1.06-9.09) was found to have a higher response rate than deep brain stimulation in this NMA. All measures had the non-inferiority acceptability than the sham-control. BL-rTMS was more acceptable than bitemporal ECT (BT-ECT, RR 0.18, 95% CI 0.03-0.89), while pTMS was more acceptable than BT-ECT (RR 0.08, 95% CI 0.01-0.55), HFL-rTMS (RR 0.34, 95% CI 0.12-0.93), and deep TMS (RR 0.15, 95% CI 0.02-0.96). Conclusion Besides electroconvulsive therapy (ECT), rTMS, priming TMS, and bilateral TBS proved effective for patients with treatment-resistant depression (TRD). BL-rTMS showed high efficacy and acceptability, and bilateral TBS had the potential to be the most efficacious neuromodulation measures.

Background Bipolar disorder (BPD) is a common mood disorder that is often goes misdiagnosed or undiagnosed. Recently, machine learning techniques have been combined with neuroimaging methods to aid in the diagnosis of BPD. However, most studies have focused on the construction of classifiers based on single-modality MRI. Hence, in this study, we aimed to construct a support vector machine (SVM) model using a combination of structural and functional MRI, which could be used to accurately identify patients with BPD. Methods In total, 44 patients with BPD and 36 healthy controls were enrolled in the study. Clinical evaluation and MRI scans were performed for each subject. Next, image pre-processing, VBM and ReHo analyses were performed. The ReHo values of each subject in the clusters showing significant differences were extracted. Further, LASSO approach was recruited to screen features. Based on selected features, the SVM model was established, and discriminant analysis was performed. Results After using the two-sample t-test with multiple comparisons, a total of 8 clusters were extracted from the data (VBM = 6; ReHo = 2). Next, we used both VBM and ReHo data to construct the new SVM classifier, which could effectively identify patients with BPD at an accuracy of 87.5% (95%CI: 72.5–95.3%), sensitivity of 86.4% (95%CI: 64.0–96.4%), and specificity of 88.9% (95%CI: 63.9–98.0%) in the test data (p = 0.0022). Conclusions A combination of structural and functional MRI can be of added value in the construction of SVM classifiers to aid in the accurate identification of BPD in the clinic.

Background Atrial fibrillation (AF) is one of the most common arrhythmia, which brings huge burden to the individual and the society. However, the mechanism of AF is not clear. This paper aims at screening the key differentially expressed genes (DEGs) of atrial fibrillation and to construct enrichment analysis and protein-protein interaction (PPI) network analysis for these DEGs. Methods The datasets were collected from the Gene Expression Omnibus database to extract data of left atrial appendage (LAA) RNA of patients with or without AF in GSE79768, GSE31821, GSE115574, GSE14975 and GSE41177. Batch normalization, screening of the differential genes and gene ontology analysis were finished by R software. Reactome analysis was used for pathway analysis. STRING platform was utilized for PPI network analysis. At last, we performed reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to validate the expression of key genes in 20 sinus rhythm (SR) LAA tissues and 20 AF LAA tissues. Results A total of 106 DEGs were screened in the merged dataset. Among these DEGs, 74 genes were up-regulated and 32 genes down-regulated. DEGs were mostly enriched in extracellular matrix organization, protein activation cascade and extracellular structure organization. In PPI network, we identified SPP1, COL5A1 and VCAN as key genes which were associated with extracellular matrix. RT-qPCR showed the same expression trend of the three key genes as in our bioinformatics analysis. The expression levels of SPP1, COL5A1 and VCAN were increased in AF tissues compared to SR tissues (P Conclusion According to the analyses which were conducted by bioinformatics tools, genes related to extracellular matrix were involved in pathology of AF and may become the possible targets for the diagnosis and treatment of AF.

Background Problematic mobile phone use (PMPU) has become a public health issue in China, particularly in adolescents and young adults. The Problematic Mobile Phone Use Questionnaire-Short Version (PMPUQ-SV) is a validated instrument that measures multiple aspects of PMPU. The current study aimed to test the psychometric characteristics of a Chinese adaption of the PMPUQ-SV and examine its measurement invariance across gender. Methods A total of 2086 participants were recruited form nine schools (six undergraduate colleges and three vocational colleges) through an online platform. Measures included socio-demographic variables, patterns of mobile phone use, the Chinese version of the PMPUQ-SV (C-PMPUQ-SV), the Chinese version of the Smartphone Addiction Proneness Scale (C-SAPS), and the Depression Anxiety Stress Scales (DASS-21). Results Exploratory and confirmatory factor analyses conducted in two independent subsamples confirmed that the postulated dimensions fit the data well. Four items, judged as either outdated or not adapted to the Chinese context, performed poorly and were removed, resulting in a shorter 11-item scale. Convergent validity was established through correlations between emotional symptoms and the C-PMPUQ-SV and addictive smartphone use. Additional measurement invariance analyses showed that the scale performed largely similarly in male and female participants. Conclusions The present study demonstrated that the C-PMPUQ-SV is an adequate instrument to study various types of PMPU in Chinese adolescents and young adults. The updated 11-item scale shortens the evaluation time and is adapted to assess contemporary smartphone use.

IntroductionFace-touching behaviour often happens frequently and automatically, and poses potential risk for spreading infectious disease. Mindfulness-based interventions (MBIs) have shown its efficacy in the treatment of behaviour disorders. This study aims to evaluate an online mindfulness-based brief intervention skill named ‘STOP (Stop, Take a Breath, Observe, Proceed) touching your face’ in reducing face-touching behaviour.Methods and analysisThis will be an online-based, randomised, controlled, trial. We will recruit 1000 participants, and will randomise and allocate participants 1:1 to the ‘STOP touching your face’ (both 750-word text and 5 min audio description by online) intervention group (n=500) and the wait-list control group (n=500). All participants will be asked to monitor and record their face-touching behaviour during a 60 min period before and after the intervention. Primary outcome will be the efficacy of short-term mindfulness-based ‘STOP touching your face’ intervention for reducing the frequency of face-touching. The secondary outcomes will be percentage of participants touching their faces; the correlation between the psychological traits of mindfulness and face-touching behaviour; and the differences of face-touching behaviour between left-handers and right-handers. Analysis of covariance, regression analysis, χ2 test, t-test, Pearson’s correlations will be applied in data analysis. We will recruit 1000 participants from April to July 2020 or until the recruitment process is complete. The follow-up will be completed in July 2020. We expect all trial results to be available by the end of July 2020.Ethics and disseminationThe study protocol has been approved by the Ethics Committee of Sir Run Run Shaw Hospital, an affiliate of Zhejiang University, Medical College (No. 20200401-32). Study results will be disseminated via social media and peer-reviewed publications.Trial registration numberNCT04330352.