Six addiction components of problematic social media use in relation to depression, anxiety, and stress symptoms: a latent profile analysis and network analysis.

BACKGROUNDS: Components of addiction (salience, tolerance, mood modification, relapse, withdrawal, and conflict) is the most cited theoretical framework for problematic social media use (PSMU). However, studies criticized its ability to distinguish problematic users from engaged users. We aimed to assess the association of the six criteria with depression, anxiety, and stress at a symptom level. METHODS: Ten thousand six hundred sixty-eight participants were recruited. Bergen Social Media Addiction Scale (BSMAS) was used to detect six addiction components in PSMU. We applied the depression-anxiety-stress scale to assess mental distress. Latent profile analysis (LPA) was conducted based on BSMAS items. Network analysis (NA) was performed to determine the symptom-symptom interaction of PSMU and mental distress. RESULTS: (1) Social media users were divided into five subgroups including occasional users (10.6%, n = 1127), regular users (31.0%, n = 3309), high engagement low risk users (10.4%, n = 1115), at-risk users (38.1%, n = 4070), and problematic users (9.8%, n = 1047); (2) PSMU and mental distress varied markedly across subgroups. Problematic users had the most severe PSMU, depression, anxiety, and stress symptoms. High engagement users scored high on tolerance and salience criteria of PSMU but displayed little mental distress; (3) NA showed conflict and mood modification was the bridge symptoms across the network, while salience and tolerance exhibited weak association with mental distress. CONCLUSIONS: Salience and tolerance might not distinguish engaged users from problematic users. New frameworks and assessment tools focusing on the negative consequences of social media usage are needed.

Night shifts, insomnia, anxiety, and depression among Chinese nurses during the COVID-19 pandemic remission period: A network approach.

Background: The outbreak of the COVID-19 pandemic imposed a heavy workload on nurses with more frequent night shifts, which led to higher levels of insomnia, depression, and anxiety among nurses. The study aimed to describe the symptom-symptom interaction of depression, anxiety, and insomnia among nurses and to evaluate the impact of night shifts on mental distress via a network model. Methods: We recruited 4,188 nurses from six hospitals in December 2020. We used the Insomnia Severity Index, Patient Health Questionnaire-9, and Generalized Anxiety Disorder Scale-7 to assess insomnia, depression, and anxiety, respectively. We used the gaussian graphical model to estimate the network. Index expected influence and bridge expected influence was adapted to identify the central and bridge symptoms within the network. We assessed the impact of night shifts on mental distress and compared the network structure based on COVID-19 frontline experience. Results: The prevalence of depression, anxiety, and insomnia was 59, 46, and 55%, respectively. Nurses with night shifts were at a higher risk for the three mental disorders. "Sleep maintenance" was the central symptom. "Fatigue," "Motor," "Restlessness," and "Feeling afraid" were bridge symptoms. Night shifts were strongly associated with sleep onset trouble. COVID-19 frontline experience did not affect the network structure. Conclusion: "Sleep maintenance," "Fatigue," "Motor," and "Restlessness" were important in maintaining the symptom network of anxiety, depression, and insomnia in nurses. Further interventions should prioritize these symptoms.

A network analysis of anxiety and depression symptoms among Chinese nurses in the late stage of the COVID-19 pandemic.

Background: Nurses 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. Method: A 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. Result: The 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. Conclusion: Restlessness 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.

The prevalence and risk factors of mental problems in medical students during COVID-19 pandemic: A systematic review and meta-analysis.

BACKGROUND: 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. METHOD: 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. RESULTS: 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. LIMITATIONS: Most studies were cross-sectional. Few studies provided a reasonable response rate, suggesting potential selection bias. CONCLUSIONS: 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.

Efficacy, immunogenicity and safety of COVID-19 vaccines in older adults: a systematic review and meta-analysis.

Background: Older adults are more susceptible to severe health outcomes for coronavirus disease 2019 (COVID-19). Universal vaccination has become a trend, but there are still doubts and research gaps regarding the COVID-19 vaccination in the elderly. This study aimed to investigate the efficacy, immunogenicity, and safety of COVID-19 vaccines in older people aged ≥ 55 years and their influencing factors. Methods: Randomized controlled trials from inception to April 9, 2022, were systematically searched in PubMed, EMBASE, the Cochrane Library, and Web of Science. We estimated summary relative risk (RR), rates, or standardized mean difference (SMD) with 95% confidence interval (CI) using random-effects meta-analysis. This study was registered with PROSPERO (CRD42022314456). Results: Of the 32 eligible studies, 9, 21, and 25 were analyzed for efficacy, immunogenicity, and safety, respectively. In older adults, vaccination was efficacious against COVID-19 (79.49%, 95% CI: 60.55-89.34), with excellent seroconversion rate (92.64%, 95% CI: 86.77-96.91) and geometric mean titer (GMT) (SMD 3.56, 95% CI: 2.80-4.31) of neutralizing antibodies, and provided a significant protection rate against severe disease (87.01%, 50.80-96.57). Subgroup and meta-regression analyses consistently found vaccine types and the number of doses to be primary influencing factors for efficacy and immunogenicity. Specifically, mRNA vaccines showed the best efficacy (90.72%, 95% CI: 86.82-93.46), consistent with its highest seroconversion rate (98.52%, 95% CI: 93.45-99.98) and GMT (SMD 6.20, 95% CI: 2.02-10.39). Compared to the control groups, vaccination significantly increased the incidence of total adverse events (AEs) (RR 1.59, 95% CI: 1.38-1.83), including most local and systemic AEs, such as pain, fever, chill, etc. For inactivated and DNA vaccines, the incidence of any AEs was similar between vaccination and control groups (p > 0.1), while mRNA vaccines had the highest risk of most AEs (RR range from 1.74 to 7.22). Conclusion: COVID-19 vaccines showed acceptable efficacy, immunogenicity and safety in older people, especially providing a high protection rate against severe disease. The mRNA vaccine was the most efficacious, but it is worth surveillance for some AEs it caused. Increased booster coverage in older adults is warranted, and additional studies are urgently required for longer follow-up periods and variant strains.

Efficacy, immunogenicity and safety of COVID-19 vaccines in older adults: a systematic review and meta-analysis

Background Older adults are more susceptible to severe health outcomes for coronavirus disease 2019 (COVID-19). Universal vaccination has become a trend, but there are still doubts and research gaps regarding the COVID-19 vaccination in the elderly. This study aimed to investigate the efficacy, immunogenicity, and safety of COVID-19 vaccines in older people aged ≥ 55 years and their influencing factors. Methods Randomized controlled trials from inception to April 9, 2022, were systematically searched in PubMed, EMBASE, the Cochrane Library, and Web of Science. We estimated summary relative risk (RR), rates, or standardized mean difference (SMD) with 95% confidence interval (CI) using random-effects meta-analysis. This study was registered with PROSPERO (CRD42022314456). Results Of the 32 eligible studies, 9, 21, and 25 were analyzed for efficacy, immunogenicity, and safety, respectively. In older adults, vaccination was efficacious against COVID-19 (79.49%, 95% CI: 60.55−89.34), with excellent seroconversion rate (92.64%, 95% CI: 86.77−96.91) and geometric mean titer (GMT) (SMD 3.56, 95% CI: 2.80−4.31) of neutralizing antibodies, and provided a significant protection rate against severe disease (87.01%, 50.80−96.57). Subgroup and meta-regression analyses consistently found vaccine types and the number of doses to be primary influencing factors for efficacy and immunogenicity. Specifically, mRNA vaccines showed the best efficacy (90.72%, 95% CI: 86.82−93.46), consistent with its highest seroconversion rate (98.52%, 95% CI: 93.45−99.98) and GMT (SMD 6.20, 95% CI: 2.02−10.39). Compared to the control groups, vaccination significantly increased the incidence of total adverse events (AEs) (RR 1.59, 95% CI: 1.38−1.83), including most local and systemic AEs, such as pain, fever, chill, etc. For inactivated and DNA vaccines, the incidence of any AEs was similar between vaccination and control groups (p > 0.1), while mRNA vaccines had the highest risk of most AEs (RR range from 1.74 to 7.22). Conclusion COVID-19 vaccines showed acceptable efficacy, immunogenicity and safety in older people, especially providing a high protection rate against severe disease. The mRNA vaccine was the most efficacious, but it is worth surveillance for some AEs it caused. Increased booster coverage in older adults is warranted, and additional studies are urgently required for longer follow-up periods and variant strains.

Mental health conditions and academic burnout among medical and non-medical undergraduates during the mitigation of COVID-19 pandemic in China.

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 < 0.001), moderate to severe anxiety symptoms (19.7% vs. 8.9%, P < 0.001), alcohol abuse/dependence (16.3% vs.10.3%, P < 0.001), excessive daytime sleepiness (47.4% vs. 43.4%, P = 0.018), high perceived stress (34.7% vs. 22.2%, P < 0.001), high level of fatigue (51.8% vs. 42.2%, P < 0.001), low QOL (35.8% vs. 21.4%, P < 0.001), and higher academic burnout score (59.4 vs. 57.5, P < 0.001). Being non-medical undergraduates, depression, alcohol abuse/dependence, excessive daytime sleepiness, and high perceived stress were positively associated with academic burnout, while high QOL was negatively associated with the burnout (all P < 0.001). Excessive daytime sleepiness was the strongest predictor for academic burnout.