A network analysis of the interrelationships between depression, anxiety, insomnia and quality of life among fire service recruits.

Background: Research on the mental health and quality of life (hereafter QOL) among fire service recruits after the end of the COVID-19 restrictions is lacking. This study explored the network structure of depression, anxiety and insomnia, and their interconnections with QOL among fire service recruits in the post-COVID-19 era. Methods: This cross-sectional study used a consecutive sampling of fire service recruits across China. We measured the severity of depression, anxiety and insomnia symptoms, and overall QOL using the nine-item Patient Health Questionnaire (PHQ-9), seven-item Generalized Anxiety Disorder scale (GAD-7), Insomnia Severity Index (ISI) questionnaire, and World Health Organization Quality of Life-brief version (WHOQOL-BREF), respectively. We estimated the most central symptoms using the centrality index of expected influence (EI), and the symptoms connecting depression, anxiety and insomnia symptoms using bridge EI. Results: In total, 1,560 fire service recruits participated in the study. The prevalence of depression (PHQ-9 ≥ 5) was 15.2% (95% CI: 13.5-17.1%), while the prevalence of anxiety (GAD-7 ≥ 5) was 11.2% (95% CI: 9.6-12.8%). GAD4 ("Trouble relaxing") had the highest EI in the whole network model, followed by ISI5 ("Interference with daytime functioning") and GAD6 ("Irritability"). In contrast, PHQ4 ("Fatigue") had the highest bridge EI values in the network, followed by GAD4 ("Trouble relaxing") and ISI5 ("Interference with daytime functioning"). Additionally, ISI4 "Sleep dissatisfaction" (average edge weight = -1.335), which was the central symptom with the highest intensity value, had the strongest negative correlation with QOL. Conclusion: Depression and anxiety were important mental health issues to address among fire service recruits in the post-COVID-19 era in China. Targeting central and bridge symptoms identified in network analysis could help address depression and anxiety among fire service recruits in the post-COVID-19 era.

Deep transcranial magnetic stimulation for schizophrenia: a systematic review.

Background: The efficacy and safety of deep transcranial magnetic stimulation (dTMS) as an intervention for schizophrenia remain unclear. This systematic review examined the efficacy and safety of dTMS for schizophrenia. Methods: A systematic search of Chinese (WanFang and Chinese Journal Net) and English databases (PubMed, EMBASE, PsycINFO, and Cochrane Library) were conducted. Results: Three randomized clinical trials (RCTs) comprising 80 patients were included in the analyses. Active dTMS was comparable to the sham treatment in improving total psychopathology, positive symptoms, negative symptoms, and auditory hallucinations measured by the Positive and Negative Syndrome Scale (PANSS), the Scale for the Assessment of Positive Symptoms (SAPS), the Scale for the Assessment of Negative Symptoms (SANS), and the Auditory Hallucinations Rating Scale (AHRS), respectively. Only one RCT reported the effects on neurocognitive function measured by the Cambridge Neuropsychological Test Automated Battery (CANTAB), suggesting that dTMS may only improve one Stockings of Cambridge measure (i.e., subsequent times for five move problems). All three studies reported overall discontinuation rates, which ranged from 16.7% to 44.4%. Adverse events were reported in only one RCT, the most common being tingling/twitching (30.0%, 3/10), head/facial discomfort (30.0%, 3/10), and back pain (20.0%, 2/10). Conclusion: This systematic review suggests that dTMS does not reduce psychotic symptoms in schizophrenia, but it shows potential for improving executive functions. Future RCTs with larger sample sizes focusing on the effects of dTMS on psychotic symptoms and neurocognitive function in schizophrenia are warranted to further explore these findings.

Global prevalence of major depressive disorder in LGBTQ+ samples: A systematic review and meta-analysis of epidemiological studies.

BACKGROUND: LGBTQ+ populations have been reported to have higher rates of depression compared with their heterosexual peers. Such data provided us the impetus to conduct a meta-analysis on the worldwide prevalence of major depressive disorder (MDD) in LGBTQ+ populations and moderating factors that contributed to differences in prevalence estimates between studies. METHODS: A systematic literature search was performed in major international (PubMed, PsycINFO, Web of Science, EMBASE) and Chinese (Chinese Nation Knowledge Infrastructure (CNKI) and WANFANG) databases from dates of inception to 10 December 2021. RESULTS: 48 articles comprising 4,616,903 individuals were included in the meta-analysis. The overall prevalence of MDD was 32.2 % (95%CI: 30.8-33.6 %, I2 = 99.6 %, τ2 = 0.284). MDD prevalence was higher in the LGBTQ+ samples from the United States than other countries, though the difference was not significant in moderator analyses. Moderator analyses indicated point and lifetime prevalence of MDD were significantly higher than estimates based on the past year (Q = 6.270, p = 0.043). Furthermore, studies that relied on convenience sampling had a higher prevalence of MDD than those based on other sampling methods (Q = 8.159, p = 0.017). In meta-regression analyses, mean age (B = 0.03, z = 9.54, p < 0.001) and study quality assessment score (B = 0.24, z = 67.64, p < 0.001) were positively associated with pooled prevalence of MDD while mediation data of year of study (B = -0.08, z = -72.55, p < 0.001) and sample size (B = -1.46, z = -37.83, p < 0.001) were negatively associated with pooled prevalence of MDD in LGBTQ+ samples. CONCLUSIONS: MDD is common among in LGBTQ+ individuals. Considering the negative consequences MDD has on daily life and well-being, appropriate prevention and treatment measures should be provided to vulnerable members of these populations. The findings of this meta-analysis could facilitate identifying at-risk subgroups, developing relevant health policy for LGBTQ+ individuals and allocating health resources from an intersectionality perspective.

The network structures of mental and behavioral problems among children and adolescents in China using propensity score matching: A comparison between one-child and multi-child families based on a nationwide survey.

BACKGROUND: Exploring networks of mental and behavioral problems in children and adolescents may identify differences between one-child and multi-child families. This study compared the network structures of mental and behavioral problems in children and adolescents in one-child families versus multi-child families based on a nationwide survey. METHODS: Propensity score matching (PSM) was used to match children and adolescents from one-child families with those from multi-child families. Mental and behavioral problems were assessed using the Achenbach's Child Behavior Checklist (CBCL) with eight syndromal subscales. In the network analysis, strength centrality index was used to estimate central symptoms, and case-dropping bootstrap method was used to assess network stability. RESULTS: The study included 39,648 children and adolescents (19,824 from one-child families and 19,824 from multi-child families). Children and adolescents from multi-child families exhibited different network structure and higher global strength compared to those from one-child families. In one-child families, the most central symptoms were "Social problems", "Anxious/depressed" and "Withdrawn/depressed", while in multi-child families, the most central symptoms were "Social problems", "Rule-breaking behavior" and "Anxious/depressed". CONCLUSION: Differences in mental and behavioral problems among children and adolescents between one-child and multi-child families were found. To address these problems, interventions targeting "Social problems" and "Anxious/depressed" symptoms should be developed for children and adolescents in both one-child and multi-child families, while other interventions targeting "Withdrawn/depressed" and "Rule-breaking behavior" symptoms could be useful for those in one-child and multi-child families, respectively.

Narrative Review and Consensus Recommendations for the Use of Transnasal Humidified Rapid-Insufflation Ventilatory Exchange in Modified Electroconvulsive Therapy.

Transnasal humidified rapid-insufflation ventilatory exchange (THRIVE) is a safe, effective, and novel technique that is currently being used in electroconvulsive therapy (ECT). This study aimed to summarize the clinical practices of THRIVE use in ECT to aid physicians and institutions in implementing the best practice guidelines for ECT. Thus, we reviewed the current literature and presented our consensus on the application of THRIVE in ECT in daily clinical practice. This consensus provides information regarding THRIVE use in ECT, including its safety, effectiveness, procedures, precautions, special case management, and application in special populations. Moreover, it guides the standardized use of THRIVE in ECT.

Prevalence and network structure of depression, insomnia and suicidality among mental health professionals who recovered from COVID-19: a national survey in China.

Psychiatric syndromes are common following recovery from Coronavirus Disease 2019 (COVID-19) infection. This study investigated the prevalence and the network structure of depression, insomnia, and suicidality among mental health professionals (MHPs) who recovered from COVID-19. Depression and insomnia were assessed with the Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index questionnaire (ISI7) respectively. Suicidality items comprising suicidal ideation, suicidal plan and suicidal attempt were evaluated with binary response (no/yes) items. Network analyses with Ising model were conducted to identify the central symptoms of the network and their links to suicidality. A total of 9858 COVID-19 survivors were enrolled in a survey of MHPs. The prevalence of depression and insomnia were 47.10% (95% confidence interval (CI) = 46.09-48.06%) and 36.2% (95%CI = 35.35-37.21%), respectively, while the overall prevalence of suicidality was 7.8% (95%CI = 7.31-8.37%). The key central nodes included "Distress caused by the sleep difficulties" (ISI7) (EI = 1.34), "Interference with daytime functioning" (ISI5) (EI = 1.08), and "Sleep dissatisfaction" (ISI4) (EI = 0.74). "Fatigue" (PHQ4) (Bridge EI = 1.98), "Distress caused by sleep difficulties" (ISI7) (Bridge EI = 1.71), and "Motor Disturbances" (PHQ8) (Bridge EI = 1.67) were important bridge symptoms. The flow network indicated that the edge between the nodes of "Suicidality" (SU) and "Guilt" (PHQ6) showed the strongest connection (Edge Weight= 1.17, followed by "Suicidality" (SU) - "Sad mood" (PHQ2) (Edge Weight = 0.68)). The network analysis results suggest that insomnia symptoms play a critical role in the activation of the insomnia-depression-suicidality network model of COVID-19 survivors, while suicidality is more susceptible to the influence of depressive symptoms. These findings may have implications for developing prevention and intervention strategies for mental health conditions following recovery from COVID-19.

The dangers of having only one pandemic exit strategy.

BACKGROUND: When it comes to pandemic response, preparation can be the key. Between 2020 and 2024, the fast-paced development of COVID-19-often compounded by pubic policies' failures to reflect the latest reality and the public's divergent reactions to the pandemic and the policies-means that society should prepare for exit strategies that can reflect the reality of the pandemic and the interests of the people. Yet oftentimes societies only have one exit strategy with limited scope. This paper investigates the dangers of having only one pandemic exit strategy for pandemics like COVID-19. METHODS: Analyses were based on a review of the literature on COVID-19 exit strategies and our own research. The PubMed literature search focused on two concepts-"COVID-19″ and "exit strategy"-and was limited to peer-reviewed papers published between 2020 and 2024 in English. RESULTS: A total of 31 articles were included in the final review. Analyses showed that existing studies on COVID-19 exit strategies often focused on using the modelling method to gauge one exit strategy. Exit strategies were often discussed in the context of implementing, easing, or lifting specific pharmaceutical or non-pharmaceutical interventions. Staged and country-wide coordinated exit strategies were also discussed in the literature, both of which were often deemed as comparatively rigorous options compared to single or stand-alone exit strategies. Drawing on the overall development of COVID-19 and our own research, we presented and discussed the importance of having multiple exit strategies that are considerate of all possible pandemic trajectories, diverse interests of the public, and the communication challenges officials might face in introducing or implementing pandemic policies. CONCLUSION: This paper underscored the importance of having multiple exit strategies for societies to prepare for pandemics. The insights of this study can help inform health policies so that they can more comprehensively and compassionately protect the needs and wants of the "public" in public health, particularly in grave times like COVID-19.

The network structures of depressive and insomnia symptoms among cancer patients using propensity score matching: Findings from the Health and Retirement Study (HRS).

OBJECTIVE: Both depression and insomnia are found to be more prevalent in cancer patients compared to the general population. This study compared the network structures of depression and insomnia among cancer patients versus cancer-free participants (controls hereafter). METHOD: The 8-item Center for Epidemiological Studies Depression Scale (CESD-8) and the 4-item Jenkins Sleep Scale (JSS-4) were used to measure depressive and insomnia symptoms, respectively. Propensity score matching (PSM) was used to construct the control group using data from the Health and Retirement Study (HRS). In total, a sample consisting of 2216 cancer patients and 2216 controls was constructed. Central (influential) and bridge symptoms were estimated using the expected influence (EI) and bridge expected influence (bridge EI), respectively. Network stability was assessed using the case-dropping bootstrap method. RESULT: The prevalence of depression (CESD-8 total score ≥ 4) in cancer patients was significantly higher compared to the control group (28.56 % vs. 24.73 %; P = 0.004). Cancer patients also had more severe depressive symptoms relative to controls, but there was no significant group difference for insomnia symptoms. The network structures of depressive and insomnia symptoms were comparable between cancer patients and controls. "Felt sadness" (EI: 6.866 in cancer patients; EI: 5.861 in controls), "Felt unhappy" (EI: 6.371 in cancer patients; EI: 5.720 in controls) and "Felt depressed" (EI: 6.003 in cancer patients; EI: 5.880 in controls) emerged as the key central symptoms, and "Felt tired in morning" (bridge EI: 1.870 in cancer patients; EI: 1.266 in controls) and "Everything was an effort" (bridge EI: 1.046 in cancer patients; EI: 0.921 in controls) were the key bridge symptoms across both groups. CONCLUSION: Although cancer patients had more frequent and severe depressive symptoms compared to controls, no significant difference was observed in the network structure or strength of the depressive and insomnia symptoms. Consequently, psychosocial interventions for treating depression and insomnia in the general population could be equally applicable for cancer patients who experience depression and insomnia.

Inter-relationships of depression and insomnia symptoms with life satisfaction in stroke and stroke-free older adults: Findings from the Health and Retirement Study based on network analysis and propensity score matching.

BACKGROUND: Depression and insomnia are common co-occurring psychiatric problems among older adults who have had strokes. Nevertheless, symptom-level relationships between these disorders remain unclear. OBJECTIVES: In this study, we compared inter-relationships of depression and insomnia symptoms with life satisfaction among older stroke patients and stroke-free peers in the United States. METHODS: The study included 1026 older adults with a history of stroke and 3074 matched controls. Data were derived from the US Health and Retirement Study. Depression, insomnia and life satisfaction were assessed. Propensity score matching was employed to identify demographically-similar groups of stroke patients and controls. Central and bridge symptoms were assessed using Expected influence (EI) and bridge EI, respectively. RESULTS: The prevalence of depression in the stroke group (25.0 %) was higher than that of controls (14.3 %, P < 0.001). In stroke group, "Feeling depressed" (CESD1; EI: 5.80), "Feeling sad" (CESD7; EI: 4.67) and "Not enjoying life" (CESD6; EI: 4.51) were the most central symptoms, while "Feeling tired in the morning" (JSS4; BEI: 1.60), "Everything was an effort" (CESD2; BEI: 1.21) and "Waking up during the night" (JSS2; BEI: 0.98) were key bridge symptoms. In controls, the most central symptoms were "Lack of happiness" (CESD4; EI: 6.45), "Feeling depressed" (CESD1; EI: 6.17), and "Feeling sad" (CESD7; EI: 6.12). Furthermore, "Feeling tired in the morning" (JSS4; BEI: 1.93), "Everything was an effort" (CESD2; BEI: 1.30), and "Waking up too early" (JSS3; BEI: 1.12) were key bridge symptoms. Life satisfaction had the most direct associations with "Not enjoying life" (CESD6) and "Feeling lonely" (CESD5) in the two groups, respectively. CONCLUSION: Older adults with stroke exhibited more severe depression and insomnia symptoms. Interventions targeting central and bridge symptoms may help to mitigate the co-occurrence of these symptoms.

Healthy lifestyle and the risk of depression recurrence requiring hospitalisation and mortality among adults with pre-existing depression: a prospective cohort study.

BACKGROUND: Although lifestyle-based treatment approaches are recommended as important aspects of depression care, the quantitative influence of aggregated healthy lifestyles on depression recurrence and mortality remains unknown. OBJECTIVE: To investigate the association between healthy lifestyle and the risks of first-time hospitalisation for recurrent depression and mortality. METHODS: 26 164 adults with depression (mean (SD) age, 56.0 (7.9) years) were included from UK Biobank between 2006 and 2010 and followed up until 2022. Depression was defined as a physician's diagnosis in hospital admissions or the use of prescribed antidepressant medication. A weighted healthy lifestyle score (HLS) was calculated based on smoking, alcohol consumption, diet, sleep pattern, physical activity, social health, employment status and greenspace interaction. FINDINGS: Over a 13.3-year follow-up, 9740 cases of first-time hospitalisation due to depression recurrence and 1527 deaths were documented. Compared with the lowest HLS tertile, the highest tertile was associated with a 27% lower risk (HR=0.73, 95% CI 0.69 to 0.77) of first-time hospitalisation for depression recurrence and a 22% (HR=0.78, 95% CI 0.68 to 0.91) lower risk of mortality among adults with depression. Lower risks of first-time hospitalisation for depression recurrence were observed among those who smoked less, drank more alcohol, followed healthier diets and sleep patterns, spent more time employed in current job or had greater exposure to greenspace. CONCLUSION AND IMPLICATIONS: Greater adherence to healthy lifestyle was associated with a lower risk of hospitalisation and mortality among adults with pre-existing depression. Incorporating behaviour modification as an essential part of clinical practice for depressed patients could complement medication-based therapies.

The impact of urbanization on youth mental health in Hong Kong.

PURPOSE OF REVIEW: Urbanization is a multifaceted process that can have both positive and negative effects on mental health, especially in adolescents. This paper attempts to summarize the impact of urbanization on youth mental health in Hong Kong. RECENT FINDINGS: Several studies have shown that urbanization is associated with an increased risk of youth mental health problems in Hong Kong. Psychosocial factors like perceived stress, social isolation, and exposure to environmental pollutants may contribute to a negative association between urbanization and mental health issues. Academic pressure, poor transparency and accessibility to mental health services in Hong Kong further exacerbate youth's mental health wellbeing. Environmental factors like housing conditions, green spaces, and visible urban greenery have been found to influence mental health outcomes. Existing empirical studies have found a positive association between urbanization and mental health problems, while others have found no association or even a negative association. SUMMARY: Further research is warranted to investigate the complex relationship between urbanization and youth mental health in Hong Kong. Exploration of effective interventions is necessary to mitigate the negative impacts of urbanization on youth mental health. Understanding this relationship can inform health policy-making and formulate interventions to promote youth's mental health well being in the short-and long run.

Pain trajectories and their associations with cognition among older adults: a 10-year cohort study from network perspective.

BACKGROUND: Few studies have examined the associations between pain trajectories and cognitive function in older adults. This study explored the associations between pain trajectories and different cognitive domains in older adults from a network perspective. METHODS: Data on pain trajectories were derived from the Health and Retirement Study between 2010 and 2020 using latent class growth analyses. Measurements of key cognition domains, including memory, attention, calculation, orientation and language, were included. Linear regression and network analysis were performed to evaluate the associations between different pain trajectories and cognition. RESULTS: A total of 9,551 older adults were included in this study and three trajectories of pain were identified. After controlling for the covariates, persistent severe pain trajectory was associated with poorer overall cognition, memory and calculation ability when compared to mild or non-persistent pain trajectory. In the pain and cognition network model, memory (expected influence (EI) = 0.62), language (EI = 0.58) and calculation (EI = 0.41) were the most central domains. CONCLUSIONS: Pain trajectories appeared stable over time among older adults in this study. Severity of persistent pain was an important risk factor for poor cognition, especially in relation to memory and calculation domains. Interventions targeting memory, language and calculation domains might be useful in addressing cognitive decline in older adults with persistent pain.

Where should "Humans" be in "One Health"? Lessons from COVID-19 for One Health.

The culling of animals that are infected, or suspected to be infected, with COVID-19 has fuelled outcry. What might have contributed to the ongoing debates and discussions about animal rights protection amid global health crises is the lack of a unified understanding and internationally agreed-upon definition of "One Health". The term One Health is often utilised to describe the imperative to protect the health of humans, animals, and plants, along with the overarching ecosystem in an increasingly connected and globalized world. However, to date, there is a dearth of research on how to balance public health decisions that could impact all key stakeholders under the umbrella of One Health, particularly in contexts where human suffering has been immense. To shed light on the issue, this paper discusses whether One Health means "human-centred connected health" in a largely human-dominated planet, particularly amid crises like COVID-19. The insights of this study could help policymakers make more informed decisions that could effectively and efficiently protect human health while balancing the health and well-being of the rest of the inhabitants of our shared planet Earth.

Prevalence and network analysis of internet addiction, depression and their associations with sleep quality among commercial airline pilots: A national survey in China.

OBJECTIVE: Airline pilots are members of a unique occupational group that is often confronted with sleep routine disruptions, yet relatively few studies have examined their mental health status. This study assessed the prevalence and network structure of internet addiction, depression and sleep quality problems in commercial airline pilots. METHOD: A total of 7055 airline pilots were included in analyses. Internet addiction and depression were measured with the Internet Addiction Test (IAT) and 9-item Patient Health Questionnaire (PHQ-9), respectively. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). The network model was constructed based on an Ising model and its association with sleep quality was evaluated using a flow procedure. RESULTS: Internet addiction, depression and sleep quality were common among airline pilots. The prevalence of internet addiction was 8.0 % (95 % CI: 7.3-8.6 %), while the rates of depression and poor sleep quality were 23.3 % (95 % CI: 22.3-24.2 %) and 33.0 % (95 % CI: 31.9-34.1 %), respectively. In the depression and internet addiction network model, "Fatigue" (PHQ4; Expected Influence (EI): 2.04) and "Depressed/moody/nervous only while being offline" (IAT20; EI: 1.76) were most central symptoms while "Fatigue" (PHQ4; Bridge EI: 1.30) was also the most important bridge symptom. The flow network model of sleep quality with internet addiction and depression showed that "Appetite" (PHQ5) had the strongest positive association with poor sleep quality. CONCLUSION: Internet addiction, depression and sleep quality were common among airline pilots and warrant regular screening and timely treatment. Strategies to improve sleep hygiene may be useful in preventing onsets or exacerbations in depression and internet addiction among airline pilots.

The prevalence of poor sleep quality in the general population in China: a meta-analysis of epidemiological studies.

BACKGROUND: The high prevalence of poor sleep quality (PSQ) in the general population leads to negative health outcomes. Since estimates of PSQ prevalence in the Chinese general population vary widely, this meta-analysis aimed to refine these estimates and to identify moderating factors. METHODS: A comprehensive literature search was undertaken in both international (PubMed, PsycINFO, Web of Science, and EMBASE) and Chinese (Wanfang, and the China National Knowledge Infrastructure databases) databases from inception to 23 November 2023. Studies were required to have used standard scales such as the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). The pooled prevalence of PSQ and 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup and meta-regression analyses were performed to identify sources of heterogeneity. RESULTS: In 32 studies with a combined 376,824 participants, the pooled prevalence of PSQ was 19.0% (95% CI 15.8-22.8%; range 6.6-43.6%). Across 22 studies that reported PSQI data, the pooled mean score was 4.32 (95%CI 3.82-4.81; SD = 0.502). The pooled mean sleep duration across 8 studies was 7.62 (95% CI 7.23-8.00; SD = 0.194) hours. Subgroup analyses showed that lower education (Q = 4.12, P = 0.042), living in less developed regions (Q = 60.28, P < 0.001), and lower PSQI cutoff values (Q = 9.80, P = 0.007) were significantly associated with PSQ. Meta-regression analyses showed that study quality was inversely associated with estimated PSQ prevalence (ß = - 0.442, P = 0.004). LIMITATIONS: Although measures such as subgroup and meta-regression analyses were performed, substantial heterogeneity remained. Information related to sleep quality, such as comorbid physical diseases or psychiatric disorders, substance use, occupational types, and employment status, were not reported in most studies. CONCLUSION: One in five people in the general population of China may have PSQ and people with lower education or living in western regions may be more susceptible.

Mapping prodromal symptoms in patients with bipolar disorder: A network perspective.

Bipolar disorder (BD) is a major mental disorder that significantly impairs behavior and social functioning. This study assessed the network structure of prodromal symptoms in patients with BD prior to their index mood episode. Semi-structured interviews were conducted with the Bipolar Prodrome Symptom Scale-Retrospective (BPSS-R) to examine patients' prodromal symptoms. Network analysis was conducted to elucidate inter-relations between prodromal symptoms. A total of 120 eligible patients participated in this study. Network analysis indicated that the observed model was stable. The edge Mania3-Depression9 ('Racing thoughts' - 'Thinking about suicide', edge weight = 14.919) showed the strongest positive connection in the model, followed by the edge Mania1-depression1 ('Extremely energetic/active' - 'Depressed mood', edge weight = 14.643). The only negative correlation in the model was for Mania7-depression2 ('Overly self-confident' - 'Tiredness or lack of energy', edge weight = -1.068). Nodes Mania3 ('Racing thoughts'), Depression9 ('Thinking about suicide'), Mania1 ('Extremely energetic/active'), and Depression1 ('Depressed mood') were the most central symptoms. Both depressive and manic or hypomanic symptoms appeared in the prodromal phase. Symptoms reflecting 'Racing thoughts', 'Thinking about suicide', 'Extremely energetic/active', and 'Depressed mood' should be thoroughly assessed and targeted as crucial prodromal symptoms in interventions to reduce the risk of BD episodes.

Global prevalence of poor sleep quality in cancer patients: A systematic review and meta-analysis.

OBJECTIVE: Poor sleep quality is common in patients with cancer, but the prevalence rates varied widely across studies. This systematic review and meta-analysis examined the pooled prevalence of poor sleep quality among patients with cancer. METHODS: Systematic literature searches were independently conducted in the major databases (Web of Science, PubMed, EMBASE and PsycINFO). Studies that reported the prevalence of poor sleep quality in patients with cancer were analyzed using a random effects model. Funnel plots and Egger's tests were used to assess publication bias. Statistical analyses were performed using R software. RESULTS: A total of 59 epidemiological studies involving 16,223 patients were included. The pooled prevalence of poor sleep quality in patients with cancer was 57.4% [95% confidence interval (CI): 53.3% - 61.6%]. Additionally, three comparative studies with 372 patients and 412 healthy controls were included. Compared to healthy controls, patients with cancer had a significantly higher risk for poor sleep quality [odd ratio (OR) = 3.0; 95%CI: 1.2-7.2; P < 0.05]. Subgroup analyses of the studies revealed that studies from Middle East & North Africa region and low income countries, and on gynecological cancer as well as those with a lower cut-off value of sleep quality (all P < 0.01) reported a higher prevalence of poor sleep quality. Meta-regression analyses showed that higher prevalence of poor sleep quality was associated with higher prevalence of comorbid depression (P < 0.05) and anxiety (P < 0.01), but was associated with a lower education level (P < 0.05) and alcohol use ratio (P < 0.05). CONCLUSION: Poor sleep quality is common among patients with cancer. Considering the overall high prevalence rate and negative impact of poor sleep quality, appropriate measures to identify and improve poor sleep quality are needed to enhance the clinical outcomes in this group.

Depression, anxiety and suicidality among Chinese mental health professionals immediately after China's dynamic zero-COVID policy: A network perspective.

BACKGROUND: Using network analysis, the interactions between mental health problems at the symptom level can be explored in depth. This study examined the network structure of depressive and anxiety symptoms and suicidality among mental health professionals after the end of China's Dynamic Zero-COVID Policy. METHODS: A total of 10,647 mental health professionals were recruited nationwide from January to February 2023. Depression and anxiety were assessed using the 9-item Patient Health Questionnaire (PHQ-9) and 7-item Generalized Anxiety Disorder Scale (GAD-7), respectively, while suicidality was defined by a 'yes' response to any of the standard questions regarding suicidal ideation (SI), suicide plan (SP) and suicide attempt (SA). Expected Influence (EI) and Bridge Expected Influence (bEI) were used as centrality indices in the symptom network to characterize the structure of the symptoms. RESULTS: The prevalence of depression, anxiety, and suicidality were 45.99 %, 28.40 %, and 7.71 %, respectively. The network analysis identified GAD5 ("Restlessness") as the most central symptom, followed by PHQ4 ("Fatigue") and GAD7 ("Feeling afraid"). Additionally, PHQ6 ("Guilt"), GAD5 ("Restlessness"), and PHQ8 ("Motor disturbance") were bridge nodes linking depressive and anxiety symptoms with suicidality. The flow network indicated that the strongest connections of S ("Suicidality") was with PHQ6 ("Guilt"), GAD7 ("Feeling afraid"), and PHQ2 ("Sad mood"). CONCLUSIONS: Depression, anxiety, and suicidality among mental health professionals were highly prevalent after China's Dynamic Zero-COVID Policy ended. Effective measures should target central and bridge symptoms identified in this network model to address the mental health problems in those at-risk.