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.

Hikikomori: A perspective from bibliometric analysis.

AIMS: Hikikomori is a common phenomenon reported in Japan and many other countries. However, the broad trends of the research publications on hikikomori are unclear. Therefore, this study examined the patterns of research on hikikomori using bibliometric analysis. METHODS: Relevant publications were searched in Web of Science. Bibliometric analyses were performed with CiteSpace, R and VOSviewer. RESULTS: In total, 297 publications on hikikomori met the eligibility criteria. The International Journal of Social Psychiatry (IF = 10.461) published the most papers (K = 17, or 5.7%) on hikikomori. Takahiro A. Kato from Kyushu University (41; 13.8%; H-index = 18) was the most influential author, while Takahiro A. Kato (total link strength [TLS]: 235), Alan R. Teo (TLS: 157), and Masaru Tateno (TLS: 153) separately had the strongest research collaboration with other researchers. Of all countries that published on hikikomori, Japan had the highest number of publications (K = 91). The keywords "United States" and "psychiatric diagnosis" received the most attention between 2013 and 2015, whereas "health" and "autism spectrum disorder" received the most attention in 2021 and 2022. CONCLUSIONS: Peer-reviewed research publications on hikikomori are growing rapidly and the research trends in this field are also changing.

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.

Poor sleep quality in schizophrenia patients: A systematic review and meta-analyses of epidemiological and case-control studies.

OBJECTIVE: Poor sleep quality is common in patients with schizophrenia but estimated prevalence rates in this population have been mixed. This systematic review and meta-analysis examined the prevalence of poor sleep quality in schizophrenia samples and moderators of prevalence from epidemiological studies as well as the risk of poor sleep quality in schizophrenia patients based on case-control studies. METHODS: Both international (PubMed, Web of Science, PsycINFO, EMBASE) and Chinese databases [Chinese Nation knowledge Infrastructure (CNKI) and WANFANG] were systematically searched. Studies that estimated the prevalence of poor sleep quality in schizophrenia 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: In total, 23 epidemiological studies and nine case-control studies were included. Based on the epidemiological studies, the pooled overall prevalence of poor sleep quality was 63.4 % [95 % confidence interval (CI): 57.0 %-69.9 %]. Additionally, based on the nine case-control studies, schizophrenia patients had a significantly higher risk for poor sleep quality compared to healthy controls [odd ratio (OR) = 4.5; 95%CI: 2.4-8.3; P < 0.0001]. CONCLUSION: Poor sleep quality is common among schizophrenia patients. Considering negative outcomes caused by poor sleep quality, regular screening on poor sleep quality should be conducted and effective interventions should be provided to those in need.

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.

Interactive changes in depression and loneliness symptoms prior to and during the COVID-19 pandemic: A longitudinal network analysis.

OBJECTIVES: Depression and loneliness co-occur frequently. This study examined interactive changes between depression and loneliness among older adults prior to and during the COVID-19 pandemic from a longitudinal network perspective. METHODS: This network study was based on data from three waves (2016-2017, 2018-2019, and 2020) of the English Longitudinal Study of Ageing (ELSA). Depression and loneliness were measured with the eight-item version of the Center for Epidemiologic Studies Depression Scale (CESD-8) and three item version of the University of California Los Angeles (UCLA) Loneliness Scale, respectively. A network model was constructed using an Ising Model while network differences were assessed using a Network Comparison Test. Central symptoms were identified via Expected Influence (EI). RESULTS: A total of 4,293 older adults were included in this study. The prevalence and network of depression and loneliness did not change significantly between the baseline and pre-pandemic assessments but increased significantly from the pre-pandemic assessment to during COVID-19 assessment. The central symptom with the strongest increase from pre-pandemic to pandemic assessments was "Inability to get going" (CESD8) and the edge with the highest increase across depression-loneliness symptom communities was "Lack companionship" (UCLA1) - "Inability to get going" (CESD8). Finally, "Feeling depressed" (CESD1) and "Everything was an effort" (CESD2) were the most central symptoms over the three assessment periods. CONCLUSIONS: The COVID-19 pandemic was associated with significant changes in the depression-loneliness network model. The most changed symptoms and edges could be treatment targets for reducing the risk of depression and loneliness in older adults.

The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the "Relatively Static Management" COVID-19 Strategy: A Perspective of Network Analysis.

Background: Suicidality is a global public health problem which has increased considerably during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the inter-relationships between depressive symptoms and suicidality using network analysis among Macau residents after the "relatively static management" COVID-19 strategy. Methods: An assessment of suicidal ideation (SI), suicide plan (SP), suicide attempt (SA) and depressive symptoms was conducted with the use of individual binary response items (yes/no) and Patient Health Questionnaire (PHQ-9). In the network analysis, central and bridge symptoms were identified in the network through "Expected Influence" and "Bridge Expected Influence", and specific symptoms that were directly associated with suicidality were identified via the flow function. Network Comparison Tests (NCT) were conducted to examine the gender differences in network characteristics. Results: The study sample included a total of 1008 Macau residents. The prevalence of depressive symptoms and suicidality were 62.50% (95% CI = 59.4-65.5%) and 8.9% (95% CI = 7.2-10.9%), respectively. A network analysis of the sample identified SI ("Suicidal ideation") as the most central symptom, followed by SP ("Suicide plan") and PHQ4 ("Fatigue"). SI ("Suicidal ideation") and PHQ6 ("Guilt") were bridge nodes connecting depressive symptoms and suicidality. A flow network revealed that the strongest connection was between S ("Suicidality") and PHQ6 ("Guilt"), followed by S ("Suicidality") and PHQ 7 ("Concentration"), and S ("Suicidality") and PHQ3 ("Sleep"). Conclusion: The findings indicated that reduction of specific depressive symptoms and suicidal thoughts may be relevant in decreasing suicidality among adults. Further, suicide assessment and prevention measures should address the central and bridge symptoms identified in this study.

Prevalence of COVID-19 fear and its association with quality of life among fire service recruits after ceasing the dynamic zero-COVID policy in China.

Background: In December 2022, China terminated its dynamic zero-COVID policy. To date, however, no research has been conducted upon mental health issues and their relationship with quality of life (hereafter QoL) among fire service recruits since the dynamic zero-COVID policy ended. This study explored fear of COVID-19 (FOC) prevalence and correlates as well as its network structure and interconnections with QoL among fire service recruits. Methods: A cross-sectional survey design was used to assess fire service recruits in Beijing and Sichuan, Guangxi and Guizhou provinces of China between February 13 and 16, 2023. Fear of COVID-19 was measured using the Fear of COVID-19 Scale, depression was assessed with the Patient Health Questionnaire, anxiety was examined using the Generalized Anxiety Disorder scale, and QOL was evaluated with the World Health Organization Quality of Life-brief version. Univariate and multivariate analyses were used to explore correlates of COVID-19 fear. Network analysis assessed the structure of fear of COVID-19 and its associations with QoL. Results: A total of 1,560 participants were included in this study. The overall prevalence of fear of COVID-19 was 38.85% (n = 606; 95% CI = 36.42-41.32%). Being afraid of COVID-19 was significantly related to depression (OR = 1.084; p < O.OO1) and physical fatigue (OR = 1.063; p = 0.026). Fire service recruits with more fear of COVID-19 had lower QOL (F = 18.061 p < 0.001) than those with less fear of COVID-19 did. The most central symptoms included FOC6 ("Sleep difficulties caused by worry about COVID-19"), FOC7 ("Palpitations when thinking about COVID-19") and FOC2 ("Uncomfortable to think about COVID-19"). The top three symptoms negatively associated with QoL were FOC4 ("Afraid of losing life because of COVID-19"), FOC6 ("Sleep difficulties caused by worry about COVID-19") and FOC2 ("Uncomfortable to think about COVID-19"). Conclusion: Over one-third of fire service recruits reported fear of COVID-19 after China's dynamic zero-COVID policy had terminated. Poorer QoL was related to fear of COVID-19. Targeting core symptoms of the fear network structure could help improve the physical and mental health of fire service recruits during public health crises.

Heart failure and depression: A perspective from bibliometric analysis.

Background: Depression commonly occurs in heart failure patients, and negatively influences quality of life and disease prognosis. This study explored heart failure and depression-related research from a bibliometric perspective. Methods: Relevant publications were searched on June 24, 2022. The Bibliometrix package in R was used to conduct quantitative analyses including the trends in publications, and related countries, articles, authors and keywords. VOSviewer software was used to conduct the visualization map on co-word, co-author, and institution co-authorship analyses. CiteSpace software was used to illustrate the top keywords with citation burst. Results: A total of 8,221 publications in the heart failure and depression-related research field were published between 1983 and 2022. In this field, the United States had the most publications (N = 3,013; 36.65%) and highest total citation (N = 149, 376), followed by China, Germany, Italy and Japan. Author Moser and Duke University were the most productive author and institution, respectively. Circulation is the most influential journal. Apart from "heart failure" and "depression," "quality of life," "mortality" and "myocardial infarction" were the most frequently used keywords in this research area; whereas more recently, "self care" and "anxiety" have been used more frequently. Conclusion: This bibliometric analysis showed a rapid growth of research related to heart failure and depression from 1989 to 2021, which was mostly led by North America and Europe. Future directions in this research area include issues concerning self-care and anxiety about heart failure. As most of the existing literature were published in English, publications in other languages should be examined in the future.

Prevalence of insomnia and its association with quality of life among Macau residents shortly after the summer 2022 COVID-19 outbreak: A network analysis perspective.

Background: The latest wave of the coronavirus disease 2019 (COVID-19) pandemic in Macau began on 18 June 2022 and was more serious than previous waves. Ensuing disruption from the wave is likely to have had a variety of negative mental health consequences for Macau residents including increased risk for insomnia. This study investigated the prevalence and correlates of insomnia among Macau residents during this wave as well as its association with quality of life (QoL) from a network analysis perspective. Methods: A cross-sectional study was conducted between 26 July and 9 September 2022. Univariate and multivariate analyses explored correlates of insomnia. Analysis of covariance (ANCOVA) examined the relationship between insomnia and QoL. Network analysis assessed the structure of insomnia including "Expected influence" to identify central symptoms in the network, and the flow function to identify specific symptoms that were directly associated with QoL. Network stability was examined using a case-dropping bootstrap procedure. Results: A total of 1,008 Macau residents were included in this study. The overall prevalence of insomnia was 49.0% (n = 494; 95% CI = 45.9-52.1%). A binary logistic regression analysis indicated people with insomnia were more likely to report depression (OR = 1.237; P < 0.001) and anxiety symptoms (OR = 1.119; P < 0.001), as well as being quarantined during the COVID-19 pandemic (OR = 1.172; P = 0.034). An ANCOVA found people with insomnia had lower QoL (F(1,1,008) = 17.45, P < 0.001). "Sleep maintenance" (ISI2), "Distress caused by the sleep difficulties" (ISI7) and "Interference with daytime functioning" (ISI5) were the most central symptoms in the insomnia network model, while "Sleep dissatisfaction" (ISI4), "Interference with daytime functioning" (ISI5), and "Distress caused by the sleep difficulties" (ISI7) had the strongest negative associations with QoL. Conclusion: The high prevalence of insomnia among Macau residents during the COVID-19 pandemic warrants attention. Being quarantined during the pandemic and having psychiatric problems were correlates of insomnia. Future research should target central symptoms and symptoms linked to QoL observed in our network models to improve insomnia and QoL.

Schizophrenia and oxidative stress from the perspective of bibliometric analysis.

Background: A growing number of studies has implicated oxidative stress in the pathophysiology of psychiatric disorders including schizophrenia. The aim of this study was to explore the field of schizophrenia and oxidative stress-related research from a bibliometric perspective. Methods: All relevant publications on schizophrenia and oxidative stress were obtained from Web of Science Core Collection (WOSCC) database from its inception date to November 8, 2022. VOSviewer software was used to examine co-authorships and co-occurring keywords. R software was used to present the main characteristics of publications and cooperation frequency among countries. CiteSpace was used to investigate keywords with the strongest citation bursts. Results: A total of 3,510 publications on schizophrenia and oxidative stress were included. The United States had the largest number of publications (26.1%), and international collaborations. University of Melbourne was the most productive institution, while Schizophrenia Research was the most productive journal in this field. Apart from "schizophrenia" and "oxidative stress", the terms "prefrontal cortex", "brain" and "nitric oxide" were among the most frequently used keywords. Conclusions: In conclusion, research on the association between oxidative stress and schizophrenia has received growing attention in the academic literature that is expected to continue its upward trajectory during the next two decades. Existing research suggests there has been a transition from research focused on pathways to animal models, and subsequently to clinical applications. Intervention studies on oxidative stress and schizophrenia are likely to be an important focus of related work in the near future.

Global prevalence of poor sleep quality in military personnel and veterans: A systematic review and meta-analysis of epidemiological studies.

Poor sleep quality is prevalent among members of the military but rates of poor sleep quality vary between studies. This study examined the global prevalence of poor sleep quality in military personnel and veterans as well as possible moderators of prevalence differences between studies. PubMed, EMBASE, Web of Science, and PsycINFO were systematically searched from their inception dates to September 1, 2022. Studies were included if they were conducted on military personnel and/or veterans and prevalence estimates of poor sleep quality could be generated from assessments with standardized tools. A random-effects model was used to calculate the pooled prevalence and its 95% confidence intervals (CIs). Fifty-nine studies (N = 28,100) were included for analysis with sample sizes ranging from 14 to 8481. Two studies were rated as "high quality" (3.39%), while 57 were rated as "moderate quality" (96.61%). The overall pooled prevalence of poor sleep quality in military personnel and veterans was 69.00% (95% CI: 62.33-75.30%); pooled rates were 57.79% (95% CI: 49.88-65.50%) and 82.88% (95% CI: 74.08-90.21%) for active duty personnel and veterans, respectively. Subgroup analyses indicated study region, study design, sampling method, Pittsburg Sleep Quality Index cut-off values, and service type moderated prevalence of poor sleep quality. Meta-regression analyses indicated sample size, mean age, depression and posttraumatic stress disorder (PTSD) were associated with prevalence differences between studies. Poor sleep quality was more common in both active duty military personnel and veterans who were older and those who reported PTSD or depression. Regular monitoring of sleep quality and sleep hygiene should be promoted in this population. More relevant studies in middle- and low-income countries should also be conducted.

Depression and anxiety among Macau residents during the COVID-19 outbreak: A network analysis perspective.

Background: The 2019 novel coronavirus disease (COVID-19) outbreak affected people's lifestyles and increased their risk for depressive and anxiety symptoms (depression and anxiety, respectively hereafter). We assessed depression and anxiety in residents of Macau during "the 6.18 COVID-19 outbreak" period and explored inter-connections of different symptoms from the perspective of network analysis. Methods: In this cross-sectional study, 1,008 Macau residents completed an online survey comprising the nine-item Patient Health Questionnaire (PHQ-9) and seven-item Generalized Anxiety Disorder Scale (GAD-7) to measure depression and anxiety, respectively. Central and bridge symptoms of the depression-anxiety network model were evaluated based on Expected Influence (EI) statistics, while a bootstrap procedure was used to test the stability and accuracy of the network model. Results: Descriptive analyses indicated the prevalence of depression was 62.5% [95% confidence interval (CI) = 59.47-65.44%], the prevalence of anxiety was 50.2% [95%CI = 47.12-53.28%], and 45.1% [95%CI = 42.09-48.22%] of participants experienced comorbid depression and anxiety. "Nervousness-Uncontrollable worry" (GADC) (EI = 1.15), "Irritability" (GAD6) (EI = 1.03), and "Excessive worry" (GAD3) (EI = 1.02) were the most central symptoms, while "Irritability" (GAD6) (bridge EI = 0.43), "restlessness" (GAD5) (bridge EI = 0.35), and "Sad Mood" (PHQ2) (bridge EI = 0.30) were key bridge symptoms that emerged in the network model. Conclusion: Nearly half of residents in Macau experienced comorbid depression and anxiety during the 6.18 COVID-19 outbreak. Central and bridge symptoms identified in this network analysis are plausible, specific targets for treatment and prevention of comorbid depression and anxiety related to this outbreak.

Depression and quality of life among Macau residents in the 2022 COVID-19 pandemic wave from the perspective of network analysis.

Background: In the summer of 2022, Macau experienced a surge of COVID-19 infections (the 618 COVID-19 wave), which had serious effects on mental health and quality of life (QoL). However, there is scant research on mental health problems and QoL among Macau residents during the 618 COVID-19 wave. This study examined the network structure of depressive symptoms (hereafter depression), and the interconnection between different depressive symptoms and QoL among Macau residents during this period. Method: A cross-sectional study was conducted between 26th July and 9th September 2022. Depressive symptoms were measured with the 9-item Patient Health Questionnaire (PHQ-9), while the global QoL was measured with the two items of the World Health Organization Quality of Life-brief version (WHOQOL-BREF). Correlates of depression were explored using univariate and multivariate analyses. The association between depression and QoL was investigated using analysis of covariance (ANCOVA). Network analysis was used to evaluate the structure of depression. The centrality index "Expected Influence" (EI) was used to identify the most central symptoms and the flow function was used to identify depressive symptoms that had a direct bearing on QoL. Results: A total 1,008 participants were included in this study. The overall prevalence of depression was 62.5% (n = 630; 95% CI = 60.00-65.00%). Having depression was significantly associated with younger age (OR = 0.970; p < 0.001), anxiety (OR = 1.515; p < 0.001), fatigue (OR = 1.338; p < 0.001), and economic loss (OR = 1.933; p = 0.026). Participants with depression had lower QoL F (1, 1,008) =5.538, p = 0.019). The most central symptoms included PHQ2 ("Sad Mood") (EI: 1.044), PHQ4 ("Fatigue") (EI: 1.016), and PHQ6 ("Guilt") (EI: 0.975) in the depression network model, while PHQ4 ("Fatigue"), PHQ9 ("Suicide"), and PHQ6 ("Guilt") had strong negative associations with QoL. Conclusion: Depression was common among Macao residents during the 618 COVID-19 wave. Given the negative impact of depression on QoL, interventions targeting central symptoms identified in the network model (e.g., cognitive behavioral therapy) should be developed and implemented for Macau residents with depression.

Brain-gut axis and psychiatric disorders: A perspective from bibliometric and visual analysis.

Background: The Brain-Gut Axis, a bidirectional signaling pathway that connects the intestinal and central nervous systems, plays an important role in the development of psychiatric disorders. However, the overall research trends in this field are unclear. This study explored the patterns of research on the brain-gut axis and psychiatric disorders from a bibliometric perspective. Methods: Relevant data were retrieved from the Web of Science Core Collection, with search terms on psychiatric disorders and the brain-gut axis. R (version 4.2.0), VOSviewer (version 1.6.17), CiteSpace software, and the online bibliometric platform were used in the data analysis. Results: A total of 2,298 articles published between 1993 and 2022 were identified, showing an increasing trend over time. China (1,859; 20.70%) was the country that contributed the most publications. The journal Nutrients (95; 4.13%) published the most publications. Cryan JF (153; H-index=73) and University College Cork (559; 22.54%) were the most influential author and the most productive institution, respectively. The high-frequency keywords were clustered into six themes, including neurodegenerative diseases, stress-related diseases, immune, brain behavior, depression, and probiotic-related topics; of which, depression (880; 2019), anxiety (207; 2018) and autism (191; 2019) were the most studied psychiatric disorders in the past 5 years. "Depressive symptom" (2019-2020) and "probiotic treatment" (2019-2020) were the main areas addressed in recent years. Conclusion: Research on the brain-gut axis and psychiatric disorders has attracted increasing attention in the past decade, with most publications originating from high-income level countries. This study provides a useful perspective on understanding the research trends, key hot topics, and research gaps in this expanding field.