The integration of artificial intelligence (AI) in mental healthcare holds promise for enhancing diagnostic precision, treatment efficacy, and personalized care. Despite AI’s potential to analyze vast datasets and identify subtle patterns, its clinical adoption in psychiatry remains limited. This review critically examines the emerging role of AI in psychiatry, elucidating its utility, challenges, and implications for clinical practice. Through an extensive analysis of the existing literature and empirical evidence, we seek to inform psychiatric stakeholders about both opportunities and obstacles that are presented by AI. We evaluate AI’s potential to improve diagnostic accuracy, prognostic performance, and therapeutic interventions. Our pragmatic approach bridges the gap between theoretical advancements and practical implementation, providing valuable insights and actionable recommendations for psychiatric professionals. This article highlights the supportive role of AI, advocating for its judicious integration to enhance patient outcomes while maintaining the human-centric essence of psychiatric practice. By addressing these challenges and fostering collaboration, AI can significantly advance mental healthcare, reduce clinical burdens, and improve patient outcomes.

COVID-19 might have long-term mental health impacts. We aim to investigate the longitudinal changes in mental problems from initial COVID-19 peak to its aftermath among general public in China. Depression, anxiety and insomnia were assessed among a large-sample nationwide cohort of 10,492 adults during the initial COVID-19 peak (28 February 2020 to 11 March 2020) and its aftermath (8 July 2020 to 8 August 2020) using the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Insomnia Severity Index. We used generalized estimating equations and linear mixed models to explore factors associated with long-term mental health symptoms during COVID-19. During the five months, mental health symptoms remained consistently elevated (baseline 46.4%; follow-up 45.1%). Long-term depression, anxiety and insomnia were associated with several personal and work-related factors including quarantine (adjusted OR for any mental health symptoms 1.31, 95%CI 1.22–1.41, p < 0.001), increases in work burden after resuming work (1.77, 1.65–1.90, p < 0.001), occupational exposure risk to COVID-19 (1.26, 1.14–1.40, p < 0.001) and living in places severely affected by initial COVID-19 peak (1.21, 1.04–1.41, p = 0.01) or by a COVID-19 resurgence (1.38, 1.26–1.50, p < 0.001). Compliance with self-protection measures, such as wearing face masks (0.74, 0.61–0.90, p = 0.003), was associated with lower long-term risk of mental problems. The findings reveal a pronounced and prolonged mental health burden from the initial COVID-19 peak through to its aftermath in China. We should regularly monitor the mental health status of vulnerable populations throughout COVID-19.

The present study assessed the willingness of the general population to receive COVID-19 vaccines and identified factors that influence vaccine hesitancy and resistance. A national online survey was conducted from 29 January 2021 to 26 April 2021 in China. Multinomial logistic regression analyses were conducted to identify factors that influence vaccine hesitancy and resistance. Of the 34,041 participants surveyed, 18,810 (55.3%) were willing to get vaccinated, 13,736 (40.3%) were hesitant, and 1495 (4.4%) were resistant. Rates of vaccine acceptance increased over time, with geographical discrepancies in vaccine hesitancy and resistance between provinces in China. Vaccine safety was the greatest concern expressed by most participants (24,461 [71.9%]), and the major reason for participants’ refusing vaccination (974 [65.2%]). Government agencies (23,131 [68.0%]) and social media (20,967 [61.6%]) were the main sources of COVID-19 vaccine information. Compared with vaccination acceptance, female, young and middle-aged, high income, and perceived low-risk of infection were associated with vaccine hesitancy. Histories of allergic reactions to other vaccines and depression symptoms were related to vaccine resistance. Common factors that influenced vaccine hesitancy and resistance were residing in cities and perceiving less protection with vaccines than with other protective measures. The results indicate that the rate of vaccine resistance is relatively low, but vaccine hesitancy is common. Individuals who are female, young and middle-aged, with a high income, and residing in cities are more likely to be hesitant for vaccination and should be the target populations for vaccination campaigns. Specific vaccine messaging from the government and social media could alleviate public concerns about vaccine safety and efficacy.

Chronic pain and sleep disturbance are highly comorbid disorders, which leads to barriers to treatment and significant healthcare costs. Understanding the underlying genetic and neural mechanisms of the interplay between sleep disturbance and chronic pain is likely to lead to better treatment. In this study, we combined 1206 participants with phenotype data, resting-state functional magnetic resonance imaging (rfMRI) data and genotype data from the Human Connectome Project and two large sample size genome-wide association studies (GWASs) summary data from published studies to identify the genetic and neural bases for the association between pain and sleep disturbance. Pittsburgh sleep quality index (PSQI) score was used for sleep disturbance, pain intensity was measured by Pain Intensity Survey. The result showed chronic pain was significantly correlated with sleep disturbance (r = 0.171, p-value < 0.001). Their genetic correlation was r_g = 0.598 using linkage disequilibrium (LD) score regression analysis. Polygenic score (PGS) association analysis showed PGS of chronic pain was significantly associated with sleep and vice versa. Nine shared functional connectivity (FCs) were identified involving prefrontal cortex, temporal cortex, precentral/postcentral cortex, anterior cingulate cortex, fusiform gyrus and hippocampus. All these FCs mediated the effect of sleep disturbance on pain and seven FCs mediated the effect of pain on sleep disturbance. The chronic pain PGS was positively associated with the FC between middle temporal gyrus and hippocampus, which further mediated the effect of chronic pain PGS on PSQI score. Mendelian randomization analysis implied a possible causal relationship from chronic pain to sleep disturbance was stronger than that of sleep disturbance to chronic pain. The results provided genetic and neural evidence for the association between pain and sleep disturbance, which may inform future treatment approaches for comorbid chronic pain states and sleep disturbance.

Background and aims: The inclusion of gaming disorder as a new diagnosis in the 11th revision of the International Statistical Classification of Diseases (ICD-11) has caused ongoing debate. This review aimed to summarise the potential neural mechanisms of gaming disorder and provide additional evidence for this debate.Methods: We conducted a comprehensive literature review of gaming disorder, focusing on studies that investigated its clinical characteristics and neurobiological mechanisms. Based on this evidence, we further discuss gaming disorder as a psychiatric disorder.Results: The present review demonstrated that the brain regions involved in gaming disorder are related to executive functioning (e.g., anterior cingulate cortex and dorsolateral prefrontal cortex), reward systems (e.g., striatum and orbitofrontal cortex), and emotional regulation (e.g., insula and amygdala). Despite the inclusion of gaming disorder in the ICD-11, the debate remains on the benefits and harms of classifying it as a mental health disorder. Opponents argue that the current manifestations that support gaming disorder as a psychiatric disorder remain inadequate, it could cause moral panic among healthy gamers, and that the label of gaming disorder is stigmatising.Discussion: Evidence suggests that gaming disorder shares similar neurobiological alterations with other types of behavioural and substance-related addictions, which further supports gaming disorder as a behavioural addiction. Ongoing debates on whether gaming disorder is a psychiatric disorder push for further exploring the nature of gaming disorder and resolving this dilemma in the field.