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Back to table of contents Previous article Next article CommentaryFull AccessMental Health Response to the COVID-19 Outbreak in ChinaJunying Zhou, M.D., Ph.D., Liu Liu, M.D., Pei Xue, M.D., Xiaorong Yang, B.N., Xiangdong Tang, M.D., Ph.D.Junying Zhou, M.D., Ph.D., Liu Liu, M.D., Pei Xue, M.D., Xiaorong Yang, B.N., Xiangdong Tang, M.D., Ph.D.Published Online:7 May 2020https://doi.org/10.1176/appi.ajp.2020.20030304AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail Transmission of the 2019 novel coronavirus (COVID-19) (1) has now widely and rapidly spread around the world. On March 11, 2020, the World Health Organization announced that COVID-19 is a pandemic (2). The rapid transmission and mortality risk of the COVID-19 infection may increase the risk of mental health problems among healthy individuals in the general public and worsen preexisting psychiatric problems in psychiatric patients, although data are still being gathered. A constellation of difficult feelings and psychological distress, including panic, worries, and depression, could be triggered by the fear of possible infection, being quarantined at hospitals and home, social isolation, and even the shortage of protective gear.A number of mental health surveys associated with the COVID-19 outbreak are being conducted in different vulnerable populations, which include infected patients, medical staff, students, and the general population. Liu et al. have reported results from a multicenter survey conducted among 1,563 medical staff members and found that the prevalence of depression and anxiety was 51% and 45%, respectively (3). So far, data on the mental health repercussions of the COVID-19 pandemic in outpatient populations have not been available. Thus, we conducted a questionnaire survey, from February 25 to March 9, 2020, among outpatients who sought care in the Departments of Psychiatry, Neurology, and Sleep Medicine in West China Hospital of Sichuan University (Chengdu, China). A self-report questionnaire was completed by outpatients, who provided consent, via the WeChat-based survey program Questionnaire Star. A total of 2,065 out of 3,441 patients completed the survey, including 589 new patients and 1,476 existing patients. The prevalence rates of mental health problems related to the COVID-19 outbreak, including anxiety (defined as a total score ≥5 on the Generalized Anxiety Disorder 7-item scale), depression (defined as a total score ≥5 on the Patient Health Questionnaire 9-item scale), and insomnia (defined as a total score ≥8 on the Insomnia Severity Index), were 25.5%, 16.9%, and 26.2%, respectively. Furthermore, 20.9% of patients (N=300) with preexisting psychiatric disorders (N=1,434) reported a deterioration of their mental health condition related to the pandemic. In particular, transportation restrictions, isolation at home, and fear of cross-infection in hospitals have inevitably become major concerns and barriers to treatment for these patients during the outbreak. Our survey also showed that 24.5% of new patients, including those with anxiety (N=46), depression (N=37), insomnia (N=79), and psychosis (N=21), could not receive timely diagnoses and treatment. Similarly, 22.0% of existing patients with diagnosed mental disorders, including depression, bipolar disorders, and schizophrenia (N=315), could not receive routine psychiatric care because of suspended hospital visits. Consequently, 18.1% of patients (N=259) have self-reduced medication dosages, and 17.2% of patients (N=247) stopped taking their medication because they could not gain access to prescriptions from physicians during the outbreak. As the lifetime prevalence of mental disorders is 16.6% among adults in China (4), millions of psychiatric patients may face barriers to help seeking for timely management of their mental health condition. The long-term repercussions of the viral pandemic on the management of psychiatric patients warrant further investigation. Nonetheless, our data reiterate the importance of implementing appropriate mental health care measures in the face of the COVID-19 pandemic.In response to the COVID-19 outbreak, there have been ongoing measures and concerted efforts in China that emphasize the importance of dealing with the potentially concurrent mental health crisis. On January 26, 2020, the National Health Commission of China released principles for emergency psychological crisis intervention for the COVID-19 pandemic (5). Mental health hotlines were quickly established across China and provided the public with counseling and psychological services. The telephone and Internet have been widely used to deliver mental health care services, and social media platforms (e.g., WeChat, Weibo) have been used to share strategies, guidelines, and education programs for managing potential mental distress. In addition, a series of self-help handbooks for psychological care associated with COVID-19 have been published by the China Association for Mental Health, medical institutions, and universities.Furthermore, a number of hospitals in China have initiated telemedicine services for patients in need during the outbreak of COVID-19. On January 26, 2020, West China Hospital of Sichuan University, as one of the leading hospitals in China, opened a free online outpatient service involving more than 100 medical doctors across specialties. This online outpatient service was created mainly to provide prescriptions to existing patients and to offer consultation to new patients. Our hospital collaborated with commercial courier services to deliver medication to patients' homes at no cost. To date, thousands of patients have received health care provided by this online outpatient service. Interestingly, only 7.4% of patients with mental disorders (N=136) in our survey have sought online help for medical care. Thus, there is a need to promote online mental health care services across China to manage mental health problems during the pandemic.The long-term outcomes of the mental health interventions in both community and hospital settings need further evaluation to determine how we can ameliorate the negative effects of viral outbreaks in the general public, especially among vulnerable patients with mental health problems.Sleep Medicine Center (Zhou, Xue, Tang), Department of Anesthesiology, Translational Neuroscience Center (Liu), and Outpatient Department (Yang), West China Hospital, Sichuan University, Chengdu, China.Send correspondence to Dr. Zhou ([email protected]).The authors report no financial relationships with commercial interests.The authors thank the clinic nurses in the Departments of Psychiatry, Neurology, and Sleep Medicine, West China Hospital, Sichuan University.References1 Lu R, Zhao X, Li J, et al.: Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 2020; 395:565–574Crossref, Medline, Google Scholar2 World Health Organization (WHO): WHO director-general's opening remarks at the media briefing on COVID-19: 11 March 2020 (https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020)Google Scholar3 Liu S, Yang L, Zhang C, et al.: Online mental health services in China during the COVID-19 outbreak. Lancet Psychiatry 2020; 7:e17–e18Crossref, Medline, Google Scholar4 Huang Y, Wang Y, Wang H, et al.: Prevalence of mental disorders in China: a cross-sectional epidemiological study. Lancet Psychiatry 2019; 6:211–224Crossref, Medline, Google Scholar5 National Health Commission of China: [Principles for emergency psychological crisis intervention for the new coronavirus pneumonia.] http://www.nhc.gov.cn/jkj/s3577/202001/6adc08b966594253b2b791be5c3b9467.shtml (Chinese)Google Scholar FiguresReferencesCited byDetailsCited byRelationship between depression and burnout among nurses in Intensive Care units at the late stage of COVID-19: a network analysis1 April 2024 | BMC Nursing, Vol. 23, No. 1Effects of Long COVID on Psycho-Physical Conditions in the Italian Population: A Statistical and Large Language Model Combined Description27 April 2024 | European Journal of Investigation in Health, Psychology and Education, Vol. 14, No. 5The efficacy of internet-delivered cognitive-behavioral therapy for posttraumatic stress disorder according to the mean age of patients: a systematic review and meta-analysis11 December 2023 | Psychology, Health & Medicine, Vol. 29, No. 4Descripción de un Programa de Telesalud Mental en el Marco de la Pandemia de COVID-19 en ColombiaRevista Colombiana de Psiquiatría, Vol. 53, No. 2Longitudinal trajectories of anxiety and depression in subjects with different mental disorders after one year in the COVID-19 pandemicPsychiatry Research, Vol. 334The Impact of the COVID-19 Pandemic on the Mental Health of Families16 April 2024Effect of anxiety and depression on self-reported adverse reactions to COVID-19 vaccine: a cross-sectional study in Shanghai, China3 March 2023 | BMC Public Health, Vol. 23, No. 1Evaluation of cognitive functions in a group of Egyptian recovered COVID-19 patients22 May 2023 | Middle East Current Psychiatry, Vol. 30, No. 1Trends in telemedicine utilization for mental illness during the COVID-19 pandemic: an analysis of a nationwide database in Korea24 October 2023 | BMC Psychiatry, Vol. 23, No. 1Investigating the dynamic relationship between stigma of fear, discrimination and employees performance among healthcare workers during Covid-19 pandemic31 July 2023 | Cognition, Technology & Work, Vol. 25, No. 4"I Can't See an End in Sight." 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Internet Research, Vol. 22, No. an Outpatient Psychiatric to During the COVID-19 Pandemic: A October 2020 | Journal of Internet Research, Vol. 22, No. disorders in people infected with the coronavirus September 2020 | Journal of Public Health, Vol. No. 4 July authors thank the clinic nurses in the Departments of Psychiatry, Neurology, and Sleep Medicine, West China Hospital, Sichuan April 2020 online May 2020 in 1 July 2020
The escalating global burden of mental health disorders, with anxiety and depression now among the principal causes of disability affecting over one in eight individuals, constitutes a critical public health crisis (1). Although these conditions emerge from a complex interplay of genetic, psychosocial, and environmental factors, there is increasing consensus that lifestyle interventions-especially dietary patterns-represent modifiable targets for both prevention and treatment (2). Within this context, Nutritional Psychiatry has emerged as an essential interdisciplinary field, elucidating the bidirectional pathways through which diet shapes brain function and emotional well-being. Still, contemporary therapeutic frameworks must evolve beyond a reductionist focus on isolated nutrients to address the fundamental determinants of mental health-how, when, and why we eat (3,4,5). Eating behaviors involve complex emotional, cognitive, and bodily processes influencing diet, stress, and mental health, but are often overlooked in clinical research (6,7).Mindfulness and mindful eating offer behavioral strategies uniquely positioned to address this gap by cultivating present-moment awareness and attunement to internal and external cues. Accumulating neuroscientific evidence suggests that mindfulness-based interventions recalibrate reward processing, enhance neurocognitive flexibility, and facilitate stress regulation (8,9,10). Notably, mindful eating has demonstrated efficacy in improving eating behaviors related to overweight and obesity, conditions closely linked with mental health disorders, by reducing emotional and binge eating and improving self-regulation (5,6). Neuroimaging data indicate that mindful eating can modulate the salience of food cues, dampen activity in the midbrain reward pathway, and strengthen prefrontal emotion regulation networks (9,11).Despite promising advances, this field faces challenges including conceptual ambiguity, methodological variability, and a scarcity of long-term mechanistic studies (12,13). This Opinion advocates that mindfulness and mindful eating can directly engage core biobehavioral mechanisms implicated in psychiatric disorders-including reward sensitivity, hedonic hunger, the gut-brain axis, and neuroplasticity. Framed within a salutogenic model prioritizing health promotion, mindful eating emerges as an accessible, low-risk approach that fosters psychological resilience and enables a paradigm shift toward holistic, personalized, and preventive mental health care.Adopting an integrative perspective that extends beyond isolated nutrients to encompass how, why, and how much we eat, we define Mindful Eating as a multidimensional biobehavioral framework rather than a mere modification of ingestion speed. It is conceptualized as the active integration of cognitive, emotional, and interoceptive domains, characterized by non-judgmental attentiveness to the complete sensory experience and internal physiological cues of hunger and satiety. Operationally, this mechanism serves to disrupt behavioral automaticity and decouple food intake from emotional reactivity, thereby realigning dietary decision-making with metabolic homeostasis rather than hedonic reward processing.The traditional focus in nutritional psychiatry on isolated nutrients has inadvertently fostered a reductionist perspective, overlooking the complex biopsychosocial nature of eating behavior (2,14). Eating transcends mere biochemical ingestion; it is an intricate behavior influenced by emotional, cognitive, and social contexts that together shape dietary adherence and clinical outcomes (4,15). Overlooking these behavioral dimensions may limit the effectiveness of nutrient-centered interventions (16).A critical flaw in many current dietary interventions is the implicit assumption of rational, linear adherence to guidelines, which overlooks how emotional states, habitual cues, and cultural scripts powerfully shape actual eating behavior. Mindful eating directly addresses this gap. By fostering heightened awareness and self-regulation, it shows preliminary promise in decoupling eating from hedonic and emotional drivers and in enhancing dietary consistency (5,6,7). However, well-powered, longitudinal trials are needed to elucidate its long-term impact on energy balance and metabolic health.For nutritional psychiatry to realize its full potential, it must treat eating behavior not merely as a confounder but as a primary therapeutic target. Cultivating a mindful, positive relationship with food could empower individuals to adopt and maintain nutrient-rich diets, maximizing the preventive and therapeutic benefits of nutrition for mental health.Mindfulness-based interventions engage complex neurobiological and behavioral pathways essential to mental health, making them promising tools in nutritional psychiatry (5,15). These approaches recalibrate maladaptive responses to hyperpalatable food cues, promote behavioral flexibility, and engage brain circuits involved in reward and stress regulation, thus offering pathways to reshape eating patterns and enhance psychological well-being (7, 9) (see Figure 1).Hedonic hunger refers to eating for pleasure rather than metabolic need, mediated by dopamine-driven reward pathways in the striatum and midbrain (17). Mindful eating appears to attenuate these hypersensitive circuits by encouraging nonjudgmental observation of cravings, decoupling conditioned food cues from compulsive eating, and modulating reward signaling (9,11). Neuroimaging shows reduced mesolimbic reward activation and improved executive control, consistent with enhanced top-down regulation (9, 10).Mindful eating also holds significant promise for mitigating compulsive and addiction-like eating patterns, which share neurobiological substrates with substance use disorders. By fostering cognitive decentering-the ability to observe thoughts and urges as transient mental events-mindfulness-based approaches disrupt the cycle of emotional eating and impulsive consumption, thereby facilitating sustainable behavioral change (5, 6, 7).The influence of mindful eating extends to the gut-brain axis. While precise mechanisms remain under investigation, evidence suggests this relationship is mediated largely by autonomic modulation via the vagus nerve (18,19). Chronic stress and distracted eating heighten sympathetic tone, which can increase intestinal permeability and alter gut motility. Conversely, by fostering a parasympathetic state during ingestion, mindful eating promotes vagal tone, creating physiological conditions that favor more diverse and resilient gut microbiota profiles. This includes an increased abundance of taxa such as Bacteroides and Lactobacilli, which produce anti-inflammatory short-chain fatty acids and support gut barrier integrity (20). Concurrently, mindfulness practice downregulates the hypothalamic-pituitary-adrenal (HPA) axis, reducing chronic stress and lowering circulating proinflammatory cytokines that are strongly implicated in the neuroinflammation characteristic of mood disorders (21,22). These interconnected pathways position mindful eating as a synergistic intervention that modulates both systemic and neural health. While these associations are compelling, current evidence is mainly correlational, and the direction of causality remains to be firmly established. Longitudinal studies tracking changes in both microbiota composition and psychological states following mindful eating interventions are essential to disentangle this complex bidirectional relationship.Mindfulness and mindful eating may drive adaptive neuroplastic changes that underpin lasting mental resilience, though the precise mechanisms remain an active area of investigation (23,24). Structural MRI studies consistently report increased gray matter density and cortical thickness in brain regions critical for executive function and emotional regulation, including the prefrontal cortex, anterior cingulate cortex, and insula (24,25,26). These anatomical changes are thought to reflect enhanced dendritic arborization and synaptogenesis.Functionally, mindfulness training systematically modulates key large-scale brain networks. It has been shown to reduce hyperactivity and connectivity within the default mode network (DMN), a system linked to mind-wandering and rumination, thereby mitigating maladaptive self-referential thought (27,28). Simultaneously, it strengthens connectivity within the central executive and salience networks, supporting enhanced attentional control, cognitive flexibility, and emotional regulation-all core components of stress resilience (29,30). At a molecular level, preliminary evidence links mindfulness with increased expression of brain-derived neurotrophic factor (BDNF), a key molecule for synaptic plasticity and neurogenesis (23,31).Collectively, these neurobiological adaptations-from cortical structure to network dynamics and molecular signaling-provide a compelling mechanistic basis for how mindfulness and mindful eating can remodel neural architecture to support healthier eating behaviors and longterm mental health (32). It is important to note that much of the foundational neuroimaging evidence for these neuroplastic changes derives from studies on general mindfulness-based interventions rather than mindful eating protocols specifically. While mindful eating shares foundational elements with general mindfulness practice, specific evidence on its impact on neuroplasticity remains limited and extrapolated mainly from broader interventions.Exposure to green spaces improves mental health by reducing stress and depression while encouraging physical activity and social connection. This well-being boost complements adherence to sustainable diets like the EAT-Lancet Planetary Health Diet, which emphasizes plant-based foods and limits red meat, reducing depression risk and mortality (33,34,35). Mindful eating further supports intentional, health-and planet-conscious choices, strengthening the link between mental health and environmental sustainability (7,36). Together, these factors form a holistic approach to planetary mental health. While specific dietary compositions may vary by clinical or cultural needs, the attentional quality of Mindful Eating serves as a foundational skill for sustainable behavior changeSalutogenesis offers a transformative framework for mental health by focusing on factors that actively promote and sustain well-being (37). Central to this model is the sense of coherence, encompassing comprehensibility, manageability, and meaningfulness (38). Mindful eating can operationalize these elements by fostering awareness of internal cues, enhancing coping with triggers, and aligning food choices with personal values. This approach transcends prescriptive dietary advice, empowering individuals to develop their own General Resistance Resources (GRRs) and navigate complex food environments with resilience (39,40,41).As a scalable, low-cost intervention, mindful eating is well-suited to diverse public health settings. School-based programs employing mindful eating demonstrate promising effects in cultivating healthier relationships with food and promoting psychological resilience (42). Such initiatives exemplify salutogenic strategies that expand both individual and collective resources, fostering self-awareness, agency, and sustainability in mental health care (43)contributing meaningfully even to planetary health goals.Mindfulness and mindful eating are increasingly recognized as behaviorally grounded strategies with neurobiological relevance to mental health. By enhancing interoceptive awareness, fostering cognitive flexibility, and reducing emotionally driven and dysregulated eating patterns, these practices target core mechanisms implicated in psychiatric conditions-including dysregulated reward processing, chronic stress, neuroinflammation, and impaired self-regulation (5,6,8,44). Despite growing interest, several conceptual and methodological limitations continue to impede their integration into clinical and public health frameworks.A persistent challenge lies in the inconsistent operationalization of mindfulness and mindful eating. As emphasized by Mantzios, definitional variability undermines comparability across studies and obscures which elements are truly therapeutic (13). Moreover, mindful eating interacts with co-factors such as self-compassion, attentional control, and emotional context-dimensions that are rarely systematically accounted for (45,46). There is an urgent need for standardized reporting guidelines and multidimensional frameworks that reflect this complexity while improving reproducibility.Methodological heterogeneity also extends to intervention protocols, which vary widely in duration, delivery format (digital vs. in-person), intensity, facilitator training, and cultural contextualization. This variability complicates the synthesis of findings and the identification of active ingredients. Notably, mindfulness-based approaches may not suit all populations equally. Individuals with trauma histories, severe eating disorders, or cognitive vulnerabilities may require trauma-informed adaptations, increased clinician support, and flexible engagement strategies (6,8).Recent findings also point to underexplored but compelling mechanisms. Mindful eating has been linked to increased behavioral flexibility, improved reversal learning, and even enhanced alignment with sustainable food choices and pro-environmental values-suggesting a broader potential for systemic impact (10,36). Integrating these findings into future trial designs could inform interventions that simultaneously address psychological, physiological, and ecological well-being.However, while this synergy with sustainability is promising, Mindful Eating should fundamentally be understood as a diet-agnostic intervention. Its core mechanismsspecifically interoceptive awareness and impulse regulation-are equally relevant across diverse nutritional contexts and are not contingent upon specific macronutrient profiles. This distinction is particularly relevant for metabolic psychiatry, where restrictive interventions such as ketogenic diets are increasingly utilized for symptom management in conditions like bipolar disorder and schizophrenia (47). Furthermore, the universality of mindful eating extends to cultural contexts with traditionally high animal-product consumption, such as circumpolar populations. In these settings, the therapeutic utility of Mindful Eating lies not in enforcing a plant-forward standard, but in optimizing the bio-behavioral relationship with food. By enhancing sensitivity to satiety signals, it supports metabolic regulation regardless of whether the dietary pattern is plant-based or animal-based (48,49).To advance the field, a focused and interdisciplinary research agenda is essential. Key priorities include:• Large-sample, longitudinal randomized controlled trials (RCTs) with active comparators, longer follow-up, and standardized outcome measures in clinically diagnosed populations.• Mechanistic studies employing objective biomarkers, including functional and structural neuroimaging, cortisol, inflammatory cytokines, gut microbiota composition, and brain-derived neurotrophic factor, to identify mediators of effect and individual predictors of response.• Hybrid trials combining mindful eating with dietary interventions-ranging from the Mediterranean, Milpa diet or functional food like berries (50) examining whether behavioral self-regulation enhances dietary adherence, bioavailability, or synergistic therapeutic outcomes.• Component and mediation analyses to isolate active ingredients (e.g., formal meditation vs. informal awareness vs. interoceptive training) and explore doseresponse effects.• Implementation science research, assessing feasibility, cost-effectiveness, digital scalability, and cultural adaptability across varied settings-including schools, primary care, and public health campaigns (51).• Personalization strategies, informed by baseline characteristics (e.g., interoceptive accuracy, trauma history, motivational readiness), to tailor interventions and enhance engagement and efficacy.Beyond clinical application, mindful eating aligns with a salutogenic model of mental health promotion. By cultivating attentional stability, emotional regulation, and embodied awareness, it empowers individuals to develop more sustainable, intentional relationships with food-supporting resilience across diverse populations, ages, and cultural contexts. Its low risk, adaptability, and potential scalability position it as a compelling adjunct within lifestyle-based mental health frameworks.While mindful eating is not a standalone treatment for psychiatric disorders, it represents a biologically plausible and theoretically robust tool that bridges disciplines-linking neuroscience, nutritional science, and behavioral psychology. Future work must prioritize methodological rigor, multidimensional measurement, and culturally informed design to realize its transformative potential in nutritional psychiatry fully.•
Some ideas are many years ahead of their time. In the last quarter of the nineteenth century, Thudichum, one of the founding fathers of neurochemistry, studied the composition of the brain. (For reviews of Thudichum’s work and his contributions to the development of neurochemistry, see Sourkes 1,2 ). His aim was to determine the composition of the brain, as far as was possible, in order to discover what changes occur in brain disorders, including mental illness. The major part of his work concerned lipids, the main constituent of the brain after water. The idea that brain lipid content may be important in the etiology or treatment of psychiatric disorders lay dormant until relatively recently, but it is growing in importance. Lipid is an important constituent of the brain, not only because of myelin, but also because of the large surface-to-volume ratio of neurons — neurons contain a higher proportion of lipid than other cells because lipid is the main constituent of the neuronal cell membrane. The precise characteristics of this lipid bilayer may affect not only the electrical properties of the membrane, but also the properties of proteins embedded in it, such as receptors. However, the extent to which the lipid content of the brain can be altered and the implications this has, both for variations in normal behaviour and for psychopathology, remain uncertain. Reports of altered plasma, red cell or brain lipid profiles in certain psychiatric disorders, including depression 3 and schizophrenia, 4 have led some investigators to postulate that impaired fatty acid and phospholipid metabolism may play a major role in the etiology of psychiatric disorders. Specifically reported are lower levels and altered ratios of the omega-6 and omega-3 essential fatty acids. 3,4 Whether these changes are secondary to other behavioural attributes of patients (e.g., altered food intake, smoking or alcohol use) or a primary metabolic event associated with the disease has not been unequivocally answered. However, increasing evidence is pointing to altered membrane turnover and release of fatty acids from phospholipids via phospholipase A2 in individuals with depression or schizophrenia. These released fatty acids, which are ultimately converted to omega-6 or omega-3 series eicosanoids, contribute to a wide variety of cellular responses, thus implicating genetic disturbances in lipid metabolizing enzymes in the psychopathology of these disorders. Although genetic disturbances in brain lipid metabolism may be associated with psychopathologic disorders, an important question is whether dietary fat can play a contributory role, a therapeutic role or both. At one time, the lipid content of the brain was considered
Estrogen exerts profound effects upon behavior by interacting with neuronal estrogen receptors. Changes in estrogen levels over a woman's life cycle are linked not only to behavioral fluctuations, but potentially to the onset or recurrence of mood disorders. The modern psychiatric evaluation of women requires obtaining a complete reproductive history, including details of hormone treatments, while identifying reproductive events as triggers of affective disorder episodes. While guidelines for the use of reproductive hormones in psychiatry are just evolving, administration of estrogen as an adjunct to antidepressants is an exciting possibility for expanding the frontiers of psychiatry into the field of women's health.
A Step Beyond PsychopathologyA New Frontier of Phenomenology in Psychiatry Melissa Garcia Tamelini (bio) and Guilherme Peres Messas (bio) Critical-philosophical commentary on theses defended in scientific articles may be guided by two distinct perspectives, each leading to inquiries and styles of responses that are both distinct and complementary: an internal perspective and an external perspective. The internal commentator belongs to the same epistemological field of the authors and, as such, shares the same categorical assumptions and the same Weltanschauung explored in the text. The dialogue with this commentator emphasizes the minutiae of the observation of the shared scientific reality and points out the frontiers toward which the discussion of a scientific branch must advance. The external commentator, in contrast, emphasizes the categorical contrasts and semantic differences between the scientific field to which this commentator belongs and the one to which the authors belong. Their inquiries summon the authors to an explanation of their concepts. The valuable comments of Daker and Dalgalarrondo to the article “Principles for pharmacological treatment of schizophrenia in light of phenomenological psychopathology” correspond with internal and external criticisms, respectively. Both allow key points in the proposed discussion to receive further clarification. Before trying to reflect on some aspects raised by the commentators, additional notes are addressed. We share the position that “to consider phenomenology as a purely descriptive science of the way the world appears to be experiencing subject is a serious misunderstanding” (Stanghellini, 2011, p. 29) and that it is the task of psychopathology itself to expand its notorious relevance to clinical practice (Mullen, 2006). However, the transposition of scientific findings from phenomenological psychopathology to psychiatric practice is still a subject of debate in the contemporary literature. Despite the obvious complexity involved in the dialogue between psychopathology and empirical studies, our contribution to this volume of the PPP aims precisely at endorsing the view that critical appreciation of clinical care is the next frontier of the phenomenological research agenda in psychiatry. We believe that a phenomenologically guided therapy is a doable and desirable pragmatic attempt “not only because of the historical legacy of phenomenology but above all its living potential to deal with the dilemmas and challenges [End Page 151] still in force in psychiatry today.” Recent studies begin to propose hypotheses in this direction, in line with the understanding that “core insights into the disorder result as well as core treatment implications” (Moskalewicz & Schwartz, 2018, p. 8). In other words, our aim is to broaden the scope of epistemological foundations already rooted in the psychiatric tradition, but still largely unexplored. This general ambition can only be presented by way of a very restricted example, in this case, a specific property of the antipsychotics in schizophrenia. Without the explanation of the thesis, by means of examples, the article would be no more than an empty manifesto. On the other hand, the presentation of a single example means in itself the possibility of exploring an investigative path, justifying the evocation of a reform of the psychiatric therapeutic agenda. Let us turn to the answers to some of the questions raised, beginning with internal criticism. Daker pertinently inquires: “How weight gain in the living body could lead to a change in the pre-reflexive structure of corporeality?” (p. 144). As the commentator himself explains, there is a common phenomenological distinction, although permeated by ambiguities and heterogeneity in the philosophical and psychopathological literature (Fernandez, 2016), between the lived body (Leib) and the corporeal body (Koerper). These two dimensions constitute the body, which is “a form of subject-object, neither purely that which perceives, nor which is perceived, but constantly both” (Bowden, 2012, p. 231). Regarding the Leib/Koerper polarity, however, it is important to note that taking the corporeal body as a “foreign body in the original life-world of prereflective experience” (Fuchs, 2002, p. 224) would only replace the classic mind–body dualism. And if, under normal conditions, “an ongoing oscillation between these two bodily modes constitutes a fluid and hardly noticed foundation of all experiencing” (Fuchs & Schlimme, 2009, p. 571), in psychopathological contexts, this dialectical balance is modified. In phenomenological terms, schizophrenia is a particular kind of severe modifications of consciousness, which can be...
In this study, we analyze 2,398 research articles published between 2020 and 2024 across eight core venues related to the field of Artificial Intelligence in Education (AIED). Using a three-step knowledge co-occurrence network analysis, we analyze the knowledge structure of the field, the evolving knowledge clusters, and the emerging frontiers. Our findings reveal that AIED research remains strongly technically focused, with sustained themes such as intelligent tutoring systems, learning analytics, and natural language processing, alongside rising interest in large language models (LLMs) and generative artificial intelligence (GenAI). By tracking the bridging keywords over the past five years, we identify four emerging frontiers in AIED--LLMs, GenAI, multimodal learning analytics, and human-AI collaboration. The current research interests in GenAI are centered around GAI-driven personalization, self-regulated learning, feedback, assessment, motivation, and ethics.The key research interests and emerging frontiers in AIED reflect a growing emphasis on co-adaptive, human-centered AI for education. This study provides the first large-scale field-level mapping of AIED's transformation i
With the growing interest in using AI and machine learning (ML) in medicine, there is an increasing number of literature covering the application and ethics of using AI and ML in areas of medicine such as clinical psychiatry. The problem is that there is little literature covering the economic aspects associated with using ML in clinical psychiatry. This study addresses this gap by specifically studying the economic implications of using ML in clinical psychiatry. In this paper, we evaluate the economic implications of using ML in clinical psychiatry through using three problem-oriented case studies, literature on economics, socioeconomic and medical AI, and two types of health economic evaluations. In addition, we provide details on fairness, legal, ethics and other considerations for ML in clinical psychiatry.
Studying psychiatric illness has often been limited by difficulties in connecting symptoms and behavior to neurobiology. Computational psychiatry approaches promise to bridge this gap by providing formal accounts of the latent information processing changes that underlie the development and maintenance of psychiatric phenomena. Models based on these theories generate individual-level parameter estimates which can then be tested for relationships to neurobiology. In this review, we explore computational modelling approaches to one key aspect of health and illness: affect. We discuss strengths and limitations of key approaches to modelling affect, with a focus on reinforcement learning, active inference, the hierarchical gaussian filter, and drift-diffusion models. We find that, in this literature, affect is an important source of modulation in decision making, and has a bidirectional influence on how individuals infer both internal and external states. Highlighting the potential role of affect in information processing changes underlying symptom development, we extend an existing model of psychosis, where affective changes are influenced by increasing cortical noise and consequent i
Land use expansion is linked to major sustainability concerns including climate change, food security and biodiversity loss. This expansion is largely concentrated in so-called frontiers, defined here as places experiencing marked transformations due to rapid resource exploitation. Understanding the mechanisms shaping these frontiers is crucial for sustainability. Previous work focused mainly on explaining how active frontiers advance, in particular into tropical forests. Comparatively, our understanding of how frontiers emerge in territories considered marginal in terms of agricultural productivity and global market integration remains weak. We synthesize conceptual tools explaining resource and land-use frontiers, including theories of land rent and agglomeration economies, of frontiers as successive waves, spaces of territorialization, friction, and opportunities, anticipation and expectation. We then propose a new theory of frontier emergence, which identifies exogenous pushes, legacies of past waves, and actors anticipations as key mechanisms by which frontiers emerge. Processes of abnormal rent creation and capture and the built-up of agglomeration economies then constitute k
Object Goal Navigation (OGN) is a fundamental task for robots and AI, with key applications such as mobile robot image databases (MRID). In particular, mapless OGN is essential in scenarios involving unknown or dynamic environments. This study aims to enhance recent modular mapless OGN systems by leveraging the commonsense reasoning capabilities of large language models (LLMs). Specifically, we address the challenge of determining the visiting order in frontier-based exploration by framing it as a frontier ranking problem. Our approach is grounded in recent findings that, while LLMs cannot determine the absolute value of a frontier, they excel at evaluating the relative value between multiple frontiers viewed within a single image using the view image as context. We dynamically manage the frontier list by adding and removing elements, using an LLM as a ranking model. The ranking results are represented as reciprocal rank vectors, which are ideal for multi-view, multi-query information fusion. We validate the effectiveness of our method through evaluations in Habitat-Sim.
In light of the NIMH's Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and personalized prognosis and diagnosis of mental disorders. Machine learning (ML) and artificial intelligence (AI) technologies are playing an increasingly critical role in the new era of precision psychiatry. Combining ML/AI with neuromodulation technologies can potentially provide explainable solutions in clinical practice and effective therapeutic treatment. Advanced wearable and mobile technologies also call for the new role of ML/AI for digital phenotyping in mobile mental health. In this review, we provide a comprehensive review of the ML methodologies and applications by combining neuroimaging, neuromodulation, and advanced mobile technologies in psychiatry practice. Additionally, we review the role of ML in molecular phenotyping and cross-species biomarker identification in precision psychiatry. We further discuss explainable AI (XAI) and causality testing in a closed-human-in-the-loop manner, and highlight the ML potential in multimedia information extraction and multimodal data fusion. Finally, we disc
The landscape of psychiatric care is poised for transformation through the integration of pharmaco-multiomics, encompassing genomics, proteomics, metabolomics, transcriptomics, epigenomics, and microbiomics. This review discusses how these approaches can revolutionize personalized treatment strategies in psychiatry by providing a nuanced understanding of the molecular bases of psychiatric disorders and individual pharmacotherapy responses. With nearly one billion affected individuals globally, the shortcomings of traditional treatments, characterized by inconsistent efficacy and frequent adverse effects, are increasingly evident. Advanced computational technologies such as artificial intelligence (AI) and machine learning (ML) play crucial roles in processing and integrating complex omics data, enhancing predictive accuracy, and creating tailored therapeutic strategies. To effectively harness the potential of pharmaco-multiomics approaches in psychiatry, it is crucial to address challenges such as high costs, technological demands, and disparate healthcare systems. Additionally, navigating stringent ethical considerations, including data security, potential discrimination, and ensuring equitable access, is essential for the full realization of this approach. This process requires ongoing validation and comprehensive integration efforts. By analyzing recent advances and elucidating how different omic dimensions contribute to therapeutic customization, this review aims to highlight the promising role of pharmaco-multiomics in enhancing patient outcomes and shifting psychiatric treatments from a one-size-fits-all approach towards a more precise and patient-centered model of care.
Stochastic Multi-Objective Optimization (SMOO) is critical for decision-making trading off multiple potentially conflicting objectives in uncertain environments. SMOO aims at identifying the Pareto frontier, which contains all mutually non-dominating decisions. The problem is highly intractable due to the embedded probabilistic inference, such as computing the marginal, posterior probabilities, or expectations. Existing methods, such as scalarization, sample average approximation, and evolutionary algorithms, either offer arbitrarily loose approximations or may incur prohibitive computational costs. We propose XOR-SMOO, a novel algorithm that with probability $1-δ$, obtains $γ$-approximate Pareto frontiers ($γ>1$) for SMOO by querying an SAT oracle poly-log times in $γ$ and $δ$. A $γ$-approximate Pareto frontier is only below the true frontier by a fixed, multiplicative factor $γ$. Thus, XOR-SMOO solves highly intractable SMOO problems (\#P-hard) with only queries to SAT oracles while obtaining tight, constant factor approximation guarantees. Experiments on real-world road network strengthening and supply chain design problems demonstrate that XOR-SMOO outperforms several baseli
Zero-shot open-vocabulary object navigation has progressed rapidly with the emergence of large Vision-Language Models (VLMs) and Large Language Models (LLMs), now widely used as high-level decision-makers instead of end-to-end policies. Although effective, such systems often rely on iterative large-model queries at inference time, introducing latency and computational overhead that limit real-time deployment. To address this problem, we repurpose ray frontiers (R2F), a recently proposed frontier-based exploration paradigm, to develop an LLM-free framework for indoor open-vocabulary object navigation. While ray frontiers were originally used to bias exploration using semantic cues carried along rays, we reinterpret frontier regions as explicit, direction-conditioned semantic hypotheses that serve as navigation goals. Language-aligned features accumulated along out-of-range rays are stored sparsely at frontiers, where each region maintains multiple directional embeddings encoding plausible unseen content. In this way, navigation then reduces to embedding-based frontier scoring and goal tracking within a classical mapping and planning pipeline, eliminating iterative large-model reason
Providing mental healthcare to individuals with limited English proficiency (LEP) remains a pressing problem within psychiatry. Because the majority of individuals trained in providing psychiatric care are English speakers, the quality of mental healthcare given to LEP patients is significantly lower than that provided for English speakers. The provision of mental healthcare is contingent on communication and understanding between the patient and healthcare provider, much more so than in the realm of physical healthcare, and English speakers are often unable to comprehend figurative language such as metaphors used by LEPs. Hence, Figurative Language Translation is invaluable to providing equitable psychiatric care. Now, metaphor has been shown to be paramount in both identifying individuals struggling with mental problems and helping those individuals understand and communicate their experiences. Therefore, this paper aims to survey the potential of Machine Translation for providing equitable psychiatric healthcare and highlights the need for further research on the transferability of existing machine and metaphor translation research in the domain of psychiatry.
Artificial Intelligence (AI) has revolutionized various fields, including medicine and mental health support. One promising application is ChatGPT, an advanced conversational AI model that uses deep learning techniques to provide human-like responses. This review paper explores the potential impact of ChatGPT in psychiatry and its various applications, highlighting its role in therapy and counseling techniques, self-help and coping strategies, mindfulness and relaxation techniques, screening and monitoring, education and information dissemination, specialized support, group and family support, learning and training, expressive and artistic therapies, telepsychiatry and online support, and crisis management and prevention. While ChatGPT offers personalized, accessible, and scalable support, it is essential to emphasize that it should not replace the expertise and guidance of qualified mental health professionals. Ethical considerations, such as user privacy, data security, and human oversight, are also discussed. By examining the potential and challenges, this paper sheds light on the responsible integration of ChatGPT in psychiatric research and practice, fostering improved mental
Computational psychiatry is a field aimed at developing formal models of information processing in the human brain, and how alterations in this processing can lead to clinical phenomena. Despite significant progress in the development of tasks and how to model them, computational psychiatry methodologies have yet to be incorporated into large-scale research projects or into clinical practice. In this viewpoint, we explore some of the barriers to incorporation of computational psychiatry tasks and models into wider mainstream research directions. These barriers include the time required for participants to complete tasks, test-retest reliability, limited ecological validity, as well as practical concerns, such as lack of computational expertise and the expense and large sample sizes traditionally required to validate tasks and models. We then discuss solutions, such as the redesigning of tasks with a view toward feasibility, and the integration of tasks into more ecologically valid and standardized game platforms that can be more easily disseminated. Finally, we provide an example of how one task, the conditioned hallucinations task, might be translated into such a game. It is our h
Large language models (LLMs) are increasingly proposed as scalable solutions to the global mental health crisis. But their deployment in psychiatric contexts raises a distinctive ethical concern: the problem of atypicality. Because LLMs generate outputs based on population-level statistical regularities, their responses -- while typically appropriate for general users -- may be dangerously inappropriate when interpreted by psychiatric patients, who often exhibit atypical cognitive or interpretive patterns. We argue that standard mitigation strategies, such as prompt engineering or fine-tuning, are insufficient to resolve this structural risk. Instead, we propose dynamic contextual certification (DCC): a staged, reversible and context-sensitive framework for deploying LLMs in psychiatry, inspired by clinical translation and dynamic safety models from artificial intelligence governance. DCC reframes chatbot deployment as an ongoing epistemic and ethical process that prioritises interpretive safety over static performance benchmarks. Atypicality, we argue, cannot be eliminated -- but it can, and must, be proactively managed.