The use of artificial intelligence (AI) in psychiatry holds promise for diagnosis, therapy, and the categorization of mental disorders. At the same time, it raises significant theoretical and ethical concerns. The debate appears polarized, with proponents and critics seemingly irreconcilably opposed. On the one hand, AI is heralded as a transformative force poised to revolutionize psychiatric research and practice. On the other hand, it is depicted as a harbinger of dehumanization. To better understand this dichotomy, it is essential to identify and critically examine the underlying arguments. To what extent does the use of AI challenge the theoretical assumptions of psychiatric diagnostics? What implications does it have for patient care, and how does it influence the professional self-concept of psychiatrists?

To explore these questions, we conducted 15 semi-structured interviews with experts from psychiatry, computer science, and philosophy. The findings were analyzed using a structuring qualitative content analysis.

The analysis focuses on the significance of AI for psychiatric diagnosis and care, as well as on its implications for the identity of psychiatry. We identified different lines of argument suggesting that expert views on AI in psychiatry hinge on the types of data considered relevant and on whether core human capacities in diagnosis and treatment are viewed as replicable by AI.

The results provide a mapping of diverse perspectives, offering a basis for more detailed analysis of theoretical and ethical issues of AI in psychiatry, as well as for the adaptation of psychiatric education.

Cognitive impairment represents a central component of major depressive disorder (MDD), affecting a large proportion of people living with MDD and showing a consistent negative impact on social, interpersonal, and occupational functioning and subjective quality of life. Cognitive remediation (CR) is a training-based psychosocial intervention targeting cognitive performance and psychosocial functioning that has shown consistent evidence of effectiveness in individuals with schizophrenia and that could provide significant benefits also in people with MDD: this study aimed to assess the effects of a computerized CR intervention in adults living with MDD.

Participants recruited in this single blind multicentric randomized controlled trial were allocated to receive a computerized CR intervention delivered by an active and trained therapist or to an active control condition (computer games – CG). Outcomes were measured with validated instruments by blind assessors and included cognitive performance, depressive symptoms, and psychosocial functioning. Outcomes were assessed using mixed models for repeated measures, considering baseline and end-of-treatment scores.

Hundred and one participants (CR=52 and CG=49) were included and 81 (CR=45 and CG=36) completed the study. CR produced superior results in clinician-rated depressive symptoms (p=0.023, d=042), global clinical severity (p=0.025, d=0.39), subjective depressive symptoms (p=0.005, d=0.45), working memory performance (p=0.004, d=0.34), executive functions/cognitive flexibility (p=0.020, d=0.43), and subjective cognitive impairment (p=0.006, d=0.48).

CR represents an effective intervention in MDD, improving clinical outcomes and cognitive performance in a clinician-rated and in a subjective manner, which should be more consistently implemented in clinical practice and included in MDD treatment recommendations.

We aimed to identify therapeutic approaches for managing schizophrenia in different phases and clinical situations – the prodromal phase, first-episode psychosis, cognitive and negative symptoms, pregnancy, treatment resistance, and antipsychotic-induced metabolic side effects – while assessing clinicians’ adherence to guidelines.

A cross-sectional online survey was conducted in 2023 as part of the Ambassador project among psychiatrists and trainees from 35 European countries, based on a questionnaire that included six clinical vignettes (cases A–F). Additionally, a review of multiple guidelines/guidance papers was performed.

The final analysis included 454 participants. Our findings revealed a moderate to high level of agreement among European psychiatrists regarding pharmacological treatment preferences for first-episode psychosis and cognitive and negative symptoms, prodromal symptoms and pregnancy, with moderate adherence to clinical guidelines. There was substantial similarity in treatment preferences for antipsychotic-induced metabolic side effects and treatment resistance; however, adherence to guidelines in these areas was only partial. Despite guideline recommendations, non-pharmacological treatments, including psychotherapy and recovery-oriented care, were generally underutilized, except for psychoeducation and lifestyle recommendations, and cognitive behavioural therapy for treatment of the prodromal phase. Contrary to guidelines, cognitive remediation and physical exercise for cognitive symptoms were significantly neglected.

These discrepancies highlight the need for effective implementation strategies to bridge the gap between research evidence, clinical guidelines/guidance papers, and real-world clinical practice. Clinicians’ unique combination of knowledge and experience positions them to shape future guidelines, especially where real-world practice diverges from recommendations, reinforcing the need to integrate both research evidence and clinical consensus.

Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.

T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).

PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).

PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.

Physical exercise improves mental and physical health of individuals with severe mental illness (SMI); however, its impact on metabolic syndrome remains unclear.

To evaluate the effects of exercise interventions on metabolic syndrome components in individuals with SMI and explore interactions between exercise and antipsychotic medications on metabolic outcomes.

Following PRISMA guidelines, we systematically searched PubMed, CINAHL, Web of Science, and APA PsycINFO through October 10, 2023, for randomized controlled trials (RCTs) assessing the effects of exercise on waist circumference, blood pressure, glucose, triglycerides, and HDL cholesterol in SMI. Risk of bias was evaluated using the Cochrane RoB-2 tool. Data were pooled using random-effects models in Comprehensive Meta-Analysis and JASP.

Ten RCTs (N = 773; mean age 39.9 ± 7.36 years; 38.7% female; 71.5% schizophrenia spectrum disorders) met inclusion criteria. Pooled analyses revealed no significant effects of exercise on waist circumference (SMD = 0.206, 95% CI [−0.118, 0.530], p = 0.171), systolic blood pressure (SMD = 0.194, 95% CI [−0.115, 0.504], p = 0.219), diastolic blood pressure (SMD = −0.21, 95% CI [−0.854, 0.434], p = 0.522), HDL (SMD = 0.157, 95% CI [−0.36, 0.674], p = 0.551), triglycerides (SMD = −0.041, 95% CI [−0.461, 0.38], p = 0.849), or glucose (SMD = −0.071, 95% CI [−0.213, 0.071], p = 0.326). Heterogeneity was moderate to high.

Exercise interventions did not significantly improve metabolic syndrome components in SMI. Future trials must prioritize tailored regimens, adjunctive therapies, and rigorous control of medication effects.

Psychotic disorders, including schizophrenia (SZ), schizoaffective disorder (SZA), bipolar disorder (BD), psychotic depression (PD), and other nonaffective psychoses (ONAP), are associated with increased risk of suicidal acts. Few studies have compared suicidal act prevalence across psychotic disorders using both self-report and register data. The impact of hospitalization duration on subsequent suicidal acts is unclear.

We used data from the SUPER-Finland study, involving 7067 participants with register-based ICD-10 diagnoses of psychotic disorders (SZ, SZA, BD, PD, ONAP). Lifetime suicidal acts were identified through self-report and register-based records of intentional self-harm events requiring medical treatment. Associations between diagnostic categories and suicidal acts were assessed using logistic regression, adjusted for sex, duration of illness, socioeconomic status, childhood abuse, and substance use. Survival analysis was used to examine the impact of hospital stay length on postdischarge self-harm.

Lifetime suicide attempts (39.1%) and register self-harm (19.3%) were prevalent. of those with self-reported suicide attempts, 40.5% also had register-based self-harm. Self-harm and suicide attempts were significantly more prevalent in SZA, BD, and PD compared to schizophrenia, with large differences between groups (24.1–46.4% for suicide attempts, 11.1–23.9% for self-harm). Adjusted odds of self-harm were higher for disorders with a mood component. Shorter hospitalizations were associated with an elevated hazard ratio for subsequent self-harm.

Prevalence of register-based self-harm and self-reported suicide attempts differ markedly. Suicidal acts are common in psychotic disorders, particularly in those with a mood component. Very short inpatient stays may not be adequate in these disorders.

Considering the high likelihood of chronicity, it is imperative to understand the risk factors and outcomes associated with severe anorexia nervosa (AN), for which Danish registers provide a unique opportunity. We developed a measure of AN severity adapted from clinical literature for use in register-based research.

The study population included all Danish individuals born between 1963 and 2007 who were diagnosed with AN from 1969 to 2013. Using register data, we constructed the anorexia nervosa register-based severity index (AN-RSI), incorporating early or late illness onset, number of inpatient admissions and outpatient treatments, cumulative treatment length, and illness duration, each weighted based on clinical importance. Associations between AN-RSI scores, evaluated 5 years after first AN diagnosis, and mortality were estimated using survival analysis.

Among 9167 individuals diagnosed with AN, 132 died during follow-up: 17 from AN, 30 from suicide, and 85 from other causes. Higher AN-RSI scores were associated with increased rates of mortality from AN, somatic anorexia diagnosis, suicide, alcohol-related causes, and any cause. AN cases who scored in the top 20% of AN-RSI had especially high mortality rates. Furthermore, severe AN cases were also more likely to be in treatment in the next 5 years after severity was established.

AN-RSI effectively captures mortality and long-term treatment in the absence of detailed patient records and is associated with later mortality in AN patients. AN-RSI could serve as a tool to examine epidemiological and genetic risk factors associated with AN course and outcomes.