Evolutionary psychiatry is a growing field that emphasizes the value of evolutionary explanations for traits that make individuals vulnerable to mental disorders. Some articles that apply evolutionary theory in psychiatry make errors, such as viewing a disease as an adaptation. We assessed article quality and error quantity in the most cited articles on evolutionary psychiatry and examined the relationship of these measures to citation number.

PubMed, Web of Science, and Google Scholar were searched in 2023 and again in 2025 using specific terms related to “evolution” and “psychiatry”, to find the most highly cited articles in the field. Based on the work of Nesse, we developed a measure for assessing overall article quality and error quantity in evolutionary psychiatry articles. We applied the measure to the 20 most highly cited articles, and calculated the correlations of article quality and error quantity with number of citations.

Twenty highly cited articles, with a mean citation count of 413.30 and publication year from 1964 to 2011, were rated. While the most highly cited articles had good quality on average, they also made important errors. There was no significant correlation of article quality or error quantity with citation count.

Highly cited articles in evolutionary psychiatry demonstrated strengths but also weaknesses. The lack of a relationship of article quality and error quantity to citation rates suggests that other factors influence such citations. Future research should focus on achieving consensus on how best to assess the quality of evolutionary psychiatry articles and what errors should be avoided.

This systematic review aimed to investigate the effectiveness of mindfulness-based interventions (MBIs) in treating depression, enhancing interoceptive awareness (IA), and whether IA mediates this relationship.

In August 2024, a comprehensive literature search was conducted in web-based medical and psychological databases, including PsycINFO, MEDLINE, and Scopus, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies were included if they were quantitative, peer-reviewed, in English, used MBIs derived from Mindfulness-based Stress Reduction (MBSR), Mindfulness-based Cognitive Therapy (MBCT), or Mindfulness-integrated Cognitive Behavioural Therapy (MiCBT), included a control/comparison group, pre- and post-intervention measures, assessed depressive symptoms and IA in adults over 18, and had at least 20 participants. Exclusion criteria included non-English publications, dissertations, case studies, qualitative research, therapies not derived from the specified MBIs, and studies with under 20 participants or individuals under 18. Methodological quality and risk of bias were assessed.

Six studies involving 646 participants met the inclusion criteria. All MBIs (MBCT, MBSR, MiCBT, Mindfulness-based Cancer Recovery, and Mindful Awareness in Body-Oriented Therapy) significantly reduced depressive symptomology and improved IA across varying effect sizes, with IA identified as a partial mediator.

MBIs appear to alleviate depressive symptoms and improve IA, with one study finding IA as a mediator. Limitations included limited literature, search term specificity, heterogeneity and mixed evidence quality. Future research should explore IA’s mediating role, develop a standardised IA measure, and integrate IA into broader treatment modalities to enhance outcomes.

CRD42023457300, https://www.crd.york.ac.uk/PROSPERO/view/CRD42023457300.

The pathophysiological mechanisms underlying alcohol use disorder (AUD) remain unclear, and its clinical evaluation largely depends on subjective assessments lacking objective biomarkers. This study employed a case-control design incorporating resting-state electroencephalography (EEG) with power spectral analysis (PSA) and dynamic functional connectivity (dFC) to explore potential biomarkers for AUD.

Resting-state EEG data were collected from individuals diagnosed with AUD and demographically matched healthy controls (HCs), alongside comprehensive neuropsychological and behavioral evaluations. PSA quantified energy distribution across specific frequency bands, with receiver operating characteristic analysis determining its discriminatory capacity. dFC was examined using a sliding window approach and the weighted phase-lag index, followed by K-means clustering to extract dominant connectivity states across frequency bands.

After excluding cases with suboptimal EEG data, the final analytic sample comprised 25 individuals with AUD and 26 HCs. Compared to HCs, the AUD group exhibited elevated low-beta power at F1, FCz, FC1, and C3 electrode sites (10-20 EEG system), with respective area under the curve values of 0.795, 0.794, 0.806, and 0.769, indicating reliable group differentiation. Temporal profiling of functional connectivity revealed three distinct brain states: S1 (60.81%), S2 (21.05%), and S3 (18.15%). Correlations between these connectivity patterns and clinical indices were observed in the AUD cohort.

Individuals with AUD showed increased brain activity in the medial frontal gyrus and left central gyrus at rest, as well as significant low-beta frequency changes in dFC analysis. Resting EEG scans with PSA and dFC analysis could serve as potential biomarkers for detecting AUD.

Treatment-resistant depression (TRD) with comorbid anxiety affects up to 30% of patients and frequently fails to respond to conventional therapeutic approaches. The Seville Protocol is a novel, accelerated, high-dose, bilateral theta burst stimulation (TBS) paradigm combining intermittent TBS (iTBS) and continuous TBS (cTBS), specifically designed to address both depressive and anxiety symptoms in TRD.

This retrospective study was conducted at the Andalusian Institute of Brain Health (Seville, Spain). All participants received the Seville Protocol, consisting of neuronavigated iTBS applied to the left and cTBS to the right dorsolateral prefrontal cortex (DLPFC), delivered at high intensity (110–133.5% of the resting motor threshold) over 30 sessions within three weeks. Symptom severity was assessed at baseline and post-treatment using the Hamilton Depression Rating Scale (HAM-D) and the Hamilton Anxiety Rating Scale (HAM-A). Treatment efficacy was analyzed using the Wilcoxon signed-rank test, and logistic regression models were applied to identify predictors of response and remission.

A total of 64 patients diagnosed with TRD and comorbid anxiety were included in the analysis. The Seville Protocol led to significant improvements in both HAM-D and HAM-A scores (p < 0.001). Response rates were 45.3% for depression (95% Confidence Interval (CI) = 33.7–57.4) and 48.4% for anxiety (95% CI = 36.6–60.4), while remission rates were 29.7% for depression (95% CI = 19.9–41.8) and 23.4% for anxiety (95% CI = 14.7–35.1). Logistic regression analysis suggested that a positive family history of mental disorders was associated with a lower likelihood of depression response (β = –1.49, 95% CI = –2.98 to –0.18, p = 0.033); however, this association did not remain significant after false discovery rate (FDR) correction (adjusted p = 0.298).

The Seville Protocol appears to be a feasible, practical, and time-efficient neuromodulation approach for patients with TRD and comorbid anxiety. These findings support the potential utility of accelerated bilateral TBS in this population, although further studies are needed to validate the findings and assess their broader applicability.

The objective of this study was to analyze the functional connectivity (FC) of the precentral gyrus (PCG) bilaterally in a sample of patients with schizophrenia experiencing chronic auditory verbal hallucinations (AVH) including a control cohort of healthy volunteers.

A total of 105 subjects underwent resting-state functional magnetic resonance imaging (MRI) scanning, including 63 healthy control individuals (HC) and 42 schizophrenia patients experiencing AVH. A comparative approach was used to analyze the FC of the PCG bilaterally.

The present study detected increased resting-state FC (rsFC) involving the right PCG and three clusters distributed bilaterally across the frontal cortex, the supplementary motor area (SMA), paracingulate gyrus and the anterior cingulate gyrus (ACC), as well as hypoconnectivity between the right PCG and the lingual gyrus – bilaterally and the left occipital fusiform gyrus in schizophrenia as compared to HC. Furthermore, we observed hyperconnectivity between the left PCG and four clusters, including right paracingulate gyrus, ACC, right frontal pole (FP), precuneus, right pre- and postcentral gyri, right superior frontal gyrus (SFG), and right SMA. In addition, the patient group demonstrated hypoconnectivity between the left PCG and the right occipital pole, right lingual gyrus, right lateral occipital cortex, as well as the right cerebellar crus 1.

In the present study we observed a lateralized impairment in rsFC between the explored seeds and specific cortical and subcortical regions in schizophrenia. These alterations might contribute to the neurobiological pathways involved in schizophrenia pathogenesis with a focus on higher hallucination proneness.

In autism spectrum disorder (ASD), the human plasma metabolome is altered but the causal relationship between the levels of metabolites and ASD is unclear. We aimed to assess bidirectional causal associations between plasma metabolites and ASD.

We investigated potential causal associations between the genetic variation contributing to the levels of metabolites and ASD via Mendelian randomization (MR) analyses. Genome-wide association study (GWAS) summary datasets were used in the study, including ASD (n = 46,350) and 871 plasma metabolite (n = 8299) datasets. We used druggability analysis to prioritize metabolites with therapeutic potential.

Our MR analysis identified 32 plasma metabolites whose levels were protective against the risk of ASD, including 5 alpha-androstan-3 alpha, 17 beta-diol disulfate (odds ratio (OR): 0.94, 95% CI: 0.90–0.97) and 11beta-hydroxyetiocholanolone glucuronide (OR: 0.95, 95% CI: 0.92–0.98). Additionally, 12 metabolites were found to be positively associated with the risk of ASD, including indoleacetylglutamine (OR: 1.04, 95% CI: 1.01–1.08) and sphingomyelin (d18:1/24:1, d18:2/24:0) (OR: 1.06, 95% CI: 1.01–1.11). Some metabolites may be regulated through drug intervention, including sphingomyelin, chiro-inositol, carotene diol (1)/(2), and glycerol. Genetic variation contributing to ASD may increase the abundance of five metabolites, including deoxycholic acid glucuronide (OR: 1.18, 95% CI: 1.03–1.34); meanwhile, the abundance of 27 metabolites, including stearoyl choline (OR: 0.80, 95% CI: 0.69–0.92) may be causally reduced.

Our MR analysis uncovered bidirectional causal associations between certain plasma metabolites and ASD, suggesting that these metabolites could be biomarkers for ASD and paving the way for novel therapeutic targets in ASD phenotypes.

Patients with narcolepsy experience excessive daytime sleepiness (EDS) and cognitive impairment. However, studies on the circadian variability associated with cognitive impairment in narcolepsy patients are scarce. This study aimed to explore circadian cognitive performance in narcolepsy patients compared with patients with obstructive sleep apnea (OSA) and EDS (OSA-with-EDS).

A total of 62 participants, 29 with narcolepsy and 33 with OSA-with-EDS completed the study. The assessments were done using questionnaires, polysomnography (PSG), the multiple sleep latency test (MSLT), and cognitive-behavioral tasks at different time points (20:00, 08:00, 10:00, 12:00, 14:00, 16:00, and 18:00) including the psychomotor vigilance task (PVT), the Stroop color-word task, and the 2-back task to separately assess the circadian variations of vigilant attention, inhibitory control, and working memory respectively.

Narcolepsy patients showed significant within-subject circadian variations in vigilant attention (p < 0.001), inhibitory control (p = 0.016), and working memory (p < 0.001) in the time domain. Overall, vigilant attention in narcolepsy patients presented a pattern with optimal performance observed at 20:00 on the previous night followed by deterioration in the morning (08:00~14:00) and improvement in the afternoon (14:00~18:00). Inhibitory control displayed a pattern of “enhancement in the morning (08:00~12:00) followed by a decline in the afternoon (12:00~18:00)”, while working memory displayed a trend of improvement during daytime hours, with these two measures showing their poorest performance at 20:00 on the previous night.

Circadian variations were prominently observed in vigilant attention, inhibitory control, and working memory performance among patients with narcolepsy. Except for EDS, the intrinsic disease specificity may play an important role in the cognitive impairments associated with narcolepsy.

Attention-Deficit/Hyperactivity Disorder (ADHD) and Major Depressive Disorder (MDD) both exhibit working memory (WM) impairments and frequently co-occur. However, the impact of comorbid MDD on WM in ADHD patients and the underlying mechanisms remain unclear.

The study included 409 adults, comprising 125 ADHD patients comorbid with MDD (ADHD+MDD), 145 ADHD patients without MDD (ADHD-MDD), and 139 healthy controls. In addition, functional connectivities (FCs) with the region of interest—the dorsolateral prefrontal cortex (DLPFC)—were analyzed in a subsample to explore the potential underlying neural mechanism.

The WM scores of the ADHD+MDD group were higher than those of the ADHD-MDD group. In all ADHD patients, depression scores were positively correlated with the WM impairment scores and explained 3.6% of the variance in WM impairment. Mediation analysis detected a potential effect of ADHD diagnosis on WM impairment via depressive symptoms. WM-related FC was identified between the left DLPFC and the right supramarginal gyrus (FC_{[DLPFC/L - SMG/R]}), which partially mediated the relationship between the co-morbid status of MDD and WM.

MDD in adults with ADHD exacerbated WM impairment, which may be related to the FC alteration between the left DLPFC and the right supramarginal gyrus (SMG). This finding provides a scientific basis for a deeper understanding of the pathogenesis and brain biomarkers of ADHD+MDD patients.

Depression relapse rates remain high after acute treatment; this study evaluates the efficacy of maintenance noninvasive brain stimulation in preventing relapse and identifies optimal treatment parameters.

This meta-analysis was conducted following PRISMA guidelines. We conducted a systematic search of PubMed, Embase, Web of Science, Cochrane Library, and PsycINFO databases up to January 5, 2025. The primary outcome was relapse rate.

A total of nine randomized controlled trials with 837 participants were included, six studies used electroconvulsive therapy (ECT) and three studies used repetitive transcranial magnetic stimulation (rTMS). Our findings indicate that ECT combined with pharmacotherapy or rTMS alone demonstrated superiority over pharmacotherapy alone in reducing the relapse of depression during 6, 9, 12-month maintenance treatment periods. Interestingly, ECT alone did not show significant results. In terms of stimulation parameters, the ECT combined with pharmacotherapy group mainly received right unilateral stimulation, while the ECT alone group had bitemporal stimulation. The stimulation frequency was similar between the two groups. In contrast, the rTMS-alone group had significantly higher stimulation frequencies than the ECT groups. We did not find any eligible studies on transcranial direct current stimulation, transcranial alternating current stimulation or magnetic seizure therapy, but they also showed potential in the maintenance treatment of depression, which warrants further investigation.

ECT combined with pharmacotherapy, or rTMS alone, is more effective than pharmacotherapy alone in preventing relapse of depression during 6 to 12 months of maintenance treatment. Future research should prioritize identifying the optimal treatment regimen and exploring the potential of combination therapies.

CRD42023490546, https://www.crd.york.ac.uk/PROSPERO/view/CRD42023490546.

Individuals suffer from depression at a high rate on university campuses and current assessment methods primarily rely on subjective questionnaires. Therefore, there is a pressing need to develop objective measures for the automatic detection of depression. This study aimed to investigate the functional near-infrared spectroscopy (fNIRS) changes associated with depression and assess the potential of fNIRS signals in detecting depression among university students.

A total of 192 participants were recruited for psychological assessment. A 48-channel fNIRS system was employed to measure cerebral blood oxygenation signals during the verbal fluency task (VFT). Two-sample t-tests were used to detect group differences. The association between fNIRS data and depression was identified using Pearson correlation analysis. We applied five machine learning classifiers to differentiate depression using fNIRS signals. Model performance was evaluated using receiver operating characteristic (ROC) curves, area under the curve (AUC), precision, accuracy, recall, and F1 score. A ten-fold cross-validation incorporating the recursive feature elimination algorithm was utilized.

Significant hemodynamic alterations were observed in the depression group at channels 4, 16, 21, 26, 32, 43, 44, and 47, in comparison with the control group. The bilateral medial prefrontal cortices (MPFC), left dorsolateral prefrontal cortex, and left temporal lobe, represented by channels 4, 16, 43, and 44, were associated with depression. Among the five machine learning algorithms, K-Nearest-Neighbors (KNN) exhibited superior classification performance (AUC = 66.51%). The left MPFC was the most significant contributor to the classification efficacy of the KNN model.

fNIRS-VFT may serve as an objective tool for evaluating depressive symptoms in university students. The findings underscore the central role of the left MPFC in the neural mechanisms underlying depression. This work developed an fNIRS-based identification system for depression in university students.

This study compared addiction severity, psychotic symptoms, suicide risk, and craving in patients with heroin use disorder, with and without methamphetamine use. We also investigated the reasons for methamphetamine use in these patients, and assessed 3-month clinical follow-up and treatment compliance.

This cross-sectional study included 166 inpatients diagnosed with heroin use disorder (DSM-5). Patients were divided into two groups: heroin use only (H), and heroin use + methamphetamine use (H+M). Clinical assessments included the Addiction Profile Index-Clinical Form (API-C), Brief Psychiatric Rating Scale (BPRS), and Suicide Probability Scale (SPS). Statistical analyses were conducted with Statistical Package for the Social Sciences (SPSS) and included descriptive statistics, Kolmogorov-Smirnov test, Chi-square test, Mann-Whitney U test, and logistic regression. Three-month follow-up results and treatment compliance were compared between the two groups.

The H and H+M groups included 80 and 86 participants, respectively. The H+M group had higher BPRS total scores, API-C subscale scores (craving, risky behaviors, excitement-seeking, impulsiveness, depression), addiction severity, additional substance use, anxiety, depressive symptoms, suicidal ideation, and 3-month lapse rate. Craving and excitement-seeking were independent predictors of methamphetamine use.

The H+M group showed more severe addiction, novelty-seeking personal characteristics, and suicidal ideation compared to the H group. Craving scores were higher in the H+M group and should not be overlooked, along with a greater risk of early lapse. Our study found that craving, risky behaviors, depressive and psychotic symptoms, and suicidal thoughts are the most critical issues to be addressed in the treatment and follow-up of the H+M patient group.

To explore the molecular mechanisms underlying clozapine-induced metabolic syndrome (MetS) in schizophrenia patients, providing scientific evidence for clinicians to prevent and manage metabolic syndrome during the treatment of psychiatric disorders.

Ten schizophrenia patients with MetS and ten matched controls were recruited from Shanghai Mental Health Center according to the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria for schizophrenia and the 2016 Chinese Adult Dyslipidemia Prevention and Treatment Guidelines for MetS. Peripheral blood RNA sequencing was performed to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network were used to pinpoint hub genes. Mendelian randomization (MR) was conducted to validate causal relationship between serum brain-derived neurotrophic factor (BDNF) levels and MetS components.

A total of 1019 DEGs were identified, grouped into eight mRNA modules through WGCNA. Key hub genes included RP11-611O2.6, acid phosphatase-like 2 (ACPL2), T cell receptor alpha variable 12-2 (TRAV12-2), matrix metallopeptidase 8 (MMP8), piggyBac transposable element derived 4 pseudogene 1 (PGBD4P1), transmembrane protein 261 (TMEM261), and BDNF, with BDNF and MMP8 further validated by PPI network analysis. MR analysis confirmed a causal association between BDNF levels and MetS risk, reinforcing its role in metabolic dysregulation. Gene Ontology (GO) annotation and pathway enrichment analysis highlighted immune response, morphological changes, and metabolic processes as key biological processes, with pathways such as biological oxidation and defensins significantly enriched.

Significant differences in gene expression are observed between schizophrenia patients with and without MetS. Individual variability in clozapine-induced MetS may be linked to DEGs.

Chronic hepatitis B (CHB) represents a significant global public health challenge. In China, the disease remains prevalent despite recent reductions in incidence. In addition to its impact on physical health, CHB adversely affects patients’ mental health, particularly in the form of anxiety and depression. However, limited research has been conducted on the psychological status of CHB inpatients, especially in metropolitan settings. This study aimed to evaluate the prevalence of anxiety and depression among hospitalized CHB patients in Shenzhen, China, and to investigate factors associated with these mental health conditions.

A cross-sectional study was conducted involving 649 inpatients with chronic hepatitis B at Shenzhen Third People’s Hospital. The Hospital Anxiety and Depression Scale (HADS) was used to assess levels of anxiety and depression. Logistic regression analysis was performed to identify factors associated with mental health outcomes.

The study revealed that 34.05% of patients experienced anxiety, while 71.65% exhibited symptoms of depression. Depression was more prevalent among older patients and those with multiple hospitalizations. Factors such as lack of health insurance and prolonged hospitalizations were significantly associated with depression. Female patients showed a higher propensity for experiencing anxiety.

The high prevalence of anxiety and depression among CHB inpatients highlights the need for integrated mental health screening and intervention strategies within hospital settings. Tailored healthcare approaches are essential to address both the physical and psychological needs of CHB patients, particularly in rapidly urbanizing areas such as Shenzhen.

The objective of this study is to develop an easily applicable scale to measure the course of treatment and the level of recovery for mental problems in various dimensions, which can be used in clinical practice and research.

The validity and reliability test of Moodist Outcome Inventory (MOI) were conducted with 293 participants. Criterion-related validity was investigated by assessment with the Brief Psychiatric Rating Scale (BPRS), Disability Assessment Schedule (WHO-DAS-II), and Psychological Distress Scale (K10-PDS). Factor analysis was investigated by assessment with clinical and non-clinical samples. The sample was followed for six clinical assessments and evaluated by repetitive analysis of Variance (ANOVA) measurement.

The Cronbach’s alpha coefficient of the total scale was noted to be 0.89 in the reliability analysis. In the exploratory factor analysis, the single factor explaining 75.64% of the total variance was attained, and all items were included in this factor. Forty cases completed six clinical assessments, and the change between the MOI scores during the time interval was noted to be statistically significant. The correlation of the MOI scale with the K-10, WHO-DAS-II, and BPRS scales was noted to be 0.62, 0.73, and 0.65, respectively. In six consecutive assessments, the mean scores of all scales dropped significantly. The cut-off point of the scale was recorded as 7.27, and the reliable change index (RCI) was noted as 2.5.

MOI was assessed as a valid and reliable scale for evaluating the course of treatment. The strengths of the scale are that it assesses both symptoms and well-being, is short, and can be implemented in clinical practice.