BackgroundAnxiety disorders and depressive disorders are the most prevalent mental disorders worldwide. Their diagnosis has long relied on clinical symptom assessment, and objective blood−based biomarkers remain lacking. Sex is a critical risk factor for these disorders; however, sex−specific divergence in blood biochemical profiles has yet to be systematically characterized.MethodsThis retrospective study enrolled 778 patients diagnosed with anxiety−depressive state at China−Japan Friendship Hospital. Demographic data, complete blood count parameters, and blood biochemical parameters were collected. Following missing value processing and multiple imputation, Mann–Whitney U tests were applied to identify sex−differentially expressed biomarkers. A random forest classifier was constructed to evaluate the discriminative capacity of combined multi−marker panels, with model performance comprehensively assessed through receiver operating characteristic curve analysis, SHAP−based explainability analysis, and multi−classifier probability projection. Age−stratified analyses were performed with a threshold of 50 years to explore the potential modifying effect of age on sex differences.ResultsSeveral biomarkers exhibiting significant differences between males and females were identified (FDR < 0.05), among which creatinine, hemoglobin, hematocrit, red blood cell count, and uric acid demonstrated the largest effect sizes. The random forest model achieved an area under the receiver operating characteristic curve of 0.902 on the independent test set. Multi−classifier probability projection following hyperparameter tuning yielded a Silhouette coefficient of 0.464 in the two−dimensional space, with permutational multivariate analysis of variance confirming highly significant centroid differences between groups (p < 0.001). Age−stratified analysis using hemoglobin as an example revealed that levels in males were significantly higher than those in females across both age strata, with the magnitude of the sex difference attenuated in the ≥50−year group compared with the <50−year group.ConclusionsRobust sex−related signals are embedded in routine blood biochemical markers. Although complete separation is difficult to achieve under unsupervised dimensionality reduction, these signals can be efficiently integrated through ensemble learning algorithms. This study provides a molecular phenotypic basis related to sex in patients with anxiety−depressive state and underscores the importance of fully considering sex as a variable in clinical laboratory testing.
A comparison between seven scales of neuropsychological assessments for cognitive impairment screening in Chinese older population: a cross-sectional study in Chongqing, China
BackgroundThe Clinical Dementia Rating Scale (CDR), the Ascertain Dementia 8 (AD8), the Mini-Cog, the Verbal Fluency Test (VFT), the Community Screener for Dementia (CSI-D), the Rey Auditory Verbal Learning Test (RAVLT), and the Activities of Daily Living Scale (ADL) represent seven commonly employed methods for community cognitive impairment screening in China that have garnered limited attention. This study aimed to assess the discriminatory power of these seven tests when administered concurrently in a single screening to detect cognitive impairment in the absence of a gold standard.MethodsWe conducted a cross-sectional survey among 1,506 elderly people aged 60 and above in the community. The cognitive and social functions of the elderly population were evaluated by using the Seven scales. The characteristics related to demographics and health were collected through questionnaire surveys, and the correlations and consistencies of the Seven scales with cognitive impairment were analyzed respectively. Multifactor logistic regression model was used to analyze the risk factors of cognitive impairment in each scale.ResultsThe positive screening proportions for the seven scales—CDR, ADL, AD8, CSI-D, Mini-Cog, VFT, and RAVLT—were 61.1%, 33.7%, 38.0%, 37.1%, 53.7%, 39.3%, and 52.9%, respectively. Agreement on cognitive impairment risk between each pair of scales was fair-to-moderate (Kappa: 0.32–0.645, all p < 0.001). Screening results differed significantly across the seven scales by age, educational, marital status, epilepsy, cerebral infarction, brain atrophy, and depression (all P < 0.001). Notably, Screen-positive proportions for cognitive impairment rose significantly with increasing age (p < 0.001); the ≥ 80-year-old group showed the highest proportions across scales. Conversely, higher educational attainment was associated with lower risk of screening positive for cognitive impairment (p < 0.001).ConclusionsOur study identified a relatively high screening positivity proportion for cognitive impairment in Chongqing, Age, Sex, Education, Marital status, Brain atrophy, Anxiety, and Depression are risk factors for screening positivity. The identified screening positivity for cognitive impairment varied across different neuropsychological assessment methods, indicating that assessment choice should be tailored to population characteristics rather than applying a one-size-fits-all approach. Selecting the appropriate tool can improve sensitivity and reduce missed diagnoses.
Changes in depression, anxiety, and post-traumatic stress symptoms among children and adolescents exposed to adverse childhood experiences following participation in the PROACT intervention in Nairobi, Kenya
IntroductionGlobally, children and adolescents exposed to Adverse Childhood Experiences (ACEs) face an increased risk of developing mental health disorders. The prevalence of these mental disorders is further amplified by the lack of access to specialised mental health treatment especially in low resource settings. There is an urgent need for scalable mental health interventions that can effectively address the needs of these vulnerable populations. Non-specialist-delivered interventions, such as PROACT (Psychoeducation, Relaxation, Problem-solving, Activation, and Cognitive Coping Therapy), represent a promising scalable approach that could help bridge the existing mental health treatment gap in low-resource settings.ObjectivesThis study aimed to assess changes in depression, anxiety, and post-traumatic stress symptoms among children and adolescents exposed to adverse childhood experiences following participation in the PROACT intervention delivered by trained social workers in Nairobi, Kenya.MethodologyMixed-methods pre-post study design was employed. Twenty purposively selected sites across Nairobi County each contributed one social worker (N = 20), who received training to deliver the intervention. A total of 40 children participated and received 4–6 PROACT sessions. Quantitative data were analysed using STATA version 17. Paired t-tests were used to compare baseline and endline scores, while mixed-effects linear regression models with participant ID as a random effect were fitted to estimate changes in outcomes over time and account for repeated measures. Statistically significant improvements were observed across all mental health outcomes. Mean anxiety scores decreased from 6.2 at baseline to 2.7 at endline (mean difference: −3.5; 95% CI: −4.7 to −2.2; p < 0.001), while mean depression scores decreased from 6.4 to 2.9 (mean difference: −3.6; 95% CI: −4.9 to −2.3; p < 0.001). Mean PTSD scores decreased from 16.7 (95% CI: 12.8–20.5) at baseline to 7.3 (95% CI: 4.4–10.1) at endline (mean difference: −9.4; 95% CI: −14.6 to −9.3; p < 0.001). Mixed-effects linear regression analyses corroborated these findings, demonstrating significant reductions in PTSD (β = −9.44), anxiety (β = −3.48), and depression (β = −3.59) symptoms (all p < 0.001).ConclusionThe PROACT intervention was feasible and acceptable when delivered by social workers in Nairobi primary healthcare facilities and was associated with improvements in mental health outcomes among children and adolescents. These findings highlight the potential of task-sharing approaches to expand access to mental healthcare in low- and middle-income countries (LMICs) and warrant further evaluation in controlled studies.
Feasibility of a Culturally Adapted Nurse-Led COPE Intervention for Caregivers of Children With Autism Spectrum Disorder
Conditions: Autism Spectrum Disorder; Psychological Distress; Depression; Anxiety
Interventions: Behavioral: Culturally Adapted Nurse-Led COPE Intervention; Other: Routine Hospital Care
Sponsors: Khyber Medical University Peshawar; Children Hospital Faisalabad
Recruiting
Interventions: Behavioral: Culturally Adapted Nurse-Led COPE Intervention; Other: Routine Hospital Care
Sponsors: Khyber Medical University Peshawar; Children Hospital Faisalabad
Recruiting
Child Mind Institute Launches Research Initiative To Inform Safer AI Systems for Youth
New project will develop tools to study youth mental health during AI chatbot use
New York, NY — Today, the Child Mind Institute announced a new research initiative, launched with support from the OpenAI Foundation, to build the research infrastructure needed to measure and better understand youth mental health while using AI chatbots and over time. The effort aims to identify valid markers that can inform the design and testing of safer AI systems.
Millions of children in the United States are struggling with mental health or learning challenges, yet there continues to be a dire shortage of qualified mental health professionals. That, along with stigma and misinformation about mental health, is pushing young people to explore using readily available, often free AI tools for support, including general-purpose chatbots, digital companions, or “therapy bots.”
Novel and emerging digital technologies are shaping mental health faster than the pace of science and the development of evidence-based care can keep up. This new initiative will help advance research studying the impact of these tools and better support youth mental health.
“As the leading nonprofit dedicated to improving youth mental health through science, education, and care, the Child Mind Institute is well positioned to help tackle the key issues affecting the well-being of young people, including technology and the proliferation of AI. It is our belief that with appropriate safeguards and evidence, digital tools may complement care from trained clinicians,” said Harold S. Koplewicz, MD, president and medical director at the Child Mind Institute. “We are excited about filling a gap that currently exists in the research of AI tools and to work toward creating a safer online experience for youth around the globe.”
Using clinical assessments, digital journals, de-identified AI chat histories, real-time behavioral measures, and existing youth mental health datasets, the Child Mind Institute will build an infrastructure to better understand interactions between youth users and AI conversational platforms. With the goal of strengthening our understanding of the mental state in AI chatbot interactions, this initial one-year project will enable the research team to identify and begin scaling the signals needed to meaningfully assess and monitor youth mental health alongside their use of AI tools.
The Child Mind Institute has long been committed to advancing technologies that make mental health research and care more precise, measurable, and connected to real-world settings. Grounded in science and focused on impact, the organization brings together scientific rigor, clinical expertise, and product development experience to build digital tools that accelerate research, improve care, and expand access without compromising safety, quality, or accountability.
“Many of our youth are turning to AI chatbots for important areas of their lives — and mental health is no exception. It is our responsibility to more holistically comprehend the impact of these tools on mental health, both in the long and short term,” said Michael P. Milham, MD, PhD, chief science officer at the Child Mind Institute. “Digital platforms provide an opportunity to rethink the way we conduct mental health research, but they also introduce new challenges and risks. It is critical to better understand the relationship between AI use and youth mental health, and to examine whether, and under what conditions, AI tools can strengthen evidence-based care, support clinician training, and expand access to high-quality mental health services.”
This research initiative is being independently developed and solely executed by the Child Mind Institute. To ensure the safety and security of all study participants, it will be conducted with strong privacy protections, informed consent, ethical oversight, and careful data governance. The project will be co-designed by its principal investigators, Gregory Kiar, PhD, Arno Klein, PhD, and Dr. Milham, who bring expertise in computational methods, digital measurement, clinical science, and youth mental health. Consistent with the Child Mind Institute’s open science philosophy, all data will be shared to help fuel discovery across the field.
About the Child Mind Institute
The Child Mind Institute is an independent nonprofit organization dedicated to transforming the lives of children and families struggling with mental health and learning disorders. Through cutting-edge research, evidence-based clinical care, and public education, the Child Mind Institute builds open science platforms and digital tools to accelerate discovery and improve youth mental health worldwide.
For press questions, contact cmiscience@ssmandl.com or mediaoffice@childmind.org.
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A conceptual multi-agent architecture for mental health triage in post-conflict Arabic-speaking populations: a theoretical proposition and staged validation argument
Syria’s protracted conflict has produced a mental health crisis of extraordinary scale, with post-traumatic stress, depression, and anxiety estimated at several times global baselines, set against fewer than 0.37 psychiatrists per 100,000 people. Existing AI mental health tools have been developed and evaluated primarily for English-speaking, non-humanitarian populations, and their transfer to this setting is constrained by three simultaneous structural deficiencies—extreme clinical scarcity, Arabic natural-language-processing underperformance for dialect, and cultural misalignment with Syrian idioms of distress—which we term the Triple Gap. This article is a conceptual contribution in the Hypothesis and Theory genre, and its central claim is theoretical rather than technical: that AI-assisted mental-health triage at a safety floor adequate for crisis relevant care in this setting is conditional on the joint satisfaction of three constraints—linguistic adequacy for the local dialect, cultural validity for local idioms of distress and help-seeking, and bounded clinical responsibility through human oversight. These constraints interact, so that a system satisfying fewer than all three is expected to fail in clinically consequential rather than random ways. As one possible design response to this proposition—neither the only one nor a validated one—we describe a conceptual multi-agent architecture aligned with the WHO mhGAP task-shifting model: a four-stage pipeline (screening, risk stratification, routing, follow-up) constrained by a cross-cutting cultural-adaptation layer, augmented by candidate verification mechanisms with explicit abstention, and governed by human oversight in which clinical responsibility rests with a licensed clinician. The proposal is a hybrid clinical decision support hypothesis, not an autonomous system. Because no Syrian Arabic clinical corpus yet exists, the conversational components of the design cannot presently be evaluated; we therefore set out a staged sequencing argument for future work in which the construction of a Syrian Arabic Mental Health Evaluation Corpus (SAMHEC) is the first and rate-limiting condition. We present no prototype, no corpus, and no clinical, cultural, or safety evaluation, and we make no claim of clinical validity, safety, or readiness for deployment. The contribution is the integration of multi-agent triage with task-shifting and cultural adaptation into a single conditional argument whose adequacy can be established only through the staged empirical work we describe.
Editorial: Treatment resistant depression: epidemiology, clinic, burden and treatment, volume II
Effects of visual art therapy on depressive symptoms in adults: a systematic review and meta-analysis
ObjectiveTo systematically evaluate the intervention effects of visual art therapy on depressive symptoms in adults, and to examine its impact on anxiety symptoms.MethodsA systematic search was conducted in databases including CNKI, WanFang Data, VIP, Chinese Biomedical Literature Database (CBM), PubMed, Web of Science, Cochrane Library, and Embase from inception to March 2026. Randomized controlled trials were included in which visual art therapy was used to intervene in depressive symptoms among adults (≥18 years).Meta-analysis was performed using Stata 18.0 software.The primary outcome was depressive symptoms, measured by scales such as the BDI, GDS, HADS-D, and SDS, and the secondary outcome was anxiety symptoms, measured by scales such as the BAI, HADS-A, and SAS. Fixed-effect or random-effect models were selected according to the level of heterogeneity, and subgroup analyses were conducted.ResultsA total of 12 randomized controlled trials involving 741 adults were included, with 377 participants in the intervention group and 364 in the control group.The meta-analysis showed that visual art therapy effectively alleviated depressive symptoms (SMD = -0.81, 95% CI: -1.16 to -0.46, P < 0.00001) and anxiety symptoms (SMD = -0.69, 95% CI: -0.90 to -0.48, P < 0.00001) in adults.Subgroup analyses indicated that interventions with a duration of <12 weeks, <12 sessions in total, and a single-session length of ≤60 minutes were associated with larger effect sizes for the improvement of depressive symptoms; improvements in anxiety symptoms were more pronounced in intervention protocols characterized by higher frequency (>12 sessions), shorter overall duration (≤6 weeks), and shorter single-session length (≤60 minutes).ConclusionAs a non-pharmacological intervention, VAT has potential as an adjunctive approach for alleviating depressive and anxiety symptoms in adults.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/view/CRD420261371354, identifier CRD420261371354.
The association between worry, rumination, and metacognitive beliefs in female adolescents with Anorexia Nervosa
BackgroundA growing body of literature has emphasized the role of worry and rumination in eating disorders (EDs). According to the metacognitive model, worry and rumination are maintained by dysfunctional metacognitive beliefs. Although metacognitive beliefs have been investigated in adults with EDs, their role in adolescents with EDs remains underexplored. The present exploratory study aimed to examine the specific association among worry, rumination, and metacognitive beliefs and eating disorder symptomatology in adolescents with AN.MethodsThirty Italian female adolescents (mean age ± SD: 15.387 ± 1.35 years, mean Body Mass Index (BMI): 16.34 ± 2.5 kg/m2) completed a self-report survey composed of the Penn State Worry Questionnaire (PSWQ), the Ruminative Response Scale (RRS), the Metacognitions Questionnaire – 30 (MCQ-30), and the Eating Disorder Inventory – 3 (EDI-3).ResultsThus, Model 1, including RRS and PSWQ, was significant (F = 17.5, p<0.001) and explained 57% of the variance (R² = 0.574). Within this model, RRS was the only significant predictor (p = 0.019) of the Eating Disorder Risk Composite (EDRC) of EDI-3, indicating that higher rumination scores were associated with greater eating disorder symptomatology. Once MCQ was entered as a predictor of EDRC, there was no significant incremental variance compared with Model 2 (ΔR² = 0.0034, p = 0.658), even though the model remained significant overall (F = 11.4, p < 0.001). The final model explained 58% of variance (R² = 0.578; Cohen’s f2 = 1.37).ConclusionRumination was significantly associated with eating disorder symptomatology. Although worry showed strong positive associations with eating disorder symptomatology at the correlational level, it did not maintain an independent role once rumination was included in the regression model. The final model showed a very large effect size (Cohen’s f² = 1.37), suggesting strong associations between predictors and eating disorder symptoms in the present sample. However, this estimate should be interpreted cautiously, given the limited sample size and the exploratory nature of the analysis. Contrary to our expectations, metacognitive beliefs did not significantly explain the variance of eating disorder symptomatology. This finding may reflect the more proximal role of RNT in explaining the variance in eating disorder symptomatology, or alternatively, the possibility that only specific metacognitive domains—rather than overall metacognitive functioning—are relevant in this population.
Clinical Study of Non-invasive 40-Hz Audiovisual Stimulation Guided by Gamma EEG Monitoring for Promoting Perioperative Brain Function Recovery in Children
Conditions: ADHD – Attention Deficit Disorder With Hyperactivity
Interventions: Device: 40-Hz non-invasive synchronized audiovisual stimulation
Sponsors: General Hospital of Ningxia Medical University
Not yet recruiting
Interventions: Device: 40-Hz non-invasive synchronized audiovisual stimulation
Sponsors: General Hospital of Ningxia Medical University
Not yet recruiting