A Digital Acceptance and Commitment Therapy and Education Intervention for Caregivers of Very Preterm Infants in the Neonatal Intensive Care Unit: Randomized Controlled Trial

Background: Parents of very preterm infants admitted to the neonatal intensive care unit (NICU) experience high levels of psychological distress, yet access to timely, evidence-based mental health support is limited by staffing and resource constraints. Digital mental health interventions offer a scalable approach to addressing this gap; however, their effectiveness has not been well established in NICU caregiver populations, particularly during periods of acute stress. Objective: This study aims to evaluate the effectiveness of a self-guided digital acceptance and commitment therapy (ACT)–based intervention combined with NICU-specific education (NICU parent acceptance and commitment therapy [NPACT]). The study explored the intervention’s effects on stress among parents and primary caregivers of very preterm infants, compared to a digital education-only intervention, and active control. Methods: We conducted a 3-arm, single-center, randomized controlled cluster trial in a tertiary NICU. Parents and primary caregivers of very preterm infants (<32 wk’ gestational age,<1 wk old) were randomized by family cluster to (1) NPACT (ACT+ education), (2) a digital education-only intervention, or (3) active control. Digital interventions were delivered via a web-based platform over 2 weeks. The primary outcome was NICU-related stress on the Parent Stressor Scale: Neonatal Intensive Care Unit (PSS:NICU) at 2 weeks postrandomization. Secondary outcomes included caregiver anxiety, depression, perceived stress, and selected neonatal outcomes. Engagement and perceived helpfulness were assessed for digital interventions. Results: A total of 102 caregivers from 68 family clusters (79 infants; mean gestational age 28.1, SD 2.2 wk) were enrolled. There were no statistically significant between-group differences in the mean PSS:NICU scores at 2 weeks (NPACT 3.0, SD 0.9; education-only 2.5, SD 1; active control 2.6, SD 0.9; adjusted mean difference for NPACT vs active control 0.04, 95% CI −0.39 to 0.47). No between-group differences were observed for secondary psychological outcomes at any time point. However, caregivers in both digital intervention groups had higher odds of full breastfeeding at discharge compared with active control. Engagement with the digital interventions was high, with 97% (28/29) of NPACT participants and 76% (19/25) of education-only participants completing at least 5 of 7 modules, and both interventions were rated as very helpful. Conclusions: In this trial, an unguided digital mental health intervention delivered during NICU admission did not reduce NICU-specific parental stress or other psychological outcomes relative to active control. However, the intervention was highly used by caregivers. These findings suggest that while a brief digital mental health intervention can be successfully implemented in a high-stress clinical setting with caregivers, its capacity to reduce acute psychological distress may be limited. Secondary findings indicate potential benefits of the digital intervention on breastfeeding, generating hypotheses for future research. Digital mental health interventions in neonatal settings may be most effective when integrated within hybrid models of care and/or delivered beyond the acute admission phase. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12623000641695; https://tinyurl.com/2e8677bb International Registered Report Identifier (IRRID): RR2-10.1016/j.cct.2024.107519

Autism-Like Traits in Mice Improved After Single Rapamycin Dose

The results of a preclinical study led by UCLA Health researchers suggest that inflammation during pregnancy in mice can trigger autism-like brain and behavior changes in offspring, and that the effects may be rapidly but temporarily reversible in adulthood with a short-term dose of the immunosuppressive drug rapamycin.

The study showed that a single dose of rapamycin rapidly improved changes including brain overactivity, seizure risk, sensory sensitivity, repetitive behaviors, and abnormal brain functional network organization. Rapamycin itself is not considered a viable candidate for human therapy, as the effects of the drug were found to be temporary, with repeated dosing losing efficacy, and repeated use also having the potential for toxicity. However, the researchers said the study findings indicate that some autism-related brain changes may still be treatable in adulthood, and point to possible therapeutic approaches that target the underlying pathway rather than only symptoms.

“These results reframe how autism-associated symptoms might be treated,” said Janel Le Belle, PhD, an associate professor in the UCLA Department of Neurosurgery. “If the adult brain remains capable of functional normalization, then some features of autism may be successfully addressed without needing to correct underlying structural differences.” Le Belle is first author of the researchers’ published paper in Nature Communications, titled “Acute rapamycin treatment reveals distinct mechanisms of dysfunction in a maternal inflammation mouse model.”

Neurodevelopmental disorders result from the disruption of brain development in utero or in early life, with genetic, environmental, epigenetic, and immunological factors all potential contributors to complex pathogenesis, the authors wrote. Previous studies have shown that offspring of mothers who experience inflammation while pregnant have a higher likelihood of developing autism-associated traits such as repetitive behaviors and difficulty with social interaction, as well as brain overgrowth and disrupted sensory processing that continue into adulthood. “Maternal inflammatory response (MIR) during early mouse gestation induces a cascade of physiological and behavioral changes associated with autism spectrum disorder (ASD),” they stated.

Rapamycin has been shown in previous mouse autism studies to improve symptoms by suppressing an overactive mTOR pathway that signals cell growth and proliferation. What has been less clear is whether these brain changes could still be modifiable in adulthood, and whether rapamycin’s benefits came from long-term structural repair or faster functional changes. “We wanted to understand the mechanisms that underlie the effects of adult mTOR inhibition, where treatment isn’t aimed at preventing or reversing structural brain abnormalities,” the team stated.

For their newly reported study the scientists exposed pregnant mice to a mild inflammatory trigger early in gestation at a dose that was too low to make the mothers significantly ill. The resulting offspring went on to develop chronic brain and body-wide inflammation, mild brain overgrowth, overactive cell-signaling in the mTOR pathway, disorganized brain functional network connectivity and behaviors associated with autism.

When researchers gave adult offspring a single dose of rapamycin they found rapid improvement across nearly every measure. Neurons that had been firing abnormally calmed down, susceptibility to seizures dropped, brain regions that had been miscommunicating reorganized into more typical patterns and repetitive behaviors and sensory over-responsivity eased. These changes occurred within roughly two hours of drug administration, which was too rapid to be explained by the kind of physical rewiring of brain synapses that typically takes longer.

“The level of functional normalization achieved over this short time suggests new mechanisms by which possible treatments may act,” said the study’s senior author Harley Kornblum, MD, PhD, director of the UCLA Intellectual and Developmental Disabilities Research Center in the Semel Institute for Neuroscience and Human Behavior. “It suggests the adult brain may be more adaptable than we assumed, even when the underlying structural changes from early development are still there. This points us toward the brain’s functional circuitry, not just its physical structure, as a target for future treatment approaches.”

To understand the mechanisms of rapid rapamycin effects, researchers examined gene activity in brain cells before and after treatment. They found that rapamycin reversed abnormal expression of genes tied to autism, epilepsy and ion channel function, particularly in excitatory neurons, suggesting the drug works by quickly rebalancing brain cell excitability rather than by repairing structural brain differences.

The findings suggest that mTOR pathway activity, brain network organization and neuronal excitation levels as potential targets for future therapies aimed at specific autism symptoms such as sensory over-responsivity, a common but difficult-to-treat symptom of autism. “Our findings demonstrate that mTOR dysregulation drives dysfunctional brain development in MIR offspring but the adult brain remains amenable to rapid functional normalization, rescuing core and comorbid ASD associated brain and behavior phenotypes,” the authors stated.

Co-senior author and professor in the UCLA Department of Neurosurgery, Neil Harris, PhD, cautioned that the results showed the treatment effects to be temporary and that daily dosing produced tolerance over several weeks. This, along with rapamycin’s high potential for toxicity and the fact that these studies were performed in mice, makes it unsuitable for broad use in humans. “This points toward new therapeutic targets like sensory circuit neuromodulation or balancing neuronal inhibition and excitation, rather than toward rapamycin itself as a treatment,” Harris said. As the authors further commented in their paper, “Restoring excitatory/inhibitory imbalance and sensory functional network modularity may be important targets for therapeutically addressing multiple ASD phenotypes.”

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Art therapy for depression: a systematic review and meta-analysis

IntroductionDepression is among the leading causes of disability globally. Therefore, exploring the various non-medical treatment options for this condition is particularly important. The aim of the review was to assess the effect of art therapy on depressive symptoms.MethodsThe foundation of this review is a pre-planned, explorative, secondary analysis of a previously published umbrella review, encompassing the databases Cochrane Library, Embase, MEDLINE, CINAHL, ERIC, American Psychological Association PsycArticles, American Psychological Association PsycInfo, PSYNDEX, the German Clinical Trials Register, and ClinicalTrials.gov. Included were all randomized trials with any patient population receiving active visual art therapy. The outcome was depressive symptoms measured by depression assessment instruments. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and conducted a bias assessment using a modified Cochrane risk of bias tool. Data was pooled using a random-effects model and visualized in forest plots. A pooled standardized mean difference (SMD) with hedges g was calculated to measure the reduction of depressive symptoms.ResultsOf 3,100 identified reports we included 26 studies. Of these, 19 studies with 997 patients were eligible for inclusion in the meta-analysis. Overall, we found a standardized mean difference of 0.53 (95% CI: 0.30 to 0.76) for depressive symptoms, favoring the intervention group. Main sources of variation were different types of control groups, methodological quality, and patient populations.ConclusionOur results suggest that art therapy is associated with improved depressive symptoms. Therefore, art therapy should be accessible as complementary treatment for patients suffering from depressive symptoms.

Sex-related molecular phenotypes in anxiety-depressive disorders: a machine learning analysis of routine blood biomarkers

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.

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.