Young Adults’ Perspectives on an Ecological Momentary Intervention for Drinking to Cope: Qualitative Study

<strong>Background:</strong> Young adults have high rates of mental health problems, such as mood or anxiety symptoms, and high rates of problematic drinking. Many young adults who undergo psychiatric hospitalization to address depression and anxiety symptoms also engage in risky drinking and tend to drink to cope with negative emotions. However, in many cases, treatment programs focusing on mood and anxiety symptoms often fail to adequately address problematic alcohol use in young adults. <strong>Objective:</strong> This study aimed to address this treatment gap by investigating patient perspectives on a potential ecological momentary intervention mobile app. Researchers used qualitative methods to gather perspectives of young adults hospitalized for psychiatric care on their use of drinking to cope with negative emotions and their feedback for a prospective app designed to suggest healthy coping strategies when participants report low mood and cravings to drink. <strong>Methods:</strong> We recruited a total of 12 young adults admitted to a partial hospitalization program to participate in a qualitative interview. To be eligible, participants needed to be aged 18-25 years and report drinking at least once weekly, binge drinking at least once monthly, drinking to cope with negative emotions, and depression and/or anxiety symptoms. <strong>Results:</strong> Qualitative analysis of our data resulted in 4 major themes. These included (1) motivations to use substances, (2) healthy coping, (3) general reactions to the proposed app, and (4) suggestions for the app. Participants generally had insight about their use of alcohol to cope and were able to identify several motivations for drinking; the most frequent motivations were to alleviate anxiety and depression, although many participants noted drinking to cope with other emotions, such as guilt or loneliness. Participants overall had positive responses to the prospective intervention and reported that they would appreciate the portability of a digital intervention in helping them “step down” from higher levels of psychiatric care. Participants also made several valuable suggestions about content, features, and usability, such as suggesting ways to “gamify” the app to increase use. <strong>Conclusions:</strong> This feedback will be crucial in designing and testing an ecological momentary intervention designed to reduce drinking to cope in young adults hospitalized for psychiatric care.

Mental Illness Shows Context-Specific Genetic Effects

Many DNA variants linked with neuropsychiatric disorders (NPD) that do not code for proteins depend on neuronal activation, a study suggests.

The findings, in Science, highlight the power of cell stimulation to reveal context-specific “hidden” genetic effects in conditions such as schizophrenia.

They suggest that genetic regulation is not fully revealed by measuring gene expression alone.

Instead, gene activity—at least in the brain—may depend on context and the physiological state of neurons.

“Liang et al. demonstrate that the genetic processes that underlie neuropsychiatric disease are heavily determined by a dynamic physiological environment rather than by fixed cellular conditions,” said Biao Zheng, PhD, and Panos Roussos, PhD, from Icahn School of Medicine at Mount Sinai in New York, in a Perspective article accompanying the study.

They added: “To understand disease genetics, we might need to study the genome in motion and not at rest.”

Genome-wide association studies have revealed hundreds of genetic loci associated with mental illness, with more than 280 identified for schizophrenia alone.

But many of these DNA regions do not encode proteins and their impact is often subtle and difficult to detect.

To investigate further, Lifan Liang, PhD, from the University of Chicago, and co-workers studied gene expression and chromatin accessibility in single neurons derived from induced pluripotent stem cells collected from a hundred human donors.

The single-cell multi-omics study involved assessing transcriptional and epigenomic profiles before and after neurons were activated through potassium-induced depolarization.

The team found that much of the activity in regulatory DNA regions only became apparent with neuronal stimulation.

Both the number of detectable expression quantitative trait loci (eQTLs)—genetic variants associated with differences in gene expression—and chromatin accessibility QTLs (caQTLs)—DNA variants associated with differences in chromatin accessibility—rose after neuronal stimulation.

Shared and cell type-specific transcription factors worked together, possibly through regulatory cascades, to drive cell type-specific neuronal responses to stimuli.

eQTLs after stimulation had substantially weaker overlap with brain eQTL catalogs derived from postmortem tissue compared with eQTLs before stimulation.

This suggested that many relationships between regulatory DNA activity and gene expression become detectable only during neuronal activation and could be missed by traditional tissue-based studies.

A higher number of caQTLs were associated with neuropsychiatric disease compared with eQTLs, suggesting that disease-associated genetic variants could have detectable effects on regulatory DNA even when downstream changes in gene expression were not obvious.

Supporting this, chromatin accessibility and transcriptional responses to neuronal activation often occurred at different times.

Regulatory regions associated with genes that respond rapidly to neuronal stimulation often remained accessible after transcription subsided. By contrast, some late response genes exhibited accessible chromatin before their expression was induced.

When taken together, these observations implied that chromatin accessibility can be an indication of both prior and future transcriptional potential.

“We identified thousands of cell type–specific and activity-dependent quantitative trait loci for gene expression (eQTLs) and chromatin accessibility (caQTLs), helping prioritize NPD risk variants and genes that manifested functional effects only upon neuronal stimulation,” the researchers asserted.

They added: “Our work provides mechanistic insights on neuron subtype–specific activity-dependent gene regulation, substantially expanding the repertoire of context-specific causal variants and genes for NPD and other brain traits.”

The post Mental Illness Shows Context-Specific Genetic Effects appeared first on Inside Precision Medicine.

Angry Kids: Dealing With Explosive Behavior

When a child — even a small child — melts down and becomes aggressive, they can pose a serious risk to themselves and others, including parents and siblings.

It’s not uncommon for kids who have trouble handling their emotions to lose control and direct their distress at a caregiver — screaming and cursing, throwing dangerous objects, or hitting and biting. It can be a scary, stressful experience for you and your child, too. Children often feel sorry after they’ve worn themselves out and calmed down.

So what are you to do?

It’s helpful to first understand that behavior is communication. A child who is so overwhelmed that they are lashing out is a distressed child. They don’t have the skill to manage their feelings and express them in a more mature way. They may lack language, impulse control, or problem-solving abilities.

Sometimes parents see this kind of explosive behavior as manipulative. But kids who lash out are usually unable to handle frustration or anger in a more effective way — say, by talking and figuring out how to achieve what they want.

Nonetheless, how you react when a child lashes out has an effect on whether they will continue to respond to distress in the same way or learn better ways to handle feelings so they don’t become overwhelming.

Behavioral techniques for anger management

Here are some pointers to help kids learn techniques to regulate their emotions:

  • Stay calm. Faced with a raging child, it’s easy to feel out of control and find yourself yelling at them. But when you shout, you have less chance of reaching them. Instead, you will only be making them more aggressive and defiant. As hard as it may be, if you can stay calm and in control of your own emotions, you can be a model for your child and teach them to do the same thing.
  • Don’t give in. Don’t encourage them to continue this behavior by agreeing to what they want in order to make it stop.
  • Praise appropriate behavior. When they have calmed down, praise them for pulling themselves together. And when they do try to express their feelings verbally, calmly, or try to find a compromise on an area of disagreement, praise them for those efforts.
  • Help them practice problem-solving skills. When your child is not upset is the time to help them try out communicating their feelings and coming up with solutions to conflicts before they escalate into aggressive outbursts. You can ask them how they feel and how they think you might solve a problem.
  • Time-outs and reward systems. Time-outs for nonviolent misbehavior can work well with children younger than 7 or 8 years old. When using time-outs, be sure to be consistent with them and balance them with other, more positive forms of attention. If a child is too old for time-outs, you want to move to a system of positive reinforcement for appropriate behavior — points or tokens toward something they want.
  • Avoid triggers. Vasco Lopes, PsyD, a clinical psychologist, says most kids who have frequent meltdowns do it at very predictable times, like homework time, bedtime, or when it’s time to stop playing, whether it’s Legos or video games. The trigger is usually being asked to do something they don’t like, or to stop doing something they do like. Time warnings (“we’re going in 10 minutes”), breaking tasks down into one-step directions (“first, put on your shoes”), and preparing your child for situations (“please ask to be excused before you leave Grandma’s table”) can all help avoid meltdowns.

What kind of tantrum is it?

How you respond to a tantrum also depends on its severity. The first rule in handling nonviolent tantrums is to ignore them as often as possible, since even negative attention, like telling the child to stop, can be encouraging.

But when a child is getting physical, ignoring is not recommended since it can result in harm to others as well as your child. In this situation, Dr. Lopes advises putting the child in a safe environment that does not give them access to you or any other potential rewards.

Critics of time-outs argue that they can be emotionally isolating for kids, but research shows that they are effective and do not cause children harm. (For more on the debate around time-outs, read our full article on the topic.) However, it’s very important to use them as just one technique in a nurturing, supportive parenting strategy. Be sure to balance use of time outs with lots of praise for kids’ positive behaviors. It’s also important to manage your own stress so that kids can learn how to regulate their emotions from your positive example.

If the child is young (usually 7 or younger), try placing them in a time out chair. If they won’t stay in the chair, take them to a backup area where they can calm down on their own without anyone else in the room. Again, for this approach to work there shouldn’t be any toys or games in the area that might make it rewarding.

Your child should stay in that room for one minute and must be calm before they are allowed out. Then they should come back to the chair for time out. “What this does is gives your child an immediate and consistent consequence for their aggression and it removes all access to reinforcing things in their environment,” explains Dr. Lopes.

If you have an older child who is being aggressive and you aren’t able to carry them into an isolated area to calm down, Dr. Lopes advises removing yourself from their vicinity. This ensures that they are not getting any attention or reinforcement from you and keeps you safe. In extreme instances, it may be necessary to call 911 to ensure your and your child’s safety.

Help with behavioral techniques

If your child is doing a lot of lashing out — enough that it is frequently frightening you and disrupting your family — it’s important to get some professional help. There are good behavioral therapies that can help you and your child get past the aggression, relieve your stress, and improve your relationship. You can learn techniques for managing their behavior more effectively, and they can learn to rein in disruptive behavior and enjoy a much more positive relationship with you.

  • Parent-child interaction therapy (PCIT). PCIT has been shown to be very helpful for children between the ages of 2 and 7. The parent and child work together through a set of exercises while a therapist coaches parents through an ear piece. You learn how to pay more attention to your child’s positive behavior, ignore minor misbehaviors, and provide consistent consequences for negative and aggressive behavior, all while remaining calm.
  • Parent management training (PMT). PMT teaches similar techniques as PCIT, though the therapist usually works with parents, not the child.
  • Collaborative and Proactive Solutions (CPS). CPS is a program based on the idea that explosive or disruptive behavior is the result of lagging skills rather than, say, an attempt to get attention or test limits. The idea is to teach children the skills they lack to respond to a situation in a more effective way than throwing a tantrum.

Figuring out explosive behavior

Tantrums and meltdowns are especially concerning when they occur more often, more intensely, or past the age in which they’re developmentally expected — those terrible twos up through preschool. As a child gets older, aggression becomes more and more dangerous to you, and the child. And it can become a big problem for them at school and with friends, too.

If your child has a pattern of lashing out it may be because of an underlying problem that needs treatment. Some possible reasons for aggressive behavior include:

  • ADHD: Kids with ADHD are frustrated easily, especially in certain situations, such as when they’re supposed to do homework or go to bed.
  • Anxiety: An anxious child may keep their worries secret, then lash out when the demands at school or at home put pressure on them that they can’t handle. Often, a child who “keeps it together” at school loses it with one or both parents.
  • Undiagnosed learning disability: When your child acts out repeatedly in school or during homework time, it could be because the work is very hard for them.
  • Sensory processing issues: Some children have trouble processing the information they are taking in through their senses. Things like too much noise, crowds and even “scratchy” clothes can make them anxious, uncomfortable, or overwhelmed. That can lead to actions that leave you mystified, including aggression.
  • Autism: Children with autism spectrum disorder are often prone to meltdowns when they are frustrated or faced with unexpected change. They also often have sensory issues that make them anxious and agitated.

Given that there are so many possible causes for emotional outbursts and aggression, an accurate diagnosis is key to getting the help you need. You may want to start with your pediatrician. They can rule out medical causes and then refer you to a specialist. A trained, experienced child psychologist or psychiatrist can help determine what, if any, underlying issues are present.

When behavioral plans aren’t enough

Professionals agree, the younger you can treat a child, the better. But what about older children and even younger kids who are so dangerous to themselves and others that behavioral techniques aren’t enough to keep them and others around them safe?

  • Medication. Medication for underlying conditions such as ADHD and anxiety may make your child more reachable and teachable. Kids with extreme behavior problems are often treated with antipsychotic medications like Risperdal or Abilify. But these medications should be partnered with behavioral techniques.
  • Holds. Parent training may, in fact, include learning how to use safe holds on your child so that you can keep both them and yourself out of harm’s way.
  • Residential settings. Children with extreme behaviors may need to spend time in a residential treatment facility — sometimes, but not always, in a hospital setting. There, they receive behavioral and, most likely, pharmaceutical treatment. Therapeutic boarding schools provide consistency and structure around the clock, seven days a week. The goal is for the child to internalize self-control so they can come back home with more appropriate behavior with you and the world at large.
  • Day treatment. With day treatment, a child with extreme behavioral problems lives at home but attends a school with a strict behavioral plan. Such schools should have trained staff prepared to safely handle crisis situations.

Explosive children need calm, confident parents

It can be challenging work for parents to learn how to handle an aggressive child with behavioral approaches, but for many kids it can make a big difference. Parents who are confident, calm, and consistent can be very successful in helping children develop the anger management skills they need to regulate their own behavior.

This may require more patience and willingness to try different techniques than you might with a typically developing child, but when the result is a better relationship and happier home, it’s well worth the effort.

Frequently Asked Questions

How can you deal with children’s anger?

One way to handle a child’s anger is to stay calm when they lose their temper. Controlling your emotions sets an example for the child. You can praise them when they express their feelings calmly and when they calm themselves down after an explosion. Adults who are confident, calm, and consistent help children develop the skills to regulate their behavior.

How do I teach a child to control their anger?

In parent-child interaction therapy, a therapist coaches parents on how to pay more attention to positive behavior, ignore minor misbehaviors, and provide consistent consequences for negative and aggressive behavior, all while remaining calm. Other forms of therapy also center on teaching the parent how to model emotional stability.

How can I calm a child down when angry?

Stay calm and ensure they are in a safe space. Yelling can escalate aggression. Speak in a steady voice, avoid giving in, and use time-outs to prevent meltdowns. When they calm down, praise them for it and for expressing their emotions appropriately. If they are frequently aggressive, behavioral therapy may help.

How do I help a child with anger issues?

Children who lash out often lack the skills to manage emotions. Identifying triggers, teaching problem-solving, and using praise or rewards can encourage better behavior. Time-outs work for younger kids, while older ones may need structured reinforcement. If outbursts are severe, you might need professional help. Programs like parent-child interaction therapy (PCIT), parent management training (PMT), or collaborative and practical solutions (CPS) can help.

The post Angry Kids: Dealing With Explosive Behavior appeared first on Child Mind Institute.

Associations between childhood trauma, intolerance of uncertainty, and symptom severity in obsessive-compulsive disorder

BackgroundChildhood trauma (CT) has been associated with obsessive-compulsive disorder (OCD), but its relationship with obsessive-compulsive symptom (OCS) severity remains inconsistent. Intolerance of uncertainty (IU) may represent one of the cognitive processes underlying this association. The present study aimed to examine differences in CT and IU between patients with OCD and healthy controls (HCs), and to test whether IU mediates the relationship between CT and OCS severity.MethodsThis study included 82 patients with OCD and 82 healthy controls (HCs) matched on age and sex. CT was assessed using the Childhood Trauma Questionnaire-33 (CTQ-33), IU using the Intolerance of Uncertainty Scale–Short Form (IUS-12), and OCS severity using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS).ResultsPatients with OCD had significantly higher scores than HCs on all CTQ-33 subscales and on IU measures. In particular, the patient group showed higher IUS-12 total scores than the HC group (39.30 ± 10.42 vs. 32.11 ± 8.62, p < 0.001), with higher prospective anxiety (22.11 ± 5.13 vs. 20.11 ± 4.59, p = 0.009) and inhibitory anxiety scores (17.19 ± 5.99 vs. 12.00 ± 4.82, p < 0.001). Within the patient group, physical abuse was the only CT dimension significantly associated with total Y-BOCS scores (r = 0.248, p = 0.025), whereas IU was positively associated with symptom severity (IUS-12 total: r = 0.346, p = 0.001). Path analysis showed that CT was associated with IU (β = 0.238, p = 0.023), IU was associated with OCS severity (β = 0.329, p = 0.007), and the direct effect of CT on OCS severity was no longer significant after IU was included in the model (c′ = 0.209, p = 0.093), supporting partial mediation.ConclusionCT appears to be elevated in patients with OCD, although its association with symptom severity is not uniform across trauma dimensions. IU may represent an important cognitive mechanism linking CT to OCS severity. These findings suggest that assessing and addressing IU may contribute to more individualized clinical approaches in OCD.

Coproduction Without Youth? Closing the Participation Gap in Digital Mental Health Research

Young people are among the most intensive users of digital and generative artificial intelligence (GenAI)–enabled mental health tools, yet they remain underrepresented in the research and design processes that shape these technologies. Although participatory approaches such as co-design and patient and public involvement are widely endorsed as best practices, youth involvement in digital youth mental health (DYMH) research is often inconsistent, superficial, or limited to late-stage consultation. This participation gap risks producing interventions that are misaligned with young people’s lived experiences, priorities, and vulnerabilities, particularly in the context of rapidly evolving and scalable GenAI systems. This Viewpoint aims to reexamine the underlying drivers of the participation gap in DYMH research; clarify how participation is conceptualized and implemented across disciplines; and propose concrete, actionable recommendations to support more meaningful and consistent youth involvement across the research life cycle. We draw on interdisciplinary literature from digital mental health, human-computer interaction, child-computer interaction, and health research policy. Our Viewpoint integrates conceptual frameworks (eg, Lundy’s model of participation), existing reviews of co-design practices, and emerging evidence on GenAI in mental health. We adopt a life cycle–oriented perspective to examine how youth participation is distributed across stages of research and development, including problem formulation, design, implementation, and evaluation. We identify 3 interrelated drivers of the participation gap. First, conceptual and linguistic fragmentation obscures what participation entails in practice, with terms such as co-design, participatory design, user-centered design, and patient and public involvement used inconsistently across disciplines. Second, youth involvement is uneven across the research life cycle, with participation often concentrated in early ideation or usability testing but largely absent from upstream decision-making and downstream evaluation. Third, institutional barriers—including ethics review processes, consent requirements, funding constraints, and adult-centric research norms—systematically limit meaningful youth partnership. These challenges are amplified in the context of GenAI, where opaque “black box” systems, simulated therapeutic interactions, and rapid deployment cycles introduce distinct risks if youth perspectives are not integrated. We propose a set of minimum expectations to address these gaps, including explicit specification of participatory models, life cycle mapping of youth involvement, reporting of youth influence on decisions, dedicated funding for participation, proportional ethics frameworks, and mechanisms for youth-informed governance of GenAI systems. Closing the participation gap in DYMH research is both an ethical imperative and a practical necessity. Moving beyond aspirational commitments requires embedding youth participation as a standard, resourced, and accountable component of research, design, and governance. In the context of rapidly evolving digital and GenAI technologies, failure to do so risks producing interventions that are scalable but not safe, credible, or responsive to the needs of young people.
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Supporting Student Mental Health With the Safespace Generative AI Chatbot: Mixed Methods Feasibility Study

Background: Generative artificial intelligence (GenAI) chatbots have the potential to provide personalized mental health support to individuals at scale. Objective: This study evaluates the feasibility and usage patterns of the Safespace GenAI chatbot, an artificial intelligence (AI)–driven smartphone app that offers a large language model–powered interactive chatbot to support mental health. Methods: Using a mixed methods approach, we explored baseline attitudes toward GenAI chatbots and chatbot usage patterns, conducted a qualitative content analysis of participants’ experiences, and descriptively assessed patterns related to preintervention depressive symptoms. The study included an initial sample of 42 university students, 20 of whom actively used the chatbot over 2 to 4 weeks, generating 286 user-chatbot interactions. Results: Preintervention surveys indicated that the majority of participants anticipated that the chatbot would be helpful (27/42, 64%) and that they trusted its privacy safeguards (39/42, 93%). Usage patterns suggested that the highest levels of interaction occurred early in the morning and late at night, when peer and professional support may be inaccessible. The qualitative analysis indicated that participants appreciated using the chatbot for reflection as a blended-care tool between their counseling sessions, while also naming technical barriers and specific design needs required to sustain engagement. In addition, our exploratory analyses descriptively showed that participants with elevated depression scores engaged in emotional disclosure during 99% (38 sessions with 8 participants) of their sessions, compared to 84% (26 sessions of 12 participants) of those with low symptoms. Due to the small sample size, future adequately powered studies are needed to inferentially examine these observed patterns. Conclusions: These findings provide initial insights into the usage and engagement dynamics of the Safespace GenAI chatbot and highlight directions for future research to optimize GenAI-driven mental health interventions. Trial Registration: AEA Registry AEARCTR-0013291; https://doi.org/10.1257/rct.13291-1.0
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Global research landscape, knowledge structure, and emerging trends in adverse childhood experiences and personality disorders: a bibliometric analysis

BackgroundThe relationship between adverse childhood experiences (ACEs) and personality disorders (PDs) has attracted sustained attention in psychiatry, psychology, and public health. Existing studies have mainly examined epidemiological associations, specific PDs diagnoses, or mechanisms, whereas bibliometric evidence mapping the field’s knowledge structure and thematic evolution remains limited. This study aimed to characterize trends, contributors, collaboration networks, core themes, and frontiers in ACEs–PDs research.MethodsEnglish-language publications on ACEs and PDs were retrieved from Web of Science Core Collection, Scopus, and PubMed from inception to December 31, 2025. After year screening, document-type filtering, and deduplication, 5,084 records were included. Bibliometric analyses were performed using R, VOSviewer, and CiteSpace. The merged dataset was used to examine annual trends, countries/regions, institutions, authors, journals, and keyword co-occurrence, while WoSCC records were used for co-citation analysis, keyword clustering, and burst detection.ResultsACEs–PDs research showed sustained growth, with a marked increase after 2000. The United States occupied a central position in publication output, citation impact, and international collaboration, while the United Kingdom, Germany, Canada, the Netherlands, and Australia also showed strong influence. Harvard University, the University of London, and Ruprecht Karls University Heidelberg were leading institutions; Zanarini M, Fonagy P, Schmahl C, Paris J, and Kleindienst N were key contributors. Influential journals mainly covered psychiatry, personality disorders, child maltreatment, trauma, and developmental psychopathology. Keyword analyses identified childhood adversity, personality disorder, borderline personality disorder, depression, childhood sexual abuse, and post-traumatic stress disorder as core themes. VOSviewer and CiteSpace analyses indicated that hotspots have expanded from childhood abuse, PDs diagnosis, and psychiatric comorbidity to emotion dysregulation, non-suicidal self-injury, social support, functional connectivity, early intervention, and mechanism validation. Highly cited publications revealed a knowledge base centered on childhood abuse/trauma, borderline personality disorder, psychiatric comorbidity, emotion regulation, and neurobiological mechanisms.ConclusionThis study maps development and knowledge structure of ACEs–PDs research. Findings suggest a shift from exposure–outcome association studies toward comorbidity, intermediate phenotypes, neurobiological mechanisms, and clinical translation. Future research should strengthen longitudinal and cross-cultural designs, consider ACE type, timing, duration, and severity, and integrate neuroimaging, inflammatory, epigenetic, and clinical-course phenotypes.

Shared reading is associated with fewer emotional/behavioral problems and better prosocial behavior in preschool children: a cross-sectional study in western China

BackgroundThe home literacy environment, particularly shared reading, plays a critical role in preschool children’s cognitive and socioemotional development. However, its associations with emotional and behavioral problems remain underexplored in large-scale studies. This study examined the relationship between shared reading and emotional/behavioral problems as well as prosocial behavior in preschool children.MethodsA cross-sectional study was conducted using stratified cluster sampling across 189 kindergartens in a major city in western China. A total of 21,366 parent-child pairs were included. Shared reading was assessed with the reading subscale of the StimQ-P (score range 0–22), which evaluates quantity, diversity of concepts and content, and interactivity quality. Emotional and behavioral problems were measured using the parent-reported Strengths and Difficulties Questionnaire (SDQ). Multivariate logistic regression and generalized additive models were employed to examine associations, adjusting for child age, gender, parental socioeconomic factors, lifestyle variables, and parental mental health (CES-D).ResultsHigher shared reading scores were significantly associated with lower odds of emotional/behavioral problems (adjusted OR = 0.96 per point increase, 95% CI: 0.95–0.97, P < 0.0001) and higher odds of adequate prosocial behavior (adjusted OR = 1.09, 95% CI: 1.08–1.10, P < 0.0001) in fully adjusted models. All four dimensions of shared reading showed independent associations. Nonlinear analyses revealed threshold effects, with associations becoming stronger above approximately 18 points for total difficulties and 15 points for prosocial behavior. These associations were largely consistent across subgroups after correction for multiple testing.ConclusionIn this large cross-sectional study conducted in western China, higher levels of shared reading were associated with lower odds of emotional/behavioral problems and higher odds of prosocial behaviors among preschool children. The results suggest possible threshold patterns in these associations. However, given the cross-sectional nature of the study, causality cannot be established.

Dynamic changes of gut microbiota during progression of three Alzheimer’s disease mice models

IntroductionAlzheimer’s disease (AD) is an age-related and progressive neurodegenerative disorder characterized by cognitive impairment and irreversible neuronal degeneration, affecting approximately 55 million individuals worldwide. Despite extensive research efforts, the underlying pathogenic mechanisms of AD remain incompletely understood, and effective therapeutic strategies for preventing or delaying disease progression are still lacking. Increasing evidence suggests that the microbiota-gut-brain axis plays an important role in neurodegenerative diseases, including AD. However, the dynamic alterations of gut microbiota during AD progression across different transgenic mouse models remain poorly characterized.MethodsIn the present study, we investigated age-dependent changes in gut microbiota composition in three commonly used AD mouse models, including APP/PS1, 3xTg, and 5xFAD mice, using 16S rRNA gene sequencing. Fecal samples were collected longitudinally at 2, 4, 6, and 8 months of age to evaluate microbial diversity, community structure, and differential bacterial taxa during aging and disease progression.ResultsOur results demonstrated distinct and model-dependent alterations in gut microbiota composition across different stages of AD progression. Significant changes in microbial diversity and bacterial community structure were observed among the three AD mouse models and wild-type controls. In particular, dynamic alterations in Verrucomicrobiota, Proteobacteria, and Actinobacteriota were consistently identified during aging in AD mice. In addition, β-diversity, Linear discriminant analysis effect size (LEfSe), and correlation network analyses further revealed differential microbial signatures associated with different AD mouse models and age stages.DiscussionOverall, our findings provide additional evidence that gut microbiota composition undergoes dynamic alterations during aging in multiple AD mouse models and may be associated with AD-related progression. This study may contribute to a better understanding of microbiota-associated changes during AD development and provide a basis for future mechanistic studies targeting the microbiota-gutbrain axis in AD.

Applications of machine learning algorithms to detect digital addiction: a meta-analysis

Digital addiction (DA) has emerged as a significant global concern, yet traditional diagnostic methods relying on self-report questionnaires face subjective bias and threshold inconsistencies. Recent advances in machine learning (ML) offer promising alternatives for automated DA detection. This study conducted a systematic meta-analysis of 64 eligible studies (75 independent datasets; N = 165,624), employing both single-group proportion and bivariate diagnostic test accuracy (DTA) models. The pooled classification accuracy was 0.87 (95% CI [0.85, 0.90]), and the DTA framework yielded a robust AUC of 0.92, with balanced sensitivity and specificity (both 0.86). Subgroup analyses showed high accuracy across subtypes, particularly for internet (0.90) and social media addiction (0.86). Accuracy was comparable between survey-based and physiological data, though physiological markers demonstrated superior specificity (0.90). These findings underscore the potential of ML-driven tools as scalable screening instruments while emphasizing the need for representative sampling and standardized diagnostic criteria to advance digital mental health practice.