Collaborative care treatment for major depressive disorder

IntroductionMajor Depressive Disorder (MDD) is a burdensome behavioral health condition that is costly and difficult to treat, particularly for patients with severe cases. The Collaborative Care Model (CoCM) has been shown to be effective for moderate depression treatment but less is known about its effectiveness for severe depression. This study analyzes the impact of CoCM treatment on outcomes for depression patients across all ranges of MDD severity at Concert Health.Materials and methodsAnalysis was completed utilizing all closed patient treatment episodes (N = 30,162) at Concert Health between 2018 and 2025. Of these patients, 5,693 began treatment with severe depression. We compare effect sizes for change between baseline and final screener scores across severity levels. Additionally, we utilize logistic regression to complete analyses to understand treatment factors and patient characteristics that are associated with treatment response and remission, as measured by changes in PHQ-9 scores.ResultsThe primary analysis showed that patients with severe depression (PHQ-9 > 20) had slightly lower odds of achieving response compared to patients with moderate depression (OR: 0.93). The treatment factors of insurance type, suicide risk, anxiety presence, and touchpoints also had significant effects on the odds of achieving response and remission.DiscussionThe results suggest that CoCM may be effective for patients with severe depression in achieving treatment response. Patients on Medicaid or with more complex conditions such as anxiety presence or elevated risk for suicide may need higher levels of engagement from the care team to achieve response and remission.

Smoking as a correlate of suicidal behavior and self-harm in adolescents with depressive disorders

Suicidal behavior and self-harm are major public health concerns among adolescents, particularly those with depressive disorders. While smoking has been linked to suicidality in general populations, its independent role in both suicidal behavior and self-harm within well-characterized clinical samples of youth with depressive disorders remains understudied. This study consecutively enrolled 2,343 adolescents (aged 12–18 years) diagnosed with unipolar depression, bipolar disorder, or depressive episode according to DSM-5 criteria at Nanhai Public Health Hospital of Foshan City and The Third People’s Hospital of Foshan between January 2025 and December 2025. Suicidal behavior (≥1 suicide attempt) and self-harm (intentional self-injury or poisoning regardless of intent) were assessed via clinical interviews. Multivariable binary logistic regression models were constructed to identify factors independently associated with each outcome, adjusting for age, sex, education, income, parental education, psychiatric diagnosis, family history of mental illness, physical disease, and smoking status. Among 2,343 participants (mean age 14.99 ± 1.65 years; 77.8% female), the prevalence of self-harm was 76.0% and suicidal behavior was 44.2%. In fully adjusted models, smoking status was the only variable significantly associated with suicidal behavior after adjustment for measured covariates: current smokers (OR = 2.74, 95% CI: 1.81–4.22, P<0.001) and past quitters (OR = 2.32, 95% CI: 1.66–3.28, P<0.001) had higher odds compared to never smokers. For self-harm, current smoking was significantly associated with increased risk (OR = 2.31, 95% CI: 1.33–4.37, P = 0.006). Education level showed a borderline association with self-harm, with each additional year of schooling corresponding to a 10% lower odds (OR = 0.90, 95% CI: 0.81–1.00, P = 0.050); however, this finding should be interpreted cautiously given the exploratory nature of the analysis. No other demographic or clinical variables, including age, sex, or psychiatric diagnosis, were independently associated with either outcome. Smoking was strongly associated with both suicidal behavior and self−harm after adjustment for measured demographic and clinical covariates. These findings underscore the importance of assessing tobacco use as a potential clinical marker of vulnerability in youth mental health settings.

Stigma and quality of life in hospitalized schizophrenia patient-family caregiver dyads in Northern China: an actor-partner interdependence model analysis

BackgroundSchizophrenia is a chronic and relapsing mental disorder that is consistently associated with a severely diminished quality of life (QoL) for patients. Existing research has predominantly focused on how the stigma experienced by patients with schizophrenia relates to their own QoL. However, stigma among family caregivers has received considerably less attention, and its potential association with patients’ QoL, in particular, remains underexplored. Therefore, this study aims to systematically analyze the dyadic associations of stigma—as experienced by both patients with schizophrenia and their family caregivers—with QoL, utilizing an actor-partner interdependence model (APIM). Through this framework, this study seeks to explore the interdependence of stigma between patients and their family caregivers and its correlational links to their quality of life.MethodsTwo hundred and sixty-four pairs of schizophrenic patients and their family caregivers were included, and the subjects’ stigma was measured using the Internalized Stigma of Mental Illness Scale and the Conjunctive Stigma Scale, respectively, and the quality of life was measured using the World Health Organization Quality of Life Measurement Short Form. The actor-partner effect of stigma on quality of life was explored by constructing an actor-partner reciprocity model.ResultsThe actor effect of stigma on quality of life was significant for people with schizophrenia and their family caregivers (β=-0.472, p < 0.001, β=-0.779, p < 0.001), and the partner effect of stigma on quality of life was significant for people with schizophrenia and their family caregivers (β=-0.128, p = 0.033, β=-0.419, p < 0.001).ConclusionIn future research and interventions aimed at improving the quality of life for people with schizophrenia and their caregivers, it is important to consider not only the individual’s own stigma, but also how the other person’s stigma is associated with one’s quality of life.

Knowledge Graphs Based on Meta-Analysis Papers Improve the Quality of Case Formulation: Mixed Methods Design

Background: Case formulation (CF) is a core skill for therapists; however, creating high-quality CFs requires considerable time. Objective: This study aims to demonstrate that providing a knowledge graph based on meta-analytic literature can enhance CF quality. Methods: Five groups were established, including 4 large language model groups and 1 human expert group, each generating 25 CFs based on 25 vignettes. The control group with Claude (Sonnet 3.7; Anthropic) produced 25 CFs. The personalization group served as the control group with additional personalization prompts. The knowledge graph group used a large language model that generated 25 CFs, which was provided with a meta-analysis knowledge graph. Further incorporation of additional personalization prompts then comprised the knowledge graph with personalization group. Finally, the expert group consisted of 25 CFs generated by a human expert. These 125 CFs in total were evaluated for general quality (ie, correctness, completeness, feasibility, and consistency) using a 7-point scale and 18 essential elements with binary scores (0 or 1) by another human expert. The CFs were also qualitatively analyzed. Results: The knowledge graph and knowledge graph with personalization groups scored significantly higher than the control group in terms of correctness, completeness, and feasibility. The expert group scored significantly higher on consistency than the machine-generated groups. Additionally, there was no significant difference in the feasibility scores among the knowledge graph, knowledge graph with personalization, and expert groups. The qualitative evaluation suggested that human CFs narrow the text to content that is easy for the client to read, whereas machine CFs are more likely to include expressions that are unnatural to the client. Conclusions: These results indicate that providing knowledge graphs to novice therapists increases the correctness, completeness, and feasibility of CF. Providing experienced therapists with knowledge graphs is suggested to improve the quality of their CF and mental health services.
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Governing Ethical Tensions in Youth Digital Mental Health Research

As mental health research increasingly aims to generate societal impact, researchers operate at the intersection of innovation and ethical responsibility. Drawing on experiences from the cocreated NEON Young Norway Study on youth recovery narratives, this viewpoint identifies four ethical tensions that arise from the existing governance frameworks in youth digital mental health research: (1) balancing safeguarding against harm with youth participation, (2) protecting privacy without undermining authentic storytelling, (3) governing unpredictable outcomes of cocreated research, and (4) meeting ethical and legal standards while ensuring youth-friendly communication. These tensions highlight limitations in mental health research that adopts participatory and digital approaches, as this often struggles to accommodate iterative designs, narrative data, and cross-sector collaboration. We argue that responsible youth mental health research requires ethics to be understood as a dynamic, participatory practice that supports safe and equitable inclusion, rather than having a focus on risk prevention. Ethical governance, therefore, needs to evolve toward proportionate, context-sensitive approaches that can enable innovation while protecting young people’s rights, agency, and voices.
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What Are Intrusive Thoughts?

When a child confesses a frightening thought that seemed to come out of nowhere — “What if I hurt someone with this knife?” “What if mom dies in a car accident?” “What if germs get into this paper cut and I die of an infection?”  — you can both find it confusing and disturbing.  But in most cases these intrusive thoughts are not evidence of a problem.

Intrusive thoughts are unwanted ideas, images, or urges that pop into the mind seemingly out of nowhere. They might feel embarrassing, violent, sexual, or just plain strange — and they feel completely out of character, which is exactly why they’re so upsetting. “An intrusive thought is a lot like your brain sending junk mail,” says Theresa Welles, PhD, a clinical psychologist and director of the Bubrick Center for Pediatric OCD at the Child Mind Institute. “Just because it shows up doesn’t mean it’s important or true or something you even want.”

It also doesn’t necessarily mean that a child has OCD or another mental health disorder. Though intrusive thoughts are associated with OCD — in which unwanted thoughts (called obsessions) drive children to perform rituals (called compulsions) to alleviate them — for many children they are just fleeting thoughts. It’s only when kids become unable to let them go that they are concerning. Another way to think about it, says Dr. Welles, is that “the brain’s job is to generate thoughts, the same way an apple tree’s job is to produce apples. Not every apple is perfect — some are misshapen or wormy. And not every thought is meaningful or worth paying attention to. Having a thought is not the same as wanting it or intending to act on it.”

Who has intrusive thoughts

“Everyone who has a brain has them,” says Caitlyn Downie, LCSW, director of trauma and resilience at the Child Mind Institute. “It’s part of the human existence.” A child might suddenly imagine something terrible happening to a parent, or a teenager might have a violent or sexual thought that feels shocking or shameful. Most of the time, these pass quickly — unpleasant, but easy enough to brush aside.

That’s the key distinction: not the thought itself, but what happens after it. The concern isn’t that the thought appeared — it’s how the child responds, how often it returns, and whether it starts getting in the way of daily life.

For some children — particularly those who are anxious, perfectionistic, or who have OCD — intrusive thoughts become “sticky.” Instead of passing through, the thought snags. The child starts paying attention to it, trying to figure it out or make it go away, which only makes it feel more powerful. “Young people lack the experience to recognize that thoughts aren’t the same as intentions, desires, or actions,” Dr. Welles says. “The thoughts feel alarming. So the child pays more attention, and the more attention they give it, the more often it returns.” That loop of fear and self-doubt is what parents and clinicians need to be alert to.

When should parents be concerned?

Many children are too ashamed or frightened to describe what’s actually going on, so parents may never hear about the thought itself. Instead, changes in behavior are often the first clue. Look for signs like:

  • Increased distress, irritability, or moodiness
  • Avoidance of something that wasn’t previously a problem
  • Trouble concentrating or sleeping
  • Excessive guilt or repeated reassurance seeking
  • Rituals like checking, counting, washing hands, or going through routines in a specific way

It’s worth seeking professional support when intrusive thoughts are frequent and intense, hard to shake, causing real distress, or getting in the way of school, friendships, or daily routines.

Why intrusive thoughts feel so frightening

When an intrusive thought appears, it can set off the body’s alarm system — the same ancient survival mechanism that helped people run from danger or fight it off. In anxiety and OCD, that alarm bell rings when there’s no real emergency. The child has a thought, the body reacts with panic, and the child assumes the thought must be important because it feels big and important.

Children may also fall into what clinicians call thought-action fusion. “That’s the mistaken belief that having a thought makes it more likely to happen,” explains Dr. Welles, “or that it reveals something terrible about who they are.” A child who thinks, “What if I hurt my baby brother?” may become convinced the thought means they secretly want to — but intrusive thoughts are often the precise opposite of what a child would ever want. Paradoxically, Dr. Welles says, “for most people with anxiety disorders and OCD, these thoughts are the actual opposite of what they would ever do.”

How parents can help

The first thing to do is stay calm — harder than it sounds if the thought is violent, sexual, or taboo. Children look to their parents to gauge whether something is truly dangerous, so if you look horrified, your child takes that as confirmation the thought is something to fear.

When a child shares an intrusive thought, Downie suggests responding with warmth and curiosity: “Say something like, ‘I appreciate you telling me — it sounds like that was really scary.’ It also helps to normalize it: ‘A lot of people have thoughts they don’t particularly like.’” Some other responses that can help:

  • “That sounds really upsetting — I’m glad you told me.”
  • “Having a thought doesn’t mean you want it or that it’ll ever happen.”
  • “You don’t have to figure this out right now.”

The goal is to help your child feel less alone and less ashamed, without treating the thought like a five-alarm emergency. And do your best to avoid reassurance. Reassuring the child about the contents of a specific thought (for example, responding to a child who asks, “Are you sure I’m a good person?” with “Yes, you’re a good person”) can actually make things worse, especially in kids with OCD. They feel very temporary relief but then the thought creeps back and they need more reassurance. It becomes a cycle. Instead try: “I know this feels awful. And I know you can handle it.”

It also helps to redirect the child to something concrete: getting dressed, eating breakfast, watching a show, texting a friend. With younger kids, you might guide them in doing slow breaths or suggest they move to another room so they distract themselves from the thought. With teens, you might mean teach them to resist the urge to Google their fears or thoughts, confess, or ask the same question over and over again. “The idea,” Downie says, “is to validate the feeling without validating the fear. You’re saying: ‘I hear you, this is hard, and you can get through it.’”

What can cause intrusive thoughts?

Intrusive thoughts aren’t a diagnosis on their own — they’re a symptom that can show up across a range of conditions, or in children who have no diagnosis at all. Disorders they may be associated with include:

  • OCD: The most closely associated condition. Common themes include harm, contamination, sexual thoughts, and religious or moral fears.
  • Generalized anxiety: Tends to involve repetitive “what if” worries about everyday concerns — school, safety, family, the future.
  • Social anxiety: Brings intrusive thoughts about embarrassment, rejection, or being judged by peers.
  • PTSD: Can involve intrusive memories, images, or sensations tied to a traumatic event. “A child who has experienced trauma may worry about being harmed again or even about harming someone else,” Downie notes, “but that doesn’t mean every child with trauma will have intrusive thoughts.”
  • Depression: Often involves intrusive thoughts that fit a negative self-image: I’m worthless. I’m a burden. I’m a bad person.
  • Autism spectrum disorder: Repetitive thoughts often center on a special interest and aren’t typically unwanted or distressing the way OCD thoughts are — though they can look similar from the outside.
  • Psychotic disorders: Young people with psychosis tend to experience intrusive thoughts as fixed and real, without the self-awareness that typically accompanies anxiety-driven ones. Psychotic disorders such as schizophrenia are rare in children, though early signs can appear in the teenage years.

How intrusive thoughts are treated

Treatment depends on what’s driving the thoughts and how much they’re disrupting the child’s life:

  • For OCD, the gold-standard treatment is exposure and response prevention (ERP), a specialized form of cognitive behavioral therapy (CBT) where children practice sitting with intrusive thoughts without doing compulsions. Over time, they learn to tolerate uncertainty and discover that the thought, however uncomfortable, isn’t actually dangerous.
  • For anxiety, the same treatments are helpful. CBT helps children understand the connection between thoughts, feelings, and behaviors, and ERP helps kids learn to tolerate the anxiety these thoughts generate, and it gradually diminishes.
  • For trauma, treatment may include trauma-focused CBT. Mindfulness, DBT skills, and breathing exercises can also help regulate the nervous system.
  • Family involvement matters a great deal. “Parents often need help learning how to respond without accidentally feeding the anxiety cycle,” Dr. Welles says. SPACE (Supportive Parenting for Anxious Childhood Emotions) is an evidence-based approach that helps parents reduce accommodation and support their child’s brave behavior instead.
  • For moderate-to-severe OCD or anxiety, medication — typically an SSRI — may also be worth discussing with a psychiatrist or pediatrician.

Helping your child trust their own mind

One of the hardest things about intrusive thoughts is that they can make children afraid of their own minds — convinced that every thought needs to be examined or explained away before they can relax. But no one gets to have only pleasant, well-behaved thoughts.  

What children can learn is that a thought can be upsetting without being meaningful, loud without being true, and it can pass through without becoming a verdict on who they are. As parents, the most powerful thing you can offer is a calm, steady presence — taking it seriously without treating it as a catastrophe. When your child sees you aren’t panicked, they get to borrow some of that calm for themselves.

Frequently Asked Questions

What are intrusive thoughts?

Intrusive thoughts are unwanted ideas, images, or urges that pop into your mind unexpectedly. They often feel upsetting or out of character, but they’re essentially “junk mail” from the brain — not meaningful or important.

Are intrusive thoughts normal?

Yes, everyone can have them. Most children (and adults) experience intrusive thoughts at times, and in many cases they pass quickly without causing problems.

What causes intrusive thoughts?

They’re a normal byproduct of how the brain works, but they can become more frequent or “sticky” in kids who are anxious, perfectionistic, or dealing with conditions like OCD or trauma. Paying extra attention to the thought can also make it return more often.

Do intrusive thoughts mean I want to act on them?

No. Having an intrusive thought doesn’t mean you want to act on it or that it reflects who you are. In fact, these thoughts are often the opposite of what someone would ever want or do.

The post What Are Intrusive Thoughts? appeared first on Child Mind Institute.

Use of a Conversational Agent for Training Mental Health Professionals in Suicide Safety Planning: Pilot Feasibility and Acceptability Study

Background: Safety planning is recognized as one of the most effective interventions for reducing suicidal behaviors. The quality of safety plans strongly depends on professional training, and traditional methods, such as role-playing, are time-consuming and offer limited opportunities for repetition across diverse patient profiles. Generative artificial intelligence (GenAI) may provide innovative solutions by offering accessible, flexible, and realistic training environments. Objective: This pilot study aimed to evaluate the acceptability and feasibility of a GenAI-based simulator designed to train mental health professionals in safety planning. Methods: Twenty nurses and nursing assistants from psychiatric units in a French university hospital participated in a pre-post, single-session evaluation. After self-rating their ability, competence, and willingness to manage patients experiencing suicidal ideation, participants interacted individually with the text-based simulator for 20 minutes to perform a safety plan with a chatbot, then completed postsimulation acceptability items, and open-ended feedback. Composite scores were computed: acceptability (eg, helpfulness; 0‐40), realism (eg, looking like real interaction with patient; 0‐20), and challenge (eg, emotional challenge; 0‐30). Pre-post changes were tested (Wilcoxon signed-rank test), and age-group comparisons were performed. Results: Acceptability was high (mean 31.9/40, SD 5.3; median 32, IQR 7), realism moderate-to-high (mean 15.1/20, SD 4.1; median 15, IQR 5.25), and challenge manageable (mean 17.0/30, SD 8; median 18, IQR 12.5). Participants rated usefulness (mean 7.65/10, SD 1.57; median 8, IQR 1.57), perceived learning (mean 7.6/10, SD 1.79; median 8, IQR 2), recommendation to use the chatbot for training (mean 8.3/10, SD 1.59; median 9, IQR 2.25), and feedback quality (mean 8.35/10, SD 1.27; median 8.5, IQR 1.25) favorably. Willingness to actively manage patients experiencing suicidal ideation significantly increased postsimulation (.03). Younger participants reported higher acceptability (.04) and realism (.03). Participants reported minimal concerns regarding the simulator’s use. Conclusions: This pilot study demonstrates that a GenAI-based simulator for safety planning is feasible and highly acceptable among experienced mental health professionals. The findings are promising and warrant larger, controlled trials to assess impacts on training effectiveness and patient outcomes.
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The effect of weather on unscheduled healthcare utilisation for mental health conditions in England, 2014–2022

BackgroundWeather conditions have been linked to adverse mental health outcomes, and rising concern about climate change has increased interest in these associations. However, most existing research focuses on extreme weather events, such as heatwaves, or on acute clinical outcomes, such as suicide. Evidence is more limited regarding population-level variations in mental health–related healthcare utilisation across the full range of daily weather conditions.ObjectiveTo examine associations between daily weather conditions and unscheduled mental health–related healthcare contacts in England using large-scale national surveillance data.MethodsWe conducted a retrospective observational study across nine English regions from 1 January 2014 to 31 December 2022. Outcomes were daily counts of unscheduled mental health–related contacts to emergency departments (EDs), general practice out-of-hours (GP OOH) services, and the NHS 111 telephone advice line. Weather exposures included mean daily temperature (°C), hours of full sunshine, and total daily rainfall (mm). Associations were estimated using distributed lag non-linear models at regional level and combined through two-stage multivariate meta-analysis. Models were adjusted for seasonality, long-term trends, day of week, public holidays, and population size.ResultsMental health–related unscheduled healthcare contacts showed modest but consistent associations with temperature and sunshine. Across services, relative risks (demand) increased with rising temperatures up to around 18 °C and were higher on days with fewer hours of sunshine. Sunshine demonstrated the clearest pattern, with increased utilisation on low-sunshine days across all healthcare settings. Rainfall was not consistently associated with healthcare contacts. Age-stratified analyses showed a U-shaped relationship between temperature and ED attendances among adults aged over 64 years, with higher utilisation during both colder and warmer conditions. Overall variations in daily healthcare demand were modest, typically within ±10–20% of baseline levels.ConclusionIn England, short-term variations in temperature and sunshine are associated with changes in unscheduled mental health–related healthcare utilisation, whereas rainfall shows little consistent effect. Although effect sizes were modest, these findings highlight the role of everyday weather conditions in influencing mental health–related healthcare demand and may support planning and preparedness efforts for mental health services under current and future climate conditions.

Real-World Engagement With a Generative AI Conversational Agent for Mental Health Support: Retrospective Descriptive Study

Background: Generative artificial intelligence (GenAI) conversational agents are increasingly integrated within digital mental health interventions (DMHIs). However, empirical data on real-world engagement, usage patterns, and satisfaction with GenAI conversational agents remain limited. Objective: This study examined real-world engagement among users who interacted with the GenAI conversational agent within Mental, a DMHI designed to support mental health. We aimed to (1) characterize users engaging with Mental’s GenAI conversational agent, (2) examine real-world usage patterns, (3) examine satisfaction and user feedback following sessions, and (4) explore preliminary predictors of engagement with Mental’s GenAI conversational agent. Methods: This retrospective study analyzed naturalistic user data from 5082 paid subscribers who engaged with Mental’s GenAI conversational agent between October 2024 and March 2026. Users’ onboarding characteristics (ie, sex, mindset, distress level, desire for greater discipline, and primary stressors) and session satisfaction were collected via optional app-native items; session-level engagement metrics were captured through backend app usage data. Descriptive statistics were used to characterize user demographics and usage patterns. Session satisfaction was compared across temporal engagement variables using ANOVAs and independent-samples tests. As an exploratory aim, session-level mixed-effects logistic regression was used to estimate predictors of session-to-session return, with session satisfaction as the primary predictor and moderation by self-reported mindset. Results: Among users reporting onboarding data, 78.8% (2610/3312) identified as male and 90.0% (2667/2964) reported moderate-to-high distress on an app-native item. A total of 59,602 sessions were recorded (mean 11.8 sessions per user), most frequently occurring in the evening (17,206/59,602, 28.9%) and outside traditional business hours (37,181/59,602, 62.4%). Mean session satisfaction was high (mean 4.5, SD 0.9) and did not differ by time of day or day of the week. The most commonly selected session descriptors were “Insightful” (9236/19,883, 46.5%), “Felt seen” (7974/19,883, 40.1%), and “Good advice” (7510/19,883, 37.8%). The session-to-session return rate was 92.6%, and 69.4% (3528/5082) of users returned after their first session. In an exploratory analysis, session satisfaction was a significant predictor of return (odds ratio 1.35, 95% CI 1.14-1.60; <.001), although this finding should be interpreted as hypothesis-generating. Conclusions: Users engaged with a GenAI conversational agent within the Mental app outside of traditional care hours and presented with high return rates. Objective behavioral engagement data (eg, session frequency, timing, and session-to-session return rate) provide novel evidence that GenAI conversational agents may sustain real-world engagement, including among individuals who face barriers to traditional mental health services. Future research should determine whether these engagement patterns translate into clinically meaningful outcomes.