Conceptualizing Acceptance and Knowledge as Process Variables in Internet-Delivered and Therapist-Supported Cognitive Behavioral Therapy and Acceptance and Commitment Therapy in Primary Care for Insomnia: Pilot Feasibility and Process-Oriented Randomized Controlled Trial

Background: Internet-based interventions for insomnia show promise, but understanding the process variables, such as knowledge acquisition and psychological acceptance, is crucial for enhancing digital adherence and clinical effectiveness. Objective: This study aimed to evaluate the feasibility, adherence, and preliminary clinical signals of 2 therapist-assisted interventions—internet-delivered cognitive behavioral therapy (iCBT) and internet-delivered acceptance and commitment therapy (iACT)—for insomnia in a primary care setting. Methods: This was a pilot randomized controlled trial. Adults seeking help for insomnia (n=18) were recruited via primary care and randomized to either a 5-module iCBT or iACT program delivered via a secure digital platform with weekly therapist feedback. Blinding of participants and therapists was not possible due to the nature of the interventions. Primary outcomes included the Insomnia Severity Index; secondary outcomes included the 9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder, and WHO Disability Assessment Schedule. A novel sleep knowledge test was used as a process variable. The data were analyzed using split-plot analyses of variance (intention-to-treat or last observation carried forward and complete case analysis) and nonparametric Friedman and Kruskal-Wallis tests. Results: A total of 18 participants were randomized (iCBT: n=9; iACT: n=9). High attrition was observed, with only 33.3% (n=3) of iCBT and 55.6% (n=5) of iACT participants completing all modules. The iACT group demonstrated a significant within-group reduction in insomnia severity (=.01, Friedman test), whereas iCBT results were nonsignificant (=.10, Friedman test). No significant between-group differences were found for any clinical or process variables. Participants rated both treatments as credible (Credibility/Expectancy Questionnaire scores remained stable), though qualitative feedback indicated a need for more flexible, less burdensome content. Conclusions: This pilot study demonstrates that while internet-delivered insomnia treatments are feasible and credible in primary care, high attrition remains a significant barrier. Preliminary signals suggest that iACT may be a viable alternative to iCBT, potentially offering better adherence. Larger, fully powered pilot randomized controlled trials (estimated N=404) with refined recruitment and automated retention strategies are required to determine definitive comparative efficacy and the mediating role of sleep knowledge and acceptance. Trial Registration: Research and Development in the Västra Götaland Region (FoU i VGR) 272866;
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Roundtables: Can AI Learn to Understand the World?

Listen to the session or watch below

AI companies want to build systems that understand the external world and overcome the limitations of LLMs. Recent developments have brought world models to the forefront of the AI discussion.

Watch a conversation with editor in chief Mat Honan, senior AI editor Will Douglas Heaven, and AI reporter Grace Huckins exploring how AI might enter the physical world.

Speakers: Mat Honan, Editor in Chief, Will Douglas Heaven, AI Senior Editor, and Grace Huckins, AI Reporter

Recorded on May 21, 2026

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<![CDATA[Explore how integrated psychotherapy—CBTp, family support, and humane alliance—reduces relapse and restores meaning beyond medication in schizophrenia.]]>

Melatonin for Kids: Is It Safe?

If you’ve spent any time talking to other parents about sleep, you’ve probably heard about melatonin. One person swears by it. Someone else warns against it. And if your child is struggling to fall asleep, it can be hard to know what to believe.

Melatonin is widely available, often marketed as a “natural” sleep aid, and increasingly used to help kids of all ages. But it may not be the right solution. The key is knowing when it makes sense, when it doesn’t, and how to make it work best as part of a bigger sleep plan.

What is melatonin?

Melatonin is a hormone the body produces naturally to regulate sleep. As it gets dark, the brain releases melatonin to signal that it’s time to wind down. Light exposure at night — especially blue light from screens — can disrupt the body’s natural rhythm so you don’t feel sleepy even when it’s bedtime.

“Melatonin supplements can help facilitate that circadian rhythm, that 24-hour sleep cycle,” says Rohn Nahmias, DO, a child and adolescent psychiatrist at the Child Mind Institute. Because it’s sold over the counter, melatonin seems to be harmless. In practice, clinicians are much more cautious. While they tend to consider it relatively low risk, with few side effects, they still don’t view it as something to take casually or indefinitely.

That’s because there are real gaps in what we know about melatonin — especially when kids take it regularly over long periods. “The longest study was about four years, and they did not find any issues,” says Judith Owens, MD, MPH, a pediatric sleep expert and professor of neurology at Harvard Medical School. “But the data are very limited in subject numbers and long-term follow-up.”

So, the question parents often ask — is melatonin safe for kids? — doesn’t have a simple yes or no answer. The more useful question may be whether melatonin is right for your kid and what guidelines should you follow if you’re going to give it to them.  

That’s why it’s especially important to consult your child’s pediatrician or tell them if you’ve already started your child on melatonin. “Because melatonin is over the counter, families often forget to mention it,” says Dr. Nahmias. But doctors need to know about supplements, especially if a child is on other medications or has additional health concerns.

Melatonin can be helpful in the right situations, but using it without looking deeper can be “kind of slapping a Band-Aid onto a problem,” Dr. Nahmias says. In his practice, he always wants to rule out anxiety, mood concerns, or a medical issue that may be impacting sleep (such as snoring, breathing problems, or pain) before introducing something new like melatonin.

When melatonin can help

Melatonin is most useful when the issue is falling asleep, not staying asleep. For example, if your child has persistent trouble falling asleep — not just occasional bedtime resistance — and you have already tried using behavioral strategies.

The immediate-release melatonin sold in the United States is primarily helpful for sleep onset. (A prolonged-release form approved in the UK and EU may help with staying asleep, but it’s not available here.) Melatonin can also help with circadian rhythm issues like delayed sleep-wake phase disorder, when a child or teen’s natural sleep and wake times are much later than their schedule allows. “That is the other real indication for melatonin,” Dr. Owens says.

How to use melatonin thoughtfully

If melatonin does make sense for your child, experts agree: Start low and go slow. Dr. Nahmias recommends beginning with 1 to 2 milligrams for kids four and up and increasing the dose only if needed — up to 3 milligrams for kids ages 6–10. Many children respond well to low amounts. More than 5 milligrams, he says, isn’t much more effective and is more likely to cause side effects like grogginess or irritability. Dr. Owens emphasizes a similarly cautious approach: Use the lowest effective dose, monitor whether it’s actually helping, and reassess regularly rather than letting it quietly become an open-ended routine.

Dr. Nahmias recommends using melatonin in “clusters” — short, purposeful stretches of nightly use to help realign the circadian rhythm — and then pulling back to use as needed. A cluster might make sense for a few weeks after travel, during a tough transition, or while the family works on behavioral changes.

If a child needs melatonin every night for months, that’s a signal to dig deeper. “That tells me that there’s something likely going on underneath that’s not being addressed,” Dr. Nahmias says.

Side effects and safety

Melatonin is generally well tolerated, but knowing the possible side effects can help you catch problems early. The most common is grogginess the next morning. Others include irritability, headaches, dizziness, stomach upset, and — in toddlers and younger children — increased bedwetting. Some children may also experience vivid dreams or nightmares, though these tend to be mild.

Check in with your child’s pediatrician if side effects appear, your child needs melatonin frequently or for more than a short period, the dose keeps creeping up, sleep problems get worse, or if you notice signs of anxiety, depression, or ADHD that might be driving their sleep struggles.

One important safety note: melatonin gummies look like candy, and Dr. Owens describes an “astronomical increase” in calls to poison control centers and emergency room visits related to melatonin in children, largely due to accidental ingestion. Store melatonin — especially gummies — like any other medication: out of reach, ideally in a locked cabinet. Never present them to children as a treat.

A bigger concern: what’s actually in the bottle

Melatonin isn’t tightly regulated in the United States, which means the dose on the label may not match what’s actually in the product. Studies have found that 22 out of 25 over-the-counter melatonin gummies were labeled inaccurately, with some containing far more melatonin than advertised.

Dr. Owens describes the variability as “huge” and says she was genuinely shocked by the findings. When shopping, look for products with a USP Verified mark. USP (United States Pharmacopeia) is an independent nonprofit that tests supplements to confirm the product contains what the label says, in the correct amount, and without harmful contaminants.

Melatonin for kids with ADHD or autism

There’s solid evidence that melatonin can benefit children with neurodevelopmental conditions, particularly autism and ADHD, who are more likely to have disrupted sleep-wake cycles. “There is a pretty robust literature supporting efficacy, without a lot of side effects,” Dr. Owens says about children on the autism spectrum.

But Dr. Nahmias encourages parents of kids with autism or ADHD to take a closer look at bedtime routines before turning to melatonin. “Both of those populations of kids do best when there is structure put into their day,” he says. He recommends having a posted list of the sleep routine that a child needs to accomplish as a helpful visual reminder that will start to become second nature as it is built into their evening.

If getting to sleep is still an issue, trying melatonin makes sense. But for kids with autism and ADHD, it may take more time to see an effect. “It can be helpful to give it a bit longer to re-right the sleep cycle,” Dr. Nahmias says. “Trying it for two to three months may be more beneficial than just a few weeks.”

 Many neurodivergent kids may also need to stay on melatonin longer than neurotypical children. “This makes it absolutely imperative that administration of melatonin for these children is under the supervision of a health professional who can monitor efficacy and side effects, and recommend periodic ‘off-drug holidays,’” Dr. Owens says. The goal is to get sleep back on track and consistent for some time. Once that goal is achieved, Dr. Nahmias adds, “it is important that there be attempts to take breaks from the medication or try lower doses.”

When melatonin is not likely to help

Melatonin is often used in situations where it’s unlikely to make much difference. That’s not a criticism of parents — sleep deprivation is exhausting, and it’s natural to reach for something that seems gentle and accessible. But if the real issue is an inconsistent routine, untreated anxiety, or an unidentified medical problem, melatonin may only be a temporary solution. The real problem will persist and need diagnosis and treatment.

For younger children — kids under five, especially — sleep problems are almost always better addressed with changes in habits and routines rather than supplements. For kids under two, “there’s no reason to use melatonin… and really, honestly, under five, for the most part,” Dr. Owens says. At those ages, behavioral approaches almost always work better.

What to try before using melatonin

Small, consistent changes in sleep habits can make a real difference — and unlike a supplement, these strategies can help children build skills that support sleep for years to come. Dr. Nahmias focuses on what’s often called sleep hygiene: a consistent bedtime and wake time, a predictable wind-down routine, and a sleep environment that actually supports rest, like keeping the bedroom dark, cool, and quiet. “The bed is meant for one thing and one thing only, and that is for sleep,” he says, emphasizing no TV or cellphones before bed. Even small amounts of light can interfere with the body’s natural melatonin production.

He also suggests addressing anxiety, rumination, or bedtime fears directly. “Behavioral interventions, time and time again, have really been shown to be very effective,” Dr. Owens says. For younger children, that might mean learning to fall asleep without a parent in the room. For older kids and teens, it often means setting limits around devices and making sure the schedule they’re keeping is actually realistic.

Making a melatonin plan

Melatonin is a tool that works best with a plan behind it. Before starting, write down what problem you’re actually trying to solve. Is your child unable to fall asleep before 11pm? Waking during the night? Scared to sleep alone? Anxious about school?

A simple sleep log can make your conversation with your child’s doctor much more useful. For a week or two, track bedtime, approximate time asleep, any night wakings, morning wake time, screen use, and whether melatonin was used and, if so, at what dose. Dr. Owens calls sleep diaries “invaluable” because they reveal patterns that are nearly impossible to see when everyone’s tired and running on memory. That information helps you and your child’s doctor decide whether melatonin is worth trying, whether it’s working, and when it might be time to stop — keeping the focus not just on getting through tonight, but on helping your child build the sleep habits they’ll carry with them for years.

Frequently Asked Questions

Is melatonin safe for kids?

Melatonin is generally considered low risk and can be helpful for some children who have trouble falling asleep, especially when used short term and under a doctor’s guidance. But experts caution that there are still gaps in research about long-term use in kids, so it shouldn’t be treated as harmless or used casually without looking at underlying issues.

Can you OD on melatonin?

Accidental overuse can happen, especially because melatonin gummies may look like candy to young children. In recent years, there has been a major increase in poison control and ER visits related to accidental ingestion, so melatonin should always be stored like any medication — out of reach and ideally locked away.

Is melatonin bad for kids?

Melatonin is not inherently “bad” for kids, but it’s not the right solution for every sleep problem. If poor sleep is caused by anxiety, inconsistent routines, or a medical issue, melatonin may only mask the problem.

How much melatonin is safe for kids?

Experts recommend starting with the lowest effective dose. Some clinicians suggest starting with 1–2 milligrams for children ages four and up, and generally not exceeding 3 milligrams for kids ages 6–10 unless advised by a doctor.

The post Melatonin for Kids: Is It Safe? appeared first on Child Mind Institute.

Scaling creativity in the age of AI

Storytelling is core to humanity’s DNA, stemming from our impulse to express ideals, warnings, hopes, and experiences. Technology has always been woven through the medium and the distribution: from early humans’ innovation of natural pigments and charcoals for cave paintings to literal representation by the camera.

The landscape of storytelling continues to shift under our feet. Social and streaming platforms have multiplied, audiences have fragmented, and our demand for fresh, unique media is insatiable. A recent McKinsey podcast cites that we are watching upwards of 12 hours of video content daily, often on multiple devices and multiple platforms.

All this content is expensive to produce: With a baseline budget of $150M, a Hollywood feature runs $1M per minute of finished film; prestige streaming content is in the hundreds of thousands per minute. And since consumers want to engage with authentic, original material, every company is now effectively a media company. That means we all face the same pressure: more content, with the same time and budget constraints.

There is no longer a question whether to use AI for content; the math doesn’t work any other way. What leaders need to focus on now is how to adapt responsibly, protect brand integrity, uplift team creativity, and build customer trust.

A few things worth holding onto as this era accelerates:

  • AI amplifies what’s already there, both good and bad. Weak strategy stays weak.
  • Responsible adoption means knowing what’s in your tools and models. Provenance and transparency are the foundation, not the finish line.
  • Scale without taste is just noise. Investing in your team’s judgment is what makes more content matter.
  • Fundamentals of great storytelling have not changed. Regardless of format or channel, what makes audiences lean in are still characters, arc, ingenuity, and surprise.

The permanent sprint

Creative teams are trapped on the endless hamster wheel of production, and it’s not slowing down. According to Adobe research, content demand will grow 5x over the next two years. Social content shelf life is now measured in hours, not weeks. Keeping fresh work in the pipeline is a permanent sprint, requiring teams to rethink how creative production functions.

The first move is freeing creative teams by having AI absorb the repetitive work so they have space for the strategic creative decisions that require human ingenuity. In a recent study from Adobe, 94% of creatives report that AI helps them produce content faster, saving an average of 17 hours per week. That recovered time is not a productivity metric; it is renewed creative capacity.

As a use case, Nestlé offers a useful blueprint. Its teams operate across 180 countries with a portfolio of iconic brands including Nescafé, KitKat, and Purina. Using Adobe Firefly Custom Models embedded in existing content workflows allows teams to generate assets in a brand-informed style without disrupting creative flow. At Nestlé, workflow cycle times dropped 50%. “With Firefly Custom Models, we can react at the speed of culture. It’s the closest thing we’ve had to magic.” says Wael Jabi, global strategic comms lead for KitKat.

As we move into the agentic era, the possibilities expand further. Adobe’s Creative Agent thinks in systems, not tasks, orchestrating across workflows, apps, and processes to close the gap between idea and execution, and get teams out of the production cycles that consume their productivity.

Build for your brand, not every brand

A company’s brand is how the world recognizes and connects with them. And it’s more than a collection of assets—it is dynamic, subjective, and expressed in thousands of micro-decisions made every day by the people who know it best. As production scales, keeping everything tuned to the brand gets more challenging. Off-the-shelf AI cannot replicate the level of nuance creative teams bring to content, and there’s a real cost to getting it wrong; diluting a brand in market with almost-right output is not an acceptable option. Customer trust is fragile.

Starting with a bespoke AI model built with Adobe Firefly Foundry addresses this directly. Firefly Foundry starts with a commercially safe base model and trains further on a company’s IP, making it possible to produce content that genuinely reflects the team’s vision.

And to ensure that Firefly Foundry models truly represent the creatives at the helm, Adobe has partnered with film studios like Wonder Studios, Promise.ai, and B5 Studios, and the “big three” talent agencies CAA, UTA, and WME to deeply understand what it means (and what it takes) to build an IP-immersive model that keeps creatives at the center as these film studios and talent agencies scale their visions. These brand ecosystems can accelerate nearly every phase of the production process, from ideation and storyboarding to production and promotion, all while preserving artistry and authorship. And to power the next generation of creativity and content, Adobe has recently announced a strategic partnership with NVIDIA, delivering best-in-class creative control along with enterprise-grade, commercially safe content at scale.

Generic AI gives teams a starting point. But a model trained on a brand’s own IP gets them to the finish line, while still leaving room for the creative calls that matter most.

When agents become the audience

AI is not only reshaping how we create; it is reshaping how customers find and engage with brands entirely. According to Adobe Digital Insights, AI-powered shopping has surged 4,700%. Agentic web traffic is up 7,851% year over year. Yet, most businesses still have significant gaps in AI-led brand visibility. If content is invisible to AI agents, then a brand is invisible to customers.

Major League Baseball is ahead of this curve. Using Adobe LLM Optimizer, the league monitors how its content surfaces across AI interfaces and makes real-time adjustments to maintain visibility. As fans search for tickets, stats, or game-day experiences, the league ensures its brand shows up wherever that search is happening. And with Adobe’s recent acquisition of Semrush, brand visibility goes even further.

The agentic web created an entirely new content surface that did not exist two years ago, and this exponential proliferation of content illustrates precisely why scaled, on-brand content production has become a strategic imperative. A well-built agentic foundation offers full visibility into (and control over) every piece of content, from production to performance.

How to prepare for AI integration

Here are a few steps to get started:

Audit before automation. Content supply chains usually include duplicated processes, unclear ownership, and assets living in many different places. Before AI can accelerate anything, develop a clear map of how content moves through the organization today: who creates it, who approves it, where it lives, and where it breaks down. AI applied to a broken process just breaks it faster.

Walk through workflows. Resist the urge to overhaul everything at once. Start with production tasks that are high-volume, low-stakes, and well-defined: asset resizing, localization, and background generation. Use those wins to build internal confidence before expanding into more complex creative territory.

Build responsible governance from the start. Governance added as an afterthought becomes a bottleneck. Building it in from the beginning creates a competitive advantage that lets teams move fast with confidence. And this means clear policies on model training, content provenance, human review thresholds, and communicating AI use to customers. The brands that earn lasting trust will treat transparency as a feature, not a footnote.

This content was produced by Adobe. It was not written by MIT Technology Review’s editorial staff.

Guarding biotech from China and big bets in longevity

On this week’s episode of “The Readout LOUD,” the hosts discuss STAT’s Breakthrough Summit West, where powerful leaders from health care and science rubbed shoulders. They share some of the juicy conversations and insights, including BridgeBio CEO Neil Kumar’s comments that the company is publishing  “not the right structures” in their research publications.

Listeners also will hear Allison’s interview with Joe Betts-LaCroix, CEO of the Sam Altman-backed longevity company Retro Biosciences. Retro is preparing for its first clinical data readout and examining just how much impact AI can have in drug development.

Read the rest…

<![CDATA[Unpack gaming, gambling, social media, and exercise addiction, spotlighting comorbid anxiety, withdrawal signs, and harm-reduction treatment.]]>

Functional brain alterations associated with acupuncture for chronic pain: a scoping review of fMRI studies

BackgroundChronic pain (CP) is a public health challenge recognized as involving large-scale functional brain dysregulation. Acupuncture is widely used as a non-pharmacological intervention for CP, yet its central mechanisms remain incompletely understood. fMRI provides an approach for investigating acupuncture-related brain alterations in CP.MethodsEight databases were searched from inception to March 27, 2025 for fMRI studies investigating acupuncture’s central effects in CP. Eligible studies included randomized controlled trials and observational studies involving migraine, knee osteoarthritis, fibromyalgia, sciatica, chronic shoulder pain, chronic neck pain, cervical spondylosis, chronic low back pain, and lumbar disk herniation. Data on characteristics, acupuncture protocols, neuroimaging findings, and outcomes were extracted and narratively synthesized. Reporting quality of acupuncture interventions was assessed using STRICTA, risk of bias of randomized controlled trials using RoB 2, and methodological quality of observational studies using the Newcastle–Ottawa Scale.ResultsA total of 64 studies were included. CP was characterized by widespread functional brain abnormalities, mainly involving the default mode network, sensorimotor network, and pain- and emotion-related regions such as the anterior cingulate cortex, precuneus, insula, and thalamus. Across longitudinal and controlled analyses, acupuncture-related brain changes were most consistently reflected in altered functional connectivity, local neural synchrony, and regional spontaneous activity. Functional connectivity findings suggested a potentially ACC-centered circuit pattern, whereas regional homogeneity findings revealed bidirectional modulation across multiple brain regions. Comparative evidence further indicated that VA, SA, and EEA may engage partially overlapping but distinct neural processes. Reporting of core acupuncture protocol components was generally adequate, whereas methodological quality remained heterogeneous.ConclusionCurrent fMRI evidence suggests that CP involves large-scale network-level functional imbalance and that acupuncture may be associated with modulation of key abnormal nodes and circuits related to pain perception, sensory processing, and emotional regulation. The available evidence supports a cautious interpretation that acupuncture-related brain effects may predominantly reflect a state-dependent recalibration of dysregulated brain networks. Future studies should prioritize large-sample, multicenter, longitudinal, and multimodal designs, together with rigorous control settings and more rigorous, externally validated machine learning-based prediction studies, to better distinguish differential central effects across intervention conditions and advance mechanism-informed personalized acupuncture in CP management.

A compressed sensing neuromorphic processor for sparse signal classification

This paper presents a neuromorphic processing system integrating a compressed sensing spiking neural network (CSSNN) designed for sparse signal classification. The proposed CSSNN combines data coding, data compression, and SNN classification, enabling end-to-end optimization of network performance and model compression. Evaluated on the MNIST, N-MNIST, and DVS Gesture datasets, under uniform compression ratios (CRs) of 0.1, 0.05, 0.025, and 0.01, the proposed CSSNN consistently reduces the total number of network operations (OPs) by at least 80% compared with compressed learning methods using fixed Gaussian random matrix (GRM) sampling matrices, while maintaining minimal accuracy loss. A specialized CSSNN processor is designed based on a spike-driven processing flow. Validated on field-programmable gate arrays (FPGAs) and evaluated in the 40 nm CMOS process for application-specific integrated circuit (ASIC) design, this CSSNN processor achieves 96.12% classification accuracy with 8-bit fixed-point quantization on the MNIST dataset. The energy consumption of the ASIC is estimated to be 2.089 mW under a 1.1-V supply voltage and 100 MHz frequency.

Structural connectome analysis using a graph-based deep model for prediction of non-imaging variables

We address the prediction of non-imaging variables based on structural brain connectivity derived from diffusion magnetic resonance images, using graph-based machine learning. We predict age and the mini-mental state examination (MMSE) score as examples of a demographic and a clinical variable. We propose a machine-learning model inspired by graph convolutional networks (GCNs), which takes a brain connectivity graph as input and processes the data separately through a parallel GCN mechanism with multiple branches. The novelty of our work lies in the model architecture, especially the Connectivity Attention Block, which learns an embedding representation of brain graphs while providing graph-level attention. We show experiments on publicly available datasets of PREVENT-AD and OASIS3. We validate our model by comparing it to existing methods and via ablations. This quantifies the degree to which the connectome varies depending on the task, which is important for improving our understanding of health and disease across the population. The proposed model generally demonstrates higher performance especially for age prediction compared to the existing machine-learning algorithms we tested, including classical methods and (graph and non-graph) deep learning.