Secondary exercise addiction shows high comorbidity with eating and body image disorders. Despite its substantial impact on physical and mental health and daily functioning, evidence on effective therapeutic interventions remains limited. The aim of this scoping review was to identify and describe therapeutic interventions applied to adult individuals with secondary exercise addiction. This review followed the PRISMA Sc-R guidelines and covered the years 2002–2024. Ultimately, five studies were included (four randomized controlled trials and one quasi-experimental study). Three studies applied psychotherapeutic interventions based on cognitive-behavioral models (Cognitive Behavioral Therapy, Lifestyle, Exercise, Attitudes, and Relationships Program, Physical Exercise and Dietary Therapy), while two integrated physical or nutritional components. A secondary analysis published in 2024 based on the LEAP trial dataset was identified but not treated as an independent study to avoid duplication. EBSCOhost, Web of Science, PubMed, and Google Scholar were searched from January to May 2025 using terms related to exercise addiction, exercise abuse, psychotherapy, intervention, and treatment. English-language studies were eligible if they described an intervention with at least one treated group with pre- and post-test measures; the participants of the study were adult patients suffering from eating disorders and exercise addiction (the therapy programs involved one inpatient and four outpatient treatments) and therapeutic intervention was carried out with outcomes based on exercise addiction level data. Four out of five included studies reported improvements in variables related to compulsivity, although these did not always imply a reduction in the amount of exercise, indicating that qualitative changes may be more relevant. Longer interventions showed more consistent effects, but even brief treatments generated positive changes in non-clinical populations. The examination of the research revealed a gap in studies addressing interventions for those with secondary exercise addiction, especially highlighting the need for randomized controlled trials (RCTs) with proper randomization methods.
Adapted RPM-08 for Substance Use Disorder in Pakistan
Conditions: Substance Use Disorder (SUD); Drug Abuse; Relapse
Interventions: Behavioral: Adapted Relapse Prevention Module (RPM-08); Other: Treatment as Usual (TAU)
Sponsors: Universiti Sains Malaysia
Completed
Interventions: Behavioral: Adapted Relapse Prevention Module (RPM-08); Other: Treatment as Usual (TAU)
Sponsors: Universiti Sains Malaysia
Completed
Trump administration warns against using federal dollars on fentanyl test strips
The Trump administration is doubling down on its opposition to harm reduction services for people who use illicit drugs.
In an open letter on April 24, the federal agency overseeing addiction and mental health policy warned its grantees against using federal funds to buy harm reduction supplies including sterile syringes and pipes, or to distribute test strips for common drug supply adulterants like fentanyl, xylazine, and medetomidine.
The Download: DeepSeek’s latest AI breakthrough, and the race to build world models
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Three reasons why DeepSeek’s new model matters
On Friday, Chinese AI firm DeepSeek released a preview of V4, its long-awaited new flagship model. Notably, the model can process much longer prompts than its last generation, thanks to a new design that handles large amounts of text more efficiently.
While the model remains open source, its performance matches leading closed-source rivals from Anthropic, OpenAI, and Google. It is also DeepSeek’s first release optimized Huawei’s Ascend chips—a key test of China’s dependence on Nvidia.
Here are three ways V4 could shake up AI.
—Caiwei Chen
The rise of world models
AI systems have already gained impressive mastery over the digital world, but the physical world remains humanity’s domain. As it turns out, building an AI that composes novels or code apps is far easier than developing one to fold laundry or navigate city streets. To bridge this gap, many researchers believe you need something called a world model.
Proponents like Stanford professor Fei-Fei Li and AMI Labs founder Yann LeCun argue these models can overcome the well-known limitations of LLMs—and realize AI’s promise for robotics. Find out why they’ve brought world models to the forefront of the field.
—Grace Huckins
World models are on our list of the 10 Things That Matter in AI Right Now, our essential guide to what’s really worth your attention in the field.
Subscribers can watch an exclusive roundtable unveiling the technologies and trends on the list, with analysis from MIT Technology Review’s AI reporter Grace Huckins and executive editors Amy Nordrum and Niall Firth.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 China has blocked Meta’s $2 billion acquisition of AI startup Manus
Regulators cited national security grounds. (WSJ $)
+ Beijing called the deal a “conspiratorial” attempt to hollow out its tech base. (FT $)
+ The country is tightening its grip on AI firms that try to leave. (TechCrunch)
+ The decision escalates China’s AI rivalry with the US. (Bloomberg $)
+ But there will be no winners in their competition. (MIT Technology Review)
2 Google is investing up to $40 billion in Anthropic
In a deal valuing the AI firm at $350 billion. (CNBC)
+ The funding will support the firm’s growing computing needs. (TechCrunch)
+ Anthropic and OpenAI are fighting for compute capacity. (Axios)
3 President Trump just fired the entire National Science Board
The NSF has played a crucial role in developing technology. (The Verge)
+ The move heightens fears over political interference in US science. (Nature)
4 Conspiracy theories about the Washington shooting are proliferating online
Over 300,000 posts appeared on X using the keyword “staged.” (NYT $)
+ The theories are also swirling on Bluesky and Instagram. (Wired)
5 The AI compute crunch is starting to hit the broader economy.
It’s affecting jobs, gadgets, and electricity prices. (404 Media)
+ The AI compute explosion is the tech story of our time. (MIT Technology Review)
6 Elon Musk says a new banking tool brings X close to a “super app”
He’s pledged to launch the tool this month. (Bloomberg)
7 AI optimism is surging across Asia while US sentiment cools
The divide could shape where adoption happens fastest. (Rest of World)
8 Apple is tying its new CEO’s ascent to its first foldable iPhone
It wants to build the buzz around John Ternus. (Gizmodo)
9 Twelve firms are developing the Golden Dome’s space-based interceptors
They’ve won contracts worth up to $3.2 billion. (Ars Technica)
10 NASA has shared promising results from Artemis II
The spacecraft and rocket fared well. (Engadget)
Quote of the day
“Getting out the truth and establishing facts and reliable information takes time. But our audiences really don’t have that kind of patience.”
—Amanda Crawford, associate professor at the University of Connecticut, tells the NYT why conspiracy theories are gaining traction online.
One More Thing
MIRIAM MARTINCIC
Welcome to Kenya’s Great Carbon Valley: a bold new gamble to fight climate change
Kenya’s Great Rift Valley is home to five geothermal power stations, which harness clouds of steam to generate about a quarter of the country’s electricity. But some of the energy escapes into the atmosphere, while even more remains underground for lack of demand. That’s what brought Octavia Carbon here.
Last year, the startup began harnessing some of that excess energy to remove CO2 from the air. The company says the method is efficient, affordable, and—crucially—scalable. But the project also faces fierce opposition.
Read the full story on the future of Kenya’s “Great Carbon Valley.”
—Diana Kruzman
We can still have nice things
A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line.)
+ Fred Again’s Tiny Desk Concert is a masterclass in intimate performance.
+ Here’s a delightful look at how we’re all linked through geography and shared heritage.
+ Take a short, peaceful break to watch Tokyo’s cherry blossoms from a bird’s eye view.
+ There’s something oddly satisfying about watching an industrial shredder turn everyday items into confetti.
How adolescent cannabis use reshapes the developing brain — a systematic review
Background and hypothesisCannabis use initiation during adolescence has increased globally, raising concerns about neurodevelopmental consequences during this critical period when the brain undergoes extensive remodeling in cannabinoid receptor-rich regions.Study designThis systematic review examines neurodevelopmental consequences of adolescent cannabis use, focusing on structural brain changes, cognitive impacts, addiction vulnerability, and long-term outcomes. We searched PubMed, EMBASE, PsycINFO, and Web of Science (2000-2025) for studies examining cannabis effects in adolescent populations. Following PRISMA guidelines, two reviewers screened 3,421 records and assessed 156 full-text articles, including studies with neuroimaging, cognitive assessments, or longitudinal follow-up.Study resultsThirty-six studies involving 8,432 participants met criteria: 23 longitudinal cohorts (62.2%), 8 cross-sectional (22.2%), 4 RCTs (11.1%), and 1 case-control study (2.8%). Neuroimaging revealed dose-dependent alterations including reduced prefrontal cortical and hippocampal/amygdala volumes, accelerated cortical thinning in longitudinal studies, and impaired white matter connectivity correlating with initiation age. Cognitive findings were mixed — some showed persistent deficits after prolonged abstinence in adolescent-onset users, others found no effects after controlling for confounders. Epidemiological studies consistently showed elevated addiction risk (ORs 3.9–7.2) in adolescents versus adults. Long-term associations included educational difficulties, mental health problems, and functional impairment, though causal relationships remained unclear.ConclusionsAdolescent cannabis use associates with structural brain changes, elevated addiction risk, and variable cognitive effects, suggesting greater vulnerability versus adult-onset use. However, methodological limitations including confounders, heterogeneous definitions, and observational designs limit causal inference. Findings support age-specific prevention and specialized interventions while highlighting needs for rigorous longitudinal research establishing causality.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifierCRD420251165329.
Psychedelics get a boost from the White House
President Trump recently signed an executive order which aims to increase access to psychedelic drug treatments. He was joined at the signing by podcaster Joe Rogan, who said he’ ha’d messaged the president about research on the psychedelic ibogaine.
In this week’s STATus Report, host Alex Hogan chats with STAT Washington correspondent Daniel Payne about what the executive order does and doesn’t do. Hogan also looks at why ibogaine, and psychedelic drugs more broadly, are increasingly being taken seriously for stubbornly hard-to-treat conditions like addiction, depression, and PTSD.
Rational causal induction from events in time.
Psychological Review, Vol 133(3), Apr 2026, 584-618; doi:10.1037/rev0000570
A longstanding focus in the causal learning literature has been on inferring causal relations from contingencies, where these abstract away from time by collating independent instances or by aggregating over regularly demarcated trials. In contrast, individual causal learners encounter events in their daily lives that occur in a continuous temporal flow with no such demarcation. Consequently, the process of learning causal relationships in naturalistic environments is comparatively less understood. In this article, we lay out a rational framework that foregrounds the role of time in causal learning. We work within the Bayesian rational analysis tradition, starting by considering how causal relations induce dependence between events in continuous time and how this can be modeled by stochastic processes from the Poisson–Gamma distribution family. We derive the qualitative signatures of causal influence and the general computations needed to infer structure from temporal patterns. We show that this rational account can parsimoniously explain the human preference for causal models that invoke shorter, more reliable, and more predictable causal influences. Furthermore, we show this provides a unifying explanation for human judgments across a wide variety of tasks in the reanalysis of seven experimental data sets. We anticipate the framework will help researchers better understand the many manifestations of continuous-time causal learning across human cognition and the tasks that probe it, from explicit causal structure induction settings to implicit associative or reinforcement learning settings. (PsycInfo Database Record (c) 2026 APA, all rights reserved)
STAT+: Trump’s boosting of psychedelics, cannabis signal a new era in GOP drug policy
The days of “Just Say No,” it seems, are long gone.
Over the weekend, President Trump signed an executive order to increase the availability of certain psychedelics as treatments for mental health conditions, ordering that $50 million be spent, and that the Food and Drug Administration fast-track reviews to usher in their approval. At one point, the president joked to the motley assembly of administration officials, a former Navy SEAL, and the podcaster Joe Rogan: “Can I have some, please?”
On Wednesday, the Trump administration announced it had downgraded medical marijuana from the highest tier of controlled substances, and was pushing the Drug Enforcement Administration to do the same for recreational marijuana.
The president’s lenient tack on some mind-altering drugs ushers in a new world of right-wing drug policy. While the administration has emphasized hardline, militaristic tactics when it comes to fentanyl, its recent actions on “softer” drugs could represent a new era not just for Republican politics but also for American drug policy writ large.
“With this imminent move, we are now confronted with the most pro-drug administration in our history,” Kevin Sabet, the CEO of the anti-legalization advocacy group Smart Approaches to Marijuana, said in a statement. “Policy is now being dictated by marijuana CEOs, psychedelics investors, and podcasters in active addiction — it is a travesty and injustice to the American people of unprecedented proportions. The marijuana industry is the new Big Tobacco, and President Trump is welcoming them to the homes of families across this country with open arms.”
Trump reclassifies state-licensed medical marijuana as a less-dangerous drug in a historic shift
WASHINGTON — President Donald Trump’s acting attorney general on Thursday signed an order reclassifying state-licensed medical marijuana as a less-dangerous drug, a major policy shift long sought by advocates who said cannabis should never have been treated like heroin by the federal government.
The order signed by Todd Blanche does not legalize marijuana for medical or recreational use under federal law. But it does change the way it’s regulated, shifting licensed medical marijuana from Schedule I — reserved for drugs without medical use and with high potential for abuse — to the less strictly regulated Schedule III. It also gives licensed medical marijuana operators a major tax break and eases some barriers to researching cannabis.
From stigma to support: the mediating role of sympathy between nurses’ perceived stigma and helping behavior tendency for alcohol use disorder
BackgroundThe detrimental effect of stigma on healthcare for individuals with alcohol use disorders (AUDs) is well-established, often resulting in social distance and diminished helping behavior tendencies. However, contemporary neuroscience reconceptualizes addiction as a brain disease, potentially altering emotional responses to stigma. This study examines a seemingly paradoxical possibility: that under specific conditions, perceived stigma is primarily associated with sympathy (rather than anger or fear), which in turn is linked to helping behavior tendencies among nurses.MethodsA cross-sectional survey was administered to 348 clinical nurses from tertiary hospitals in China. Participants completed standardized scales assessing perceived stigma of patients with AUDs, causal attributions, emotional responses (including sympathy, anger, and fear), and helping behavior tendencies. Data were analyzed using Pearson correlation and mediation analysis (PROCESS macro, Model 4) with 5,000 bootstrap samples to test the mediating role of sympathy.ResultsPerceived stigma showed a significant positive correlation with sympathy (r= .160, p<.05), which was in turn positively correlated with helping behavior tendencies (r= .269, p<.05). Critically, mediation analysis revealed that sympathy fully mediated the relationship between perceived stigma and helping behavior tendencies. The standardized indirect effect was significant (β= 0.15, 95% CI [0.08, 0.23]), accounting for the total observed relationship, as the direct effect was non-significant. Additionally, compared to non-psychiatric nurses, psychiatric nurses perceived patients as significantly less dangerous and reported lower levels of fear and anger, along with a stronger intention to help and a lower tendency to avoid patients.ConclusionChallenging conventional perspectives, this study supports a dual-pathway model in which perceived stigma can indirectly associated with professional helping behavior tendencies through the elicitation of sympathy. While other emotions like anger and fear were also measured, the findings highlight the pivotal role of cognitive-affective processes, shaped by neurobiological understandings of addiction, in determining nursing care. Specifically, sympathy, but not anger or fear, was found to mediate the stigma-helping relationship. Enhancing neuroscience-informed education and targeted empathy training, particularly for general nurses, could transform stigmatizing attitudes into supportive care, ultimately improving outcomes for patients with AUDs.