Cultural and intergenerational pathways between family alcohol use, trauma exposure, and probable PTSD in Taiwanese adolescents

BackgroundPosttraumatic stress disorder (PTSD) and alcohol use (AU) frequently co-occur, yet little is known about how family drinking patterns shape trauma exposure and PTSD risk in non-Western and Indigenous adolescent populations. Taiwan’s multi-ethnic eastern region—home to Amis and Atayal Indigenous groups—provides a unique context for examining culturally specific trauma pathways.ObjectiveTo examine how caregiver and adolescent alcohol use relate to exposure to traumatic events (TEs) and probable PTSD likelihood among Han Chinese and two Indigenous groups, Amis and Atayal, in eastern Taiwan.MethodsA cross-sectional survey was conducted among 751 junior-high students (Han, Amis, Atayal) in rural eastern Taiwan. Adolescents completed the Chinese UCLA PTSD Reaction Index and a trauma-exposure checklist. Caregiver and adolescent AU were assessed via self-report. Logistic regression tested associations among caregiver and adolescent AU, trauma exposure, and probable PTSD likelihood, adjusting for demographic factors.ResultsCaregiver AU was significantly associated with both trauma exposure and probable PTSD across all ethnic groups. While adolescent AU was associated with trauma exposure among Han and Amis youth, no such link was found for Atayal adolescents. Furthermore, exploratory testing rejected the self-medication hypothesis, lending support to the high-risk environmental framework. Trauma types most strongly associated with probable PTSD differed by ethnicity: sexual trauma and painful medical procedures among Han youth; bereavement among Amis adolescents; and witnessing community violence among Atayal adolescents. Indigenous participants showed consistently higher trauma exposure than Han peers.ConclusionsFamily drinking patterns exert strong intergenerational effects on adolescent trauma exposure and probable PTSD risk. The culturally distinct trauma profiles across Han, Amis, and Atayal adolescents highlight the need for trauma-informed, culturally grounded, and family-centered mental-health interventions. Reducing caregiver AU and addressing structural inequities affecting Indigenous communities may offer critical leverage points for preventing PTSD among youth in Taiwan and comparable multi-ethnic settings.

Functional MRI evidence of brain alterations in premenstrual dysphoric disorder: a systematic review

IntroductionPremenstrual Dysphoric Disorder (PMDD) affects approximately 1.6% of women of reproductive age and significantly impacts quality of life. Despite its prevalence, the underlying pathophysiology remains incompletely understood. First-line treatment typically involves selective serotonin reuptake inhibitors (SSRIs); however, approximately 40 percent of women with PMDD do not respond to these medications. This systematic review synthesizes current evidence on functional brain alterations in women with PMDD, as assessed using functional magnetic resonance imaging (fMRI), with the goal of identifying potential novel therapeutic strategies.MethodsData from 598 participants, including 294 PMDD patients and 304 healthy controls, were analyzed.ResultsThe findings suggest alterations in both topdown regulatory mechanisms and large-scale brain networks, including the salience network, default mode network, and executive control network. These alterations are characterized by decreased activation in the anterior cingulate cortex, dorsolateral prefrontal cortex, medial orbitofrontal cortex, and postcentral gyrus, alongside increased activation in the amygdala and insula, as well as impairments in corticolimbic connectivity.DiscussionThese results highlight the complexity of PMDD, implicating widespread neural circuits rather than a single localized dysfunction. Targeting these mechanisms may inform the development of novel interventions for symptom relief.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD420251174749.

Spectral EEG-guided adaptive neuromodulation for social anxiety disorder, performance-only subtype: a case report

Social anxiety disorder (SAD) is often complicated by anticipatory anxiety, hyperarousal, and variability in response to first-line treatments such as cognitive behavioral therapy (CBT) and pharmacotherapy. These limitations highlight the need for adjunctive modalities capable of enhancing the magnitude and durability of treatment response. This case report explores outcomes following spectral EEG-guided personalized repetitive transcranial magnetic stimulation (PrTMS) in a patient with SAD, performance-only subtype. Weekly psychometric assessments revealed reductions in social anxiety intensity, avoidance behaviors, and negative self-appraisal, along with improvements in mood and daily function. Symptom changes were quantified using the Liebowitz Social Anxiety Scale (LSAS), Social Phobia Inventory (SPIN), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-Item Scale (GAD-7), and Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF). Clinical improvements were accompanied by increased alpha band power, decreased delta band power, and an increased alpha-delta ratio on serial spectral resting-state EEGs. Our findings suggest that PrTMS may warrant further investigation as a potential adjunctive treatment for SAD. Further large-scale, blinded, and randomized studies are warranted to validate our observations on the feasibility of PrTMS for SAD.

Marked for destruction

Nature Biotechnology, Published online: 04 June 2026; doi:10.1038/s41587-026-03182-5

The significance of the first FDA-approved PROTAC lies not in proving that targeted protein degradation is superior to conventional therapies, but in proving that degrading proteins is possible as a therapeutic.

A socially assistive robot to support mental wellbeing in LGBTQ+ young people at risk of self-harm: a randomized controlled trial

Nature Medicine, Published online: 04 June 2026; doi:10.1038/s41591-026-04422-6

A randomized controlled trial integrating Purrble, a socially assistive tactile robot, into safety planning found that LGBTQ+ youth at risk of self-harm experienced improvements in Difficulties in Emotion Regulation Scale and fewer depressive symptoms compared to safety planning alone.

How courts are coping with a flood of AI-generated lawsuits

Most days in her chambers, Judge Maritza Braswell, a federal magistrate judge in Colorado, sifts through stacks of documents written by people without a lawyer. Many of them can’t afford to hire a lawyer, and others have cases too weak or too small to interest one. She reads each one carefully, mindful of how daunting it is to walk into the courtroom alone. 

Lately, like many judges across the US, she has seen a noticeable uptick in such filings. According to a new study that examined 4.5 million federal civil cases from 2005 to 2026, the share of lawsuits brought by self-represented people increased from 11% in 2022 to 16.8% in 2025. Within those cases, the number of filings made more than doubled compared to before 2023. 

Judge Braswell puts that jump down to AI. 

“I do correlate that to AI in part because I see AI use,” she says. As a tech-savvy judge who uses AI to vet court documents, she’s learned to recognize how large language models write. She can tell based on the prose and at times, hallucinated cases and fabricated quotes. 

“I’m also actually seeing better-drafted pleadings,” she says. 

But while AI appears to be expanding access to justice, it doesn’t seem to be improving people’s chances of winning. Judges are also starting to question what kinds of rights and responsibilities large language models should bear as they step into lawyers’ shoes, such as whether a chatbot has a duty to provide good advice, as a human lawyer does. And a growing number of lawmakers across the US are starting to grapple with who should pay the price when chatbots dish out bad legal advice. 

AI supercharges lawsuits

To test whether AI was driving the increase in lawsuits filed by people without a lawyer, the authors of the study, Anand Shah at MIT and Joshua Levy at USC, ran 1,600 randomly sampled court documents through Pangram, a commercial AI-text detector. The share flagged as containing AI-generated writing rose from 1% in 2023 to 18% in 2026. 

To Judge Braswell, that’s not necessarily a cause for concern. While the surge of AI-assisted filings might be adding to their workloads, she and many other judges find the cases easier to rule on because AI is helping people without legal training better articulate their arguments. 

Court documents written by people without lawyers are notoriously hard to decipher. Some arrive as handwritten scrawls bordering on gibberish that judges take a while to decode. However cryptic, judges are required to read them charitably.

These days, Judge Braswell has been churning through motions drafted by AI faster than the ones written by the litigants. “I have to be really careful because some of them contain hallucinations and errors, but I can generally understand what they’re arguing better with AI assistance from them than without it,” she says.

The clearer filings let Judge Braswell hear them better. “If I understand an argument a little bit better, I’m probably going to be able to help a little bit more.”

Online communities are springing up to trade self-help guides on using AI to sue. In December 2024, a viral Reddit post walked immigration applicants through suing the United States Citizenship and Immigration Services over delayed review of their applications: draft a writ of mandamus with Microsoft Copilot, pay a lawyer $150 to polish it, and file in the expedient District of Vermont. Cases filed by people without lawyers in Vermont rose from about 45 a year before 2022 to more than 1,100 in 2024. 

Even so, people without lawyers are far more likely to lose their case than people with lawyers, and that’s not changing even with the addition of AI, the study found. 

“It turns out that mounting a lawsuit is a complex, multifaceted task. Not all of it is just drafting text,” says Joshua Levy, a doctoral student at University of Southern California, who co-authored the study. 

Chatbot-client privilege

Judge William Garfinkel, a federal magistrate judge in Connecticut, has served on the bench for three decades, pondering all sorts of questions about lawyers’ relationship with their clients. Lately, he has been wondering whether people’s conversations with chatbots dispensing legal advice should be privileged, the way that their conversations with lawyers are. 

“You can make a good argument that … conversations with large language models like Claude or ChatGPT or Grok should deserve some protection,” he says.

Courts are starting to grapple with this question. In February, a federal court in Michigan ruled that a self-represented person’s conversations with ChatGPT to prepare her case were work product—legal work that is shielded from the opposing side.

The decision came on the same day that a federal court in New York held that documents that a criminal defendant generated using Claude were not privileged attorney-client conversations or work product. The Court argued that Claude is not an attorney and that a user has no “reasonable expectation of confidentiality in his communication” with Claude because AI companies could disclose user data to third parties. 

In March, Judge Braswell also ruled that a self-represented person’s use of a chatbot should stay off limits. “It is true that AI systems like ChatGPT, Claude, Gemini, and others … collect user data for training and other purposes. But … that does not eliminate all expectations of privacy,” she wrote. Courts have since remained split on the issue.

Malpractice without a pulse

Some judges are also wondering whether a chatbot, like a lawyer, has a duty to provide good legal advice. Judge Allison Goddard, a federal magistrate judge in California, has noticed that people without lawyers often get the wrong advice from ChatGPT when trying to assess the value of their case during settlement negotiations. In one case, a plaintiff who slipped and fell in a store asked for $700,000 from the store, which was wildly more than the case was worth.

“Where are you getting the idea that you’re getting $700,000? Did you go to ChatGPT?” Judge Goddard asked. “Well…” the plaintiff mumbled. She then walked them through the law to explain why ChatGPT was wrong and suggested a lower amount. “It’s like Dr. Google went to law school,” she says.

Then there’s the question of who’s liable when a chatbot gives bad legal advice. In March, Nippon Life Insurance Company sued OpenAI alleging that ChatGPT practiced law without a license and helped a woman reopen a lawsuit that was already settled, flooding the court with frivolous filings. “ChatGPT is not an attorney,” the lawsuit said. 

In May, OpenAI asked the court to dismiss the case, arguing that ChatGPT does not practice law. “ChatGPT is not a person and neither has nor uses any degree of legal ​knowledge or skill,” OpenAI said in its filing. The case is still pending before the court.

States have started to weigh legislation that would hold AI companies liable when their chatbots offer bad legal advice. New York introduced a bill in March that would bar chatbots from impersonating lawyers, even if they notify ​users that they are interacting with chatbots. In Congress, a series of bills have been proposed to ban chatbots from posing as lawyers, doctors, and other licensed professionals. The bills have yet to gain traction.

For now, people will continue turning to AI to be their lawyer. For many of them, the rewards outweigh the risks. Not long ago, when Judge Braswell asked a self-represented litigant why they wanted a particular piece of evidence, they mumbled timidly. Now, they answer her questions confidently, having rehearsed with a chatbot. 

“This is a really tough system to navigate. With AI, though, it gets a little less complex,” she says.