Construct Validation of a Remote Brain Health Assessment Battery to Evaluate Vocational Aptitude and Factors Associated With Cognitive Resilience in the Military: Observational Trial

<strong>Background:</strong> Vocational aptitude and cognitive resilience predict military success, yet current assessments rely on resource-intensive, in-person testing that limits scalability. A brief, self-administered, remotely deployable computerized battery offers a practical solution for large-scale screening and monitoring. <strong>Objective:</strong> This study aims to deploy a set of computerized assessments among National Guard recruits and assess their preliminary construct validity against a standardized aptitude measure and a research-based proxy for cognitive resilience. <strong>Methods:</strong> In this observational study, 267 enlisted service members from the Minnesota Army National Guard participated in 2 complementary ethics-approved observational trials: Office of Naval Research Neuropsychometrics and Advancing Research on Mechanisms of Resilience (ARMOR). National Guard soldiers in ARMOR completed the Armed Forces Qualification Test (AFQT), Penn Computerized Neurocognitive Battery (Penn CNB), and a 20-minute computerized brain health assessment battery (BrainHQ) at separate time points over the course of their military careers. BrainHQ assessments consisted of adaptive psychophysical tasks measuring the speed and accuracy of visual and auditory information processing. The battery assessed decision-making speed, emotion-processing speed, selective attention under speeded conditions, working memory capacity for speeded visual elements, verbal memory and learning of speeded speech, and problem-solving speed. The Penn CNB included nonspeeded neuropsychological assessments of executive function, verbal memory, social cognition, and reasoning. Linear regression evaluated the association between BrainHQ performance and AFQT percentiles, and partial correlations assessed associations between conceptually related BrainHQ and Penn CNB subtests. <strong>Results:</strong> Participants were predominantly young (mean age 19.1 years) and male (178/267, 66.7%). BrainHQ performance was significantly associated with enlistment eligibility and vocational aptitude, as measured by the AFQT (<i>P</i>&lt;.001), after controlling for age and education. The overall model explained 24.4% of the variance in AFQT percentiles (adjusted R2=0.227). The BrainHQ assessment composite was the strongest predictor, uniquely accounting for 19.2% of the variance and supporting the construct validity of aptitude. These associations persisted despite the temporal separation between assessment time points. Quartile analyses showed graded relationships between BrainHQ performance and AFQT eligibility thresholds, with higher BrainHQ performance associated with progressively greater probabilities of meeting higher AFQT benchmarks. Preplanned partial correlations between BrainHQ subtests and standardized neurocognitive measures from the Penn CNB showed significant positive associations (r=0.17-0.25; all <i>P</i>&lt;.001 to .02) with cognitive domains typically associated with cognitive resilience. <strong>Conclusions:</strong> A brief, self-administered, and scalable brain health battery demonstrates associations with military vocational aptitude and with neurocognitive domains associated with cognitive resilience. Future studies should evaluate whether integrating these assessments into current practices predicts success in Basic Combat Training, guides military progression, and supports long-term cognitive screening and monitoring across the Armed Forces.

Biomarkers Could Help in Antidepressant Choice

Antidepression treatment based on a person’s individual biomarkers could help determine which of the world’s most popular medications to use, a clinical trial suggests.

The SMART Trial to Predict Anhedonia Response to Antidepressant Treatment results suggest that behavioral, brain, and clinical data could together determine the optimal antidepressant to choose before a person starts treatment.

There were no significant primary endpoint differences in depression outcomes between participants who received bupropion or sertraline based on biomarkers identified in the prior Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study.

But people negative for biomarkers with both drugs had significantly worse depression symptom trajectories than those who had at least one positive biomarker, regardless of the drug they received.

Response rates among participants with both biomarkers were almost double that of those without any biomarkers, with those who had at least one biomarker having an intermediate response.

“Our results suggest that we could boost response rate by using two sets of biomarkers previously identified in the EMBARC study, making an important contribution to advancing the goals of precision psychiatry,” reported Peter Zhukovsky, PhD, from Harvard Medical School, and co-workers in Nature Mental Health.

“Ultimately, we strongly hope these advances will enable personalized treatment guidance to accelerate and boost antidepressant benefits.”

Treatment for depression is often still trial and error, with symptoms improving in only half the people taking an antidepressant. This could be due to treatments not being chosen based on people’s individual characteristics.

Finding markers that predict response to different antidepressants could therefore provide patients and clinicians with valuable information to guide treatment choice.

The trial was among the first to investigate how treatment could be guided using clinical information such as responses to questionnaires, behavioral information such as performance in computerized tasks, and brain data such as magnetic resonance imaging (MRI) scans.

It was carried out as part of the Wellcome Leap Multi-Channel Psych Program effort to double the number of people who respond to the first treatment they try for depression via the integration of multimodal biomarkers.

Firstly, the researchers investigated biomarker models that predicted response to the selective serotonin reuptake inhibitor (SSRI) sertraline or the norepinephrine-dopamine reuptake inhibitor bupropion using the EMBARC study.

The treatment-assignment algorithm that was developed generated two marker-based indications for each patient—one for bupropion and sertraline—with the predictive model achieving a cross-validated area under the curve of 0.86 and 0.66, respectively.

The team then examined whether antidepressant response could be boosted using their created biomarker combination of a functional MRI imaging marker, reward learning and sensitivity, cognitive control, the clinical variables of depression severity and neuroticism, and the demographic variable of employment status.

After analyzing these biomarkers among participants, who had major depressive disorder, the group was randomly assigned to receive a full 8-week course of an SSRI or non-SSRI.

The primary outcome was the change in depression severity from pretreatment baseline to eight weeks after the start of treatment, with no significant differences in treatment outcomes for those assigned a drug consistent versus inconsistent with their biomarkers.

This, the researchers say was possibly due to the limited power to detect moderate effects.

However, significant differences emerged in symptom reduction trajectories for those with positive markers for both medications, with a response rate of 71.4% compared with 65.4% for those with a positive biomarker for either drug and 42.9% for those with two negative markers.

The authors concluded: “We found that, relative to patients with two negative markers, those with one or two markers were characterized by significantly larger reduction in depressive symptoms, showing that biomarker-guided treatment selection can boost efficacy for two of the most widely prescribed antidepressants around the world.”

The post Biomarkers Could Help in Antidepressant Choice appeared first on Inside Precision Medicine.

South Korea’s hottest new bachelors are chip workers

Baek, a 35-year-old manager at the South Korean semiconductor titan SK Hynix, was enrolled in Sunoo, a matchmaking company based in Seoul, a year ago. In a move typical of anxious South Korean parents, his mother signed him up, hoping to find a good wife for her son.

Lately, says Baek (who asked to be referred to by his last name to protect his privacy), he and his coworkers are having better luck finding dates than they used to, perhaps because of the dazzling bonuses they just got. Flush with eye-popping profits from the AI chip boom, SK Hynix struck a landmark deal last year with its labor union to pay out 10% of operating profits to employees, which translates to an extra $476,000 per employee this year. A similar agreement and sizable lump sum followed for Samsung workers this May.

With their newfound wealth, chip workers like Baek have become the most sought-after bachelors and bachelorettes in South Korea. “I have a coworker who’s perpetually going on blind dates, and he’s been getting so many recently,” says Baek. “For the past few months, I’ve been getting many blind dates too, perhaps because of the bonuses I got.”

Lately, young South Koreans joke online that the best outfit to wear on a blind date is an SK Hynix uniform

The AI chip boom is changing the social fabric of South Korea by minting a new elite of “silicon-collar” workers earning about 20 times as much as the average South Korean. Although it’s helping some chip workers to find relationships, it’s also fueling fears of a deepening wealth disparity—and a loud public debate about inequality.

Love in the time of chips

South Korea is the epicenter of the chip boom fueling the AI race. Samsung and SK Hynix supply the vast majority of the world’s high-bandwidth memory (HBM) chips, which power Nvidia’s AI accelerators—the GPUs used to train AI models. As AI companies spend hundreds of billions of dollars on building data centers around the world, demand for HBMs is rising beyond what suppliers can keep up with, driving their prices to unprecedented levels. Samsung and SK Hynix are raking in record profits as a result. 

South Korea’s economy now orbits the two chip giants. In May, both companies topped $1 trillion in market value. And chip exports helped fuel a 1.7% surge in South Korea’s gross domestic product in the first quarter of 2026. South Korea’s main equity index, Kospi, has nearly tripled over the past year, becoming the best-performing market in the world.

Swimming in cash, chip workers are going on shopping sprees in department stores near the “semicon belt” fabs—splurging on everything from lavish furniture and electronic appliances to jewelry and watches. They’re also snapping up homes near the commuter-shuttle routes that ferry workers to campus. And they’re shelling out for matchmakers.

“Quite a lot of people ask me if I can introduce them to chip workers,” says Lee Sung-mi, a matchmaker at Sunoo, who has been playing Cupid for chip workers for years. “In fact, people who once rejected them are asking to be matched with them again, now that their salaries and bonuses have shot so far above what everyone else earns.”

One woman who lives in Gangnam, a ritzy district in Seoul lined with luxury high-rises and designer boutiques, previously turned down a chip worker at SK Hynix because his fab was too far out in Icheon, a rural city about 50 miles southeast of Seoul that’s dotted with rice farms and manufacturing plants. But in May, she asked her matchmaker to set them up again. They’ve now been dating for a month.                                                                                                                                                                                                                                                                                                                                                                                                                             

In South Korea, matchmaking companies evaluate their clients on a long list of criteria such as education, job, income, looks, and family background, including whether their aging parents have saved enough for retirement. In an economy where housing prices and child care costs are soaring, competition for jobs is fierce, and the social safety net is thin, a good job is the ultimate dating credential—all the more coveted at a time when many young South Koreans are forgoing marriage and children altogether, seeing family life as an unaffordable dream.

Every client at Sunoo gets a spouse rating, determined by an algorithm that assigns scores for each criterion. Since their hefty bonuses were announced, the job ratings of Samsung employees have risen from 80 to 84, while those of SK Hynix employees climbed from 78 to 82. Scores above 90 are reserved for doctors and lawyers. Long prized as paragons of prestige and wealth, they’re now close to being overtaken by chip workers. A score of 99, the highest possible rating, is earmarked for heads of state.  

Their new status is reshaping how chip workers themselves approach dating. “Chip workers from Samsung and SK Hynix are enrolling in our services because they feel more financially ready,” says Lee. “They’re also becoming pickier, as they feel like they’re now in a good position. The women want to meet men with higher incomes and better jobs, and the men want to meet younger and better-looking women with better jobs.” 

An SK Hynix engineer in her 40s, who was once desperate to get married as soon as possible, started turning down men she would’ve dated before the chip boom. Lately, showered with more matches, she’s been sifting through her suitors more carefully. “She now has peace of mind and wants to take her time to meet someone better,” says Lee.

A mixed blessing

While chip workers enjoy the fruits of their labor, the bonus bonanza is stoking anxieties among other South Koreans. “When wealth disparity is no longer a mere difference of income but, rather, a difference in identity … it can fuel social conflict,” says Se-eun Jung, an economist at Inha University. 

Earlier this month, the Bank of Korea warned that the chip boom will create a “K-shaped” economy, where a handful of workers race ahead while everyone else falls behind. The windfall, the bank said, is flowing to high income earners and then barely trickling out to the broader economy. Such polarization could erode people’s motivation to work by narrowing the path to upward mobility, it cautioned. 

Workers in other industries are venting online about feeling demoralized by the ballooning wealth gap. “The one-billion-won ($650,000) bonuses have crushed my motivation to work. I have no energy when I teach,” an employee of the Seoul Metropolitan Office of Education wrote on Blind, an app where employees can discuss their workplaces anonymously. Others are giving up the job hunt, lamenting that years of working at a small company could never match a year’s bonus at Samsung. 

In a Facebook post in May, presidential policy chief Kim Yong-beom proposed paying an “AI dividend” to citizens by taxing AI profits. The idea sparked a heated public debate over whether the government should redistribute gains from the chip boom. Some argue that the industry is indebted to the society that has educated its engineers, subsidized its infrastructure, and provided tax credits. Others counter that the profits are already being shared with the public as stocks.

Then there’s the question of how long this new social class will last. The semiconductor industry is notoriously cyclical; AI spending may cool, or rival chipmakers could catch up. There’s also the risk that chip workers will be replaced by automation. Samsung announced in March that it plans to fully automate its fabs by 2030, drawing backlash from chip workers. 

Although he doesn’t know how long the boom will last, chip workers like Baek are riding high. “These days, we say we want to work hard and bury our bones here [at SK Hynix],” he says. “And I hope I can find [a wife] similar to me.”

Opinion: The smart way to regulate the peptide boom

Americans are using peptide compounds (short chains of amino acids promoted for recovery, sleep, performance, metabolic health, and longevity) in large and growing numbers. Many obtain them from unregulated online sellers and informal markets, often without medical supervision, reliable quality controls, or accurate dosing information. Whether we like it or not, this is a mainstream reality, and it creates the very risks regulators seek to avoid.

With Kyle Diamantas now at the helm of the Food and Drug Administration as acting commissioner, the agency has a timely opportunity. Rather than choosing between unrestricted gray-market access or a blanket crackdown that simply drives use underground, the agency can chart a third way on peptides. 

Read the rest…

Opinion: Stopping doctors from ordering unnecessary diagnostic tests requires a structural fix

American medicine runs more than 14 billion tests a year. While some tests can be lifesaving, many are used at the wrong time or on the wrong patient and are useless or even harmful.

The medical industry has spent enormous effort making more advanced tests but expended little effort learning how to use tests correctly. There is a science for how to better use tests, diagnostic stewardship, but most doctors have never heard of it.

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STAT+: GOP lawmakers push Trump’s FDA to make sure clinical trials are diverse

WASHINGTON — Clinical trial policy got caught up in the Trump administration’s attack on policies related to diversity, equity, and inclusion. Republicans in Congress would like to change that. 

Days after Trump took office, the Health and Human Services Department began purging all references to DEI from the websites of its agencies. Those efforts were supposed to target DEI initiatives focused on hiring practices, communications, and social issues.

But supporters of clinical trial diversity say the policy has nothing to do with DEI in that sense. Instead, it aims to ensure that clinical trials enroll people who are similar to the patients who would use the drugs and medical devices being tested. 

Continue to STAT+ to read the full story…

STAT+: I spoke to Anthropic’s CEO about how AI may affect biotech. Here’s what I learned

The most convincing thing Dario Amodei, the CEO and co-founder of Anthropic, said to me during an on-stage conversation last week was that perhaps his original vision of how AI would change biotech might not start to be visible for a decade.

In a 2024 essay, “Machines of Loving Grace,” Amodei had argued that artificial intelligence, and in particular large language models like Anthropic’s Claude, could allow researchers to make what we think of as a decade’s worth of progress every year, covering a century in a decade. Now he admits we’re not there yet.  

“I don’t think that today we can make progress at a rate of ten years per year for a number of reasons,” Amodei said. Those included: Models aren’t as good as they someday will be; researchers need time to figure out how to use these tools; and the infrastructure and regulatory systems will take time to change.

Amodei and I were speaking at an Anthropic event where the company, a public-benefit corporation meant to be focused on improving the world, unveiled a product for biologists and pharmaceutical companies called Claude Science. I agreed to interview Amodei on-stage as part of the event, with the stipulation that I would decide on my own what to ask. 

Continue to STAT+ to read the full story…