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During the first wave of COVID-19, Hungary launched a large study called PROACTIVE-19. It started in March 2020. The focus was on adults aged 60 and older. These older adults faced higher dangers from the virus. Researchers wanted to know if phone-based lifestyle coaching could help them stay healthier. A total of 441 people took part. They were split into two equal groups. One group received general advice. The other received personalized coaching over the phone. The calls covered eating habits, exercise, smoking, alcohol use, and mental well-being. Because infection rates turned out lower than expected, the team tracked deaths from any cause instead of severe COVID outcomes. The results showed no big difference in death rates between the two groups. Still, many daily habits improved ov

In 1803, William Pickering first showed signs of serious mental trouble. His parents and seven siblings quickly sprang into action. They gathered hundreds of letters between themselves to track his condition. Initially they focused on keeping him safe at home. The family's response was swift and determined. Every letter revealed new details about his changing state. The family tried many approaches before giving up on home treatment. They shifted toward lifestyle changes and medical care. Then they found a physician who specialized in mental disorders. By 1807, they decided William needed professional help beyond the family home. He was sent to the Pennsylvania Hospital. This marked a turning point in his care. William passed away in 1814 while staying at the Pennsylvania Hospital. His b

Athletes often feel a sharp ache in their lower belly or groin. Doctors call this core muscle injury. It hits the inguinal canal, the RA-AL aponeurosis, and the pubic symphysis. These areas work together. When they hurt, movement suffers. There is no clear rulebook for naming or spotting this injury. That makes it hard for doctors to agree. It slows down care and research. Some call it one thing, others another. This confusion hurts patients. Finding the problem takes more than a quick look. Doctors must ask the right questions. They check how the body moves. They press on key spots. Then they use special MRI scans. These images show fluid near the injured tissue. That helps confirm the diagnosis. Different doctors treat it differently. Sports medicine docs may focus on rest and rehab.

A lot of teens and adults watch videos about type 1 diabetes on TikTok, Bilibili, and YouTube. Many of those videos get thousands of likes and shares. But popularity does not mean the information is correct. Researchers checked 263 videos and found that the most popular ones were not always the most reliable. Researchers used tools like mDISCERN, GQS, and JAMA benchmarks to grade each video. They wanted to know if the health advice was trustworthy. Videos posted by doctors or specialists earned higher scores than videos from everyday users. YouTube videos also ranked higher overall than those on the other two platforms. This gap matters because bad health tips can cause real harm. If a video looks cool but gives wrong guidance, viewers might follow dangerous steps. The study shows that h

Interest in catching type 1 diabetes early in children is growing. Presymptomatic screening programs and new disease‑modifying therapies are expanding. Yet the views of the professionals who actually implement these programs have not been pulled together. A team performed a systematic review to gather professional opinions on pediatric early screening. They followed PRISMA rules and searched six major databases plus grey literature up to January 2026. Twelve studies made the cut, most of them focusing on paediatricians and diabetes specialists. The review found that nurses, genetic counsellors, policymakers and other health workers appeared in only a few studies. Researchers used the Mixed Methods Appraisal Tool to judge quality. They spotted common problems such as small or unrepresentat

A single matchday in German soccer revealed a flood of betting ads. Researchers counted 18,708 gambling references. Most appeared on the electronic boards lining the pitch during live broadcasts. That means viewers saw betting messages constantly while watching the game. The study focused on nine matches from the 31st matchday of the 2024/2025 Bundesliga season. It looked at live television, pre-match shows, halftime segments, and commercial breaks. Two sports highlight programs were included too. For social media, the team reviewed ten sports betting accounts and searched the Meta-Ad Library. Paid social media ads mostly targeted young men. This is worrying because children and teenagers are vulnerable to gambling harm. Germany has a State Treaty on Gambling. The law says advertising mu

Doctors need to know if a patient is on parole or probation. This fact can shape the right care plan. But it is rarely in the structured parts of a health record. It usually lives in free-text doctor notes. Finding it by hand is slow and expensive. Privacy rules also make it hard to get enough real examples. A research team built a fake dataset named Synth-PPD. It contains 7,579 made-up clinical notes. Large language models wrote these notes. Filters removed duplicates. Automated checks judged quality. Two people then reviewed 1,517 of the synthetic notes. The goal was to train systems without needing real, expert-labeled data. The scientists tested the fake notes using several tools. They tried large language models, older machine learning methods, and transformer encoders. They looked

AI tools are showing up in clinics. They help write notes, talk to patients, and sort cases. But medicine is not always black and white. Some situations are ethically tricky. Different AI models might give different advice in those moments. That could change what a doctor decides to do. This matters for patient care. Researchers wanted to see how much these models disagree. They made 60 original medical ethics cases. The cases covered four topics. Three experts reviewed each case. They agreed on how hard it was and which ethical ideas mattered. Five AI models were tested. The list included GPT-5, Claude Sonnet 4. 5, Gemini 2. 5 Pro, DeepSeek-R1, and Meta Llama-3-8B-Instruct. A smaller model called DeepSeek-R1-Distill-Qwen-1. 5B was also tested on its own. Each model answered every case three

The researchers wanted to know how mental health clinicians see AI across the whole therapy process. They talked to 18 practitioners using a flexible interview guide. The conversations were later grouped into themes. Ethical issues were sorted using four standard biomedical principles. The project got approval from Lancaster University’s ethics board (ID 3530). When it comes to spotting problems, the clinicians said AI could be a helpful assistant. They imagined AI tools that sift through patient data quickly and flag patterns that humans might miss. In the diagnosis room, however, worries grew. Bias in the algorithms and the fear that human judgment could be sidelined were top concerns. Trust also played a big role; if clinicians didn’t feel confident in the system, they would likely ign

One AI finding was not what many might expect. Employees who perceived benefits from AI showed higher burnout. The link showed up both directly and indirectly. Greater quantitative job demands carried the indirect connection, linking perceptions of the technology to workplace pressure. Researchers gathered a snapshot of working life by surveying 3,488 employees in 11 Icelandic municipalities. They used the Burnout Assessment Tool to measure burnout. The survey covered AI use, organizational support, perceived benefits, AI-related worries and insecurity, and trust in ethical governance of AI. Hierarchical regression and mediation analyses examined the links, with age and gender taken into account. Psychosocial working conditions had the strongest relationship with burnout. When employees

Recent reviews reveal that money-focused discussions about migrant populations and health systems are surprisingly thin. While scholars frequently bring up expenses tied to medical treatment and hospital visits, they seldom ground those claims in hard data or formal economic models. This weakness leaves policymakers without clear numbers to guide fair decisions about who gets care and who doesn't. The literature shows two sides of the same coin. On one hand, cost issues dominate the conversation around migrant health outcomes. On the other hand, few studies provide actual measurements or rigorous economic evaluations to prove those points. The disconnect between theory and practice makes it hard to design truly inclusive health programs. Closing this gap requires teams from economics and