Its leaders were visible throughout the convention, participating in discussions on biopharma innovation, precision medicine, artificial intelligence, investment, genomics and policy. Partnership announcements emerged throughout the week. Delegations moved between panel discussions and private meetings with investors, entrepreneurs, researchers, and industry leaders. The message was clear. Abu Dhabi is making a strategic effort to become a notable player in biotechnology and the life sciences.

The timing is not accidental.

Around the world, governments increasingly view biotechnology as a strategic investment industry. Scientific innovation drives economic growth. Advanced therapeutics create new manufacturing opportunities. Genomics and precision medicine are reshaping approaches to disease prevention and treatment. Nations that attract talent, investment and scientific expertise position themselves at the forefront of one of the century’s most consequential industries and life-sustaining movements.

Abu Dhabi is determined to be among those countries.

Building the Innovation Foundation

Substantial investments and partnerships in infrastructure, research, education and health innovation support the Emirate’s ambitions.

In April 2025, Abu Dhabi launched the Health, Endurance, Longevity and Medicine (HELM) Cluster, an initiative designed to establish a globally competitive ecosystem spanning biotechnology, pharmaceuticals, medical technology, genomics, digital health, artificial intelligence and advanced manufacturing.

Officials project the initiative will contribute AED 94 billion to the economy by 2045, attract more than AED 42 billion in investment and create approximately 30,000 jobs.

Those figures reflect more than economic development goals. They signal a growing recognition that biotechnology is a cornerstone of future growth and global competitiveness.

The Emirate is not starting from scratch. Organizations including M42, PureHealth, Mubadala Bio, Khalifa University, and the Mohamed bin Zayed University of Artificial Intelligence have established a foundation that combines research, clinical capabilities, advanced analytics and investment resources. The UAE Genome Program has surpassed 900,000 sequenced genomes, making it one of the world’s largest population genomics initiatives and providing a valuable resource for scientific research and precision medicine.

These investments provide the ingredients necessary to compete. Partnerships provide the opportunity to accelerate progress.

Building Through Collaboration

Biotechnology has long been a collaborative enterprise among private equity and entrepreneurs, academic medicine and corporations, and, now, nations working side by side with other countries’ governments.

Scientific discovery depends on the exchange of knowledge among researchers, entrepreneurs, clinicians, manufacturers, regulators, and investors. No single country possesses every advantage. Successful ecosystems learn how to connect their strengths with those of others.

Abu Dhabi’s recent actions suggest its leaders understand this reality more than anyone else. They act on it.

During the BIO International Convention, the Department of Health – Abu Dhabi announced a strategic collaboration with Sanofi focused on vaccine development and life sciences innovation. The previous year at BIO in Boston, the Department established a partnership with Boehringer Ingelheim that expanded access to the company’s OpnME research platform, creating new opportunities for translational research and scientific discovery.

An additional 2025 agreement was signed with Abbott, focused on pharmaceutical innovation, manufacturing capabilities, and emerging technologies.

These were not isolated announcements. They represented a broader effort to connect Abu Dhabi with leaders across the global life sciences community. That strategy continued at BIO 2026.

On June 23, 2026, the Department of Health – Abu Dhabi announced a strategic partnership with Biocom California, one of the world’s largest life sciences associations representing more than 1,800 biotechnology, pharmaceutical, and medical technology organizations. The agreement creates a formal gateway between the California innovation ecosystem and Abu Dhabi’s growing life sciences sector, strengthening opportunities for collaboration among researchers, entrepreneurs, investors, and innovators across both markets.

The significance of the announcement extends beyond California. It reflects Abu Dhabi’s effort to connect itself to some of the world’s most influential innovation networks and to participate in the exchange of scientific knowledge, talent, and investment that increasingly defines biotechnology leadership.

Moving Up the Biotech Value Chain

If the Biocom agreement demonstrated Abu Dhabi’s commitment to global collaboration, a second announcement made the Emirate’s ambitions even clearer.

On June 24, 2026, the Department of Health – Abu Dhabi, M42, and Mammoth Biosciences announced a partnership to advance gene-editing therapies, clinical research, and advanced therapy manufacturing in Abu Dhabi. The agreement seeks to leverage insights generated through the Emirati Genome Program while supporting the development of next-generation treatments for inherited diseases.

This announcement stands out because it moves beyond ecosystem building and into the development of future therapies.

Mammoth Biosciences was co-founded by Nobel Prize-winning scientist Jennifer Doudna, whose pioneering work helped bring CRISPR gene-editing technology into medicine. Under the agreement, Mammoth will contribute its proprietary gene-editing platform, M42 will provide genomics, health, and clinical research infrastructure, and the Department of Health will support the regulatory and research environment needed to advance development.

The collaboration includes plans to introduce Mammoth’s lead clinical candidate, MB-111, into Abu Dhabi’s research ecosystem, support advanced gene-editing clinical trials, establish advanced therapy manufacturing capabilities, and develop local expertise through workforce training programs.

Perhaps most significantly, the partnership highlights how Abu Dhabi is leveraging its genomics investments. The Emirati Genome Program has created one of the world’s most comprehensive population genomics initiatives. The Mammoth agreement represents an effort to translate those insights into therapies targeting inherited diseases.

As H.E. Dr. Noura Al Ghaithi noted when announcing the partnership, Abu Dhabi is focused on translating genomic insights into therapies to address some of the most complex inherited diseases affecting populations in the region and worldwide.

Leadership Matters

The prominence of Abu Dhabi at BIO 2026 reflects sustained engagement from senior leaders. H.E. Dr. Noura Khamis Al Ghaithi, Undersecretary of the Department of Health – Abu Dhabi, and Dr. Mohamed Al Ameri, Division Director of Genome and Biobank at DoH, are among the officials representing the Emirate’s vision throughout the convention.

Their participation reflects a broader commitment. During Abu Dhabi’s 2025 strategic mission to the United States, approximately 40 representatives from 12 organizations attended more than 20 strategic meetings, conducted 16 institutional visits, participated in 9 BIO-related panels, and established 7 new partnerships and agreements.

Such activity underscores an important point. Building a biotechnology ecosystem requires more than investment capital. It requires leadership, patience, and a willingness to build relationships across borders and disciplines.

A Must-Watch Innovation Hub

For decades, discussions about biotechnology leadership have focused on a familiar collection of cities and regions. Boston, San Diego, Basel, London, and Singapore earned their positions through scientific excellence, entrepreneurial activity, and investment.

Abu Dhabi is pursuing a different path.

The Emirate is leveraging capital, scientific infrastructure, genomics, artificial intelligence, policy support, and international partnerships to establish a presence in the global biotechnology landscape. Its strategy recognizes that modern biotechnology advances through collaboration and that scientific leadership increasingly depends upon connecting talent, expertise, and resources across borders.

BIO 2026 demonstrated that Abu Dhabi is no longer simply expressing an ambition to participate in the life sciences sector. Through initiatives such as the HELM Cluster, partnerships with organizations including Sanofi, Boehringer Ingelheim, Abbott, Biocom California, and Mammoth Biosciences, and investments spanning genomics, research, and advanced therapies, the Emirate is laying the foundations for a biotechnology ecosystem with global aspirations.

Whether Abu Dhabi joins the ranks of the world’s leading life sciences hubs remains to be seen – but it should be watched closely. What is increasingly difficult to overlook is the depth of its commitment and the speed with which effort is being translated into action.

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The body remains, but the self doesn’t.

We understand something in those moments that we rarely say plainly. And perhaps, it’s time we put this idea front and center. Cognition isn’t merely something a person has, it’s something a person is.

Day after day, we become ourselves through the act of thinking. From the complex to the trivial, we traverse a reality that bumps and bruises us into personhood. And that friction isn’t an obstacle to identity, it’s how identity forms.

Aristotle understood this long before neuroscience provided a name for it. Character isn’t something we possess. It is something we create. What we think shapes what we do. What we do, repeatedly, shapes who we become. Which is why the question of artificial intelligence, at least to me, isn’t primarily a question about productivity or efficiency.

Of course, AI doesn’t arrive as a threat, it arrives as a relief. And that’s what makes it so insidious. There’s no cognitive check engine light to warn you. There’s just the comfort of a swift and almost effortless answer. The friction that used to shape you simply didn’t happen. Do that enough times and something changes, not dramatically, but in the way that habits shift things. Gradually, then all at once.

Technology has always extended human capability. The wheel extended our legs. Writing extended memory. The calculator extended arithmetic. But AI is different in kind, and not merely degree. It reaches into cognition itself, into the territory where “we” live—into the domain of judgment, understanding, and idenity. A calculator doesn’t threaten to do your becoming for you.

The neuroscientist Michael Merzenich is well-known for the mechanism that we today call neuroplasticity. Simply put, neural connections are strengthen when used and weakened when not. The brain adapts continuously to the demands placed upon it. This isn’t a lofty metaphor but measurable biology. The brain you exercise is not the brain you don’t.

But cognitive surrender isn’t a neutral act. Every decision handed off to AI are small withdrawals from the account of the self. Of course, handing the process over to a machine provides certain efficiency or even relief, but you step away from the mechanism through which you author, well, you.

There is a phrase, adapted from the Upanishads, that I alluded to earlier: as you think, so you act. As you act, so you become. This is doing more than describing habit. It is describing identity formation. We are not simply what we know. We are, in part, what we have struggled to understand.

The answers may still sound like you. What fills the space is not.

That’s the abyss. Not a dramatic fall, but a quiet retreat from the very process that makes a person a person.

I wrote about the Borrowed Mind as a possibility. Now, I think it’s worth asking, with some regularity, whether it has become a habit.

John Nosta is the author of the best seller:  The Borrow Mind—Reclaiming Human Thought in the Age of AI.

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Despite living longer than men, women spend approximately 25 percent more of their lives in poor health, according to research from the World Economic Forum and the McKinsey Health Institute. Across reproduction, brain health, autoimmune conditions, cardiovascular disease, and mental health, the gaps in research, funding, and care are persistent.

That reality provided important context for the launch of The Shift, a new mini documentary series from BBC StoryWorks Commercial Productions, unveiled at HLTH Europe. The series explores issues ranging from reproductive health and cardiovascular disease to autoimmune disorders, menopause, mental health and healthy aging. Through storytelling, the documentary project elevates the experiences of women while highlighting the challenges that persist and the opportunities for progress.

The HLTH EU panel discussion was timed for the opening of The Shift and featured Shahnoor Abbas, Senior Series Developer and Research Development Lead for The Shift at BBC StoryWorks Commercial Productions; Elena Bonfiglioli, General Manager, Global Health & Life Sciences at Microsoft, and Priya Agrawal, MD, Vice President, Global Health Equity and Partnerships at MSD. Their conversation, moderated by Jody Tropeano Greene, Head of Content for HLTH, explored why women’s health remains one of the most significant opportunities for innovation, investment and system improvement.

A Conversation Decades in the Making

The panelists approached the topic from different perspectives, yet a common theme emerged. Women’s health has received increasing attention for more than a decade, but many of the barriers women encounter remain rooted in the design of health systems.

For BBC StoryWorks, The Shift represents an effort to sustain attention on issues that too often receive episodic interest. The series combines personal stories with broader insights into the realities women face across different countries, cultures and stages of life.

The BBC initiative and the HLTH EU mainstage conversation arrive at a time when women’s health is attracting growing attention from investors, entrepreneurs, policymakers and health industry leaders. New companies are emerging. New technologies are being developed. More organizations are recognizing both the societal and economic importance of addressing longstanding gaps in care.

The timing of The Shift is notable. Women’s health innovation is receiving growing attention from investors, entrepreneurs, policymakers and health leaders. Industry analysts estimate that approximately $2 billion was invested in venture-backed women’s health companies across the United States and Europe in 2025, reflecting increased interest in addressing challenges that extend beyond reproductive health to include cardiovascular disease, menopause, mental health, oncology and healthy aging.

The trend signals growing recognition that improving women’s health is a societal imperative and a significant economic opportunity. Yet as the discussion at HLTH Europe made clear, investment and innovation alone will not be enough if women continue to face fragmented systems that are difficult to navigate.

When Access Exists but Navigation Fails

Dr. Agrawal, an obstetrician-gynecologist by training, whose work has included clinical practice in the UK NHS, global pharma brand stewardship in emerging middle-income nations, maternal health awareness initiatives, and the creation of sustainable health markets, described a reality familiar to many women. Access to care may exist on paper; however, reaching that care, understanding available options and navigating fragmented systems remains a challenge.

“We’ve built systems like mazes with different entry points, different providers and different messages,” said Dr. Agrawal. “Women are often left navigating all of this themselves at the moments where they are most vulnerable.”

Her observation echoed the comments by fellow panelists, which touched on an issue that extends beyond women’s health. Across many countries, patients frequently encounter disconnected providers, inconsistent communication and care journeys that require them to coordinate appointments, referrals and information on their own. The burden of connecting those pieces often falls on the individual seeking care rather than the system intended to support them.

For women, that complexity can be especially challenging. Responsibilities related to caregiving, work, family and personal health often intersect at the very moment care is needed. Understanding what symptoms are normal, knowing when to seek help, determining where to go and finding trusted sources of information become added obstacles.

That reality led to one of the discussion’s compelling observations. “This is not an access problem. It’s a design problem.”

The distinction matters. Discussions about women’s health often focus on whether services exist. Design asks a different question: can people realistically find, understand and benefit from those services when they need them most?

The Power of Stories to Sustain Change

The panel also explored the role technology may play in addressing those challenges. Rather than adding new layers of complexity, emerging digital tools and artificial intelligence applications are increasingly being developed to simplify navigation, improve continuity and support people between clinical encounters.

“What excites me is that technology is finally starting to reduce friction instead of adding layers of complexity,” Dr. Agrawal observed.

That perspective aligned with comments from Bonfiglioli, whose work at Microsoft focuses on helping health systems leverage data, cloud technologies and artificial intelligence to improve outcomes. Technology, however, was not presented as a solution on its own. The discussion repeatedly returned to the importance of human connection.

Those themes are central to the documentary series itself. BBC StoryWorks has built a reputation for transforming complex issues into compelling narratives that audiences can understand and relate to. Through The Shift, the goal is not merely to document challenges but to foster greater understanding of the experiences women face and the opportunities that exist to improve care.

Abbas emphasized the power of storytelling to connect data and lived experience. Statistics can identify a problem. Research can explain it. Stories help people understand why it matters and why action is necessary.

That may be the enduring value of The Shift. The series does not introduce a new conversation. Instead, it brings fresh perspectives to longstanding challenges. Through stories from around the world, the films remind viewers that behind every statistic is a person navigating the complexities of health and care. By fostering greater understanding and empathy, the series encourages health leaders, innovators and policymakers to view women’s health not as a periodic topic of interest, but as an ongoing priority deserving sustained attention and action.

The women featured throughout the series deserve more. The discussion at HLTH Europe reinforces that improving women’s health is more than developing new technologies and expanding services. It is also about creating systems that are easier to navigate, more responsive to people’s medical priorities and ultimately more human in their design.

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A growing body of research is connecting GLP-1 receptor agonists, the class of drugs behind brand names like Ozempic, Wegovy, Mounjaro, and Zepbound, to a serious eye condition that can cause permanent vision loss. The condition has a long medical name: non-arteritic anterior ischemic optic neuropathy, or NAION. Eye specialists sometimes describe it as a stroke of the optic nerve. And once the damage is done, there is currently no treatment that can undo it.

This article is not written to frighten you or push you off your medication without talking to your physician. Millions of people are benefiting from these drugs every day. But the question health experts are now asking out loud is this: when a rare side effect starts appearing in large numbers of people, does it stay rare?

What Are GLP-1 Drugs and Why Are So Many People Taking Them?

GLP-1 stands for glucagon-like peptide-1. These drugs mimic a hormone your gut naturally releases after eating. They slow digestion, reduce hunger, and help control blood sugar. Originally developed for type 2 diabetes, they became household names when studies showed they could also produce significant weight loss.

The popularity of these drugs has been extraordinary. Roughly 15 million people in the United States are currently taking GLP-1 medications, and that number keeps climbing. Many of these users do not have diabetes at all. They are taking the drug specifically to lose weight, often without a full picture of what the long-term risks might look like.

The Eye Condition No One Was Expecting

NAION occurs when blood flow to the front portion of the optic nerve is cut off or severely reduced. The optic nerve is the cable that carries visual signals from your eye to your brain. When that nerve loses its blood supply, even briefly, it can suffer damage that leads to permanent partial or total vision loss in that eye. Health authorities, including the World Health Organization, confirm that this vision loss is usually permanent.

The condition is not brand new. It was already known to affect adults over 50, people with high blood pressure, and people with diabetes. What caught researchers off guard was a cluster of cases appearing in people who had recently started taking semaglutide-based medications.

The alarm was first raised in 2024, when physicians at Massachusetts Eye and Ear, a Harvard Medical School-affiliated hospital, published findings in the journal JAMA Ophthalmology. Their retrospective study of more than 16,000 neuro-ophthalmic patients found that people with type 2 diabetes or obesity who were taking semaglutide had a significantly higher rate of NAION compared to those taking other medications. Among diabetes patients in the study, semaglutide users showed a hazard ratio of 4.28, meaning the risk of developing NAION was more than four times higher than in comparable patients on other glucose-lowering drugs.

A separate Danish and Norwegian study that same year, drawing on data from more than 424,000 patients with type 2 diabetes, found that once-weekly semaglutide use more than doubled the five-year risk of NAION compared to patients taking other diabetes medications.

A Small Percentage Times Millions of People

Here is where the math matters. NAION is classified as “very rare,” meaning it may affect up to 1 in 10,000 people. The European Medicines Agency, which regulates drugs across 27 countries, formally added this classification in June 2025, recommending that product information for Ozempic, Wegovy, and Rybelsus be updated to include NAION as a side effect. The World Health Organization issued its own safety alert shortly after.

But consider what “very rare” actually means when tens of millions of people are taking a drug. If even 1 in 10,000 semaglutide users develops NAION, and 15 million Americans are using GLP-1 medications, that translates to roughly 1,500 potential cases in the United States alone. And that figure is based on the most conservative estimate.

The American Optometric Association’s clinical guidance report put it bluntly: “There is a low risk of serious ocular side effects. But a low risk of a big number is a big risk.”

The University at Buffalo researchers who published a related case series in JAMA Ophthalmology noted something else that raised eyebrows. NAION almost always strikes one eye at a time. But some patients on GLP-1 drugs were presenting with the condition in both eyes simultaneously, which is considered atypical and potentially more alarming.

The Research Is Still Sorting Itself Out

To be fair, the picture is not entirely clear-cut. A large February 2025 retrospective study that pooled data from 37 million diabetes patients across 14 international databases found that semaglutide users showed about 14 to 15 NAION cases per 100,000 patients annually, and when compared to other GLP-1 drugs, the risk was not significantly different. This suggests the vision risk may apply to the entire class of GLP-1 medications, not just semaglutide specifically.

A separate large cohort study published in JAMA Network Open, covering 185,000 individuals on GLP-1 drugs, found a slightly higher risk of developing diabetic retinopathy, but a similar rate of NAION compared to those on other treatments. And two studies presented at the American Academy of Ophthalmology’s 2025 annual meeting offered conflicting signals: one tied GLP-1 drugs to increased NAION risk and diabetic retinopathy risk, while another suggested the drugs might actually protect against dry age-related macular degeneration.

Scientists are careful to note that none of the current evidence proves that GLP-1 drugs cause NAION. What exists is a statistically significant association that has now been observed across multiple studies, multiple countries, and multiple drug databases. That is enough to prompt regulatory bodies to act and researchers to dig deeper.

Who May Be at Highest Risk?

Physicians are paying special attention to patients who already have underlying vascular risk factors. High blood pressure, high cholesterol, diabetes, a history of cardiovascular disease, and a structural eye condition called a small optic disc are all considered risk factors for NAION independent of GLP-1 use. When these pre-existing vulnerabilities are combined with a medication that may affect blood flow to the optic nerve, the potential for harm may be higher.

The symptoms to watch for are specific and sudden: vision loss in one eye that seems to come on without warning, often noticed upon waking. There may be a dark or blurry area in part of your field of vision, or a sense that something has been “wiped away” in one corner of sight. There is typically no pain, which is part of why people sometimes wait before seeking care. Any of these symptoms should be treated as a medical emergency.

Where Things Stand Right Now

As of June 2026, the European Medicines Agency has updated its labeling requirements for semaglutide to include NAION. The World Health Organization has issued a formal safety alert. And a multidistrict litigation involving GLP-1 vision loss lawsuits was consolidated in the Eastern District of Pennsylvania in December 2025. Legal analysts report that over 1,800 lawsuits had been filed by mid-2025, with more expected as scientific review continues.

The U.S. Food and Drug Administration has not yet added a NAION warning to American drug labels for semaglutide. Novo Nordisk, which manufactures Ozempic and Wegovy, has not yet updated its U.S. prescribing information to reflect the risk. Public health advocates and some legal experts have called for a black box warning, the FDA’s highest-level alert.

The American Academy of Ophthalmology and the North American Neuro-Ophthalmology Society have both weighed in, stating that they do not recommend that all semaglutide users stop their medication immediately if they develop NAION, since the benefits of the drug may still outweigh individual risks, depending on the patient’s overall health. But both organizations agree that sudden vision changes of any kind require immediate medical evaluation.

What This Means for You

If you are currently taking a GLP-1 medication for weight loss or diabetes management, here are the most important things to keep in mind.

1. Do not stop your medication without talking to your physician. For many people, the health benefits of these drugs are substantial, and an abrupt stop can create its own risks.
2. Tell your physician if you have existing eye problems, high blood pressure, or a history of cardiovascular disease. These factors may influence how closely you should be monitored.
3. Take sudden vision changes seriously. If you wake up one morning and something looks wrong with one eye, that is not something to wait out. Call your physician or go to an emergency room. Time may matter.
4. Ask questions. Ask your physician whether NAION has been discussed in your care plan. Ask whether your specific risk factors warrant more frequent eye exams. You have the right to that conversation

The Larger Question

GLP-1 medications have been genuinely life-changing for many people. They have helped reduce the burden of obesity, lower cardiovascular risk, and control blood sugar in ways that were difficult to achieve before. None of that is in dispute.

But when a drug reaches the scale of tens of millions of users, even rare side effects become a public health question. A risk that affects fewer than 1 in 10,000 people in a clinical trial still produces thousands of real individuals with real and permanent vision loss when multiplied across the population taking these drugs. Those individuals deserve answers, updated labels, and the chance to make informed decisions before the lights go out.

Research is ongoing. Regulatory conversations are happening. In the meantime, staying informed, staying in communication with your physician, and taking any sudden change in vision seriously are the most important steps you can take.

The post The Weight-Loss Drug Nobody Warned You About: When the Scale Goes Down, and Your Sight Goes With It appeared first on Medika Life.

Diabetes

40 million Americans have diabetes mellitus, or 12% of the population. Of these 38 million have type 2 diabetes (previously known as “adult onset”) and 2 million have type 1 (previously known as “juvenile diabetes.) 29 million have been diagnosed, yet 11 million are unaware that they have the disease. Our focus is type 2 diabetes.

Diabetes type 2 incidence increases with age, such that nearly 30% of those over 65 have diabetes, compared to ages of 40 to 59 with a 12% incidence, and 4% for those under 40.

Of great concern is the rising incidence over time. In 2000, a total of 8% of Americans had diabetes. This has risen to about 12% or a 50% increase in just two decades. Some would term this an epidemic. Of further concern, many young people are now developing diabetes.

Diabetes substantially increases the risk of multiple diseases. Among them are blindness, kidney failure (the most common reason for a kidney transplant is diabetes damage), cardiovascular disease, including heart attacks and strokes, loss of sensation in the feet and lower legs (neuropathy and paresthesia), reduced vascular supply to the lower legs and the feet, often resulting in amputation of toes, feet, or legs, and Alzheimer’s disease.

Diabetes and its associated diseases combined cost America $640 billion per year, or 25% of all healthcare spending.

The major risk factors for type two diabetes include being substantially overweight, having a family history, being inactive or sedentary, and being over the age of 45.

You can’t change your family history. But your genes need not be your destiny. The basics of prevention include losing weight, increasing activity, eating healthy foods, and substantially reducing the intake of ultra-processed foods.

Diabetes and Alzheimer’s disease

Type 2 diabetes increases the risk of Alzheimer’s disease by 50 to 65%. It’s a shared risk factor with increased blood pressure and increased cholesterol, all leading to brain cell inflammation.

The increased risk of diabetes correlates with insulin resistance not only throughout the body but also in the brain. Some scientists think that brain insulin resistance is separate from the resistance in other parts of the body, and as a result, use the term “type 3 diabetes” as a synonym for Alzheimer’s disease. The brain cells are in effect “starved” for glucose, which is the neurons’ principal source of energy, despite plenty of glucose circulating in the bloodstream.

Insulin resistance of brain cells is associated with increased oxidative stress and neuroinflammation, which in turn leads to neurodegeneration.

Bottom line — reducing the possibility of developing diabetes markedly reduces your chances of developing Alzheimer’s disease. Diabetes begins with prediabetes, so the place to start your preventive work is there.

Prediabetes

115 million Americans have prediabetes. 81% do not know it. 18% of teens have prediabetes, and this number is on the rise.

The typical person with prediabetes is overweight, has excess belly fat, and is sedentary. They tend to eat a diet high in sugar and foods that are quickly digested into sugar, as well as ultra-processed foods. Many will also have a family history of diabetes.

Those with prediabetes have a 5–10% chance of progressing to diabetes each year, which accumulates so that in 3–5 years, 15–30% will have developed diabetes. And, if followed for enough years, up to 70% will progress.

Prediabetes is diagnosed by measuring your average blood glucose over the course of 2 to 3 months. This is done with a test called A1c, a blood test that can be drawn at any time of day. If the A1c is between 5.7% and 6.4%, that is diagnostic of prediabetes. If it’s 6.5% or higher, that’s diagnostic of diabetes. As noted, most people with prediabetes don’t know it. However, the A1c test is simple and inexpensive. If you have any of the risk factors for prediabetes, it’s well worth your while to have the test. Your doctor may order it at your annual evaluation. Ask to have it done and then ask for the result.

Knowing you have prediabetes is essential because the progression to diabetes can be reversed with lifestyle changes. Yes, these can be challenging, but they are well worth the time and effort so that you do not progress to diabetes and all of its downstream complications, including dementia.

The other reason to reverse prediabetes is that it is not a benign condition. It is silent but causes trouble over time. Prediabetes leads to slow but long-term damage to blood vessels, the heart, and the kidneys. Prediabetes can be part of the metabolic syndrome — a combination of any three of elevated blood sugar, high blood pressure, high LDL cholesterol and low HDL cholesterol, elevated triglycerides, and excess belly fat. These conditions in combination lead to diabetes, heart disease, stroke, fatty liver disease, and cognitive decline.

Although usually not measured, the underlying problem is the early stages of insulin resistance when the pancreas can still compensate by producing excessive insulin to overcome the resistance. Once it can no longer do that, blood glucose remains high, and you now have diabetes.

Reversing prediabetes

The good news is that you can reverse prediabetes back to normal. The steps are straightforward and usually do not require medication. Since prediabetes develops because of being overweight, being sedentary, and eating too much sugar and foods that readily convert to sugar, the steps are straightforward.

Check your waist-to-height ratio. Your waist should be less than 50% of your height. Details here.

Losing just 5 to 7% of body weight will reduce the risk of progressing to diabetes by 50%. For a 200-pound person, this is only 10–14 pounds. The second step is to get about 150 minutes of aerobic exercise each week. A brisk 30-minute walk five days a week will suffice. Add resistance exercises 2 to 3 times per week.

The third step is to eat a low-glycemic (meaning food that does not digest to sugar rapidly and thereby leads to rapid increases in blood sugar — think candy, ice cream, cakes), micronutrient-dense diet that includes increased fiber intake, non-starchy vegetables (for example, dark green veggies), whole grains (whole wheat, brown rice), legumes (beans and lentils), lean meats, fish, eggs, nuts, and avocados.

It is very important to reduce sugary drinks and high-sugar foods, such as pastries, pies, and ice cream. Eating only whole grains means no products made from white flour, such as white bread, most prepared cereals, pastries, and donuts.

Avoid ultra-processed foods, as they contain high levels of sugar, salt, and white flour. Ultra-processed foods themselves are linked to dementia. It is also important to get adequate sleep and to reduce chronic stress.

It’s a good idea to monitor your progress with continuous glucose monitoring. It will show you whether certain foods cause spikes in blood sugar and how exercise affects it. These monitors are now available at most pharmacies.

These lifestyle changes can reverse prediabetes within a few months.

You want to get your A1c level down, not just to the upper limit of normal at 5.6, but lower still, because the cutoff from normal to prediabetes, although highly useful, is still a static number. You want to be well under the top limit of “normal.”

Some people have tried but cannot lose weight or can’t keep it down after losing. They often benefit from using a GLP1 drug such as Wegovy (semaglutide) and Zepbound (tirzepatide). For many people, these have proven highly valuable. A word of caution. Weight loss usually includes both fat and muscle, so you need to do resistance exercises to counteract muscle loss. Once started, many people need to continue indefinitely, otherwise they regain weight, fat, but not muscle.

It is to your definite advantage to learn if you have prediabetes and then to do what is needed to reverse it. Habits can be difficult to modify, but the benefits are so great that the time and effort are well worth it, including a major risk reduction in dementia. And remember, it is never too late to get started.

With thanks to retired long-time expert diabetes educator Charlene Freeman, RN CDE CPT

The post Diabetes Is a Major Risk Factor for Dementia. 115 Million Americans Have Prediabetes. appeared first on Medika Life.

Health care is not short on ideas. It is not short on innovation, intelligence, technology or ambition. What it risks losing is focus on why those ideas matter and who they are meant to serve.

That concern shaped a fireside conversation with Tom Lawry at the Digital Health & AI Innovation (DHAI) Summit. Tom and I came to the stage from parallel and connected bodies of work. He is a best-selling author, the author of Health Care Nation: The Future Is Calling and It’s Better Than You Think, Hacking Healthcare and his classic, AI in Health: A Leader’s Guide to Winning in the New Age of Intelligent Health Systems.

Tom is one of the most respected voices on artificial intelligence and health information. My own book, Healing the Sick Care System: Why People Matter, another bestseller, looks at health care through the lives of patients, families and clinicians navigating a system that can be brilliant in moments and bewildering in motion.

Two Books, One Shared Concern

Our books were already in conversation before we arrived at the Summit. Tom wrote the Foreword to Healing the Sick Care System: Why People Matter, and I wrote the back-of-book review for Health Care Nation. We had each recognized the connection between the two. Readers, however, often encounter books separately. One may see Tom’s as a system-level call to redesign health care and mine as a people-first call to restore humanity to care. On stage, with an audience ready for the discussion, the relationship became easier to feel and internalize.

One book shares why the system must change. The other asks who that change must serve. Together, they return health innovation to the question that should guide every decision: whose life is made better because we invent?

That question was at the heart of Amir Lahav’s DHAI Summit. Curated by Amir Lahav, PhD, the Summit brings together people across artificial intelligence, digital health, health systems, research, investment and care delivery, from industry leaders such as Amazon Web Services, represented at the Summit by its Global Chief Medical Officer, Rowland Illing, MD, to trade groups like the Decentralized Trials Research Alliance championed by Craig Lipset, co-chair, and companies such as MassiveBio, an AI-powered platform to match patients to 19,000+ oncology and hematology trials worldwide, represented by Arturo Loaiza Bonilla, MD MSEd, are harnessing information to advance science and save lives.

Lahav’s achievement is far more than assembling experts. He has created a setting where different parts of the health community can bench-test their thinking against one another.  The action on the mainstage spills over to the hallways and receptions. That matters because AI in health cannot mature within a single discipline. Data scientists need clinicians. Clinicians need workflow support. Innovators need patient insight. Investors need to understand adoption. Health system leaders need to know when technology solves a problem and when it adds another layer of friction to an already complex ecosystem.

The audience brought energy to the room because the topic was more than technical. People wanted to talk about what AI makes possible. They wanted to talk about what health care cannot afford to forget. Health has become transactional. The operational aspects of care carry more friction than compassion. Patients are asked to coordinate their care across portals, referrals, insurance prior authorizations, clinical handoffs, and delayed communication. Clinicians are asked to heal while absorbing new layers of documentation, digital alerts, measurement and workflow pressure.

That is the context in which AI enters health care.

AI is curated knowledge and amplified pattern recognition. It can search for information no person could hold alone. It can surface signals, compare data, support decisions and make complexity more manageable. Used well, it can help clinicians, researchers, health systems and patients see what might otherwise remain hidden.

Harvey Castro, MD, MBA, a physician futurist and AI health-care innovator, understood that connection. He shared that he was heading to Portugal to speak on AI and health care, and that he would be reading Healing the Sick Care System during this flight. His encouragement reflected what made the Summit meaningful. The conversation was not ending with our fireside chat. It was traveling with people who are carrying the future of health AI into new rooms, new audiences and new decisions.

Insight, however, is different from wisdom. A pattern is different from a person. A recommendation is different from a relationship. AI can help reveal possibilities. People must decide how those possibilities impact the realities of illness, fear, family, access, culture and care.

That is where Tom’s work and mine meet. Health Care Nation asks why a country with extraordinary science, clinical talent, and technology continues to struggle with fragmentation, costs, incentives, and uneven access. Tom challenges the habit of waiting for someone else to fix what is broken. Policymakers, executives, payers, providers, employers, innovators and citizens all shape health care through choices, incentives, habits and expectations.

Healing the Sick Care System: Why People Matter starts from the same concern through the experience of a person seeking and delivering care. It asks what happens when a system with remarkable capabilities becomes so difficult to navigate that professional burnout leads to abdication, shifting more of the confusion, delay and uncertainty onto the very people seeking care. It looks at what care feels like when people seek treatment yet still feel lost, when they meet skilled professionals yet leave without understanding the next step, and when they are surrounded by technology yet feel lost and alone.

When Innovation Forgets the Person

Health care does not lack brilliance. It has extraordinary science, dedicated professionals, ambitious innovators and vast resources. Yet brilliance loses force and investment loses meaning when the system becomes more focused on transactions than on the people seeking care.

Soner Haci, CEO of PONS, captured that spirit after the session, writing that the story Tom and I shared was exactly why PONS was founded. His response mattered because it connected the fireside conversation to entrepreneurial purpose. Strong health companies often begin with the recognition that a problem people have learned to work around should no longer continue.

That is also why Lahav’s careful curation mattered. The Summit gave innovators a place to discuss more than what can be built. It invited people to consider whether what is being built is useful, human and ready for the realities of care. In health, possibility is never enough. The measure is whether the possibility improves the experience of the person seeking care and the person trying to provide it.

Tom is especially conscious of how many health professionals experience new technology. AI may be introduced as an aid, yet it can feel like another responsibility added to an already strained workflow. When a tool requires more clicks, more documentation, more review or more mental switching, it becomes one more demand on the people it was meant to support.

That concern should be central to the AI conversation. Implementation matters as much as innovation. AI earns trust when it reduces burden, fits the rhythm of care and gives clinicians back time for judgment, conversation and healing. A tool that adds work, noise or uncertainty to care has missed the purpose of health innovation.

Leanne West, innovation catalyst, patient advocate, connector, Chief Engineer of Pediatric Technology at Georgia Tech, and President of the International Children’s Advisory Network, reflected on LinkedIn that the fireside discussion was “speaking my language.” She highlighted a line from Healing the Sick Care System, that doctors should be people first and doctors second. Her reaction captured why the discussion resonated. The audience heard an AI conversation that kept returning to people.

That return to people is not sentimental. It is central to the challenge. People navigating illness often understand system failure with painful precision. They know where the instructions were confusing, where the portal failed, where follow-up disappeared, where a handoff became a gap and where no one seemed accountable for the whole experience.

Communication belongs in the same conversation. In health care, silence changes the experience. Confusing instructions, disconnected portals, delayed follow-up, fragmented records and unanswered questions become part of how people remember care. AI and digital health can help by making communication more useful, timely, and understandable. The goal is better understanding, not more automated volume.

Prevention also belongs in the same conversation. Health Care Nation argues that the health of people and the nation are inseparable. A country cannot continue spending enormous resources on illness while underinvesting in what helps people stay well. Healing the Sick Care System reaches that point through the patient’s experience. People should be seen, supported and guided before their physical and mental health reaches the snapping point.

This is the power of DHAI. Amir Lahav created a space where AI was discussed in the context of health’s larger obligation. Lahav even hosted a panel on pediatrics, where adults and children as young as six sat together on the mainstage, offering counsel. The conversation was not limited to algorithms, platforms or market opportunity. It asked whether innovation can reduce friction, protect health professionals, support patients, strengthen communication and make care more human.

Those are the questions that move AI from novelty to value. Can it help identify risk earlier? Can it make information easier to understand? Can it reduce administrative burden? Can it help match people to appropriate care? Can it support better conversations? Can it give clinicians back time to listen, think and guide? Can it help people feel less alone, less confused and more supported?

Together, Tom’s book and mine point toward priorities that health leaders should keep close: build around people, invest in prevention, reduce friction, protect clinicians, align incentives, listen to patients, measure outcomes and use technology wisely.

AI as Insight, Not Replacement

AI will not repair a fragmented system on its own. If incentives remain misaligned, AI may optimize the wrong outcomes. If patients remain peripheral, AI may scale impersonal care. If communication remains broken, AI may create more messages without creating more meaning. If trust is treated as an assumption, people will resist new tools for understandable reasons. This is why people absolutely matter.

The future worth building is hopeful. AI can help us see patterns earlier, connect knowledge faster and support better decisions. It can help researchers, clinicians and health systems work with greater insight. It can help people move through care with less confusion and more support. Its value grows when insight is joined with human judgment.

That was the heart of our fireside conversation, and that was why the audience response was powerful. We are not lacking ideas. We are not lacking innovation. We risk allowing health care to become ever more transactional at the very moment when technology should help us make it more connected, understandable and humane.

In Health Care Nation, Tom Lawry reminds us that we must stop waiting for someone else to fix the system. Healing the Sick Care System reminds us that every improvement must be judged by the lives of the people seeking care and the people providing it. These are companion calls to action.

“The future is calling,” as Tom writes. It may indeed be better than we think. It will become better when insight is joined with empathy, when innovation is guided by purpose and when the people touched by health-care systems shape what comes next.

AI can help us see more. People must decide what to do with what they see.

The next chapter belongs to us.

The post Health AI Faces a Human Test appeared first on Medika Life.

It goes without saying that artificial intelligence has digitalized everything these days, including the healthcare sector—ranging from mental health chatbots to health assessment and monitoring tools. While these tools are impressive in terms of quality and speed, many users may abandon them after initial use. Alternatively, there may be a lack of sufficient trust in user data privacy, and this inability to capture consumer trust can leave product developers disheartened. These are just a small fraction of the challenges and issues that the digital health sector faces today.

These concerns are not merely theoretical assumptions. Recent digital health industry reports show that sustaining user engagement and retention remains one of the most critical challenges in this field. Despite heavy investments in developing technical and AI capabilities, many digital health startups face high drop-off rates and declining user engagement after the first few weeks of use. Recent reports from Rock Health and Deloitte have also shown that trust, user experience, and user-perceived value are among the most critical factors determining the success or failure of digital health solutions.

Let us dissect the core challenge a bit more deeply.

The reality is that the ultimate success of digital health tools does not depend solely on their technical prowess, even though the most precise mathematical calculations are designed and implemented by elite engineering teams to build these tools. Rather, their ultimate success depends on the quality of the user’s “cognitive,” “motivational,” and “behavioral” experience. In other words, the core issue is not simply “what the AI knows” and how fast it delivers it to users; the golden nugget is “how the human interacts with the AI.”

In the previous article or part one, the importance of “learning sciences” in developing “human-centered AI” in digital health was discussed. I highlighted the crucial point that the missing link in AI technology, including digital health, is the absence of a vital foundation known as the learning sciences. The present article is an operational continuation of that discussion, attempting to demonstrate how the learning sciences can serve as a framework for designing cognitive and behavioral experiences in AI-driven digital health tools.

In this article, I offer recommendations that are more operational in nature for manufacturers and designers of AI tools within the digital health industry.

Learning Sciences as the Foundation for AI Design in Digital Health

The learning sciences and psychology of learning consist of a body of findings and theories regarding how a relatively permanent change occurs within an organism or learner. These changes depend on various internal and external factors. Furthermore, this change involves the learner’s cognitive, behavioral, motivational, and physiological dimensions.

With this simple description, it becomes clear that the learning sciences are not limited strictly to educational environments. Because they study the processes of cognition, attention, motivation, mental engagement, feedback, self-regulation, and behavior change in human-environment interaction, the learning sciences are vital wherever learning, interaction, action and reaction, or behavioral continuity are involved. They aid us in understanding the behaviors, motivations, cognitions, and perceptions of learners.

Especially in the era of AI, the science and psychology of learning demand deeper immersion and greater precision in constructing AI tools. This urgency arises from growing concerns that these tools may not be human-centered, neglecting the existential dimensions of the human being as the primary user.

One of the most important areas of AI application is digital health. The learning sciences can serve as a necessary prerequisite in AI design, acting as both an interpreter and a facilitator.

In what ways are they a prerequisite for AI and digital health?

They are a prerequisite because digital health tools can themselves be viewed as environments for learning and behavior change—environments where users are constantly interpreting information, making decisions, regulating behavior, and building trust. Many current digital health tools, despite their technical complexity, are not designed based on the cognitive, behavioral, motivational, and transactional complexities of human beings.

Some users have reported that the explanations provided by AI systems were ambiguous, complex, or even confusing to them. This finding aligns with the World Health Organization (WHO) report on the ethics and governance of artificial intelligence for health. The report emphasizes that explainability is only valuable when it is understandable to the end-user, as overly complex explanations can themselves become a factor in reducing trust and increasing confusion.

In certain studies, users have stated that they cannot comprehend the system’s decision-making logic and are forced to simply trust or distrust its output blindly. In many cases, the user eventually abandons these tools after a while—a reaction that a learner might similarly display in an AI-driven educational environment!

These and similar problems demonstrate that providing information clearly and orderly is not enough on its own. The interaction must be meaningful and comprehensible within the user’s cognitive dimension; the tool must understand the user’s behavior and reinforce their motivations. As a result, continuous, purposeful interaction and trust will be fostered. It is precisely through purposeful interaction and trust that the tool becomes useful and works in service of the consumer (or the learner).

Designing Tools Aligned with the User’s Cognitive Dimension

As previously stated, the human being is a creature of interwoven, complex dimensions. According to psychological and especially learning theories, a major part of the learning process occurs mentally within the dimension of cognition. Therefore, understanding the formula of learning and its cognitive dimension is an essential blueprint for designing digital tools.

For instance, in the human learning process, an unfamiliar and unknown topic transitions into a familiar one through distinct stages. This process can typically occur via mental stimulation and environmental support. If this learning is deep and meaningful (rather than superficial or based on rote, parrot-like memorization), it can be recalled for a long time, and the likelihood of forgetting is minimized.

The science of learning encompasses cognitive theories that emphasize concepts such as perception, meaningfulness, the integrated whole, problem-solving, scaffolding, and similar ideas. If designers implement these abstract concepts operationally, they can achieve practical results, including solving the following issues:

1. Information Overload: One of the most significant challenges in digital health tools is information overload. For example, in some studies conducted on chronic disease monitoring platforms, users reported that a high volume of simultaneous notifications, charts, and recommendations led to mental fatigue and a decreased willingness to continue usage. Researchers describe this phenomenon as a type of Cognitive Overload, which can even degrade the quality of health decision-making. Users often interact with these tools under conditions of stress, anxiety, or mental exhaustion. In such states, presenting a massive volume of data, alerts, or advice simultaneously can induce cognitive fatigue, confusion, and reduced decision-making quality.
2. Complex Explanations: In some research, users of AI-driven health systems reported that overly complex explanations did not increase their trust; instead, they heightened anxiety, hesitation, and mental strain. These findings demonstrate that successful cognitive design does not mean providing more information, but rather reducing mental strain and facilitating user comprehension.
3. Sustaining Attention: Maintaining users’ attention and mental engagement is another major challenge in digital health. Many health applications are abandoned by users after a short period. Reviews published in the mHealth sector show that a significant portion of health app users severely reduce or entirely stop their interaction within the first three months. This indicates that initially acquiring a user and retaining their cognitive engagement for continuous use are two completely different challenges. Part of this issue stems from the interaction experience becoming repetitive, impersonal, and cognitively tedious. The missing goal here is the personalization of the process!
4. Gradual Adaptation: On the other hand, altering a user’s attitude and perception is typically a gradual process, not an instantaneous one. Yet, some digital health tools deliver a large volume of recommendations and information abruptly, without accounting for the user’s gradual learning and adaptation process. Learning sciences can help design experiences that create progressive, sustainable paths for shifting attitudes and beliefs toward a process or a tool, rather than applying sudden pressure.

Designing Tools with Regard to the Users’ Behavioral Dimension

As noted earlier, learning involves permanent changes in behavioral potential. Therefore, if a change occurs in the users’ cognition and attitude, we expect to see corresponding changes in their behavioral performance as well.

The learning sciences introduce frameworks to help us understand when and how a behavior becomes consolidated. How, and under what conditions, can we successfully navigate the channel of user cognition, establish a positive attitude toward using a tool or smart test, and ultimately compel them toward stable, purposeful behavior?

The psychology of behavior, as a branch of the learning sciences, steps in at this stage to assist digital tool designers. It prescribes that the formation and continuity of behavioral learning follow specific stages. Therefore, you must clearly define the behavioral prescription you intend to instill in the user:

For instance, in many diabetes management or weight loss programs, merely presenting information about an individual’s health status has not led to behavior change. Studies have shown that when tools provide features for gradual goal-setting, self-monitoring, and continuous feedback, the probability of forming sustainable health behaviors increases.

In short, determine what the target behavior is and define it clearly. Through what stages and micro-steps does this behavior form? What types of feedback and responses guide the user toward the final target behavior? Once the target behavior is formed, what factors or feedback mechanisms can sustain it? And based on what metrics can we determine that the user’s behavior and its continuity result from the proper functioning of the tool?

Furthermore, because our objective is to build human-centered AI and tools, we do not intend to control the user. Instead, we aim to reinforce healthy attitudes and behaviors by boosting their sense of self-efficacy and perceived control over their health journey. In doing so, we guide their behavior and choices along the right path, aligned with the human blueprint.

In fact, one of the growing concerns in the literature on AI in healthcare is the reduction of Human Agency. Some experts have warned that if systems replace human decision-making rather than enhancing it, cognitive dependency and diminished independent judgment may lead to unintended consequences. Hence, the goal of human-centered design must be user empowerment, not user replacement.

Additionally, creating sustainable behavioral habits requires progressive interaction, continuous feedback, and a design that adapts to the real-world context of users’ lives. Tools designed without considering the cognitive and social conditions of the user frequently fail to yield lasting change. Understanding behavioral science and the factors influencing the reinforcement or weakening of a response helps designers correctly guide user behavior while identifying and controlling potential confounding variables inherent in digital tools.

Designing Tools Aligned with the User’s Motivational Dimension

Precisely when some neuroscience specialists argue that everything occurs at the level of cognition and that all other complex human aspects are overshadowed by it, the learning sciences (of which neuroscience is only a part) tell us it is not that simple!!! Learning an idea is a process. If we want a meaningful idea—such as using a health monitoring app—to transform into a highly repetitive, sustained behavior, we must account for other human dimensions as well!

“Trust” is one of the most critical factors in the adoption and motivational continuity of digital health tools. However, trust is not built solely through technical transparency. Users need to feel that the system is understandable, predictable, and psychologically safe.

Several studies have shown that complex or overly technical explanations fail to build trust and instead trigger greater anxiety and confusion among users. Moreover, concerns regarding privacy, data sharing, and the secondary use of health data represent major drivers of distrust among users. In digital health, trust is not merely a technical issue; it is part of the relational experience between the human and the system. For this reason, user experience design must consider psychological safety and relational trust alongside technical security.

Why is trust important? Because it is the loop that connects a user’s cognition, beliefs, and attitudes to their actual behavior! It generates the necessary motivation for follow-through, and ultimately, consolidates a behavior.

Findings from studies conducted on mental health chatbots indicate that anxiety over how personal data is stored, secondary data use, and a lack of transparency regarding data ownership are primary factors driving down user trust. In many instances, users evaluated the perceived quality of the relationship with the system as even more critical than the technical complexity of the algorithm.

While many digital health tools focus heavily on delivering information, possessing information does not automatically translate into the “motivation” required for behavior change. If the user does not feel capable of performing the recommended behavior, the likelihood of continued system utilization drops.

Alongside trust as a motivational component of user behavior, one of the most foundational concepts in the psychology of learning is “self-efficacy.”

Extensive research in health behavior change demonstrates that individuals who believe they possess the capacity to execute recommended actions are far more likely to initiate and maintain the new behavior. Consequently, successful design does not stop at giving advice; it must craft an experience where the user can taste small but meaningful victories.

Self-efficacy refers to an individual’s belief and confidence in their own abilities to organize and execute the courses of action required to achieve a specific goal. This psychological attribute can be modulated via controllable, situational feedback, and AI designers can leverage it as a key lever to impact human motivation.

In a digital health environment, this motivational characteristic can serve as the driving force behind consumer behavior when interacting with smart medical tools. Therefore, AI-driven tools must be capable of reinforcing a sense of empowerment and progressive mastery in the user, rather than merely broadcasting a barrage of alerts and directives. Studies indicate that users achieve more sustainable, satisfying engagement with health systems when feedbacks are personalized, actionable, and contextualized within the actual reality of their daily lives.

Feedback itself is only effective when it is timely, clear, and meaningful. Generic, non-actionable feedback—such as vague lifestyle advice—typically exerts a highly limited impact on behavior change. Conversely, contextualized, action-oriented feedback can significantly heighten both the cognitive and motivational engagement of the user.

Expected Operational Implications for Design and Development Teams

Many digital health tools still focus predominantly on algorithmic performance and technical functionalities, whereas the sustainability of human-system interaction relies on the quality of the cognitive and behavioral experience—and, of course, the motivational loop that links cognition to behavior and drives its continuity.

The learning sciences and psychology of learning can empower design and development teams to move far beyond the mere metrics of “ease of use” and “time management.” This shift is the most vital achievement of a cognitive, motivational, and behavioral architecture governing human-AI interaction.

This issue holds particular urgency for startups, product design teams, and digital health developers; the true success of these tools does not hinge on the sheer number of features, but on their capacity to preserve sustained engagement, secure trust, and guide human behavior change.

The learning sciences offer a framework to design tools that are not just usable, but comprehensible and justifiable within the users’ cognitive schemas. It shapes and directs user behavior under their own autonomy through self-regulation mechanisms, supplies the motivational loops connecting thought to action, and stabilizes user behavior.

Perhaps the most definitive question for the future of digital health is not how much smarter artificial intelligence will become, but rather how much better it can comprehend human cognition, motivation, agency, and behavior. Ultimately, the most successful tools will not necessarily feature the most advanced algorithms, but those that possess the deepest understanding of the human being.

References

Bandura, A. (1997). Self-Efficacy: The Exercise of Control. New York: W.H. Freeman.

Schunk, D. H. (2020). Learning Theories: An Educational Perspective (8th ed.). Pearson.

Hergenhahn, B. R., & Olson, M. H. (2015). Theories of Learning (7th ed.). Pearson.

Zimmerman, B. J. (2002). “Becoming a Self-Regulated Learner: An Overview.” Theory Into Practice, 41(2), 64-70.

Deloitte. (2024). 2024 Global Health Care Outlook.

Deloitte Center for Health Solutions. (2024). Digital Transformation and Consumer Engagement in Healthcare.

Rock Health. (2024). Digital Health Consumer Adoption Survey.

Blease, C., Kaptchuk, T. J., Bernstein, M. H., et al. (2019). “Artificial Intelligence and the Future of Primary Care.” The Lancet Digital Health, 1(8), e353-e354.

Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.

World Health Organization (WHO). (2021). Ethics and Governance of Artificial Intelligence for Health.

Sweller, J. (1988). “Cognitive Load During Problem Solving: Effects on Learning.” Cognitive Science, 12(2), 257-285.

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A bill passed by the state legislature in March then signed into law by Democratic Gov. Jared Polis allows Colorado to further uncouple itself from federal guidance.

The law allows health officials to follow the recommendations of national medical groups when making decisions such as purchasing bulk vaccines for the Medicaid program.

“We are insulating our state from the dysfunction coming out of Washington,” said Democratic state Sen. Kyle Mullica, a co-sponsor of the bill and a registered nurse. “We’re going to rely on science.”

“From fighting during the pandemic for Coloradans to get vaccines as quickly as possible to combating the Trump Administration’s barriers to getting vaccinated, we have expanded access to vaccines for Coloradans who want them,” Polis said in a statement when he signed the law.

Colorado is one of at least 29 states that, along with Washington, D.C., have taken steps to bypass the new federal recommendations amid worries that the changes could chip away at public trust in vaccines and erode broad vaccine coverage.

Previously, Colorado, like most states, had followed federal guidance set by the Centers for Disease Control and Prevention. In January, CDC advisory panelists, selected by Health and Human Services Secretary Robert F. Kennedy Jr., removed six pediatric immunizations from the agency’s universal recommendation list.

Last year, doctors, scientists, local leaders, and other supporters came together to form an outreach and advocacy coalition called Colorado Chooses Vaccines.

The group aims to offer a clear, unified voice on the proven benefits of vaccines and reassure residents confused by the many federal changes.

Carol Boigon, a former Denver City Council member, joined the group because she wants more people to hear her own chilling story about vaccine-preventable illness.

“Every summer everybody got sick,” Boigon said, recounting her childhood in 1950s Detroit.

The illness was polio, a highly contagious viral disease that attacks the nervous system, sometimes causing partial or full paralysis.

During the summer of 1953, “the whole block was sick and some of us got crippled, and that was just the way it was,” she said.

New Group Steps Up

Boigon’s personal history will be part of the coalition’s work to educate new generations about the dangers of infectious diseases that were once common in the U.S. but are now relatively rare.

The group, which formed last September, will also compile vaccine information from medical groups and the state health department and advocate for policy proposals with the state government.

“It was in direct response to the federal threats,” said another coalition member, former state lawmaker Susan Lontine. She leads the nonprofit Immunize Colorado.

Another member, public relations specialist Elizabet Garcia, wants more outreach to Hispanics, whose vaccination rates lag behind other groups’.

“A lot of time it’s this fear that they’re going to have to pay out-of-pocket, that their insurance doesn’t cover it, that they might not even have insurance in general,” Garcia said.

Boigon was 5 when she got sick and was hospitalized for six weeks with a fever. The virus attacked her spine.

“None of my limbs worked immediately afterwards,” Boigon said.

Although she regained function in her other limbs, her right arm never fully recovered. She had to adapt, relearning everyday tasks such as reaching out to shake hands with people with her left hand.

In 1955, not long after she got sick, the new polio vaccine became more widely available to the public. As vaccinations took off, U.S. cases of polio, once one of the nation’s most feared diseases, dropped by an estimated 85%-90%.

Increasing Public Trust

State leaders have taken other steps to promote public health. After the Trump administration pulled the U.S. out of the World Health Organization, several states, including Colorado, decided to join the WHO’s Global Outbreak Alert and Response Network on their own.

Colorado also joined a multistate lawsuit challenging the Trump administration’s changes to the childhood vaccine schedule.

And the new state law has provisions besides allowing the state to diverge from federal recommendations. It codifies pharmacists’ ability to prescribe and give vaccines themselves. It also increases legal protections for healthcare workers who give vaccines.

“This law will provide more clarity to guide all Coloradans, including providers who administer vaccines,” Lontine said.

But the legislation has opponents who say it would interfere with parental choice and claim vaccines might be unsafe or ineffective.

“I just want to make sure we’re not just getting into a big political dispute between the federal recommendations — the CDC and so forth — and different political views in Colorado here,” said Republican state Sen. John Carson, who voted against the vaccine bill.

NPR contacted the U.S. Department of Health and Human Services about Colorado’s new law. Spokesperson Emily Hilliard answered in an email: “The updated CDC childhood schedule continues to protect children against serious diseases.”

Preventable Illnesses Surge

The flurry of statewide activity comes as Colorado and the nation have seen surges in illnesses such as flu and measles.

As of mid-May, Colorado had recorded 22 measles cases this year. In 2025, it registered 36 cases, according to the state health department, far surpassing totals from previous years.

Across Colorado, kindergarten vaccination rates for measles were 88% last school year — with only a few counties achieving rates of 95%, the level needed for herd immunity, according to data published by The Washington Post in December.

This has also been Colorado’s worst flu season in recent years.

Vaccination rates for both flu and covid-19 have dropped slightly in Colorado, according to the state health department.

Eight children in Colorado have died this season from flu; one from covid; and one from RSV, or respiratory syncytial virus. Vaccines for all three are available for children and recommended by the state’s health department.

Kennedy, a longtime anti-vaccine activist, has defended his decisions to overhaul the recommended schedule for childhood vaccinations.

In March, a federal judge put on hold many of the changes.

“We’re not taking vaccines away from anybody. If you want to get the vaccine, you could get it. It’s going to be fully covered by insurance just like it was before,” Kennedy told CBS News in January.

When a reporter suggested the new changes could result in fewer people getting a flu vaccine, Kennedy said: “Well, that may be, and maybe that’s a better thing.”

Boigon is sometimes incredulous at everything that has happened.

“It’s like we’re going backwards,” she said. “It’s like we have decided we don’t want a modern life; we want to be back in the 1950s, where children are sick and dying.”

This article is from a partnership with Colorado Public Radio and NPR.

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Despite this extraordinary pace of innovation, something fundamental remains broken. Patients still struggle to navigate care. Physicians continue to wrestle with fragmented systems, administrative overload and technologies that often add work rather than reduce it. Health innovators repeatedly introduce sophisticated tools into environments overwhelmed by operational complexity, lack of governance, cybersecurity concerns, workflow disruption and communication gaps.

The issue is no longer whether innovation benefits care. The issue is friction.

Consumers compare health care experiences to every interaction in daily life. They compare health care to Apple, where design simplifies complexity, to Amazon, where communication is continuous and immediate, and to banking and travel platforms providing real-time updates and seamless transactions. Some may even compare it to Domino’s Pizza, which promises delivery within 15 minutes or the pie is free. Expectations surrounding responsiveness and convenience have fundamentally changed.

Then they enter health care environments where forms are repeated, portals fail to communicate, prior authorizations delay treatment and updates disappear into silence. Patients are left to navigate disconnected systems during moments of vulnerability. The expectation gap between consumer and health care experiences continues to widen and increasingly shapes reputation.

In Healing the Sick Care System: Why People Matter, the observation is made that “Health care isn’t failing because we lack innovation. It’s failing because the system around that innovation has calcified.” The statement remains painfully real because innovation alone does not create confidence. Experience does.

Patients Remember the Journey, Not the Molecule

The patient and physician experience is shaped less by what a product promises and more by what happens after that promise enters real life. A medicine may be clinically meaningful, yet the experience surrounding it can still become exhausting if coverage is difficult to secure, prior authorization is confounding, specialty pharmacy coordination is slow, follow-up instructions are unclear or support programs require patients to become navigators of their own care.

In those moments, people are not judging science on its own merits. They are judging the total experience of trying to make that medicine or care available and understandable.

Physicians face their own administrative version of friction. A therapy may be medically appropriate, yet before treatment can begin, office staff must determine coverage, complete documentation, respond to payer step-through requirements, manage rejection appeals and explain delays that were never created in the exam room. Every additional administrative step consumes time, stretches staff and places additional strain on the physician-patient relationship. Even non-medical formulary changes can force physicians to restart conversations, explain unexpected medication switches and reestablish patient confidence in treatment decisions already made.

Patients remember counting the hours as they waited for answers. Physicians remember losing uncompensated time navigating systems and approvals. Nurses remember caring for patients through computer screens while typing notes into laptops on rolling carts in crowded hallways. Office managers remember the relentless cycle of paperwork, rejected claims, disconnected portals and endless callbacks trying to move care forward.

The therapy may eventually do its job, yet the pathway becomes inseparable from the memory associated with the brand, the company and the broader health care system. Every new process, technology and treatment promises improvement. For patients and health professionals, however, if the path to care feels uphill, the friction surrounding the experience can overshadow the value of the benefit.

For many patients, repeated uncertainty, delays and administrative obstacles contribute to a form of medical PTSD, where anxiety surrounding the system becomes inseparable from the treatment experience. For health professionals, the constant burden of navigating fragmented systems, managing approvals and compensating for communication gaps has become a leading contributor to burnout.

Friction is rarely remembered as an operational issue inside organizations. Patients and physicians experience it personally. This is why communication must be elevated operationally within health care. Communication is not marketing layered onto innovation after development is complete.

Health care organizations often think they are going through the process of delivering a product, therapy or platform. Patients and physicians experience something more personal: time invested in every interaction surrounding the innovation is time lost forever.

Health Technology Cannot Create More Work

The same reality applies to health technology startups and digital health innovators. Technological advancement alone does not guarantee adoption within health care environments already burdened by operational complexity and workforce fatigue.

Health care organizations do not merely evaluate whether technology works. They evaluate whether it integrates with existing workflows, whether cybersecurity standards are state-of-the-art, whether onboarding is manageable, whether interoperability gaps create additional burdens, and whether the institution can trust the accuracy of data.

Every additional step is a friction point, while every unresolved operational issue becomes part of the patient and physician experience surrounding the journey.

A sophisticated AI platform that requires clinicians to validate outputs continuously adds cognitive burden. A monitoring platform generating clinically important alerts contributes to fatigue. A system that requires extensive retraining or manual workarounds may succeed in demonstration but stumble in real-world conditions.

Innovation may arrive elegantly designed; however, it enters health care environments already strained by workflow complexity, disconnected systems, cybersecurity demands and administrative fatigue. The operational realities surrounding implementation often become as important as the innovation itself.

That reality does not diminish the importance of continuous invention. It reinforces the importance of implementation, communication and operational design within real-world clinical environments.

This shift is increasingly visible across the global health innovation marketplace itself. At HLTH Europe 2026, conversations are moving well beyond excitement surrounding artificial intelligence, digital therapeutics and next-generation platforms. The agenda sessions focus on interoperability, workflow integration, governance, patient engagement and operational implementation. Conference themes repeatedly emphasize connected systems, coordinated experiences and technologies that reduce fragmentation rather than add to a growing list of patches.

One of the more revealing themes from HLTH Europe focuses directly on interoperability and the longstanding frustration surrounding disconnected systems. The conference site notes that clinicians continue spending enormous energy managing platforms that fail to communicate effectively with one another. At the same time, artificial intelligence is increasingly viewed not as a replacement for care, but as a bridge helping systems “finally speak the same language.”

Another major focus involves provider realities. HLTH Europe speakers highlight workforce fatigue, cyber risks, operational strain and workflow challenges facing clinicians and health systems across Europe and beyond. These agenda themes reinforce a growing recognition throughout the industry that innovation cannot succeed if it increases the burden for the people expected to use it every day.

Health professionals increasingly describe a workplace dominated by more screens, more alerts, more documentation and less time with patients. Technology interrupting workflow rather than integrating into it creates resistance, regardless of how advanced the platform may appear. The hidden work behind implementation often becomes the defining experience for the people expected to use the system every day.

Cybersecurity provides another important example. Health professionals and patients may never fully understand the technical architecture protecting health information, yet they absolutely understand the emotional consequence of uncertainty surrounding data privacy, reliability and trust. Confidence in health technology is not built solely through functionality. It is reinforced through consistency, service, transparency and confidence that information is accurate, protected and responsibly governed.

Communication plays an equally important role here. If clinicians are left uncertain about updates, system changes or data governance responsibilities, confidence weakens. If patients do not understand how information is protected, trust erodes, regardless of how advanced the technology.

Communication remains inseparable from the care experience.

The organizations most likely to lead the future of health care will not distinguish themselves solely through technological achievement. They will reduce friction around the user interface, workflows and data accuracy.

The Companies That Win Will Simplify Complexity

This reality explains why access organizations such as Hims & Hers Health and Cost Plus Drugs deserve careful study from across the health care sector, regardless of whether industry leaders agree with every aspect of their business models. These organizations are built around reducing friction in how people access and experience care.

Their importance extends beyond convenience or pricing. These companies recognize that many traditional health institutions have underestimated: people increasingly expect health care experiences to reduce anxiety, simplify decision-making and provide continuity throughout the care journey.  They are “Amazon-like,” offering a “Buy It Now” simple click medical oversight option.

The rise of concierge medicine, direct-to-consumer health platforms and walk-in clinics with reduced wait times reflects a broader market signal the health sector cannot ignore. Patients are increasingly gravitating toward experiences where communication is clearer and access is more immediate.

For those able to afford concierge care, the attraction often extends beyond physician access itself. Patients value responsiveness, shorter wait times, easier scheduling, follow-up communication and the sense that someone is helping coordinate their journey through the system. Walk-in clinics and urgent care centers appeal for similar reasons. People are searching for environments where care is readily accessible, understandable and administratively manageable. The downside of loss of care continuity is offset by immediacy, which is what the consumer values most.

This migration reflects frustration with friction embedded throughout the trending health care experience. Long hold times, delayed callbacks, countless portals, disconnected records, repeated paperwork on clipboards and uncertainty surrounding next steps all shape how people perceive quality of care.

Communication once again sits at the center of the experience. Patients rarely separate operational snafus from expert care. They experience the entire journey as one connected reality – positive or negative.

The lesson is not that health care should behave exactly like retail commerce. Medicine carries ethical, scientific and regulatory responsibilities far beyond consumer transactions. Nevertheless, the operational expectations consumers now bring into the setting have changed.

People increasingly expect health care to be as responsive as the communication they experience elsewhere in life. Is that expectation reasonable?

The pharmaceutical industry, payers, providers, and health technology innovators must recognize that they no longer own just the patents on therapies, platforms or services. They also own the surrounding user experience.

Patients experience health as a continuous journey, not a “build your own adventure” exercise in navigating fragmented systems. Most people enter the system anxious and seeking reassurance from their health professionals. A delayed approval, clinically sterile information delivered through a diagnostic portal or a physician struggling to navigate complexity alongside them deepens that burden. These experiences shape how health care is remembered more powerfully than advertising campaigns or corporate positioning statements.

Those experiences ultimately shape reputations.

The future winners in health care will not simply develop innovative products. They will reduce friction around the human experience surrounding those products. They will recognize that communication, workflow design and responsiveness are not secondary considerations attached to innovation. They are part of the experience.

Patients and physicians rarely remember the elegance of molecular or system architecture behind a therapy or platform. They remember whether the experience made care delivery easier and more humane during moments that mattered.

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Health versus wellness and the loss of muscle

Health and wellness are often conflated, but they’re actually quite different. Health is the absence of disease, such as heart disease, cancer, diabetes, obesity, or dementia. Wellness is the ability to do the things in life that matter, that give joy, such as carry the groceries, open a pickle jar, cuddle your great-grandchild, or, importantly, get up off the floor without assistance.

The fundamental issue is the loss of muscle mass and the resulting decline in strength. As we lose muscle mass, we often lose our sense of balance. Muscle loss begins in midlife and initially declines at about 1% per year. It speeds up in the late 70s and early 80s, so that by age 80 or so, the average individual has lost about 40% or more of their muscle mass and muscle strength.

Physicians call this loss of muscle sarcopenia. The graphic shows a cross-section of a muscle from a man at age 25 and from a man at age 63. The younger man’s muscle is pretty much all muscle, with just a little fat around it, but the older man has thick fat around and within his much-reduced muscle.

Swedish study results are striking

There’s a study from Sweden in the Journal of Cachexia, Sarcopenia and Muscle from November 2025 called “The rise and fall of physical capacity in a general population: a 47-year longitudinal study. “

Dr. Maria Weserstahl and colleagues have followed 427 men and women for 47 years. Each participant was age 16 at initiation of the study and is now 63. Multiple tests have been conducted every few years to assess muscle strength, power, and aerobic capacity. They observed that each of these measures increased from age 16 to about age 35, then began to decline. Initially, the decline was about 0.3% per year, but it accelerated to 2.5% per year by age 63. The total decline from the peak ranged from 30% to 48%.

The first graphic shows bench press as a measure of strength. Strength is largely dependent on slow-twitch, or red, muscle fibers. The upper part of the graph shows the men, and the lower part shows the women. The key point is that, at age 16, boys were stronger than girls, and this persisted throughout adulthood. Both men and women reached peak strength about age 36 and then began the steady decline. Not appreciated from the graphic, those of either sex who had the highest level of strength at age 16 tended to have the highest strength at age 63. Those who began to exercise at any point during the 47 years had a higher or greater strength by age 63

The second graph shows vertical jump performance as a measure of power, or the status of white or fast-twitch muscle fibers. The investigators had each individual stand next to a wall and jump as high as they could, touching their fingers at the high point. Here again, the boys’ power was greater than the girls’. The peak occurred around age 26 in the men and didn’t increase in most of the women. Thereafter, both men’s and women’s power declined steadily through age 63.

The third graphic shows aerobic capacity as a measure of endurance. Here again, the boys had a higher aerobic capacity than the girls at age 16. But both men’s and women’s aerobic capacity increased substantially, peaking around age 35 and then dropping off quickly.

As noted, those at the highest point at age 16 remained at the highest level at age 63. But those who started exercising at any age reached a higher level by age 63. The message I take away from this is “it is never too late” to improve your lifestyle.

It will be very interesting to learn what happens to these muscle values as the study continues into the participants’ 70s, 80s, and 90s. But from other studies we know that muscle mass and strength continue to decline, accelerating in the late 70s and early 80s, consistent with my friend’s and my own experience.

The good news, not emphasized in this report, was that beginning to exercise led to greater strength, power, and aerobic capacity at age 63 than among those who did not.

Reclaiming lost muscle

It’s no surprise that older people will often say something like, “I don’t like it, but losing muscle is just what happens when you get older.” Or “It’s too late for me to do anything about it “. But these statements are not true! It is never too late. You can slow the decline. You can rebuild muscle. But, to be honest, it takes real work and persistence over time. The following image is of a 70-year-old triathlete. You don’t need to be that aggressive, but the point is that it is possible to maintain muscle mass, and it is possible to regain it if you have lost it.

To reverse muscle loss, the critical steps are to 1) do resistance exercises, 2) increase protein intake, and 3) increase the micronutrients found in fruits and veggies, while 4) managing stress, and 5) enhancing sleep.

Resistance exercises can be done all at once over an hour or two, and repeated later in the week. But it is often more practical to do some each day. For example, do upper-body resistance exercises on Monday and Thursday, core on Tuesday and Friday, lower body on Wednesday and Saturday, and leave Sunday as a day off.

There is a pernicious myth that seniors should not do resistance exercises because they can hurt themselves. This advice has come from well-meaning physicians, physical therapists, personal trainers, and friends, but the data is clear: resistance exercises are not dangerous and, indeed, are essential. They’re proven to be safe and effective at any age, up to and beyond age 100. Inactivity risk is far greater than weight training risk for older adults. That said, it would be wise for an older person to work with a personal trainer to develop an effective yet safe exercise plan.

It takes more effort for an older person to build muscle mass and strength than for a younger person. But there’s no question that an older person can do both, do it effectively, and do it safely. It is never too late.

Building muscle requires protein and various micronutrients. Most people, and certainly most older people, do not get adequate protein. The current rule of thumb is that an active senior should get between 0.5 and 0.9 g per pound. This translates to about 115 g of protein per day for a 150-pound active senior. It’s quite possible to consume 115 g of protein in a day, but for some, that may be daunting without adding a protein supplement. If you do choose to supplement, choose one without added sugars. Also, consider adding a creatine supplement.

Micronutrients are found in high concentration in dark, green, leafy vegetables, nuts, seeds, beans, and fruits, especially berries.

At the same time, avoid ultraprocessed foods (UPFs), reduce calories, and avoid sugar (candy, ice cream) and foods made with white flour (white bread, pasta, pastries). The reason to avoid white flour is that it quickly breaks down into glucose (sugar). Since older people are less active and have less muscle mass, they need fewer calories. This may sound like a paradox, but reducing ultraprocessed foods with their sugar, fat, and salt while increasing protein means fewer calories.

Finally, your body needs a good night’s sleep, usually 7 ½ hours and it is important to manage your chronic stresses to reduce the stress chemicals that can slow muscle regrowth.

It is never too late
Maintaining muscle mass and strength is not just about feeling well and doing those things that are both fun and important to daily living. Low muscle mass is a predictor of all-cause mortality and of lifespan. It prevents you from becoming fail which is itself a mortality predictor. Muscle mass is also key to avoiding metabolic diseases such as diabetes.

You can reverse the loss of muscle that comes with aging. You can slow muscle loss of aging. You can rebuild muscle mass and strength. And in doing so, you can remain or become “well.”

Remember that it’s never too late to make the change and modify your lifestyles for the better. It can make life more enjoyable, healthier, and add to your health span and your lifespan. Here is a plus: you will find new friends where you exercise.

Please note: This article is for your education; it is not medical advice. I recommend you take this article to your physician and seek their advice on what is best for you.

The post You Lose 40% of Muscle Strength by Your 60s and Then It Accelerates appeared first on Medika Life.