Category: 8. Health

Myths about long COVID abound. Untruths about this post-pandemic condition have gone viral in their own way. Whether misinformation or outdated advice is to blame, stick to these COVID-19 facts, backed by experts and science.

Meet the experts: Lisa Sanders, M.D., medical director of Yale New Haven Health’s Multidisciplinary Long COVID Care Center; and Saahir Khan, M.D., Ph.D., an assistant clinical professor of infectious diseases at Keck School of Medicine, University of Southern California

Here, doctors debunk popular misconceptions associated with the condition.

Myth: Long COVID isn’t a real condition.

Myth buster: “Long COVID is very real and has very real biological causes,” says Lisa Sanders, M.D., medical director of Yale New Haven Health’s Multidisciplinary Long COVID Care Center. People with long COVID may have characteristic abnormalities in blood tests, such as high or low white blood cell counts or low levels of the stress hormone cortisol; however, many will have normal blood tests. Other diagnostic tests have shown suspected effects: For instance, in some people with long COVID, the mitochondria—small structures in cells that are responsible for producing energy—aren’t as good as usual at picking up oxygen from the blood, says Dr. Sanders. That partly explains why more than one-third of people with long COVID have exercise intolerance and nearly 12% have symptoms compatible with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). “The changes might be invisible, but they are there,” she says.

Myth 2: COVID boosters don’t protect against long COVID.

Myth buster: They absolutely do. “Compared to having received the primary vaccination series alone, receiving a booster vaccination reduces the risk of long COVID by up to 23%,” says Saahir Khan, M.D., Ph.D., an assistant clinical professor of infectious diseases at Keck School of Medicine, University of Southern California. “And having more recently received a COVID-19 vaccine can also reduce the risk of long COVID.” Even if you do get COVID after having been vaccinated (it can happen), the vaccine can help the immune system eliminate the virus more quickly, making it less likely that viral particles will stick around to cause more damage. “If you get COVID, the vaccine protects you from some of the worst possible outcomes, like long COVID, as well as from dying,” Dr. Sanders says.

Myth 3: Long COVID isn’t much of a problem anymore.

Myth Buster: We wish. While the percentage of people getting long COVID these days is down, overall COVID infections remain high, so “that still turns out to be a big number,” says Dr. Sanders. About 4% of vaccinated people and 8% of unvaccinated people get long COVID (down from a high of 10% at the start of the pandemic), and it can take a long time for some people to get better. A recent study showed that 68% of people who had long COVID symptoms six months after a COVID infection still had the same symptoms in year two. And those symptoms were no picnic—they included fatigue or exhaustion, breathlessness, anxiety and/or depression, and sleep problems. Also, COVID-19 infection can damage the brain, including by causing brain shrinkage and accelerated aging, not to mention that brain fog is one of the most common long COVID symptoms. Bottom line: You can avoid getting long COVID by avoiding COVID.

Myth 4: Long COVID is forever.

Myth buster: Long COVID isn’t always a lifelong condition. A study last year showed that about half of people who once had long COVID say they’ve recovered. And 48% of people with long COVID report recovering within three months, another analysis found. Not everyone will be that lucky, of course, but “studies say most people recover,” Dr. Sanders says, though that doesn’t necessarily mean their bodies and minds go back to a pre-infection state. “There may be lasting cognitive changes, but our brains are plastic. If something changes, we can often learn to work around it,” Dr. Sanders explains. Long COVID is a collection of symptoms, so there is no single remedy, but many of the symptoms can be treated with options like medication, physical therapy, and pulmonary rehabilitation.

Myth 5: Doctors know what causes long COVID.

Myth buster: Nobody knows exactly what causes long COVID. And while being older, being a woman, being in poor health, and having a severe COVID-19 infection can increase risk, “anyone who is infected with the virus that causes COVID-19 can get long COVID,” says Dr. Khan. Still, doctors and researchers have some ideas: Research points to several reasons some people develop long COVID, including having remnants of the virus that continue to cause inflammation; reactivation of latent viruses like the Epstein-Barr virus; an autoimmune response in which the body attacks its own tissues and organs; and organ and tissue damage caused by the initial infection. Essentially, COVID-19 kickstarts a complex immune response that must shut down once the infection is over; if it does not, says Dr. Khan, problems (and symptoms) can potentially pop up.

The smaller body surface area of Indians leads to smaller coronary artery dimensions. Narrower the arteries, higher the risk of early blockage. But the worst part is, blocked artery symptoms aren’t easy to identify. Eating clean, following a healthy lifestyle aren’t enough. However, certain symptoms can be identified through standard medical tests. In a recent video Cardiovascular Surgeon Dr Jeremy London shared 4 tests that can help identify blocked arteries and lower the risk of Cardiovascular complications.

Dr Jeremy explains blood pressure gets easily modified by lifestyle changes. According to The World Health Organisation (WHO), only 12% of the Indian population have blood pressure under control. High blood pressure is a ‘silent killer’ that increases the risk of blocked arteries as it damages the artery walls and leads to the accumulation of fatty deposits. Tracking blood pressure is critical for early detection and can lower the risk of blocked arteries.

Advanced Blood Panel can detect hidden risks

An Advances Blood Panel goes beyond the standard blood tests. It is a set of blood tests that identifies the hidden dangers of Atherosclerosis or Plaque build-up in the arteries. While a basic blood panel usually checks cholesterol and sugar, an Advances Blood Panel goes beyond that and may reveal number and type of cholesterol particles, inflammation in blood vessels and blood clotting tendency. Researchers have found, even if cholesterol numbers are low, one can still develop blocked arteries that lead to the risk of heart attack.

Visceral fat or the ‘dangerous’ fat around internal organs of the abdominal area is a risk factor for Artery Blockage. Cardiovascular Surgeon Dr London describes Visceral fat as ‘an engine for inflammation’. The third test Dr London recommends is DEXA scan or the Dual-Energy X-ray Absorptiometry. DEXA Scan reveals the level of Visceral fat in the body. Identification of Visceral fat is crucial as it secretes inflammatory proteins into the bloodstream that damage the Endothelium, the inner lining of arteries.

The fourth test Dr London recommends and describes as the most powerful determinants of longevity is the VO2 Max Test. This Maximum Oxygen Uptake test measures Cardiovascular efficiency and reflects aerobic fitness. While athletes are familiar with the VO2 test, Cardiologists too, are recommending this test, as early signs of a low VO2 max can lead to artery blockage.

If a food could earn a “most nutritionally confusing” award, it would be eggs. It can feel as if one day eggs are heart-healthy, and the next, they’re heart-harming. 

First, the good news: For most people, eggs can be part of a healthy, balanced diet. “Eggs are an economical source of high-quality protein and vitamins like A, D, E, K and B vitamins, as well as lutein and choline,” says Susan White, RDN, a registered dietitian specializing in heart health. 

At the same time, eggs also contain dietary cholesterol. And that’s where things get sticky. Turns out, we don’t all absorb or metabolize cholesterol the same way. So, if you’re wondering what eating a daily egg (or two) will do to your cholesterol, the answer is different for everyone.

If you could use a little help figuring out how many eggs it’s OK for you to eat every day, keep reading. 

3 Ways Eggs May Impact Cholesterol

Your body needs cholesterol for critical functions like hormone and vitamin D production. So, it’s not entirely a bad thing. However, too much cholesterol can raise the risk of heart disease. 

Depending on the following three factors, eggs may—or may not—raise your cholesterol levels.

Everyone Absorbs Eggs’ Cholesterol Differently

We get cholesterol from foods of animal origin, especially red and processed meat, poultry with skin, butter, full-fat dairy, shrimp and, of course, eggs. One whole large egg contains 206 milligrams of cholesterol. However, the amount of cholesterol in our bloodstreams doesn’t just come from the foods we eat. “Your body’s own cholesterol production has the main impact on your blood cholesterol level,” says White. “Most people don’t realize that our own body produces 800 to 1,000 milligrams of cholesterol per day. This depends on genetics and liver function, but this is an average.”

Your genes don’t just determine how much cholesterol your liver makes. They also influence how much cholesterol you absorb from the foods you eat. While the typical person absorbs about 50% of the cholesterol in their food, this amount can vary widely from person to person. In fact, cholesterol absorption rates can range from as little as 20% to as high as 80%. So, if you happen to be one of the lucky people who absorb little cholesterol, eggs may not make much of a difference in your blood cholesterol at all. But if you’re a cholesterol-absorbing machine, a daily egg probably isn’t the best thing for your cholesterol levels.

They Are Low in Saturated Fat

The cholesterol in your food isn’t the only thing that impacts your blood cholesterol. Saturated fat is also a big part of the cholesterol picture. When overconsumed, saturated fat can promote the gunking-up of your arteries, raising your “unhealthy” LDL cholesterol levels, which increases the risk of heart disease. That’s why keeping saturated fat intake low is key for keeping cholesterol levels in a healthy range. To manage your cholesterol, the American Heart Association recommends limiting saturated fat intake to less than 6% of your total daily calories. That’s about 11 to 13 grams for someone who eats 2,000 calories per day.

The good news: Eggs are surprisingly low in saturated fat, with one egg providing just 1.6 grams. The rest of their fat is unsaturated fat, which is considered heart-healthy.

They May Help with Weight Management

Overweight or obesity can increase your risk of high cholesterol. This is because excess body fat triggers the body to produce more cholesterol. On the flip side, losing about 10% of one’s body weight has been found to reduce cholesterol levels.

That’s where eggs come in. One whole egg has about 70 calories and 6 grams of protein, which helps promote satiety. This is one reason why eggs are often included in weight-loss or weight-management eating plans. In fact, eating eggs as part of a low-calorie eating plan has been found to decrease body mass index (BMI). So, as long as you’re not one of those people who absorb tons of cholesterol from food, eggs may indirectly help keep your cholesterol in check.

How Many Eggs Are Safe for Cholesterol?

In the past, guidelines have recommended limiting dietary cholesterol to 300 mg per day. Today, recommendations are more vague, telling us to keep consumption low without any specific limit. That makes it confusing to figure out where eggs fit in, especially since research can be mixed. “You might read one meta-analysis that says you don’t have to worry about eating eggs, while another says that you should stick to one per day,” says White. “It becomes challenging to weed through all of the information.” 

“When it comes to the impact on cardiovascular disease risk, we still want to be conscientious of dietary cholesterol,” says White. In terms of how many eggs you can safely eat per day or week, consider your heart risk. When White works with patients with diabetes, hypertension or high cholesterol, she might recommend that they consume no more than three egg yolks per week, as the yolks are where all the cholesterol is (since the whites are cholesterol-free, they can eat as many whites as they desire). 

If your cholesterol is in a healthy range or you don’t have cardiovascular risk factors, you’re generally OK eating one whole egg per day. In fact, one umbrella review found no difference in mortality risk between people who ate roughly one egg per day compared to people who practically never ate eggs. However, the study authors also note that the scientific evidence on this topic is insufficient and of low strength. So, more high-quality research is needed.

Of course, some people like to eat more than one egg. After all, have you seen people on social media who might have three, four or five whole eggs for breakfast? So, what then? “There are studies that say up to two eggs per day is permissible for a healthy individual, but beyond that, I don’t think we have strong clinical evidence to provide reassurance that more is fine,” says White. 

When it comes to deciding how many eggs are right for you, an individualized approach is the best way to go. This allows you to feed yourself in a way that you enjoy and find nourishing, while minimizing health risks. 

Talk to your health care provider about having your cholesterol checked regularly and how often they recommend checking it. When you do, watch for any jumps in harmful LDL cholesterol that may be related to increased egg intake. If your cholesterol rises to an unhealthy level, your health care provider might recommend decreasing egg consumption and looking for alternate, lower-cholesterol or cholesterol-free protein sources. These may include skinless poultry, fish, legumes, nuts, seeds or whey or pea protein powders.

Tips to Eat Eggs for Better Cholesterol

If you’re an egg lover, these tips can help you enjoy eggs and keep your heart healthy, too:

• Eat more plants:  “A plant-forward diet is associated with less cardiovascular disease,” says White. A healthy diet that contains eggs should also have lots of plant foods like fruits, vegetables, nuts, seeds and legumes.
• Balance your meal: Your overall diet matters, so eat eggs along with other nutrient-rich foods. For example, consider having a veggie omelet with fruit on the side or serving up a hard-boiled egg with a bowl of oatmeal topped with nuts and berries. 
• Consider adding more whites: To boost the protein content of your scramble or omelet, mix a couple of egg whites with one whole egg.
• Opt for heart-healthy preparations: Hard-boiled and poached eggs don’t require any added cooking fat compared to frying or scrambling them in saturated fat-heavy butter or bacon grease. If you’re more of a fried or scrambled egg person, cook them in heart-healthy olive or canola oil.

Our Expert Take

If you’re wondering what happens to your cholesterol when you eat eggs every day, the answer is different for everyone. On the upside, eggs are rich in vitamins and minerals and contain high-quality protein, which may help lower cholesterol by promoting a healthier body weight. They are also low in saturated fat, which is a primary culprit for raising cholesterol. Although eggs do contain cholesterol, dietary cholesterol has a lesser impact on blood cholesterol levels compared to the cholesterol the body naturally produces. So, consuming one whole egg per day is generally safe for most healthy adults. 

However, some people are genetically prone to absorb more cholesterol from food than others. If you notice that your cholesterol spikes when you start eating more eggs, you may want to back off.  Likewise, if you have risk factors for heart disease, including diabetes, hypertension or high cholesterol, your doctor may recommend eating no more than three whole eggs per week. In the end, everyone has different nutritional needs. “Historically, when we think of nutrition, too often we think of specific foods as ‘yes’ or ‘no,’” says White. But when it comes to eggs and cholesterol, one size doesn’t fit all.

We’ve written about men getting leg-lengthening surgery before. They’re spending thousands of dollars and months of recovery to inch closer to six feet. But now, women are heading in the opposite direction. Not to correct deformities or injury. Just to be…shorter. In the hope that it will help them in the love department.

Clinics in Istanbul are offering a new kind of cosmetic service: limb-shortening surgery for women who believe their height is working against them romantically. And while it might sound like the setup to a dystopian rom-com, it’s very real and very painful.

Surgeons cut the femur or tibia, remove bone, then secure what’s left with a metal rod. The upper leg can be reduced by up to 5.5 centimeters (2.2 inches), the lower leg by 3 centimeters (1.2 inches). One woman reportedly went from 172 to 167.9 centimeters (5’7¾” to 5’6″).

Most clinics promote the surgery as part of a complete “package,” including hospitalization, city tours, restaurant dinners, and even boat rides. But the post-op reality isn’t glamorous. Patients spend months recovering, often in wheelchairs, with intensive physical therapy four to five times a week.

Risks include nerve damage, bone infections, muscle weakness, and nonunion fractures that may never heal properly. Metal rods have weight limits, too, so you need to be under 75 kg (165 lbs) to even qualify.

Women Are Undergoing Limb-Shortening Surgery Just for Love

According to the Daily Mail, one Istanbul clinic has done at least 10 cosmetic limb-shortening surgeries since 2023. And while no global registry tracks these procedures yet, forums and Reddit threads have started filling up with stories from tall women who say they’ve struggled to date.

One reason? Height politics. Studies show that most men prefer women shorter than themselves, and women tend to prefer taller partners. That leaves some taller women caught in between, and apparently willing to sacrifice inches to close the gap.

Despite the absurdity of breaking your legs to be shorter, height has been directly connected to health. Researchers have linked tall stature in women to conditions like endometriosis and increased cancer risk. But that’s not what’s driving this particular trend. For many, it circles back to dating and the belief that being smaller may make them more “approachable.”

It’s a complicated equation. Shrinking yourself to feel seen by someone else seems a bit over the top. 

The World Health Organization (WHO) has added Ozempic to its list of drugs and medications required to treat obesity, along with treatments for cancer and cystic fibrosis.

WHO updates essential medicines list and calls for wider access to obesity treatments

In a statement on Friday, the United Nations agency said that drugs for obesity also include generic versions of the glucagon-like peptide-1 (GLP-1) drugs. This can help grant wider access to the medication, particularly in low and middle-income settings. 

“Today WHO is releasing the latest editions of the WHO Model Lists of Essential Medicines and Essential Medicines for Children. These lists are among WHO’s most important products, used in over 150 countries to shape public sector procurement, the supply of medicines, health insurance and reimbursement schemes,” a WHO post on X by Director-General of the World Health Organization, Dr Tedros Adhanom Ghebreyesus, said.

“The updated lists include new treatments for various types of cancer, and for diabetes with associated conditions such as obesity. Medicines for cystic fibrosis, psoriasis, haemophilia and blood-related disorders are among the other additions.”

A new brain imaging study provides evidence that deep brain stimulation of a specific brain region called the ventral anterior limb of the internal capsule (vALIC) may change how key emotional and cognitive areas in the brain interact in people with severe, treatment-resistant depression. Published in the journal Psychological Medicine, the findings suggest that the treatment induces long-term changes centered around the amygdala, a brain structure linked to emotional processing, and shorter-term effects focused on the insula, a region involved in internal bodily awareness and emotional states.

The results help explain how deep brain stimulation could help people with depression who have not responded to standard interventions such as medication, psychotherapy, or even electroconvulsive therapy. They also provide new insights into how the brain’s emotional networks adapt to stimulation over time.

Deep brain stimulation is a neurosurgical procedure in which electrodes are implanted deep into specific brain areas. These electrodes deliver controlled electrical pulses to modulate abnormal brain activity. The treatment is most commonly used to manage symptoms in conditions like Parkinson’s disease and obsessive-compulsive disorder. Over the past two decades, researchers have also explored its use in severe depression, particularly for patients who have not responded to any conventional treatments.

In depression, brain imaging studies have consistently shown altered activity in areas involved in mood regulation, including the amygdala, prefrontal cortex, and striatum. Some areas, such as the amygdala and insula, tend to show heightened activity, while others, like parts of the prefrontal cortex, appear underactive. Deep brain stimulation aims to restore balance in these networks, though the exact mechanisms remain unclear.

“Deep brain stimulation is under investigation as new treatment for patients with major depressive disorder, or depression for short. We have performed one of the only positive controlled clinical trials which suggests that it is effective compared to sham (fake) stimulation,” said study author Guido van Wingen, a professor of neuroimaging in psychiatry at Amsterdam UMC.

“The question for the current study was to investigate how it actually works. Depression is thought to be caused by altered interactions between distant brain regions. We therefore investigated how DBS alters the interactions of brain regions that are key for particular depression symptoms: the nucleus accumbens for reduced pleasure (anhedonia) and the amygdala for negative mood.”

The researchers recruited individuals with long-standing depression who had not improved after trying multiple classes of antidepressants, mood stabilizers, and electroconvulsive therapy. Participants received deep brain stimulation targeting the vALIC, which is located near another brain region often implicated in mood disorders—the nucleus accumbens.

The study included both patients and a control group of healthy participants. Patients were scanned using functional magnetic resonance imaging (fMRI) before and after the stimulation settings were optimized for each individual. This optimization process could take up to a year and involved biweekly clinical evaluations and adjustments to the stimulation parameters. After this period, patients entered a randomized, double-blind phase during which the stimulator was turned on and off in alternating blocks, allowing researchers to assess the immediate effects of stimulation.

The imaging data were analyzed in two ways. One method looked at overall functional connectivity—how strongly different brain regions are linked during rest. The second method, known as effective connectivity analysis, used a mathematical model to estimate the direction and strength of influence that one region exerts on another, helping to clarify whether certain brain areas were exciting or inhibiting each other.

One major finding was that connectivity between the amygdala and the left insula increased in patients who received deep brain stimulation, whereas it decreased over time in healthy controls. This connection is thought to be important for linking emotional experiences with awareness of internal bodily states. Previous studies have reported that this pathway is often weaker in people with depression, so an increase in connectivity might suggest a return toward more typical emotional processing.

In contrast, connectivity between the nucleus accumbens and the ventromedial prefrontal cortex decreased in patients following stimulation. This was true for both the left and right nucleus accumbens. The ventromedial prefrontal cortex is often linked to self-referential thinking and rumination, a pattern of repetitive negative thoughts common in depression. While previous studies have shown mixed results regarding the direction of this connectivity in depression, the decrease observed here suggests a shift in how reward and decision-making circuits interact during rest.

Additional changes were observed in the connection between the amygdala and the precentral gyrus, a brain region typically associated with motor planning but also implicated in emotional responding. Patients showed an increase in connectivity between these regions after treatment, while healthy controls showed a decrease over time.

In the short-term crossover phase, when stimulation was switched on and off, the researchers found different patterns of change. The amygdala showed stronger self-inhibition when the device was turned on, making it less responsive to signals from other brain areas. At the same time, communication between the insula and the prefrontal cortex weakened, suggesting a dampening of circuits involved in emotional and internal monitoring.

The study also found that the balance of influence between the insula and the nucleus accumbens shifted during stimulation. When the stimulator was active, the nucleus accumbens exerted more inhibition over the insula, and the insula had less influence over the nucleus accumbens. These effects appeared only during the short-term crossover phase and were not observed after the longer optimization period.

“We found that long-term deep brain stimulation indeed changes functional connectivity of the nucleus accumbens and amygdala with brain regions involved in the regulation (prefrontal cortex) and experience (insula) of emotions and feelings,” van Wingen told PsyPost. “Short-term cessation of deep brain stimulation resulted in more subtle rebalancing of how these brain regions influenced each other.”

The study sheds light on how deep brain stimulation reshapes emotional brain networks. But there are some limitations. The sample size was small, as is often the case in studies involving neurosurgical interventions. Only nine patients had usable imaging data from both the preoperative and post-optimization phases. This limited the researchers’ ability to examine individual differences or explore how factors like medication use or stimulation settings might influence outcomes.

The study was also limited to a predefined set of brain regions, chosen based on earlier work in obsessive-compulsive disorder. While this allowed for targeted analysis, it means that other relevant brain areas might have been overlooked.

The researchers plan to replicate their findings in future studies with larger samples. A better understanding of how deep brain stimulation influences emotional and cognitive networks could help refine the procedure and tailor it more effectively for individuals with depression.

The study, “Deep brain stimulation modulates directional limbic connectivity in major depressive disorder,” was authored by Egill A. Fridgeirsson, Isidoor Bergfeld, Bart P. de Kwaasteniet, Judy Luigjes, Jan van Laarhoven, Peter Notten, Guus Beute, Pepijn van den Munckhof, Rick Schuurman, Damiaan Denys, and Guido van Wingen.

Russia has announced the development of Enteromix, the world’s first cancer vaccine built on mRNA technology, which has demonstrated 100% efficacy and safety in clinical trials.

The development is being hailed as a major medical breakthrough, offering renewed hope to millions of cancer patients across the globe.

Clinical Trials Results and Side Effects

According to researchers, Enteromix has already moved into early clinical use at select oncology centers in Russia while awaiting final approval from the Ministry of Health for nationwide distribution.

During clinical testing, the vaccine showed no significant adverse effects—a notable departure from conventional cancer treatments such as chemotherapy and radiation, which often cause severe side effects including hair loss, fatigue, and organ damage.

Technology Behind Enteromix

The vaccine uses mRNA technology, the same platform that powered several COVID-19 vaccines.

This method enables the body’s own cells to produce proteins that mimic those found on cancer cells, training the immune system to identify and destroy malignant cells with precision.

Unlike traditional therapies, Enteromix targets tumors selectively, sparing healthy tissue and significantly improving patient tolerance.

Mode of Administration

Enteromix is administered through a simple intramuscular injection, making it less invasive compared to complex cancer treatments.

It was developed by the National Medical Research Radiological Centre in partnership with the Engelhardt Institute of Molecular Biology (EIMB), two leading Russian institutions specializing in oncology and molecular medicine.

Potential Beneficiaries

Medical experts believe Enteromix could benefit a wide spectrum of patients, including those suffering from lung, breast, colorectal, and pancreatic cancers.

It may also offer new options for individuals with hereditary cancer syndromes such as BRCA1/2 mutations, those with tumors resistant to chemotherapy, and even patients with compromised immune systems who typically struggle with conventional treatments.

A New Era in Cancer Care

If final clearance is granted, Enteromix could represent a turning point in global oncology, offering patients an alternative to harsh treatments while boosting survival rates and quality of life. Oncologists are optimistic that such vaccines may pave the way for a new generation of precision therapies, shifting cancer treatment from generalized approaches to personalized, targeted medicine.

Introduction

Chronic neck pain (CNP) is a significant global health issue that is garnering increasing attention. Statistics indicate that approximately 223 million people worldwide are affected, leading to an estimated 22 million years lived with disability,¹ with the majority being elderly.² The annual incidence rate of CNP is approximately 8% globally.³ It has become the fourth leading cause of years lived with disability and is a key factor contributing to reduced work productivity.⁴

Physical exercise is commonly used as a management strategy in the first-line treatment of neck pain.⁵ The American College of Sports Medicine also provides corresponding exercise prescription recommendations for CNP.⁶ Prior systematic reviews have demonstrated that conventional exercise therapies can effectively reduce pain in individuals with CNP.^7,8 However, Cieza et al found that 2.4 billion people have rehabilitation needs, with this segment of the population experiencing a 63% increase in recent years.¹ This trend indicates that traditional rehabilitation intervention methods may not be adequate to meet the rehabilitation needs of patients. Considering the limited per capita access to rehabilitation opportunities and the constraints on resources, exploring new technological solutions to enhance patients’ rehabilitation interventions is of utmost importance. Mobile health, commonly known as mHealth, encompasses medical and public health activities that utilize mobile technology.⁹ mHealth-based exercise represents a highly viable alternative to conventional in-person outpatient treatments.¹⁰ This modality denotes an exercise paradigm that utilizes mobile terminals (eg, smartphones, wearable devices) and supporting software to deliver personalized exercise prescriptions, enable real-time data capture (eg, heart rate, movement trajectories), and facilitate remote intervention.^11,12 Numerous research studies have demonstrated that exercise interventions based on mHealth significantly enhance pain relief and functional abilities in individuals suffering from CNP.^7,13–15

During the COVID-19 pandemic, when individuals were confined to their homes and unable to access regular face-to-face rehabilitation, mHealth exercise interventions emerged as a primary form of rehabilitation. This transition has facilitated the development of mHealth exercise interventions as effective alternatives for pain management.

Despite the increasing focus on mHealth-driven exercise strategies for CNP, several concerns highlighted in earlier studies persist unresolved. Initially, it is crucial to conduct more research to evaluate how conventional exercise programs measure up against mHealth-based alternatives. Furthermore, questions remain regarding the impact of supervision on the results of traditional exercise methods and the correlation between mHealth interventions and both supervised and unsupervised conventional techniques. Therefore, this review aims to evaluate the effectiveness of mHealth-based exercise interventions in comparison with conventional exercise, focusing on their impact in reducing pain intensity, improving functional disability, and enhancing quality of life among individuals with CNP.

Methods

The meta-analysis was performed following the PRISMA guidelines for systematic reviews and meta-analyse.¹⁶ This study has been registered on PROSPERO (CRD420250652524).

Search Strategies and Study Selection

An extensive and thorough strategic literature search was conducted utilizing several reputable databases, including Web of Science, Medline (accessible via PubMed), the Excerpta Medica Database (Embase), and the Cochrane Central Register of Controlled Trials (CENTRAL), with the search extending up until December 25, 2024. This search was intentionally limited to scholarly articles that were published in the English language to maintain a focused and relevant compilation of study findings. To effectively screen the identified studies, Boolean logic operators were employed in combination with specific medical subject terms and pertinent keywords, such as “chronic neck pain”, “mobile health”, “sports intervention”, and “RCTs”, among others. This structured approach facilitated a comprehensive examination of the available literature. Moreover, in addition to the primary search methods, a series of recursive searches were carried out manually as a supplementary retrieval strategy. This was executed by reviewing leading academic journals, including notable publications like Sports Medicine and JAMA Network Open.^17,18 The goal of these additional searches was to guarantee that no relevant articles meeting our predefined inclusion criteria were inadvertently overlooked. For a complete understanding of the search methodologies used across all databases, further details are available in the Supplementary search strategy provided.

The selection process was conducted independently by two researchers. In instances of discrepancies, a third expert was consulted for guidance. Duplicate entries were automatically eliminated. Each of the two authors assessed the titles and abstracts individually. Subsequently, a thorough evaluation of the complete articles was conducted to ensure the accuracy and integrity of the studies.

Inclusion Criteria

The study adhered to the criteria of population, interventions, comparators, outcomes, and study design for the included studies. First, only patients diagnosed with CNP were recruited. Second, the intervention group can be any mHealth-based exercise rehabilitation intervention. Third, the comparison group may consist of traditional exercise interventions delivered through non-telemedicine methods, which include, but are not limited to, face-to-face outpatient interventions and self-practice. Fourth, the primary outcome indicator was pain, while the secondary outcome indicators included functional disability and quality of life (QOL). In instances where multiple assessment scales were utilized in a study, the main measurement was chosen. When the text failed to clearly define the primary measure, the measurement from the most frequently utilized scale was incorporated instead. Ultimately, only RCTs published in English were selected, as data from English-language RCTs are generally considered to exhibit less bias compared to those derived from other study designs.

Data Extraction and Quality Assessment

We extracted the following data points using a predesigned form: study basic information (eg, authors, publication year, intervention duration), participant baseline characteristics (eg, sample size, age, gender ratio) and outcomes (eg, pain, functional disability and QOL). If the papers did not report the necessary data, such as outcome measures, we would contact the corresponding authors via Email to obtain this information.

The risk of bias (RoB) for each publication was assessed by two independent reviewers utilizing the Revised Cochrane risk-of-bias tool for randomized trials (RoB2),¹⁹ and if there were disagreements, they were resolved by a third person in a joint discussion. This tool encompasses five components, each element from the studies included was rated as uncertain, low, or high RoB.

The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system was utilized to evaluate the quality of evidence for each statistically significant outcome.²⁰ The evidence level could be reduced by one tier based on several factors, including risk of bias, inconsistency, indirectness of the evidence, imprecision, and publication bias. Conversely, the evidence might be elevated by one level for reasons such as a large effect size, a dose–response relationship, or situations where all plausible biases merely diminish an apparent treatment effect. GRADE categorizes the quality of evidence into four tiers: high, moderate, low, and very low.

Statistical Analyses

In accordance with the Cochrane Collaboration Handbook, a conventional pairwise meta-analysis was performed utilizing random effects models using STATA software version 14.0 (Stata, Inc., College Station, TX).²¹ Initially, I² statistics were applied to assess the studies’ heterogeneity, with I² values of 25%, 50%, and 75% representing low, moderate, and high heterogeneity, respectively. Moreover, a Q statistical analysis was performed, in which P values that fell below 0.1 indicated notable heterogeneity.²² Subsequently, we computed the standardized mean difference (SMD), which is defined as the mean difference divided by the standard deviation (SD), along with the corresponding 95% confidence interval (CI). In addition, a comparison-adjusted funnel plot was generated to visually assess potential publication bias by analyzing the plot for any signs of asymmetry. To further evaluate the funnel plot quantitatively, the Egger test was conducted to determine whether the P value was less than 0.05.²³ Finally, multiple subgroup analyses were carried out to investigate any differences or statistically meaningful variations among the trials. The subgroup analyses encompassed the following factors: duration of intervention (≥3 months and <3 months), type of control group intervention (unsupervised exercise control group versus face-to-face exercise control group), geographical region (Asia contrasted with America and Europe) and so on.

Results

Literature Selection and Characteristics of Included Studies

A preliminary search of the database resulted in 5454 publications, from which 1972 studies were removed due to duplication. Upon examining the titles and abstracts, we found 3461 studies that failed to meet the eligibility criteria. This led to the selection of 21 papers for an in-depth full-text review, consisting of 3 papers that were discovered through manual searches. After conducting a meticulous evaluation of the documents, we excluded 15 records for the following reasons: 6 studies were not RCTs, 4 studies did not have suitable outcomes, and 4 studies lacked pertinent data. As a result, our analysis focused on 6 studies.^24–29 The PRISMA screening process is depicted in Figure 1, and Table 1 outlines the characteristics of the studies included.

Table 1 Demographic Characteristics of Included Studies

Figure 1 Flowchart.

The six studies comprised a total of 381 participants, aged between 30 and 61 years, with findings published between 2017 and 2024. Notably, the majority of participants were women (56.68%), and most interventions lasted between 8 and 12 weeks. Of these studies, one was conducted in America, two in Europe, and three in Asia.

Quality of the Included Studies

Supplementary Figures 1 and 2 illustrate the quality at both the individual and overall study levels. Each of the six trials demonstrated a sufficient randomization process, and all studies were rated as having some concerns regarding bias in the implementation of the predefined interventions. No study exhibited bias related to missing outcome data. One trial showed a high risk of selection bias concerning the reported results, while the other five trials were categorized as having a low risk of selection bias. Overall, one study had a high risk of bias, while the remaining five studies had an uncertain risk of bias.

Primary Outcomes

Effects of mHealth-Based Exercise on Pain

In total, six studies explored the effect of mHealth-based exercise on pain, making a comparison between mHealth-centered exercise (involving 191 participants) and traditional exercise (involving 190 participants). The findings showed no statistically significant differences in pain alleviation between mHealth-supported workouts and traditional intervention techniques (SMD = −0.31, 95% CI: −0.74 to 0.12, I² = 74.1%, P_{heterogeneity} < 0.1) (Figure 2). Based on the GRADE evaluation, the level of quality of evidence was moderate (Supplementary Figure 3). Furthermore, the funnel plot analysis did not indicate any asymmetry (Figure 3), implying an absence of potential publication bias (P_egger = 0.16).

Figure 2 Literature review forest plot based on primary outcome.

Figure 3 Literature review funnel plot based on primary outcome.

Secondary Outcomes

Functional Disability

A total of six studies evaluated the impact of mHealth-based exercise on functional disability, involving 381 participants. The findings revealed that those engaged in mHealth-based exercise did not show significant enhancements in functional disability when compared to individuals participating in conventional exercise programs (SMD: −0.33, 95% CI: −0.68 to 0.02, I² = 60.0%, P_{heterogeneity} < 0.1) (see Supplementary Figure 4). Based on the GRADE evaluation, the level of quality of evidence was low. Additionally, the funnel plot’s observed asymmetry related to functional disability suggested a potential presence of publication bias (refer to Supplementary Figure 5).

Quality of Life

Three investigations examined the impact of mHealth-based exercise on QOL. The combined results indicated that there was no notable difference between the groups involved in mHealth-based exercise and those participating in conventional exercise (SMD: −0.19, 95% CI: −0.19 to 0.56, I² = 41.2%, P_{heterogeneity} = 0.18) (see Supplementary Figure 6). Based on the GRADE evaluation, the level of quality of evidence was low. Furthermore, the funnel plot displayed a lack of symmetry, suggesting the possibility of publication bias (refer to Supplementary Figure 7).

Subgroup Analyses

Subgroup analyses were performed based on the primary outcome of pain, utilizing data from various factors including intervention type from the control group, duration of the intervention, methods of outcome measurement, and geographical region. Most of the analyses demonstrated consistency, showing no statistically significant differences among the subgroup factors. However, when analyzing the intervention types within the control group, notable differences were found in pain reduction between mHealth-supported exercise and unsupervised traditional exercise interventions (SMD = −0.76, 95% CI = −1.06 to −0.45; see Supplementary Figure 8).

Subgroup analyses were additionally conducted based on secondary outcomes related to the duration of the intervention, geographical region, and the type of control group intervention. The findings indicated that exercise supported by mHealth considerably exceeded the effectiveness of unsupervised traditional exercise interventions in enhancing functional disability (SMD = −0.66, 95% CI = −1.31 to −0.32). However, no significant differences were observed across subgroups when considering the region and duration of the intervention (refer to Supplementary Figure 9).

Discussion

From the statistical results, we conclude that CNP patients who engaged in mHealth exercise interventions did not demonstrate any significant improvement in pain intensity, functional disability, or QOL compared to those participating in conventional exercise programs. However, in comparison to unsupervised traditional exercise interventions, mHealth exercise interventions have significantly improved pain and functional ability in patients suffering from CNP.

This meta-analysis revealed that there was no notable difference in the enhancement of pain relief between mHealth exercise interventions and conventional exercise interventions for individuals with chronic neck pain (SMD = −0.31; 95% CI: −0.73 to 0.12). Current research demonstrates that both remote exercise interventions and traditional rehabilitation methods can effectively alleviate pain symptoms in this patient population.^30–33 The lack of significant difference in pain symptom improvement between the two intervention types may be attributed to the fact that both were conducted under the supervision of clinicians or rehabilitators.^34–36 Supervised exercise interventions ensure full participant engagement and minimize the likelihood that individuals will fail to achieve adequate exercise intensity due to personal inertia. Additionally, such supervision provides timely feedback, which may enhance patient compliance and facilitate the ongoing development of the exercise intervention.^37,38 Given that both online and offline intervention modes effectively reduce pain levels in CNP patients, and that no significant differences in efficacy were observed, this finding expands the possibilities for exercise rehabilitation interventions in this demographic. Furthermore, it offers a more convenient recovery option for patients who may find it difficult to attend outpatient clinics for treatment. For instance, patients with CNP residing in remote areas may face geographical barriers that prevent regular hospital visits for rehabilitation; thus, remote exercise rehabilitation interventions can provide consistent online guidance for these individuals.³⁹ Furthermore, our study revealed no significant differences in the improvement of functional disability and quality of life between remote and conventional exercise interventions. This similarity may also be linked to the strong supervision and high compliance associated with both intervention approaches and functional disability.

Our subgroup analysis, based on the intervention forms within the control group, revealed that, for the two outcome measures of pain (SMD=−0.76; 95% CI: −1.06 to −0.45) and functional disability (SMD=−0.66; 95% CI: −1.01 to −0.32) in patients with CNP, remote exercise interventions exhibited a more significant effect than unsupervised traditional exercise interventions. This finding aligns with previous research and emphasizes the critical role of supervised exercise,^40,41 as discussed earlier. Therefore, in future exercise intervention trials, it is essential that interventions—whether delivered online or offline—are conducted under the supervision of sports rehabilitation professionals, as this may enhance their effectiveness. Furthermore, in the context of significant crises that prevent individuals from attending regular rehabilitation sessions at outpatient clinics, such as the COVID-19 pandemic, remote exercise interventions provide a viable alternative for healthcare providers to deliver rehabilitation services via telemedicine.⁴²

mHealth technologies reshape rehabilitation accessibility by breaking down geographical and temporal barriers, synergizing with the global trend of physical therapy transitioning toward a “prescription-free profession”. Studies have shown that direct access to physical therapy improves patient outcomes and reduces healthcare costs.⁴³ mHealth, through wearable devices and AI technologies, further enables “prescription-free” remote rehabilitation—for instance, rural communities in Canada have witnessed a 27% increase in physical therapy utilization by integrating direct access policies with remote technologies.⁴⁴ Future explorations could focus on integrating AI-based triage systems with real-time movement data to construct an “assessment-intervention-monitoring” closed loop, whose autonomy and scalability align with the professional autonomy framework of “prescription-free physical therapy”.

Strengths and Limitations

This meta-analysis emphasizes several key advantages. As far as we know, it represents the first comprehensive review to examine the effects of mHealth exercise interventions versus traditional exercise approaches on pain levels in individuals suffering from CNP. The findings suggest that mHealth exercise interventions did not produce a significant enhancement in pain relief when compared to their traditional alternatives. Furthermore, remote rehabilitation approaches, unlike conventional rehabilitation strategies, are less constrained by geographical limitations and the availability of medical resources, potentially enhancing continuity and adherence to rehabilitation practices for individuals with CNP. Consequently, this study may serve as a vital reference point for policymakers, healthcare providers, and caregivers in making informed decisions and shaping clinical practices, thereby facilitating future research and clinical applications.

Several constraints need to be recognized. To begin with, the findings arise from a rather small pool of included research (merely six studies), which might yield inadequate evidence for our assessment. Moreover, the poor quality of certain qualifying studies might undermine the dependability of the results, as a number of the studies failed to utilize blinding for either participants or personnel. Moreover, due to limitations in the original data, no subgroup analyses were performed based on age, gender, disease type, intervention frequency, or publication year. The types of subgroup analyses were restricted to the type of control group and the intervention duration. Therefore, further studies with larger sample sizes, a multi-center design, and diverse treatment types are necessary to yield additional insights and evidence, ultimately offering more specific and detailed guidance for clinical application.

Conclusions and Implications

mHealth-based exercise interventions represent a valuable alternative therapy aimed at enhancing pain management and functional capabilities in young and middle-aged patients suffering from chronic non-specific neck pain. These interventions appear to be as effective as traditional exercise programs, indicating that patients may benefit from either approach without a notable difference in outcomes. Furthermore, when compared specifically to unsupervised traditional exercise regimens, mHealth-based exercise interventions demonstrate more pronounced benefits, suggesting that the structured and guided nature of mHealth can lead to superior results for individuals undergoing rehabilitation for non-specific neck pain.

Data Sharing Statement

Some or all data generated or analyzed during this study are included in this published article or in the data repositories listed in References.

Acknowledgment

We affirm that the Work submitted for publication is original. This paper has been uploaded to Research Gate as a preprint: [https://www.researchgate.net/publication/390147679_Comparing_mHealth-based_Exercise_and_Offline_Exercise_for_Chronic_Neck_Pain_A_Systematic_Review_and_Meta-analysis_Preprint]. We affirm that each person listed as authors participated in the Work in a substantive manner, in accordance with ICMJE authorship guidelines, and is prepared to take public responsibility for it. All authors consent to the investigation of any improprieties that may be alleged regarding the work.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This research received no supports from any funding sources.

Disclosure

The authors have no conflicts of interest to disclose for this work.

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