Some companies claim remote work hurts wellbeing. Research shows the opposite.
Many leaders at top companies are trying to get workers to return to the office. They say remote and hybrid work are bad for their employees’ mental well-being and lead to a sense of social isolation, meaninglessness, and lack of work-life boundaries, so we should just all go back to office-centric work.
One example is Google, where the company’s leadership is defending its requirement of mostly in-office work for all staff as necessary to protect social capital, meaning people’s connections to and trust in one another. That’s despite a survey of over 1,000 Google employees showing that two-thirds feel unhappy about being forced to work in the office three days per week. In internal meetings and public letters, many have threatened to leave, and some are already quitting to go to other companies with more flexible options.
Last month, GM rolled out a policy similar to Google’s, but had to backtrack because of intense employee opposition. The same is happening in some places outside of the U.S. For instance, three-fifths of all Chinese employers are refusing to offer permanent remote work options, according to a survey this year from The Paper.
For their claims that remote work hurts well-being, some of these office-centric traditionalists cite a number of prominent articles. For example, Arthur Brooks claimed in an essay that “aggravation from commuting is no match for the misery of loneliness, which can lead to depression, substance abuse, sedentary behavior, and relationship damage, among other ills.” An article in Forbes reported that over two-thirds of employees who work from home at least part of the time had trouble getting away from work at the end of the day. And Fast Company has a piece about how remote work can “exacerbate existing mental health issues” like depression and anxiety.
For his part, author Malcolm Gladwell has also championed a swift return to the office, saying there is a “core psychological truth, which is we want you to have a feeling of belonging and to feel necessary…I know it’s a hassle to come into the office, but if you’re just sitting in your pajamas in your bedroom, is that the work life you want to live?”
These arguments may sound logical to some, but they fly in the face of research and my own experience as a behavioral scientist and as a consultant to Fortune 500 companies. In these roles, I have seen the pitfalls of in-person work, which can be just as problematic, if not more so. Remote work is not without its own challenges, but I have helped 21 companies implement a series of simple steps to address them.
Research finds that remote work is actually better for you
The trouble with the articles described above - and claims by traditionalist business leaders and gurus - stems from a sneaky misdirection. They decry the negative impact of remote and hybrid work for wellbeing. Yet they gloss over the damage to wellbeing caused by the alternative, namely office-centric work.
It’s like comparing remote and hybrid work to a state of leisure. Sure, people would feel less isolated if they could hang out and have a beer with their friends instead of working. They could take care of their existing mental health issues if they could visit a therapist. But that’s not in the cards. What’s in the cards is office-centric work. That means the frustration of a long commute to the office, sitting at your desk in an often-uncomfortable and oppressive open office for at least 8 hours, having a sad desk lunch and unhealthy snacks, sometimes at an insanely expensive cost and, for making it through this series of insults, you’re rewarded with more frustration while commuting back home.
In a 2022 survey, the vast majority of respondents felt that working remotely improved their work-life balance. Much of that improvement stemmed from saving time due to not needing to commute and having a more flexible schedule.
So what happens when we compare apples to apples? That’s when we need to hear from the horse’s mouth: namely, surveys of employees themselves, who experienced both in-office work before the pandemic, and hybrid and remote work after COVID struck.
Consider a 2022 survey by Cisco of 28,000 full-time employees around the globe. Nearly 80 percent of respondents say that remote and hybrid work improved their overall well-being: that applies to 83 percent of Millennials, 82 percent of Gen Z, 76 percent of Gen Z, and 66 percent of Baby Boomers. The vast majority of respondents felt that working remotely improved their work-life balance.
Much of that improvement stemmed from saving time due to not needing to commute and having a more flexible schedule: 90 percent saved 4 to 8 hours or more per week. What did they do with that extra time? The top choice for almost half was spending more time with family, friends and pets, which certainly helped address the problem of isolation from the workplace. Indeed, three-quarters of them report that working from home improved their family relationships, and 51 percent strengthened their friendships. Twenty percent used the freed up hours for self-care.
Of the small number who report their work-life balance has not improved or even worsened, the number one reason is the difficulty of disconnecting from work, but 82 percent report that working from anywhere has made them happier. Over half say that remote work decreased their stress levels.
Other surveys back up Cisco’s findings. For example, a 2022 Future Forum survey compared knowledge workers who worked full-time in the office, in a hybrid modality, and fully remote. It found that full-time in-office workers felt the least satisfied with work-life balance, hybrid workers were in the middle, and fully remote workers felt most satisfied. The same distribution applied to questions about stress and anxiety. A mental health website called Tracking Happiness found in a 2022 survey of over 12,000 workers that fully remote employees report a happiness level about 20 percent greater than office-centric ones. Another survey by CNBC in June found that fully remote workers are more often very satisfied with their jobs than workers who are fully in-person.
Academic peer-reviewed research provides further support. Consider a 2022 study published in the International Journal of Environmental Research and Public Health of bank workers who worked on the same tasks of advising customers either remotely or in-person. It found that fully remote workers experienced higher meaningfulness, self-actualization, happiness, and commitment than in-person workers. Another study, published by the National Bureau of Economic Research, reported that hybrid workers, compared to office-centric ones, experienced higher satisfaction with work and had 35 percent more job retention.
What about the supposed burnout crisis associated with remote work? Indeed, burnout is a concern. A survey by Deloitte finds that 77 percent of workers experienced burnout at their current job. Gallup came up with a slightly lower number of 67 percent in its survey. But guess what? Both of those surveys are from 2018, long before the era of widespread remote work.
By contrast, in a Gallup survey in late 2021, 58 percent of respondents reported less burnout. An April 2021 McKinsey survey found burnout in 54 percent of Americans and 49 percent globally. A September 2021 survey by The Hartford reported 61 percent burnout. Arguably, the increase in full or part-time remote opportunities during the pandemic helped to address feelings of burnout, rather than increasing them. Indeed, that finding aligns with the earlier surveys and peer-reviewed research suggesting remote and hybrid work improves wellbeing.
Remote work isn’t perfect – here’s how to fix its shortcomings
Still, burnout is a real problem for hybrid and remote workers, as it is for in-office workers. Employers need to offer mental health benefits with online options to help employees address these challenges, regardless of where they’re working.
Moreover, while they’re better overall for wellbeing, remote and hybrid work arrangements do have specific disadvantages around work-life separation. To address work-life issues, I advise my clients who I helped make the transition to hybrid and remote work to establish norms and policies that focus on clear expectations and setting boundaries.
For working at home and collaborating with others, there’s sometimes an unhealthy expectation that once you start your workday in your home office chair, and that you’ll work continuously while sitting there.
Some people expect their Slack or Microsoft Teams messages to be answered within an hour, while others check Slack once a day. Some believe email requires a response within three hours, and others feel three days is fine. As a result of such uncertainty and lack of clarity about what’s appropriate, too many people feel uncomfortable disconnecting and not replying to messages or doing work tasks after hours. That might stem from a fear of not meeting their boss’s expectations or not wanting to let their colleagues down.
To solve this problem, companies need to establish and incentivize clear expectations and boundaries. They should develop policies and norms around response times for different channels of communication. They also need to clarify work-life boundaries – for example, the frequency and types of unusual circumstances that will require employees to work outside of regular hours.
Moreover, for working at home and collaborating with others, there’s sometimes an unhealthy expectation that once you start your workday in your home office chair, and that you’ll work continuously while sitting there (except for your lunch break). That’s not how things work in the office, which has physical and mental breaks built in throughout the day. You took 5-10 minutes to walk from one meeting to another, or you went to get your copies from the printer and chatted with a coworker on the way.
Those and similar physical and mental breaks, research shows, decrease burnout, improve productivity, and reduce mistakes. That’s why companies should strongly encourage employees to take at least a 10-minute break every hour during remote work. At least half of those breaks should involve physical activity, such as stretching or walking around, to counteract the dangerous effects of prolonged sitting. Other breaks should be restorative mental activities, such as meditation, brief naps, walking outdoors, or whatever else feels restorative to you.
To facilitate such breaks, my client organizations such as the University of Southern California’s Information Sciences Institute shortened hour-long meetings to 50 minutes and half-hour meetings to 25 minutes, to give everyone – both in-person and remote workers – a mental and physical break and transition time.
Very few people will be reluctant to have shorter meetings. After that works out, move to other aspects of setting boundaries and expectations. Doing so will require helping team members get on the same page and reduce conflicts and tensions. By setting clear expectations, you’ll address the biggest challenge for wellbeing for remote and hybrid work: establishing clear work-life boundaries.
Some 900 miles off the coast of Portugal, nine major islands rise from the mid-Atlantic. Verdant and volcanic, the Azores archipelago hosts a wealth of biodiversity that keeps field research scientist, Marlon Clark, returning for more. “You’ve got this really interesting biogeography out there,” says Clark. “There’s real separation between the continents, but there’s this inter-island dispersal of plants and seeds and animals.”
It’s a visual paradise by any standard, but on a microscopic level, there’s even more to see. The Azores’ nutrient-rich volcanic rock — and its network of lagoons, cave systems, and thermal springs — is home to a vast array of microorganisms found in a variety of microclimates with different elevations and temperatures.
Clark works for Basecamp Research, a biotech company headquartered in London, and his job is to collect samples from ecosystems around the world. By extracting DNA from soil, water, plants, microbes and other organisms, Basecamp is building an extensive database of the Earth’s proteins. While DNA itself isn’t a protein, the information stored in DNA is used to create proteins, so extracting, sequencing, and annotating DNA allows for the discovery of unique protein sequences.
Using what they’re finding in the middle of the Atlantic and beyond, Basecamp’s detailed database is constantly growing. The outputs could be essential for cleaning up the damage done by toxic chemicals and finding alternatives to these chemicals.
Catalysts for change
Proteins provide structure and function in all living organisms. Some of these functional proteins are enzymes, which quite literally make things happen.
“Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development. Biocatalysis is providing advantages, both to make more complex drugs and to be more sustainable, reducing the pollution and toxicity of conventional chemistry," says Ahir Pushpanath, who heads partnerships for Basecamp.
“Enzymes are perfectly evolved catalysts,” says Ahir Pushpanath, a partnerships lead at Basecamp. ”Enzymes are essentially just a polymer, and polymers are made up of amino acids, which are nature’s building blocks.” He suggests thinking about it like Legos — if you have a bunch of Lego pieces and use them to build a structure that performs a function, “that’s basically how an enzyme works. In nature, these monuments have evolved to do life’s chemistry. If we didn’t have enzymes, we wouldn’t be alive.”
In our own bodies, enzymes catalyze everything from vision to digesting food to regrowing muscles, and these same types of enzymes are necessary in the pharmaceutical, agrochemical and fine chemical industries. But industrial conditions differ from those inside our bodies. So, when scientists need certain chemical reactions to create a particular product or substance, they make their own catalysts in their labs — generally through the use of petroleum and heavy metals.
These petrochemicals are effective and cost-efficient, but they’re wasteful and often hazardous. With growing concerns around sustainability and long-term public health, it's essential to find alternative solutions to toxic chemicals. “Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development,” Pushpanath says.
Basecamp is trying to replace lab-created catalysts with enzymes found in the wild. This concept is called biocatalysis, and in theory, all scientists have to do is find the right enzymes for their specific need. Yet, historically, researchers have struggled to find enzymes to replace petrochemicals. When they can’t identify a suitable match, they turn to what Pushpanath describes as “long, iterative, resource-intensive, directed evolution” in the laboratory to coax a protein into industrial adaptation. But the latest scientific advances have enabled these discoveries in nature instead.
Marlon Clark, a research scientist at Basecamp Research, looks for novel biochemistries in the Azores.
Whether it’s Clark and a colleague setting off on an expedition, or a local, on-the-ground partner gathering and processing samples, there’s a lot to be learned from each collection. “Microbial genomes contain complete sets of information that define an organism — much like how letters are a code allowing us to form words, sentences, pages, and books that contain complex but digestible knowledge,” Clark says. He thinks of the environmental samples as biological libraries, filled with thousands of species, strains, and sequence variants. “It’s our job to glean genetic information from these samples.”
“We can actually dream up new proteins using generative AI," Pushpanath says.
Basecamp researchers manage this feat by sequencing the DNA and then assembling the information into a comprehensible structure. “We’re building the ‘stories’ of the biota,” Clark says. The more varied the samples, the more valuable insights his team gains into the characteristics of different organisms and their interactions with the environment. Sequencing allows scientists to examine the order of nucleotides — the organic molecules that form DNA — to identify genetic makeups and find changes within genomes. The process used to be too expensive, but the cost of sequencing has dropped from $10,000 a decade ago to as low as $100. Notably, biocatalysis isn’t a new concept — there have been waves of interest in using natural enzymes in catalysis for over a century, Pushpanath says. “But the technology just wasn’t there to make it cost effective,” he explains. “Sequencing has been the biggest boon.”
AI is probably the second biggest boon.
“We can actually dream up new proteins using generative AI,” Pushpanath says, which means that biocataylsis now has real potential to scale.
Glen Gowers, the co-founder of Basecamp, compares the company’s AI approach to that of social networks and streaming services. Consider how these platforms suggest connecting with the friends of your friends, or how watching one comedy film from the 1990s leads to a suggestion of three more.
“They’re thinking about data as networks of relationships as opposed to lists of items,” says Gowers. “By doing the same, we’re able to link the metadata of the proteins — by their relationships to each other, the environments in which they’re found, the way those proteins might look similar in sequence and structure, their surrounding genome context — really, this just comes down to creating a searchable network of proteins.”
On an Azores island, this volcanic opening may harbor organisms that can help scientists identify enzymes for biocatalysis to replace toxic chemicals.
Uwe Bornscheuer, professor at the Institute of Biochemistry at the University of Greifswald, and co-founder of Enzymicals, another biocatalysis company, says that the development of machine learning is a critical component of this work. “It’s a very hot topic, because the challenge in protein engineering is to predict which mutation at which position in the protein will make an enzyme suitable for certain applications,” Bornscheuer explains. These predictions are difficult for humans to make at all, let alone quickly. “It is clear that machine learning is a key technology.”
Benefiting from nature’s bounty
Biodiversity commonly refers to plants and animals, but the term extends to all life, including microbial life, and some regions of the world are more biodiverse than others. Building relationships with global partners is another key element to Basecamp’s success. Doing so in accordance with the access and benefit sharing principles set forth by the Nagoya Protocol — an international agreement that seeks to ensure the benefits of using genetic resources are distributed in a fair and equitable way — is part of the company's ethos. “There's a lot of potential for us, and there’s a lot of potential for our partners to have exactly the same impact in building and discovering commercially relevant proteins and biochemistries from nature,” Clark says.
Bornscheuer points out that Basecamp is not the first company of its kind. A former San Diego company called Diversa went public in 2000 with similar work. “At that time, the Nagoya Protocol was not around, but Diversa also wanted to ensure that if a certain enzyme or microorganism from Costa Rica, for example, were used in an industrial process, then people in Costa Rica would somehow profit from this.”
An eventual merger turned Diversa into Verenium Corporation, which is now a part of the chemical producer BASF, but it laid important groundwork for modern companies like Basecamp to continue to scale with today’s technologies.
“To collect natural diversity is the key to identifying new catalysts for use in new applications,” Bornscheuer says. “Natural diversity is immense, and over the past 20 years we have gained the advantages that sequencing is no longer a cost or time factor.”
This has allowed Basecamp to rapidly grow its database, outperforming Universal Protein Resource or UniProt, which is the public repository of protein sequences most commonly used by researchers. Basecamp’s database is three times larger, totaling about 900 million sequences. (UniProt isn’t compliant with the Nagoya Protocol, because, as a public database, it doesn’t provide traceability of protein sequences. Some scientists, however, argue that Nagoya compliance hinders progress.)
“Eventually, this work will reduce chemical processes. We’ll have cleaner processes, more sustainable processes," says Uwe Bornscheuer, a professor at the University of Greifswald.
With so much information available, Basecamp’s AI has been trained on “the true dictionary of protein sequence life,” Pushpanath says, which makes it possible to design sequences for particular applications. “Through deep learning approaches, we’re able to find protein sequences directly from our database, without theneed for further laboratory-directed evolution.”
Recently, a major chemical company was searching for a specific transaminase — an enzyme that catalyzes a transfer of amino groups. “They had already spent a year-and-a-half and nearly two million dollars to evolve a public-database enzyme, and still had not reached their goal,” Pushpanath says. “We used our AI approaches on our novel database to yield 10 candidates within a week, which, when validated by the client, achieved the desired target even better than their best-evolved candidate.”
Basecamp’s other huge potential is in bioremediation, where natural enzymes can help to undo the damage caused by toxic chemicals. “Biocatalysis impacts both sides,” says Gowers. “It reduces the usage of chemicals to make products, and at the same time, where contamination sites do exist from chemical spills, enzymes are also there to kind of mop those up.”
So far, Basecamp's round-the-world sampling has covered 50 percent of the 14 major biomes, or regions of the planet that can be distinguished by their flora, fauna, and climate, as defined by the World Wildlife Fund. The other half remains to be catalogued — a key milestone for understanding our planet’s protein diversity, Pushpanath notes.
There’s still a long road ahead to fully replace petrochemicals with natural enzymes, but biocatalysis is on an upward trajectory. "Eventually, this work will reduce chemical processes,” Bornscheuer says. “We’ll have cleaner processes, more sustainable processes.”
Dave Arnold retired in his 60s and began spending time volunteering in local schools. But then he started misplacing items, forgetting appointments and losing his sense of direction. Eventually he was diagnosed with early stage Alzheimer’s.
“Hearing the diagnosis made me very emotional and tearful,” he said. “I immediately thought of all my mom had experienced.” His mother suffered with the condition for years before passing away. Over the last year, Arnold has worked for the Alzheimer’s Association as one of its early stage advisors, sharing his insights to help others in the initial stages of the disease.
Arnold was diagnosed sooner than many others. It's important to find out early, when interventions can make the most difference. One promising avenue is looking at how people talk. Research has shown that Alzheimer’s affects a part of the brain that controls speech, resulting in small changes before people show other signs of the disease.
Now, Canary Speech, a company based in Utah, is using AI to examine elements like the pitch of a person’s voice and their pauses. In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Developing the AI model
Canary Speech’s CEO, Henry O’Connell, met cofounder Jeff Adams about 40 years before they started the company. Back when they first crossed paths, they were both living in Bethesda, Maryland; O’Connell was a research fellow at the National Institutes of Health studying rare neurological diseases, while Adams was working to decode spy messages. Later on, Adams would specialize in building mathematical models to analyze speech and sound as a team leader in developing Amazon's Alexa.
It wasn't until 2015 that they decided to make use of the fit between their backgrounds. ““We established Canary Speech in 2017 to build a product that could be used in multiple languages in clinical environments,” O'Connell says.
The need is growing. About 55 million people worldwide currently live with Alzheimer’s, a number that is expected to double by 2050. Some scientists think the disease results from a buildup of plaque in the brain. It causes mild memory loss at first and, over time, this issue get worse while other symptoms, such as disorientation and hallucinations, can develop. Treatment to manage the disease is more effective in the earlier stages, but detection is difficult since mild symptoms are often attributed to the normal aging process.
O’Connell and Adams specialize in the complex ways that Alzheimer’s effects how people speak. Using AI, their mathematical model analyzes 15 million data points every minute, focusing on certain features of speech such as pitch, pauses and elongation of words. It also pays attention to how the vibrations of vocal cords change in different stages of the disease.
To create their model, the team used a type of machine learning called deep neural nets, which looks at multiple layers of data - in this case, the multiple features of a person’s speech patterns.
“Deep neural nets allow us to look at much, much larger data sets built out of millions of elements,” O’Connell explained. “Through machine learning and AI, we’ve identified features that are very sensitive to an Alzheimer’s patient versus [people without the disease] and also very sensitive to mild cognitive impairment, early stage and moderate Alzheimer's.” Based on their learnings, Canary is able to classify the disease stage very quickly, O’Connell said.
“When we’re listening to sublanguage elements, we’re really analyzing the direct result of changes in the brain in the physical body,” O’Connell said. “The brain controls your vocal cords: how fast they vibrate, the expansion of them, the contraction.” These factors, along with where people put their tongues when talking, function subconsciously and result in subtle changes in the sounds of speech.
Further testing is needed
In an initial trial, Canary analyzed speech recordings from phone calls to a large U.S. health insurer. They looked at the audio recordings of 651 policyholders who had early stage Alzheimer’s and 1018 who did not have the condition, aiming for a representative sample of age, gender and race. They used this data to create their first diagnostic model and found that it was 96 percent accurate in identifying Alzheimer’s.
Christian Herff, an assistant professor of neuroscience at Maastricht University in the Netherlands, praised this approach while adding that further testing is needed to assess its effectiveness.
“I think the general idea of identifying increased risk for cognitive impairment based on speech characteristics is very feasible, particularly when change in a user’s voice is monitored, for example, by recording speech every year,” Herff said. He noted that this can only be a first indication, not a full diagnosis. The accuracy still needs to be validated in studies that follows individuals over a period of time, he said.
Toby Walsh, a professor of artificial intelligence at the University of New South Wales, also thinks Canary’s tool has potential but highlights that Canary could diagnose some people who don’t really have the disease. “This is an interesting and promising application of AI,” he said, “but these tools need to be used carefully. Imagine the anxiety of being misdiagnosed with Alzheimer’s.”
As with many other AI tools, privacy and bias are additional issues to monitor closely, Walsh said.
A related issue is that not everyone is fluent in English. Mahnaz Arvaneh, a senior lecturer in automatic control and systems engineering at the University of Sheffield, said this could be a blind spot.
“The system may not be very accurate for those who have English as their second language as their speaking patterns would be different, and any issue might be because of language deficiency rather than cognitive issues,” Arvaneh said.
The team is expanding to multiple languages starting with Japanese and Spanish. The elements of the model that make up the algorithm are very similar, but they need to be validated and retrained in a different language, which will require access to more data.
Recently, Canary analyzed the phone calls of 233 Japanese patients who had mild cognitive impairment and 704 healthy people. Using an English model they were able to identify the Japanese patients who had mild cognitive impairment with 78 percent accuracy. They also developed a model in Japanese that was 45 percent accurate, and they’re continuing to train it with more data.
Canary is using their model to look at other diseases like Huntington’s and Parkinson’s. They’re also collaborating with pharmaceuticals to validate potential therapies for Alzheimer’s. By looking at speech patterns over time, Canary can get an indication of how well these drugs are working.
Dave Arnold and his wife dance at his nephew’s wedding in Rochester, New York, ten years ago, before his Alzheimer's diagnosis.
Ultimately, they want to integrate their tool into everyday life. “We want it to be used in a smartphone, or a teleconference call so that individuals could be examined in their home,” O’Connell said. “We could follow them over time and work with clinical teams and hospitals to improve the evaluation of patients and contribute towards an accurate diagnosis.”
Arnold, the patient with early stage Alzheimer’s, sees great promise. “The process of getting a diagnosis is already filled with so much anxiety,” he said. “Anything that can be done to make it easier and less stressful would be a good thing, as long as it’s proven accurate.”