scientificamerican--2020-10-03--The Science of America's Dueling Political Narratives

Whatever else one might say about the Trump era in American politics , it ’ s provided a wealth of data for scientists studying public opinion .
For those of us interested in “ metanarratives ” —the stories that groups tell themselves about who they are and where they ’ re headed—the 2016 and 2020 campaigns have been a gold mine .
Every vision of America has a metanarrative at its core .
Are we a land of endless opportunity , a beacon for the world ’ s huddled masses ?
Are we the world ’ s lone superpower , @ @ @ @ @ @ @ , every social movement and every political campaign offers its own answers to questions like these , and for the people who believe these answers , these stories can be vital to their identity .
The science of metanarratives and how we respond to them is still in its infancy .
Our research team , headed by psychologist Gerard Saucier , has uncovered the metanarratives typical of terrorists and genocidal leaders worldwide .
More broadly , my own work seeks to understand how the structure and features of metanarratives can elicit emotional responses @ @ @ @ @ @ @ reactions .
Emotions arise when we make comparisons relevant to our own needs and desires .
We contrast our present circumstances with the future , the past and alternative versions of today .
Improvements make us happy and inspire us ; losses sadden or frustrate us .
If we can blame someone else for our loss , we may become angry with them .
And if we ’ re faced with threats , our fear can motivate action .
As with fiction , we can categorize metanarratives by their emotional “ genres , @ @ @ @ @ @ @ optimism ) or looming catastrophe ( fear ) .
The metanarratives in U.S. presidential elections are usually predictable .
Each party wants progress , although the Democratic and Republican “ flavors ” of progress tend to differ .
Each party also wants the stability needed for progress to work , so that policies can have predictable outcomes .
The party in office typically offers more progress , or preserving a Triumph its administration achieved ; the other promises a course correction back toward its own goals .
Compared with the usual metanarratives , @ @ @ @ @ @ @ much more dynamic .
First , he introduced a restoration story line , a promise to “ Make America Great Again.
” This story line contrasts an idealized past and potential future with a fallen present , creating more dramatic emotional contrasts than a course correction .
But Trump didn ’ t stop there .
“ Drain the Swamp ” and even “ Lock Her Up !
” were examples of transformation—an abrupt end to “ business as usual.
” His infrastructure expansion plans were classic Progress , and his nomination by the @ @ @ @ @ @ @ party faithful .
Voters could latch onto whichever vision most resonated with them , ignoring the others .
The drama in Trump ’ s metanarratives excited new segments of the public and helps explain his appeal , both to Republicans and others ( like 12 percent of previous Bernie Sanders voters ) .
As cognitive scientists George Lakoff and Drew Westen remind us , it ’ s emotion that wins elections .
If we like , we can picture Trump as an amateur scientist , conducting a rudimentary experiment to see if new @ @ @ @ @ @ @ , the Democrats tried an informal experiment of their own , weighing the motivational power of the usual progress/stability versus a Sanders “ revolution ” to sharply reorient government priorities .
They concluded the temporary loss of stability from a transformation would cause too much collective anxiety , and went with Hillary Clinton , then Joe Biden .
Biden ’ s early metanarrative choices had been vaguely along the expected course correction line , but by the Democratic National Convention he ’ d settled on a much stronger genre , the crossroads .
@ @ @ @ @ @ @ the Soul of the Nation ” and his references to “ inflection points ” portray America as at a critical juncture .
In narrative terms , this story line sets up suspense between two possible outcomes—as Biden put it , “ shadow and suspicion ” versus “ hope and light ” —a suspense that makes our votes meaningful , as we each participate in its resolution .
Trump ’ s reelection slogan , “ Keep America Great , ” is a triumph story line that logically follows a restoration , yielding pride and @ @ @ @ @ @ @ is vulnerable .
His RNC speech also featured progress ( such as “ new frontiers of ambition and discovery ” ) , a course correction ( including “ returning to full employment ” and “ rekindle new faith in our values ” ) , and his own version of a crossroads : either “ save the American Dream ” or “ allow a socialist agenda to demolish our cherished destiny.
” Trump ’ s kitchen-sink approach to conveying a vision for the country means we can ’ t compare the effectiveness of one @ @ @ @ @ @ @ are impractical .
However , we can still explore the factors influencing our reactions to different story lines .
The public doesn ’ t accept every metanarrative it 's offered .
We tend to be loyal to the cultural beliefs favored by our social circles and encouraged by our leaders .
Even then , some voters stay open to alternatives , if there ’ s enough dissonance between the party line and their own experiences .
A useful analogy again comes from narrative science .
Psychologist Keith Oatley has described three ways to @ @ @ @ @ @ @ such that its emotional world becomes our own ; reflectively exploring its ideas by making our own connections and thinking critically ; or staying emotionally detached .
Similarly , we can treat the metanarratives in our lives as truths we shouldn ’ t question , potentially valid perspectives we can weigh and choose among , or just plain wrong .
Trump favors a “ full immersion ” approach , with his affinity for sensory-rich rallies and his insistence on personal loyalty .
Biden ’ s give-and-take style aligns more with critical thinking .
@ @ @ @ @ @ @ aren ’ t reflective Republicans or unquestioning Democrats ; of course there are .
My personal , untestable hypothesis is that the election ’ s bottom line will be emotional .
As they weigh the personalities , policies , and metanarrative visions offered by the candidates , voters may choose the one who best offers an end to 2020 's turmoil .
The newfound appeal of stability could be the deciding factor .
And as formal science works to catch up with the intuitive “ science ” practiced by politicians , we may @ @ @ @ @ @ @ metanarratives in action .

Whatever else one might say about the Trump era in American politics, it’s provided a wealth of data for scientists studying public opinion. For those of us interested in “metanarratives”—the stories that groups tell themselves about who they are and where they’re headed—the 2016 and 2020 campaigns have been a gold mine.
Every vision of America has a metanarrative at its core. Are we a land of endless opportunity, a beacon for the world’s huddled masses? Are we the world’s lone superpower, throwing its weight around? Every institution, every social movement and every political campaign offers its own answers to questions like these, and for the people who believe these answers, these stories can be vital to their identity.
The science of metanarratives and how we respond to them is still in its infancy. Our research team, headed by psychologist Gerard Saucier, has uncovered the metanarratives typical of terrorists and genocidal leaders worldwide. More broadly, my own work seeks to understand how the structure and features of metanarratives can elicit emotional responses, and how social factors influence public reactions.
Emotions arise when we make comparisons relevant to our own needs and desires. We contrast our present circumstances with the future, the past and alternative versions of today. Improvements make us happy and inspire us; losses sadden or frustrate us. If we can blame someone else for our loss, we may become angry with them. And if we’re faced with threats, our fear can motivate action. As with fiction, we can categorize metanarratives by their emotional “genres,” such as progress (pride, optimism) or looming catastrophe (fear).
The metanarratives in U.S. presidential elections are usually predictable. Each party wants progress, although the Democratic and Republican “flavors” of progress tend to differ. Each party also wants the stability needed for progress to work, so that policies can have predictable outcomes. The party in office typically offers more progress, or preserving a Triumph its administration achieved; the other promises a course correction back toward its own goals.
Compared with the usual metanarratives, Donald Trump’s 2016 campaign was much more dynamic. First, he introduced a restoration story line, a promise to “Make America Great Again.” This story line contrasts an idealized past and potential future with a fallen present, creating more dramatic emotional contrasts than a course correction. But Trump didn’t stop there. “Drain the Swamp” and even “Lock Her Up!” were examples of transformation—an abrupt end to “business as usual.” His infrastructure expansion plans were classic Progress, and his nomination by the conservative GOP promised the stability valued by party faithful. Voters could latch onto whichever vision most resonated with them, ignoring the others. The drama in Trump’s metanarratives excited new segments of the public and helps explain his appeal, both to Republicans and others (like 12 percent of previous Bernie Sanders voters). As cognitive scientists George Lakoff and Drew Westen remind us, it’s emotion that wins elections.
If we like, we can picture Trump as an amateur scientist, conducting a rudimentary experiment to see if new metanarratives would inspire the public. Meanwhile, the Democrats tried an informal experiment of their own, weighing the motivational power of the usual progress/stability versus a Sanders “revolution” to sharply reorient government priorities. They concluded the temporary loss of stability from a transformation would cause too much collective anxiety, and went with Hillary Clinton, then Joe Biden.
Biden’s early metanarrative choices had been vaguely along the expected course correction line, but by the Democratic National Convention he’d settled on a much stronger genre, the crossroads. Both his slogan, “Battle for the Soul of the Nation” and his references to “inflection points” portray America as at a critical juncture. In narrative terms, this story line sets up suspense between two possible outcomes—as Biden put it, “shadow and suspicion” versus “hope and light”—a suspense that makes our votes meaningful, as we each participate in its resolution.
Trump’s reelection slogan, “Keep America Great,” is a triumph story line that logically follows a restoration, yielding pride and self-satisfaction, but anxiety if the achievement is vulnerable. His RNC speech also featured progress (such as “new frontiers of ambition and discovery”), a course correction (including “returning to full employment” and “rekindle new faith in our values”), and his own version of a crossroads: either “save the American Dream” or “allow a socialist agenda to demolish our cherished destiny.”
Trump’s kitchen-sink approach to conveying a vision for the country means we can’t compare the effectiveness of one metanarrative against another. Such real-world experiments are impractical. However, we can still explore the factors influencing our reactions to different story lines.
The public doesn’t accept every metanarrative it's offered. We tend to be loyal to the cultural beliefs favored by our social circles and encouraged by our leaders. Even then, some voters stay open to alternatives, if there’s enough dissonance between the party line and their own experiences.
A useful analogy again comes from narrative science. Psychologist Keith Oatley has described three ways to read a book: deeply immersed, such that its emotional world becomes our own; reflectively exploring its ideas by making our own connections and thinking critically; or staying emotionally detached. Similarly, we can treat the metanarratives in our lives as truths we shouldn’t question, potentially valid perspectives we can weigh and choose among, or just plain wrong. Trump favors a “full immersion” approach, with his affinity for sensory-rich rallies and his insistence on personal loyalty. Biden’s give-and-take style aligns more with critical thinking. Which is not to say that there aren’t reflective Republicans or unquestioning Democrats; of course there are.
My personal, untestable hypothesis is that the election’s bottom line will be emotional. As they weigh the personalities, policies, and metanarrative visions offered by the candidates, voters may choose the one who best offers an end to 2020's turmoil. The newfound appeal of stability could be the deciding factor. And as formal science works to catch up with the intuitive “science” practiced by politicians, we may learn to better understand the functioning of metanarratives in action.


scientificamerican--2020-10-03--Can CBD Cure What Ails You?

Can CBD Cure What Ails You?

When a shop selling cannabidiol ( CBD ) , a compound found in marijuana , opened near the place where I get coffee in my Southern California neighborhood , I was of two minds .
Actually , for several weeks I was of one mind , which was to wish for the speedy demise of the business .
As a physician , I just know too much about some of the deleterious consequences associated with marijuana use : memory issues , altered judgment , addiction , longer-term cognitive issues , chronic bronchitis symptoms , and so on .
But as @ @ @ @ @ @ @ glimpse the other side of the conversation .
In the end , I spent quality time with the supervisors of three CBD stores in my area , and each had inspiring stories to share of customers who alleviated their aches , overcame chronic pain , reduced stress , had a good night ’ s sleep or got a semblance of their lives back .
They told me stories like that of Lorraine , who had been bucked off a horse , broke some vertebrae , was ridden with chronic pain , yet experienced @ @ @ @ @ @ @ a month , she rode her horse 400 miles through the south of Spain .
That ’ s certainly storybook enough .
So , is CBD a miracle cure ?
Despite its promise , if you ’ re someone who hopes to read that science proves CBD is a wonder product , I ’ m afraid this isn ’ t the place to look .
The truth is unforgiving .
The studies around pure CBD—that is , CBD without THC—are limited due to the fact that some are small and inconsistently designed .
@ @ @ @ @ @ @ Health Organization Expert Committee on Drug Dependence , told me in an interview that he believes the number of randomized control trials ( RCTS ) specific to pure CBD is small , likely fewer than 10 .
Outside of one prescription drug created to treat two rare pediatric seizure disorders , the Food and Drug Administration ( FDA ) has not evaluated or approved pure CBD for any therapeutic use .
This is a thicket of often conflicting claims .
Before we go any deeper , let ’ s cover the basics .
@ @ @ @ @ @ @ plant does have more than 100 different compounds within it called cannabinoids .
Its primary component is THC , which has the psychotropic properties that give users the feeling of being “ high.
” CBD is the second-most prevalent component , and does not have this same effect .
Perhaps more significant , THC and CBD are also found in hemp , but the THC concentrations are very low .
In the U.S. , hemp plants by definition have no more than 0.3 percent THC , while marijuana plants are bred to have @ @ @ @ @ @ @ is primarily used as a drug , hemp is found in all sorts of products , including fabrics and textiles , paper , food , animal feed and supplements .
CBD ’ s popularity has skyrocketed because of its purported therapeutic benefits , along with a low potential for abuse .
There ’ s also plenty of it , and it ’ s profitable .
According to Julian Wright , Founder of Science and Recreation , farmers can make $ 60,000 per acre to produce hemp high in CBD , versus $ 750 @ @ @ @ @ @ @ .
The commercial market for CBD , meanwhile , is projected to rise from an estimated $ 500 million in 2018 to $ 1.8 billion by 2022 .
Why so popular ?
Well , CBD is being marketed as a health supplement and a medicine , with the ability to reduce inflammation , lessen pain and reduce anxiety as well as to potentially help alleviate other conditions like post-traumatic stress disorder , some of the side effects of chemotherapy , and even spasticity associated with multiple sclerosis .
The Hemp Farming Act of @ @ @ @ @ @ @ Schedule 1 substance , like marijuana , to an agricultural product that could now be grown and distributed legally .
Though CBD is legal to sell , the FDA has made it clear that unapproved CBD products can not be in food , beverages , cosmetics or sold as a dietary supplement ; neither can they be marketed with unsubstantiated health claims .
CBD can be purchased as oils , tinctures , sprays , creams , capsules , lollipops , chocolates , energy bars , trail mix and gummies , among other things @ @ @ @ @ @ @ ( According to Pam Miles , past president of the Association of Food and Drug Officials , one restaurant chain offered sandwiches infused with CBD as part of a promotion , so you know we ’ re already there in terms of availability . )
I visited three stores in the San Diego area .
At the Golden State Greens shop , the supervisor , Jake C. told me his customers use CBD primarily for stress , anxiety , insomnia and pain , including several cancer patients who found that the product helped @ @ @ @ @ @ @ they ’ d lost while undergoing treatments .
Shawn McManigal , owner of the Injoi CBD store in La Jolla , said a 92-year-old customer of his stopped taking his constipating pain medications after realizing that CBD gummies relieved the pain and allowed him to rest .
“ I ’ m not saying this is a miracle cure , ” McManigal told me , “ but there is science behind it and it really proves what it does.
” Does it , though ?
The question of what pure CBD ( without THC @ @ @ @ @ @ @ genuinely difficult to answer .
Much of the peer-reviewed research looks at CBD as a medicinal drug or includes cannabis in the study .
In a review of 79 randomized clinical trials ( RCTS ) of cannabinoids for the below indications , the authors found moderate-quality evidence for cannabinoid use for the treatment of chronic pain and spasticity , and only low quality evidence for improvements in vomiting resulting from chemotherapy , weight gain in HIV infection , sleep disorders and Tourette syndrome .
But the study was limited because it included multiple @ @ @ @ @ @ @ by different routes , with many products containing THC .
Jason White , who chairs the World Health Organization Expert Committee on Drug Dependence , told me he believes CBD will prove efficacious for a broader range of seizure types , that it likely has some anti-psychotic efficacy , and that it may help improve the quality of life among those who suffer from Parkinson ’ s disease .
In studies , CBD has been found to treat certain types of seizures , has benefited schizophrenia patients with psychotic symptoms in two of @ @ @ @ @ @ @ of daily life and sleep in Parkinson ’ s patients in early trials .
On the other hand , a review that included 83 studies ( 40 of them RCTs ) involving over 3,000 people with various mental health conditions found that there was “ scarce evidence ” to show that cannabinoids improved depression or anxiety disorders , attention-deficit hyperactivity disorder , Tourette syndrome , post-traumatic stress disorder or psychosis .
One of the most comprehensive reports , produced by the National Academies of Sciences , Engineering , and Medicine , examined over @ @ @ @ @ @ @ evidence existed for CBD treatment of three conditions : chronic pain , chemotherapy-induced vomiting and muscle spasms .
The active components of cannabis have been shown to modulate the immune system and inflammation yet a WHO report concluded that CBD ’ s effect on the immune system is unclear with evidence showing suppression at higher doses , but stimulation at lower doses .
You can see the limits of existing CBD research : multiple small trials that yield conflicting results , along with RCTs and meta-analyses that too often include marijuana and mixed @ @ @ @ @ @ @ products—many of them in varying amounts .
These certainly influence the results , and they also leave consumers rightly wondering what the proper dose for them might be .
“ You don ’ t know the dose , you don ’ t know the formulation and therefore [ you don ’ t know ] the absorption , ” White told me .
“ In a lot of places , it 's essentially a backyard pharmacy where people just sort of make it up… .
When you get in a situation where people are @ @ @ @ @ @ @ is really out of control.
” As for potential users , “ low and slow ” was the refrain from the CBD store managers with whom I spoke .
With CBD tincture , for example , McManigal recommended placing a half of vial of oil under the tongue—the equivalent of 17 milligrams in his formulation—and waiting 45 minutes to an hour .
“ If you don ’ t feel the effect of being more relaxed , use more , ” he said .
According to a WHO report , CBD is generally well-tolerated @ @ @ @ @ @ @ in humans it exhibits no effects that would indicate potential for abuse or dependence .
The side effects are generally mild and may include sleepiness , diarrhea , mood changes , etc.
, but concerns exist of potential liver injury , medication interactions , and male fertility issues .
White said there is little known about the effects of sustained and/or cumulative use of CBD , or its use in special populations like adolescents , the elderly and pregnant women .
The FDA is investigating reports of CBD containing such dangerous contaminants as @ @ @ @ @ @ @ lead ) , pesticides , bacteria and fungi .
Law enforcement agencies found that 128 samples out of more than 350 tested by government labs in nine states had synthetic marijuana in products being sold as CBD .
At Golden State Greens shop , Jake C. told me that CBD containing THC is highly regulated by the state of California , and he believes the products to be safe and labeled appropriately .
However , he said over-the-counter hemp-derived CBD ( depending on state regulations ) or black-market cannabis product , could have @ @ @ @ @ @ @ , to say nothing of potential contaminants .
The lack of high-quality studies reflects the hoops one has to jump though to conduct marijuana research .
Regulatory barriers need to be streamlined and funding sources need to be identified so that large , well-designed RCTs can be conducted to explore the beneficial and harmful health effects of CBD use , which ultimately would better inform states , the FDA and the public .
Currently , there are 120 clinical trials registered ( planned , recruiting , or active ) which are investigating CBD @ @ @ @ @ @ @ can provide much needed answers .
`` This industry is not going to go away .
Our sales are up , ” one shop owner told me .
All the more reason for us to do the research , prove CBD ’ s efficacy , standardize dosing and ensure quality , among other things .
I no longer growl when I pass my local store ; the people there genuinely believe they ’ re doing a good thing .
Let ’ s find out if they ’ re right .

When a shop selling cannabidiol (CBD), a compound found in marijuana, opened near the place where I get coffee in my Southern California neighborhood, I was of two minds. Actually, for several weeks I was of one mind, which was to wish for the speedy demise of the business. As a physician, I just know too much about some of the deleterious consequences associated with marijuana use: memory issues, altered judgment, addiction, longer-term cognitive issues, chronic bronchitis symptoms, and so on.
But as the days passed, I began to glimpse the other side of the conversation. In the end, I spent quality time with the supervisors of three CBD stores in my area, and each had inspiring stories to share of customers who alleviated their aches, overcame chronic pain, reduced stress, had a good night’s sleep or got a semblance of their lives back. They told me stories like that of Lorraine, who had been bucked off a horse, broke some vertebrae, was ridden with chronic pain, yet experienced such dramatic improvement with CBD that after a month, she rode her horse 400 miles through the south of Spain.
That’s certainly storybook enough. So, is CBD a miracle cure? Despite its promise, if you’re someone who hopes to read that science proves CBD is a wonder product, I’m afraid this isn’t the place to look.
The truth is unforgiving. The studies around pure CBD—that is, CBD without THC—are limited due to the fact that some are small and inconsistently designed. Jason White, who chairs the World Health Organization Expert Committee on Drug Dependence, told me in an interview that he believes the number of randomized control trials (RCTS) specific to pure CBD is small, likely fewer than 10. Outside of one prescription drug created to treat two rare pediatric seizure disorders, the Food and Drug Administration (FDA) has not evaluated or approved pure CBD for any therapeutic use. This is a thicket of often conflicting claims.
Before we go any deeper, let’s cover the basics. I mentioned marijuana above, and that plant does have more than 100 different compounds within it called cannabinoids. Its primary component is THC, which has the psychotropic properties that give users the feeling of being “high.” CBD is the second-most prevalent component, and does not have this same effect.
Perhaps more significant, THC and CBD are also found in hemp, but the THC concentrations are very low. In the U.S., hemp plants by definition have no more than 0.3 percent THC, while marijuana plants are bred to have much higher levels. And where marijuana is primarily used as a drug, hemp is found in all sorts of products, including fabrics and textiles, paper, food, animal feed and supplements.
CBD’s popularity has skyrocketed because of its purported therapeutic benefits, along with a low potential for abuse. There’s also plenty of it, and it’s profitable. According to Julian Wright, Founder of Science and Recreation, farmers can make $60,000 per acre to produce hemp high in CBD, versus $750 per acre in hemp sold for fiber. The commercial market for CBD, meanwhile, is projected to rise from an estimated $500 million in 2018 to $1.8 billion by 2022.
Why so popular? Well, CBD is being marketed as a health supplement and a medicine, with the ability to reduce inflammation, lessen pain and reduce anxiety as well as to potentially help alleviate other conditions like post-traumatic stress disorder, some of the side effects of chemotherapy, and even spasticity associated with multiple sclerosis. The Hemp Farming Act of 2018 reclassified hemp from a highly controlled Schedule 1 substance, like marijuana, to an agricultural product that could now be grown and distributed legally.
Though CBD is legal to sell, the FDA has made it clear that unapproved CBD products cannot be in food, beverages, cosmetics or sold as a dietary supplement; neither can they be marketed with unsubstantiated health claims. CBD can be purchased as oils, tinctures, sprays, creams, capsules, lollipops, chocolates, energy bars, trail mix and gummies, among other things. It can even be vaped. (According to Pam Miles, past president of the Association of Food and Drug Officials, one restaurant chain offered sandwiches infused with CBD as part of a promotion, so you know we’re already there in terms of availability.)
I visited three stores in the San Diego area. At the Golden State Greens shop, the supervisor, Jake C. told me his customers use CBD primarily for stress, anxiety, insomnia and pain, including several cancer patients who found that the product helped them sleep and perhaps regain some weight they’d lost while undergoing treatments. Shawn McManigal, owner of the Injoi CBD store in La Jolla, said a 92-year-old customer of his stopped taking his constipating pain medications after realizing that CBD gummies relieved the pain and allowed him to rest. “I’m not saying this is a miracle cure,” McManigal told me, “but there is science behind it and it really proves what it does.”
Does it, though? The question of what pure CBD (without THC) has been proven to treat is genuinely difficult to answer. Much of the peer-reviewed research looks at CBD as a medicinal drug or includes cannabis in the study. In a review of 79 randomized clinical trials (RCTS) of cannabinoids for the below indications, the authors found moderate-quality evidence for cannabinoid use for the treatment of chronic pain and spasticity, and only low quality evidence for improvements in vomiting resulting from chemotherapy, weight gain in HIV infection, sleep disorders and Tourette syndrome. But the study was limited because it included multiple cannabinoids that were evaluated at different doses by different routes, with many products containing THC.
Jason White, who chairs the World Health Organization Expert Committee on Drug Dependence, told me he believes CBD will prove efficacious for a broader range of seizure types, that it likely has some anti-psychotic efficacy, and that it may help improve the quality of life among those who suffer from Parkinson’s disease. In studies, CBD has been found to treat certain types of seizures, has benefited schizophrenia patients with psychotic symptoms in two of three RCTS, and has improved activities of daily life and sleep in Parkinson’s patients in early trials.
On the other hand, a review that included 83 studies (40 of them RCTs) involving over 3,000 people with various mental health conditions found that there was “scarce evidence” to show that cannabinoids improved depression or anxiety disorders, attention-deficit hyperactivity disorder, Tourette syndrome, post-traumatic stress disorder or psychosis.
One of the most comprehensive reports, produced by the National Academies of Sciences, Engineering, and Medicine, examined over 10,000 scientific abstracts and concluded that substantial evidence existed for cannabis and cannabinoid treatment of three conditions: chronic pain, chemotherapy-induced vomiting and muscle spasms. “There was little or no evidence for any therapeutic effects of CBD,” according to oncologist Donald Abrams, one of the study’s committee members. The active components of cannabis have been shown to modulate the immune system and inflammation, yet a WHO report concluded that CBD’s effect on the immune system is unclear, with evidence showing suppression at higher doses but stimulation at lower doses.*
You can see the limits of existing CBD research: multiple small trials that yield conflicting results, along with RCTs and meta-analyses that too often include marijuana and mixed THC/CBD compounds rather than just pure CBD products—many of them in varying amounts. These certainly influence the results, and they also leave consumers rightly wondering what the proper dose for them might be.
“You don’t know the dose, you don’t know the formulation and therefore [you don’t know] the absorption,” White told me. “In a lot of places, it's essentially a backyard pharmacy where people just sort of make it up…. When you get in a situation where people are kind of doing it themselves then that is really out of control.”
As for potential users, “low and slow” was the refrain from the CBD store managers with whom I spoke. With CBD tincture, for example, McManigal recommended placing a half of vial of oil under the tongue—the equivalent of 17 milligrams in his formulation—and waiting 45 minutes to an hour. “If you don’t feel the effect of being more relaxed, use more,” he said.
According to a WHO report, CBD is generally well-tolerated with a good safety profile, and in humans it exhibits no effects that would indicate potential for abuse or dependence. The side effects are generally mild and may include sleepiness, diarrhea, mood changes, etc., but concerns exist of potential liver injury, medication interactions, and male fertility issues. White said there is little known about the effects of sustained and/or cumulative use of CBD, or its use in special populations like adolescents, the elderly and pregnant women.
The FDA is investigating reports of CBD containing such dangerous contaminants as unhealthy levels of heavy metals (including lead), pesticides, bacteria and fungi. Law enforcement agencies found that 128 samples out of more than 350 tested by government labs in nine states had synthetic marijuana in products being sold as CBD.
At Golden State Greens shop, Jake C. told me that CBD containing THC is highly regulated by the state of California, and he believes the products to be safe and labeled appropriately. However, he said over-the-counter hemp-derived CBD (depending on state regulations) or black-market cannabis product, could have wildly varying amounts of THC and CBD, to say nothing of potential contaminants.
The lack of high-quality studies reflects the hoops one has to jump though to conduct marijuana research. Regulatory barriers need to be streamlined and funding sources need to be identified so that large, well-designed RCTs can be conducted to explore the beneficial and harmful health effects of CBD use, which ultimately would better inform states, the FDA and the public. Currently, there are 120 clinical trials registered (planned, recruiting, or active) which are investigating CBD; hopefully, some of these trials can provide much needed answers.
"This industry is not going to go away. Our sales are up,” one shop owner told me. All the more reason for us to do the research, prove CBD’s efficacy, standardize dosing and ensure quality, among other things. I no longer growl when I pass my local store; the people there genuinely believe they’re doing a good thing. Let’s find out if they’re right.
*Editor’s Note (10/5/20): This paragraph was edited after posting to correct the description of the report by the National Academies of Sciences, Engineering, and Medicine.


scientificamerican--2020-10-03--Diagnosing COVID From a Person's Voice

Diagnosing COVID From a Person's Voice

In March , as the staggering scope of the coronavirus pandemic started to become clear , officials around the world began enlisting the public to join in the fight .
Hospitals asked local companies to donate face masks .
Researchers called on people who had recovered from COVID-19 to donate their blood plasma .
And in Israel , the defence ministry and a start-up company called Vocalis Health asked people to donate their voices .
Vocalis , a voice-analysis company with offices in Israel and the United States , had previously built a smartphone app that could detect flare-ups of @ @ @ @ @ @ @ signs that users were short of breath when speaking .
The firm wanted to do the same thing with COVID-19 .
People who had tested positive for the coronavirus could participate simply by downloading a Vocalis research app .
Once a day , they fired up the app and spoke into their phones , describing an image aloud and counting from 50 to 70 .
Then Vocalis began processing these recordings with its machine-learning system , alongside the voices of people who had tested negative for the disease , in an attempt to @ @ @ @ @ @ @ By mid-summer , the firm had more than 1,500 voice samples and a pilot version of a digital COVID-19 screening tool .
The tool , which the company is currently testing around the world , is not intended to provide a definitive diagnosis , but to help clinicians triage potential cases , identifying people who might be most in need of testing , quarantine or in-person medical care .
“ Can we help with our AI algorithm ?
” asks Tal Wenderow , the president and chief executive of Vocalis .
“ This @ @ @ @ @ @ @ not a drug , we ’ re not changing anything .
All you need to do is speak.
” They ’ re not the only ones racing to find vocal biomarkers of COVID-19—at least three other research groups are working on similar projects .
Other teams are analysing audio recordings of COVID-19 coughs and developing voice-analysis algorithms designed to detect when someone is wearing a face mask .
It ’ s a sign of how hungry the young field of vocal diagnostics is to make its mark .
Over the past decade , @ @ @ @ @ @ @ ) and machine-learning systems to identify potential vocal biomarkers of a wide variety of conditions , including dementia , depression , autism spectrum disorder and even heart disease .
The technologies they have developed are capable of picking out subtle differences in how people with certain conditions speak , and companies around the world are beginning to commercialize them .
For now , most teams are taking a slow , stepwise approach , designing tailored tools for use in doctors ’ offices or clinical trials .
But many dream of deploying this technology @ @ @ @ @ @ @ ubiquitous in consumer products to identify diseases and disorders .
These systems could one day allow epidemiologists to use smartphones to track the spread of disease , and turn smart speakers into in-home medical devices .
“ In the future , your robot , your Siri , your Alexa will simply say , ‘ Oh you ’ ve got a cold , ’ ” says Björn Schuller , a specialist in speech and emotion recognition with a joint position at the University of Augsburg in Germany and Imperial College London , who is @ @ @ @ @ @ @ But automated vocal analysis is still a new field , and has a number of potential pitfalls , from erroneous diagnoses to the invasion of personal and medical privacy .
Many studies remain small and preliminary , and moving from proof-of-concept to product won ’ t be easy .
“ We are at the early hour of this , ” Schuller says .
Some ailments cause obvious vocal distortions ; consider the telltale stuffiness of someone afflicted by allergies .
But many scientists think that vocal analysis could help to identify an enormous @ @ @ @ @ @ @ complexity of human speech .
Speaking requires the coordination of numerous anatomical structures and systems .
The lungs send air through the vocal cords , which produce sounds that are shaped by the tongue , lips and nasal cavities , among other structures .
The brain , along with other parts of the nervous system , helps to regulate all these processes and determine the words someone is saying .
A disease that affects any one of these systems might leave diagnostic clues in a person ’ s speech .
Machine learning has @ @ @ @ @ @ @ , quickly and at scale .
Researchers can now feed hundreds or thousands of voice samples into a computer to search for features that distinguish people with various medical conditions from those without them .
Much of the early work in the field focused on Parkinson ’ s disease , which has well-known effects on speech—and for which there is no definitive diagnostic test .
The disorder causes a variety of motor symptoms , including tremors , muscle stiffness and problems with balance and coordination .
The loss of control extends to the @ @ @ @ @ @ @ result , many people with Parkinson ’ s have weak , soft voices .
“ It ’ s one of those things that you can hear with the human ear , ” says Reza Hosseini Ghomi , a neuropsychiatrist at EvergreenHealth in Kirkland , Washington , who has identified vocal features associated with several neurodegenerative diseases .
“ But if you can get 10,000 samples and a computer , you can get much more accurate.
” More than a decade ago , Max Little , a researcher in machine learning and signal processing @ @ @ @ @ @ @ UK , began to investigate whether voice analysis might help doctors to make difficult diagnoses .
In one study , Little and his colleagues used audio recordings of 43 adults , 33 of whom had Parkinson ’ s disease , saying the syllable “ ahhh ” .
They used speech-processing algorithms to analyse 132 acoustic features of each recording , ultimately identifying 10—including characteristics such as breathiness and tremulous oscillations in pitch and timbre—that seemed to be most predictive of Parkinson ’ s .
Using just these 10 features , the system could @ @ @ @ @ @ @ people with the disease with nearly 99 % accuracy .
Little and others in the field have also demonstrated that certain vocal features correlate with the severity of Parkinson ’ s symptoms .
The systems are not yet robust enough for routine use in clinical practice , Little says , but there are many potential applications .
Vocal analysis might provide a quick , low-cost way to monitor individuals who are at high risk of the disease ; to screen large populations ; or possibly even to create a telephone service that could @ @ @ @ @ @ @ have access to a neurologist .
Patients could use the technology at home—in the form of a smartphone app , say—to track their own symptoms and monitor their response to medication .
“ This kind of technology can allow a high-speed snapshot , an almost continuous snapshot of how someone ’ s symptoms are changing , ” Little says .
Researchers are now working to identify speech-based biomarkers for other kinds of neurodegenerative disease .
For instance , a trio of scientists in Toronto , Canada , used voice samples and transcripts from @ @ @ @ @ @ @ of differences between the speech of people with possible or probable Alzheimer ’ s disease and that of people without it .
Among the participants , those with Alzheimer ’ s tended to use shorter words , smaller vocabularies and more sentence fragments .
They also repeated themselves and used a higher ratio of pronouns , such as ‘ it ’ or ‘ this ’ , to proper nouns .
“ It can be a sign that they ’ re just not remembering the names of things so they have to use pronouns @ @ @ @ @ @ @ a computer scientist at the University of Toronto , who led the study .
When the system considered 35 of these vocal features together , it was able to identify people with Alzheimer ’ s with 82 % accuracy .
( This has since improved to roughly 92 % , Rudzicz says , noting that the errors tend to be more or less evenly split between false negatives and false positives . )
“ Those features add up to sort of a fingerprint of dementia , ” Rudzicz says .
“ It ’ @ @ @ @ @ @ @ ’ s hard for us to see on the surface , but machine learning can pick it out , given enough data.
” Because some of these vocal changes occur in the early stages of neurodegenerative diseases , researchers hope that voice-analysis tools could eventually help clinicians to diagnose such conditions earlier and potentially intervene before other symptoms become obvious .
For now , however , this idea remains largely theoretical ; scientists still need to do large , long-term , longitudinal trials to demonstrate that voice analysis can actually detect disease earlier @ @ @ @ @ @ @ some clinicians note that voice analysis alone will rarely yield definitive diagnoses .
“ I learn a lot by listening to someone ’ s voice , ” says Norman Hogikyan , a laryngologist at the University of Michigan in Ann Arbor .
“ I do it for a living .
But I put it together with a history and then my exam .
All three parts of that assessment are important.
” Researchers in the field stress that the goal is not to replace doctors or create standalone diagnostic devices .
Instead , @ @ @ @ @ @ @ physicians can use to inform their decisions , as another ‘ vital sign ’ they can monitor or test they can order .
“ My vision is that collecting speech samples will become as common as a blood test , ” says Isabel Trancoso , a researcher in spoken-language processing at the University of Lisbon .
A number of voice-analysis start-ups—including Winterlight Labs , a Toronto firm co-founded by Rudzicz , and Aural Analytics in Scottsdale , Arizona—are now providing their software to pharmaceutical companies .
Many are using the technology to help @ @ @ @ @ @ @ trials are responding to experimental treatments .
“ Using speech as a more subtle proxy for changes in neurological health , you can help push drugs across the finish line or at the very least identify those that are not promising early on , ” says Visar Berisha , the co-founder and chief analytics officer at Aural Analytics .
Neurodegenerative disorders are just the beginning .
Scientists have identified distinct speech patterns in children with neurodevelopmental disorders .
In one small 2017 study , Schuller and his colleagues determined that algorithms that analysed @ @ @ @ @ @ @ with some accuracy which children would go on to be diagnosed with autism spectrum disorder .
The system correctly classified roughly 80 % of children with autism and 70 % of neurotypical children .
Researchers have also found that many children with attention deficit hyperactivity disorder speak louder and faster than their neurotypical peers , and show more signs of vocal strain .
The firm PeakProfiling in Berlin is now developing a clinical speech-analysis tool that it hopes can help doctors to diagnose the condition .
But some clinicians are sceptical about how @ @ @ @ @ @ @ provide .
“ Some of it is a little overblown , ” says Rhea Paul , a specialist in communication disorders at Sacred Heart University in Fairfield , Connecticut .
Children with neurodevelopmental disorders often have many easily observable behavioural symptoms , she notes .
Moreover , it ’ s not yet clear whether the algorithms are really identifying specific markers for , say , autism spectrum disorder , or just picking up on general signs of atypical brain development—or even just transient aberrations in speech .
“ Development is a meandering path @ @ @ @ @ @ @ looking like they have autism grows up to be an adult with autism , ” Paul says .
Even if scientists do identify a highly reliable , specific vocal biomarker , she adds , it should only be used to identify children who might benefit from a more thorough evaluation .
“ It shouldn ’ t be sufficient in and of itself to label a child , especially so early in life.
” Scientists are also turning the technology to mental illnesses .
Numerous teams around the world have developed systems that can @ @ @ @ @ @ @ , monotonous speech that tends to characterize depression , and others have identified vocal biomarkers associated with psychosis , suicidality and bipolar disorder .
“ Voice is enormously rich in terms of carrying our emotion signals , ” says Charles Marmar , a psychiatrist at New York University .
“ The rate , the rhythm , the volume , the pitch , the prosody [ stress and intonation ] —those features , they tell you whether a patient is down and discouraged , whether they ’ re agitated and anxious , or whether @ @ @ @ @ @ @ In his own work , Marmar has used machine learning to identify 18 vocal features associated with post-traumatic stress disorder ( PTSD ) in 129 male military veterans .
By analysing these features—which were mainly indicators of slow , flat , monotonous speech—the system could identify , with nearly 90 % accuracy , which of the veterans had PTSD .
Marmar and his colleagues are now expanding their research to women and civilians ; if the team can generalize the findings , Marmar thinks that the technology could be a useful way to @ @ @ @ @ @ @ more thorough psychiatric assessment .
“ The first real-world application would be for high-throughput screening of PTSD , ” he says .
“ You can do 4,000 voice screens in a matter of hours.
” Similar consumer applications are already beginning to make their way into the world .
The US Department of Veterans Affairs is studying whether an app that monitors mental health can identify service members experiencing psychological distress .
The smartphone app , developed by Cogito , a conversational guidance and analytics company in Boston , Massachusetts , collects metadata @ @ @ @ @ @ @ they call or text other people—and analyses voice memos they leave on their phones .
There might even be vocal biomarkers for conditions that seem to have nothing to do with speech .
In one study from 2018 , scientists analysing speech samples from 101 people who were scheduled to undergo coronary angiograms discovered that certain vocal frequency patterns were associated with more severe coronary artery disease .
It ’ s not clear what explains these differences .
“ We struggle with the mechanism because it ’ s not obvious , ” says @ @ @ @ @ @ @ Mayo Clinic in Rochester , Minnesota , who led the research .
Coronary artery disease could theoretically change the voice by reducing blood flow , he says .
But it ’ s also possible that it ’ s not the disease itself that causes the vocal changes , but other associated risk factors , such as stress or depression .
That study demonstrates both the promise and the limitations of this technology .
It ’ s one thing for a computer to pick out vocal patterns , but it ’ s another , @ @ @ @ @ @ @ and whether they ’ re clinically meaningful .
Are they fundamental characteristics of the disease in question ?
Or merely markers of some other difference between groups , such as age , sex , body size , education or fatigue , any of which could be a confounding factor ?
“ We ’ re trying to move away from just shoving data into an algorithm , and really diving into the data sets , coming up with a model of the disease first and then testing that with machine learning , ” Ghomi @ @ @ @ @ @ @ identified potential biomarkers in just a small , single population of patients .
“ Reproducibility is still a question , ” Lerman says .
“ Is my voice today and tomorrow and the day after tomorrow the same ?
” To ensure that the results can be generalized—and to reduce the possibility of bias , a problem known to plague medical algorithms—researchers will need to test their classification systems in larger , more diverse samples and in a variety of languages .
“ We don ’ t want to validate a speech model @ @ @ @ @ @ @ Jim Schwoebel , vice-president of data and research at Sonde Health , a Boston-based voice-analysis company .
“ We think we need 10,000 or more.
” The company runs SurveyLex , an online platform that allows researchers to easily create and distribute voice surveys , as well as the Voiceome project , an effort to collect voice samples and health information from up to 100,000 people , across a wide variety of speech tasks , locations and accents .
“ You might be depressed in New York , and sound differently depressed in @ @ @ @ @ @ @ .
For many of the applications that researchers have in mind , voice-analysis systems will have to not only distinguish sick people from healthy controls , but also differentiate between a variety of illnesses and conditions .
And they ’ ll need to do this outside the lab , in uncontrolled everyday situations and on a wide variety of consumer devices .
“ You ’ ve got smartphones which have a limited range of sensors , and people are using them everywhere in very uncontrolled environments , ” says Julien Epps , a @ @ @ @ @ @ @ University of New South Wales in Sydney , Australia .
When Epps and his colleagues , including a researcher at Sonde Health , analysed voice samples recorded with high-quality microphones in a lab , they were able to detect depression with roughly 94 % accuracy .
When using speech samples that people recorded in their own environments on their smartphones , the accuracy dropped to less than 75 % , the researchers reported in a 2019 paper .
And just because the technology is non-invasive doesn ’ t mean that it is without @ @ @ @ @ @ @ , including the possibility that individuals could be identified from anonymous speech samples , that the systems might inadvertently capture private conversations , and that sensitive medical information could be sold , shared , hacked or misused .
If the technology isn ’ t regulated properly , there ’ s a danger that insurers or employers could use these systems to analyse speech samples without explicit consent or to obtain personal health information , and potentially discriminate against their customers or employees .
And then there ’ s the perennial risk of false @ @ @ @ @ @ @ to be real and realize that a lot of this is still research , ” Rudzicz says .
“ And we need to start thinking about what ’ s going to happen when we put it into practice.
” This article is reproduced with permission and was first published on September 30 2020 .

In March, as the staggering scope of the coronavirus pandemic started to become clear, officials around the world began enlisting the public to join in the fight. Hospitals asked local companies to donate face masks. Researchers called on people who had recovered from COVID-19 to donate their blood plasma. And in Israel, the defence ministry and a start-up company called Vocalis Health asked people to donate their voices.
Vocalis, a voice-analysis company with offices in Israel and the United States, had previously built a smartphone app that could detect flare-ups of chronic obstructive pulmonary disease by listening for signs that users were short of breath when speaking. The firm wanted to do the same thing with COVID-19. People who had tested positive for the coronavirus could participate simply by downloading a Vocalis research app. Once a day, they fired up the app and spoke into their phones, describing an image aloud and counting from 50 to 70.
Then Vocalis began processing these recordings with its machine-learning system, alongside the voices of people who had tested negative for the disease, in an attempt to identify a voiceprint for the illness. By mid-summer, the firm had more than 1,500 voice samples and a pilot version of a digital COVID-19 screening tool. The tool, which the company is currently testing around the world, is not intended to provide a definitive diagnosis, but to help clinicians triage potential cases, identifying people who might be most in need of testing, quarantine or in-person medical care. “Can we help with our AI algorithm?” asks Tal Wenderow, the president and chief executive of Vocalis. “This is not invasive, it’s not a drug, we’re not changing anything. All you need to do is speak.”
They’re not the only ones racing to find vocal biomarkers of COVID-19—at least three other research groups are working on similar projects. Other teams are analysing audio recordings of COVID-19 coughs and developing voice-analysis algorithms designed to detect when someone is wearing a face mask.
It’s a sign of how hungry the young field of vocal diagnostics is to make its mark. Over the past decade, scientists have used artificial intelligence (AI) and machine-learning systems to identify potential vocal biomarkers of a wide variety of conditions, including dementia, depression, autism spectrum disorder and even heart disease. The technologies they have developed are capable of picking out subtle differences in how people with certain conditions speak, and companies around the world are beginning to commercialize them.
For now, most teams are taking a slow, stepwise approach, designing tailored tools for use in doctors’ offices or clinical trials. But many dream of deploying this technology more widely, harnessing microphones that are ubiquitous in consumer products to identify diseases and disorders. These systems could one day allow epidemiologists to use smartphones to track the spread of disease, and turn smart speakers into in-home medical devices. “In the future, your robot, your Siri, your Alexa will simply say, ‘Oh you’ve got a cold,’” says Björn Schuller, a specialist in speech and emotion recognition with a joint position at the University of Augsburg in Germany and Imperial College London, who is leading one of the COVID-19 studies.
But automated vocal analysis is still a new field, and has a number of potential pitfalls, from erroneous diagnoses to the invasion of personal and medical privacy. Many studies remain small and preliminary, and moving from proof-of-concept to product won’t be easy. “We are at the early hour of this,” Schuller says.
Some ailments cause obvious vocal distortions; consider the telltale stuffiness of someone afflicted by allergies. But many scientists think that vocal analysis could help to identify an enormous range of disorders, thanks to the complexity of human speech.
Speech signals
Speaking requires the coordination of numerous anatomical structures and systems. The lungs send air through the vocal cords, which produce sounds that are shaped by the tongue, lips and nasal cavities, among other structures. The brain, along with other parts of the nervous system, helps to regulate all these processes and determine the words someone is saying. A disease that affects any one of these systems might leave diagnostic clues in a person’s speech.
Machine learning has given scientists a way to detect aberrations, quickly and at scale. Researchers can now feed hundreds or thousands of voice samples into a computer to search for features that distinguish people with various medical conditions from those without them.
Much of the early work in the field focused on Parkinson’s disease, which has well-known effects on speech—and for which there is no definitive diagnostic test. The disorder causes a variety of motor symptoms, including tremors, muscle stiffness and problems with balance and coordination. The loss of control extends to the muscles involved in speech; as a result, many people with Parkinson’s have weak, soft voices. “It’s one of those things that you can hear with the human ear,” says Reza Hosseini Ghomi, a neuropsychiatrist at EvergreenHealth in Kirkland, Washington, who has identified vocal features associated with several neurodegenerative diseases. “But if you can get 10,000 samples and a computer, you can get much more accurate.”
More than a decade ago, Max Little, a researcher in machine learning and signal processing now at the University of Birmingham, UK, began to investigate whether voice analysis might help doctors to make difficult diagnoses. In one study, Little and his colleagues used audio recordings of 43 adults, 33 of whom had Parkinson’s disease, saying the syllable “ahhh”. They used speech-processing algorithms to analyse 132 acoustic features of each recording, ultimately identifying 10—including characteristics such as breathiness and tremulous oscillations in pitch and timbre—that seemed to be most predictive of Parkinson’s. Using just these 10 features, the system could identify the speech samples that came from people with the disease with nearly 99% accuracy.
Little and others in the field have also demonstrated that certain vocal features correlate with the severity of Parkinson’s symptoms. The systems are not yet robust enough for routine use in clinical practice, Little says, but there are many potential applications. Vocal analysis might provide a quick, low-cost way to monitor individuals who are at high risk of the disease; to screen large populations; or possibly even to create a telephone service that could remotely diagnose people who don’t have access to a neurologist. Patients could use the technology at home—in the form of a smartphone app, say—to track their own symptoms and monitor their response to medication. “This kind of technology can allow a high-speed snapshot, an almost continuous snapshot of how someone’s symptoms are changing,” Little says.
Researchers are now working to identify speech-based biomarkers for other kinds of neurodegenerative disease. For instance, a trio of scientists in Toronto, Canada, used voice samples and transcripts from more than 250 people to identify dozens of differences between the speech of people with possible or probable Alzheimer’s disease and that of people without it. Among the participants, those with Alzheimer’s tended to use shorter words, smaller vocabularies and more sentence fragments. They also repeated themselves and used a higher ratio of pronouns, such as ‘it’ or ‘this’, to proper nouns. “It can be a sign that they’re just not remembering the names of things so they have to use pronouns instead,” says Frank Rudzicz, a computer scientist at the University of Toronto, who led the study.
When the system considered 35 of these vocal features together, it was able to identify people with Alzheimer’s with 82% accuracy. (This has since improved to roughly 92%, Rudzicz says, noting that the errors tend to be more or less evenly split between false negatives and false positives.) “Those features add up to sort of a fingerprint of dementia,” Rudzicz says. “It’s a very intricate hidden pattern that’s hard for us to see on the surface, but machine learning can pick it out, given enough data.”
Because some of these vocal changes occur in the early stages of neurodegenerative diseases, researchers hope that voice-analysis tools could eventually help clinicians to diagnose such conditions earlier and potentially intervene before other symptoms become obvious.
For now, however, this idea remains largely theoretical; scientists still need to do large, long-term, longitudinal trials to demonstrate that voice analysis can actually detect disease earlier than standard diagnostic methods can.
And some clinicians note that voice analysis alone will rarely yield definitive diagnoses. “I learn a lot by listening to someone’s voice,” says Norman Hogikyan, a laryngologist at the University of Michigan in Ann Arbor. “I do it for a living. But I put it together with a history and then my exam. All three parts of that assessment are important.”
Researchers in the field stress that the goal is not to replace doctors or create standalone diagnostic devices. Instead, they see voice analysis as a tool physicians can use to inform their decisions, as another ‘vital sign’ they can monitor or test they can order. “My vision is that collecting speech samples will become as common as a blood test,” says Isabel Trancoso, a researcher in spoken-language processing at the University of Lisbon.
Expanding applications
A number of voice-analysis start-ups—including Winterlight Labs, a Toronto firm co-founded by Rudzicz, and Aural Analytics in Scottsdale, Arizona—are now providing their software to pharmaceutical companies. Many are using the technology to help assess whether people enrolled in their clinical trials are responding to experimental treatments. “Using speech as a more subtle proxy for changes in neurological health, you can help push drugs across the finish line or at the very least identify those that are not promising early on,” says Visar Berisha, the co-founder and chief analytics officer at Aural Analytics.
Neurodegenerative disorders are just the beginning. Scientists have identified distinct speech patterns in children with neurodevelopmental disorders. In one small 2017 study, Schuller and his colleagues determined that algorithms that analysed the babbling of ten-month-old infants could identify with some accuracy which children would go on to be diagnosed with autism spectrum disorder. The system correctly classified roughly 80% of children with autism and 70% of neurotypical children.
Researchers have also found that many children with attention deficit hyperactivity disorder speak louder and faster than their neurotypical peers, and show more signs of vocal strain. The firm PeakProfiling in Berlin is now developing a clinical speech-analysis tool that it hopes can help doctors to diagnose the condition.
But some clinicians are sceptical about how much useful information such systems will really provide. “Some of it is a little overblown,” says Rhea Paul, a specialist in communication disorders at Sacred Heart University in Fairfield, Connecticut. Children with neurodevelopmental disorders often have many easily observable behavioural symptoms, she notes.
Moreover, it’s not yet clear whether the algorithms are really identifying specific markers for, say, autism spectrum disorder, or just picking up on general signs of atypical brain development—or even just transient aberrations in speech. “Development is a meandering path and not every kid who starts out looking like they have autism grows up to be an adult with autism,” Paul says. Even if scientists do identify a highly reliable, specific vocal biomarker, she adds, it should only be used to identify children who might benefit from a more thorough evaluation. “It shouldn’t be sufficient in and of itself to label a child, especially so early in life.”
Scientists are also turning the technology to mental illnesses. Numerous teams around the world have developed systems that can pick up on the slow, pause-heavy, monotonous speech that tends to characterize depression, and others have identified vocal biomarkers associated with psychosis, suicidality and bipolar disorder.
“Voice is enormously rich in terms of carrying our emotion signals,” says Charles Marmar, a psychiatrist at New York University. “The rate, the rhythm, the volume, the pitch, the prosody [stress and intonation]—those features, they tell you whether a patient is down and discouraged, whether they’re agitated and anxious, or whether they’re dysphoric and manic.”
In his own work, Marmar has used machine learning to identify 18 vocal features associated with post-traumatic stress disorder (PTSD) in 129 male military veterans. By analysing these features—which were mainly indicators of slow, flat, monotonous speech—the system could identify, with nearly 90% accuracy, which of the veterans had PTSD.
Marmar and his colleagues are now expanding their research to women and civilians; if the team can generalize the findings, Marmar thinks that the technology could be a useful way to quickly identify people who might need a more thorough psychiatric assessment. “The first real-world application would be for high-throughput screening of PTSD,” he says. “You can do 4,000 voice screens in a matter of hours.”
Similar consumer applications are already beginning to make their way into the world. The US Department of Veterans Affairs is studying whether an app that monitors mental health can identify service members experiencing psychological distress. The smartphone app, developed by Cogito, a conversational guidance and analytics company in Boston, Massachusetts, collects metadata on users’ habits—such as how frequently they call or text other people—and analyses voice memos they leave on their phones.
There might even be vocal biomarkers for conditions that seem to have nothing to do with speech. In one study from 2018, scientists analysing speech samples from 101 people who were scheduled to undergo coronary angiograms discovered that certain vocal frequency patterns were associated with more severe coronary artery disease.
It’s not clear what explains these differences. “We struggle with the mechanism because it’s not obvious,” says Amir Lerman, a cardiologist at the Mayo Clinic in Rochester, Minnesota, who led the research. Coronary artery disease could theoretically change the voice by reducing blood flow, he says. But it’s also possible that it’s not the disease itself that causes the vocal changes, but other associated risk factors, such as stress or depression.
Tricky translation
That study demonstrates both the promise and the limitations of this technology. It’s one thing for a computer to pick out vocal patterns, but it’s another, harder task to understand what they mean and whether they’re clinically meaningful. Are they fundamental characteristics of the disease in question? Or merely markers of some other difference between groups, such as age, sex, body size, education or fatigue, any of which could be a confounding factor? “We’re trying to move away from just shoving data into an algorithm, and really diving into the data sets, coming up with a model of the disease first and then testing that with machine learning,” Ghomi says.
Most studies so far have identified potential biomarkers in just a small, single population of patients. “Reproducibility is still a question,” Lerman says. “Is my voice today and tomorrow and the day after tomorrow the same?” To ensure that the results can be generalized—and to reduce the possibility of bias, a problem known to plague medical algorithms—researchers will need to test their classification systems in larger, more diverse samples and in a variety of languages. “We don’t want to validate a speech model just with 300 patients,” says Jim Schwoebel, vice-president of data and research at Sonde Health, a Boston-based voice-analysis company. “We think we need 10,000 or more.”
The company runs SurveyLex, an online platform that allows researchers to easily create and distribute voice surveys, as well as the Voiceome project, an effort to collect voice samples and health information from up to 100,000 people, across a wide variety of speech tasks, locations and accents. “You might be depressed in New York, and sound differently depressed in Houston, Texas,” Schwoebel says.
For many of the applications that researchers have in mind, voice-analysis systems will have to not only distinguish sick people from healthy controls, but also differentiate between a variety of illnesses and conditions. And they’ll need to do this outside the lab, in uncontrolled everyday situations and on a wide variety of consumer devices. “You’ve got smartphones which have a limited range of sensors, and people are using them everywhere in very uncontrolled environments,” says Julien Epps, a researcher who studies speech-signal processing at the University of New South Wales in Sydney, Australia.
When Epps and his colleagues, including a researcher at Sonde Health, analysed voice samples recorded with high-quality microphones in a lab, they were able to detect depression with roughly 94% accuracy. When using speech samples that people recorded in their own environments on their smartphones, the accuracy dropped to less than 75%, the researchers reported in a 2019 paper.
And just because the technology is non-invasive doesn’t mean that it is without risks. It poses serious privacy concerns, including the possibility that individuals could be identified from anonymous speech samples, that the systems might inadvertently capture private conversations, and that sensitive medical information could be sold, shared, hacked or misused.
If the technology isn’t regulated properly, there’s a danger that insurers or employers could use these systems to analyse speech samples without explicit consent or to obtain personal health information, and potentially discriminate against their customers or employees.
And then there’s the perennial risk of false positives and overdiagnosis. “We have to be real and realize that a lot of this is still research,” Rudzicz says. “And we need to start thinking about what’s going to happen when we put it into practice.”
This article is reproduced with permission and was first published on September 30 2020.


scientificamerican--2020-10-04--Greenland Melting Fastest Any Time in Last 12,000 Years

Greenland is the biggest island in the world .
And the ice sheet that sits atop it is massive .
`` The pile of ice is so thick it extends more than 10,000 feet above the ocean .
And if all that ice were to melt and go into the ocean , global sea levels would rise by 24 feet everywhere around the world . ''
Jason Briner , a geologist at the University at Buffalo .
The ice sheet IS melting , of course .
But just how much , compared to the past ?
Briner 's team did @ @ @ @ @ @ @ of the Greenland ice sheet—which he says is a good proxy for ice melt across the entire ice sheet .
The researchers plugged past climate data into that model , to `` hindcast '' , rather than forecast , the past activity of the ice sheet .
They then checked the model 's predictions of the past shape and size of the ice sheet , by looking at piles of rocks and boulders and dirt on Greenland today , which outline the edges of ancient ice .
And the simulation was in good @ @ @ @ @ @ @ that reconstruction of the ice sheet over time , the team could compare the ice sheet ’ s historic losses to those happening today , under human-caused global warming .
And they determined that Greenland is on track to lose more ice this century than during any century in the past 12,000 years .
Possibly four times as much .
The results appear in the journal Nature .
[ Jason P. Briner et al , Rate of mass loss from the Greenland Ice Sheet will exceed Holocene values this century ] Ultimately it @ @ @ @ @ @ @ actually melts .
`` Humanity has the knob—the carbon knob , and that knob is going to influence the rates of ice loss from the Greenland ice sheet . ''
If the world goes net carbon zero by 2100 , for example , Briner says ice loss could stop entirely at the end of the century , according to one model .
`` That was what kept me from being completely depressed about our study . ''
Dozens of countries have already announced goals to go net zero by the middle of this @ @ @ @ @ @ @ of them .
[ The above text is a transcript of this podcast . ]

Full Transcript
Greenland is the biggest island in the world. And the ice sheet that sits atop it is massive.
“The pile of ice is so thick, it extends more than 10,000 feet above the ocean. And if all that ice were to melt and go into the ocean, global sea levels would rise by 24 feet everywhere around the world.”
Jason Briner, a geologist at the University at Buffalo. The ice sheet is melting, of course. But just how much, compared to the past?
Briner’s team did a computer simulation of the southwest portion of the Greenland ice sheet—which he says is a good proxy for ice melt across the entire ice sheet. The researchers plugged past climate data into that model to “hindcast,” rather than forecast, the past activity of the ice sheet. They then checked the model’s predictions of the past shape and size of the ice sheet by looking at piles of rocks and boulders and dirt on Greenland today, which outline the edges of ancient ice. And the simulation was in good agreement with the actual situation.
Using that reconstruction of the ice sheet over time, the team could compare the ice sheet’s historic losses to those happening today under human-caused global warming. And they determined that Greenland is on track to lose more ice this century than during any century in the past 12,000 years—possibly four times as much.
The results appear in the journal Nature. [Jason P. Briner et al., Rate of mass loss from the Greenland Ice Sheet will exceed Holocene values this century]
Ultimately it’s up to us how much ice actually melts.
“Humanity has the knob—the carbon knob—and that knob is going to influence the rates of ice loss from the Greenland ice sheet.”
If the world goes net carbon zero by 2100, for example, Briner says ice loss could stop entirely at the end of the century, according to one model.
“That was what kept me from being completely depressed about our study.”
Dozens of countries have already announced goals to go net zero by the middle of this century—so far the U.S. is not one of them.
—Christopher Intagliata
[The above text is a transcript of this podcast.]


scientificamerican--2020-10-04--When Whales Stop Calling

When Whales Stop Calling

Imagine that you ’ re at a summer barbeque , catching up with some friends , when you hear the sound of fire truck sirens going off in the distance .
You might wonder whether there ’ s danger nearby , but you and your friends keep talking anyway , slightly louder now that you have to be heard over the noise .
A few minutes later , the truck gets closer , and the sirens become so loud that trying to maintain conversation becomes futile .
So , you wait until the sound of the sirens fades into the @ @ @ @ @ @ @ the raucous sirens remained close by all afternoon , and you had to wait for several hours before you could carry on with conversation ?
What if this happened nearly every day ?
It turns out that this is a reality for some whales .
A 2015 study found that when bowhead whales in the Alaskan Beaufort Sea were exposed to airgun blasts from ships doing seismic surveys used to locate oil and gas reserves , the animals increased their rates of calling to try to be heard over the blasts when they @ @ @ @ @ @ @ as the seismic vessel got closer to them , the whales sharply decreased their call rates , eventually ceasing to call altogether .
Noise from ship traffic has long been recognized as a disturbance for whales , but the high-decibel explosive impulses produced during seismic surveys are an emerging , even more formidable , threat that ’ s begun to receive attention from marine mammologists in the past few decades .
To carry out a seismic survey , ships tow along several airgun arrays that typically fire off every 10–20 seconds , over @ @ @ @ @ @ @ months , albeit not continuously .
The “ source level , ” or loudness , of airgun arrays can exceed 240 decibels ( dB ) ( in water ) .
For reference , a blue whale , one of the world ’ s loudest animals , can produce calls at a volume of over 180 dB .
If the source level of a sound increases by 10 dB , it means that it gets 10 times more intense .
So , the sound of seismic airguns is about a million times more intense @ @ @ @ @ @ @ deafen the largest animal in the world if it happens to be near an active seismic vessel .
While airguns can damage whales ’ hearing if they ’ re fired within a kilometer or so of an animal , they can also be disturbingly loud at great distances .
In fact , the sound waves can propagate halfway across the globe .
The blasts can travel so far not only because they start out so loud , but also because they ’ re low-frequency ( i.e.
, low-pitch ) sounds .
Low-frequency sounds @ @ @ @ @ @ @ , like bird chirps , which travel only short distances .
This means that seismic surveys can potentially have a range of behavioral impacts on whales located dozens of kilometers away from airgun arrays .
The low-frequency blasts emitted during surveys overlap with the bandwidth of calls produced by baleen whales , which rely critically on sound for communication .
So , in addition to disturbing whales , seismic surveys can “ mask ” their calls to each other , as scientists say .
This explains why bowhead whales in the Alaskan Beaufort @ @ @ @ @ @ @ it was futile to try to make themselves heard over the high-decibel explosive sounds .
This phenomenon has also been documented in blue whales .
The effect of seismic surveys on North Atlantic right whales , a critically endangered species , has yet to be studied , but there is now a dire need to do so .
In 2018 , the National Oceanic and Atmospheric Administration authorized an expansion of offshore drilling using seismic airgun blasting in the coastal waters of the eastern United States , the right whales ’ primary habitat @ @ @ @ @ @ @ the Bureau of Ocean Energy Management before surveys can be conducted , but the proposed seismic operations could disrupt the behavioral patterns ( e.g.
, migration , breeding , and feeding ) of marine mammals , including right whales , hundreds of thousands of times each year .
The North Atlantic right whale population ’ s recovery from 19th-century whaling is already seriously impaired by mortalities from ship collisions and fishing gear entanglements , and the impending seismic surveys in their habitat could present a less visible but pervasive disturbance .
Right whales @ @ @ @ @ @ @ , including mating , so a reduction in time or space for acoustic communication could have drastic implications for the species ’ survival and reproduction .
While increases in low-frequency ocean noise are a potential anthropogenic stressor for all baleen whales , depleted populations experiencing the cumulative effect of multiple stressors are at heightened risk .
The behavioral impacts of airgun blasts on endangered species like right whales must be carefully studied using controlled exposure experiments prior to starting actual seismic surveys in their habitat .

Imagine that you’re at a summer barbeque, catching up with some friends, when you hear the sound of fire truck sirens going off in the distance. You might wonder whether there’s danger nearby, but you and your friends keep talking anyway, slightly louder now that you have to be heard over the noise. A few minutes later, the truck gets closer, and the sirens become so loud that trying to maintain conversation becomes futile. So, you wait until the sound of the sirens fades into the distance once more. But what if the raucous sirens remained close by all afternoon, and you had to wait for several hours before you could carry on with conversation? What if this happened nearly every day?
It turns out that this is a reality for some whales. A 2015 study found that when bowhead whales in the Alaskan Beaufort Sea were exposed to airgun blasts from ships doing seismic surveys used to locate oil and gas reserves, the animals increased their rates of calling to try to be heard over the blasts when they were distant and relatively faint. But as the seismic vessel got closer to them, the whales sharply decreased their call rates, eventually ceasing to call altogether.
Noise from ship traffic has long been recognized as a disturbance for whales, but the high-decibel explosive impulses produced during seismic surveys are an emerging, even more formidable, threat that’s begun to receive attention from marine mammologists in the past few decades.
To carry out a seismic survey, ships tow along several airgun arrays that typically fire off every 10–20 seconds, over periods of days, weeks, or months, albeit not continuously. The “source level,” or loudness, of airgun arrays can exceed 240 decibels (dB) (in water). For reference, a blue whale, one of the world’s loudest animals, can produce calls at a volume of over 180 dB. If the source level of a sound increases by 10 dB, it means that it gets 10 times more intense. So, the sound of seismic airguns is about a million times more intense than a blue whale call—powerful enough to deafen the largest animal in the world if it happens to be near an active seismic vessel.
While airguns can damage whales’ hearing if they’re fired within a kilometer or so of an animal, they can also be disturbingly loud at great distances. In fact, the sound waves can propagate halfway across the globe. The blasts can travel so far not only because they start out so loud, but also because they’re low-frequency (i.e., low-pitch) sounds. Low-frequency sounds attenuate much more slowly than high-frequency sounds, like bird chirps, which travel only short distances. This means that seismic surveys can potentially have a range of behavioral impacts on whales located dozens of kilometers away from airgun arrays.
The low-frequency blasts emitted during surveys overlap with the bandwidth of calls produced by baleen whales, which rely critically on sound for communication. So, in addition to disturbing whales, seismic surveys can “mask” their calls to each other, as scientists say. This explains why bowhead whales in the Alaskan Beaufort Sea stopped calling to each other: it was futile to try to make themselves heard over the high-decibel explosive sounds. This phenomenon has also been documented in blue whales.
The effect of seismic surveys on North Atlantic right whales, a critically endangered species, has yet to be studied, but there is now a dire need to do so. In 2018, the National Oceanic and Atmospheric Administration authorized an expansion of offshore drilling using seismic airgun blasting in the coastal waters of the eastern United States, the right whales’ primary habitat. Geological permits must be approved by the Bureau of Ocean Energy Management before surveys can be conducted, but the proposed seismic operations could disrupt the behavioral patterns (e.g., migration, breeding, and feeding) of marine mammals, including right whales, hundreds of thousands of times each year.
The North Atlantic right whale population’s recovery from 19th-century whaling is already seriously impaired by mortalities from ship collisions and fishing gear entanglements, and the impending seismic surveys in their habitat could present a less visible but pervasive disturbance. Right whales use social calls to mediate vital interactions, including mating, so a reduction in time or space for acoustic communication could have drastic implications for the species’ survival and reproduction.
While increases in low-frequency ocean noise are a potential anthropogenic stressor for all baleen whales, depleted populations experiencing the cumulative effect of multiple stressors are at heightened risk. The behavioral impacts of airgun blasts on endangered species like right whales must be carefully studied using controlled exposure experiments prior to starting actual seismic surveys in their habitat.