future research science

The future of brain science

Guest Sergiu Pasca is a physician-scientist who turns skin cells into stem cells and then into brain tissues he calls “organoids” and “assembloids” in order to study psychiatric and neurological illness in a dish instead of in living human beings.

With this knowledge, Pasca hopes to develop new treatments for conditions ranging from schizophrenia and autism spectrum disorders to chronic pain, he tells host Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast.

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Related : Sergiu Pasca , professor of psychiatry and behavioral sciences

[00:00:00] Sergiu Pasca: For Timothy Syndrome in particular, because this is, you know, the paper that is coming out next week. We got such a good understanding of the biology of this condition through these human cellular models, organoids, assembloids, 2D cultures, that at one point the therapeutic opportunity just became self-evident.

[00:00:18] It just became clear this is exactly what we need to do. And this came like three, four years ago. And then through a series of experiments that we've done, we've now developed a strategy that can essentially reverse almost all the phenotypes, all the defects that we've discovered in patient cells over the years, literally within some of them within hours, some of them within days, but they're essentially just like completely reversing them.

[00:00:47] Russ Altman: This is Stanford Engineering's The Future of Everything. And I'm your host Russ Altman. If you're enjoying the show or if it's helped you in any way, please consider rating and reviewing it to share your thoughts. Your input is extremely valuable and it'll help others learn about the show. 

[00:01:01] Today, Professor Sergiu Pasca from Stanford University will tell us how his group has figured out how to take skin cells, turn them into brain cells, and then study some of the most vexing psychiatric and neurological diseases in a dish with the idea of generating new therapies. It's The Future of Brain Science. 

[00:01:22] Before we get started, please remember to rate and review if the show has helped you in any way. That will help us immensely.

[00:01:35] Psychiatric and neurological diseases are some of the toughest diseases to study and to treat. And those are related. Because we don't have good ways to study the brain. Nobody wants to give up a piece of their brain for scientific research. It's really hard to understand what goes wrong at the molecular and cellular level, and how we can invent new ways to treat terrible diseases such as chronic pain, schizophrenia, bipolar disorder and depression.

[00:02:03] Well, Sergiu Pasca is a professor of Psychiatry and Behavioral Sciences at Stanford University. And his group has figured out how to take skin cells, make them go backwards in time to become stem cells, which have many potential future fates, and then get those stem cells to differentiate into little pieces of brain. His group has shown that they can do this reliably, and they can generate little circuits where the cells talk to one another and recapitulate some of the deficits that are seen in patients who have certain diseases. It's an amazing story, and you're about to hear about it. 

[00:02:43] Sergiu. You've developed this amazing ability to grow living tissue that mimics parts of the human brain. First of all, how does that work? Then we can talk about why you did it and what we can use it for. But tell me, how do we grow little pieces of brain? 

[00:02:57] Sergiu Pasca: Well, the process starts by generally taking a tiny skin biopsy, so just taking a few cells from the skin of any individual, say a patient with autism or with schizophrenia, bringing those cells into the lab and then essentially doing some mumbo jumbo to the cells, you know, playing cellular alchemy and pushing those cells back in time to essentially turn into stem cell like cells. Um, and the reason why we do this is because stem cells have this remarkable ability of turning into any other cell types. So once you have the stem cells from any individual, not only can you store them and share them with others, but now you can gently guide them in a dish to become brain cells.

[00:03:43] And we spent essentially the past fifteen years designing strategies to turn these stem cells from any individual, into various types of brain stems and ever, brain cells into various ever more complicated preparations. 

[00:03:59] Russ Altman: Fantastic. So a couple of questions to follow up. I think everybody knows that the part of what makes the brain is there's a very complicated architecture of the cells where they are and how they interact with one another.

[00:04:11] Are you able to get that to happen or are these just individual cells sitting in a dish, but not talking to each other and not creating the kinds of structures that we see when we do, you know, uh, studies of brain tissue?

[00:04:24] Sergiu Pasca: That's a very good question. So about fifteen years or so ago, we were doing exactly that, kind of like at the bottom of a dish, a flat layer of brain cells. Um, let's say cortical neurons, so neurons of the cerebral cortex. Of course, they're great. I mean, they look like neurons. They're human neurons, you know, their shape and their properties were those of human neurons. But they're not able to communicate with each other the way they do in the three-dimensional brain.

[00:04:49] And more importantly, as you pointed out, they're not able to communicate with neurons at a distance because what makes the human brain unique, or the brain really unique, is that unlike other organs that are more homogeneous, let's say the liver, it does matter which part you're actually probing or you're looking at.

[00:05:06] And so what we've actually slowly done is first of all, generate three dimensional preparations that are now known as organoids that resemble parts of the nervous system. Let's say parts of the spinal cord or parts of the cerebral cortex. And that we spend, you know, five, six, seven years, kept refining those methods.

[00:05:26] And at one point we really became interested in studying cell interactions. We thought that was important, that forming circuits from the cells will be, um, enabling for so many applications. So then we introduced what are now known as assembloids. 

[00:05:42] Russ Altman: Assembloids. 

[00:05:43] Sergiu Pasca: Assembloids, which are essentially assembled three dimensional cultures where, let's say, you, uh, make a three-dimensional culture that resembles a simple cortex. And one that resembles the spinal cord. And then you culture them separately. You provide different cues and small molecules so that they become those cells. And then at the right time, which, you know, depends a little bit on the brain region, you start putting them together. And by putting them together, literally you put them in physical proximity to each other.

[00:06:13] And initially we thought we're going to have to guide, and we're going to have to like tell the cells what to do, kind of like in engineering, right? Provide the blueprint. Of course, what we got wrong at that time was like in biology, the cells already know what to do. So once you actually put them together, there are this emergent properties.

[00:06:32] The cells will recognize where they actually have to go and they'll start project and find, for instance, motor neurons, connect with them. And then if you put a third part, let's say a piece of muscle that you get from a biopsy, then those neurons will connect to the muscle. And suddenly the muscle was just starts twitching in a dish under the control of cortical neurons.

[00:06:51] So I was like really exciting because suddenly you can witness the remarkable power of self-organization for a process that, to be honest, we don't even understand that well. It's not like we know how the rules of assembly of those, but once you provide, so like the minimal conditions necessary, you unleash these forces of self-organization.

[00:07:12] Russ Altman: So the cells really want to be a brain, they want to be a spinal cord, and you just have to let them do it almost. 

[00:07:19] Sergiu Pasca: Precisely. 

[00:07:20] Russ Altman: So one, one final preparatory question is when you're creating these individual organoids or that will become part, I guess, become part of an assembloid, does it always have to be just one type of cell?

[00:07:30] You talked about livers and even livers, as we know, are made out of multiple cell types. So how advanced is your ability to make a mix of cells, for example, the cells that are feeding the neurons or that are supporting the infrastructure of the brain? Or is that a future topic? 

[00:07:47] Sergiu Pasca: Well, I mean, one way to look at you know, brain developments is that, um, there are multiple niches. There are multiple places where cells are born. Um, and those niches will have cues for those stem cells to generate the diversity of cells. They're all kind of like coming from there. Let's take the example of the cerebral cortex, like the outer layer of the brain. The region of the brain where, you know, we think that all of our cognition and what makes us human comes from.

[00:08:13] Most of the cells in the cerebral cortex are born, uh, in a region close to the ventricle, a ventricular zone, where there are these progenitors called radial glia. This radial glia will essentially generate almost all the cells in the cerebral cortex in a sequential manner. For instance, they'll first make deep layers of the cortex and then upper layer of the cortex, and the cells will organize themselves in a sequential manner.

[00:08:38] So, as you can imagine, if you specify, um, the generation of this particular type of stem cells, you can expect to generate all of the cells. 

[00:08:48] Russ Altman: Fantastic. 

[00:08:49] Sergiu Pasca: Now that doesn't mean that you get all of them, because some of the cells do come from outside of the nervous system. So for instance, microglia, the resident immune cells of the brain are not even born in the brain. They're born far away. They're mesodermal in origin. So if you really want to put them in, you have to make them separately. And then insert them into this preparation. 

[00:09:07] Russ Altman: Okay. 

[00:09:08] Sergiu Pasca: And, uh, but it, so that becomes again, an assembloid to a large extent. 

[00:09:12] Russ Altman: Okay, great. Well, this is, I could go on forever, but that has set us up beautifully for the conversation, which is why did you do this? And what are you using these brain tissues to do? 

[00:09:24] Sergiu Pasca: Well, you know, deep in core, I think what I am is a frustrated physician. And that's what I think I've been, and I continue to be. And for me, as I was doing my medical training, I was, you know, in awe of what molecular biology can do for most branches of medicine, as you very well known.

[00:09:44] And, you know, I was training at a time where we started to see some of the first rationally designed drugs in oncology, where literally, you know, you weren't just like hitting all the cells, you know, so that they will all die, but you will have a pathway. Uh, and you'll have a targeted, uh, therapeutic that will just cure like the cancer.

[00:10:06] And then, you know, you go on the, you know, oncology and then you move and you go in psychiatry, uh, to see patients. And it's almost like a completely different world. Their disorders are not defined molecularly or cellularly in any way, they're defined behaviorally. And they're, um, you know, also most of the drugs that we already have, have not been designed rationally, have not been discovered because we understand the pathophysiology, but rather in reverse, you know, they're found by chance.

[00:10:36] And then we've kind of like tried to figure out how they work and what the disease is like based on that. And that was really frustrating for me, I must say. Um, and it became clear that the reason why psychiatry and neurology have been left behind versus all other branches of medicine is to a large extent because we cannot access the human brain.

[00:10:54] Russ Altman: Right. People don't usually want to give you a sample of their brain to study. 

[00:10:58] Sergiu Pasca: They don't. 

[00:11:00] Russ Altman: For understandable reasons. 

[00:11:01] Sergiu Pasca: For very understandable reasons and nor do they give you one to test a drug, you know, before you do it. And that was really, uh, frustrating for me at that time. And I was doing a lot of experiments in animals, uh, cat and rats and animals.

[00:11:16] And it was incredibly powerful to be able to like stick an electrode into the brain of an animal and listen to electrical activity. Right? As the animal was performing various tasks. And it becomes clear that if we really want to understand these neuropsychiatric diseases, ultimately we will need to listen very carefully, very closely to those neurons and understand the molecular basis for that.

[00:11:41] And at that time, as I was finishing my clinical training, there was this remarkable breakthrough that was published around that time. That certainly still sounded at science fiction. A lot of people didn't believe that it was true, which was this idea that you could take any cell, a skin cell, and turn it into a stem cell.

[00:12:03] And it was, as you can imagine, outrageous because everybody thought, and it was dogma at that time, that development is a one-way street, you can never go back. Once a cell has been formed, you just don't go back to become a stem cell. It would be a liability to like forming cancers. And yet, you know, Yamanaka showed convincingly that you could do that.

[00:12:24] And in my mind, that kind of like clicked. Uh, and realize that it would be a remarkable opportunity for us in psychiatry to form, uh, to build brain cells from individuals in a non-invasive way without really accessing their brains. 

[00:12:38] Russ Altman: Yep. 

[00:12:39] Sergiu Pasca: And that essentially derailed my career to a large extent. And I sort of like gave myself fifteen years of like trying to do basic science. Hoping that, uh, you know, we'll make some advances and I'm coming very close to those fifteen years, so we'll see how it goes. But for me, it really came out of this frustration that I felt we were making much biological progress in understanding this. 

[00:13:01] Russ Altman: Okay. So let's go right to it. So if you take the skin of somebody who has, let's say, bipolar disorder or schizophrenia, and if you make a little piece of brain, it's not the whole brain, it's a little piece. Can you tell that there are problems with that, with those cells that might relate to the fact that the patient has schizophrenia? Because that's, that would be remarkable, because then you could sprinkle drugs on top of it. I use that as a metaphor, of course. And see, does that fix whatever is wrong? So, does a schizophrenic patient, when they go through this process of giving them, giving you their skin cells, do you wind up with little pieces of brain that you that have relevance to schizophrenia?

[00:13:40] Sergiu Pasca: Well, the challenge with that approach generally is that we wouldn't even really know what to look for. 

[00:13:47] Russ Altman: Right, right. 

[00:13:48] Sergiu Pasca: You know, like for a patient with bipolar, how would we know that we found something? And then that was really the challenge in the beginning because a lot of people said like, well, sure you can make the cells, but how are we going to know?

[00:13:59] So actually choosing the disease that you study, uh, judiciously is actually crucial. So what we actually did is we anchored it in genetics, actually. We went back and we thought, well, there are genetic forms of psychiatric disease, highly penetrant disorders, where if you have this mutation, you will certainly be very sick.

[00:14:20] And some of those mutations are in genes that we kind of know what they do overall. So we could test the function of those cells and the classic example, the one that we focused on fifteen years ago. 

[00:14:31] Russ Altman: Yes. 

[00:14:32] Sergiu Pasca: Is this rare form of autism and epilepsy called Timothy Syndrome, which is caused by a mutation in a calcium channel. And calcium channel, as the name implies, they carry calcium inside the cells.

[00:14:43] Russ Altman: Yep. 

[00:14:44] Sergiu Pasca: So we thought if we're going to be able to make neurons from this patient, we could actually measure how calcium goes inside the cells. And if there's something abnormal, we'll know what to look for. 

[00:14:53] Russ Altman: Right. So you have the hook there that you know what you're expecting, where the abnormality might be.

[00:14:59] Sergiu Pasca: Precisely. At least we have some sort of, you know, benchmarking that we can do. Not that we would know what would come afterwards, but it would tell us at least that there is something valid about these models. And that's exactly what we did early on. And then of course, continued characterizing the cells.

[00:15:15] And you can find all kinds of like defects now we know, not just in how the cells handle calcium, but how the cells are moving, for instance, throughout the nervous system, how they're making connections with each other. And once you find some of these defects, whether they're like in organoids or in assembloids, then you can really start contemplating the idea, let's try to reverse them.

[00:15:33] Let's try to sprinkle specific drugs or, you know, find other therapeutics to reverse them. 

[00:15:39] Russ Altman: Yes. 

[00:15:39] Sergiu Pasca: With the idea that if you were to reverse those in a dish or in some of these models, they will have an effect in patients. Uh, and of course that step has not yet been done. Nobody has really, went all the way. We're getting close, but nobody has really gone all the way to saying, okay, we'll reverse this now in a dish. Let's move into a patient and show that this will work. 

[00:15:58] Russ Altman: Fantastic. Okay. So you have some big news coming out around now. Can you give us a little flavor as we close this first segment? What's the latest things that coming out of the lab that you're most excited about?

[00:16:12] Sergiu Pasca: Yeah, I mean, for the past ten, fifteen years, essentially what we did, I feel, has been building tools to a large extent. And then paradoxically, my lab is probably much more well known as a tool building lab than I wish. I don't consider myself a tool builder. I never really wanted to build tools, to be honest. I wanted to understand the pathophysiology of disease.

[00:16:35] All these years of actually using these novel tools or trying to understand the biology of these disorders are starting to pan out. In the sense that, for Timothy Syndrome in particular, because this is, uh, you know, the paper that is coming out next week, we got such a good understanding of the biology of this condition through this human cellular models, organoids, assembloids, 2D cultures, that at one point, the therapeutic, opportunity just became self-evident.

[00:17:04] Russ Altman: Wow. 

[00:17:04] Sergiu Pasca: It just became clear. This is exactly what we need to do. And this came like three, four years ago. And then through a series of experiments that we've done, we've now developed a strategy that can essentially reverse almost all the phenotypes, all the defects that we've discovered in patient cells, uh, over the years, literally within, some of them within hours, some of them within days. But they're essentially just like, uh, completely reversing them.

[00:17:28] And I think that's very powerful. Of course, it poses all kinds of questions of like, what do you do next? There's not a very good animal model for this disease. So how do you test before you go into patients? And that's where another tool that we were developing in parallel came uh, to help. Which is, uh, you know, most of the therapeutics really do need to be tested in a living organism, in vivo, rather than just in a dish.

[00:17:50] It's very important. We know that already. A lot of failures come from the fact that something works really well in the dish. You go in a living organism, it doesn't work, or it has like unanticipated side effects. So how do you do that? How do you test something, you know, while keeping the patient safe? How do you test it on human patient cells without harming the patient? 

[00:18:09] So, a few years ago, we devised a strategy where we actually can take some of these organoids, but then transplant them into animals. We put them into a rat early in development, so that you essentially build a unit of human cortex into that rat. So almost a third of a rat hemisphere will essentially have human tissue. 

[00:18:28] Russ Altman: Hemisphere of its brain. 

[00:18:31] Sergiu Pasca: Of a rat. Yes. So you can do an MRI and you can see that a third of a hemisphere now has human tissue that we transplanted there early on. And it's vascularized, it receives sensory input, you can move the whiskers of the rat.

[00:18:43] Russ Altman: I'm going to bookmark putting a human tissue, brain tissue, into a rat for later on in our discussion, but I just wanted to bookmark that. Keep going, keep going. 

[00:18:53] Sergiu Pasca: But essentially now the human cells, the human neurons, uh, are integrated into the rat circuitry. And the reason why that is important is because now you, if you have a therapeutic, uh, for that disease, you can come and inject it into the rat, so in an in vivo system, but then look at the effect on human cells. And you can envision that it could be exactly the patient that you plan on treating. 

[00:19:19] Russ Altman: Yep. Right. 

[00:19:20] Sergiu Pasca: And then a week later you can get out the tissue and say, has there been an effect? Is the drug working? Is it having unanticipated side effects, like an immune reaction or other? So I think that is a very powerful way, uh, to actually test these drugs before we move into the clinic. 

[00:19:38] Russ Altman: Yes. 

[00:19:39] Sergiu Pasca: And so that's one of the things that we've done for Timothy Syndrome in particular. As we've had all these in vitro studies at one point, we were like, what is next? Where are we going to do? How are we going to get into? 

[00:19:49] Russ Altman: And for just to finish up for this part of the conversation, do the rats that you generated have brain tissue from patient's skin who had Timothy Syndrome? 

[00:20:00] Sergiu Pasca: Exactly.

[00:20:02] Russ Altman: This is The Future of Everything with Russ Altman. More with Sergiu Pasca next.

[00:20:20] Welcome back to The Future of Everything. I'm Russ Altman, and I'm speaking with Professor Sergiu Pasca from Stanford University. In the last segment, Sergiu told us about his amazing ability to take skin cells and turn them into small pieces of human brain tissue that can be studied for disease and for new therapies.

[00:20:37] In this segment, he'll tell us how complex these brain circuits can get, and some new results showing that they're even able to model the complex circuits like the perception of pain. He's also going to address the ethical issues about manipulating what are peculiar to humans, brain cells. And also he'll talk about how his group is sharing their technologies so that brain scientists all over the world can benefit.

[00:21:03] Sergiu. There's a lot of things that go wrong in the brain, and it's not always as simple. It's sometimes a complex set of connections between cells. They call them, like, neural circuits. So, where is our ability to, uh, engineer these more complex communication pathways that are important to understand certain diseases?

[00:21:22] Sergiu Pasca: You're right on point, because most psychiatric disorders are likely gonna arise not from, you know, drastic changes to cell composition of the brain. It's not like parts of the nervous system are missing, but rather arise from faulty communication between neurons in specific circuits. So it's becoming really important that with our human cell models, we're building ever more complex circuitry in a dish that allows us to probe some of this mechanism.

[00:21:51] So, you know, initially the assemblers that we were building had just like two parts. You would just put them in close proximity. Cells will migrate from one part to the other or they'll project. Then of course we wanted to put like more parts because most of the circuits have more, um, uh, more components.

[00:22:05] So we put three parts, cortex, spinal cord, the muscle. But then of course, some of these pathways have more than three. And actually adding a fourth component was not trivial. It took several years. to create both the components and, you know, kind of like the technology that is necessary to grow some of these cultures for longer periods of time.

[00:22:24] And just to give you an example of something that we've, uh, put together quite recently has been to actually build a sensory pathway, a somatosensory pathway from four parts. And somatosensory, uh, or somatosensation, essentially sends information from the periphery to the nervous system. So for instance, tactile information or pain information or temperature is sent by terminals in our skin, uh, that send those signals to the spinal cord, the spinal cords project it all the way in the middle of the brain in a structure called the thalamus, and then the thalamus will send it to the cortex where that sensation ultimately arises. And so there are multiple components. So we spent several years making each of this component, components of the circuit, and then we put them together. And recently we've succeeded in assembling the entire pathway, uh, that actually, uh, can respond to pain stimuli, pain like stimuli.

[00:23:25] Um, so you can actually make a sensory organoid, a spinal cord organoid, a thalamus organoid, and a cortical organoid. You put them together and form a somatosensory assembly. 

[00:23:36] Russ Altman: So earlier in our conversation, you were telling us about this amazing capability for the cells. You just have to give them the chance to be successful and they figure out what to do.

[00:23:46] In this case of these four different cells, was that still the case that they knew what to do? Or do things get sufficiently complicated that you kind of have to nudge them a little bit more than you do in the previous cases? 

[00:23:57] Sergiu Pasca: Oh, actually, again, they know what to do. 

[00:23:59] Russ Altman: Wow. 

[00:24:00] Sergiu Pasca: I mean, they know what to do and we wouldn't know how to instruct them, to be honest. We're still like pretty ignorant about this. But the cell, some of the circuits are so ancestral and so well conserved, that probably their evolutionary mechanism in place to establish some of that basic connectivity, uh, almost intrinsically. 

[00:24:17] Russ Altman: And I find this so exciting because based on your story with the Timothy Syndrome, you now can create pain or create touch, and then you can try to manipulate with drugs to see if you can modify the experience in a dish, and then presumably, modify the experience in the rat and then the humans. Is that the kind of plan you imagine? 

[00:24:39] Sergiu Pasca: Absolutely. And you know, it's quite interesting because once you put all these four components together, you know, they connect with each other and the reason why we know they're connecting with each other is because if you look at the activity of the neurons across the four components, they become synchronized. Rather than each kind of like sparkling their own kind of like song, suddenly, they're all talking to each other, and you see this emergent property, uh, this emergent activity of the four-part component. And then, what you can do, is you can sprinkle in some of the stimuli that we know are mimicking uh, let's say pain. So, you know, one thing that people, 

[00:25:15] Russ Altman: We'll call it pepper. 

[00:25:17] Sergiu Pasca: Exactly. So you can take capsaicin from like hot pepper. And if you sprinkle that, which by the way, if you add it even to your skin, it's painful. But if you add it here, if you add it here, then you'll suddenly just see that the first component lights up the sensory one and it transmits activity throughout the entire pathway.

[00:25:35] So that gives us, you know, some indication that indeed it actually works. And then what you can do even more is you can now model diseases. And so there are mutations that cause either loss of pain, or exacerbation of pain. Both of which are bad, obviously. And you can induce those mutations that are generally in sodium channels.

[00:25:55] You can actually induce those mutations in this preparation and suddenly see that there's either, you know, this synchronization of activities, so the sensory systems are not, you know, processing the stimuli right, or there's over processing. So it gives us really, for the first time, the ability to watch this communication between the sensory neurons and the circuitry right in front of our eyes, but with human cells. 

[00:26:18] Russ Altman: And I can see how the adding of four, it's just the beginning because anybody who's a clinician knows that after patients are exposed to pain chronically, they start to get psychiatric responses to the pain.

[00:26:29] You know, part of the pain is their high-level processing of the experience of pain. I've even had guests on the show talking about these, and you can imagine that you're going to need to build level five, six, and seven so that we can start to understand how those raw stimulation of pain leads to changes in how you process information at a much higher level. I mean, I'm not, I don't mean to give you any homework, but I could imagine that this could be on the list. 

[00:26:54] Sergiu Pasca: Absolutely. And right now our system, and I think this is important to clarify also so to not create any confusion, is the valence of pain, the sensation of pain. It's usually processed in other brain regions.

[00:27:07] This is, this information is taken from the cortex and it's processed and it gives us the sensation of pain. We don't have that yet in the system.

[00:27:14] Russ Altman: Right. 

[00:27:15] Sergiu Pasca: That will have to be built exactly as you said, separately. And in fact, many of the circuits are loop circuits. They're going up in, in loop, which is really important.

[00:27:23] And so we've been working quite diligently in trying to build ever more complex circuits. Of course, they're all in vitro, so they're never going to have the full, you know, complexity of an in vivo circuit, but we also don't want the full complexity. We want the system to be sufficiently complex, yet simple for us to use to dissect the molecular components and move forward therapeutically. 

[00:27:46] Russ Altman: So as I promised a few minutes ago, I definitely want to go to the ethics of this because, you know, the headline here, well, the headline is really that you're addressing diseases that we didn't have an ability to address before. But another headline is that we're taking human, pieces of human brain cells and we're putting them in animals and basically you're manipulating a lot of things that some people may consider very sacrosanct, very human and very peculiar to humans. So tell me a little bit about how as a scientist and a physician, you have navigated some of the ethical issues about making sure that your work is accepted and that people understand what you are doing and where you, if you're drawing any lines, where you're drawing those, what's the situation there?

[00:28:27] Sergiu Pasca: Yeah, no, this is a very important component. To be honest, I never really kind of like thought or planned for it as we were like moving forward. But you know, the paradox is as follows. Psychiatric disorders are to a large extent uniquely human, or you know, most of them, if not all of them are uniquely human.

[00:28:45] And so, as you can imagine, if you want to understand this, the models that we have for those disorders need to be as human as possible. And yet, the more human they become, the more uncomfortable we feel about creating something that is really human like experience. And so, certainly we're not there with any of the preparations that we have.

[00:29:05] But as our preparations are getting ever more complex, there are all kinds of concerns that are being raised about this. Some of them, you know, very careful, uh, one, some of them anchored in misunderstanding of what it's actually done. But I think that is exactly the moment when you have to have conversations with, first of all, the broader scientific community, and then with the public itself.

[00:29:30] I think the public has a responsibility to be part of these conversations. You know, most of this work is paid by federal grants. And I think the general public has, uh, the right to be involved in this conversation. 

[00:29:41] Russ Altman: What kind of feedback have you gotten? Oh, I'm sure you've given popular talks like to, you know, to, to the lay public, how do they respond?

[00:29:49] Sergiu Pasca: So generally, I think like the public understands really well what the motivator, I think if the motivation comes through very clearly. Uh, I think it's, uh, you know, everybody will connect. Everybody knows somebody who's suffering from a psychiatric disease, right? I mean, this are affecting one in five individuals. And everybody knows just how devastating these conditions are and that we will need some solutions.

[00:30:11] So I think people will understand, but at the same time, this type of research needs to be done responsibly. Because we are crossing various boundaries, you know, you could say by building ever more complex circuitry. And I think in vitro, there are fewer concerns that I think are realistic, uh, in the sense that sure, the circuit can get very complex, but there's no sensory, uh, input that is like, there's no output that is meaningful, it's very difficult to do both.

[00:30:38] But you can envision that if you transplant into an animal, uh, there is another series of like controversies that are arising. So what I've done is, first of all, we've had a lot of conversations with others. I gave a series of public talks, including a TED talk, which was a really important component of engaging already the public. And, uh, just recently, uh, I co-organized a meeting at Asilomar in kind of like the historical, uh, side where some of this conversation actually started with like Berg doing, 

[00:31:09] Russ Altman: The 1970’s when genetic engineering became possible. Yes? 

[00:31:13] Sergiu Pasca: Yeah. So together with my colleague here at Stanford, Hank Greely, we co organized this meeting at, uh, at Asilomar where we brought together not just scientists from the field, but actually scientists from outside the field, people who are studying consciousness, philosophers, evolutionary biologists, uh, social scientists to really think, uh, you know, very openly about this.

[00:31:36] And we're putting together a series of, uh, guidelines, uh, that we're in the process of like writing up, that hopefully, uh, will catalyze farther discussions. And our hope is that in the future we'll have an even bigger meeting that will engage even more broadly, uh, you know, families of patients, but other scientists across the field and neuroscientists in particular as we think about these issues. 

[00:32:01] Russ Altman: Fantastic. Well, we're a little bit, we're almost out of time, but I wanted to give you thirty seconds to talk about the very exciting prospect that you are now sharing this technology so that others can use it. And just give me a fifteen, twenty seconds on what's the idea about sharing these technologies?

[00:32:16] Sergiu Pasca: Yeah, well, you know, as you know, I realized very quickly that, uh, as we were developing technologies, and again, as I mentioned, I never envisioned being a tool developer. I don't consider myself a tool developer, but at one point, once we've had, you know, half a dozen or a dozen of these techniques put out, there are a lot of people who wanted to implement them.

[00:32:34] There are a lot of like troubleshooting, and these experiments are not trivial, you know, unlike like CRISPR where, you know, you can do your experiments like very quickly in two or three days and maybe even try them in the kitchen at home. These experiments require hundreds of days. 

[00:32:46] Russ Altman: Not for the kitchen. 

[00:32:47] Sergiu Pasca: And there's a lot of troubleshooting, and not in the kitchen. And so they require a lot of effort. And initially we've helped individual labs one by one. I mean, literally more than a hundred labs. Helping them to implement step by step the technique. At one point it became overwhelming. 

[00:33:01] And so what we did is through the center that I lead here at Stanford, the Stanford Brain Organogenesis Center, we started putting together a course, an international course where we would bring, you know, twenty-five students at a time and teach them essentially all the tricks of the trade.

[00:33:17] And within one week, and we prepare of course for months before because it's kind of like a cooking show, you know, I mean, we have all the components ready. They do the critical steps. They would never be able to do a hundred days long experiments in a week. But they land their critical steps. And when they come here, they also make a pledge that they will go back home and they will teach others at their own institutions.

[00:33:36] And that has, you know, beautiful amplifying effects because now there are hundreds and hundreds of alumni. I mean, I travel around the world and people come and say, oh, we've learned at the course, or we've learned from somebody who learned at the course. So it's been really remarkable and there's so much to do in neurology and psychiatry for a lifetime.

[00:33:54] So, and I think here at Stanford, we've always had a culture of like broadly and openly sharing whatever we developed early. So it, it really just aligned beautifully, I think, with the philosophy that we have here. 

[00:34:05] Russ Altman: Thanks to Sergiu Pasca. That was The Future of Brain Science. Thanks for tuning into this episode with over 250 episodes back in our archive. You can have instant access to lots of good conversations with brilliant people passionate about their work. If you're enjoying the show, or if it helps you in any way, please write and review and give it a five. You can connect with me on X or Twitter @RBAltman, and you can follow Stanford engineering @StanfordENG.

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NSF announces 4 new Engineering Research Centers focused on biotechnology, manufacturing, robotics and sustainability

Engineering innovations transform our lives and energize the economy.  The U.S. National Science Foundation announces a five-year investment of $104 million, with a potential 10-year investment of up to $208 million, in four new NSF Engineering Research Centers (ERCs) to create technology-powered solutions that benefit the nation for decades to come.   

"NSF's Engineering Research Centers ask big questions in order to catalyze solutions with far-reaching impacts," said NSF Director Sethuraman Panchanathan. "NSF Engineering Research Centers are powerhouses of discovery and innovation, bringing America's great engineering minds to bear on our toughest challenges. By collaborating with industry and training the workforce of the future, ERCs create an innovation ecosystem that can accelerate engineering innovations, producing tremendous economic and societal benefits for the nation."  

The new centers will develop technologies to tackle the carbon challenge, expand physical capabilities, make heating and cooling more sustainable and enable the U.S. supply and manufacturing of natural rubber.  

The 2024 ERCs are:  

• NSF ERC for Carbon Utilization Redesign through Biomanufacturing-Empowered Decarbonization (CURB) — Washington University in St. Louis in partnership with the University of Delaware, Prairie View A&M University and Texas A&M University.   CURB will create manufacturing systems that convert CO2 to a broad range of products much more efficiently than current state-of-the-art engineered and natural systems.    
• NSF ERC for Environmentally Applied Refrigerant Technology Hub (EARTH) — University of Kansas in partnership with Lehigh University, University of Hawaii, University of Maryland, University of Notre Dame and University of South Dakota.   EARTH will create a transformative, sustainable refrigerant lifecycle to reduce global warming from refrigerants while increasing the energy efficiency of heating, ventilation and cooling.    
• NSF ERC for Human AugmentatioN via Dexterity (HAND) — Northwestern University in partnership with Carnegie Mellon University, Florida A&M University, and Texas A&M University, and with engagement of MIT.  HAND will revolutionize the ability of robots to augment human labor by transforming dexterous robot hands into versatile, easy-to-integrate tools.     
• NSF ERC for Transformation of American Rubber through Domestic Innovation for Supply Security (TARDISS) — The Ohio State University in partnership with Caltech, North Carolina State University, Texas Tech University and the University of California, Merced.   TARDISS will create bridges between engineering, biology, and agriculture to revolutionize and on-shore alternative natural rubber production from U.S. crops.  

Since its founding in 1985, NSF's ERC program has funded 83 centers (including the four announced today) that receive support for up to 10 years. The centers build partnerships with educational institutions, government agencies and industry stakeholders to support innovation and inclusion in established and emerging engineering research.  

Visit NSF's website and read about NSF Engineering Research Centers .  

Research areas

New Classical Algorithm Enhances Understanding of Quantum Computing’s Future

In an exciting development for quantum computing, researchers from the University of Chicago’s Department of Computer Science , Pritzker School of Molecular Engineering , and Argonne National Laboratory have introduced a groundbreaking classical algorithm that simulates Gaussian boson sampling (GBS) experiments. This achievement not only helps clarify the complexities of current quantum systems but also represents a significant step forward in our understanding of how quantum and classical computing can work together. The research just appeared in the prominent Nature Physics Journal this past June.

The Challenge of Gaussian Boson Sampling

Gaussian boson sampling has gained attention as a promising approach to demonstrating quantum advantage, meaning the ability of quantum computers to perform tasks that classical computers cannot do efficiently. The journey leading up to this breakthrough has been marked by a series of innovative experiments that tested the limits of quantum systems. Previous studies indicated that GBS is challenging for classical computers to simulate under ideal conditions. However, Assistant Professor and author Bill Fefferman pointed out that the noise and photon loss present in actual experiments create additional challenges that require careful analysis.

Notably, experiments ( such as these ) conducted by teams at major research centers from the University of Science and Technology of China and Xanadu, a Canadian quantum company, have shown that while quantum devices can produce outputs consistent with GBS predictions, the presence of noise often obscures these results, leading to questions about the claimed quantum advantage. These experiments served as a foundation for the current research, driving scientists to refine their approaches to GBS and better understand its limitations.

Understanding Noise in Quantum Experiments

“While the theoretical groundwork has established that quantum systems can outperform classical ones, the noise present in actual experiments introduces complexities that require rigorous analysis,” explained Fefferman. “​​Understanding how noise affects performance is crucial as we strive for practical applications of quantum computing.”

This new algorithm addresses these complexities by leveraging the high photon loss rates common in current GBS experiments to provide a more efficient and accurate simulation. The researchers employed a classical tensor-network approach that capitalizes on the behavior of quantum states in these noisy environments, making the simulation more efficient and manageable with available computational resources.

Breakthrough Results

Remarkably, the researchers found that their classical simulation performed better than some state-of-the-art GBS experiments in various benchmarks.

“What we’re seeing is not a failure of quantum computing, but rather an opportunity to refine our understanding of its capabilities,” Fefferman emphasized. “It allows us to improve our algorithms and push the boundaries of what we can achieve.”

The algorithm outperformed experiments by accurately capturing the ideal distribution of GBS output states, raising questions about the claimed quantum advantage of existing experiments. This insight opens doors for improving the design of future quantum experiments, suggesting that enhancing photon transmission rates and increasing the number of squeezed states could significantly boost their effectiveness.

Implications for Future Technologies

The implications of these findings extend beyond the realm of quantum computing. As quantum technologies continue to evolve, they hold the potential to revolutionize fields such as cryptography, materials science, and drug discovery. For instance, quantum computing could lead to breakthroughs in secure communication methods, enabling more robust protection of sensitive data. In materials science, quantum simulations can help discover new materials with unique properties, paving the way for advancements in technology, energy storage, and manufacturing. By advancing our understanding of these systems, researchers are laying the groundwork for practical applications that could change the way we approach complex problems in various sectors.

The pursuit of quantum advantage is not just an academic endeavor; it has tangible implications for industries that rely on complex computations. As quantum technologies mature, they have the potential to play a crucial role in optimizing supply chains, enhancing artificial intelligence algorithms, and improving climate modeling. The collaboration between quantum and classical computing is crucial for realizing these advancements, as it allows researchers to harness the strengths of both paradigms.

A Cumulative Research Effort

Fefferman worked closely with Professor Liang Jiang from the Pritzker School of Molecular Engineering and former postdoc Changhun Oh , currently an Assistant Professor at the Korea Advanced Institute of Science and Technology, on previous work that culminated in this piece of research.

In 2021, they examined the computational power of noisy intermediate-scale quantum (NISQ) devices through lossy boson sampling . The paper revealed that photon loss affects classical simulation costs depending on the number of input photons, which could lead to exponential savings in classical time complexity. Following this, their second paper focused on the impact of noise in experiments designed to demonstrate quantum supremacy, showing that even with significant noise, quantum devices can still produce results that are difficult for classical computers to match. In their third article, they explored Gaussian boson sampling (GBS) by proposing a new architecture that improves programmability and resilience against photon loss, making large scale experiments more feasible. They then introduced a classical algorithm in their fourth paper that generates outcomes closely aligned with ideal boson sampling, enhancing benchmarking techniques and emphasizing the importance of carefully selecting experiment sizes to preserve the quantum signal amidst noise.Finally, in their latest study, they developed quantum-inspired classical algorithms to tackle graph-theoretical problems like finding the densest k-subgraph and the maximum weight clique and a quantum chemistry problem called the molecular vibronic spectra generation . Their findings suggested that the claimed advantages of quantum methods may not be as significant as previously thought, with their classical sampler performing similarly to the Gaussian boson sampler.

Looking Ahead

The development of the classical simulation algorithm not only enhances our understanding of Gaussian boson sampling experiments but also highlights the importance of continued research in both quantum and classical computing. The ability to simulate GBS more effectively serves as a bridge toward more powerful quantum technologies, ultimately helping us navigate the complexities of modern challenges. As we explore these insights, we move closer to realizing the full potential of quantum technologies, which could lead to innovative solutions that benefit society as a whole. Each step forward in this journey brings us closer to a future where quantum computing plays a vital role in addressing some of the world’s most pressing challenges. With ongoing research and collaboration, the future of quantum computing looks promising, unlocking new realms of possibility for science and society.

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A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org .

• Data Science

How Pew Research Center is – and is not – using large language models in our work

At Pew Research Center, we’re watching with great interest as new generations of large language models such as GPT, Claude and Gemini develop. These models, also known as LLMs, are machine learning tools that are trained on massive digital datasets to predict and generate humanlike language. They’re sometimes described as a subset of generative artificial intelligence.

As public-facing social scientists committed to innovation, we’re intrigued by what this fast-moving technology might add to our toolkit. As researchers, we’re committed to explaining how the public is reacting to these advances . And as information providers whose fundamental values include accuracy and methodological rigor, we’re moving with great deliberation so as not to affect the quality of our work.

In this post, we’ll share our current guidelines for the internal use of LLMs. We hope to start a dialogue with our peers and broader audiences about the best ways to use this technology as it continues to develop.

LLMs aren’t new to the research community. The computational social scientists on our Data Labs team have regularly used these tools in specialized, narrowly defined research tasks for years.

What is new is that developments in scale, computational capacity and model training have led to a massive leap forward in these models’ general capabilities.

Modern LLMs can perform a much wider variety of tasks, particularly when it comes to interpreting and mimicking human communication. But even though LLMs are increasingly capable (and increasingly integrated into common software), they are just pattern recognition systems. And in their 2024 iteration, at least, they are not guaranteed to provide accurate, factual information. When they fail to produce accurate information, it can be hard to explain what went wrong because of the complexity of their internal workings and the sheer amount of data on which they were trained.

Our commitments when using LLMs

Given the above, the Center’s approach in 2024 is a version of “proceed with caution.” Here are our commitments to ourselves and to our audiences:

Our work is people-centered

Real people, not machines, answer our surveys. Collecting people’s opinions in the United States and abroad is our most important task. We do not use LLMs to create or model “synthetic” public opinion. Our survey results are based on the views reported to us by real people.

Photos on our site are of and by real people. We are not using AI to create images. Human artists create the artwork.

Humans oversee, and are responsible for, every aspect of our work. From survey questionnaires to published research reports, our work begins and ends with human experts. We do not use LLMs to decide on research topics or questionnaire items. We do not use LLMs to identify the storylines and key findings of our reports and blog posts . We believe that trained and experienced humans must guide the process of going from a raw dataset to a report that helps our audience make sense of the data.

Accuracy and rigor remain paramount

In everything we do, we prioritize accuracy and rigor, and our explorations of AI are no different. To the extent that modern technologies can help facilitate our mission to generate a trustworthy foundation of facts, we’re interested in adopting them. But only if they allow us to maintain our existing standards for quality research.

We’ll experiment as a path to innovation

Current areas of experimentation.

In the production of our website. We see real potential in using this technology to help write the code needed to produce our website – a detailed, structured and often repetitive process. While we’re not currently using AI to improve users’ search and navigation experiences on our website, we see that as an area worth exploring in the near term.

In our research process. Coding assistance is also potentially useful to our researchers. For example, we may use an LLM code assistant to format or help write the code needed to analyze survey datasets. But it needs guardrails. At the Center, researchers who are fluent in a coding language can access an LLM coding assistant only if they have a full, human-run code check process .

We’ll also continue experimenting with using LLMs to analyze textual data, such as coding open-ended survey responses into categories or scraping websites for key data. This work has been and will always be overseen by Center staff. We will continue to be transparent and acknowledge in our report methodologies whenever we have used these tools.

In the final stages of our editorial functions. Many widely available tools already use this technology to clean up grammar, punctuation, etc. And we are using these tools, too, though a human verifies our final copy. In our judgment, this level of use does not require external labeling.

Possible future areas of experimentation

We’re watching developments in the publishing industry carefully. Some interesting uses of AI include:

Creating derivative products. We see potential for leveraging LLMs to quickly generate derivative products that would create new access points to our content for a wider array of consumers. This could include drafting social media posts in a variety of styles for a variety of platforms. Or it could mean creating a first-draft, thematic summarization for our topic index landing pages. As of this writing, however, we are not ready to cross this bridge. Our current internal guidance is that any external-facing products need to be human-authored, not just overseen.

Summarizing research in search results. Currently, the search function on the Pew Research Center website delivers a list of links. We hope at some future point to incorporate a “smart search” overlay that would deliver a more pointed summary of our data to interested users. We’re following developments in the accuracy of model results so we can experiment further at the right moment.

We’ll be transparent

For currently approved uses:

• If we use an LLM in any aspect of our research process, we will note that in the published methodology section.
• Using an LLM to make minor grammatical, spelling or reading grade level changes is not considered a meaningful use and will not be cited.
• As made clear above, our developers are already using human-supervised AI to write the code that creates our website.

We’d love to hear from you about your thoughts, hopes and concerns on this topic. We already know it’s one we’ll be revisiting this year and beyond.

Categories:

More from Decoded

More from decoded, what a survey experiment tells us about measuring religious tolerance in australia, measuring partisanship in europe: how online survey questions compare with phone polls, reproducibility as part of code quality control.

To browse all of Pew Research Center findings and data by topic, visit  pewresearch.org

About Decoded

This is a blog about research methods and behind-the-scenes technical matters at Pew Research Center. To get our latest findings, visit pewresearch.org .

Copyright 2024 Pew Research Center

Webb Finds Early Galaxies Weren’t Too Big for Their Britches After All

It got called the crisis in cosmology. But now astronomers can explain some surprising recent discoveries.

When astronomers got their first glimpses of galaxies in the early universe from NASA’s James Webb Space Telescope, they were expecting to find galactic pipsqueaks, but instead they found what appeared to be a bevy of Olympic bodybuilders. Some galaxies appeared to have grown so massive, so quickly, that simulations couldn’t account for them. Some researchers suggested this meant that something might be wrong with the theory that explains what the universe is made of and how it has evolved since the big bang, known as the standard model of cosmology.

According to a new study in the Astronomical Journal led by University of Texas at Austin graduate student Katherine Chworowsky, some of those early galaxies are in fact much less massive than they first appeared. Black holes in some of these galaxies make them appear much brighter and bigger than they really are.

“We are still seeing more galaxies than predicted, although none of them are so massive that they ‘break’ the universe,” Chworowsky said.

The evidence was provided by Webb’s Cosmic Evolution Early Release Science (CEERS) Survey , led by Steven Finkelstein, a professor of astronomy at UT Austin and study co-author.

Image A : CEERS Deep Field (NIRCam)

Black holes add to brightness.

According to this latest study, the galaxies that appeared overly massive likely host black holes rapidly consuming gas. Friction in the fast-moving gas emits heat and light, making these galaxies much brighter than they would be if that light emanated just from stars. This extra light can make it appear that the galaxies contain many more stars, and hence are more massive, than we would otherwise estimate. When scientists remove these galaxies, dubbed “little red dots” (based on their red color and small size), from the analysis, the remaining early galaxies are not too massive to fit within predictions of the standard model.

“So, the bottom line is there is no crisis in terms of the standard model of cosmology,” Finkelstein said. “Any time you have a theory that has stood the test of time for so long, you have to have overwhelming evidence to really throw it out. And that’s simply not the case.”

Efficient Star Factories

Although they’ve settled the main dilemma, a less thorny problem remains: There are still roughly twice as many massive galaxies in Webb’s data of the early universe than expected from the standard model. One possible reason might be that stars formed more quickly in the early universe than they do today.

“Maybe in the early universe, galaxies were better at turning gas into stars,” Chworowsky said.

Star formation happens when hot gas cools enough to succumb to gravity and condense into one or more stars. But as the gas contracts, it heats up, generating outward pressure. In our region of the universe, the balance of these opposing forces tends to make the star formation process very slow. But perhaps, according to some theories, because the early universe was denser than today, it was harder to blow gas out during star formation, allowing the process to go faster.

More Evidence of Black Holes

Concurrently, astronomers have been analyzing the spectra of "little red dots" discovered with Webb, with researchers in both the CEERS team and others finding evidence of fast-moving hydrogen gas, a signature of black hole accretion disks. This supports the idea that at least some of the light coming from these compact, red objects comes from gas swirling around black holes, rather than stars – reinforcing Chworowsky and their team’s conclusion that they are probably not as massive as astronomers initially thought.  However, further observations of these intriguing objects are incoming, and should help solve the puzzle about how much light comes from stars versus gas around black holes.

Often in science, when you answer one question, that leads to new questions. While Chworowsky and their colleagues have shown that the standard model of cosmology likely isn’t broken, their work points to the need for new ideas in star formation.

“And so there is still that sense of intrigue,” Chworowsky said. “Not everything is fully understood. That’s what makes doing this kind of science fun, because it’d be a terribly boring field if one paper figured everything out, or there were no more questions to answer.” The James Webb Space Telescope is the world’s premier space science observatory. Webb is solving mysteries in our solar system, looking beyond to distant worlds around other stars, and probing the mysterious structures and origins of our universe and our place in it. Webb is an international program led by NASA with its partners, ESA (European Space Agency) and CSA (Canadian Space Agency).

Right click any image to save it or open a larger version in a new tab/window via the browser's popup menu.

View/Download all image products at all resolutions for this article from the Space Telescope Science Institute.

View/Download the research results from the Astronomical Journal .

Media Contacts

Laura Betz  -  [email protected] , Rob Gutro - [email protected] NASA’s Goddard Space Flight Center , Greenbelt, Md.

Marc Airhart - [email protected] University of Texas at Austin

Christine Pulliam - [email protected] Space Telescope Science Institute , Baltimore, Md.

Related Information

VIDEO : CEERS Fly-through data visualization

ARTICLE : Webb Science - Galaxies Through Time

INFOGRAPHIC : Learn More about black holes

VIDEO : Webb Science Snippets Video: “The Early Universe”

INFOGRAPHIC : What is Cosmological Redshift?

More Webb News

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Webb Mission Page

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Related Terms

• Astrophysics
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• Goddard Space Flight Center
• James Webb Space Telescope (JWST)
• Science & Research
• The Universe

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Dear Colleague Letter: NSF Support for Natural Hazards Engineering Research Infrastructure (NHERI) during FY 2026-FY 2035

August 13, 2024

Dear Colleagues:

The purpose of this Dear Colleague Letter (DCL) is to inform the natural hazards engineering research community of plans for U.S. National Science Foundation (NSF) support for operations of the Natural Hazards Engineering Research Infrastructure (NHERI) during fiscal year (FY) 2026-FY 2035.

Since 2015, NHERI has operated through NSF support as a national distributed, multi-user facility that provides the natural hazards engineering community with access to research infrastructure - earthquake and windstorm engineering testing facilities, cyberinfrastructure, computational modeling and simulation tools, and research data - coupled with education and community outreach activities to advance knowledge and innovation for the performance of the nation's civil infrastructure and communities under natural hazard events (earthquakes, windstorms, and the associated hazards of tsunamis and storm surge).

PAST AND CURRENT NSF SUPPORT

The NHERI portfolio is described at the NHERI web portal . NHERI was developed through two NSF program solicitations NSF 14-605 and NSF 15-598 . As the outcomes of these two solicitations, NSF supported eleven cooperative agreements for a Network Coordination Office (NCO), Cyberinfrastructure (CI), Computational Modeling and Simulation Center (SimCenter), and eight awards for earthquake and windstorm engineering experimental laboratory and field equipment facilities. These eleven cooperative agreements will expire on September 30, 2025, the end of FY 2025.

NSF-supported researchers have used these NHERI resources to advance fundamental knowledge and innovation on the performance of civil infrastructure under earthquake, tsunami, windstorm, storm surge, and climate change hazards. NHERI research has led to (1) resilient and sustainable materials and new structural systems for building design and structural rehabilitation; (2) new methods to predict and improve the performance of soil, underground infrastructure, and on soil-structure-interactions; (3) strategies for safeguarding coastal infrastructure; (4) open source computational, simulation, and workflow research and educational tools; (5) new experimental simulation techniques and instrumentation; and (6) systematic field data collection procedures that capture civil infrastructure performance site response information during post-disaster field reconnaissance investigations. Laboratory, field, simulation, and post-disaster reconnaissance data from NHERI research have been published in the certified NHERI Data Depot for data management, community sharing, and data reuse. The NCO has supported the NHERI Summer Institute for early career scholars, a NHERI-wide Graduate Student Council, and a NHERI-wide Research Experiences for Undergraduates program. NHERI awardees have organized Natural Hazards Summits in 2022 and 2024, NHERI Computational Symposia, NHERI Computational Academies, and workshops and bootcamps for uses of NHERI resources.

FUTURE NSF SUPPORT

Providing research infrastructure that can support new knowledge advancements, innovations, and workforce development for the resilience and sustainability of the nation’s civil infrastructure and communities under natural hazard events continues to be a high priority for NSF and the Directorate for Engineering. This DCL conveys the NSF plan for continued support of a visionary NHERI construct for FY 2026-FY 2035, with initial five-year cooperative agreements, starting on October 1, 2025, to be supported through the two funding mechanisms described below.

First, to provide continuity in NHERI operations to the natural hazards engineering community, this DCL conveys the NSF plan for potential cooperative agreement renewal of NHERI’s Network Coordination Office, Cyberinfastructure ( NHERI web portal ), Computational Modeling and Simulation Center, and Natural Hazard and Disaster Reconnaissance (RAPID) facility originally supported under NSF 14-605 and NSF 15-598 . NSF encourages the Recipients of these awards to discuss with the cognizant Program Officer the potential to submit an initial five-year renewal proposal for FY 2026-FY 2030. Renewal proposals are anticipated to be submitted by a target date of February 1, 2025 . If renewed for FY 2026-FY 2030, and then based on the Recipient’s satisfactory performance during that period and availability of funds, NSF would consider a second five-year proposal for FY 2031-FY 2035. NSF support will also be contingent upon the outcome of the external merit review of each five-year proposal.

Second, a forthcoming program solicitation is anticipated to be issued in 2024 by NSF’s Directorate for Engineering, Division of Civil, Mechanical and Manufacturing Innovation. The new program solicitation is expected to be for a competition to establish a new NHERI portfolio for exemplary operations of experimental and field equipment/instrumentation facilities to serve as national resources for NHERI research and education. These facilities will be expected to advance frontier science and engineering research focused on the impact of climate change, earthquake, tsunami, windstorm, storm surge, flooding, and fire/wildland-urban interface (WUI) hazards on the nation’s civil infrastructure. Current NSF-supported NHERI facilities, as well as other existing facilities that can bring new national resources to NHERI, would be eligible for this competition. Through this new solicitation, it is anticipated that support will be provided, for “multi-user ready” facilities that can provide fully operational experimental laboratory and/or field equipment/instrumentation, with unique, benchmarked capabilities not elsewhere available in the U.S., coupled with fully operational data acquisition system(s).

The planned solicitation is not intended to support the construction of a new facility or upgrade of an existing facility. Funding opportunities for equipment, instrumentation, and facility development are available through NSF programs such as Major Research Instrumentation , Mid-scale Research Infrastructure-1 , and Mid-scale Research Infrastructure-2 .

NSF does not intend to provide additional information beyond this DCL until the program solicitation is issued, as that will be the official issuance for this competition and take precedence over the information in this DCL. The anticipated due date for proposals submitted in response to this new program solicitation will be at least 90 days following the publication date. NSF will host an information webinar after the solicitation is issued.

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It is anticipated that all NHERI proposals for FY 2026-FY 2035 will be expected to build upon input gathered from the research community through workshop reports and community studies. These documents articulate the research needs and the consensus that continued support of a natural hazards engineering research infrastructure is critical for the research community to advance frontier engineering and science for understanding and mitigating the impacts of natural hazards on civil infrastructure and communities. These documents can include the NHERI Science Plan , U.S. National Science Foundation Natural Hazards Engineering Research Infrastructure (NHERI) Decadal Visioning Study 2026-2035 , Frontiers in Built Environment NHERI Series , The Role of Engineering to Address Climate Change: A Visioning Report , Engineering Materials for a Sustainable Future: A Visioning Report , AI Engineering: A Strategic Research Framework to Benefit Society , Strategic Plan for the National Earthquake Hazards Reduction Program, Fiscal Years 2022-2029 , and Strategic Plan for the National Windstorm Impact Reduction Program .

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Scientists from the California and Nevada Water Science Centers attended the 28th annual Lake Tahoe Summit to discuss the work the USGS is doing in the Tahoe Basin. The theme of this year’s event was “Connecting Tahoe: Investing in Transit, Trails, and Technology for the Future.”

The Lake Tahoe Summit is an annual event that brings local, federal, and state leaders together to discuss ways to protect Lake Tahoe and strengthen the partnership underlying the Lake Tahoe Environmental Improvement Program. This year’s summit took place on Wednesday, August 14 at Round Hill Pines Beach Resort in Zephyr Cove, Nevada. The event was hosted by U.S. Senator Catherine Cortez Masto from Nevada and included the following speakers: Serrell Smokey from the Washoe Tribe of Nevada and California, Sen. Jacky Rosen of Nevada, Sen. Laphonza Butler of California, U.S. Representative Mark Amodei of Nevada, and U.S. Representatives John Garamendi and Kevin Kiley of California. The keynote speaker for the event was U.S. Secretary of Transportation Pete Buttigieg. 

Scientists from the California and Nevada Water Science Centers were on hand to answer questions about work the USGS is doing in the Tahoe Basin. 

USGS booth at the 2024 Lake Tahoe Summit. Shown are Zachery Hood (left) and Sara Doyle (right) of the Nevada Water Science Center. Also present were Joseph Nawikas of the California Water Science Center and Ramon Naranjo of Nevada. (Photo by Ramon Naranjo.)

Read more information about USGS monitoring and research activities at Lake Tahoe.

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• Published: 10 March 2021

The next 25 years

Nature Biotechnology volume  39 ,  page 249 ( 2021 ) Cite this article

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Since this journal launched in March 1996, biotech has become a US economic powerhouse. To reach its full potential over the next 25 years, touching all corners of the globe, it must become more inclusive.

In biotech, past performance rarely predicts future results. Who foresaw CRISPR gene editing sweeping the world in 2012 or, for that matter, mRNA vaccines saving humanity? In the next 25 years, the watchwords must be “change” and “inclusiveness.” Biological technology has the potential to alter many aspects of human life, and it will transform them in ways we cannot imagine. But the ways we deploy biotech must change, too. Thus far, it has been a largely elitist enterprise, serving niche markets in rich nations. If biotech is not to be just another source of inequity in our world, it must redefine itself. That means focused, collective efforts to address the needs of patients and consumers—and of the planet.

Technologies for engineering, manipulating and monitoring living systems have come a long way since this journal launched in 1996 . They have propelled biotech to one of the fastest-growing sectors of the US economy, contributing $300–400 billion annually.

Sequencing has been part of that transformation. Today, sequencing a human genome takes just ~$100 and a few hours—compared with the decades of effort and billions of dollars spent on the first three-gigabase genome. This means the DNA of an increasingly representative and diverse slice of the world’s population will be sequenced: a million or so human genomes have been sequenced to date and 60 million genomes are projected by 2025 , with another 100 million just in China by the decade’s end. In tandem, smart devices and wearables will make mass phenotyping a reality. In the new era of human and holobiont real-world research, wearables and in-home sensors will provide longitudinal data , enabling detailed parsing of hitherto ill-defined states related to nutrition, health and disease. Crucially, it may also provide direction on how and when to intervene .

With DNA synthesis already a penny per base, bioengineers are moving from making small changes in single genes to writing and editing with precision throughout genomes. Through iterative design–build–test cycles, bioengineered products will become increasingly sophisticated; indeed, some of the most complex metabolic pathways in nature have already been recapitulated through synthetic biology .

Not all areas of biotech will move quickly: we still manufacture proteins in Chinese hamster ovary cells, use ancient PCR technology in diagnostics, and make ethanol from corn. But the rate of knowledge expansion—and the rate of technology dissemination —is increasing every year. Digitization and virtualization of samples and findings in the cloud will allow ever larger datasets to be shared around the planet for analysis. Product development times will shorten, as they have for biopharmaceuticals and vaccines in this pandemic; new breeding and diversification technologies will accelerate crop development times. Cumbersome global supply lines for bulk manufacture of biotech products may be displaced by a shift to faster, distributed manufacturing .

Patients will be at the center of everything. Precision therapy will continue its slow march, but must practitioners must heed what people want: shorter treatments, oral or dermal drug formulations, and interventions for both quality and quantity of life. As populations gray, biopharma will have to expand beyond its preoccupation with oncology and rare disease to broader comorbidities associated with aging.

An urbanizing population—estimated to be 6.3 billion people (66% of the world) by 2050—will drive new biotech solutions for sanitary, microbe surveillance , and waste recycling systems. Efforts to slow the transmission of pathogens between populous urban centers (via air travel or otherwise) will necessitate the deployment of efficient detection systems for infectious agents.

In the face of threats from global warming, in farm fields, bioengineering will feed the growing global population through crops resistant to extremes of drought, cold, heat, salinity, pests and disease ; in the lab, it will produce in vitro meat and alternative proteins. Fossil fuel–free routes will be bioengineered to a vast panoply of chemicals, plastics, fuels, materials, flavorings and textiles.

As the dominance of the US biotech sector comes under increasing challenge, bioengineered products will spread more widely across the world. Innovative therapies from China will begin to compete with products from North America or Europe. A burgeoning pharmacopeia—supplemented with biosimilars and biobetters from China, South Korea and India—will drive down prices and increase usage; generic oligonucleotide therapeutics and gene therapies will follow. Emerging countries will similarly drive innovation in manufacturing, making products affordable not only for their domestic markets, but also for Latin America, Asia and Africa. China’s ‘ Belt and Road ’ initiative will place it in a strong position to capitalize on links with the global South.

But the future of biotech is as much about political and cultural leadership as it is about the science and technology itself. In healthcare, premium-priced biotech products have exacerbated, rather than assuaged, long-standing health and wealth disparities in our societies. Most biologics are available to only a select few. In agbiotech, a lack of civil society dialog and the concentration of intellectual property within a few large corporations have brought bioengineered crops to a standstill in Europe and much of the rest of the world. For livestock engineering, the situation in the United States has similarly gone awry.

In the next 25 years, biotech must put people at its center. Today, the expertise walled off in academia or closeted in industrial franchises is in a bubble—cut off from the people it seeks to serve. The bioengineers of the future must not only promote technical excellence, but also foster equity, ethics, dialogue and social responsibility in how the fruits of their research are deployed. Only then can biotech become the “ broad and inclusive enterprise ” that will serve the needs of the many, rather than the few.

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3 scenarios for the future of research – which is most likely?

March 20, 2019 | 11 min read

By Alison Bert, DMA

Experts at AAAS weigh in on the new Research Futures study by Elsevier and Ipsos MORI

Caption: Experts debate the future of research at an interactive panel at the AAAS Annual Meeting in Washington, DC (from left): Dr. Peter Tindemans, Secretary General of EuroScience; Mary Woolley, President and CEO of Research!America; Prof. Sir Peter Gluckman, President Elect of the International Science Council; Dr. Joanne Tornow, Assistant Director for Biological Sciences at the National Science Foundation and, at the podium, Adrian Mulligan, Research Director for Customer Insights at Elsevier. (Photos by Alison Bert)

Imagine yourself 10 years from now. It’s 2029, and the world of research has changed – dramatically for some of you. But how?

Where will your research funding come from? Will your collaborators be academics or colleagues at a tech company?

Will you use artificial intelligence to determine your research hypothesis – and will journals use AI to decide whether to accept your paper? Will that “paper” even look like the manuscript you’re used to submitting?

If you’re a professor, will your students come to the university or study from afar?

These are just a few of the questions the new  Research Futures  scenario-planning study delves into. To forecast how research might be created and exchanged 10 years from now, investigators from Elsevier and Isos MORI examined the literature and market drivers, interviewed over 50 funders, futurists, publishers and technology experts and surveyed more than 2,000 researchers.

From the analysis, key themes emerged. The investigators then held creative workshops, and participants used this knowledge to develop three plausible scenarios    of the future:

Brave open world considers the rise of open science.

Tech titans looks at the growing influence of technology.

Eastern ascendance considers the role the East – and China in particular – might play.

Elsevier colleagues initially conceived this project to gain insights into how they could collaborate with the research community to build a better information system supporting research.

“We needed some information to inform our own decisions as an information analytics provider,” said Hannfried von Hindenburg, SVP of Global Communications, in introducing the panel. “But we felt we should make it public so that all of you could make your decisions based on this research.

“It’s meant to stimulate a discussion, and it’s meant to stimulate decision-making.”

That conversation continued when the report was released at the  Annual Meeting of the American Association for the Advancement of Science (AAAS) opens in new tab/window  in Washington, DC. A panel of research leaders – along with researchers in the audience – weighed in on which scenarios seemed most likely.

“Since we’re envisioning the future, there are no wrong answers,” said moderator Dr. Brad Fenwick, SVP of Global Strategic Alliances at Elsevier.

Hannfried von Hindenburg, SVP of Global Communications at Elsevier, introduces the report and panel at AAAS.

Exploring the future through a 3D lens

Adrian Mulligan summarizes key themes and scenarios in the report before seeking input from the panel and audience.

In his introduction to the report, lead investigator  Adrian Mulligan opens in new tab/window , Director of Research for Customer Insights at Elsevier, summarized the key points – starting with the “three dimensions” the experts  used to contemplate the future.

Three dimensions were used to contemplate the future: the progress of technology (blue); the degree of openness and sharing of research (orange); and those who support research and whether they would be aligned or fragmented (grey).

Blue represents the world of technology. “On one extreme, technology is revolutionary and drastically alters the way science is done,” Mulligan explained. “On the other, evolutionary tech is just like it is now, steadily progressing.”

Orange, meanwhile, represents the exchange of research and data and the degree to which it will be open or controlled, and gray represents whether organizations or nation states are aligned or fragmented.

Each of these elements combines with the others in a distinct way in the three future scenarios.

Scenario 1: Brave open world

In the Brave open world scenario, various factors converge for open collaboration.

“Brave open world” is characterized by open sharing of research, revolutionary technology and more convergence among stakeholders, Mulligan explained. For example, big tech partners with funders and research institutes to develop interoperable machine learning tools and platforms.

“In this scenario, all the actors and funders … come together to create an open platform in which science is shared,” he said. “Research articles are all open access, and the research article moves on from the current format to a more dynamic ‘notebook’ style that is more atomized and broken up.”

In addition, AI accelerates the speed and volume of research, and researchers are rewarded by a range of measures, including interdisciplinary collaboration, data dissemination and social impact.

Trust in science has increased because the public has greater access to published science, and researchers are expected present their work in a way that’s understandable to the lay person.

Scenario 2: Tech titans

In the Tech titans scenario, big tech companies take charge of the research landscape.

The “Tech titans” scenario is characterized by revolutionary technology, with the large tech companies becoming the main supporters, curators and distributors of knowledge. “The big technology companies step in and play a key role in the communication of science and the funding of research,” Mulligan said. “There are massive advances in AI in this world. Here, we see AI play such an important role that it changes society in essential ways. There are lots of job losses … in research as well.”

Much of research has become automated, driven by AI and data mining, and AI enables data-driven hypothesis generation – a practice we’re already experimenting with. Researchers often work closely with industry as independent consultants for large corporations.

Data sharing and machine learning have supported successful commercial breakthroughs, and the platforms the tech companies create have lowered the cost of doing research. However, there are concerns about data being held by private companies and not being made public – or medical advances not being evenly distributed. That competitive drive would likely spill onto the global stage.

“A number of countries are competing to deploy artificial intelligence, keeping it close to their chests in terms of the knowledge they have acquired in developing of new products,” Mulligan said. “And we find some countries struggling to adapt to making use of these new technologies.”

Meanwhile, it’s a politically fragmented world; state funding for research has been reduced, and industry and philanthropic organizations have stepped in to fill the gap, investing in challenge-led science.

Scenario 3: Eastern ascendance

In the Eastern ascendance scenario, China’s desire to transform into a knowledge-based economy has led to heavy public investment in R&D.

The third scenario – Eastern ascendance – is also a fragmented world, with a sharp division between the United States and China. “China has invested massively into research and development, and it’s really paying dividends for them,” Mulligan said. “In the West, we’re unable to keep up with what China is doing, and as a consequence, the sheer volume of that investment is really shaping the way research is being communicated and the advances that are being made.

“Actually, the world changes so much that China becomes a magnet for western researchers. So rather than Western researchers going to Oxford or MIT or the top universities in Europe, they’re heading towards China.

“Open science is embraced in this world,” he continued, “but only partly embraced because it’s quite a fragmented world. People are trying to take commercial advantage of the data and science that’s been communicated, so there’s a lack of global alignment on research projects. Everyone’s trying to do things in their own way.”

As a result, products like self-driving cars, or developments in personalized medicine, are not universally available.

In publishing, the Impact Factor continues to prevail and the subscription model plays a role. Meanwhile, big tech companies form  partnerships with publishers  to provide AI-enabled workflow and publishing tools.

Researchers or technology: which will drive new knowledge?

For the rest of the workshop, Dr. Fenwick posted questions from the survey, and audience members used their smart phones to register their answers in  Menti opens in new tab/window . For example:

Question:  “In 10 years, the creative force   driving forward new knowledge will be …”

Answer:  Researchers – Technology – Either equally likely

Mulligan started by alluding to the “robust intelligence of the ‘tech titan’ world” and the expanding role of AI in driving research: Could AI become so advanced that it could create new science? “We had a number of experts say that much of the hypotheses being generated will be coming from machines rather than humans,” he said. “The role of technology has the the potential to transform research.”

Two panelists challenged the question itself.

"The real idea underlying this statement is that AI will replace researchers completely, and this will not be the case," said Dr. Peter Tindemans, founding member and Secretary General of  EuroScience opens in new tab/window .

“I think it depends how you look at this,” said  Prof. Sir Peter Gluckman opens in new tab/window , President Elect of the  International Science Council opens in new tab/window  and former Chief Science Advisor for the Prime Minister of New Zealand. He referred to Prof.  Dan Sarewitz’s 2016 essay “Saving Science” in  The New Atlantis opens in new tab/window :

As Dan Sarewitz suggests … science is driven by technological development. Until the microscope was invented, you couldn’t look at the cell – etcetera, etcetera, etcetera. … Always new technologies allow new questions to be answered. So by definition, much science is driven ultimately by technological possibilities.

Dr.  Joanne Tornow opens in new tab/window , Assistant Director for Biological Sciences at the  National Science Foundation opens in new tab/window , countered with a vote for the researcher:

Technology by itself doesn’t answer the questions. It’s the researcher. … You have to have the technology – I agree. And technology is as disruptive and as transformational as an aha moment in understanding. But it doesn’t in and of itself solve a problem.

Dr. Fenwick then asked: “Where will the new idea to do the research come from? Where will the idea for the hypothesis come from? (How will it be decided whether) it’s worth researching? Will this be  in silico opens in new tab/window  or will it still be the PI that comes up with the idea?”

Dr. Tornow responded with still another question: “Where does new technology come from? New technology comes from ideas that researchers have. It’s kind of a virtuous cycle.”

Dr. Fenwick agreed that technology is often developed to meet the needs of science: “You wouldn’t build a collider if you didn’t have the scientific community saying I need this tool to answer this question.”

Then he played devil’s advocate: “On the other hand, I could make an argument that if we can’t digest all the science, but a machine can through machine learning, what if a machine came up with a question or hypothesis or a question worth asking and answering? Would we accept it?”

Not only would we accept it; researchers who enable their questions to be generated by AI would have a competitive advantage, Prof. Gluckman said. “Those researchers who do big data and use big-data tools tend to write papers that get into high impact journals,” he said. “And funders love big-data-based, meta-analysis type research.”

As the “chicken-and-egg” aspect of this conundrum became increasingly apparent, a woman in the audience aptly pointed out, “Someone had to write the algorithm.”

Ultimately, the panelists as well as the audience voted more in favor of researchers.

In the  Research Futures  survey of researchers, the most popular response was ‘researchers.’

Will students actually  go  to universities?

The next question dealt with the rising trend of distance learning in higher education:

Question:  “In 10 years, university student will be educated …

Answer:  Mostly on campus – Mostly remotely – Either equally likely.

Dr. Tindemans said there are pressing reasons for students to be on campus:

Students go to a university not just to learn something. Secondly, in many areas of study, you need to work together with your professors by doing experiments (and) other things together, and that is very difficult to organize another way. And the third thing is simply the status: a diploma is a link to what university and not just to a collection of exams you have passed online.

Mary Woolley opens in new tab/window , President and CEO of  Research!America opens in new tab/window , said the answer depends on the university and subjects being studied:

I would say there’s a context … of elite vs non-elite university and college institutions and education. For the elite, students would be more likely on campus. But for all the rest, which is a much higher percentage, I would think it would be increasingly remotely.

Dr. Fenwick pointed out that more elite universities in the US are “making a bet that they can do more distance learning.” As an example, he mentioned a university that bought a large education company, using Elsevier to create their learning platform.

Prof. Gluckman agreed that university education is likely to change, with a rise in interdisciplinary and team-based research, but added that other as yet uncertain factors would also impact these future scenarios. Prof. Gluckman foresees the probability of a more focused investment of government funding in a smaller proportion of research-intensive universities, with the other universities becoming more education-focused and offering more distance-learning options for current and continuing education. However, it’s not clear what form “lifelong re-learning and retraining” will take for many people, he said, “and I think we’re still a decade away from understanding how that’s going to evolve.”

Woolley mentioned “competing pressures” that could turn the tide either way: “the move toward interdisciplinary work and team science that really does require (in-person) interaction” versus the fact that “we’re getting much, much better at connecting remotely.” Ultimately, she said, it would depend on what fields people are studying, some of which will still require a presence on campus.

Similar to the panel’s responses, the audience’s were equally divided, as were those of the researchers who took the survey:

In the  Research Futures  survey of researchers, responses were divided almost equally.

“The best way to influence the future …”

In reflecting on the topic and what was learned from the study, Mulligan said: “You can think about the future, but the best way to influence the future is to create the future.”

Download the report and supporting material

The report  Research Futures: drivers and scenarios for the next decade  is freely available.

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Elements of the underlying study data are also freely available:

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The future of research: Emerging trends and new directions in scientific inquiry

The world of research is constantly evolving, and staying on top of emerging trends is crucial for advancing scientific inquiry. With the rapid development of technology and the increasing focus on interdisciplinary research, the future of research is filled with exciting opportunities and new directions.

In this article, we will explore the future of research, including emerging trends and new directions in scientific inquiry. We will examine the impact of technological advancements, interdisciplinary research, and other factors that are shaping the future of research.

One of the most significant trends shaping the future of research is the rapid development of technology. From big data analytics to machine learning and artificial intelligence, technology is changing the way we conduct research and opening up new avenues for scientific inquiry. With the ability to process vast amounts of data in real-time, researchers can gain insights into complex problems that were once impossible to solve.

Another important trend in the future of research is the increasing focus on interdisciplinary research. As the boundaries between different fields of study become more fluid, interdisciplinary research is becoming essential for addressing complex problems that require diverse perspectives and expertise. By combining the insights and methods of different fields, researchers can generate new insights and solutions that would not be possible with a single-discipline approach.

One emerging trend in research is the use of virtual and augmented reality (VR/AR) to enhance scientific inquiry. VR/AR technologies have the potential to transform the way we conduct experiments, visualize data, and collaborate with other researchers. For example, VR/AR simulations can allow researchers to explore complex data sets in three dimensions, enabling them to identify patterns and relationships that would be difficult to discern in two-dimensional representations.

Another emerging trend in research is the use of open science practices. Open science involves making research data, methods, and findings freely available to the public, facilitating collaboration and transparency in the scientific community. Open science practices can help to accelerate the pace of research by enabling researchers to build on each other’s work more easily and reducing the potential for duplication of effort.

The future of research is also marked by scientific innovation, with new technologies and approaches being developed to address some of the world’s most pressing problems. For example, gene editing technologies like CRISPR-Cas9 have the potential to revolutionize medicine by allowing scientists to edit DNA and cure genetic diseases. Similarly, nanotechnology has the potential to create new materials with unprecedented properties, leading to advances in fields like energy, electronics, and medicine.

One new direction in research is the focus on sustainability and the environment. With climate change and other environmental issues becoming increasingly urgent, researchers are turning their attention to developing sustainable solutions to the world’s problems. This includes everything from developing new materials and technologies to reduce greenhouse gas emissions to developing sustainable agricultural practices that can feed the world’s growing population without damaging the environment.

Another new direction in research is the focus on mental health and wellbeing. With mental health issues becoming increasingly prevalent, researchers are exploring new approaches to understanding and treating mental illness. This includes everything from developing new therapies and medications to exploring the role of lifestyle factors like diet, exercise, and sleep in mental health.

In conclusion, the future of research is filled with exciting opportunities and new directions. By staying on top of emerging trends, embracing interdisciplinary research, and harnessing the power of technological innovation, researchers can make significant contributions to scientific inquiry and address some of the world’s most pressing problems.

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Science | February 25, 2020

Ten Trends That Will Shape Science in the 2020s

Medicine gets trippy, solar takes over, and humanity—finally, maybe—goes back to the moon

Katherine J. Wu and Rachael Lallensack

When the 2010s began, private spaceflight had barely gotten off the ground, Google was rolling out early personalized search results and CRISPR-Cas9 gene-editing technology was still in its infancy. By decade’s end, artificial intelligence had trounced people at a bevy of board games, SpaceX had become a household name and genetically modified human embryos became a controversial reality.

Clearly, a lot can happen in a decade—but innovation has to start somewhere. Based on what’s breaking through now, here are some trends that have the potential to shape the 2020s.

Missions to the Moon, Mars and More

The decade ahead promises an impressive lineup of space missions . NASA’s Artemis program aims to land the first woman and next man on the moon by 2024—but will likely be pushed back to 2028— with additional trips each year thereafter, paving a path for future missions to Mars. Landing astronauts on Mars won’t happen in this decade, but this summer, a new rover will be headed to the Red Planet.

Also in 2024, Japan plans to send its Martian Moon eXplorer (MMX) probe to Mars' two moons, Phobos and Deimos. MMX will touch down on Phobos, which has a gravitational pull 1,800 times weaker than Earth’s, making landing a breeze but is still strong enough to keep the spacecraft ground-based after landing. A sampling device connected to the spacecraft will collect a bit of soil to take back to Earth. MMX will also drop off a rover and then leave Phobos to survey Deimos before returning to Earth in 2029.

MMX won’t be the only spacecraft bringing samples back home. Japan’s Hayabusa 2 mission will collect samples from Ryugu, an asteroid believed to have organic matter and water remnants from when the solar system first formed roughly 4.6 billion years ago. Similarly, NASA’s OSIRIS-REx has been orbiting and surveying the asteroid Bennu since December 2018. Beginning this year, it will start practicing landing on the asteroid to collect a sample from its surface. According to NASA, researchers suspect that dirt on Bennu may contain “the molecular precursors to the origin of life and the Earth’s oceans.” (Bennu could collide with Earth late in the 22nd century, making it a valuable research target.)

Flying Cars—No, Really

A future with flying cars may seem cliché , but this might be the decade that gets this reality off the ground.

Most flying vehicles currently in development resemble large, electrically-powered drones that can be mostly automated so the operator doesn’t need a pilot’s license. But other details vary from model to model: While some resemble the “Jetsons” dream of the 1950s—they’re convertible from wheeled to winged, allowing them to transition from the open road to the airways—most of today’s “flying cars” look and operate much more like helicopters.

The biggest market for so-called “flying cars” isn’t for personal usage, but rather for fleets of air taxis. Uber, for example, has been pushing for air taxi services since 2016. This year, the company set its sights on Dallas, Los Angeles and Dubai as cities to test the system that would bypass standstill road traffic. Uber expects to expand commercially as early as 2023, according to Digital Trends . Until regulations and infrastructure are able to support air traffic, though, most people won’t be able to upgrade their personal vehicles just yet—and many doubt the practice will ever go mainstream.

But the reality of flying cars is hard to ignore when the field is packed with industry big shots, including Boeing, Porsche, Hyundai, Aston Martin, Rolls Royce and the Chinese firm Geely, which owns or holds stake in numerous auto companies. (Even the U.S. military is partnering with personal air vehicle manufacturers.)

Better Batteries

The future is electric, which means advancements in battery technology will be crucial to innovation in the 2020s. The next generation of electric cars, solar panels and smartphones will require improvements to battery life and cleaner, more efficient ways to mass-produce them.

All batteries have two electrodes, a cathode and an anode, connected by a liquid electrolyte that allows ions to flow between them. In lithium-ion batteries , the current state of the art that powers machines from laptops to Teslas, most anodes are graphite, but engineers continue to play around with different cathode materials. Most smartphones and laptops today use lithium cobalt oxide as a cathode, which is good at storing energy but costs a lot of money, doesn’t last long and often conducts heat easily. The coming decade could be defined by the search for better chemistry.

A handful of engineers are also making strides in introducing graphene into lithium-ion batteries—something Samsung says it will do by 2021. Graphene is a wunderkind in the materials world because it’s made of a single layer of carbon atoms arranged in hexagonal patterns. Graphene could lead to much smaller batteries that charge much faster.

America’s electrical grid needs a power-up, too. The U.S. Department of Energy’s (DOE) new national grid energy research facility at Pacific Northwest National Laboratory (PNNL) was awarded a multi-million dollar commitment from DOE to update the grid, and a major portion of that funding will be funneled into new battery technologies.

PNNL associate lab director Jud Virden tells Forbes’ James Conca that lithium-ion batteries took 40 years of development to get to what we have now. But as Conca writes: “We don’t have 40 years to get to the next level. We need to do it in 10.”

Mainstream Medicine Gets Trippy

The 2010s saw 18 states approve the use of marijuana for medical purposes, bringing the total to 33 states . In the 2020s, research into the potential medicinal uses of psychedelics could increase dramatically.

John Hopkins Medicine in 2019 launched the Center for Psychedelic and Consciousness Research to study the use of psychedelics and “identify therapies for diseases such as addiction, PTSD, and Alzheimer's,” according to a statement . So far, the university has primarily investigated how psilocybin—the chemical in “magic mushrooms”—can be applied in low doses as a therapeutic treatment method for a swath of conditions, including nicotine addiction, major depressive disorder and anxiety. Scientists are now considering whether psilocybin could ease the pain of life-threatening conditions such as cancer.

In another recent example, one researcher found that MDMA, or ecstasy, can make the characteristically shy octopus act friendlier . Though cephalopod brains are more similar to snails than to humans, scientists gleaned insights about how neurons and neurotransmitters behave on the drug that could inform future studies in humans. Other researchers doing experiments with mice hope MDMA ability to manipulate oxytocin could benefit people suffering PTSD.

A form of ketamine that causes dissociative hallucinations is used as a party drug, but in the medical field, the drug is commonly used as a medical anesthetic. Now, scientists are studying its efficacy for cases of hard-to-treat depression. Last year, the Food and Drug Administration approved a nasal-spray form of ketamine for severe cases of depression. (But beware pop-up “clinics” that are overhyping its usefulness in improper applications, according to a Stat investigation .)

Facing ‘Apocalyptic’ Species Decline

Insects , amphibians , birds and creatures of every stripe are in serious decline because of a cocktail of threats, primarily habitat destruction, pollution and climate change. The United Nations has set the end of the 2020s as the deadline for serious measures to save these populations.

Big-picture commitments to protect habitats, reduce carbon emissions, eliminate plastic waste, and curb pesticide use are needed. In addition, scientists are getting creative about studying and protecting species. Tech giants like Google are helping, too. Through passive tracking devices like camera traps, researchers can collect spatial and temporal data that inform conservation efforts. Collectively, these traps will accumulate millions of images, but sorting that immense well of data has been a longstanding problem for researchers.

Projects like Wildlife Insights , which is sponsored in part by Google and Smithsonian Institution, are using cloud technology and artificial intelligence to identify animals in images at the species level so scientists can map a population’s range more easily. Elsewhere, startups like Conservation X are pooling money to create devices like portable DNA scanners to help officials identify illegally traded items like rhino horns or pangolin scales, reports Lisa Palmer for Nature . The group also funded a program called ChimpFace , which uses facial-recognition software to combat illegal chimpanzee trafficking online by training an algorithm on thousands of images of chimps.

On the ground, one team of researchers in New Zealand is using a suite of tech to recover the endangered kākāpō bird. They pilot drones to move semen samples for breeding across the island quickly; advanced microsatellite DNA tests are used to prevent inbreeding; and they’ve even 3D-printed eggs to assist incubation. Several teams are using satellites in space to track populations of whales , wombats and penguins .

Food to Feed the Planet

By some estimates, the planet will need to generate more food in the next 35 years than has ever been produced in human history—an ask that will unquestionably strain agricultural resources.

Though genetically modified crops have been around in some form or another for millennia, engineered plants are poised to make a splash in the next decade. Altered staples like golden rice—a variant of white rice engineered to combat vitamin A deficiency —might be on their way to distribution before we hit the 2030s. Also in development are heat-resistant crops that will, in theory, fare better than their counterparts as Earth’s temperature ticks upward.

These biotechnological fixes have their critics. Genetically modified plants come with risks, as they can transfer genes to other organisms in their ecosystems, according to National Geographic . Skeptics also point out their relative impracticality: By the time GMOs clear the regulatory hurdles and reach the populations most in need, the aid could be too late .

Instead, experts recommend pouring resources into developing more sustainable agricultural practices that can bolster land management and even out food distribution. Calorically speaking, the planet already produces enough food to keep all its residents fed—something that won’t be fixed by focusing on production alone, according to the Verge . Researchers are also prioritizing technology that might minimize food waste, or reduce the world’s dependence on foods that carry big carbon footprints, like meat and dairy.

Really, Really Intelligent Machines

We’re in the midst of a digital revolution. Computers, programmed to “think” for themselves, can now beat people at games , forecast the weather and even diagnose medical abnormalities better than some doctors. What artificial intelligence will attempt and conquer next is hard to guess, but a few companies have already lined up some potentially heavy hitters for the next ten years. One prominent example is Google, which made headlines earlier this year for a breast cancer diagnostic technology and has announced plans to roll out more of the same for other health-related conditions .

Another buzzworthy topic involves facial recognition, brought to the fore last month when the New York Times published an exposé on a startup gunning to make facial recognition a fixture of law enforcement agencies. Many of these advances have been made possible by so-called neural networks —a form of machine learning modeled after the connectivity of the human brain that have become excellent at picking hidden patterns out of massive datasets, like medical records or photos of people.

The 2020s will bring more than technical advancements: Experts are now pushing for the world to grapple with the legal, social and ethical implications of artificial intelligence. Machines mining personal data raise issues of privacy. Increasingly “conscious” algorithms evoke difficult questions of personhood, and whether computers will ever reach the point of deserving their own rights . Even the best-intentioned programs are prone to problems: Artificial intelligence can’t (yet) tell when people give them incorrect or biased data, and has the potential amplify human errors in medicine , in some cases spitting out discriminatory results .

Solving the Plastics Problem

In the past 70 years, humans have produced more than 8 billion tons of plastic —and most of it is still around today, wreaking havoc on the environment and compromising human health. To move beyond simply reusing and recycling, researchers and policymakers alike are turning to alternative technologies and regulations.

Companies are developing substitutes for plastic based on materials such as flax fibers , mushrooms and shrimp shells . Others are attempting to modify existing plastic formulations to make them more degradable , according to the United Nations . In dire need of an upgrade is recycling technology itself: Only about nine percent of the world’s plastic is recycled, according to the Economist . One big issue is contamination, which sends about 25 percent of the stuff we try to recycle to the landfill.

Even the simplest of inventions can take years to hit the market. In the meantime, countries around the world are instituting single-use plastic bans, with several already in place in members of the European Union, China and New Zealand, among others, according to Fortune . Similar legislation is gaining traction in the United States, albeit on a state-by-state basis .

Progress in Global Public Health

Infectious diseases, including many that are treatable, remain the leading cause of death in low-income countries, due in large part to poor and inconsistent access to healthcare resources. To streamline diagnostics and treatments, researchers are increasingly turning to easy-to-use devices—some of which offer simplified proxies for clinics or human professionals.

At the University of California, Berkeley, scientists have developed cell phone apps that can spot pathogens in biologic samples. The World Health Organization has increased funding to initiatives working to scale up vaccine production in disease-afflicted countries. Artificial intelligence is also starting to make a big splash in the infectious disease arena as computer scientists deploy the technology to predict—and hopefully temper—outbreaks that originate in animals.

In the 2020s the world might finally eradicate Guinea worm —a parasitic disease that researchers have been battling for decades. The annual count of new infections dropped to just 28 in 2018—down from 3.5 million in the 1980s. Recent efforts to fully stamp out the disease have plateaued, due in part to the parasite’s frustrating tendency to hide out in dogs, according to Nature News . But if the World Health Organization meets its goal of officially purging the globe of Guinea worm by 2030, the parasite would become the second pathogen eradicated in human history, after smallpox.

A Bright Future for Solar Energy

Due in large part to human-driven climate change, the 2010s were the hottest decade on record . Without a serious drop in carbon emissions, the next ten years are likely to bring the world another wave of record temperatures, imperiling natural ecosystems and human societies around the world.

Global consumption of coal has begun to plateau as world powers switch to clean energy alternatives. According to the New York Times , experts predict that wind, solar and hydropower will surpass coal as the world’s dominant source of electricity by 2030. Solar power in particular shines with potential, as the price tag for harvesting the sun’s energy continues to drop for commercial and residential rooftops alike. If solar expansion predictions pan out, the sun’s energy will drive about one-fifth of the United States’ electricity generation by the start of the 2030s, according to Forbes .

But an expanded clean energy market doesn’t guarantee a cut in carbon emissions—especially one substantial enough to save the planet from a disastrous uptick in temperature . Renewables like wind and solar still make up a small fraction of the total power sector, and the world’s electricity needs are only growing. As James Temple writes for MIT Technology Review , repeating the advances made in the 2010s won’t be enough. What’s needed now is an acceleration in the pace of energy breakthroughs while there’s still time to make a difference.

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Katherine J. Wu | | READ MORE

Katherine J. Wu is a Boston-based science journalist and Story Collider senior producer whose work has appeared in National Geographic , Undark magazine, Popular Science and more. She holds a Ph.D. in Microbiology and Immunobiology from Harvard University, and was Smithsonian magazine's 2018 AAAS Mass Media Fellow.

Rachael Lallensack | READ MORE

Rachael Lallensack is the former assistant web editor for science and innovation at Smithsonian .

38 Scientists Helping Chart the Future of Biomedical Research

Pew’s 2022 scholars and fellows selected to explore the intricacies of health and medicine.

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Biomedical researchers are at the forefront of scientific innovation, seeking answers to the world’s most pressing questions in human health. For 37 years, The Pew Charitable Trusts has encouraged these pursuits by supporting promising, early-career biomedical scientists tackling these challenges and driving medical breakthroughs.

This year, a total of 38 researchers join the Pew Scholars Program in the Biomedical Sciences ,  Pew Latin American Fellows Program in the Biomedical Sciences , and Pew-Stewart Scholars Program for Cancer Research . They will receive multiyear grants to pursue scientific interests in the United States and Latin America at a time when biomedical science has never been more critical.

Infectious disease prevention and treatment

The COVID-19 pandemic put a spotlight on the immune system in the fight against infectious diseases.

Several members of the 2022 class are studying the intricacies of this essential defense mechanism. One scientist will explore how bacterial exposure changes the body’s circadian rhythm—the cellular clock regulating activities such as sleeping and eating—and influences immune system function, particularly in how the body fights infections. Another will investigate how parents pass on disease-fighting knowledge to their children through what is known as “immune memory,” a process that can enhance their offsprings’ responses when exposed to the same pathogen. And another scientist will study how structural changes in cell surface molecules drive white blood cells to curb infections.

A separate group will investigate how to prevent and treat certain diseases. One scientist will study how immune cells respond to viral hemorrhagic fevers, while another will examine how Ebola enters host cells. Others will explore a new, promising class of antibiotics that targets the production of essential bacterial proteins, as well as a potential “universal vaccine” for rapidly mutating viruses such as HIV, SARS-CoV-2, and influenza.

Wonders of the brain

From walking and talking to sleeping and socializing, the brain is critical to the human body’s most essential tasks. But much is still unknown about how this complex organ coordinates with other bodily systems.

Scientists in this year’s class will explore how the brain and gut work together to ensure that the body has needed nutrition, and also which neurological processes are at play when individuals experience physical pain. One researcher will use schooling fish to explore how the brain processes visual information to inform movement, while another will seek to determine how neurons detect pheromones to decipher social engagement cues.

Because the brain controls functions from learning and memory to social behaviors, disturbances to the neural system can cause dire consequences. Some scientists will investigate mechanisms that contribute to neuronal dysfunction and potential strategies to keep this from occurring. For example, one researcher will explore how memory-encoding cells that are activated by negative experiences affect the development of Alzheimer’s disease. Another will examine how mutations in enzymes involved in protein clearance disrupt neuronal function and survival.

Decoding cancer development

Cancers develop when abnormal cells proliferate uncontrollably and spread throughout the body unchecked. The 2022 class is studying different elements of this complex disease—exploring mechanisms that drive cancer initiation and novel strategies to control its progression.

Cancer cells are highly reliant on the metabolic process for the energy they need to grow and spread. One researcher will examine the dependence of cancer cells on the lysosome—a specialized cellular structure—to fuel their demand for nutrients. Another will build a novel system to study how cancer cells adapt to new metabolic pathways to evade therapy. And one is looking at the compounds produced in the breakdown of nutrients used by acute lymphoblastic leukemia cells for clues about how treatment resistance mechanisms arise.

Researchers also are studying different aspects of the immune system response to cancer. One class member is examining how sensory neurons regulate an immune response to lung cancer, while another is investigating the effect a new immunotherapy has on T-cells and their ability to attack skin cancer.

Finally, a group will explore the role of genetic variations in cancer. Members of the 2022 class will study how mutations in a cell receptor that binds sugars contributes to the formation of aggressive cancers and also how accumulation of mutations promotes the risk for blood cancer development. Another researcher will look at how genetic variation can help protect us from cancer—using wolves in the Chernobyl Exclusion Zone, surrounding the failed nuclear power plant, as a novel case study.

Unraveling the human genome

The genome is a tightly packed set of instructions that determines everything from peoples’ physical traits to their behavioral tendencies. Careful regulation is needed to maintain the integrity of our genetic material and prevent a myriad of human diseases.

Members of the 2022 class are studying mechanisms that regulate proper gene expression. One will examine how DNA structural rearrangements are coordinated, while another will study how some novel and overlooked structures within the genome contribute to the maintenance of our genetic code. And one researcher will examine specialized genome sequences to understand how variations of gene products arise.

Researchers are also investigating the cellular machines that help accurately distribute and separate chromosomes during cell division, as well as how these specialized complexes ensure that DNA in the mitochondria—the powerhouses of the cell—is replicated with fidelity. Finally, some scientists are studying how disruptions or defects in proteins that help safeguard and maintain the genome contribute to the development of blood and bone cancers. 

Intestinal health and disease

The gut is home to trillions of bacteria, viruses, and fungi that coexist in a community, also known as the microbiome. Some components of the microbiome are present at birth, but exposure to environmental elements and diet as we age diversifies the makeup of this community.

One class member will explore how different lipids in human milk are processed by gut bacteria to promote health in babies. Another will examine how early antibiotic exposure can disrupt the composition of the microbiome and how these changes may contribute to weight gain later in life.

Gut health can be influenced by other factors as well. A member of the class will explore how brain signals may impact intestinal inflammation. Another scientist will investigate how factors such as age can alter nutrient transport by intestinal cells and lead to the development of metabolic and intestinal disturbances in the elderly.

Kara Coleman is the project director and Jennifer Villa is an officer with The Pew Charitable Trusts’ biomedical programs.

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Beyond Passion and Perseverance: Review and Future Research Initiatives on the Science of Grit

Grit, which is originally conceptualized as passion and perseverance for long-term goals, has been associated with optimal performance. Although previous meta-analytic and systematic reviews summarized how grit relates to performance outcomes, they possess considerable shortcomings, such as (a) absence of summary on the association of grit with well-being outcomes; (b) absence of discussion on social, psychological, and emotional mechanisms linking grit to well-being; and (c) lack of elaboration on how alternative models can resolve fundamental problems in the grit construct. This integrative review provides a comprehensive summary on the link of grit to performance and well-being outcomes. Importantly, it elaborates how alternative models can potentially address flaws in the existing grit theory. Future research directions are discussed on how to move forward the science of grit.

Psychological scientists have recognized the importance of exploring non-cognitive predictors of success in work, school, and other domains of life (Robbins et al., 2006 ; Duckworth and Yeager, 2015 ). One of the non-cognitive constructs gaining considerable attention in the existing literature is grit (Duckworth et al., 2007 ). Grit was originally defined as one's disposition to demonstrate perseverance and passion for long-term goals (Duckworth et al., 2007 , p. 1087). Earlier studies have pointed out that grit was a higher-order construct composed of consistency of interests (ability to stick to a similar set of interests over time) and perseverance of effort (tendency to show diligence despite challenges or difficulties associated with pursuing a long-term goal), which could predict variety of positive performance outcomes including success in school, spelling quiz bee competition, and work among others (Duckworth et al., 2007 ; Duckworth and Quinn, 2009 ; Eskreis-Winkler et al., 2014 ).

There has been accumulating body of empirical evidences demonstrating the power of grit in predicting useful outcomes, success at school (Duckworth et al., 2007 ; Eskreis-Winkler et al., 2014 ; Strayhorn, 2014 ), positive organizational behaviors (Suzuki et al., 2015 ; Ceschi et al., 2016 ), and well-being (Vainio and Daukantaite, 2016 ; Li et al., 2018b ; Datu et al., 2019 ). Moreover, Lee and Duckworth ( 2018 ) have accentuated the promising institutional benefits of “gritty” organizations.

Despite the growing interest on the role of grit in fostering success and well-being, a recent meta-analytic evidence has casted serious doubts regarding the theoretical validity of the originally theorized two-factor model of grit (Credé et al., 2017 ). The result of the authors' meta-analysis has shown that compared to consistency of interests, perseverance of effort is a stronger predictor of performance outcomes. Furthermore, the correlation of grit to academic achievement was not comparable to other known predictors of academic success. Studies have demonstrated that whereas perseverance was associated with various indicators of positive student functioning (i.e., academic adjustment and engagement), consistency was not significantly correlated with such outcomes (Bowman et al., 2015 ; Datu et al., 2016 ). The authors have also pointed out that the “primary utility of the grit construct may lie in the perseverance facet” (p. 113). Moreover, another review (Datu et al., 2017b ) has pointed out possible cultural biases in the original grit framework. Indeed, more effort is needed to resolve empirical threats to the science of grit.

Although existing reviews on grit (Credé et al., 2017 ; Datu et al., 2017b ; Credé, 2018 ; Lam and Zhou, 2019 ; Fernández et al., 2020 ) have provided comprehensive, detailed, and nuanced review on how grit tracks performance and other positive psychological outcomes, they have a number of considerable shortcomings. As these meta-analytic (Credé et al., 2017 ) and systematic (Datu et al., 2017b ; Lam and Zhou, 2019 ; Fernández et al., 2020 ) reviews primarily focused on summarizing the association between grit and domain-specific performance (e.g., achievement in school contexts), conclusions have myopic implications for understanding the role of grit in optimizing other equally important outcomes, such as psychological well-being and physical health. Moreover, previous reviews have paid little attention to summarizing studies on psychological processes underpinning the complex link of grit to a wide range of outcomes. Most importantly, whereas these reviews have pinpointed fundamental theoretical flaws in the theorizing of grit, they failed to discuss alternative models that can potentially address such conceptual and measurement issues.

Therefore, this integrative review aims to provide a comprehensive summary regarding the measurement, correlates, and alternative models of the grit construct through answering these overarching questions: (1) What's wrong with the existing grit theory? (2) What are alternative theoretical models on grit? and (3) how can these alternative grit frameworks address fundamental flaws in the original grit theory? This article addresses such questions via (a) defining the grit construct; (b) summarizing literature on how grit is linked to adaptive performance, psychological, and physical outcomes as well as neural bases of grit; (c) providing a summary about the predictors of grit and its dimensions; (d) discussing theoretical flaws of the extant grit theory; (e) describing the caveats of continuously incorporating consistency of interests as a dimension of grit; (f) elaborating alternative conceptualization of grit, such as triarchic model of grit (Datu et al., 2017a , 2018a ) and refined conceptualization of passion (Jachimowicz et al., 2018 ); and (g) elucidating how theoretical refinement of grit can potentially address its major conceptual shortcomings. Future research agenda and initiatives are elaborated.

What is Grit?

Grit was operationalized as trait-level passion and perseverance for long-term aspirations (Duckworth et al., 2007 ). Specifically, Duckworth et al. ( 2007 ) conceptualized grit as a hierarchical construct underpinned by two interrelated dimensions, namely, consistency of interests and perseverance of effort. Consistency of interests entails constantly showing interest and efforts, whereas perseverance of effort involves demonstrating heightened intensity of persistence even after experiencing concrete setbacks or failures. The authors argued that grit was conceptually distinct from theoretically relevant constructs, such as conscientiousness and resilience. This multiphasic research has revealed that grit was associated with higher levels of educational attainment among adult participants in an online website, academic performance in undergraduate students, fulfillment of military training in a sample of freshmen cadets who enrolled in the US Military Academy, and advancement to more challenging stages of a national spelling quiz bee contest. Furthermore, grit accounts for ~1.4–6.3% of the variances in successful outcomes.

For the past several years, studies continued to adopt a trait-level conceptualization of grit emphasizing the relative stability of this construct regardless of situational conditions (Duckworth and Eskreis-Winkler, 2015 ). Even the existing measures on grit, such as the 12-item Original Grit Scale (Duckworth et al., 2007 ) and 8-item Short Grit Scale (Duckworth and Quinn, 2009 ) focused on assessing grit as an individual difference construct. Yet, although some studies have provided evidence about the incremental validity of grit over and beyond the effects of known predictors (i.e., conscientiousness and self-control) of achievement-related outcomes (Duckworth et al., 2007 ; Li et al., 2018c ), there have been serious concerns on the psychometric validity of such grit scales (see Credé et al., 2017 and Datu et al., 2017b for reviews); more research is needed to understand the complex nature of grit.

Grit is also different from relevant psychological constructs (i.e., conscientiousness, need for achievement, and self-control). For instance, whereas conscientiousness is a Big Five personality trait characterized by diligence, achievement–orientation, and diligence (Soto et al., 2016 ), grit involves consistently working on a specific interest or endeavor and persisting over difficult tasks over a long period of time. In addition, while need for achievement (McClelland, 1961 ) involves strenuously spending effort and time on potentially “rewarding” activities, grit may not necessarily require incentives and feedback to boost desire for accomplishing long-term goals. Existing literature has also pointed out that grit was essentially distinct from self-control because the former appears to be more applicable to highly demanding contexts or situations, whereas the latter is more fitting for commonly faced day-to-day challenges (Duckworth and Gross, 2014 ; Eskreis-Winkler et al., 2016 ).

Performance, Psychological, and Physical Benefits of Grit

There has been a steady inflation in the number of studies documenting the advantageous role of grit in facilitating success and well-being outcomes. This section summarizes previous research on how grit and its dimensions relate to various indicators of optimal performance, psychological well-being, and physical health.

Grit and Academic Outcomes

There has been a considerable body of literature showing how grit may relate to school-related performance and behaviors. Gritty students are more likely to have higher levels of general academic achievement among university students in the United States (Duckworth et al., 2007 ; Duckworth and Quinn, 2009 ; Akos and Kretchmar, 2017 ); high school students in mainland China (Li et al., 2018c ), secondary education students in the United States (Cosgrove et al., 2018 ; Park et al., 2018 ), Germany (Schmidt et al., 2019 ), Austria (Dumfart and Neubauer, 2016 ), and Russia (Tovar-García, 2017 ); course-specific academic achievement among military cadet samples in the United States (Mayer and Skimmyhorn, 2017 ); literacy achievement among primary school students (O'Neal et al., 2018 ); academic achievement in science in secondary school students in Australia (Hagger and Hamilton, 2019 ); performance in a national spelling bee contest (Duckworth et al., 2010 ); retention in selected undergraduate students in the United States (Saunders-Scott et al., 2018 ); academic engagement in selected university and high school students in the Philippines (Datu et al., 2016 , 2018b ); academic self-efficacy among university students in the Philippines (Datu et al., 2017a ) and the United States (Renshaw and Bolognino, 2016 ); generalized self-efficacy (Renshaw and Bolognino, 2016 ); intellectual self-concept among selected twin sample in the United States (Tucker-Drob et al., 2016 ); emotional engagement among dual language learners in the United States (O'Neal et al., 2018 ); school-related motivation among Filipino, American, and Mexican American students (Eskreis-Winkler et al., 2014 ; Yeager et al., 2014 ; Piña-Watson et al., 2015 ; Datu et al., 2018b ); learning engagement in selected mainland Chinese adolescents (Lan and Moscardino, 2019 ); test motivation among twins in the United States (Tucker-Drob et al., 2016 ); deliberate practice in optional and required practice in specific sports domains among selected athletes mostly from the North American context (Tedesqui and Young, 2017 ); satisfaction with e-learning systems among university students in Portugal (Aparicio et al., 2017 ); college satisfaction (Bowman et al., 2015 ); leadership skills among military cadets (Mayer and Skimmyhorn, 2017 ); mastery orientation (Tucker-Drob et al., 2016 ); meaningfulness of academic activities (Yeager et al., 2014 ); and growth mindset (Tucker-Drob et al., 2016 ). Furthermore, domain-specific grit in the school context is linked to elevated levels of academic performance among high school students in Germany (Schmidt et al., 2019 ) and middle school students in the United States (Clark and Malecki, 2019 ).

Grit and Career Outcomes

Grit is associated with elevated levels of retention and teaching effectiveness among selected teachers in the United States (Robertson-Kraft and Duckworth, 2014 ) and career exploration self-efficacy in Filipino university students (Datu et al., 2017a ), as well as fewer changes in career (Duckworth et al., 2007 ). Both perseverance and consistency are linked to higher work performance incentives in selected Chinese insurance employees (Zhong et al., 2018 ). In the context of selected cadets in the Corps, both perseverance and consistency were not associated with decision to become officers in the US Military institute (Jordan et al., 2015 ). In the case of surgical residents in the United States, grit has been found to be a key risk factor for attrition in the residency program (Burkhart et al., 2014 ). Also, residents whose scores fell below the median value are likely to report dissatisfaction with their residency programs.

Grit and Work-Related Functioning

Gritty adults are more likely to demonstrate higher venture or business performance among entrepreneurs in the United States (Mueller et al., 2017 ), work engagement in Japanese adults (Suzuki et al., 2015 ), and positive leadership behaviors (Caza and Posner, 2019 ), as well as sports-related engagement in a sample of wheelchair basketball athletes in the United States (Martin et al., 2015 ) and selected male soccer athletes in Australia (Larkin et al., 2015 ). Conversely, grittier employees are less likely to experience work burnout and engage in counterproductive work behaviors (Ceschi et al., 2016 ). In a sample of surgical trainees in England, grit is related to lower levels of work burnout (Walker et al., 2016 ).

Grit, Well-Being, and Positive Psychological Outcomes

Researchers have offered evidence on the well-being benefits of grittiness in diverse contexts. Grit is linked to higher levels of life satisfaction among undergraduate students in the United States (Renshaw and Bolognino, 2016 ); adults in Switzerland (Samson et al., 2011 ); selected male adults in the United States (Hammer and Good, 2010 ); employees in mainland China (Li et al., 2018a ); university and post-graduate students in Sweden (Vainio and Daukantaite, 2016 ), as well as adults in South Korea (Jin and Kim, 2017 ); meaning in life among university students in the United States (Kleiman et al., 2013 ); psychological well-being among selected surgical residents in the United States (Salles et al., 2014 ) and student populations in Sweden (Vainio and Daukantaite, 2016 ); adolescent well-being in Australian and American youth samples (Kern et al., 2016 ); self-esteem (Hammer and Good, 2010 ) and optimism and mental health in selected US military recruits (Lovering et al., 2015 ); well-being in a sample of undergraduate and post-graduate students in England (Kannangara et al., 2018 ); money-conserving actions among US university students (Maddi et al., 2013 ); gratitude in selected Swiss adults (Samson et al., 2011 ) and Filipino high school students (Valdez and Datu, 2020 ); sense of coherence (Vainio and Daukantaite, 2016 ); subjective happiness (Samson et al., 2011 ); action-oriented tendencies of Romanian adult sample (Constantin et al., 2011 ); and harmony in life (Vainio and Daukantaite, 2016 ). Also, grit positively predicts prosocial behaviors in older adults in the United States (Wenner and Randall, 2016 ), as well as good habits in selected US university students (Feldman and Freitas, 2016 ). Domain-specific grit (i.e., academic grit) is linked to life satisfaction and school satisfaction among middle school students in the United States (Clark and Malecki, 2019 ). Moreover, analysis of data involving Western (e.g., United States, England, Russia, and Canada) and non-Western societies (e.g., Mexico, Malaysia, and China) shows that grit is positively correlated with both hedonic and eudemonic well-being (Disabato et al., 2016 ).

Individuals' passion and perseverance for long-term goals are also associated with various types of orientations to happiness (i.e., orientation toward pleasure, meaning, and engagement). Whereas, grit is positively correlated with orientations toward engagement and meaning among adults in the United States (Von Culin et al., 2014 ) and Japan (Suzuki et al., 2015 ), this construct is linked to lower levels of orientations to pleasure. These results indicate that grit may be linked to different types of orientations to happiness in Western and non-Western contexts.

Moreover, grit is associated with lower depression among undergraduate students in the United States (Anestis and Selby, 2015 ), adults in South Korea (Jin and Kim, 2017 ), military recruits in the United States (Lovering et al., 2015 ), and undergraduate students in Thailand (Musumari et al., 2018 ), as well as selected high school students in the Philippines (Datu et al., 2019 ); decreased levels of perceived stress in selected university and post-graduate students in England (Kannangara et al., 2018 ) and United States (Saunders-Scott et al., 2018 ); reduced chances of using alcohol and marijuana among Latino adolescents (Guerrero et al., 2016 ); decreased levels of anxiety (Musumari et al., 2018 ); lessened fear of being laughed at or gelatophobia (Samson et al., 2011 ); reduced anxiety sensitivity among young adults in the United States (Moshier et al., 2016 ); and lower suicidal ideation among US undergraduate students (Kleiman et al., 2013 ; White et al., 2017 ). Students with higher grit are also less likely to engage in problematic use of internet, as well as compulsive buying and gambling behaviors (Maddi et al., 2013 ).

Neural Correlates of Grit

Prior studies have generated findings that have implications for understanding the neurobiological bases of grit. Drawing from functional magnetic resonance imaging approaches, one of the important regions in the brain that has been linked to grit is the medial prefrontal cortex (Myers et al., 2016 ; Wang et al., 2017 ). Specifically, neural connections in the medial prefrontal and rostral anterior cingulate cortices were associated with increased perseverance (Myers et al., 2016 ). There was also a negative correlation between grit and regional fractional amplitude of low-frequency fluctuations, which has been implicated for setting goals, implementing plans, self-control, and capacity to adaptively interpret setbacks. Using a voxel-based morphometric design, Wang et al. ( 2018 ) have shown that regional gray matter volume in the right putamen is linked to increased levels of grit. In addition, an event-related potential study has demonstrated that undergraduate students with higher scores on perseverance of effort subscale tend to have lower reaction times in the Attention Network Task and lower mean difference in N1 amplitudes (Kalia et al., 2018 ), which suggest positive correlations between grit and task-related attention. Vlasova et al. ( 2018 ) have also revealed that “structural integrity in white matter pathways,” which was commonly implicated for emotion regulation and resilience, was positively correlated with grit among depressed adults.

Moderation Studies on Grit on Maladaptive Functioning

Another promising line of evidence on grit alludes to the buffering role of grit. For instance, a synergistic interplay between grit and gratitude diminishes suicidal ideation through boosting meaning in life in selected US undergraduate students (Kleiman et al., 2013 ). Also, grit moderates the association of negative life events on suicidal ideation such that for students who scored lower in grit, negative events can promote suicidal ideation among undergraduate students in the United States (Blalock et al., 2015 ). Yet, little is known on whether long-term exposure to undesirable environmental conditions or events can dampen the protective role of grit on well-being outcomes. In addition, rumination heightened suicidal ideation for undergraduate students who had lower scores on grit (White et al., 2017 ).

Grit also serves as a protective factor against the psychological hazards (i.e., suicidal ideation) of hopelessness in selected US military personnel (Pennings et al., 2015 ). Furthermore, in situations where students do not have positive relationships with teachers, demonstrating grit is linked to elevated levels of school engagement and satisfaction with school (Lan and Moscardino, 2019 ). Lastly, for individuals with average and low scores on expressive suppression (an emotion regulation strategy that involves intentionally hiding or reducing one's emotional states; Gross and Levenson, 1997 ), showing elevated levels of consistency of interests may not result in maladaptive eating attitude and actions (Knauft et al., 2019 ).

Grit and Physical Health

Contemporary investigations have also explored the link of grit to various indices of optimal physical health. Research suggests that grittier individuals are more likely to have a habitual exercise routine (Reed et al., 2013 ) and decreased chances of experiencing food insecurity (Nikolaus et al., 2019 ). In the case of adolescents and young adults who are facing long-term medical illnesses, grit is linked to lower levels of depression and anxiety, as well as emotional well-being (Sharkey et al., 2017 ). Composite grit scores are also negatively correlated with deficits in executive functioning, cognitive failures, and symptom severity among selected diagnosed undergraduate students with attention-deficit/hyperactivity disorder (ADHD) in Canada (Gray et al., 2015 ). Similarly, demonstrating increased perseverance of effort is associated with optimal neurocognitive functioning in a sample of people living with human immunodeficiency virus in the United States (Moore et al., 2018 ).

Although results from previous studies generally suggest that overall grit can facilitate success and well-being in various domains of functioning, it may be challenging to delineate what aspects of grittiness may promote desirable outcomes. In the succeeding section, I summarized studies demonstrating how each dimension of grit differentially relates to various domains of optimal performance, psychological health, and physical well-being.

Grit Dimensions as Differential Predictors of Optimal Functioning

Previous research has offered robust evidence on the importance of perseverance of effort in fostering positive performance, psychological, and well-being outcomes. Perseverance is associated with higher levels of academic achievement among undergraduate students in the United States (Chang, 2014 ; Wolters and Hussain, 2015 ; Muenks et al., 2017 ), adolescent twins in the United Kingdom (Rimfeld et al., 2016 ), secondary school students in Germany (Steinmayr et al., 2018 ), adolescent students in Finland (Tang et al., 2019 ), associate degree students in Hong Kong (Lee, 2017 ), and selected high school students (Li et al., 2018c ) and primary school students (Jiang et al., 2019 ) in mainland China; subjective academic performance in selected undergraduate students in Australia (Hodge et al., 2018 ); academic adjustment in the United States (Bowman et al., 2015 ); academic self-efficacy in US university students (Wolters and Hussain, 2015 ) and Filipino undergraduate students (Datu et al., 2017a ); all achievement goal orientations (i.e., mastery–approach, mastery–avoidance, performance–approach, and performance–avoidance goals) among selected university students in the United States and mainland China (Chen et al., 2018 ); generalized self-efficacy in a sample of selected cadets in the United States (Jordan et al., 2015 ); entrepreneurial success in selected entrepreneurs in Australia (Mooradian et al., 2016 ); and academic self-regulation strategies, such as cognitive, metacognitive, motivational, and time and environment strategies among undergraduate students in the United States (Wolters and Hussain, 2015 ). This dimension of grit is also linked to higher levels of job satisfaction in a sample of employed students in the United States (Meriac et al., 2015 ), orientations to engagement among Japanese adults (Suzuki et al., 2015 ), general self-esteem among university students in the United States (Weisskirch, 2018 ), and mindfulness in selected Thai and New Zealand university students (Raphiphatthana et al., 2019 ). In a sample of adults in the United States, compared to consistency of interests, which is associated with weaker indications of sympathetic activity, perseverance of effort is related to increased activation of autonomic nervous system (Silvia et al., 2013 ).

Consistent with the arguments on the performance and well-being benefits of perseverance, studies show that this facet of grit is negatively correlated with turnover intentions (Meriac et al., 2015 ), academic maladjustment (Hwang et al., 2018 ), perceived stress (Meriac et al., 2015 ; Lee, 2017 ; Mullen and Crowe, 2018 ; Zhong et al., 2018 ), burnout (Mullen and Crowe, 2018 ; Zhong et al., 2018 ), and academic procrastination among selected undergraduate students in Italy (Pierro et al., 2011 ). School-specific perseverance is also positively correlated with academic achievement (Schmidt et al., 2019 ).

On the other hand, research indicates that consistency of interests is not related to academic performance (Chang, 2014 ; Wolters and Hussain, 2015 ; Rimfeld et al., 2016 ; Lee, 2017 ; Hodge et al., 2018 ; Jiang et al., 2019 ; Tang et al., 2019 ), academic maladjustment (Hwang et al., 2018 ), most academic self-regulation approaches except time and environment management strategies (Wolters and Hussain, 2015 ), job satisfaction (Meriac et al., 2015 ), and turnover intent (Meriac et al., 2015 ). Few researches provide insights regarding the benefits of consistency by showing how this facet of grit may be linked to higher academic performance (Li et al., 2018c ), elevated self-esteem and adaptive learning strategies (Weisskirch, 2018 ), lower likelihood of shifting to another major or vocational tracks (Bowman et al., 2015 ), reduced performance–avoidance goals (Chen et al., 2018 ), decreased bulimia and body satisfaction among selected adults from eating disorder treatment facilities (Knauft et al., 2019 ), reduced perceived stress (Meriac et al., 2015 ; Lee, 2017 ; Mullen and Crowe, 2018 ), decreased levels of academic procrastination (Pierro et al., 2011 ), and lower levels of burnout (Mullen and Crowe, 2018 ; Zhong et al., 2018 ).

Why Does Grit Predict Positive Outcomes?

As grit and its dimensions have linked to increased achievement in various domains of performance and well-being, past studies have identified precise mechanisms underscoring the positive impacts of grit on desirable outcomes. Based on the results from previous investigations, this review proposes the optimal performance and health (OPAH) model of grit ( Figure 1 ), which summarizes processes involved in the anticipated benefits of grittiness, as well as intrinsic (i.e., personality) and extrinsic (e.g., life events) factors that moderate the link of grit to positive outcomes.

The optimal performance and health (OPAH) model of grit.

The first path of the diagram demonstrates why grit can optimize elevated levels of achievement in specific domains of performance. It is likely that persevering for long-term goals can predict achievement because existing studies have shown actual effort invested in specific activities mediated the link of grit to positive academic outcomes (Duckworth et al., 2010 ; Hagger and Hamilton, 2019 ). Grittier students, for instance, advanced to more complicated rounds in a national spelling bee because they have spent more effort and time in keenly preparing for the said competition (Duckworth et al., 2010 ). In the same way, the capacity of perseverance to boost effort in accomplishing science-related tasks explains why this facet of grit predicts increased achievement in Science (Hagger and Hamilton, 2019 ). Moreover, perseverance is related to increased time and environment management academic regulation strategies (Wolters and Hussain, 2015 ) and active participation in school-related tasks (Datu et al., 2016 ). Thus, “behavioral effort” is operationalized as one the psychological processes underpinning the effects of grit on achievement outcomes.

Moreover, results from past studies point to the role that “adaptive motivation” plays in grit–success relationship. This type of process variable encompasses one's drive or desire to achieve optimal levels of performance. Corroborating this perspective, grit is positively linked to mastery–approach goals, mastery–avoidance goals, performance–approach goals, and performance–avoidance in selected undergraduate students in the United States and mainland China (Chen et al., 2018 ), as well as autonomous motivation among Filipino high school students (Datu et al., 2018b ). Research also demonstrates that autonomous motivation mediates the positive associations of grit with agentic, behavioral, cognitive, and emotional engagement (Datu et al., 2018b ).

“Cognitive resourcefulness” characterizes another type of variable serving as a mechanism that explains why grit may be linked to appealing performance outcomes. It covers any construct that necessitates usage of cognitive resources to successfully accomplish a wide range of tasks in various settings. For instance, research shows that perseverance is linked to increased entrepreneurial success due to the mediating role of innovativeness (Mooradian et al., 2016 ). In addition, perseverance of effort is related to higher levels of cognitive and metacognitive study strategies (Wolters and Hussain, 2015 ) and elevated cognitive engagement (Datu et al., 2018a , b ). Moreover, grit enhances subsequent desirable changes in goal attainment among samples from different societies (Sheldon et al., 2015 ).

The second path in the diagram illustrates how grit can foster different well-being outcomes through concrete psychological processes. One of the mechanisms underlying the complex link of grit to well-being involves “needs satisfaction.” This type of process variable refers to fulfillment of basic psychological needs (c.f., autonomy, relatedness, and competence; Ryan, 1995 ). It is reasonable to expect that satisfaction of needs can mediate the association of grit with well-being because self-determination theory has pointed out that satisfying psychological needs can serve as a route to achieve intrinsic motivation, well-being, and optimal psychological functioning (Ryan, 1995 ; Deci and Ryan, 2000 ; Ryan and Deci, 2000 ). Research dovetails with this prediction as satisfaction of basic needs for autonomy and competence mediate the positive influence of grit on well-being (Jin and Kim, 2017 ).

Another psychological process that can elucidate why grit may increase well-being outcomes is “emotion regulation.” This category of mediating variables pertains to one's ability to manage emotions in different situations, such as (a) cognitive reappraisal, which involves modifying the interpretation of a specific situation to change its emotional consequences; and (b) expressive suppression, which entails decreasing or hiding one's true emotional states (Gross and Levenson, 1997 ). Consistent with this premise, perseverance of effort and consistency of interests are linked to higher levels of cognitive reappraisal (Knauft et al., 2019 ; Valdez and Datu, 2020 ). Yet, consistency is related to lower levels of expressive suppression. Also, cognitive reappraisal mediates the association of grit with psychological flourishing (Valdez and Datu, 2020 ).

The third classification of process variables underpinning the linkage of grit to well-being outcomes is “positive cognitions.” This type of variable encompasses one's capability to espouse positive thoughts about self, others, and environment. Echoing this prediction, research demonstrates how constructs belonging to this category of mediating variable mediate the association of grit on well-being outcomes, such as meaning in life (Kleiman et al., 2013 ), mindfulness (Li et al., 2018b ), and self-esteem (Li et al., 2018a ). Moreover, authenticity (perceived feelings of being connected to one's self; Wood et al., 2008 ) and sense of coherence (degree to which one's self and the world are sensible, meaningful, and controllable; Antonovsky and Sagy, 1986 ) mediate the association of grit with subjective and psychological well-being outcomes (Vainio and Daukantaite, 2016 ). For adolescents and young adults with long-term medical conditions, grit is associated with well-being (i.e., higher emotional well-being and lower depression, as well as anxiety) because this construct is linked to reduced perceptions that illnesses can disrupt their daily activities (Sharkey et al., 2017 ).

Aside from pinpointing specific psychological mechanisms that can underscore the benefits of grit on well-being, existing studies indicate how dispositional and contextual variables may strengthen or attenuate the effects of grit on various outcomes. It is likely that personality traits can moderate the anticipated impacts of grit on psychological functioning. For instance, a synergistic interaction between gratitude and grit increases meaning in life, which in turn decreases suicidal ideation (Kleiman et al., 2013 ). Furthermore, life events can also interact with grit to yield differential effects on well-being outcomes. Supporting this prediction, research reveals that negative life events can lead to suicidal ideation for individuals with lower inclination to show passion and perseverance for long-term goals (Blalock et al., 2015 ).

In general, Figure 1 recapitulates concrete cognitive, emotional, motivational, and behavioral processes that elucidate how and why grit cultivates optimal levels of performance outcomes and psychological health. Although this diagram offers a brief overview of precise psychological mechanisms linking grit to meaningful outcomes, note that this model is generated from past investigations that relied on the original two-factor model of grit (Duckworth et al., 2007 ), which attracted numerous conceptual and methodological criticisms on the grit construct.

Demographic, Psychological, and Social Factors Associated with Grit

Prior studies have demonstrated different demographic and psychological predictors of grit. In terms of demographic factors that relate to grit, there is evidence showing that age and length of work experience are associated with increased levels of grit over time (Duckworth et al., 2007 ; Camp et al., 2018 ). However, Usher et al. ( 2019 ) have shown that older students and those with low socioeconomic status tend to report low levels of grit. These findings indicate that the role of specific factors, such as age on grit is inconclusive.

Previous investigations have also shown specific psychological factors that may be linked to grit. For example, positive affect and purpose commitment have been associated with higher levels of grit in selected American and Canadian students (Hill et al., 2014 ). In a sample of Latina/o students, higher levels of hope positively predicted grit, whereas higher levels of search for meaning in life negatively predicted grit (Vela et al., 2015 ). Further, mindfulness positively predicted grit (Raphiphatthana et al., 2018 , 2019 ; Vela et al., 2018 ). There is also evidence showing that whereas experiencing fitness-related pride attributed to one's own effort (i.e., authentic fitness-related pride) was found to predict grit, fitness-related success attributed to one's innate ability or superiority (i.e., hubristic fitness-related pride) negatively predicted persistence and interest toward goal attainment (Gilchrist et al., 2018 ). Belief in free will has been also associated with increased perseverance in selected Chinese adolescents (Li et al., 2018d ).

Further, Armstrong et al. ( 2018 ) have demonstrated six self-regulation strategies, such as temporal perspective, perpetual evaluation, motivational orientation, strength and resource gathering, system thinking, and framing, were linked to higher levels of grit. In a national sample of American college students, Sriram et al. ( 2018 ) have shown that others-focused purpose, success-focused purpose, time spent in socializing, time spent in academic activities, and religious beliefs positively predict grit. Spirituality has also shown direct and positive effects on grit via the mediating role of employment hope among underemployed urban African Americans (Hodge et al., 2019 ).

There are studies showcasing the link of social factors to grit in different contexts. Whereas, excessively controlling parenting behaviors negatively predicted grit, parental involvement positively predicted grit (Howard et al., 2019 ). Grit also mediates the link of parenting-related behaviors to academic success (Howard et al., 2019 ). Relatedness to different social agents (i.e., parents, peers, and teachers) has different pattern of associations with grit and its dimensions with relatedness to teachers positively predicting perseverance, consistency, and overall grit, while relatedness to parents positively predicting consistency and overall grit (Datu, 2017 ).

What's Wrong with the Existing Grit Theory?

The considerable fund of empirical evidences showcasing the performance, well-being, and psychological advantages of fostering grit does not come without substantial controversies. This section summarizes results from previous studies highlighting major flaws in the extant theorizing and measurement of grit. Specifically, this is divided into four subsections, namely, measurement issues, theoretical validity, cultural bias in grit, and consistency or adaptability.

Measurement Issues

The existing grit framework (Duckworth et al., 2007 ) is continuously plagued by cumulative number of investigations indicating major problems in measuring the grit construct. Studies reveal psychometric issues on the items belonging to the consistency of interests dimension of grit in non-Western societies, such as Japan (Yoshitsu and Nishikawa, 2013 ; Datu et al., 2020 ) and the Philippines (Datu et al., 2016 , 2017a , 2018a ). Specific items (“My interests change from year to year” and “I have difficulty maintaining my focus on projects that take more than a few months to complete”) on consistency, for instance, were omitted in the investigation of Suzuki et al. ( 2015 ) because these items did not load onto the consistency dimension of grit in a preceding study (Yoshitsu and Nishikawa, 2013 ). Similarly, in an investigation conducted among selected Romanian adults, correlating two error terms (indicating issues in the wording of items) resulted in an acceptable measurement model of grit (Ion et al., 2017 ). In a sample of school-based counselors in the United States by Mullen and Crowe ( 2018 ), one item in the perseverance of effort dimension (“Setbacks don't discourage me.”) had a poor factor loading (0.15). Including this item in examining the internal consistency of perseverance of effort facet of grit resulted in a low Cronbach α coefficient (α = 0.57). Moreover, the two-factor model of grit generated from the 12-item original grit scale was not confirmed in a sample of athletes in North America (Tedesqui and Young, 2017 ). There is also evidence showing that the consistency subscale had poor reliability coefficients in non-Western and collectivist settings (Disabato et al., 2019 ).

When the hierarchical model of grit underpinned by perseverance and consistency as first-order latent factors was tested in selected Filipino university and high school student samples (Datu et al., 2016 ), results have shown that the scores from the said measurement model did not achieve an adequate fit. The factor structure of original grit model also differs among secondary school and undergraduate student samples (Muenks et al., 2017 ). Analyses of grit scales (e.g., Short Grit and Original Grit Scales) using item response theory (IRT) approaches also showed mixed evidence regarding the dimensionality of grit with one research demonstrating its unidimensionality (Areepattamannil and Khine, 2018 ), while other studies demonstrating its multidimensionality (Tyumeneva et al., 2019 ; Gonzalez et al., 2020 ). Furthermore, existing measure of grit is plagued by social desirability bias (DiMenichi and Richmond, 2015 ). Much like what other studies have consistently noted (Datu et al., 2016 , 2018a ; Datu and McInerney, 2017 ; Muenks et al., 2017 ), there is a need to improve existing measures of grit.

Adopting an extension procedures of confirmatory factor analysis (CFA) that enabled a more nuanced account on how dimensions of grit relate to conscientiousness while taking into consideration the hierarchical and lower-level factors of both constructs across German student and adult samples, Schmidt et al. ( 2018 ) have shown that perseverance exhibited strong association with common factors (95% shared variance) indicating this dimension of grit could be subsumed under the proactive aspect of conscientiousness (Roberts et al., 2005 ). Perseverance was also strongly linked to the industriousness facet of conscientiousness. Furthermore, consistency demonstrated a high relationship to the common factors of conscientiousness but more specifically related to the self-discipline facet of conscientiousness. Another research also demonstrated that the grit construct overlapped with self-control (Gonzalez et al., 2020 ). These findings further offer additional evidence on the conceptual resemblance of grit with conscientiousness and self-control.

Contrary to the fundamental tenets of original grit theory, previous research alludes to the possibility that consistency of interests does not belong to the higher-order grit latent construct (Abuhassàn and Bates, 2015 ). There is a significant but weak correlation between perseverance and consistency (Constantin et al., 2011 ; Jordan et al., 2015 ; Meriac et al., 2015 ; Wolters and Hussain, 2015 ; Tedesqui and Young, 2017 ). Indeed, measurement issues raised in the aforementioned studies reinforces the theoretical value of perseverance but not consistency in understanding the nature of grit.

Taken together, prior studies suggest considerable issues not only with its specific items but also with the entire consistency subscale of existing grit measures (i.e., Grit-O and Grit-S). There are different reasons that might account for psychometric problems on the consistency subscale. For example, whereas the consistency of interests has been conceptualized as one's tendency to constantly stick to interests that enable fulfillment of long-term ambitions (Duckworth et al., 2007 ), items in the extant grit scales tap into one's capacity to maintain focus on ideas or projects, which may not necessarily capture activities or endeavors that individuals consider meaningful. As previous investigations (Carlson et al., 2011 ; Zhang et al., 2016 ; Lee and Duckworth, 2018 ) have shown that scales with negatively worded or reverse-scored items are likely to yield undesirable impact on the overall psychometric validity of such measures, it is possible that the nature of wording in the consistency subscale in existing grit measures contributes to the fundamental problems in assessing grit.

Theoretical Validity

The existing two-factor model of grit has a few considerable flaws. One of the major shortcomings of theory includes the inability of consistency of interests to predict success and other meaningful outcomes. Dovetailing with this argument, previous investigations have found that consistency of interests does not relate to optimal functioning, such as academic achievement (Akos and Kretchmar, 2017 ; Muenks et al., 2017 ; Jiang et al., 2019 ), academic engagement (Datu et al., 2016 , 2018a ), and generalized self-efficacy (Jordan et al., 2015 ). Consistency is negatively correlated with an adaptive orientation to happiness (i.e., orientation to engagement; Suzuki et al., 2015 ). Overall grit score was not significantly correlated with achievement scores (Chang, 2014 ) and life satisfaction (Martin et al., 2015 ).

Moreover, although grit is positively correlated with in-role performance and organizational citizenship behaviors, it has limited predictive validity relative to Big Five personality factors on work-related (i.e., in-role performance, organizational citizenship behaviors, and counterproductive work behaviors) and well-being outcomes among selected Romanian adults (Ion et al., 2017 ). Although perseverance positively predicts academic performance, academic engagement and self-regulation were more strongly linked to achievement outcomes (Muenks et al., 2017 ). Conscientiousness also emerged as the strongest correlate of achievement when grit, intelligence, Big Five personality factors, self-efficacy, motivation, and test anxiety were entered as predictors of such outcome (Dumfart and Neubauer, 2016 ). Compared with grit, conscientiousness served as a stronger predictor of military cadets' academic and non-academic outcomes (Mayer and Skimmyhorn, 2017 ). After controlling the effects of extraversion, neuroticism, agreeableness, and openness, composite grit score did not predict academic achievement, academic recognition, honors, and rule-violating actions (Ivcevic and Brackett, 2014 ). Compared to grit, hardiness has been found to be a robust negative predictor of maladaptive internet usage and compulsive behaviors (Maddi et al., 2013 ). Similarly, only the perseverance dimension of grit predicted academic performance after controlling for the influence of conscientiousness (Rimfeld et al., 2016 ; Credé et al., 2017 ). Further, a recent study (Usher et al., 2019 ) demonstrated that grit did not predict academic achievement when relevant demographic covariates, such as gender, year level, and socioeconomic status were added as covariates among elementary and middle school students in the United States.

Vazsonyi et al. ( 2019 ) have offered evidence on the (a) unidimensionality of grit construct with latent method factors to characterize positively and negatively worded items and (b) substantial overlap between grit and self-control. Moreover, contrary to the theoretical predictions of Duckworth and Gross ( 2014 ) about the differential roles of both constructs on desirable performance outcomes (e.g., possessing high grit and low self-control will be strongly linked to approach outcomes, whereas having high self-control and low self-control will strongly relate to avoidance outcomes), there was no difference on how grit and self-control relate to various outcomes, such as approach or avoidance temperament, present goals, and past goals. Yet, as the study used cross-sectional research design and self-reported measures in exploring the internal, discriminant, and construct validity of existing grit scales, results may provide myopic evidence on the measurement problems associated with grit along with its conceptual similarity with self-control.

Cultural Bias in Grit

Aside from budding line of empirical evidences magnifying the theoretical shortcomings of the original grit framework, another critical problem in the existing grit literature is the excessive quantity of published articles that examined the nature, antecedents, and consequences of grit in countries regarded by previous researchers (Henrich et al., 2010 ) as WEIRD (Western, educated, industrialized, rich, and democratic) societies. Given that citizens in non-Western cultures comprises more than 60% of the world's population, it is imprecise and deceptive to automatically generalize that findings from previous research might apply to individuals from non-WEIRD contexts. Despite the relative significance of advancing grit literature in non-Western cultures, there is still marked paucity of studies investigating the role of grit's facets in collectivist countries.

To date, studies on grit have focused on exploring the role that grit plays in optimizing optimal academic, work-related, and well-being outcomes in some non-Western societies, such as Japan (Suzuki et al., 2015 ), China (Li et al., 2018a , b , c ), Hong Kong (Lee, 2017 ; Datu and Fong, 2018 ), mainland China (Chen et al., 2018 ), Philippines (Datu et al., 2016 , 2017a , 2018a , b , 2019 , 2020 ), South Korea (Jin and Kim, 2017 ), and Thailand (Raphiphatthana et al., 2019 ), among others. Without additional investigations on the antecedents and consequences of grit in non-WEIRD settings, it may be challenging to offer convincing insights on how grit dimensions may differentially relate to performance and positive psychological outcomes in various societies. Moreover, few studies (Chen et al., 2018 ), thus far, have adopted a cross-cultural design in exploring how grit relates to academic and well-being outcomes (Chen et al., 2018 ; Disabato et al., 2019 ; Raphiphatthana et al., 2019 ; Datu et al., 2020 ).

Consistency or Adaptability

As serious issues are raised on the heuristic value of consistency of interests in the validity of grit construct (e.g., Credé et al., 2017 ; Schmidt et al., 2018 ; Datu et al., 2020 ), it is important to discuss how and why consistency may not necessarily contribute to successful accomplishment of long-term goals. This subsection draws from diverse perspectives to elaborate the mechanisms underscoring the non-significant role of consistency in catalyzing achievement and well-being in various contexts.

First, as it is likely that individuals can face many demanding situations in the pursuit of long-term goals, shifting from one interest to another and even relaxing difficult goals can serve as equally beneficial approaches to achieve optimal performance (Kashdan and Rottenberg, 2010 ; Dreisbach and Fröber, 2019 ). In situations where failure is inevitable, showing passion and persistence may not eventually pay off. Instead of achieving visible indicators success, persevering in face of failure might even result in irreparable damages or losses. Blind persistence (Baumeister et al., 2003 ) therefore is not an ideal strategy when one is facing tasks that could not be realistically completed. Studies have underscored the practical importance of knowing when to jettison life goals that are bound to fail (Baumeister et al., 2003 ; Lucas et al., 2015 ). Other research has emphasized the equally appealing value of dropping originally identified long-term goals in lieu of more realistic aspirations (Wolters and Hussain, 2015 ; Datu and McInerney, 2017 ; Datu et al., 2018a ).

Second, individuals who espouse higher interdependent self-construal are inclined to exhibit self-variability, a tendency to engage in behaviors based on situational demands or cues (Suh, 2007 ; Vignoles et al., 2016 ). Salience of self-variability can potentially account for why consistency of interests is not linked to well-being in many collectivist societies (Disabato et al., 2019 ). Instead, adaptability is linked to higher levels of self-efficacy, academic engagement, motivation, and well-being in Filipino high school students (Datu et al., 2017a , b ). These findings underscore the importance of calibrating interests, behaviors, and goals contingent on one's context or situation.

Third, from the vantage point of psychosocial theory of development (Erikson, 1982 ), human beings go through distinct developmental stages requiring various sets of psychological and interpersonal competencies. If one consistently sticks to specific interests or goals that may not facilitate successful resolution of a psychosocial crisis (e.g., identity vs. role confusion), he or she may end up losing trail of succeeding more advance developmental stages, which is detrimental to psychological health. For example, an adolescent who is constantly showing excessive interests in playing online computer games but aspiring to become a medical doctor may face difficulties in achieving better academic performance. This, in turn, can cause a serious toll on his vocational identity (thus leading to inability to achieve a sense of identity) as it may be challenging to be admitted in good university degree programs with mediocre performance. Consistent with this perspective, research indicates that in the case of older adults, it is likely that grit may yield desirable effects on prosocial behaviors because espousing this trait expands their opportunity to achieve their developmental tasks (Wenner and Randall, 2016 ). To the extent that grit afford adults with concrete prospects of being productive members of communities, this trait can optimize successful resolution of psychosocial developmental stage, such as generativity vs. stagnation (Erikson, 1982 ).

Fourth, whereas the original grit theory (Duckworth et al., 2007 ) highlighted the role of consistency, existing studies indirectly point to the benefits of adaptability (e.g., calibrating one's interests or goals based on situational demands) in achieving long-term aspirations. Dovetailing with this prediction, research suggests that grit may have state-like features (DiMenichi and Richmond, 2015 ) and is more strongly associated with the openness to experience compared to conscientiousness in Japanese adults (Suzuki et al., 2015 ). Furthermore, a study has shown that compared to other grit profiles (i.e., high perseverance and high consistency as well as low perseverance and high consistency), students belonging to a profile characterized by high perseverance and low consistency had significantly higher scores on hope and lower scores on anxiety and shame (Datu and Fong, 2018 ).

Indeed, the aforementioned theoretical premises indicate that consistency may have limited predictive power in shaping meaningful outcomes. Instead, it is reasonable to propose that adaptability can facilitate successful fulfillment of long-term goals. However, more research is needed to understand how replacing consistency with adaptability can improve the theoretical validity of grit construct.

Moving Forward with the Science of Grit

The identified controversies on the theorizing and measurement of grit open considerable spaces for refining the existing grit framework. Evidences clearly suggest that improving the two-factor model of grit can advance our understanding on the nature, and antecedents, and consequences of grittiness in various contexts (Credé et al., 2017 ; Datu et al., 2017b ).

Designing Alternative Conceptualizations and Measures of Grit

One of the recent attempts to improve grit framework involves development of the triarchic model of grit (Datu et al., 2017a , 2018a ), which conceptualizes grit as a disposition to show passion, perseverance, and adaptability for long-term goals. Like the original grit model (Duckworth et al., 2007 ), this model of grit has emphasized the importance of perseverance of effort and consistency of interests in achieving very challenging distal goals. However, the revised model highlights the theoretical value of incorporating adaptability to situations, defined as capacity to constantly calibrate one's interests and actions depending on situational and contextual factors. Triarchic Model of Grit Scale (TMGS; Datu et al., 2017a ) was developed based on the items under the perseverance and consistency dimension of the Short Grit Scale (Duckworth and Quinn, 2009 ) and newly formulated items on adaptability. Research has provided preliminary evidence regarding the validity, reliability, and gender invariance of TMGS among Filipino undergraduate and high school student samples (Datu et al., 2017a , 2018b ).

Triarchic model of grit dimensions has been found to be differentially linked to positive academic, psychological, and well-being outcomes. For instance, whereas perseverance and adaptability are associated with higher levels of self-efficacy in various domains of performance (i.e., academic, career exploration, and talent development self-efficacy), consistency was not (Datu et al., 2017a ). Similarly, while adaptability and perseverance are linked to optimal school functioning, such as autonomous motivation, controlled motivation, and all components of academic engagement (i.e., agentic, behavioral, cognitive, and emotional engagement), consistency was linked only to behavioral engagement (Datu et al., 2018b ). Although all dimensions of grit are positively correlated with life satisfaction, only perseverance and adaptability are associated with well-being outcomes (Datu et al., 2018b ; Datu and Restubog, 2020 ). Datu and Restubog ( 2020 ) have shown that these TMG dimensions were linked to increased positive emotions due to the intermediate variable—social emotional learning. Both perseverance and adaptability are also related to increased well-being not just in the context of Filipino students but also in selected Japanese and Polish undergraduate students (Datu et al., 2020 ).

Although there is a reason to argue that triarchic model of grit (Datu et al., 2017a , 2018a ) may potentially address theoretical and methodological issues raised in the existing two-factor model of grit (Duckworth et al., 2007 ), this program of research remains to be at the embryonic phase. For example, to what extent does this revised model of grit incrementally predict performance outcomes beyond and above the effects of relevant personality factors, such as openness to experience and conscientiousness? Can triarchic model of grit predict overall and domain-specific academic achievement beyond the influence of theoretically related constructs, such as academic self-regulation, academic self-efficacy, motivation, and engagement? Do consistency, perseverance, and adaptability serve as differential predictors of success and well-being? What psychological processes underpin the hypothesized educational benefits of this grit model? In what ways do different grit profiles relate to achievement and well-being outcomes?

Furthermore, a more recent approach involves polishing the consistency (a.k.a. passion) dimension of grit. Jachimowicz et al. ( 2018 ) refined the passion facet of grit through redefining this dimension as “as a strong feeling toward a personally important value/preference that motivates intentions and behaviors to express that value/preference” (p. 9980). The study demonstrates that combining perseverance and passion is linked to higher levels of work-related and academic performance. However, recent research has pointed out theoretical and measurement issues on the validity of the total score generated by their scale measuring perseverance of effort and passion, to assess perseverance (Credé, 2019 ).

Despite the potential benefits of “redefining” the consistency dimension of grit, future research is necessary to strengthen the evidence on the validity of this modified grit framework. For instance, how does the consistency facet of grit differ from the harmonious passion conceptualized in the dualistic model of passion (Vallerand et al., 2003 )? Will this modified grit model incrementally predict achievement and optimal psychological outcomes beyond the contributions of different types of passion (e.g., obsessive and harmonious passion), Big Five personality factors, domain-specific motivation, and self-regulation? In what ways do the recently conceptualized passion facet and perseverance relate to various forms of well-being (i.e., subjective well-being, psychological well-being, psychological flourishing, and physical health)? Clearly, more studies are needed to understand the nature of grit given the growing body of evidence raising criticisms on the original two-factor model (Duckworth et al., 2007 ) and recently conceptualized models, such as the triarchic model of grit (Datu et al., 2017a , 2018a ) and perseverance + passion model of grit (Jachimowicz et al., 2018 ).

Additional investigations are warranted to explore how domain-specific forms of grit may contribute to objective and subjective performance indicators. Past research has also underpinned the significance of assessing domain specificity of grit (Duckworth et al., 2007 ; Duckworth and Quinn, 2009 ; Wolters and Hussain, 2015 ; Clark and Malecki, 2019 ; Cormier et al., 2019 ). For instance, Clark and Malecki ( 2019 ) have shown that academic grit had incremental validity over domain-general grit scores in predicting academic performance and well-being outcomes (i.e., life and school satisfaction). Similarly, school-specific grit incrementally predicts academic achievement beyond the influence of domain-general grit and gender (Cormier et al., 2019 ). Other researchers have developed and validated domain-specific grit scales for foreign language learning (Ebadi et al., 2018 ). Yet, it is evident that except for the study of Ebadi et al. ( 2018 ), existing studies primarily focused on the consequences of domain-specific grit in Western societies (e.g., United States). Addressing this methodological grit entails exploring the role of domain-specific grit in non-Western and collectivist contexts to provide evidence about the cross-cultural applicability of grit in various cultural settings.

On top of refining extant grit scales, future studies can adopt alternative approaches in assessing grittiness. Duckworth and Yeager ( 2015 ), for instance, have enumerated teacher-report measures and performance task assessment as potential tools to evaluate non-cognitive abilities in school contexts. Biographical evidence of long-term commitments can also serve as a complementary approach to assess individuals' determination to accomplish challenging longstanding aspirations (Robertson-Kraft and Duckworth, 2014 ). Other researchers (Bowman et al.,) have recommended the use of personal statements and documents indicating academic and extracurricular engagements of individuals to assess individuals' grittiness.

Moreover, it is also essential to continuously examine the validity of grit measures based on alternative statistical approaches, such as an extended procedure of CFA conducted in the investigation of Schmidt et al. ( 2018 ) and IRT analyses. To date, there were few studies that adopted IRT-based approaches to investigate the psychometric properties of existing grit scales (Areepattamannil and Khine, 2018 ; Tyumeneva et al., 2019 ; Gonzalez et al., 2020 ). Further, these studies primarily concentrated on providing psychometric information about Grit-O and Grit-S, so findings have limited implications for evaluating the validity of other grit scales, such as TMGS (Datu et al., 2017a ) and Academic Grit Scale (Clark and Malecki, 2019 ). Adopting more sophisticated analytic procedures (e.g., polytomous IRT modeling techniques and extended versions of CFA) can generate stronger evidence on the psychometric validity of existing grit measures.

Strengthening Evidence on the Incremental Validity of Grit

Given the empirical evidences dampening the incremental validity of grit above and beyond the effects of theoretically related constructs, such as conscientiousness (Maddi et al., 2013 ; Ivcevic and Brackett, 2014 ; Rimfeld et al., 2016 ; Credé et al., 2017 ; Muenks et al., 2017 ) and academic variables, such as motivation and engagement (Steinmayr et al., 2018 ), there is a need to conduct additional studies on how refined models of grit can uniquely contribute to desirable performance outcomes beyond and above the effects of theoretically relevant constructs (i.e., Big Five personality factors, self-control, self-efficacy, and motivation). In addition, it is equally important to the unique predictive power of grit on psychological and physical health after controlling for pertinent covariates (e.g., neuroticism, self-discipline, and eating behaviors).

Furthermore, although other studies have shown that the original model of grit can predict retention beyond the influence of traditional variables that relate to admission in college programs (e.g., high school GPA and college GPA) in selected undergraduate students in the United States (Saunders-Scott et al., 2018 ) and cadets in West Point (Duckworth et al., 2007 ), not so much is known on how alternative models of grit predict retention outcomes in non-WEIRD societies. It is therefore essential to carry out investigations on the incremental validity of triarchic model of grit (Datu et al., 2017a , 2018a ) and revised model of grit (Jachimowicz et al., 2018 ) on retention outcomes in different domains of performance (e.g., sports, post-graduate degree, extracurricular activities, and artistic activities).

Future research can also generate stronger evidence on the construct validity of grit through exploring how grit and its dimensions may relate to specific neurocognitive and physiological processes. For instance, research shows that perseverance of effort is associated with smaller mean difference in N1 amplitude for double cue trials, which suggest higher levels of sustained attention (Kalia et al., 2018 ) and neural activities in the medial prefrontal cortex (Myers et al., 2016 ). Moreover, future research can explore the connection of grit to objective indicators of optimal physical health, such as frequency of visits to physicians, regulation of antibody genes, and actual blood pressure. Studies of these kinds can provide more rigorous and convincing insights about the predictive power of grit in various domains of performance and well-being.

Adopting Alternative Methodological Approaches

Except for a few investigations that used longitudinal (O'Neal, 2018 ; O'Neal et al., 2018 ; Park et al., 2018 ; Jiang et al., 2019 ; Datu et al., 2020 ) and experimental (Lucas et al., 2015 ) research approaches, previous studies mainly relied on cross-sectional research designs in examining the role of grit in performance, optimal psychological, and well-being outcomes. Given that cross-sectional designs are prone to common method bias that can delimit the validity of such studies (Podsakoff et al., 2003 ), future investigations are encouraged to adopt longitudinal designs (e.g., cross-lagged panel and latent growth curve modeling approaches) to offer stronger evidence about the complex association of grit with desirable performance and well-being. Furthermore, the extant grit literature may profit from conducting person-oriented approaches to explore how various profiles of grit may relate to optimal levels of achievement in different domains of performance. The use of experimental research design is needed to provide cause evidence on the effects of grit to achievement and well-being outcomes.

As majority of published studies on grit examined the benefits of grit in student populations, future research can also explore how grit may foster meaningful outcomes in clinical populations. Past investigations have already initiated exciting avenues for unpackaging the appealing values of grittiness in specialized populations, such as college students with ADHD (Gray et al., 2015 ) and patients with substance dependence (Griffin et al., 2016 ). Consistent with this point of contention, previous research (Griffin et al., 2016 ) points out that integrating grit in motivating clients to achieve optimal recovery can complement existing clinical psychological interventions. Hence, it is a promising research initiative to investigate the effects of grit on the lives of clients with diverse medical conditions.

Identifying Antecedents of Grit

There is a need to explore how specific social and contextual factors relate to grit. Recognizing the importance of interpersonal factors on passion and perseverance for long-term goals, research demonstrates that relationship with peers (Lan and Moscardino, 2019 ) and school connectedness (Renshaw and Bolognino, 2016 ) are linked to higher levels of grit. Even classroom-level variables, such as classroom peer grit (O'Neal, 2018 ) and perceived mastery–approach and the capacity of classroom to promote mastery–approach goals (Park et al., 2018 ) are linked to increased grit in student populations. In fact, classroom peer grit has stronger influence than individual-level grit on subsequent literacy achievement even after controlling for previous literacy achievement and relevant demographic covariates, such as age, gender, and home language (O'Neal, 2018 ). However, in the context of Latino undergraduate students, perceived family support did not contribute to grit (Vela et al., 2015 ). Moreover, there is no evidence yet that report how specific academic and non-academic policies or programs in school contribute to development of grit in academic settings. Indeed, more studies are desired to explore how different social factors catalyze grit, as well as precise psychological mechanisms linking, such as social, contextual, and interpersonal variables to grit construct.

Exploring the “Dark Side” of Grit

Existing investigations indirectly point to the caveats of embodying a sustained interest and perseverance to achieve goals even in the face of failures. Consistent with this perspective, a series of experiments carried out by Lucas et al. ( 2015 ) has shown that grittier individuals exerted more effort than their less gritty counterparts when finding solutions to unsolvable tasks at the expense of accomplishing fewer duties (Study 1) and when losing a game (Study 2). Moreover, when grittier participants were given an opportunity to quit, they showed greater persistence and stayed in a losing game. Indeed, these results indicate that there are potentially damaging psychological costs associated with espousing grit especially in contexts where failure is bound to happen. Similarly, espousing higher grit and tendency to give up on difficult or boring activities (i.e., perseverance dimension of impulsivity) has been linked to more incidence of suicidal attempts (Anestis and Selby, 2015 ). This evidence points to the potential maladaptive effects of grit on well-being outcomes. Future investigations, therefore, are needed to explore the adverse “side effects” of grittiness and specific contextual conditions that may amplify the “dark side” of grit in various domains of performance and psychological functioning.

Addressing Cultural Biases in Grit

Many issues revolving around the “cultural biasness” of grit remain unresolved. One of the most controversial problems points to grit as a “racist” construct that characterized motivational intensity for distal goals for individuals belonging to families with high socioeconomic status (Herold, 2015 ). In a similar vein, McGee and Stovall ( 2015 ) have criticized extant grit theory for being a “racist” construct that fails to capture unique mental health needs of Black students in predominantly White educational institutions. Future researchers can eventually address these conceptual speculations on the cultural insensitivity of grit construct through exploring the invariance of specific grit models across individuals from diverse economic and racial backgrounds, as well as examining the moderating role of socioeconomic status and racial backgrounds on the hypothesized link of grit to positive performance and well-being outcomes in different settings. Because the present grit literature is dominated by studies carried out in WEIRD societies, more investigations are necessary to explore how grit operates in non-WEIRD contexts, which, in turn, generate solid evidence regarding the cross-cultural generalizability of grit.

Theoretical Implications

Before discussing the anticipated theoretical contributions of this review, it is important to note its limitations. Given that studies included in this review were not done in a systematic manner, it is likely that this review might be prone to selection bias. Future reviews can address this methodological shortcoming through conducting systematic reviews that involve organized and careful selection of studies based on a specific range of inclusion criteria. In addition, the qualitative nature of this review precludes concrete insights on the magnitude of relationship between grit and well-being or other positive health outcomes. Future researchers can fill this gap through carrying out meta-analyses in order to quantitatively summarize the effects sizes between grit and a wide range of optimal outcomes. In order to generate more robust and comprehensive evidence regarding the mental health, physical, and neural correlates of grit, future research may integrate the methodological strengths of qualitative (e.g., systematic) and quantitative (e.g., meta-analyses) reviews through performing a systematic and meta-analytic review. Further, given the limited evidence about the incremental validity of alternative models of grit (e.g., triarchic model of grit) above and beyond the effects of relevant psychological constructs, such as conscientiousness and self-control, caution should be observed when interpreting conclusions about the educational and psychological payoffs associated with these frameworks of grit.

This integrative review has implications for advancing research programs about the generalizability, measurement, antecedents, and consequences of grit. First, although prior reviews (Credé et al., 2017 ; Datu et al., 2017a , b ; Credé, 2018 ; Lam and Zhou, 2019 ) primarily concentrated on summarizing the link of grit to academic performance and relevant outcomes, this review offers a more holistic overview about the correlates of grit through providing substantive summary on how grit and its dimensions predict optimal psychological, mental health, and physiological outcomes. Drawing from previous scientific findings about the consequences and correlates of grit, this review also organizes cognitive, affective, behavioral, and social mechanisms underscoring the educational, organizational, and mental health benefits of grit into the optimal performance and health (OPAH) model of grit. Second, unlike previous reviews on grit that offered broad insights on how to address conceptual and measurement issues on grit, this review outlines a few specific recommendations on how to address existing conceptual and psychometric issues in the grit construct. Future researchers may consider such suggestions in order to design more culturally nuanced grit scales that can capture individual difference in persistence toward accomplishing long-term ambitions in various cultural contexts. Third, while past review articles focused on summarizing studies about the benefits of grit (Datu et al., 2017b ; Lam and Zhou, 2019 ), these reviews provide scant insights about the importance of exploring maladaptive impacts of staying gritty. This review addresses this limitation through briefly rationalizing the significance of pinpointing the disadvantages associated with grittiness as a future scholarly initiative.

Practical Implications

This review carries valuable implications for educational and mental health practitioners in various contexts. Given the mixed evidence regarding the psychometric validity and construct validity of the Grit-S and Grit-O (Muenks et al., 2017 ; Areepattamannil and Khine, 2018 ; Tyumeneva et al., 2019 ), educational policy makers and administrators (e.g., principals, vice principals, admission office director, and subject area coordinators) should practice caution when integrating these questionnaires as assessment tools in high-stake academic activities and career placements. Further, as most studies appear to indicate that only perseverance of effort serves as a consistent predictor of many key educational outcomes, such as academic achievement (Chang, 2014 ; Wolters and Hussain, 2015 ; Muenks et al., 2017 ; Steinmayr et al., 2018 ), motivation (Eskreis-Winkler et al., 2014 ; Datu et al., 2018b ), engagement (Datu et al., 2016 ), and achievement goal orientation (Chen et al., 2018 ), schools are encouraged to invest in psychological programs that aim to cultivate persistence among typically developing and at-risk students. To date, there have been a number of educational interventions (see Alan et al., 2020 ) that provided promising evidence about the effects of these initiatives on key learning outcomes.

School-based and community mental health practitioners are also likely to benefit from the findings of this review. As prior studies have demonstrated the mental health benefits of grit's dimensions such as perseverance (Pierro et al., 2011 ; Lee, 2017 ; Hwang et al., 2018 ) and adaptability (Datu et al., 2018b , 2020 ; Datu and Restubog, 2020 ; Datu and Zhang, 2020 ), school psychologists and guidance counselors are recommended to consider designing school-wide psychoeducational interventions that aim to promote these personal qualities in student populations. The extant literature on the association of grit with optimal neural activities (Myers et al., 2016 ; Kalia et al., 2018 ; Wang et al., 2018 ) points to the potential benefits of initiating interdisciplinary collaborations between neuroscientists and educational practitioners (e.g., teachers and subject area coordinators) in order to build grit interventions that can optimize effective learning and psychological health.

Conclusions

There is an ongoing debate on the theoretical validity and benefits of fostering grit in various contexts. This integrative review contributes to extant grit literature through (a) discussing concrete issues on the measurement, validity, and correlates of grit; (b) reviewing alternative models of grit; and (c) discussing how these alternative models of grit can address existing issues on the generalizability and measurement of grit. Much like other valuable psychological constructs, better theorizing, measurement, and methodological approaches can address skepticisms raised against grit. Indeed, understanding the complex nature of grit goes beyond investigating the roles of passion and perseverance in pursuing long-term goals.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

The Future of Science: Humanity Takes a Front Seat

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Over the last few years, we saw breakthroughs and discoveries that scientists had only dreamed of. From the development of the life-saving COVID-19 vaccines to N ASA crashing a spacecraft into an asteroid in a successful attempt to alter its orbit , clearly a lot can happen in a short period of time.

With the world of science rapidly evolving, we look at the trends breaking through right now, asking experts: where is the world of science headed?

Feeding the planet in a climate changing world

By some estimates the planet will need to produce 60% more food by 2050 to sustain the world’s growing population – an ask that will likely strain the already fatigued agriculture industry and place a heavy burden on natural resources. Major changes are necessary to keep up with such high demands – but where do we start?

One proposed approach is genetically modifying heat-resistant crops by “hacking” photosynthesis . Photosynthesis uses sunlight, water and carbon dioxide to make sugars and other molecules plants need, but in hot and dry conditions the necessity of water and carbon dioxide poses a problem. To let carbon dioxide in, plants must keep their pores open, but this can lead to water loss, which can ultimately kill the plant. By hacking the system, geneticists have been working to engineer plants like rice, wheat and maize to withstand extreme temperatures , while other vegetables that already have a high heat tolerance – like eggplant, sweet potatoes and okra – are being engineered to sustain longer periods of heat and increase yield. Just this month, a study published in Nature described the discovery of two-million year old DNA from an ancient ecosystem in Finland where temperatures at that time were of the levels we should expect if climate change were to continue. Researchers are hoping to use this data to show how plant species were able to adapt to better understand how genetically-modified modern species could withstand today’s increasing temperatures.

Putting resources into developing more sufficient and nutrient-rich food that is accessible and can withstand demand pressures is also encouraged by scientists. This can be achieved through actions beyond the farm, according to Dr. Patrick Webb , Alexander McFarlane professor of nutrition at Tufts University and director for USAID’s Feed the Future Nutrition Innovation Lab . “Much of what is produced today never reaches the consumer,” he said. “Around 30% of food is lost or wasted, and in addition much is fed to livestock, who contribute to greenhouse gas emissions. Some is used for alcohol and ethanol, and even more is used in creating ultra-processed foods that have little nutritional or health value. We need to change what is done to food in the supply chain, and help shift demand for higher quality diets, to support actions already being pursued on the farm.”

In other words, noticeable change could occur with a shift in subsidies towards nutrient dense foods, cutting out food waste and reducing meat and dairy consumption in countries that currently consume these at levels contributing to ill-health.

“All of this would substitute for the so-called needed “increases” in current production patterns, while at the same time making food systems contribute more positively to both human and planetary health,” Webb added.

Genome-editing takes a front seat in healthcare

Genome-editing techniques like CRISPR-Cas9 technology have gained further momentum in the last few years. The 2020 Nobel Prize in Chemistry was awarded jointly to Professors Emmanuelle Charpentier and Jennifer Doudna for discovering one of the gene technology’s most precise tools – the CRISPR-Cas9 genetic scissors. The number of clinical trials testing CRISPR-based therapeutics continues to grow each year, with the technology currently being tested against cancer , blood disorders , metabolic conditions and even urinary tract infections .

Just last year, the first clinical trial using a CRISPR-based therapy to treat blindness yielded positive results. The therapy targets mutations in the CEP290 gene, which causes a rare form of blindness known as Leber congenital amaurosis type 10 (LCA10) that is incurable. The clinical trial injected CRISPR machinery into the body to repair CEP290 mutations. T wo of the six participants dosed in March 2020 can now sense light better , and one can navigate a maze in dim light.

Another recent study tested a one-time treatment that uses an ex vivo approach to correct a defective gene behind sickle cell disease and beta thalassemia. Here, a patient’s cells are extracted and CRISPR-Cas9 is used to modify them such that they produce fetal hemoglobin. The study presented at the European Hematology Association (EHA) Congress, showed that both β-thalassemia patients had hemoglobin levels of 14.2 and 12.5 grams per deciliter, respectively, following the study, compared to a range of 12 to 15 grams, normally seen in healthy adults. Participants also saw continued benefits for up to three years after administration, with this approach being cited as a potentially safer treatment option than an allogeneic transplant from a donor.

While the ingenuity of CRISPR-Cas9 has proven successful in certain clinical trials, the technology faces barriers relating to ethics, precision and accessibility. These include the difficulty in delivering the technology to mature cells in large numbers, which can ultimately affect accuracy and efficiency. As of 2014, the EU Clinical Trials Regulation banned clinical trials of any gene therapy that might result in germline modifications – edits to reproductive cells that could be inherited – because of ethical and safety concerns. And “off target” edits, nonspecific and unintended genetic modifications, can have severe consequences , particularly in clinical settings.

In 2017, The National Academy of Sciences and National Academy of Medicine issued a 258-page report focused on human genome editing. It included recommendations for the US government and governments around the world on how best to handle the advances in genome editing and included recommendations for basic laboratory research like requiring broad public input prior to extending resources and limiting clinical trials to prevention and treatment of disease or disability at this time. The committee also discussed the issue of equity and access to genome-editing technology – which is currently priced highly due to the investments required for R&D that can be lengthy and expensive. Globally, it will need to be ensured that people with disabilities have an equal voice and equitable access. The report acknowledged the inevitable bottleneck that will occur as more people learn about emerging CRISPR-based therapeutics and request them.

Progress in global vaccination efforts

Infectious diseases remain the leading cause of death for people in low-income countries, with malaria and RSV killing as many as 1 in 50 children, according to a recent study . But experts are hopeful that immunization research and the introduction of new vaccines to the marketplace will provide relief in the years to come.

“I am excited about the new malaria vaccine, called R21,” said Dr. Gavin Yamey , professor of global health and public policy at Duke University. “Developed by scientists at Oxford University, it was found to be up to 80% efficacious at preventing malaria in young children in a clinical trial . We don’t yet know whether we’ll see the same level of benefit once the vaccine is rolled out in the real world, but if it turns out to be highly effective under real world conditions, it could have a dramatic impact.” The vaccine was the first to reach the World Health Organization (WHO)’s Malaria Vaccine Roadmap goal of a vaccine with at least 75% efficacy in 2021 .

Dr. Yamey said that providing timely access to vaccines – like R21 – and medical care is crucial in preventing disease. He adds that a possible solution to ensuring better access and health resources come from the implementation of strong primary care systems in all countries that can deliver prevention, treatment and rehabilitation services to any and everyone in need.

Vaccine equity plays a major role in providing that. The WHO announced it has increased funding to initiatives working to scale-up vaccine production in disease afflicted countries, while data scientists are using technology to better understand and predict potential viral outbreaks that can originate in animals, with the ultimate goal of preventing any future pandemic outbreaks.

“We need globalized vaccine manufacturing capacity, so that all regions can make pandemic vaccines when needed,” added Yamey. “We need to agree up front on a fair global allocation of vaccine doses, and we need to share the intellectual property on any future pandemic vaccine.”

Consciousness-expanding medicines go mainstream

The use of marijuana for medical purposes has grown in popularity over the last decade, but researchers are now exploring psychedelics for a myriad of neurological and psychiatric conditions.

“Many drugs that are used recreationally can aid medical conditions, or they’re undergoing clinical trials to determine if they are safe and effective,” said Betty Aldworth , director of communications at the Multidisciplinary Association for Psychedelic Studies (MAPS) . “In fact, this is true with drugs from every psychoactive class.”

While still in research, and not permitted for routine clinical practice, some psychoactive drugs have already demonstrated their potential for treating neurological disorders. The use of ketamine, a dissociative commonly used for induction and maintenance of anesthesia, showed significant improvement in depression and anxiety symptoms after a 0.5 mg/kg dose was administered six times over a two-week period in  a 2019 study . Stimulants like amphetamines have also shown effective ness in reducing ADHD symptoms, where the drugs work to increase levels of dopamine and norepinephrine in the brain.

In mid-November, MAPS Public Benefit Corporation announced that the second MAPS-sponsored Phase III trial of MDMA-assisted therapy for PTSD was complete. “In the first Phase III trial of MDMA-assisted therapy for PTSD, 88% of participants experienced a clinically significant reduction in PTSD symptoms and 67% no longer met the criteria for a PTSD diagnosis,” Aldworth said. “Psilocybin-assisted therapy for treatment resistant depression is entering Phase III trials.”

While no psychedelic has been FDA-approved, clinical trials so far have delivered promising results and it seems likely that FDA approval will happen in the coming years, said Aldworth: “FDA approval will also help dismantle the decades of disinformation, myths, and stigma associated with psychedelics.”

As the future of science continues to evolve and the field matures, leveraging technology against the world’s top problems will be the key to success. As Milton H. Saier, Jr. wrote , it won’t be enough to focus on just the science, but recognize the people it most directly affects: “They allow us to recognize what we have in common with each other and with other living beings,” he said.

The Scientific Observer Issue 21