 The concept of emotional disorder In August 2024, a special report on ‘ecological medicine’ was published in Psychiatry Online. The authors of the report describe ecological medicine as “the structured and deliberate use of connectedness and interaction with plants, animals, and other species to generate a therapeutic effect for individuals.” While few would doubt the value of spending time in the natural world, the suggestion that we need medicine to mediate our connection to nature is a striking one. Surely nothing could be more direct and immediate than the sense of awe we feel when we gaze upon the vast night sky, or the sense of renewal we feel when wandering in a spring meadow? And surely, too, it is more than just our health that is affected by this engagement; we are affected. That the concept of ecological medicine seems to be pointing at something so familiar, and yet seems to be expressing it in such a striking and novel manner, gives us pause to reflect. How have we arrived at a point in our civilisation where it seems sensible to describe as a medical discovery the idea that “other species are worthy of respect”, and that the recognition of inter-species reciprocity that is enabled by participating in ecological medicine “serves to counteract some of the societal elements contributing to society’s epidemic of mental health problems”? This manner of approaching our sense of connection with nature is, arguably, emblematic of a sweeping cultural trend: We appear to be losing our grasp on ways of conceiving of human flourishing other than in medical terms. Today, we speak of ‘mental health’, often treating this as synonymous with the notion of flourishing itself. To accept the notions of ‘mental health’ and ‘flourishing’ as synonymous with each other involves a commitment to the conjunction of the following two claims: C1: To be mentally healthy is to flourish; and C2: To flourish is to be mentally healthy. C1 takes mental health to be sufficient for flourishing, whilst C2 takes it to be a necessary condition. C1 is the stronger of the two claims insofar as it asserts that nothing else—apart from being mentally healthy—is required for human flourishing. C2, unlike C1, allows for the possibility that there may be other conditions besides that of mental health that are also necessary for human flourishing—conditions pertaining to other domains of value such as ethics or aesthetics (domains that are of course salient in our connection with nature). But even the weaker claim, C2, imports a medical connotation into our conception of human flourishing that would have once seemed novel, perhaps even puzzling. Aristotle in the Eudaimian Ethics, for instance, takes health (like wealth or honour) to be a means by which we might come to flourish, rather than as tantamount to flourishing itself. How did this connotation appear, signalling the shift towards the medicalisation of our understanding of what it means to flourish? Here is one story of the origin of this connotation (told by Martin Seligman, a founding father of the positive psychology movement): if (severely) distressing emotional experiences are cast as states of pathology, as contemporary psychiatry does, then it isn’t a huge leap (although it is a substantive one) from this claim to the idea that being in a state opposite to this—that is, enjoying a preponderance of pleasant emotional experiences—amounts to a state of wellness, a state of wellbeing, indeed a state of flourishing. This chain of inference is one of the major paths we have taken that has led us towards the medicalisation of our conception of flourishing. If this is right, then recovering alternate, non-medicalised conceptions of human flourishing, conceptions that might well return to us the expressive power to capture (amongst other things) our immediate connection with nature that we intuit, will involve a dissection of the concept of emotional disorder. What, then, is the basis of the claim that (severely) distressing emotional states constitute states of pathology? From what general concept of disorder is this identification derived, and in light of what conception of our emotional lives might this identification be motivated? Surprising lines of inquiry emerge in the course of this exploration, all of which point to the pivotal role that our emotions play in the myriad ways we appraise our lives and make sense of ourselves. One particular line is worth mentioning here: it is often assumed that the medicalisation of our understanding of human flourishing signifies progress, at least in the sense that it yields an understanding that is informed by scientific knowledge. But this line of inquiry invites us to consider whether human flourishing is something we should seek to understand exclusively in scientific terms (as the invocation of the idea of progress implies). Indeed, is it something we should seek to understand in scientific terms at all? A systematic investigation of the value of emotions in human life suggests that there are visions of human flourishing that invite, indeed compel, not the detachment of the scientific gaze, but our immersion in life through the exercise of our rational agency. It is in appreciating the trade-offs between these alternative conceptions of human flourishing, and the appraisals they lead us to make of our emotional experiences, that we arrive at a clearer reflective understanding of our current predicament. It is in so doing that we may recover our power to express the immediate connection we feel with nature when we plant an acorn and tend its growth. My aim is not to argue in favour of any particular conception of flourishing—and so I do not, for instance, claim that it is a mistake to medicalise our sense of connection with nature. It is rather to display as perspicuously as possible some of the conceptual structures that guide our ongoing quest to live happier and more enlightened lives. This quest has, for the most part, taken a very distinctive shape over the past half century: we pour billions of dollars each year into the enterprise of improving our ‘mental health’. It is ultimately for us to decide, individually and collectively, whether thinking of our flourishing in terms of the notion of ‘mental health’ is a good thing to do—rather than being, merely, something we’ve simply ended up doing. Featured Image by Sébastien Bourguet on Unsplash. OUPblog - Academic insights for the thinking world. 
 In the spirit of Oswald It’s been more than 60 years since the assassination of John F. Kennedy. Those who remember where they were and what they were doing on that fateful day in 1963 are becoming smaller in number. Since that afternoon in Dallas, Lee Harvey Oswald has been viewed as a glory-seeking sociopath who, according to every official account, acted alone. No one offered him the adulation or hero worship he so desired. That is, perhaps, until now. For today’s potential assassins and mass shooters, there could not be a better role model than this isolated extremist seeking fame and achieving it, albeit the short-lived kind. Now, among certain young people, Oswald is achieving the admiration he sought. Thomas Matthew Crooks’ thinking may have been remarkably like Oswald’s when he took the shot at Donald Trump. Both were outcasts by all accounts—bullied, isolated, and in desperate need of validation. Oswald’s bullet hit his target; Crooks’ only grazed his. But while the distance from Oswald’s nest in the Texas Schoolbook Depository to Kennedy’s limousine was some 265 feet, Crooks’ bullet had to travel roughly 400 feet. Crooks’ shot was more difficult and surprisingly accurate in light of the fact that years earlier he had failed to make the high school rifle team because he was such a bad shot. Oswald’s name surfaced again in reference to rooftop shooter Robert Crimo III, who killed seven people and injured dozens of others during a Highland Park Fourth of July parade in 2022. A famous photo of Crimo features a newspaper announcing Oswald’s murder taped to an otherwise bare wall behind him. Mass shootings have become commonplace in the modern world. But as every incident and shooter is analyzed, new common denominators are emerging—a link between shooters of the past and those of the present. More often than not, these perpetrators are neither insane nor delusional. But they are political extremists, with their beliefs constantly reinforced by others of the same mind: their violent acts are in fact due to their extreme overvalued beliefs. An extreme belief “is one that is shared by others in a person’s cultural, religious, or subcultural group. The belief is often relished, amplified, and defended,” forensic scientist Tahir Rahman states. “An extreme belief may grow more dominant over time, more refined, and more resilient to challenge. Thinking becomes simplistic, binary, and absolute. The individual has an intense emotional commitment to the belief and may carry out violent behavior because of it.” Extreme Overvalued Beliefs include: - The 9/11 attacks;
- Unabomber (Ted Kaczynski);
- Oklahoma City bombing;
- Boston Marathon attack;
- Dylan Roof (hate crime);
- Thomas Matthew Crooks (attack on former president Trump).
The individual has an intense emotional commitment to the belief and may carry out violent behavior because of it. Crucial to Rahman’s discourse is the fact that the post 9/11 world set the stage for a breakthrough—the Terrorism Radicalization Assessment Protocol (TRAP-18), developed by psychologist and FBI consultant Dr. J. Reid Meloy. The TRAP-18 is a structured and scientifically tested approach for threat assessment that has undoubtedly saved numerous lives. Importantly, the TRAP-18 helps professionals identify potential attackers before the violence starts. Behaviors of potential assailants fall into two categories: distal characteristics (of which there are 10) and proximal warning signs (of which there are 8). Distal characteristics include personal grievances, failure to affiliate with a group (rejection from those with like beliefs), and criminal violence. Proximal warning signs include things like fixation, a sudden burst of energy in the perpetrator, or a directly communicated threat. Oswald was not unknown to the state department and other federal agencies of 1963. If FBI and Secret Service units had access to current threat assessment tools, he might never have made it as far as his sniper’s nest in the Texas School Book Depository. To thwart potential future offenders, TRAP-18 needs to be utilized to an even greater degree, Rahman feels. Threat AnalysisTo do this, Rahman has created a four-part threat analysis to identify facts and circumstances that would lead a reasonable person to believe that an individual is committing or is attempting to commit a criminal offense (poses a threat to self and/or others). This assessment tool takes away personal bias and instead focuses on actual behavioral signatures, in doing so avoiding profiling people based solely on their race, ethnicity, etc. 1. Threats due to psychotic delusions (fixed, false, idiosyncratic)“My neighbor is a space alien and is trying to kill me.” “Satan has instructed me to kill them.” Commonly seen in: Schizophrenia, Bipolar Disorder with psychosis, Depression with psychosis, Drug-induced psychosis. Treatment: Secure weapons with law enforcement, antipsychotic medications, emergency civil commitment to a mental health facility, case management. 2. Threats due to Extreme Overvalued Beliefs“I am going to be a professional school shooter.” “The West is at war with Islam.” “Black people are replacing White people.” Intervention: Secure weapons with law enforcement, treat co-occurring problems (e.g. mood, anxiety, drug use), crisis response teams, unique behavioral management (e.g. family, group, and individual therapy), case management. 3. Threats due to obsessions (intrusive, unwanted thoughts)Usually pose a low risk of harm to others. “I can’t stop thinking that I might hurt someone.” Treatment: OCD medication, talk therapy, OCD foundation. 4. Threats due to addictive/behavioral issues, alcohol/drugs, paraphilias, domestic violence, or personality disorder (e.g. Psychopathy)Treatment: Secure weapons with law enforcement, drug rehabilitation centers, medication- assisted treatment, (family, individual, and group) therapy. Sometimes jail or prison is the only answer. This assessment tool takes away personal bias and instead focuses on actual behavioral signatures Since 2014, the U.S. has witnessed more than 4,000 shootings involving multiple victims. More often than not, mental illness or delusional thinking is blamed. But in truth, what lies beyond these facades may be as diverse as the cultures from which they spring. Extreme Overvalued Beliefs lie at the heart of many incidents. Once that is recognized, the steps toward preventing radicalization may well be doable. Featured image by Dakota L. via Wikimedia Commons CC BY-SA 4.0. OUPblog - Academic insights for the thinking world. 
 Speech, AI, and the future of neurology Imagine what your life would be like if you did not know where you are or who you are with, and a young man told you, “We’re home and I’m your son.” Now imagine how you would feel if your body became still when you want to walk or shaky when you try to keep still. Do it. Take a moment and think about it. Those who do not need to imagine are the 55 million people living with Alzheimer’s and the 10 million living with Parkinson’s, respectively, as they experience similar challenges every day. While these figures raise concern, future projections are alarming: by 2050, the number of cases is expected to double in high-income countries and triple in low/middle-income countries. Things are particularly bleak in the latter, as they account for 60% of the cases but less than 25% of global investment in research, prevention, diagnosis, and treatment. With growing patient-per-clinic ratios and soaring inequities across the globe, how will we detect these diseases early and massively enough for timely intervention? What solutions could balance the scales of brain health worldwide? An unsuspected answer involves combining natural speech and artificial intelligence. Yes, this sounds like another flight of imagination, but it all rests on solid science. Note that these diseases are incurable. Rapid and mass detection is our best alternative; and this is precisely where the need for innovation emerges. Tracking diseasesAlzheimer’s and Parkinson’s are neurodegenerative disorders, characterized by progressive atrophy of distinct brain regions. Alzheimer’s usually begins with neuron degeneration in the hippocampus and temporal lobe, affecting memory and several other abilities. In Parkinson’s, neuronal degradation begins in the basal ganglia, leading to motor and cognitive difficulties. Yet, this is just the tip of the iceberg. For patients, these diseases are disabling and often fatal. For families, they undermine emotional stability, financial solvency, and quality of life. For governments, they challenge health systems’ infrastructure and finances. Thus, these conditions project from the brain onto society, tracing a devastating trajectory. That is why timely detection is crucial. Early diagnosis can mitigate the impact of symptoms, reduce their emotional burden on patients and caregivers, increase time to plan neuroprotective habits, and reduce costs by favoring routine over emergency care. Note that these diseases are incurable. Rapid and mass detection is our best alternative; and this is precisely where the need for innovation emerges. Today, diagnosis rests on interviews with specialists, extensive paper-and-pencil tests, and, when conditions allow, brain MRI studies and biomarker assessments. These procedures are invaluable, but imperfect. Many countries lack enough qualified personnel and appropriate technology (and when these resources exist, their costs can be prohibitive). Furthermore, outcomes depend on the judgments of examiners, who vary in training and experience. Moreover, assessments are usually stressful and appointments take weeks or months. Worse yet, these limitations are exacerbated as patient numbers increase and socioeconomic disparities between countries deepen. An urgent need thus arises for new affordable, user-friendly, scalable, and immediate approaches. Red flags in speechThis is where digital speech biomarkers come into play. Suppose that Tom, who is pushing 70, has been showing signs of cognitive decline and you suspect he might be suffering from Alzheimer’s. What if you asked him to recount a memory and an app detected traces of the disease in his speech? This non-invasive, low-cost approach offers real-time results without the need to visit a clinic, sparking great enthusiasm. Yet, how exactly does it work? The key is that when we speak, we engage multiple brain regions that are affected by these diseases. Some, such as the hippocampus and the temporal lobe, are involved in accessing words as discourse unfolds; others, like the basal ganglia, coordinate the physical movements during speech production. So, if such regions were atrophied, one would expect alterations in the types of words used, their articulation, or other relevant aspects. By testing specific linguistic dimensions, we can uncover the integrity or dysfunction of those brain areas. The first step is to record the natural speech of individuals with and without a given disease (the more, the better). Subsequently, complex algorithms quantify multiple aspects of the recording (say, speech rhythm) and its transcription (say, word properties). These metrics are used to train computational models that learn the typical speech characteristics of diagnosed individuals and healthy ones. Once the model is trained, it is presented with acoustic and linguistic measures from Tom, and, essentially, queried with this question: “Model, based on what you’ve learned, does Tom have the disease or not?” In a recent study, our team identified Alzheimer’s disease with nearly 90% success via word property analysis. The model learned that patients, compared to their healthy peers, use words with higher frequency (‘doctor’ rather than ‘physician’), lower specificity (‘dog’ instead of ‘poodle’), and more common sound sequences (like ‘bat’, which resembles ‘cat’, ‘fat’, ‘mat’, ‘rat’, ‘bet’, ‘bit’, ‘bought’, ‘boot’, ‘bad’, ‘bag’, and ‘ban’; as opposed to ‘giraffe’, whose sound sequence is quite unique). Indeed, these lexical properties predicted the patients’ level of cognitive decline and brain atrophy. The reason is quite simple: word selection is a central function of semantic memory, which becomes impaired since the onset of temporo-hippocampal atrophy in Alzheimer’s. When navigating semantic memory, people with the disease prioritize the most accessible parts of their vocabulary, consisting of frequent, unspecific, and common-sounds words. And the more severe their disorder is, the simpler the words they favor. In another study, we detected Parkinson’s disease with over 90% accuracy by measuring motor aspects of speech. We found that patients, compared to healthy individuals, leave longer pauses between words and produce less recognizable sounds. These patterns even differentiated between disease variants. Once again, the finding is clear. Speech production requires coordinating movements of the tongue, lips, and vocal cords, among other organs. Since basal ganglia atrophy affects motor skills, these actions in people with Parkinson’s prove slow, shaky, and imprecise. The audio signal carries traces of these alterations. The breakthroughs do not stop there. These methods can anticipate who will develop specific conditions in the future. Some studies also suggest that they outperform standard tests in estimating disease severity and discriminating between syndromes. The approach has been validated with data acquired in hospitals and over the phone, incorporated in clinical trials, and harnessed by user-friendly apps. These are critical milestones towards rethinking clinical assessments. The breakthroughs do not stop there. These methods can anticipate who will develop specific conditions in the future. A story in the making For all its promise, this story is only beginning. The approach requires more validation, especially in large groups of patients. New studies should focus on vulnerable populations to balance the abundant data coming from high-income countries. More generally, a digital medical culture must be cultivated for clinicians to incorporate computational tools. Of course, these milestones demand concerted efforts of scientists, medical professionals, patients, family members, companies, and policymakers. None of this is easy or immediate. The path from science to clinical practice and public policy is long, crooked, and uphill. Fortunately, this is not an isolated endeavor. Various teams are working on other digital tools for disease detection, including eye-tracking devices, motion sensors, and gamified cognitive tests. Speech analysis is part of a vast movement pushing for clinical equity through technological innovations. To conclude, imagine that we can detect these diseases before Tom shows symptoms of decline. Imagine doing so by reducing the social gaps among world nations. And imagine a future where all this needs no longer be imagined. If such a day ever arrives, it will be through disruptions like this. Featured image by TungArt7 via Pixabay. OUPblog - Academic insights for the thinking world. 
 Better together: coupling up to watch TV and talk synchronizes brain waves Scientists are a step closer to finding out just why watching TV together and talking is such a popular pastime. Watching the same movie stimulates similar neural activity across brains: a phenomenon referred to as inter-subject correlation. Subjects sitting in the same room and talking over the content have been shown to increase various other measures of brain synchrony. Now it turns out that we don’t even need to be discussing what’s on the screen to get more in tune with each other during the next show. Lead author Dr. Sara De Felice, Professor Antonia Hamilton, and other colleagues at University College London used functional near-infrared spectroscopy (fNIRS) to measure brain activity in 27 pairs of adults as they each watched two different episodes of the short BBC children’s cartoon Dipdap. In between the episodes, the subjects talked over trivial facts unrelated to the show, such as exotic animals and musical instruments. The researchers then compared the data on brain activity recorded during each episode to see if the non-relevant chatter had affected mental synchrony. Their results, published in Oxford Open Neuroscience, showed increased brain synchrony over the right dorso-lateral pre-frontal cortex (DLPFC) and right superior parietal lobe (SPL) in familiar pairs (housemates, friends, or partners) watching the cartoon together compared to pseudo pairs who had not met, and who watched the short film alone. These results are in line with previous studies into these brain regions which indicate that the DLPFC is associated with functions like working memory, abstract reasoning, and cognitive flexibility while the SPL receives significant visual input, and is also associated with reasoning and memory, as well as attention. The study also found that co-watching after a conversation was associated with greater brain synchrony over the right temporoparietal junction (TPJ)–an area of the brain famous for allowing other perspectives (theory of mind)–compared to co-watching before a conversation. This effect was significantly higher in familiar pairs engaging in conversation with each other than in pseudo pairs who talked to someone else. “Two things are surprising and novel here,” says Dr. De Felice (now at the University of Cambridge). “First, having a chat resulted in brains also synchronising afterwards. Second, the chat didn’t have to be related to the movie to see this effect.” Brain gamesThe scientists selected fNIRS for this research as it uses light to map blood flow in response to neural activity at sites across the head, allowing the study of natural face-to-face interactions because subjects aren’t physically confined in a noisy fMRI machine. “fNIRS is non-invasive and robust to movement, allowing the measurement of brain activity from people as they act and interact normally,” says Dr. De Felice. On the downside, its lag time of around five seconds makes it much less spatially and temporally accurate than other techniques. The researchers found no significant differences in the other five brain regions selected for measurement. “Brain synchrony was observed in three areas (the DLPFC, SPL, and TPJ) which play a key role in our ability to interact with others, understand intentions and emotions, and interpret other people’s perspectives,” explains Dr. De Felice. “It makes sense that we observe synchrony over these areas during co-watching of the BBC Dipdap cartoon, where the watcher is encouraged to follow and predict what the puppet will face next.” She suggests the findings, along with those from numerous other studies, could indicate that brain synchrony extends to and from further behaviours: “This might explain why people who spend considerable time together often find themselves in greater agreement with each other than with those they’ve never met. Through such interactions, individuals can develop a shared reality, both physically and mentally.” The next challenge is to better explore the causal relationship between synchrony and social interaction, examining if altering this synchrony using brain stimulation would alter the parameters of interaction, she says. Featured image by Sarandy Westfall via Unsplash. OUPblog - Academic insights for the thinking world. 
 Mental disorder or something magical? Each generation finds their own way of understanding mental distress. The ‘shell-shocked’ soldiers of World War I were understood at the time to be of weak character, although now we might diagnose them with post-traumatic stress disorder (PTSD). Victorian women were subject to ‘hysteria’ and fainting fits, something we might now understand as non-epileptic seizures. The way that we understand distress is deeply rooted in our culture and time, but it doesn’t feel like that to us. We tend to think that the way we understand things now is the right way, superior to previous generations and other cultures. Which makes our current time a particularly interesting one to be working in mental health. The dominant way to understand mental distress in the West in the last 70 years has been the medical model. This sees distress and unusual behaviour as symptoms of an underlying mental disorder. Diagnosing clinicians compare a person’s experiences to lists of criteria and give them (or not give them) a diagnosis. That diagnosis should lead to treatment, which should then (hopefully) lead to an improvement in symptoms. This system is one of categorisation. It matters which diagnosis a person gets because that will affect the services they receive. Get a diagnosis of PTSD and you’ll find yourself offered very different treatment than if you are given a diagnosis of ADHD, even if your symptoms have similarities. The system is pragmatic and structures many mental health services. A psychiatric diagnosis is a description, rather than an explanation. It gives a name to a cluster of symptoms. However, in recent decades, the fundamental principles of the diagnostic system have been undermined by neuroscientific and behavioural genetic research. Research has failed to find biological correlates for the diagnostic groupings defined by the manuals (called DSM and ICD). According to behavioural geneticist Robert Plomin, instead of finding ‘genes for schizophrenia’ as expected, large scale studies have shown that many genes combine in tiny, cumulative, and generalised effects. Studies of mental health have consistently found dimensionality. Symptoms such as anxiety, or hearing voices, or low mood vary across the whole population, and a diagnosis draws a line where none exists in nature. The implications of this for how we conceptualise mental health are profound. Researchers are working on dimensional frameworks and influential neuroscientists argue that a reliance on diagnostic categories is holding back advances in research. It has become increasingly clear that diagnostic groups may be practical, but they don’t reliably reflect distinctions between people. However, alongside this revolution in how scientists understand mental health has come the advent of social media and a huge cultural shift. Here the way in which psychiatric diagnoses are understood have also changed dramatically in the last few decades, but in a very different way. On social media, psychiatric diagnoses have become identities and online communities have formed around them. ‘Mental health influencers’ post about their symptoms and put their diagnoses in their bios. Some of their followers start to define themselves in the same way, or even to develop new symptoms. We are only just starting to understand how influential social media can be. For many, these diagnoses signify far more than a list of symptoms. They provide an explanation as to why they are the way that they are and validation that their life struggles are not their fault. The mainstream media have also adopted this narrative, with articles published with titles like ‘My New Life: Being Diagnosed with ADHD in My 40’s has Given Me Something Quite Magical.’ This has led us to the strange situation where just as scientists are moving away from grouping people by diagnosis, more people than ever before are thinking of themselves as belonging to a diagnostic category. Many are self-diagnosing, and several clinicians have informed me of official complaints after they told service users that they didn’t fit the criteria. If a person sees a diagnosis as the key to something magical, it’s understandable that they are furious if it is withheld. There has always been a gulf between how the general public understands mental health and how scientists and clinicians conceptualise it. What perhaps is new is that many now see a diagnosis as their route to compassion and community, as an affirmation of who they are. This was not what the medical model was designed for, and it is not well-suited to the task. Psychiatric diagnoses were intended to identify pathology in order to provide treatment. Waiting lists soar as a result, and when a person finally does see a clinician, expectations can be very different to the reality. Anger grows when people are not able to get the diagnosis they feel they need or when their diagnostic assessment doesn’t provide the validation they were hoping for. We’re in the middle of a cultural clash in the way that we understand mental health. As science is pushing us towards reconsidering diagnostic categories, those same categories are becoming ever more important in popular culture. This inevitably leads to tension. ‘Mental disorder’ or ‘something magical’—can a diagnosis be both at the same time? Or are there other ways to understand mental distress entirely? Feature image by Brooke Cagle on Unsplash. OUPblog - Academic insights for the thinking world. 
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