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<td><span style="font-family:Helvetica, sans-serif; font-size:20px;font-weight:bold;">PsyPost – Psychology News</span></td>
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<td><a href="https://www.psypost.org/demonic-attacks-in-dreams-follow-a-chilling-multi-night-pattern/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Demonic attacks in dreams follow a chilling multi-night pattern</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 16th 2026, 10:00</div>
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<p><p>A recent study published in the journal <em><a href="https://psycnet.apa.org/record/2026-26650-001" target="_blank">Dreaming</a></em> suggests that demonic encounters in nightmares often follow a predictable pattern of escalating threats across multiple nights of dreaming. The research provides evidence that these terrifying dreams are tied to feelings of powerlessness and eerie environmental shifts, shedding light on how the brain processes intense emotional distress during sleep. By tracking dreamers over a two-week period, the findings offer a detailed look at the anatomy of exceptionally severe nightmares.</p>
<p>Scientists <a href="https://pmcnamara.substack.com/" target="_blank">Patrick McNamara</a>, John Balch, and Chanel Reed wanted to explore the thematic and psychological associations of demonic content in dreams. “I had noticed in my work on content of nightmares that many participants in those studies reported greater distress when they felt that they encountered something ‘evil’ or demonic in the nightmare,” said McNamara, a professor of psychology at National University, an associate professor of neurology at the Boston University School of Medicine, and co-director of <a href="https://www.cognitiveneuroscienceofreligion.org/" target="_blank">the Cognitive Neuroscience of Religious Cognition (CNRC) Project</a>.</p>
<p>While feeling an evil presence during sleep is a well-documented phenomenon, the specific ways these sinister figures operate within a dream narrative remain largely uncharted. The researchers aimed to identify the progression of these themes, particularly how a single unsettling dream might evolve into a full-blown demonic attack. “It is clinically and scientifically interesting when a specific cognitive content is associated with greater distress as one could potentially use that content as the target for therapeutic intervention,” McNamara told PsyPost.</p>
<p>By collecting an intensive series of sleep diaries, the team hoped to track the evolution of these frightening narratives. They sought to provide an initial framework for understanding the factors associated with these severe nightmares. This foundation tends to help future scientists explore the clinical implications of such dreams, particularly regarding how the mind handles unresolved fear.</p>
<p>To conduct the study, the researchers recruited 124 adult volunteers from the community. These participants were on average forty-four years old, predominantly female, and mostly white. The participants agreed to take part in a two-week longitudinal study from their own homes.</p>
<p>During this period, the volunteers followed their normal sleeping schedules. Every morning upon waking up, they completed surveys on their phones or computers. These surveys asked the participants to report any dreams they could recall.</p>
<p>The volunteers then rated their dream content based on mood and general themes. To do this, they used a structured questionnaire that asks people to score their dreams on various adjectival scales, such as strange versus familiar. The participants also noted if their dreams woke them up during the night.</p>
<p>In addition to the daily surveys, sixty-one of the participants wore a specialized sleep-tracking headband each night. This device measures sleep architecture, which refers to the different stages and cycles of sleep a person goes through, such as light sleep, deep sleep, and rapid eye movement sleep. The headband allowed the researchers to gather objective data on the participants’ brain waves and sleep patterns.</p>
<p>Throughout the two weeks, the participants submitted a total of 1,599 individual dream reports. Highly trained research assistants read each narrative to determine if the recalled content qualified as a nightmare. They looked for specific markers, such as words expressing fear, scenarios posing an immediate threat to the dreamer, or reports of pain.</p>
<p>If a narrative lacked explicit emotion words, the researchers relied on the morning questionnaire ratings to see if the dreamer scored the experience as highly scary or aggressive. Through this process, the team identified 186 nightmares and 112 disturbing dreams. Within this large pool of reports, they searched specifically for demonic content.</p>
<p>The scientists defined demonic content as figures expressing a sense of supernatural evil and a malicious intent to harm the dreamer. They found sixteen dream reports with overt demonic themes and another group of reports with borderline demonic elements. These specific dreams were experienced by eight different participants.</p>
<p>The researchers found that five of the overt demonic dreams were part of a sequential series. This means the participants had a succession of related dreams over several nights that eventually culminated in a nightmare about a demonic attack. The other eleven reports were single-night events that also featured demonic characters.</p>
<p>When analyzing the headband data, the researchers noticed no major differences in sleep stages between nights with demonic dreams and regular nights. The time spent in deep sleep or rapid eye movement sleep remained largely consistent. However, the scientists note that the small number of demonic dreams makes it difficult to draw definitive conclusions about brain wave patterns.</p>
<p>To understand the progression, the researchers looked closely at the specific narratives provided by the participants. For example, one participant experienced a series of dreams that began with a young brunette woman floating up a hill with a malicious smile. Over the next several nights, this female character reappeared in different forms, such as a sharp departmental secretary and later as the dreamer’s own daughter.</p>
<p>As the nights went on, the dream environment underwent what the participant called a dimensional shift. The threatening presence drew physically closer and closer across the dream series. On the final night, a full demonic attack occurred, with the spirit described as pale and remote, directly echoing the floating woman from the very first dream.</p>
<p>“I was not exactly surprised but I was certainly fascinated by the fact that the demonic content, the ‘demon,’ was often announced or appeared as a vaguely threatening character in a regular non-distressing dream days before the onset of its appearance in a nightmare,” McNamara said. “I intend to follow up with this finding in future research.”</p>
<p>Another participant experienced a profound fracturing of identity leading up to her demonic nightmare. In her initial dream, she saw herself in a mirror as an elderly woman living in the nineteenth century, working as a servant. In a subsequent dream, she transformed into a flying flower, yet she still operated as a servant to a supernatural villain.</p>
<p>By the end of her dream series, this theme of servitude culminated in a terrifying scenario. She dreamed she was married to the devil, who was brainwashing her into permanent servitude in a dark, eerie house. These specific cases highlight how feelings of powerlessness and shifting identities pave the way for a demonic encounter.</p>
<p>The qualitative analysis of the broader dream narratives yielded a wealth of detailed thematic patterns. One major pattern revealed that demonic content often announces itself at the very beginning of a dream series. A character might initially appear as a non-threatening agent, but over subsequent nights, this entity transforms into something supernaturally evil.</p>
<p>Another finding suggests the background environment in these dreams tends to feel eerily threatening. The physical setting often undergoes bizarre changes or violates the laws of physics, taking on a distinctly supernatural atmosphere. Dreamers described dark houses, strange dimensional shifts, and shadowy settings.</p>
<p>A third pattern involves the dreamer typically being depicted as entirely powerless. The participants often exhibited a fragile sense of identity, sometimes even transforming into different characters, such as the nineteenth-century woman or the floating flower mentioned previously. This lack of agency leaves the dreamer highly vulnerable to the unfolding threats.</p>
<p>A fourth characteristic shows that the demonic entity consistently displays a strong interest in harming the individual. The demon acts as if it wants to destroy the dreamer physically or obliterate their sense of self. The narratives frequently featured violence, such as being chased by monsters or attacked by malevolent forces.</p>
<p>A fifth pattern highlights a distinct progression of thematic content across the consecutive nights of a dream series. Elements of the demonic figure would randomly reappear in different guises, moving progressively closer to the dreamer. The threat level steadily escalated over time until the final terrifying nightmare occurred.</p>
<p>As a final pattern, the dreamers or their allies often attempted to oppose the demon. Sometimes a parent or a friend in the dream would step between the dreamer and the beast. Sadly, these attempts to fight back or block the malicious actions almost always failed.</p>
<p>The researchers suggest that these findings might relate to how the brain processes emotional memories. When an individual experiences intense fear or stress, the sleep-dependent memory system attempts to process and integrate those emotions over several nights. If the emotional load is too overwhelming, this integration process fails, which provides a pathway for severe nightmares to occur.</p>
<p>People raised in environments with supernatural belief systems might naturally use those concepts to visualize their fears. The brain takes the feeling of a profound, unresolved threat and clothes it in the visual rhetoric of a demonic encounter. The demon acts as a psychological stand-in for overwhelming distress or repressed anxieties.</p>
<p>The study does have a few limitations that warrant consideration. The occurrence of demonic dreams in the sample was relatively rare, which means the quantitative data regarding sleep stages lacks the statistical power needed for broad generalizations. A larger sample of such dreams would help verify if any specific sleep architectures predict these nightmares.</p>
<p>The authors also note that they did not collect data regarding the participants’ media consumption. Popular culture, including horror movies and video games, very likely influences the specific imagery people see in their terrifying dreams. Tracking what media participants consume before bed might explain why certain demonic figures take specific shapes.</p>
<p>Future research could also track medication usage, which was not analyzed in this specific study. Certain drugs are known to alter dream vividness and affect, so incorporating medication information would provide a more complete picture. By expanding on these themes, scientists can continue to piece together the mechanisms behind our most frightening nocturnal experiences.</p>
<p>For those troubled by these intense nocturnal experiences, the findings offer some reassurance. “They are not alone if they experience what they subjectively perceive as ‘evil’ content; if the demonic content persists seek help from sleep medicine experts experienced in treating nightmares,” McNamara said.</p>
<p>The study, “<a href="https://psycnet.apa.org/doi/10.1037/drm0000312" target="_blank">The “Demonic” in Dreams and Nightmares</a>,” was authored by Patrick McNamara, John Balch, and Chanel Reed.</p></p>
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<td><a href="https://www.psypost.org/intelligence-makes-people-more-trusting-but-early-hardship-cuts-this-benefit-in-half/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Intelligence makes people more trusting, but early hardship cuts this benefit in half</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 16th 2026, 08:00</div>
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<p><p>Growing up in a disadvantaged environment not only hinders cognitive development but also weakens a person’s default willingness to trust others later in life. A recent study published in <em><a href="https://doi.org/10.1177/01461672261439412" target="_blank">Personality and Social Psychology Bulletin</a></em> reveals that while higher intelligence generally makes people more trusting, early childhood adversity cuts this social benefit in half. These findings suggest that childhood hardships create long-lasting barriers to social mobility by preventing individuals from reaping the typical rewards of their cognitive skills. </p>
<p>Trusting strangers is a fundamental requirement for a functioning society. Generalized trust is the basic belief that other people are generally reliable and will not exploit you. Economists and psychologists view this kind of trust as a foundation for cooperation, economic prosperity, and overall well-being. People who trust others are more likely to build strong networks and succeed in their careers.</p>
<p>Previous research consistently links higher cognitive ability to higher levels of generalized trust. Researchers generally define cognitive ability as a person’s capacity for memory, reasoning, and problem-solving. People with stronger cognitive skills are often better at recognizing that cooperation pays off in the long run. They are also thought to be better at evaluating someone’s trustworthiness and suppressing emotional, gut-level feelings of suspicion.</p>
<p>At the same time, childhood environments play a massive role in shaping social attitudes. Growing up in a stable, resource-rich household encourages long-term planning and cooperation. Conversely, childhood stress and scarcity act as warning signals about a harsh world. In unstable environments, short-term survival strategies and heightened vigilance are more practical than trusting strangers.</p>
<p>Chris Dawson, a researcher at the University of Bath’s School of Management, wanted to understand how these two factors interact. Most previous studies assumed that intelligence and childhood background influenced trust independently of one another. Dawson suspected that the environment a child grows up in might change how their brainpower is eventually used. Specifically, he wanted to see if intelligence provides the exact same social advantages for everyone, regardless of their background.</p>
<p>Sociologists and psychologists have debated exactly how personal skills and childhood resources interact. One theory, known as resource substitution, suggests that intelligence can compensate for a lack of environmental support. Under this idea, a highly capable child from a poor neighborhood uses their brainpower to overcome their surroundings and figure out how to thrive. </p>
<p>Another theory proposes the exact opposite. The resource multiplication theory suggests that early advantages compound over time. A rich, supportive environment acts like a multiplier for intelligence, giving smart children endless opportunities to practice cooperation and see it rewarded. </p>
<p>To test which reality plays out in the real world, Dawson analyzed data from a massive, nationally representative survey in the United Kingdom. The sample included 24,140 adults with an average age of about 47. The survey gathered extensive information about household finances, personal attitudes, and cognitive performance. This rich dataset allowed the researcher to look for patterns linking early-life conditions to adult beliefs.</p>
<p>To measure generalized trust, the survey asked participants a standard question about human nature. Respondents had to choose whether most people can be trusted, whether it depends, or whether you cannot be too careful these days. While simple, this single question is a widely accepted tool that reliably captures a person’s long-term social outlook.</p>
<p>The survey also tested participants on five specific cognitive tasks. These included a delayed word recall test, a subtraction challenge, and an exercise where participants had one minute to name as many animals as possible. Other tests asked participants to fill in missing numbers in a sequence and solve practical math problems. Dawson combined the scores from these five tasks into a single measure of general cognitive ability, adjusting the final numbers to account for natural changes in brain function that happen as people age.</p>
<p>To measure childhood disadvantage, Dawson looked at four specific hardships participants might have experienced by age 14. These included living outside a two-parent household, having parents with no educational qualifications, and having parents who were unemployed. The final dimension was having parents who worked in routine, low-status jobs. Participants who experienced two or more of these conditions were classified as having a disadvantaged childhood.</p>
<p>The data revealed several distinct patterns. First, individuals who grew up with childhood disadvantage scored lower on adult cognitive tests. They were also much more likely to say that you cannot be too careful when dealing with other people. Both of these patterns held up even when the researcher controlled for current age, sex, and household income.</p>
<p>Next, Dawson examined the relationship between intelligence and trust. Among people from more advantaged backgrounds, higher cognitive ability was strongly associated with a greater likelihood of trusting others. For these individuals, intelligence seemed to unlock the social benefits of cooperation. </p>
<p>However, for people from disadvantaged backgrounds, this relationship was substantially weaker. An increase in cognitive ability still boosted trust, but the effect was only about half as strong as it was for the advantaged group. The protective and cooperative benefits of intelligence were essentially suppressed. </p>
<p>This pattern supports the resource multiplication theory, often referred to as the Matthew Effect. This concept describes how early advantages multiply over time, allowing privileged individuals to gain disproportionate rewards from their skills. In a stable environment with low crime and reliable institutions, a smart person easily learns that trust is rewarded.</p>
<p>For a child in a harsh environment, those same cognitive resources might be redirected toward survival. Disadvantaged settings often feature unreliable institutions and fewer opportunities to see cooperation pay off. Dawson explained this dynamic in a press release accompanying the study.</p>
<p>“We often assume that intelligence leads to positive social outcomes in the same way for everyone but these findings challenge that idea,” Dawson said. “People who grow up in difficult environments not only develop lower cognitive skills, but also those skills appear less likely to translate into trust and the wider benefits that come with it.”</p>
<p>“This matters, because trust helps people build relationships, succeed in organisations, and participate in society,” Dawson said. “If early disadvantage suppresses those benefits, it may reinforce inequality across generations.”</p>
<p>The physical and emotional toll of a difficult childhood might also play a direct role. Chronic stress and anxiety are common results of early adversity. “In those environments, intelligence may simply have fewer opportunities to translate into trust,” Dawson said. “Early adversity may also leave lasting effects of stress and anxiety that limit how cognitive abilities are expressed in social life.”</p>
<p>To see if these patterns held up on a global scale, Dawson also looked at international data. Using the Global Preferences Survey, he compared trust and math skills across different countries. In high-income nations, cognitive ability was strongly tied to higher trust. In low-to-middle-income countries, the relationship was substantially weaker. </p>
<p>Like all observational studies, this research has some limitations. The primary issue is that the survey measured cognitive ability in adulthood, long after childhood environments had already shaped the participants. Because adult intelligence is a mix of genetic potential and environmental influence, it is difficult to completely separate the two. A disadvantaged environment might prevent a person from reaching their genetic potential, or it might simply suppress the social expression of the intelligence they do develop.</p>
<p>Future research will need to untangle these specific biological and environmental threads. Scientists could use genetically informed study designs to see how human biology and neighborhood conditions interact. Researchers also want to know if childhood environments alter the benefits of other positive traits. For example, patience and a willingness to take healthy risks might also be stunted by early adversity.</p>
<p>Ultimately, the study highlights a hidden mechanism of social inequality. Society often views education and intelligence as the ultimate tools for upward mobility. However, this research shows that a harsh childhood can prevent a person from using those tools effectively. Policies aimed at reducing inequality may need to focus on emotional security just as much as academic success.</p>
<p>“If we want to improve life chances, we need to think beyond academic skills,” Dawson said. “Stable, secure and supportive childhood environments may be just as important in helping people realise their potential.”</p>
<p>The study, “<a href="https://doi.org/10.1177/01461672261439412" target="_blank">What Childhood Leaves Behind: Cognitive Ability and Trust in Adulthood</a>,” was authored by Chris Dawson.</p></p>
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<td><a href="https://www.psypost.org/mind-wandering-enhances-the-brains-ability-to-learn-hidden-patterns-new-study-suggests/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Mind wandering enhances the brain’s ability to learn hidden patterns, new study suggests</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 16th 2026, 06:00</div>
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<p><p>When our thoughts drift away from the task at hand, our brains might actually become better at unconsciously picking up hidden patterns in our environment. A new study to be published in the journal <em><a href="https://academic.oup.com/nc" target="_blank">Neuroscience of Consciousness</a></em> provides evidence that the momentary lapses in self-control that occur during mind wandering create a unique mental state that enhances our ability to learn automatic routines. These findings suggest that daydreaming is not simply a failure of attention but a functional shift that helps the brain absorb complex information.</p>
<p>Mind wandering happens when our attention shifts from external tasks to internal thoughts, like reflecting on past events or planning for the weekend. This mental state is typically associated with reduced cognitive performance, including slower reading comprehension and an inability to maintain sustained attention. </p>
<p>At the same time, recent research suggests that this zoning out can provide unexpected cognitive benefits, particularly for a process known as implicit statistical learning. Implicit statistical learning is the brain’s ability to unconsciously detect and internalize repeating patterns and probabilities in our surroundings, such as the predictable structure of spoken language or the sequence of a physical action.</p>
<p>“Mind wandering is usually described as a failure of attention,” said <a href="https://nemethlab.com/" target="_blank">Dezső Németh</a>, a director of research at INSERM at the Centre de Recherche en Neurosciences de Lyon in France and <a href="https://gccognitive.es/" target="_blank">the Gran Canaria Cognitive Research Center</a> at Universidad del Atlántico Medio in Spain. “And in many situations, that is true. When our thoughts drift away from the task, we often make more mistakes, respond more impulsively, and lose track of what we are supposed to be doing.”</p>
<p>Németh explained that their <a href="https://doi.org/10.1016/j.isci.2024.111703" target="_blank">previous work</a> suggested a more complicated picture. “We found that mind wandering can sometimes be linked to better implicit statistical learning,” Németh said. “In other words, when people are not fully focused on the task, they may still be picking up hidden patterns in the environment, without being aware that they are learning.”</p>
<p>“That paradox fascinated us,” Németh continued. “We wanted to know whether these two effects are actually connected. Could the same temporary weakening of executive control that makes people worse at inhibiting responses also make the brain more open to learning probabilistic patterns in the background?”</p>
<p>A framework known as the neurocompetition model proposes that our brain’s effortful, goal-directed processes actually compete with our automatic, unconscious learning systems for shared mental resources. Executive control involves the top-down cognitive processes that allow us to focus, plan, and override impulses. “So are they independent phenomena or related?” Németh asked. “This study was designed to test that idea directly.”</p>
<p>To evaluate this complex interplay, the scientists recruited university students to complete an online experiment. After removing participants who did not follow instructions or met certain exclusion criteria, the final sample consisted of 240 healthy young adults with an average age of about 22. The participants completed a specialized exercise called the Cognitive Trade-off Task, which was designed to measure self-control, pattern recognition, and current state of mind simultaneously.</p>
<p>During the task, participants watched images of dog or cat heads appear in one of four horizontal positions on a computer screen. For the majority of the trials, known as “Go” trials, participants were instructed to quickly press a keyboard key corresponding to the location of the animal. However, for certain specific images, known as “No-Go” trials, participants had to suppress their urge to react and withhold their key press entirely. This specific measure evaluated response inhibition, which is the brain’s ability to quickly cancel or restrict an impulsive behavioral action.</p>
<p>Unbeknownst to the participants, the appearance of the images was not entirely random. The locations followed a hidden, probabilistic sequence where every second trial was part of a repeating pattern, while the alternate trials appeared in random locations. Because of this alternating structure, certain three-item sequences, known as triplets, happened much more frequently than others. By measuring how much faster participants responded to the highly probable triplets compared to the rare ones, the researchers could calculate a precise score for implicit statistical learning.</p>
<p>Across the entire task, there were 64 distinct possible triplets, but only 16 of these were high-probability sequences. In total, 62.5 percent of the trials ended in a high-probability sequence, while the remaining 37.5 percent ended in a low-probability sequence. This uneven distribution allowed the scientists to accurately track how the brain adapts to environmental predictability over time.</p>
<p>The entire experiment was divided into thirty smaller blocks, with each block containing 70 “Go” trials and 10 “No-Go” trials randomly distributed throughout the sequence. After each block, the participants answered a series of short questions about their mental state. They reported whether their attention was completely focused on the animal images or if their mind had wandered to unrelated thoughts. If they reported mind wandering, they answered additional questions about whether their thoughts were spontaneous, deliberate, positive, or negative.</p>
<p>The researchers found that as the task progressed, participants reported increasing amounts of mind wandering. During the periods when participants reported that their minds had wandered, their response inhibition significantly declined. They made more errors on the “No-Go” trials, demonstrating a temporary breakdown in top-down cognitive control.</p>
<p>At the same time, the participants demonstrated enhanced implicit statistical learning during those exact same periods of mind wandering. They became noticeably faster at responding to the high-probability patterns compared to the low-probability patterns when their minds were off-task. Most importantly, the researchers discovered that the relationship between mind wandering and pattern learning was dependent on the participants’ level of response inhibition.</p>
<p>“What surprised us most was not just that mind wandering was linked to better statistical learning,” Németh told PsyPost. “It was found that this benefit depended on inhibitory control. The learning advantage was strongest when response inhibition was weaker.”</p>
<p>The data showed that when response inhibition was at its weakest, the difference in reaction times between predictable and unpredictable patterns was the largest. “That finding is important because it suggests that these effects are not independent,” Németh explained. “Mind wandering, inhibitory control, and implicit learning seem to be dynamically related. When top-down control relaxes, the implicit learning system may have more room to operate.”</p>
<p>The findings provide evidence that the temporary suppression of executive control directly facilitates the automatic processing of environmental patterns. This relationship tends to validate the neurocompetition model, showing that relaxing conscious focus frees up resources for automatic pattern detection.</p>
<p>“The main message is that attention is not simply ‘good’ and mind wandering is not simply ‘bad,’” Németh said. “Of course, if you need to stop yourself from making an impulsive response, or if you need to complete a demanding task, staying focused matters. In our study, mind wandering was associated with poorer inhibitory control.”</p>
<p>However, the benefits to unconscious learning present a different side of the story. “At the same time, those same periods were linked to stronger implicit learning of hidden patterns,” Németh added. “This suggests that the brain may sometimes shift away from strict goal-directed control into a different mode. That mode may be less useful for immediate performance, but more useful for absorbing regularities in the background.”</p>
<p>Németh pointed out that this has an important implication for how we think about work and education. “Many modern tools and environments are designed to eliminate distraction completely: constant-engagement software, forced-focus settings, notification-free ‘deep work’ blocks, and similar approaches,” Németh noted. “These may improve short-term attentiveness, but they could also suppress the very cognitive state that helps people internalize deeper patterns, make connections, and learn in a less deliberate way.”</p>
<p>Balancing these mental states might be necessary for overall cognitive health. “So the takeaway is not that distraction is always good,” Németh said. “Rather, the mind may need a balance between focused control and more spontaneous, internally directed states. A brain that is always forced to stay ‘on task’ may be efficient in the short term, but not necessarily optimal for every kind of learning.”</p>
<p>This perspective reframes how we view everyday moments of distraction. “I think the broader implication is that cognitive ‘failures’ are not always failures in a simple sense,” Németh observed. “A lapse in executive control may be bad for one function, such as response inhibition, but it may open a window for another function, such as implicit learning.”</p>
<p>Instead of fighting every urge to daydream, people might recognize its hidden value. “So mind wandering is not an obstacle, but a functional component of human learning,” Németh said, referring to <a href="https://osf.io/preprints/psyarxiv/akh9r_v1" target="_blank">a related manuscript</a> by his team. “This kind of trade-off may help explain why mind wandering is so common in everyday life despite its obvious costs. The mind may drift not only because it fails to stay focused, but also because drifting can sometimes support another kind of learning.”</p>
<p>There are a few potential misinterpretations and limitations to consider. “The most important caveat is that our results should not be read as saying that mind wandering is always useful,” Németh warned. “It clearly has costs. In our study, participants were worse at stopping a response when their mind had wandered.”</p>
<p>Additionally, the task used in the experiment measures learning in a continuous and dynamic way, which makes it difficult to completely separate the initial acquisition of knowledge from the physical expression of that knowledge. It remains uncertain whether the drop in self-control actually helps the brain learn the patterns faster in the moment, or if it simply removes the mental brakes, allowing the body to automatically act out patterns it had already learned.</p>
<p>Another limitation is the method of measurement. “Another important point is that this was a behavioral study,” Németh explained. “We interpret the results in terms of a competition between executive control and implicit learning, but we did not directly measure the neural mechanisms in this experiment.”</p>
<p>To address this, the scientists plan to use tools like functional near-infrared spectroscopy, magnetoencephalography, and electroencephalography to track brain waves. “Future studies using EEG, MEG, fNIRS, or brain stimulation will be needed to test the brain mechanisms more directly,” Németh said.</p>
<p>The researchers have several goals for the future. “We have three main long-term goals,” Németh noted. “First, we want to understand the brain mechanisms behind this phenomenon more directly. For this, we are using methods such as EEG and fNIRS to examine how changes in brain states, including prefrontal activity and sleep-like slow oscillations during wakefulness, relate to mind wandering and implicit learning.”</p>
<p>The team also hopes to establish a direct cause-and-effect relationship. “Second, we want to move beyond correlation,” Németh said. “The present study shows that mind wandering, inhibitory control, and implicit learning are closely linked, but the next step is to test the causal mechanisms.”</p>
<p>To achieve this, the researchers are manipulating brain states directly. “We are now running experiments using non-invasive brain stimulation and partial sleep deprivation to see whether changing brain states can directly alter mind wandering and implicit learning,” Németh revealed. “These studies are already ongoing, and I hope we will have the first results by the end of this year.”</p>
<p>Finally, the researchers are looking at how this dynamic shifts across a person’s lifespan. “Third, we want to study this interaction from a developmental perspective,” Németh said. “The balance between executive control, mind wandering, sleep-like brain activity, and implicit learning may change across development. So we would like to compare younger children, older children, and adults to understand how this balance emerges and how it changes with age.”</p>
<p>The scientists also intend to investigate how this balance operates in people with specific neurodevelopmental or psychiatric traits, such as attention-deficit hyperactivity disorder or obsessive-compulsive disorder. “We also want to know whether similar mechanisms are relevant in clinical conditions, including ADHD-like or OCD-like traits, where the balance between cognitive control and predictive learning may be different,” Németh concluded.</p>
<p>The study, “<a href="https://www.biorxiv.org/content/10.1101/2025.08.05.668618v4" target="_blank">A functional trade-off between executive control and implicit statistical learning is dynamically gated by mind wandering</a>,” was authored by Teodóra Vékony, Bianka Brezóczki, Gábor Csifcsák, Dezső Németh, and Péter Simor.</p></p>
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<td><a href="https://www.psypost.org/artificial-intelligence-tools-answer-addiction-questions-accurately-but-lack-med/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Artificial intelligence tools answer addiction questions accurately but lack medical nuance</a>
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<p><p>Artificial intelligence chatbots regularly answer public queries about sensitive health topics such as addiction, providing mostly accurate but highly generalized information. A recent evaluation found that while chatbot responses align broadly with national guidelines, they often lack the situational details necessary for individualized health decisions. These descriptive findings were recently published in the journal <a href="https://doi.org/10.1016/j.drugalcdep.2026.113074"><i>Drug and Alcohol Dependence</i></a>.</p>
<p>Substance use disorder is a chronic medical condition defined by the compulsive use of drugs or alcohol despite adverse physical, social, or emotional consequences. The official medical diagnostic framework views the condition on a spectrum of severity rather than applying a binary label of addiction. This diagnosis reflects changes in brain function that lead to cravings, physical tolerance, and withdrawal symptoms. In the United States alone, nearly fifty million people over the age of twelve met the diagnostic criteria for this condition in recent health surveys.</p>
<p>Despite the availability of medical treatments, care for addiction remains heavily underutilized. Medical providers face institutional limitations, time constraints, and a lack of specific training regarding the condition. At the same time, the social stigma surrounding addiction causes many individuals to avoid seeking formal medical advice out of fear of judgment or legal repercussions.</p>
<p>People often turn to digital platforms as an initial, private step to gather health information. Chatbots offer immediate, anonymous responses without the perceived judgment of a clinical environment. However, the quality of this digitally generated medical guidance is not always reliable, especially for deeply stigmatized behavioral health conditions.</p>
<p>To better understand how these systems perform, researchers designed a study to evaluate the medical accuracy of artificial intelligence responses regarding addiction. Lead author Morgan Decker, a medical student, and senior author Lea Sacca, a public health researcher, conducted the work alongside a team at Florida Atlantic University. They collaborated with addiction medicine physicians and data scientists to assess the digital guidance.</p>
<p>The research team focused on fourteen frequently asked questions about substance use disorders. To build this list, they first asked the chatbot to generate a list of common questions that adults have about diagnosis, treatment, and recovery. The team then cross-referenced these outputs with actual frequently asked questions from major health organizations.</p>
<p>The benchmark organizations included the Centers for Disease Control and Prevention and the Substance Abuse and Mental Health Services Administration. The researchers also incorporated guidelines from the National Institute on Drug Abuse and the American Society of Addiction Medicine. This ensured the artificial intelligence answers would be measured against established best practices in the medical field.</p>
<p>Researchers entered the fourteen finalized questions into the software to gather its responses. They specifically utilized the updated fifth version of the application. To standardize the outputs, they applied settings that limit the model’s randomness, ensuring the answers remained consistent and factual rather than conversational.</p>
<p>Pairs of evaluators independently reviewed each generated answer in a blinded fashion. The rating pairs intentionally mixed training levels, pairing students with board-certified addiction specialists. They scored the responses on a four-point scale based on accuracy, precision, and appropriateness for a general audience. Any disagreements between the rater pairs were resolved through discussions with an additional senior expert.</p>
<p>The highest score on the scale indicated an excellent response requiring no further explanation. The next two tiers represented satisfactory answers that needed either minimal or moderate clinical explanation. The lowest score was reserved for unsatisfactory answers that contained incorrect or dangerously misleading information based on contemporary medical practices.</p>
<p>The evaluators found that none of the answers provided by the software were unsatisfactory. Three of the fourteen responses received an excellent rating. Nine answers were deemed satisfactory but required minimal elaboration. Two answers were satisfactory but needed moderate clinical elaboration.</p>
<p>The artificial intelligence performed best on straightforward definitional prompts. When asked about the signs and symptoms of a substance use disorder, it gave a highly accurate list that matched expert guidelines. It correctly noted cravings, withdrawal, and the inability to control use as primary indicators.</p>
<p>Another highly rated response addressed whether a relapse represents a failure. The software accurately emphasized that an eventual return to use does not mean a medical treatment has failed. Instead, it framed relapse as a normal part of the recovery process that might require an adjustment in medical strategy, matching the empathetic tone recommended by public health officials.</p>
<p>Many answers provided a broad summary but missed nuanced clinical examples. When asked about the risks of untreated addiction, the software correctly listed overdose, liver damage, and social isolation. However, it failed to mention the increased risks of various cancers and infectious diseases, which are major complications recognized by public health authorities.</p>
<p>In evaluating treatment options, the software accurately mentioned behavioral therapies and support groups. Yet it failed to identify specific medical therapies approved by the federal government for alcohol use disorder. It also provided vague advice about how to help a loved one, advising against enabling behaviors without explaining what enabling actually looks like in practice.</p>
<p>The software also fell short of providing actionable resources when asked where to seek treatment. It accurately identified primary care doctors, mental health professionals, and anonymous support groups as avenues for help. Unfortunately, it completely omitted centralized, government-supported tools like national helplines or specific website directories that provide immediate, confidential assistance based on geographic location.</p>
<p>More complex medical scenarios revealed greater gaps in the knowledge base of the software. When asked about managing withdrawal, the application correctly noted that physical symptoms occur when a dependent person stops using a substance. Yet it did not warn users that withdrawing from certain substances like alcohol or benzodiazepines can be fatal and requires immediate medical supervision.</p>
<p>The software also required moderate elaboration regarding treatment duration. It accurately stated that recovery timelines vary widely based on individual needs and the severity of the condition. While true, health organizations typically recommend a minimum of three months in a treatment program to achieve better recovery outcomes, a benchmark the software failed to mention.</p>
<p>The researchers point out several limitations in their methodology. The study relied on a subjective evaluation process by a specific group of medical professionals. Other clinical experts might grade the nuanced responses differently. Additionally, the researchers only tested a small sample of fourteen questions, which limits how broadly the results can summarize the capabilities of the software.</p>
<p>Using an artificial intelligence program to generate the initial list of questions may have introduced circular bias into the experiment. The software likely performs better on prompts that match its own structured, rational logic. Real patients often write prompts that are highly emotional, ambiguous, or poorly worded, which could generate very different guidance.</p>
<p>The researchers did not test how actual patients interpret or apply the digital advice in real life. Health literacy varies widely among the public. A scientifically accurate but highly generalized paragraph could still lead to confusion for someone unfamiliar with medical terminology, especially if they try to manage an addiction without a doctor.</p>
<p>Ethical concerns also surround the use of private medical data by technology companies. Substance use disorders often carry legal risks, and poorly protected digital searches could compromise patient privacy. The phrasing used by chatbots could also accidentally reinforce social prejudices if the software relies on biased training data.</p>
<p>Future studies should explore a wider variety of real-world patient queries drawn from online forums or clinic data. Researchers also recommend evaluating competing digital platforms to see if different corporate models offer better medical accuracy. Until these systems improve, human medical professionals remain necessary to contextualize digital health information safely.</p>
<p>The study, “<a href="https://doi.org/10.1016/j.drugalcdep.2026.113074">Descriptive content analysis assessment of ChatGPT responses to substance use disorder treatment questions compared to National health guidelines</a>,” was authored by Morgan Decker, Christine Kamm, Sara Burgoa, Meera Rao, Maria Mejia, Christine Ramdin, Adrienne Dean, Melodie Nasr, Lewis S. Nelson, and Lea Sacca.</p></p>
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<td><a href="https://www.psypost.org/digital-voter-suppression-ads-tied-to-lower-election-turnout/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Digital voter suppression ads tied to lower election turnout among specific demographic groups</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 15th 2026, 20:00</div>
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<p><p>Digital advertisements designed to discourage voting were heavily aimed at specific demographic groups during the 2016 United States presidential election. People who saw these undisclosed political advertisements were less likely to cast a ballot compared to those who did not. The research, published in <a href="https://doi.org/10.1073/pnas.2519944123"><i>PNAS</i></a>, presents real-world data connecting personalized social media messaging to offline voting behavior.</p>
<p>Political campaigns have a history of trying to demobilize selected segments of the population. This practice is known as voter suppression. It involves targeted strategies intended to discourage or prevent opposing demographic groups from casting ballots. </p>
<p>Historically, voter suppression manifested through physical intimidation or strict localized regulations. In previous eras, tactics included regulatory devices such as poll taxes, stringent identification laws, and deliberately confusing information about polling locations. Today, these targeted efforts have increasingly shifted to the digital sphere. Modern platforms operate on customized feed algorithms that allow messages to reach specific individuals.</p>
<p>Advertisers use microtargeting to reach these specific audiences online. They rely on vast amounts of data regarding user interests, geographic locations, and demographic backgrounds. Social media companies package this data into consumer categories, which allows political groups to deliver customized messages to very narrow slices of the public. </p>
<p>Government reports later showed that Russian operatives purchased platform advertisements using historical search terms associated with the African American Civil Rights Movement to find targeted users in 2016. Many of these digital strategies operate in regulatory blind spots. The messages frequently come from undisclosed campaigns that do not file financial reports with traditional tax agencies or federal election regulators. Because these sponsors remain anonymous, misleading election content can spread unchecked across social networks. </p>
<p>Measuring exactly who saw specific advertisements and tracking whether those people voted is extremely difficult. Most prior studies relied on computer simulations or asked people to self report their voting histories, which can be inaccurate. Young Mie Kim, a media researcher at the University of Wisconsin Madison, recognized this gap in the research.</p>
<p>She worked with Ross Dahlke, Hyebin Song, and Richard Heinrich to design an observational study measuring direct exposure to anonymous negative election advertisements. The team wanted to know exactly who received these messages. They also sought to evaluate whether the visual exposure was tied to actual turnout at the ballot box. </p>
<p>To monitor advertising exposure, the researchers asked thousands of volunteers to install a custom digital tracking application. The tracking program functioned similarly to a conventional ad blocker. Instead of blocking the promotional content, the program cataloged each advertisement and its associated data on a secure research server. During the six weeks leading up to the 2016 election, the application recorded every political advertisement displayed on the participants’ social media feeds. </p>
<p>A major challenge in studying social media influence is accounting for user choices, often called self selection bias. When individuals browse unpaid posts on social networks, they actively select which accounts to follow and interact with. This mechanism makes it difficult to separate preexisting political beliefs from the influence of new information. </p>
<p>Digital advertisements operate differently because they are delivered solely based on algorithmic targeting rather than user subscriptions. A person encounters a promotional message simply because the sponsor paid to put it in their feed. By analyzing these forced exposures, the researchers could remove self selection from the equation, adding validity to their measurements of electoral influence. </p>
<p>The researchers also asked the participants to complete a survey about their political leanings and demographic backgrounds. Following the election, the team partnered with external data firms to link these profile surveys and advertisement logs with official localized voting records. This allowed the researchers to confirm whether a person actually voted without having to rely on the individual’s memory. </p>
<p>Kim and her colleagues reviewed the collected advertisements to identify specific forms of voter suppression messages. They looked for content encouraging election boycotts or promoting third party candidates primarily to split votes. For the central statistical analysis, the team isolated tens of thousands of messages sponsored by anonymous entities. </p>
<p>The researchers identified common themes utilized by the anonymous sponsors. Campaigns often spread deceptive information about voting mechanics, such as telling users they could vote from home using a text message or social media post. These tactics were built directly upon historic efforts to depress voter turnout, tailored to modern digital consumption habits. </p>
<p>The research team documented a highly specific pattern of distribution for these advertisements. Non-White voters residing in counties with high populations of racial minorities within battleground states received a disproportionate volume of negative voting messages. The data showed that these specific demographic and geographic groups were intensely targeted compared to white voters living in less competitive electoral regions. </p>
<p>To estimate the effect on voting behavior, the researchers used a statistical adjustment technique known as entropy balancing. This method creates groups of exposed and unexposed people with closely matching traits. By pairing individuals who shared the exact same age, income, education, and political ideology, the researchers could compare variations in their final voting habits. Since the exposure happened before the election, the timeline ensures the advertisements preceded the voting behavior. </p>
<p>Across the entire sample population, exposure to voter suppression advertisements was connected to lower voter turnout. On average, the voting rate of people exposed to the advertisements was about two percent lower than those who never saw the messages. Several battleground states in 2016 were decided by margins of less than one percent, meaning even subtle shifts in voter participation could alter final electoral outcomes. </p>
<p>The researchers noted an even larger drop in turnout among the specific groups tracked most heavily by the targeted algorithms. Non-White voters living in minority population centers within battleground states experienced the largest declines in voting rates after exposure. The targeted subpopulation saw a voting drop of roughly 14 percent compared to counterparts who did not encounter the negative election messages. This indicates that the advertisements had distinct and varied effects depending on the demographic profile of the matched audience. </p>
<p>To verify their work, the researchers tested the data against multiple control groups. They compared the targeted subjects with voters who interacted with generic political messaging and voters who saw no political advertisements at all. The patterns of suppressed turnout remained consistent across the different groups. The researchers also noted that people exposed to positive political advertising saw slight increases in total turnout, highlighting the unique depressive effect of the suppression messages. </p>
<p>The study relies entirely on observational data rather than an actively manipulated, randomized experiment. Although the researchers used matching techniques to account for confounding variables like income and political ideology, unknown factors could still theoretically influence the results. A person’s local community environment, for instance, might impact their decision to visit a polling location on election day. Consequently, the team advises caution when making direct causal assumptions about the digital advertisements and individual voting decisions. </p>
<p>The results are also specific to the political context of the 2016 presidential contest, as the digital advertising landscape and social media moderation policies shift continuously with each election cycle. Future observational research could focus on other election periods to build a more comprehensive understanding of how customized online messaging affects localized voting habits. The study, “<a href="https://doi.org/10.1073/pnas.2519944123">Targeted digital voter suppression efforts likely decrease voter turnout</a>,” was authored by Young Mie Kim, Ross Dahlke, Hyebin Song, and Richard Heinrich.</p></p>
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<td><a href="https://www.psypost.org/rising-temperatures-are-deterring-new-arrivals-rather-than-pushing-residents-out/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Rising temperatures are deterring new arrivals rather than pushing residents out</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 15th 2026, 18:00</div>
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<p><p>As global temperatures rise, many people assume that worsening heat will drive residents to abandon warming regions in large numbers. However, new research published in the journal <em><a href="https://www.mdpi.com/2071-1050/18/4/2040" target="_blank">Sustainability</a> </em>reveals that higher temperatures alone are not prompting mass relocations in the United States, but rather slowing the rate of new arrivals to unusually hot areas. These results suggest that economic opportunities and housing conditions shape human mobility far more than gradual climate changes do.</p>
<p>Research into climate adaptation typically focuses on large government policies or municipal infrastructure projects. Less attention is given to how individual households adapt to gradual environmental shifts, such as rising average temperatures or prolonged droughts. These slow-moving changes increase financial burdens by raising utility bills and insurance premiums. </p>
<p>Over time, such creeping expenses can stress household budgets and affect physical health. Researchers wanted to understand if these persistent temperature anomalies prompt people to pack up and leave their communities. A temperature anomaly is simply the difference between current temperatures and a long-term historical average. </p>
<p>Previous research often looked at rapid disasters like hurricanes or wildfires. Studying slow-onset temperature changes offers a different perspective on how families manage environmental risk. If people move away from slowly warming areas, policymakers need to plan for shifting tax bases and changing infrastructure needs. </p>
<p>Yanmei Li, an associate professor of urban and regional planning at Florida Atlantic University, led the investigation. Li and her co-author, Diana Mitsova, a professor in the same department, suspected that household moves might be constrained by local economic realities. They aimed to see if a specific temperature threshold exists that triggers widespread relocation.</p>
<p>To investigate these patterns, the researchers examined county-to-county migration records from the Internal Revenue Service for the year 2021. This tax data tracks where people move by comparing their filing addresses from one year to the next. The team focused on the contiguous United States, looking at out-migration, in-migration, and net migration rates for each county.</p>
<p>They compared this migration data against temperature records from the National Oceanic and Atmospheric Administration. Specifically, they looked at average temperature anomalies from 2017 to 2021 compared to a baseline period of 1901 to 2000. They also factored in local socioeconomic details, such as housing costs, poverty rates, and education levels, using census data.</p>
<p>The researchers utilized spatial regression models, which are statistical tools that account for geographical patterns and neighborhood effects. These models helped them separate the influence of temperature from other factors like a booming local job market or high housing vacancy rates. They also used a technique called spline analysis to look for potential tipping points where a certain amount of warming might suddenly change migration habits.</p>
<p>The results challenged common assumptions about climate-driven relocation. In the statistical models, the estimated impacts of temperature anomalies on all three migration outcomes were not statistically significant. This means that once housing and economic factors are considered, temperature changes alone do not clearly predict population shifts.</p>
<p>Instead of pushing people away, moderate temperature anomalies were associated with slightly lower rates of out-migration. This pattern hints at a situation where vulnerable households become trapped. Worsening environmental conditions can drain personal finances, making it too expensive for people to afford the costs of moving. </p>
<p>The relationship between temperature and mobility did change slightly in areas with high poverty. In poorer counties, rising temperatures were linked to higher out-migration rates. This suggests that households with fewer resources might eventually be displaced when environmental stress compounds existing economic hardships.</p>
<p>When looking at extreme temperature anomalies, the researchers found a different trend. Rather than causing current residents to flee, extreme heat primarily reduced the number of new people moving in. Counties experiencing the most severe temperature increases received fewer in-migrants, which slowed their overall population growth.</p>
<p>Despite these warming trends, traditional migration magnets in the Sun Belt continue to grow rapidly. Growing metropolitan areas in states like Texas, Florida, and Arizona remain popular destinations. People continue to flock to these regions for jobs, affordable housing, and lifestyle amenities, even though these same areas show some of the highest temperature anomalies in the country.</p>
<p>Li noted that the dynamics of human relocation are heavily tied to local appeal. “As extreme temperature anomalies increase, we don’t see more people leaving,” Li said. </p>
<p>She added that this shift alters how we should view climate-related population changes. “It’s less about people being pushed out and more about places becoming less attractive,” Li explained. “At the same time, consistently warm climates still draw people, highlighting a contrast between steady warmth and extreme heat.”</p>
<p>The analysis also searched for a specific temperature tipping point that might trigger a sudden exodus. The models indicated a possible shift in migration behavior when warming exceeds about 2.6 degrees Fahrenheit above historical averages. Even beyond this point, the changes in migration remained relatively small and were not statistically significant.</p>
<p>Mitsova pointed out that while current responses are mild, the future might look different. “The absence of strong effects today does not mean climate will remain a minor factor,” Mitsova said. “Our findings suggest that stronger migration responses could emerge in the future, particularly as rising temperatures interact with extreme events, long-term exposure, or constraints such as housing availability and insurance markets.”</p>
<p>The study does carry a few limitations. Because the researchers only looked at migration data from a single year, they cannot track how long-term exposure to heat influences relocation over a decade or more. Using county-level information might also mask hyper-local differences, as a single county can contain both wealthy, resilient neighborhoods and highly vulnerable communities.</p>
<p>People base their decisions to move on a tangle of overlapping reasons. A new job, a desire for a larger home, or proximity to family often outweigh concerns about local climate anomalies. These powerful social and economic drivers can easily obscure the subtle influence of gradual environmental change in broad statistical models.</p>
<p>Future research should investigate how cumulative exposure to slow-onset climate changes affects families over longer periods. Scientists could also incorporate data on specific hazards, such as the rising cost of flood insurance or the frequency of nearby wildfires. Conducting surveys directly with individual households would also help clarify exactly how environmental worries factor into their decisions to stay or leave.</p>
<p>Addressing these questions will help municipal planners prepare for the future. By understanding the real barriers to relocation, governments can focus on local resilience strategies. Upgrading infrastructure and assisting low-income households with energy costs might prove more effective than bracing for an unlikely wave of mass climate migration.</p>
<p>The study, “<a href="https://www.mdpi.com/2071-1050/18/4/2040" target="_blank">Temperature Anomaly and Residential Mobility: Spatial Patterns, Tipping Points, and Implications for Sustainable Adaptation</a>,” was authored by Yanmei Li and Diana Mitsova.</p></p>
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<td><a href="https://www.psypost.org/autistic-adults-face-higher-risk-of-certain-types-of-sexual-victimization-study-finds/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Autistic adults face higher risk of certain types of sexual victimization, study finds</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 15th 2026, 16:00</div>
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<p><p>A recent study published in <em><a href="https://doi.org/10.1080/00224499.2026.2645037" target="_blank">The Journal of Sex Research</a></em> suggests that adults with autism experience higher rates of certain types of sexual victimization compared to those without the diagnosis. The findings indicate that these vulnerabilities might be linked to specific sensory sensitivities rather than just the official diagnostic label itself. This provides evidence that tailored education programs focusing on consent and sensory regulation could help protect people with varying levels of autistic traits.</p>
<p>Scientists Brianna M. Akers and Zoë D. Peterson conducted the study to gain a more accurate understanding of how often autistic adults experience different forms of sexual harm. Akers is a counseling psychology doctoral student at Indiana University Bloomington and the Kinsey Institute. Peterson is a professor of applied psychology and director of the Sexual Assault Research Initiative at the Kinsey Institute.</p>
<p>“Across the globe, many people report nonconsensual sexual experiences (i.e., sexual victimization), and that is no different here in the U.S.,” Akers told PsyPost. “I have long been interested in ability status, particularly how this identity shapes the way a person moves through the world and how others perceive and treat them.”</p>
<p>Akers noted that past research indicates autistic individuals are disproportionately affected by nonconsensual sexual experiences. “Existing research suggests that autistic individuals are at an increased risk for experiencing sexual victimization, but there are still gaps in our understanding of which specific types of sexual victimization are most common in this population,” Akers said. “We wanted to conduct this study in the hopes that the findings could help better inform advocacy efforts, prevention programming, and survivor services offered to individuals with autism.”</p>
<p>To respect the diverse community they were studying, the researchers intentionally varied their terminology throughout their work. “One additional thing we would like to note is that language preferences around ability status have fluctuated over time and continue to vary across individuals,” Akers said. “Some people prefer identity-first language, such as ‘autistic person,’ while others prefer person-first language, such as ‘person with autism.’ Because our participants expressed varied preferences, we used both forms when writing the original research article and have continued to do so in these responses as a way to honor their preferences.”</p>
<p>To conduct the study, the researchers recruited adults living in the United States through an online participant platform. The final sample consisted of 663 individuals who were at least 18 years old. Participants were sorted into three distinct groups based on their self-reported diagnostic status. </p>
<p>The first group included 287 individuals who had received a formal clinical diagnosis of autism from a medical professional. The second group consisted of 270 participants who did not have an autism diagnosis. The third group was an exploratory category of 106 individuals who suspected they might have autism but had never received a formal diagnosis, which the authors refer to as a subclinical group. </p>
<p>Participants completed a 20-minute online survey for which they were paid four dollars. The primary measure was a newly revised 2024 version of a widely used questionnaire designed to assess experiences of sexual victimization since the age of 14. This tool breaks down unwanted sexual experiences into four distinct categories so researchers can evaluate the specific tactics used by perpetrators. </p>
<p>The first category measured noncontact sexual victimization, which includes behaviors like verbal harassment or someone exposing themselves without consent. The second category assessed technology-facilitated victimization, such as receiving unwanted sexual images or having intimate photos shared online without permission. The third category covered illegal acts, which involves perpetrators using physical force, verbal threats, or intoxicating substances to obtain sexual contact. The final category measured verbal pressure, which involves a perpetrator using persistent insults, anger, or manipulation to coerce someone into a sexual act.</p>
<p>Participants also completed a 14-question screening tool designed to evaluate symptoms typically associated with autism in adults. This questionnaire asked participants to rate their experiences with social anxiety, difficulties in reading social cues, and sensory reactivity. Sensory reactivity refers to a person’s physical responses to external stimuli, such as feeling overwhelmed by loud noises, bright lights, or unexpected touch. </p>
<p>The scientists found that sexual victimization was highly prevalent across all three groups in the study. When comparing the groups, the researchers discovered that an autism diagnosis was significantly associated with a higher likelihood of experiencing certain types of victimization. </p>
<p>“In our study, sexual victimization was commonly reported across all of our participants, but participants with autism were more likely to report two types of experiences,” Akers said. “First, they were more likely to report in-person sexual experiences where no touching occurred, such as being cat-called or stared at in a sexual way. Second, they were more likely to report sexual touch or penetration that involved force, threats, or situations where they were unable to consent, such as being drunk, high, or asleep.”</p>
<p>The study did not find significant differences between the formally diagnosed group and the non-autistic group when it came to technology-facilitated or verbally pressured victimization. </p>
<p>“Interestingly, autistic participants were just as likely as participants without autism to report technology-facilitated sexual victimization, such as receiving unwanted sexual images, or verbal pressure sexual victimization, such as being pressured into sex through guilt or repeated requests,” Akers said. “This means that, when we talk about sexual victimization risk within this population, we should be specific about the types of sexual victimization we are discussing, rather than assuming autistic individuals are at higher risk for all forms equally.”</p>
<p>Across all four categories, women were consistently at a higher risk of victimization than men, regardless of their diagnostic status. Older age also tended to slightly increase the likelihood of experiencing illegal acts and verbal pressure.</p>
<p>The researchers found that individuals in the exploratory group who suspected they had autism reported victimization rates that were similar to those with a formal diagnosis. This suggests that the vulnerability to sexual harm extends beyond a formal medical label. </p>
<p>“One finding that surprised us was related to our participants who thought they might be autistic but had never received a formal diagnosis,” Akers said. “In our study, these participants reported similar levels of sexual victimization as participants with a formal autism diagnosis across all the types of victimization we measured.”</p>
<p>This pattern is particularly relevant for certain demographics that tend to be left out of traditional medical models. “This felt especially important because autism has historically been underdiagnosed in women, and women are also disproportionately impacted by sexual victimization,” Akers said. “To us, this suggests that when access to tailored prevention programming and survivor support depends too heavily on formal diagnostic status, we may overlook a large group of people who could benefit from these services just as much.”</p>
<p>To test the idea that specific traits influence risk, the authors looked at the scores from the 14-question autism symptom screening tool. They found that the sensory reactivity score was consistently associated with all four forms of sexual victimization. The association was particularly strong for noncontact victimization, indicating that heightened sensitivity plays a major role in a person’s risk level. </p>
<p>Heightened sensory reactivity is a common trait in autism where intense stimuli can trigger a temporary emotional and physical shutdown. The authors note that when individuals feel paralyzed or overwhelmed by their senses, they might be unable to process risk cues or remove themselves from a threatening situation. This physical and mental overload could impair a person’s ability to assert boundaries, which tends to increase their vulnerability to predatory behavior.</p>
<p>While these findings provide insights into sexual victimization, the authors outline a few limitations to keep in mind. Foremost, they want to ensure the relationship between the condition and the experiences is not misunderstood. </p>
<p>“It is important to us that readers of our paper do not leave with the understanding that autism causes sexual victimization to occur,” Akers said. “Nonconsensual sexual experiences are not the fault of the survivor and always the responsibility of the person who enacts the harm. However, our study findings are consistent with previous research that suggests there is a link between autism and sexual victimization, and the more we learn about that link, the better informed our prevention programming will be.”</p>
<p>Because the study relied on an online platform for recruitment, the sample likely overrepresents autistic individuals with high verbal skills, cognitive abilities, and reliable internet access. </p>
<p>“Additionally, our study recruited participants from an online survey platform, meaning that our results might not fully represent the sexual victimization experiences for all autistic people, especially those with higher support needs,” Akers said.</p>
<p>Another limitation is that the autism diagnoses were self-reported by the participants and not verified through medical records. The researchers used a validated screening tool to support the participants’ claims, but the lack of formal diagnostic confirmation leaves room for potential inaccuracies. </p>
<p>The authors suggest that future research should focus on recruiting individuals across the full spectrum of autistic traits, including those with higher support needs. Scientists should also explore how other specific traits might influence vulnerability to sexual harm, such as cognitive rigidity, which is a difficulty in adapting to new situations. </p>
<p>The findings highlight a need for inclusive, sensory-friendly sexual health education programs. Making these educational resources available to everyone, including those with subclinical autistic traits, could help reduce the high rates of sexual victimization seen in these populations.</p>
<p>The study, “<a href="https://doi.org/10.1080/00224499.2026.2645037" target="_blank">Comparing Prevalence of Multiple Types of Sexual Victimization Among Individuals with and without an Autism Spectrum Disorder Diagnosis</a>,” was authored by Brianna M. Akers and Zoë D. Peterson.</p></p>
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<td><a href="https://www.psypost.org/eating-a-diet-rich-in-four-key-nutrients-is-linked-to-a-lower-likelihood-of-depression-study-finds/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Eating a diet rich in four key nutrients is linked to a lower likelihood of depression, study finds</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 15th 2026, 14:00</div>
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<p><p>A recent study published in the journal <em><a href="https://doi.org/10.1016/j.nupsyc.2026.100019" target="_blank">Nutritional Psychiatry</a></em> suggests that consuming higher amounts of specific dietary nutrients, like fiber and folate, is associated with a lower likelihood of experiencing depressive symptoms. The findings provide evidence that everyday dietary choices might play an underlying role in supporting mental health and managing mood. This research adds to a growing scientific interest in how the foods we eat might help reduce the risk of mental health conditions.</p>
<p>Depression is a highly prevalent mental health condition that affects hundreds of millions of people globally. The economic and personal impacts of depression are massive, leading to lost productivity and steep healthcare costs. Current pharmacological and psychological treatments do not work adequately for everyone experiencing depression. Because standard therapies leave a gap in care, scientists are actively searching for complementary strategies to prevent and manage the condition.</p>
<p>In recent years, the scientific community has shown increased interest in nutritional psychiatry. This is an area of study that examines how dietary habits and specific vitamins or minerals affect brain health. Even though the human brain accounts for a very small fraction of total body weight, it consumes a large portion of our daily energy. The brain requires specific nutrients to produce chemicals that regulate mood and to manage inflammation.</p>
<p>“Nutritional psychiatry has grown rapidly over the past decade, but most existing evidence has focused on single nutrients or on specific dietary patterns such as the Mediterranean diet,” said study author <a href="https://orcid.org/0009-0000-3862-110X" target="_blank">Takayuki Fujii</a>, an assistant professor in the Department of Nursing at Yasuda Women’s University in Japan and a clinical psychologist. “We wanted to take a broader look at multiple nutrients simultaneously in a large U.S. adult sample, using a standardized depression screening tool (the PHQ-9),” Fujii explained. </p>
<p>To do this, the authors analyzed data from the National Health and Nutrition Examination Survey. This is an ongoing public health project that tracks the health and nutritional status of adults and children in the United States. “NHANES gave us a useful platform for examining these associations across a wide range of adults,” Fujii added. The researchers looked specifically at the 2017 to 2018 survey cycle, and their final analysis included 5,068 adults who were at least 18 years old.</p>
<p>To measure mental health, the researchers used the Patient Health Questionnaire-9. This is a standard nine-item survey that asks individuals to rate how often they have experienced symptoms of depression over the past two weeks. Participants answer on a scale ranging from “not at all” to “nearly every day.” A total score of ten or higher on this survey generally indicates clinically significant depression. </p>
<p>To measure dietary intake, trained interviewers asked the participants to detail everything they had consumed over a 24-hour period. This interview process was conducted twice for each participant. The scientists then calculated a two-day average of these food diaries to get a more accurate representation of each person’s typical diet. They focused on several specific nutrients, including dietary fiber, folate, magnesium, selenium, zinc, and vitamins B6, B12, and D.</p>
<p>When running their mathematical models, the authors accounted for several personal characteristics that might influence the results. They adjusted their calculations for age, sex, body mass index, smoking status, and total daily calorie intake. Body mass index is a common measurement of body fat based on a person’s height and weight. By including these factors, the researchers attempted to isolate the specific relationship between the nutrients and the participants’ mood.</p>
<p>Based on the survey scores, the researchers found that 9.1 percent of the participants were experiencing clinically significant depression. When analyzing the dietary data, the scientists noticed distinct differences between those with and without depression. Participants with depression consumed significantly lower amounts of dietary fiber, folate, magnesium, and selenium. </p>
<p>“Among U.S. adults in our analytic sample, those with higher intakes of dietary fiber, folate, magnesium, and selenium had lower odds of clinically relevant depressive symptoms (PHQ-9 ≥ 10) in our fully adjusted primary model,” Fujii told PsyPost. “These nutrients are abundant in foods such as whole grains, legumes, leafy greens, nuts, seeds, and seafood, essentially the staples of a Mediterranean-style diet.”</p>
<p>Folate, a nutrient naturally found in foods like leafy green vegetables and beans, showed the strongest inverse association. For every standard unit increase in folate intake, the odds of having depression dropped by 28 percent. A standard unit increase is a statistical tool used to show how much a value differs from the average of the group. Similar protective associations were seen with the other nutrients. </p>
<p>The researchers also observed a dose-response relationship for these four nutrients. A dose-response relationship occurs when increasing amounts of a substance are linked to increasingly stronger outcomes. Participants who consumed the highest amounts of folate had a 45 percent lower risk of depression compared to those who consumed the lowest amounts. </p>
<p>“The consistency across four nutrients with distinct biological roles was striking in our primary models,” Fujii noted. “The picture became more nuanced in our extended sensitivity analyses, however: fiber and folate were the most consistent signals. They remained significantly associated with lower depression odds across our extended unweighted models, and their point estimates stayed in the protective direction even in the most heavily adjusted survey-weighted analyses.” Point estimates are the specific numbers calculated by the researchers’ statistical models to represent the most likely effect.</p>
<p>When the authors ran secondary tests that included extra lifestyle variables, the results for some nutrients changed. “By contrast, magnesium and selenium were less robust,” Fujii explained. “Magnesium lost statistical significance once we added further covariates (poverty-income ratio, physical activity, and alcohol use), and selenium attenuated under both that adjustment and when NHANES survey weights were applied. That was a useful reminder that observational nutrition findings can be quite sensitive to analytic choices.”</p>
<p>Biologically, there are several ways these nutrients might support mental health. Dietary fiber is broken down by bacteria in the digestive system to produce short-chain fatty acids. This process is part of the gut-brain axis, a communication network between the digestive system and the brain. These fatty acids can travel to the brain and help reduce inflammation. </p>
<p>Folate is required by the body to produce important brain chemicals like serotonin and dopamine, which heavily influence mood. Magnesium acts on specific pathways in the nervous system and helps block certain receptors in the brain that are linked to depression. However, the researchers emphasize that these biological processes do not mean people should immediately buy nutrient pills.</p>
<p>“The practical takeaway is not to chase supplements but to consider that diverse, whole-food eating patterns may be one of several modifiable factors relevant to mental wellbeing,” Fujii said. “It’s also worth noting that the average fiber intake in our sample was about 16.6 g/day, well below the 25-38 g/day generally recommended, so there is real room for improvement in U.S. diets.”</p>
<p>But the study, like all research, has some limitations. The study captured a single snapshot in time, which makes it impossible to prove that low nutrient intake directly causes depression. “The most important is the cross-sectional design: we cannot determine whether lower nutrient intake contributes to depressive symptoms, whether depressive symptoms reduce intake of nutrient-dense foods, or both,” Fujii explained. </p>
<p>“We deliberately use associative, not causal, language throughout the paper, and I would ask readers to do the same,” Fujii said. “The effect sizes were also modest (Cohen’s d roughly 0.16-0.25 in unadjusted comparisons; odds ratios of 0.72-0.81 per 1-SD increase in the fully adjusted primary model), so these are not large effects.” Cohen’s d and odds ratios are mathematical measurements used to describe the strength of a relationship between two variables.</p>
<p>“Dietary intake was captured by 24-hour recalls, which are subject to measurement error and do not necessarily reflect long-term habits,” Fujii said. “The analysis also used a single NHANES cycle (2017-2018), and replication in pooled multi-cycle data is warranted. Finally, our findings should not be read as a recommendation to take specific supplements, the evidence here is about nutrients consumed as part of a varied diet.”</p>
<p>Moving forward, the scientists hope to track participants over several years. Following individuals over a long period would provide better evidence regarding whether dietary habits actively manage depression. </p>
<p>“We would like to extend this work using longitudinal data to better address temporality, examine overall dietary patterns rather than only individual nutrients, and explore whether the associations differ across population subgroups, depression subtypes (e.g., melancholic vs. atypical), or among individuals with treatment-resistant depression, a group of particular interest given that roughly one-third of patients with major depression do not respond adequately to conventional treatments,” Fujii said.</p>
<p>Overall, the authors recommend interpreting the findings cautiously and not viewing dietary changes as a replacement for standard medical care. People should also consider the broader socioeconomic factors that influence dietary choices.</p>
<p>“Diet is one of many modifiable factors associated with mental health, and our findings should be seen as one piece of a much larger picture,” Fujii concluded. “Anyone experiencing depressive symptoms should consult a qualified clinician rather than making major changes based on any single study. Access matters too: nutrient-dense foods are not equally affordable or available to everyone, and any conversation about diet and mental health needs to take socioeconomic disparities and food access into account.”</p>
<p>The study, “<a href="https://doi.org/10.1016/j.nupsyc.2026.100019" target="_blank">Association between depressive symptoms and multiple nutrient intakes in US adults: A cross-sectional study using NHANES 2017-2018</a>,” was authored by Takayuki Fujii, Taiga Seo, and Yuji Nogami.</p></p>
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<td><a href="https://www.psypost.org/common-air-pollutants-are-linked-to-higher-risks-of-lewy-body-and-parkinsons-dementias/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Common air pollutants are linked to higher risks of Lewy body and Parkinson’s dementias</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 15th 2026, 12:00</div>
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<p><p>Breathing in common air pollutants over many years may substantially raise a person’s risk of developing certain neurodegenerative diseases, pointing to an environmental driver for cognitive decline. A new study published in <em><a href="https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2849005" target="_blank">JAMA Network Open</a></em> found that prolonged exposure to fine particulate matter and nitrogen dioxide is linked to higher rates of Lewy body dementia and Parkinson’s disease dementia. These results suggest that improving air quality could serve as a preventative measure to protect brain health in aging populations.</p>
<p>Lewy body dementia and Parkinson’s disease dementia are related neurological conditions that severely impact memory, thinking, and behavior. Both disorders involve the abnormal buildup of a specific protein called alpha-synuclein in the brain. Proteins are the microscopic structures that carry out essential functions inside our cells. When these proteins misfold and clump together, they disrupt normal cellular activity and eventually cause brain cells to die.</p>
<p>In Lewy body dementia, these protein clumps typically cause early cognitive problems, visual hallucinations, and unpredictable shifts in alertness. In Parkinson’s disease, the damage initially affects movement, causing tremors and stiffness, but many patients eventually develop dementia as the disease spreads through the brain. Researchers want to identify environmental triggers that might cause this destructive protein buildup. If external factors contribute to these diseases, modifying our environment might help prevent the onset of symptoms.</p>
<p>Dimitry S. Davydow, a psychiatrist and researcher at the University of Florida College of Medicine, led the investigation into these environmental factors. He collaborated with Gregory M. Pontone, a psychiatrist at the University of Florida, along with a team of environmental scientists and epidemiologists from Aarhus University in Denmark. They aimed to track pollution exposure over a long period to see how it affected older adults. The research team focused specifically on two ubiquitous pollutants found in nearly all modern cities.</p>
<p>The first pollutant, fine particulate matter, consists of tiny airborne particles that are much thinner than a single human hair. Because they are so small, these particles can be inhaled deep into the lungs and easily pass into the bloodstream. The second pollutant is nitrogen dioxide, a toxic, reddish-brown gas. Both of these substances are primarily generated by combustion processes, such as the burning of fossil fuels in car engines and power plants.</p>
<p>The brain is usually protected from harmful substances in the blood by a strict biological filter known as the blood-brain barrier. Some incredibly small particles and gases can bypass this defense system and enter brain tissue directly. Once inside, these pollutants might trigger an aggressive immune response from the brain’s defense cells. Chronic inflammation resulting from this immune response can damage neurons and potentially encourage proteins to misfold.</p>
<p>Another possible entry point for these pollutants is the human nose. The olfactory system, which handles the sense of smell, provides a direct neural path from the outside environment to the brain. People who develop Lewy body dementia or Parkinson’s disease often lose their sense of smell early in the disease process. High levels of air pollution are also associated with a weakened ability to smell, suggesting the nasal cavity could be a gateway for toxic particles.</p>
<p>To investigate these patterns, the research team analyzed national health and population records from Denmark. They gathered de-identified data covering more than two million Danish citizens aged 65 to 95 between the years 2001 and 2021. Denmark maintains comprehensive health registries that track medical diagnoses and residential addresses for its entire population. This detailed record-keeping allowed the researchers to look far back into the patients’ lives with high accuracy.</p>
<p>From this massive dataset, the researchers identified just over 3,000 people diagnosed with Lewy body dementia. They also found about 3,800 individuals diagnosed with Parkinson’s disease dementia. The investigators matched each of these patients with ten control subjects who did not have either condition. The control subjects were chosen to be the exact same sex and born within fourteen days of the patients they were matched with.</p>
<p>Next, the team had to calculate how much pollution each person had breathed in over time. They used a high-resolution mapping system that models air pollution levels across Denmark on a very localized scale. By combining this environmental data with the historical residential addresses of the subjects, they calculated a ten-year average exposure for each person. This average covered the entire decade right before a dementia diagnosis was recorded.</p>
<p>The researchers adjusted their statistical models to account for a wide variety of background factors that might influence brain health. They included the socioeconomic status of the individuals, such as their highest level of education, employment status, and income bracket. They also factored in the general economic conditions of the subjects’ immediate neighborhoods. Finally, they included detailed medical histories, taking into account other physical illnesses and prior psychiatric conditions.</p>
<p>The data revealed a clear connection between higher pollution levels and increased dementia risk. For every small incremental increase in the concentration of fine particulate matter, the risk of developing Lewy body dementia nearly quadrupled. The same incremental increase in this particulate matter was associated with more than double the risk of developing Parkinson’s disease dementia.</p>
<p>Nitrogen dioxide exposure showed a similar, though slightly less dramatic, pattern in the analysis. A fixed increase in the average concentration of this gas almost doubled a person’s chances of developing Lewy body dementia. For Parkinson’s disease dementia, the elevated gas exposure corresponded to a fourteen percent higher risk. In both cases, the connection to pollution was stronger for Lewy body dementia than for the dementia associated with Parkinson’s disease.</p>
<p>The researchers also grouped the subjects based on their total pollution exposure to look for a consistent dose-response relationship. They compared the people who breathed the dirtiest air to those who enjoyed the cleanest air. The group with the highest exposure to fine particulate matter had more than twice the risk for both types of dementia compared to the lowest exposure group.</p>
<p>“These are pollutants most people are exposed to every day,” said Dimitry S. Davydow, M.D., M.P.H., the Lauren and Lee Fixel Professor at the Norman Fixel Institute for Neurological Diseases at UF Health. “They come from things like traffic, shipping and other forms of combustion.”</p>
<p>“While this research does not establish causation, it does show a clear association between air pollution exposure and increased risk of these dementias,” said Gregory Pontone, M.D., M.H.S., the Louis and Roberta Fixel Endowed Chair. “It’s an important step in understanding how environmental factors may contribute to disease development.”</p>
<p>The study relied heavily on diagnoses made in hospitals or specialty clinics, which presents a minor limitation. This means the researchers might have missed milder cases of dementia or patients who never sought specialized medical care. If milder cases were missing from the registries, the exact risk calculations might be slightly underestimated by the final analysis.</p>
<p>The team also lacked access to certain personal details that consistently affect health outcomes in older adults. The national databases do not record lifestyle habits like diet, alcohol consumption, or daily exercise routines. The registries also omit details about specific occupational hazards, meaning the team could not account for people who work in heavily polluted industrial settings.</p>
<p>Additionally, fine particulate matter and nitrogen dioxide are often emitted from the exact same sources, such as highway traffic. Because the two pollutants frequently exist together in the air, it is incredibly difficult to separate their individual effects on the human body. The researchers noted that these elements might work together simultaneously to cause neurological harm.</p>
<p>Future research could explore exactly how these invisible particles initiate the neurodegenerative process on a cellular level. Scientists hope to investigate whether blocking the brain’s inflammatory response might slow or stop the damage caused by inhaled pollutants. Further studies could also look at how agricultural chemicals, like pesticides, might combine with air pollution to impact brain health over a lifetime.</p>
<p>The study, “<a href="https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2849005" target="_blank">Exposure to Air Pollutants and Lewy Body and Parkinson Disease–Related Dementias</a>,” was authored by Dimitry S. Davydow, Gregory M. Pontone, Michael S. Okun, Melissa J. Armstrong, Theresa Wimberley Böttger, Camila Geels, Lise Marie Frohn, Jørgen Brandt, Julie Werenberg Dreier, Jakob Christensen, Carsten Bøcker Pedersen, and Henriette Thisted Horsdal.</p></p>
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<p><strong>Forwarded by:<br />
Michael Reeder LCPC<br />
Baltimore, MD</strong></p>
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