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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/scientists-identify-dynamic-brain-patterns-linked-to-symptom-severity-in-children-with-autism/" 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;">Scientists identify dynamic brain patterns linked to symptom severity in children with autism</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Dec 25th 2025, 08:00</div>
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<p><p>Recent research has identified specific patterns of brain activity that distinguish young children with autism from their typically developing peers. These patterns involve the way different regions of the brain communicate with one another over time and appear to be directly linked to the severity of autism symptoms. The findings suggest that these neural dynamics influence daily adaptive skills, which in turn affect cognitive performance. The study was published in <em><a href="https://doi.org/10.1523/JNEUROSCI.0161-25.2025" target="_blank">The Journal of Neuroscience</a></em>.</p>
<p>Diagnosing Autism Spectrum Disorder in young children currently relies heavily on observing behavior. This process can be subjective because symptoms vary widely from one child to another. Scientists have sought to find objective biological markers to improve the accuracy of early diagnosis. They also aim to understand the underlying neural mechanisms that contribute to the social and cognitive challenges associated with the condition.</p>
<p>Most previous research in this area has looked at the brain as a static object. These earlier studies calculated the average connection strength between brain regions over a long period. This approach assumes that brain activity remains constant during the measurement. However, the brain is highly active and constantly reorganizes its networks to process information.</p>
<p>A team of researchers led by Conghui Su and Yaqiong Xiao at the Shenzhen University of Advanced Technology decided to investigate these changing patterns. They focused on a concept known as dynamic functional connectivity. This method treats brain activity like a movie rather than a photograph. It allows scientists to see how functional networks configure and reconfigure themselves from moment to moment.</p>
<p>To measure this activity, the team used a technology called functional near-infrared spectroscopy. This technique involves placing a cap with light sensors on the child’s head. The sensors emit harmless near-infrared light that penetrates the scalp and skull. The light detects changes in blood oxygen levels in the brain, which serves as a proxy for neural activity.</p>
<p>This method is particularly well suited for studying young children. Unlike magnetic resonance imaging scanners, which are loud and require participants to be perfectly still, this optical system is quiet and tolerates some movement. This flexibility allows researchers to collect data in a more natural and comfortable environment.</p>
<p>The study included 44 children between the ages of two and six years old. Approximately half of the participants had been diagnosed with Autism Spectrum Disorder. The other half were typically developing children who served as a control group. The researchers recorded brain activity while the children sat quietly and watched a silent cartoon.</p>
<p>The researchers analyzed the data using a “sliding window” technique. They looked at short segments of the recording to see which brain regions were synchronized at any given second. By applying mathematical clustering algorithms, the team identified four distinct “states” of brain connectivity that recurred throughout the session.</p>
<p>One specific state, referred to as State 4, emerged as a key point of difference between the two groups. This state was characterized by strong connections between the left and right hemispheres of the brain. It specifically involved robust communication between the temporal and parietal regions, which are areas often associated with language and sensory processing.</p>
<p>The data showed that children with autism spent considerably less time in State 4 compared to the typically developing children. They also transitioned into and out of this state less frequently. The reduced time spent in this high-connectivity state was statistically distinct.</p>
<p>The researchers then compared these brain patterns to clinical assessments of the children. They found a correlation between the brain data and the severity of autism symptoms. Children who spent the least amount of time in State 4 tended to have higher scores on standardized measures of autism severity.</p>
<p>The study also looked at adaptive behavior. This term refers to the collection of conceptual, social, and practical skills that people learn to function in their daily lives. The analysis revealed that children who maintained State 4 for longer durations exhibited better adaptive behavior scores.</p>
<p>In addition to watching cartoons, the children performed a visual search task to measure their cognitive abilities. They were asked to find a specific shape on a touchscreen. The researchers found that the brain patterns observed during the cartoon viewing predicted how well the children performed on this separate game.</p>
<p>The team conducted a statistical mediation analysis to understand the relationship between these variables. This type of analysis helps determine if a third variable explains the relationship between an independent and a dependent variable. The results suggested a specific pathway of influence.</p>
<p>The analysis indicated that the dynamic brain patterns directly influenced the child’s adaptive behavior. In turn, the level of adaptive behavior influenced the child’s cognitive performance on the visual search task. This implies that adaptive skills serve as a bridge connecting neural activity to cognitive outcomes.</p>
<p>To test the robustness of their findings, the researchers analyzed data from an independent group of 24 typically developing children. They observed the same brain states in this new group. The relationship between the duration of State 4 and cognitive response time was replicated in this validation sample.</p>
<p>The researchers also explored whether these brain patterns could be used for classification. They fed the connectivity data into a machine learning algorithm. The computer model was able to distinguish between children with autism and typically developing children with an accuracy of roughly 74 percent.</p>
<p>This accuracy rate suggests that dynamic connectivity features have potential as a diagnostic biomarker. The ability to identify such markers objectively could complement traditional behavioral assessments. It may help clinicians identify the condition earlier or monitor how a child responds to treatment over time.</p>
<p>The study highlights the importance of interhemispheric communication. The reduced connections between the left and right temporal regions in the autism group align with the “underconnectivity” theory of autism. This theory proposes that long-range communication between brain areas is weaker in individuals on the spectrum.</p>
<p>There are limitations to this study that require consideration. The sample size was relatively small. A larger group of participants would be needed to confirm the results and ensure they apply to the broader population.</p>
<p>The demographics of the study participants may also limit generalization. The group with autism was predominantly male, which reflects the general diagnosis rates but leaves the patterns in females less explored. There were also socioeconomic differences between the autism group and the control group in terms of family income.</p>
<p>The technology used in the study has physical limitations. The sensors were placed over the frontal, temporal, and parietal lobes. This placement means the researchers could not analyze activity in the entire brain. Deeper brain structures or other cortical areas might play a role that this study could not detect.</p>
<p>The researchers suggest that future work should focus on longitudinal studies. Tracking children over several years would help scientists understand how these brain dynamics develop as the child grows. It would also clarify whether improvements in adaptive behavior lead to changes in brain connectivity.</p>
<p>The findings point toward potential avenues for intervention. Therapies that target adaptive behaviors might have downstream effects on cognitive performance. Understanding the specific neural deficits could also lead to more targeted treatments designed to enhance connectivity between brain hemispheres.</p>
<p>This research represents a step forward in linking the biology of the brain to the behavioral characteristics of autism. It moves beyond static snapshots of brain activity. Instead, it embraces the dynamic, ever-changing nature of the human mind to find clearer signals of neurodevelopmental differences.</p>
<p>The study, “<a href="https://doi.org/10.1523/JNEUROSCI.0161-25.2025" target="_blank">Linking Connectivity Dynamics to Symptom Severity and Cognitive Abilities in Children with Autism Spectrum Disorder: An FNIRS Study</a>,” was authored by Conghui Su, Yubin Hu, Yifan Liu, Ningxuan Zhang, Liming Tan, Shuiqun Zhang, Aiwen Yi, and Yaqiong Xiao.</p></p>
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<td><a href="https://www.psypost.org/new-research-frames-psychopathy-as-a-potential-survival-adaptation-to-severe-early-adversity/" 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;">New research frames psychopathy as a potential survival adaptation to severe early adversity</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Dec 25th 2025, 06:00</div>
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<p><p>New research suggests that specific personality traits may amplify the way childhood adversity shapes an individual’s approach to life. A study published in the journal <a href="https://doi.org/10.1016/j.paid.2025.113467"><em>Personality and Individual Differences</em></a> provides evidence that subclinical psychopathy strengthens the link between childhood trauma and “fast” life history strategies. The findings indicate that for those who have experienced severe early difficulties, certain dark personality traits may function as adaptive mechanisms for survival.</p>
<p>Psychologists use a framework called Life History Theory to explain how people allocate their energy. This theory proposes that all living organisms must make trade-offs between investing in their own growth and investing in reproduction. These trade-offs create a spectrum of strategies that range from “fast” to “slow.”</p>
<p>A fast life history strategy typically emerges in environments that are harsh or unpredictable. Individuals with this orientation tend to prioritize immediate rewards and reproduction over long-term planning. They often engage in riskier behaviors and invest less effort in long-term relationships. This approach makes evolutionary sense when the future is uncertain.</p>
<p>Conversely, a slow life history strategy is favored in stable and safe environments. This approach involves delaying gratification and investing heavily in personal development and long-term goals. It also involves a focus on building deep, enduring social and family bonds.</p>
<p>The researchers also examined the “Dark Triad” of personality. This cluster includes three distinct traits: narcissism, Machiavellianism, and psychopathy. Narcissism involves grandiosity and a need for admiration. Machiavellianism is characterized by manipulation and strategic calculation. Psychopathy involves high impulsivity and a lack of empathy.</p>
<p>The research team, led by Vlad Burtaverde from the University of Bucharest, sought to understand how these dark traits interact with early life experiences. They hypothesized that these traits might help individuals adapt to traumatic environments by accelerating their life strategies. The study aimed to determine if the Dark Triad traits or childhood socioeconomic status moderate the relationship between trauma and life outcomes.</p>
<p>To investigate this, the researchers recruited 270 undergraduate students. The participants had an average age of approximately 20 years. The majority of the sample was female. The participants completed a series of online questionnaires designed to measure their childhood experiences and current personality traits.</p>
<p>The Childhood Trauma Questionnaire assessed exposure to emotional, physical, and sexual abuse, as well as neglect. The Short Dark Triad measure evaluated levels of narcissism, Machiavellianism, and psychopathy. The High-K Strategy Scale assessed life history strategies by asking about health, social capital, and future planning. Participants also answered questions regarding their family’s financial situation during their childhood.</p>
<p>The results showed that participants who reported higher levels of childhood trauma were more likely to exhibit fast life history strategies. These individuals also tended to report lower childhood socioeconomic status. This aligns with the expectation that adverse environments encourage a focus on the present rather than the future.</p>
<p>Among the Dark Triad traits, subclinical narcissism showed a unique pattern. It was the only trait that had a statistically significant direct relationship with life history strategies. Specifically, higher narcissism was associated with slower life history strategies. This suggests that narcissism may function differently than the other dark traits.</p>
<p>The most significant finding involved subclinical psychopathy. The analysis revealed that psychopathy moderated the relationship between childhood trauma and fast life history strategies. For individuals with low levels of psychopathy, the link between trauma and a fast strategy was weaker. However, for those with high levels of psychopathy, the link was much stronger.</p>
<p>This means that psychopathy may act as a catalyst. It appears to amplify the effect of trauma, pushing the individual more aggressively toward a fast life strategy. The authors suggest this frames psychopathy as a “survival” trait. It helps the individual pursue immediate resources in a world they perceive as dangerous.</p>
<p>In contrast, the researchers found that childhood socioeconomic status did not moderate this relationship. While growing up poor was linked to faster life strategies, it did not change how trauma impacted those strategies. This suggests that the psychological impact of trauma operates somewhat independently of financial resources.</p>
<p>These findings build upon a growing body of research linking environmental conditions to personality development. A global study by Peter Jonason and colleagues analyzed data from over 11,000 participants across 48 countries. They found that macro-level ecological factors, such as natural disasters and skewed sex ratios, <a href="https://www.psypost.org/scientists-identify-ecological-factors-that-predict-dark-personality-traits-across-48-countries/" target="_blank" rel="noopener">predict national averages of Dark Triad traits</a>. For instance, countries with more men than women tended to have higher levels of narcissism.</p>
<p>That global study suggested that these traits are not merely pathologies. They may be functional responses to broad ecological pressures. The current study by Burtaverde and colleagues zooms in from the national level to the individual level. It shows how personal history interacts with these traits to shape behavior.</p>
<p>Research by Lisa Bohon and colleagues provides further context regarding gender and environment. Their study of female college students found that <a href="https://www.psypost.org/childhood-instability-primes-women-for-fast-reproductive-strategies-via-psychopathy-and-impulsivity/" target="_blank" rel="noopener">a disordered home life predicted fast life history traits</a>. They found that father absence and childhood trauma were strong predictors of psychopathy in women. These traits then mediated the relationship between childhood environment and mating effort.</p>
<p>The Bohon study highlighted that immediate family dynamics, or the “microsystem,” are powerful predictors of adult personality. This aligns with the Burtaverde study’s focus on childhood trauma. Both studies suggest that the “dark” traits serve a function in regulating reproductive effort and survival strategies.</p>
<p>Another study by Junwei Pu and Xiong Gan examined the social roots of these traits in adolescents. They found that social ostracism led to increased loneliness. This loneliness <a href="https://www.psypost.org/early-social-rejection-may-foster-dark-personality-traits-through-loneliness-study-suggests/" target="_blank" rel="noopener">subsequently promoted the development of Dark Triad traits</a> over time. Their work suggests that social isolation acts as a signal to the individual that the environment is hostile.</p>
<p>This hostility prompts the development of defensive personality traits. Psychopathy, in particular, was strongly connected to feelings of loneliness in their sample. This complements the Burtaverde finding that psychopathy strengthens the reaction to trauma. A person who feels rejected and traumatized may develop callousness as a protective shell.</p>
<p>David Pineda and his team investigated the specific role of parental discipline. They found that psychological aggression from parents <a href="https://www.psypost.org/harsh-parenting-in-childhood-linked-to-dark-personality-traits-in-adulthood-study-finds/" target="_blank" rel="noopener">was a unique predictor of psychopathy and sadism</a> in adulthood. Severe physical assault was linked to Machiavellianism and narcissism. Their work emphasizes that specific types of mistreatment yield specific personality outcomes.</p>
<p>This nuance helps explain why the Burtaverde study found a link between general trauma and life strategies. The specific type of trauma likely matters. Pineda’s research suggests that psychological aggression may be particularly potent in fostering the traits that Burtaverde identified as moderators.</p>
<p>Finally, research by Jacob Dye and colleagues looked at the buffering effect of positive experiences. They found that <a href="https://www.psypost.org/how-good-and-bad-childhood-experiences-shape-dark-personality-traits/" target="_blank" rel="noopener">positive childhood experiences could reduce psychopathic traits</a>, but only up to a point. If a child faced severe adversity, positive experiences were no longer enough to prevent the development of dark traits.</p>
<p>This limitation noted by Dye supports the Burtaverde finding regarding the strength of the trauma-psychopathy link. In cases of high trauma, the “survival” mechanism of psychopathy appears to override other developmental pathways. The protective factors become less effective when the threat level is perceived as extreme.</p>
<p>Nevertheless, the authors of the new study note some limitations to their work. The reliance on self-reported data introduces potential bias. Participants may not accurately remember or report their childhood experiences. The sample consisted largely of female undergraduate students. This limits the ability to generalize the findings to the broader population or to men specifically.</p>
<p>Future research is needed to track these relationships over time. Longitudinal studies could help determine the direction of causality. It is possible that children with certain temperaments elicit different reactions from their environment. Understanding the precise timeline of these developments would require observing participants from childhood through adulthood.</p>
<p>The study, “<a href="https://doi.org/10.1016/j.paid.2025.113467" target="_blank" rel="noopener">Childhood trauma and life history strategies – the moderating role of childhood socio-economic status and the dark triad traits</a>,” was authored by Vlad Burtaverde, Peter K. Jonason, Anca Minulescu, Bogdan Oprea, Șerban A. Zanfirescu, Ștefan -C. Ionescu, and Andreea M. Gheorghe.</p></p>
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<td><a href="https://www.psypost.org/epilepsy-drug-topiramate-shows-mixed-results-for-treating-combined-alcohol-and-tobacco-use/" 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;">Epilepsy drug topiramate shows mixed results for treating combined alcohol and tobacco use</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Dec 24th 2025, 20:00</div>
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<p><p>An 18-week experimental study examining the effects of topiramate on tobacco smoking and alcohol use found no differences between groups treated with topiramate and those receiving placebo treatment in the last 4 weeks of treatment. However, the authors report a lower average percentage of heavy drinking days and drinks per day in participants treated with the highest tested dose of the substance compared to the other groups across the assessments conducted after the target quit date. The research was published in <a href="https://doi.org/10.1111/acer.70193"><em>Alcohol Clinical & Experimental Research</em></a>.</p>
<p>Topiramate is a prescription medication originally developed as an antiepileptic drug to treat seizures. It is also commonly used for migraine prevention and, in combination with other drugs, for weight management.</p>
<p>Topiramate works by modulating multiple neurotransmitter systems, including enhancing the activity of the inhibitory neurotransmitter GABA and reducing the excitatory activity of the neurotransmitter glutamate. Because of these mechanisms, topiramate can reduce the heightened excitability of neurons in the brain.</p>
<p>The medication is sometimes used off-label for conditions such as bipolar disorder, alcohol use disorder, and binge eating disorder. However, it has substantial cognitive and neurological side effects (e.g., cognitive slowing, difficulty with word finding, tingling sensations in hands or feet), which limit its long-term use.</p>
<p>Study author Jason D. Robinson and his colleagues wanted to explore whether topiramate would be effective in treating individuals with alcohol use disorder and tobacco use disorder. More specifically, they wanted to see whether 250 mg and 125 mg of topiramate per day would result in reducing heavy drinking and cigarette smoking behaviors in individuals motivated to try to quit both substances. The study authors hypothesized that the higher dose would be more effective than the lower dose.</p>
<p>Study participants were 236 adults who met the criteria for both alcohol use disorder and tobacco use disorder. They were recruited from San Diego, Houston, and Charlottesville. Participating women had been drinking at least 8 standard drink units (of alcohol) per week in the past 30 days, while this minimum limit was 15 standard drink units for men.</p>
<p>One standard drink unit is the amount of alcohol that contains about 14 grams of pure ethanol, roughly equivalent to a small beer (350 ml), a glass of wine (150 ml), or a shot of spirits (45 ml). They were also smoking an average of 5 or more cigarettes per day in the 30 days before the study.</p>
<p>Study participants were randomly divided into three groups. One group was assigned to receive a high dose of topiramate, up to 250 mg/day; the second group would receive up to 125 mg/day of topiramate; and the third group would receive a placebo.</p>
<p>The placebo consisted of pills that looked like topiramate pills but contained no active ingredients. Participants did not know which treatment they were receiving, and the same was the case for the researchers directly working with them. In other words, the study was double-blind.</p>
<p>The treatment lasted for 18 weeks. During this period, participants took their assigned treatment and received adherence counseling, including a self-help manual for smoking cessation. In the first 5 weeks, the dose was gradually increased, and at the start of week 6, participants were expected to actively stop both alcohol drinking and tobacco smoking.</p>
<p>Results showed no differences between the study groups regarding the primary outcomes. In other words, the three groups did not differ significantly in the percentage of heavy drinking days and the rate of continuous smoking abstinence in the last 4 weeks of treatment.</p>
<p>However, study authors report that participants in the group that received 250 mg of topiramate had a lower average percentage of heavy drinking days and drinks per day compared to the other two groups when all assessments done from week 6 onward were taken into account. Similarly, participants in both topiramate groups smoked fewer cigarettes per day and reported greater cigarette abstinence than those in the placebo group during the same period.</p>
<p>“While the primary analyses did not find evidence that topiramate decreases drinking and smoking behavior, likely influenced by a high attrition rate and poor medication adherence, exploratory repeated measures analyses suggest that topiramate 250 mg reduces drinking behavior and that both the 125 mg and 250 mg doses reduce smoking behavior,” the study authors concluded.</p>
<p>The study contributes to the scientific understanding of the effects of topiramate. However, it should be noted that 236 participants started the treatments, but only 107 completed them, which is less than half. This extremely high attrition rate could have substantially altered the results.</p>
<p>The paper, “<a href="https://doi.org/10.1111/acer.70193">High- and low-dose topiramate for the treatment of persons with alcohol use disorder who smoke cigarettes: A randomized control trial,</a>” was authored by Jason D. Robinson, Robert M. Anthenelli, Paul M. Cinciripini, Maher Karam-Hage, Yong Cui, George Kypriotakis, and Nassima Ait-Daoud Tiouririne.</p></p>
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<td><a href="https://www.psypost.org/data-from-6-million-couples-reveals-a-surprising-trend-in-how-we-pick-our-partners/" 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;">Data from 6 million couples reveals a surprising trend in how we pick our partners</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Dec 24th 2025, 18:00</div>
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<p><p>“Birds of a feather flock together” is a cliche for a reason when it comes to romantic relationships. Shared religious beliefs, values, <a href="https://psycnet.apa.org/doi/10.1037/pspi0000467">political affiliation</a> and even music taste all <a href="https://doi.org/10.1371/journal.pone.0129688">influence attraction</a> and satisfaction in a relationship. But a recent study has now identified another unexpected factor that may bring couples closer together: sharing a similar mental health diagnosis.</p>
<p>The concept of romantic partners sharing a psychiatric diagnosis is not new. Indeed, between <a href="https://www.cambridge.org/core/journals/the-british-journal-of-psychiatry/article/mental-disorders-in-married-couples-assortative-mating/B021C0E81DD730C802612CDA65BA809D">1964</a> and <a href="https://www.cambridge.org/core/journals/the-british-journal-of-psychiatry/article/mates-of-schizophrenic-mothers/ABC12CEE463EEF7DECFC2CF608A84B9A">1985</a> several studies that explored the reasons why people choose their romantic partners included <a href="https://www.cambridge.org/core/journals/psychological-medicine/article/assortative-mating-among-inpatients-with-primary-affective-disorder/17CA2893AB36365CF334CBDDB17DCD89">psychiatric diagnosis</a> as a variable. However, no large-scale, cross-cultural investigation had been conducted until recently.</p>
<p>Using national health insurance data from more than six million couples in total, a team of researchers recently analysed the degree to which psychiatric disorders were <a href="https://doi.org/10.1038/s41562-025-02298-z">shared between couples</a>. They examined data from five million couples in Taiwan, 571,534 couples in Denmark and 707,263 couples in Sweden.</p>
<p>They looked at nine psychiatric disorders in their analysis, including depression, anxiety, substance-use disorder, bipolar disorder, anorexia nervosa, ADHD, autism, obsessive-compulsive disorder and schizophrenia. They found that people with a diagnosed psychiatric disorder had a higher likelihood of marrying someone with the same or a similar psychiatric disorder than they did of marrying someone who isn’t diagnosed with one.</p>
<p>While the finding is robust, the authors do acknowledge there are some limitations when interpreting the results.</p>
<p>The first is that the timing of relationships and diagnoses were not recorded. This means that diagnosis could have occurred after the beginning of the relationship – and thus may not be the result of active choice.</p>
<p>Furthermore, a care provider’s <a href="https://doi.org/10.1007/s10597-020-00590-y">own biases</a> may influence how likely they are to diagnose a person with a specific mental health condition. Since many couples share the same family doctor, this could influence their likelihood of being diagnosed with a psychiatric condition — and could have biased the results seen in the study.</p>
<p>Finally, the authors stress their results are purely observational. This means they don’t explicitly consider the contributing factors as to why people with psychiatric diagnoses might be more likely to choose romantic relationships with each other.</p>
<p>However, there are several psychological theories that may help to explain this phenomenon.</p>
<h2>Understanding this phenomenon</h2>
<p><strong>1. Assortative mating:</strong></p>
<p>This theory assumes that we choose partners who are <a href="https://psycnet.apa.org/doi/10.1037/ebs0000342">similar to us</a>. Normally this is applied to <a href="https://doi.org/10.1016/j.paid.2019.109739">personality and social factors</a> (such as shared religious or socioeconomic background). But this recent study suggests that this choice may extend beyond these factors and into how we think.</p>
<p>So a person with a specific psychiatric disorder – such as anxiety or autism – may be drawn to someone with a similar psychiatric disorder because they share similar traits, values or approaches to daily life (such as prioritising <a href="https://doi.org/10.1016/j.pnpbp.2006.01.010">structure and routine</a>).</p>
<p><strong>2. Proximity:</strong></p>
<p>According to the <a href="https://doi.org/10.1111/1467-8721.00154">mere exposure effect</a>, we often choose relationships with people that we live or work in <a href="https://doi.org/10.4324/9780367198459-REPRW43-1">close proximity to</a> – or otherwise spend time around.</p>
<p>People who share psychiatric diagnoses may be drawn to similar social situations. For example, people with substance use disorder may visit bars or other social settings where taking substances is more commonplace – and thus may be more likely to meet potential mates who are struggling with a <a href="https://doi.org/10.2174/1874473708666150916112913">similar disorder</a>.</p>
<p><strong>3. Attachment theory:</strong></p>
<p><a href="https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/abs/bowlbyainsworth-attachment-theory/6D35C7A344107195D97FD7ADAE06C807">Attachment theory</a> assumes that as infants, we develop a specific emotional bond to our primary caregivers. This early bond then shapes our subsequent emotional and psychological patterns of behaviour as we get older – and also <a href="https://doi.org/10.1111/j.1467-6494.2011.00723.x">influences what we’re looking for</a> in a relationship.</p>
<p>So someone with an anxious attachment style (which can manifest as fear of abandonment, desire for closeness or need for reassurance) might feel drawn to a partner who has a similar attachment style or exhibits the kind of behaviour they desire – such as a partner who texts them all night when they’re apart. Even if this is not a healthy dynamic, the validation gained from a high-intensity relationship would likely make it hard to resist.</p>
<p>Research shows certain attachment styles are more common in people with specific psychiatric conditions. For example, anxious attachment style is more common in people who have <a href="https://doi.org/10.2991/assehr.k.200826.207">anxiety</a>, <a href="https://www.ajol.info/index.php/sajpsyc/article/view/287901">depression</a> and <a href="https://doi.org/10.3389/fpsyt.2020.00410">bipolar disorder</a>. This might help explain why the study found people with certain psychiatric conditions were more likely to be married to each other.</p>
<p><strong>4. Social identity theory:</strong></p>
<p><a href="https://www.taylorfrancis.com/chapters/edit/10.4324/9780203505984-16/social-identity-theory-intergroup-behavior-henri-tajfel-john-turner">Social identity theory</a> assumes that our self-esteem is gained through a sense of belonging within our social groups. So when you begin a relationship with somebody from within your social group, it boosts self-esteem as it brings a greater sense of belonging and feeling understood.</p>
<p>This might explain why people with the same psychiatric diagnosis (a social group) would be drawn to each other. Finding someone who understands and experiences the same struggles you do could help you bond and make you feel understood and validated.</p>
<p>What does this mean for us? Well, the results reported by this recent study can only tell us whether couples share psychiatric diagnoses. They don’t tell us the quality and duration of the relationship, nor do they account for individual differences which may also affect the relationship.</p>
<p>Ultimately, shared experiences <a href="https://doi.org/10.1007/s10803-020-04790-z">promote closeness</a> and empathetic communication for couples – and it stands to reason that this would extend to psychiatric diagnosis. Having a partner who understands and can relate to your mental illness can provide social support and validation that’s not available from someone who has never struggled with their <a href="https://journals.co.za/doi/abs/10.4102/curationis.v42i1.2015">mental health</a>.<!-- Below is The Conversation's page counter tag. Please DO NOT REMOVE. --><img decoding="async" src="https://counter.theconversation.com/content/264837/count.gif?distributor=republish-lightbox-basic" alt="The Conversation" width="1" height="1"><!-- End of code. If you don't see any code above, please get new code from the Advanced tab after you click the republish button. The page counter does not collect any personal data. More info: https://theconversation.com/republishing-guidelines --></p>
<p> </p>
<p><em>This article is republished from <a href="https://theconversation.com">The Conversation</a> under a Creative Commons license. Read the <a href="https://theconversation.com/spouses-are-more-likely-to-be-diagnosed-with-the-same-mental-health-conditions-heres-why-264837">original article</a>.</em></p></p>
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<td><a href="https://www.psypost.org/weak-muscles-linked-to-higher-dementia-risk-in-middle-aged-and-older-adults/" 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;">Weak muscles linked to higher dementia risk in middle-aged and older adults</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Dec 24th 2025, 14:00</div>
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<p><p>A new analysis suggests that physical frailty serves as a robust warning sign for cognitive decline in later life. Researchers found that middle-aged and older adults with weaker muscles faced a much higher likelihood of developing dementia compared to their stronger peers. These findings were published in the <em><a href="https://doi.org/10.1016/j.jpsychires.2025.09.043" target="_blank" rel="noopener">Journal of Psychiatric Research</a></em>.</p>
<p>Dementia rates are climbing globally as life expectancy increases. This condition places a heavy strain on families and healthcare systems. Medical experts are urgently looking for early indicators to identify people at risk before severe memory loss begins. One potential marker is sarcopenia. This is the age-related loss of muscle mass and power. Previous investigations have hinted at a link between physical frailty and brain health. However, many prior attempts to measure this connection did not account for body size differences among individuals.</p>
<p>Wei Jin and colleagues from Xinxiang Medical University in China sought to clarify this relationship. They wanted to see if the connection held true when adjusting for body mass and weight. They also aimed to look at both upper and lower body strength. Most previous work focused only on handgrip strength. The team believed a comprehensive approach could offer better insights into how physical decline might mirror changes in the brain.</p>
<p>The research team utilized data from the English Longitudinal Study of Ageing (ELSA). This is a long-running project that tracks the health and well-being of people living in England. The analysis included nearly 6,000 participants. All subjects were at least 50 years old at the start of the review. The researchers followed these individuals for a median period of about nine years.</p>
<p>To measure upper body strength, the team used a handheld dynamometer. Participants squeezed the device as hard as they could using their dominant hand. The researchers recorded the maximum force exerted during three trials.</p>
<p>Absolute strength is not always the best measure of health. A heavier person typically requires more muscle mass to move their body than a lighter person. To address this, the researchers standardized the grip strength scores. They adjusted the measurements based on the person’s body mass index (BMI) and total weight. This calculation ensured that strength scores were fair comparisons between people of different sizes.</p>
<p>The team also needed a reliable way to assess lower body function. They utilized a test involving a chair. Participants had to stand up from a sitting position five times as fast as possible. They were not allowed to use their arms for support. A stopwatch recorded the time it took to complete the five repetitions. Slower times indicated weaker leg muscles.</p>
<p>During the follow-up period, 197 participants developed dementia. This represented about 3.3 percent of the study population. The data revealed a clear pattern connecting muscle weakness to cognitive diagnoses.</p>
<p>Participants with the lowest absolute handgrip strength faced a high probability of diagnosis. Their risk was roughly 2.8 times higher than those with the strongest grip. This relationship remained consistent even after the researchers accounted for differences in body mass.</p>
<p>When looking at BMI-standardized strength, the trend persisted. Those in the lowest tier of strength relative to their size had more than double the risk of dementia. This suggests that low muscle quality is a danger sign regardless of a person’s weight.</p>
<p>The results for leg strength were similarly distinct. People who took the longest to stand up from a chair had a much higher probability of developing dementia. Their risk was approximately 2.75 times higher than those who could stand up quickly.</p>
<p>The researchers checked to see if these trends varied by demographic. They found the pattern was consistent for both men and women. It also held true for middle-aged adults between 50 and 64, as well as for those over 65. The connection appeared to be linear. This means that for every incremental decrease in strength, the estimated risk of dementia rose.</p>
<p>The team performed a sensitivity analysis to check the robustness of their data. They excluded participants who were diagnosed with dementia within the first two years of the study. This step helps rule out the possibility that the muscle weakness was caused by pre-existing, undiagnosed dementia. The results remained largely the same after this exclusion.</p>
<p>There are several biological theories that might explain these results. One theory involves white matter hyperintensities. These are lesions that appear on brain scans. They represent damage to the brain’s communication network. Previous research shows that declines in muscle strength often correlate with an increase in these lesions.</p>
<p>Another potential mechanism involves the nervous system’s interconnectivity. The systems that control movement, senses, and cognition are linked. Damage to the neural pathways that control muscles might occur alongside damage to cognitive pathways.</p>
<p>Inflammation may also play a specific role. Chronic inflammation is known to damage both muscle tissue and neurons. High levels of inflammatory markers in the blood are associated with both sarcopenia and dementia. This creates a cycle where inflammation degrades the body and the brain simultaneously.</p>
<p>The authors noted several limitations to their work. This was an observational study. It can show a relationship between two factors, but it cannot prove that muscle weakness causes dementia directly. It is possible that unmeasured lifestyle factors contribute to both conditions.</p>
<p>The study also relied partly on self-reported medical diagnoses. This method can sometimes lead to inaccuracies if participants do not recall their medical history perfectly. Additionally, the study did not distinguish between different types of dementia. It grouped Alzheimer’s disease and other forms of cognitive decline together.</p>
<p>The study population was specific to the United Kingdom. The participants were predominantly white and over age 50. The results may not apply perfectly to younger populations or different ethnic groups. Cultural and genetic differences could influence the strength-dementia relationship in other parts of the world.</p>
<p>Despite these caveats, the implications for public health are clear. The study highlights the value of maintaining muscle strength as we age. Grip strength and chair-rising speed are simple, non-invasive tests. Doctors could easily use them to screen patients for dementia risk.</p>
<p>Future research should focus on intervention strategies. Scientists need to determine if building muscle can actively delay the onset of dementia. Clinical trials involving strength training exercises would be a logical next step.</p>
<p>The researchers conclude that muscle strength is a key component of healthy aging. Both upper and lower limb strength appear to matter. Interventions that target total body strength could be an effective way to support brain health. Identifying physical decline early provides a window of opportunity for preventative care.</p>
<p>The study, “<a href="https://doi.org/10.1016/j.jpsychires.2025.09.043" target="_blank" rel="noopener">Association between muscle strength and dementia in middle-aged and older adults: A nationwide longitudinal study</a>,” was authored by Wei Jin, Sheng Liu, Li Huang, Xi Xiong, Huajian Chen, and Zhenzhen Liang.</p></p>
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<td><a href="https://www.psypost.org/common-adhd-medications-function-differently-than-scientists-previously-thought/" 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 ADHD medications function differently than scientists previously thought</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Dec 24th 2025, 12:30</div>
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<p><p>Prescription stimulants are among the most widely used psychiatric medications in the world. For decades, the prevailing medical consensus held that drugs like methylphenidate treat attention deficit hyperactivity disorder by targeting the brain’s executive control centers. A new study challenges this long-held dogma, revealing that these medications act primarily on neural networks responsible for wakefulness and reward rather than attention. The study was published in the journal <a href="https://www.cell.com/cell/fulltext/S0092-8674(25)01373-X"><em>Cell</em></a>.</p>
<p>Medical textbooks have traditionally taught that stimulants function by enhancing activity in the prefrontal cortex. This region of the brain is often associated with voluntary control, planning, and the direction of focus. The assumption was that by boosting activity in these circuits, the drugs allowed patients to filter out distractions and maintain concentration on specific tasks. However, the precise neural mechanisms have remained a subject of debate among neuroscientists.</p>
<p>Earlier research into these medications often produced inconsistent results. Some studies suggested that stimulants improved motivation and reaction times rather than higher-level reasoning. Furthermore, behavioral experiments have shown that the drugs do not universally improve performance. They tend to help individuals who are performing poorly but offer little benefit to those who are already performing well.</p>
<p>To resolve these discrepancies, a research team led by neurologist Benjamin P. Kay at Washington University School of Medicine in St. Louis undertook a massive analysis of brain activity. Working with senior author Nico U.F. Dosenbach, Kay aimed to map the effects of stimulants across the entire brain without restricting their focus to pre-determined areas. They sought to understand which specific brain networks were most altered when a child took these medications.</p>
<p>The researchers utilized data from the Adolescent Brain Cognitive Development Study. This large-scale project tracks the biological and psychological development of thousands of children across the United States. The team selected functional magnetic resonance imaging scans from 5,795 children between the ages of eight and eleven.</p>
<p>Kay and his colleagues compared the brain scans of children who had taken prescription stimulants on the day of their MRI against those who had not. They employed a technique known as resting-state functional connectivity. This method measures how different regions of the brain communicate and synchronize with one another when the person is not performing a specific task.</p>
<p>The analysis did not rely on small, isolated samples. The researchers used a data-driven approach to look at the whole connectome, which is the complete map of neural connections in the brain. They controlled for various factors that could skew the results, such as head motion during the scan and socioeconomic status.</p>
<p>The findings contradicted the traditional “attention-centric” view of stimulant medication. The researchers observed no statistical difference in the functional connectivity of the dorsal or ventral attention networks. The drugs also did not produce measurable changes in the frontoparietal control network, which is usually linked to complex problem-solving.</p>
<p>Instead, the most substantial changes occurred in the sensorimotor cortex and the salience network. The sensorimotor cortex is traditionally associated with physical movement and sensation. However, recent discoveries suggest this area also plays a major role in regulating the body’s overall arousal and wakefulness levels.</p>
<p>The salience network is responsible for determining what is important in the environment. It helps the brain calculate the value of a task and decides whether an action is worth the effort. The study found that stimulants increased connectivity between these reward-processing regions and the motor systems.</p>
<p>This shift in connectivity suggests that the drugs work by altering the brain’s calculation of effort and reward. By boosting activity in the salience network, the medication makes tedious activities feel more rewarding than they otherwise would. This reduces the urge to switch tasks or seek stimulation elsewhere.</p>
<p>“Essentially, we found that stimulants pre-reward our brains and allow us to keep working at things that wouldn’t normally hold our interest — like our least favorite class in school, for example,” Dosenbach said. This explains the paradox of why a stimulant can help a hyperactive child sit still. The drug removes the biological drive to fidget by satisfying the brain’s need for reward.</p>
<p>To verify that these findings were not an artifact of the pediatric data, the team conducted a separate validation study. They recruited five healthy adults who did not have attention deficits. These volunteers underwent repeated brain scans before and after taking a controlled dose of methylphenidate.</p>
<p>The results from the adult trial mirrored the findings in the children. The medication consistently altered the arousal and reward networks while leaving the attention networks largely unchanged. This replication in a controlled setting provides strong evidence that the drugs act on basic physiological drivers of behavior.</p>
<p>The study also uncovered a distinct relationship between stimulant medication and sleep. The researchers compared the brain patterns of medicated children to those of children who reported getting a full night of sleep. The functional connectivity signatures were remarkably similar.</p>
<p>Stimulants appeared to mimic the neurological effects of being well-rested. Children who were sleep-deprived showed specific disruptions in their sensorimotor and arousal networks. When sleep-deprived children took a stimulant, those disruptions disappeared.</p>
<p>This “rescue” effect extended to cognitive performance as well. The researchers analyzed school grades and test scores for the children in the study. As expected, children with attention deficits performed better when taking medication. However, the data revealed a nuance regarding sleep.</p>
<p>Stimulants improved the grades and test scores of children who did not get enough sleep. In fact, the medication raised the performance of sleep-deprived children to the level of their well-rested peers. Conversely, for children who did not have attention deficits and already got sufficient sleep, the drugs provided no statistical benefit to performance.</p>
<p>“We saw that if a participant didn’t sleep enough, but they took a stimulant, the brain signature of insufficient sleep was erased, as were the associated behavioral and cognitive decrements,” Dosenbach noted. The medication effectively masked the neural and behavioral symptoms of fatigue.</p>
<p>This finding raises important questions about the use of stimulants as performance enhancers. The data suggests that the drugs do not make a well-rested brain smarter or more attentive. They simply counteract the drag of fatigue and lack of motivation.</p>
<p>The authors of the study advise caution regarding this sleep-masking effect. While the drugs can hide the immediate signs of sleep deprivation, they do not replace the biological necessity of sleep. Chronic sleep loss is linked to cellular stress, metabolic issues, and other long-term health consequences that stimulants cannot fix.</p>
<p>Kay highlighted the clinical implications of these findings for doctors and parents. Symptoms of sleep deprivation often mimic the symptoms of attention deficit hyperactivity disorder, including lack of focus and irritability. Treating a sleep-deprived child with stimulants might mask the root cause of their struggles.</p>
<p>“Not getting enough sleep is always bad for you, and it’s especially bad for kids,” Kay said. He suggested that clinicians should screen for sleep disturbances before prescribing these medications. It is possible that some children diagnosed with attention deficits are actually suffering from chronic exhaustion.</p>
<p>The study also provides a new framework for understanding the brain’s motor cortex. The researchers noted that the changes in the motor system align with the recently discovered Somato-Cognitive Action Network. This network integrates body control with planning and arousal, further cementing the link between movement and alertness.</p>
<p>Future research will need to investigate the long-term effects of using stimulants to override sleep signals. The current study looked at a snapshot in time, but the cumulative impact of masking fatigue over years remains unknown. The researchers also hope to explore whether these arousal mechanisms differ in various subtypes of attention disorders.</p>
<p>By shifting the focus from attention to arousal and reward, this research fundamentally alters the understanding of how psychostimulants function. It suggests that these drugs are not “smart pills” that boost intelligence. Instead, they are endurance tools that help the brain maintain effort and wakefulness in the face of boredom or fatigue.</p>
<p>The study, “<a href="https://www.cell.com/cell/fulltext/S0092-8674(25)01373-X">Stimulant medications affect arousal and reward, not attention</a>,” was authored by Benjamin P. Kay, Muriah D. Wheelock, Joshua S. Siegel, Ryan Raut, Roselyne J. Chauvin, Athanasia Metoki, Aishwarya Rajesh, Andrew Eck, Jim Pollaro, Anxu Wang, Vahdeta Suljic, Babatunde Adeyemo, Noah J. Baden, Kristen M. Scheidter, Julia Monk, Nadeshka Ramirez-Perez, Samuel R. Krimmel, Russel T. Shinohara, Brenden Tervo-Clemmens, Robert J. M. Hermosillo, Steven M. Nelson, Timothy J. Hendrickson, Thomas Madison, Lucille A. Moore, Óscar Miranda-Domínguez, Anita Randolph, Eric Feczko, Jarod L. Roland, Ginger E. Nicol, Timothy O. Laumann, Scott Marek, Evan M. Gordon, Marcus E. Raichle, Deanna M. Barch, Damien A. Fair, and Nico U.F. Dosenbach.</p></p>
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<td><a href="https://www.psypost.org/study-finds-little-evidence-of-the-dunning-kruger-effect-in-political-knowledge/" 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;">Study finds little evidence of the Dunning-Kruger effect in political knowledge</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Dec 24th 2025, 12:00</div>
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<p><p>A new study suggests that the average person may be far more aware of their own lack of political knowledge than previously thought. Contrary to the popular idea that people consistently overestimate their competence, this research indicates that individuals with low political information generally admit they do not know much. These findings were published in <em><a href="https://doi.org/10.1177/10659129251398531" target="_blank" rel="noopener">Political Research Quarterly</a></em>.</p>
<p>Political scientists have spent years investigating the gap between what citizens know and what they think they know. This gap is often attributed to the Dunning-Kruger effect. This psychological phenomenon occurs when people with low ability in a specific area overestimate their competence.</p>
<p>In their new study, Alexander G. Hall and Kevin B. Smith of the University of Nebraska sought to answer several unresolved questions regarding this phenomenon. They wanted to determine if receiving objective feedback could reduce overconfidence. The researchers also intended to see if the Dunning-Kruger effect remains stable over time or changes due to major events. The study utilized a natural experiment to test these ideas in a real-world educational setting.</p>
<p>“Kevin and I have had an ongoing interest in this question: if you make someone’s substantive knowledge salient, will they do a more accurate job of reporting it?” explained Hall, who is now a staff statistician for Creighton University’s School of Medicine and adjunct instructor for the University of Nebraska-Omaha.</p>
<p>“I noticed that in his intro political science course he had been consistently collecting information that could speak to this, and that we had the makings of a neat natural experiment where participants had either taken this knowledge assessment before (presumably increasing that salience) or after being asked about their self-rated political knowledge.”</p>
<p>This data collection spanned eleven consecutive semesters between the fall of 2018 and the fall of 2023. The total sample included 1,985 students. The mean sample size per semester was approximately 180 participants.</p>
<p>The course required students to complete two specific assignments during the first week of the semester. One assignment was a forty-two-question assessment test designed to measure objective knowledge of American government and politics. The questions included items from textbook test banks and the United States citizenship test. The second assignment was a class survey that asked students to rate their own knowledge.</p>
<p>The researchers measured confidence using a specific question on the survey. Students rated their knowledge of American politics on a scale from zero to ten. A score of zero represented no knowledge, while a score of ten indicated the student felt capable of running a presidential campaign.</p>
<p>The study design took advantage of the order in which students completed these assignments. The course did not require students to finish the tasks in a specific sequence. Approximately one-third of the students chose to take the objective assessment test before completing the survey. The remaining two-thirds completed the survey before taking the test.</p>
<p>This natural variation allowed the researchers to treat the situation as a quasi-experiment. The students who took the test first effectively received feedback on their knowledge levels before rating their confidence. This group served as the experimental group. The students who rated their confidence before taking the test served as the control group.</p>
<p>The results provided a consistent pattern across the five-year period. The researchers found that students objectively knew very little about American politics. The average score on the assessment test was roughly 60 percent. This grade corresponds to a D-minus or F in academic terms.</p>
<p>Despite these low scores, the students did not demonstrate the expected overconfidence. When asked to rate their general political knowledge, the students gave answers that aligned with their low performance. The average response on the zero-to-ten confidence scale was modest.</p>
<p>The researchers compared the confidence levels of the group that took the test first against the group that took the survey first. They hypothesized that taking the test would provide a “reality check” and lower confidence scores. The analysis showed no statistically significant difference between the two groups. Providing objective feedback did not reduce confidence because the students’ self-assessments were already low.</p>
<p>The study also examined the stability of these findings over time. The data collection period covered significant events, including the COVID-19 pandemic and the 2020 presidential election. The researchers looked for any shifts in knowledge or confidence that might have resulted from these environmental shocks.</p>
<p>The analysis revealed that levels of political knowledge and confidence remained remarkably stable. The pandemic and the election cycle did not lead to meaningful changes in how much students knew or how much they thought they knew. The gap between actual knowledge and perceived knowledge remained substantively close to zero throughout the study.</p>
<p>“More than anything, I thought we’d see an impact of the natural experiment,” Hall told PsyPost. “I was also somewhat surprised by how flat the results appeared around 2020, when external factors like COVID-19 and the presidential election may have been impacting actual and perceived student knowledge.”</p>
<p>The authors utilized distinct statistical methods to verify their findings regarding overconfidence. They calculated overconfidence using quintiles, which divides the sample into five equal groups based on performance. They also used Z-scores, which measure how far a data point is from the average. Both methods yielded similar conclusions.</p>
<p>Using the quintile method, the researchers subtracted the quintile of the student’s actual score from the quintile of their self-assessment. The resulting overconfidence estimates were not statistically different from zero across all eleven semesters. This finding persisted regardless of whether the students took the assessment before or after the survey.</p>
<p>The Z-score analysis showed minor fluctuations but supported the main conclusion. There was a slight decrease in overconfidence in the control group between 2020 and 2023. However, the magnitude of this change was so small that it had little practical meaning. The overarching trend showed that students consistently recognized their own lack of expertise.</p>
<p>These results challenge the prevailing narrative in political science regarding the Dunning-Kruger effect. Hall and Smith suggest that the difference in findings may stem from how confidence is measured. Many previous studies ask participants to estimate their performance on a specific test they just took. This prompt often triggers a psychological bias where people assume they performed better than average.</p>
<p>In contrast, this study asked students to rate their general knowledge of a broad domain. When faced with a general question about how much they know about politics, individuals appear to be more humble. They do not default to assuming they are above average. Instead, they provide a rating that accurately reflects their limited understanding.</p>
<p>“The gap between what people know and what they think they know (over-or-under-confidence) may be less of a problem than we think, at least in the realm of political knowledge,” Hall said. “What we found is that if you ask someone what they know about politics they are likely to respond with ‘not much.’ You don’t have to provide them with evidence of that lack of information to get that response, they seem to be well-aware of the limitations of their knowledge regardless.”</p>
<p>“The short version here is that we did not find the Dunning-Kruger effect we expected to find. People with low information about politics did not overestimate their political knowledge, they seemed well-aware of its limitations.”</p>
<p>The authors argue that the Dunning-Kruger effect in politics might be an artifact of measurement choices. If researchers ask people how they did on a test, they find overconfidence. If researchers ask people how much they generally know, the overconfidence disappears. This distinction implies that the gap between actual and perceived knowledge may be less problematic than previously feared.</p>
<p>The study does have limitations that the authors acknowledge. The sample consisted entirely of undergraduate students. While the sample was diverse in terms of gender and political orientation, students are not perfectly representative of the general voting population. It is possible that being in an educational setting influences how students rate their own knowledge.</p>
<p>Another limitation involves the nature of the questions. The assessment relied on factual knowledge about civics and government structure. It is possible that overconfidence manifests differently when discussing controversial policy issues or specific political events. Future research could investigate whether different types of political knowledge elicit different levels of confidence.</p>
<p>The study also relied on a natural experiment rather than a randomized controlled trial. While the researchers found no significant differences between the groups initially, they did not control who took the test first. However, the large sample size and repeated data collection add weight to the findings.</p>
<p>“We should certainly be mindful of the principle that ‘absence of evidence isn’t evidence of absence,’ given the frequentist nature of null hypothesis significance testing,” Hall noted. “It’s also critical to understand the limitations of a natural experiment. There’s a lot of work on the Dunning-Kruger effect, and this is just one study, but I think it challenges us to think closely about the construct and how it generalizes.”</p>
<p>Future research could explore these measurement discrepancies further. The authors suggest that scholars should investigate how different ways of asking about confidence affect the results. Understanding whether overconfidence is a stable trait or a response to specific questions is vital for political psychology.</p>
<p>“Whether or not the Dunning-Kruger effect applies to broad domain knowledge is an important question for addressing political engagement – continuing down this line to broaden the domain coverage (something like civic reasoning, or real-world policy scenarios), and trying to move from a knowledge-based test scenario towards some closer indicator of manifest political behavior may give us a better sense of what’s likely to succeed in addressing political informedness,” Hall said.</p>
<p>The study, “<a href="https://doi.org/10.1177/10659129251398531" target="_blank" rel="noopener">They Know What They Know and It Ain’t Much: Revisiting the Dunning–Kruger Effect and Overconfidence in Political Knowledge</a>,” was authored by Alexander G. Hall and Kevin B. Smith.</p></p>
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<td><a href="https://www.psypost.org/neuroticism-predicts-stronger-emotional-bonds-with-ai-chatbots/" 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;">Neuroticism predicts stronger emotional bonds with AI chatbots</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Dec 24th 2025, 10:00</div>
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<p><p>As artificial intelligence becomes a staple of modern life, people are increasingly turning to chatbots for companionship and comfort. A new study suggests that while users often rely on these digital entities for stability, the resulting bond is built more on habit and trust than deep emotional connection. These findings on the psychology of human-machine relationships were published in the journal <em><a href="https://psycnet.apa.org/record/2026-75165-001?doi=1" target="_blank" rel="noopener">Psychology of Popular Media</a></em>.</p>
<p>The rise of sophisticated chatbots has created a unique social phenomenon where humans interact with software as if it were a living being. This dynamic draws upon a concept known as social presence theory. This theory describes the psychological sensation that another entity is physically or emotionally present during a mediated interaction.</p>
<p>Designers of these systems often aim to create a sense of social presence to make the user experience more engaging. The goal is for the artificial agent to appear to have a personality and the capacity for a relationship. However, the academic community has not fully reached a consensus on what constitutes intimacy in these synthetic scenarios.</p>
<p>Researchers wanted to understand the mechanics of this perceived intimacy. They sought to determine if personality traits influence how a user connects with a machine. The investigation was led by Yingjia Huang from the Department of Philosophy at Peking University and Jianfeng Lan from the School of Media and Communication at Shanghai Jiao Tong University.</p>
<p>The team recruited 103 participants who actively use AI companion applications such as Doubao and Xingye. These apps are designed to provide emotional interaction through text and voice. The participants completed detailed surveys designed to measure their personality traits and their perceived closeness to the AI.</p>
<p>To measure personality, the researchers utilized the “Big Five” framework. This model assesses individuals based on neuroticism, conscientiousness, agreeableness, openness, and extraversion. The survey also evaluated intimacy through five specific dimensions: trust, attachment, self-disclosure, virtual rapport, and addiction.</p>
<p>In addition to the quantitative survey, the researchers conducted in-depth interviews with eight selected participants. These conversations provided qualitative data regarding why users turn to digital companions. The interview subjects were chosen because they reported higher levels of intimacy in the initial survey.</p>
<p>The study revealed that most users do not experience a profound sense of intimacy with their chatbots. The average scores for emotional closeness were relatively low. This suggests that current technology has not yet bridged the gap required to foster deep interpersonal connections.</p>
<p>When analyzing what composed the relationship, the authors identified trust and addiction as the primary drivers. Users viewed the AI as a reliable outlet that is always available. The researchers interpreted the “addiction” component not necessarily as a pathology, but as a habit formed through daily routines.</p>
<p>The data showed that specific personality types are more prone to bonding with algorithms. Individuals scoring high in neuroticism reported stronger feelings of intimacy. Neuroticism is a trait often associated with emotional instability and anxiety.</p>
<p>For these users, the predictability of the computer program offers a sense of safety. Humans can be unpredictable or judgmental, but a coded companion provides consistent responses. One participant noted in an interview, “He’s always there, no matter what mood I’m in.”</p>
<p>People with high openness to experience also developed tighter bonds. These users tend to be imaginative and curious about new technologies. They engage with the AI as a form of exploration.</p>
<p>Users with high openness are willing to suspend disbelief to enjoy the interaction. They view the exchange as a form of experimental play rather than a replacement for human contact. They do not require the AI to be “real” to find value in the conversation.</p>
<p>The interviews highlighted that users often engage in emotional projection. They attribute feelings to the bot even while knowing it has no consciousness. This allows them to feel understood without the complexities of reciprocal human relationships.</p>
<p>The researchers identified three distinct ways users engaged with these systems. The first is “objectified companionship.” These users treat the AI like a digital pet, engaging in routine check-ins without deep emotional investment.</p>
<p>The second category is “emotional projection.” Users in this group use the AI as a safe container for their vulnerabilities. They vent their frustrations and anxieties, finding comfort in the machine’s non-judgmental nature.</p>
<p>The third category is “rational support.” These users do not seek emotional warmth. Instead, they value the AI for its logic and objectivity, using it as a counselor or advisor to help regulate their thoughts.</p>
<p>Despite these uses, participants frequently expressed frustration with technological limitations. Many described the AI’s language as too formal or repetitive. One user compared the experience to reading a customer service script.</p>
<p>This lack of spontaneity hinders the development of genuine immersion. Users noted that the AI lacks the warmth and fluidity of human conversation. Consequently, the relationship remains functional rather than truly affective.</p>
<p>The study posits that this form of intimacy relies on a “functional-affective gap.” Users maintain a high frequency of interaction for functional reasons, such as boredom relief or anxiety management. However, this does not translate into high emotional intimacy.</p>
<p>Trust in this context is defined by reliability rather than emotional closeness. Users trust the AI not to leak secrets or judge them. This form of trust acts as a substitute for the intuitive understanding found in human bonds.</p>
<p>The authors reference the philosophical concept of “I–Thou” versus “I–It” relationships. A true intimate bond is usually an “I–Thou” connection involving mutual recognition. Interactions with AI are technically “I–It” relationships because the machine lacks subjectivity.</p>
<p>However, the findings suggest that users psychologically approximate an “I–Thou” dynamic. They project meaning onto the AI’s output. The experience of intimacy is co-constructed by the user’s imagination and needs.</p>
<p>This dynamic creates a new relational paradigm. The line between simulation and reality becomes blurred. The user feels supported, which matters more to them than the ontological reality of the supporter.</p>
<p>The researchers argue that AI serves as a technological mediator of social affect. It functions as a mirror for the user’s emotions. The intimacy is layered and highly dependent on the context of the user’s life.</p>
<p>The study relies on a relatively small sample size of users from a specific cultural context. This focus on Chinese users may limit how well the results apply to other populations. Cultural attitudes toward technology and privacy could influence these results in different regions.</p>
<p>The cross-sectional nature of the survey also limits the ability to determine causality. It is unclear if neuroticism causes users to seek AI, or if the interaction appeals to those traits. Longitudinal studies would be needed to track how these relationships evolve over time.</p>
<p>Future investigations could examine how improved AI memory and emotional mimicry might alter these dynamics. As the technology becomes more lifelike, the distinction between functional and emotional intimacy may narrow. The authors imply that ethical design is essential as these bonds become more common.</p>
<p>The study, “<a href="https://psycnet.apa.org/doi/10.1037/ppm0000636" target="_blank" rel="noopener">Personality Meets the Machine: Traits and Attributes in Human–Artificial Intelligence Intimate Interactions</a>,” was authored by Yingjia Huang and Jianfeng Lan.</p></p>
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<p><strong>Forwarded by:<br />
Michael Reeder LCPC<br />
Baltimore, MD</strong></p>
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